{"pageNumber":"146","pageRowStart":"3625","pageSize":"25","recordCount":68799,"records":[{"id":70232228,"text":"fs20223030 - 2022 - By land, air, and water — U.S. Geological Survey science supporting fish and wildlife migrations throughout North America","interactions":[],"lastModifiedDate":"2022-06-29T15:38:00.02555","indexId":"fs20223030","displayToPublicDate":"2022-06-22T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3030","displayTitle":"By Land, Air, and Water—U.S. Geological Survey Science Supporting Fish and Wildlife Migrations Throughout North America","title":"By land, air, and water — U.S. Geological Survey science supporting fish and wildlife migrations throughout North America","docAbstract":"<p>Countless species of animals—big game, birds, bats, insects, amphibians, reptiles, and fish—migrate to reach suitable habitats to feed, reproduce, and raise their young. Animal migrations developed over millennia commonly follow migration corridors—unique routes for each species—to move among seasonal habitats. Changes along those corridors, whether from human development (buildings, roads, dams) or from natural disturbances (for example, climate change, drought, fire, flooding, or invasive species), can make them harder to navigate. The U.S. Geological Survey’s Ecosystems Mission Area provides science that assists land managers in mapping, enhancing, protecting, and reconnecting migration corridors critical for diverse fish and wildlife populations that migrate, such as <i>Odocoileus hemionus</i> (mule deer) and <i>Antilocapra americana</i> (pronghorn), trout and salmon, salamanders, tortoises, bats, and <i>Danaus plexippus</i> (monarch butterflies).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223030","usgsCitation":"Khalil, M., Wimer, M., Hu, D., Adams, M., Steinkamp, M., and Soileau, S.C., 2022, By land, air, and water—U.S. Geological Survey science supporting fish and wildlife migrations throughout North America: U.S. Geological Survey Fact Sheet 2022–3030, 4 p., https://doi.org/10.3133/fs20223030.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-126390","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":402255,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3030/images/"},{"id":402254,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3030/fs20223030.XML"},{"id":402253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3030/fs20223030.pdf","text":"Report","size":"3.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3030"},{"id":402252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3030/coverthb.jpg"}],"country":"Canada, Mexico, United States","otherGeospatial":"North America","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        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            -59.765625,\n              82.40242347938855\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Associate Director, <a href=\"https://www.usgs.gov/mission-areas/ecosystems\" data-mce-href=\"https://www.usgs.gov/mission-areas/ecosystems\">Ecosystems Mission Area</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Over Land</li><li>In the Air</li><li>Through the Water</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-06-22","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Khalil, Mona 0000-0002-6046-1293","orcid":"https://orcid.org/0000-0002-6046-1293","contributorId":207187,"corporation":false,"usgs":true,"family":"Khalil","given":"Mona","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":844725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wimer, Mark 0000-0003-1589-8151 mwimer@usgs.gov","orcid":"https://orcid.org/0000-0003-1589-8151","contributorId":4119,"corporation":false,"usgs":true,"family":"Wimer","given":"Mark","email":"mwimer@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hu, David H. 0000-0002-5676-5649","orcid":"https://orcid.org/0000-0002-5676-5649","contributorId":292473,"corporation":false,"usgs":true,"family":"Hu","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":844727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steinkamp, Melanie J. 0000-0001-9322-609X","orcid":"https://orcid.org/0000-0001-9322-609X","contributorId":292474,"corporation":false,"usgs":true,"family":"Steinkamp","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":5057,"text":"NGTOC Reston","active":true,"usgs":true}],"preferred":true,"id":844729,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Soileau, Suzanna C. 0000-0002-4331-0098","orcid":"https://orcid.org/0000-0002-4331-0098","contributorId":204690,"corporation":false,"usgs":true,"family":"Soileau","given":"Suzanna C.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":844730,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70238603,"text":"70238603 - 2022 - Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer","interactions":[],"lastModifiedDate":"2022-12-01T14:20:07.824544","indexId":"70238603","displayToPublicDate":"2022-06-22T08:14:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer","docAbstract":"<p><span>Interbasin water transfers are becoming an increasingly common tool to satisfy municipal and agricultural water demand, but their impacts on movement and gene flow of aquatic organisms are poorly understood. The Grand Ditch is an interbasin water transfer that diverts water from tributaries of the upper Colorado River on the west side of the Continental Divide to the upper Cache la Poudre River on the east side of the Continental Divide. We used single nucleotide polymorphisms to characterize population genetic structure in cutthroat trout (</span><i>Oncorhynchus clarkii</i><span>) and determine if fish utilize the Grand Ditch as a movement corridor. Samples were collected from two sites on the west side and three sites on the east side of the Continental Divide. We identified two or three genetic clusters, and relative migration rates and spatial distributions of admixed individuals indicated that the Grand Ditch facilitated bidirectional fish movement across the Continental Divide, a major biogeographic barrier. Previous studies have demonstrated ecological impacts of interbasin water transfers, but our study is one of the first to use genetics to understand how interbasin water transfers affect connectivity between previously isolated watersheds. We also discuss implications on native trout management and balancing water demand and biodiversity conservation.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10592-022-01455-5","usgsCitation":"Harris, A., Oyler-McCance, S.J., Fike, J., Fairchild, M., Kennedy, C.M., Crockett, H.J., Winkelman, D.L., and Kanno, Y., 2022, Population genetics reveals bidirectional fish movement across the Continental Divide via an interbasin water transfer: Conservation Genetics, v. 23, p. 839-851, https://doi.org/10.1007/s10592-022-01455-5.","productDescription":"13 p.","startPage":"839","endPage":"851","ipdsId":"IP-136388","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":409921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Arapaho and Roosevelt National Forests, Rocky Mountain National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.48445207177413,\n              40.56757183578418\n            ],\n            [\n              -106.39934138151587,\n              40.56757183578418\n            ],\n            [\n              -106.39934138151587,\n              39.6680633227534\n            ],\n            [\n              -105.48445207177413,\n              39.6680633227534\n            ],\n            [\n              -105.48445207177413,\n              40.56757183578418\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Audrey","contributorId":299560,"corporation":false,"usgs":false,"family":"Harris","given":"Audrey","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":858065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":858067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fairchild, Matthew P","contributorId":299561,"corporation":false,"usgs":false,"family":"Fairchild","given":"Matthew P","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":858068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Christopher M","contributorId":299562,"corporation":false,"usgs":false,"family":"Kennedy","given":"Christopher","email":"","middleInitial":"M","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":858069,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crockett, Harry J","contributorId":299564,"corporation":false,"usgs":false,"family":"Crockett","given":"Harry","email":"","middleInitial":"J","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":858070,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":858071,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":858072,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232216,"text":"fs20223040 - 2022 - Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana","interactions":[],"lastModifiedDate":"2026-03-24T21:25:05.594876","indexId":"fs20223040","displayToPublicDate":"2022-06-22T08:03:13","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3040","displayTitle":"Evaluating the Use of Video Cameras to Estimate Bridge Scour Potential at Four Bridges in Southwestern Montana","title":"Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, installed cameras and large-scale particle image velocimetry (LSPIV) recording equipment at four sites where the U.S. Geological Survey and Montana Department of Transportation are monitoring bridge scour using other methods. Determination of stream velocities is an important component of hydraulic engineering, river ecology, and fluvial geomorphology. LSPIV is an emerging technique that can be used to estimate stream surface velocities and streamflow using video cameras. Video from the camera is referenced to known locations on streambanks, and postprocessed using computer software that calculates water surface velocity and flow direction between video frames.</p><p>The goal of the study was to determine if LSPIV can increase the accuracy of current bridge scour prediction methods using video recordings from 2019 to 2021. Scour around piers is one of the primary failure mechanisms for bridges and poses threats to public safety and interstate commerce. LSPIV installations can capture the flow velocities and directions near bridge piers where other measurement methods might fail or be too dangerous. Additional benefits to the LSPIV technique were continuous data collection throughout the hydrologic cycle and enhanced safety of the methods for estimating velocity magnitude and direction during flood events. Limitations of the LSPIV technique included the angle of the camera to incoming flow; video recordings that were not usable because of ice cover, night, or high winds; and vegetation along the streambank that interfered with water flow analysis. Future applications of the LSPIV technique may continue to improve the processing of the video and reduce limitations for this process.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223040","usgsCitation":"Armstrong, D.W., Holnbeck, S.R., and Chase, K.J., 2022, Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana: U.S. Geological Survey Fact Sheet 2022–3040, 2 p., https://doi.org/10.3133/fs20223040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-137820","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":402153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3040/coverthb.jpg"},{"id":402154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.pdf","text":"Report","size":"1.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3040"},{"id":402155,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3040/fs20223040.XML"},{"id":402156,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3040/images"},{"id":402157,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223040/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":501493,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113199.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.5,\n              45\n            ],\n            [\n              -110.5,\n              45\n            ],\n            [\n              -110.5,\n              46\n            ],\n            [\n              -112.5,\n              46\n            ],\n            [\n              -112.5,\n              45\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/wy-mt-water/\" data-mce-href=\"https://www.usgs.gov/centers/wy-mt-water/\">Wyoming-Montana Water Science Center</a> <br>U.S. Geological Survey <br>3162 Bozeman Avenue <br>Helena, MT 59601</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Using Cameras to Describe Streamflow</li><li>Site Installation and Video Analysis</li><li>Evaluation and Limitations of LSPIV</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-22","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Armstrong, Daniel W. 0000-0001-9816-1002 darmstrong@usgs.gov","orcid":"https://orcid.org/0000-0001-9816-1002","contributorId":264331,"corporation":false,"usgs":true,"family":"Armstrong","given":"Daniel","email":"darmstrong@usgs.gov","middleInitial":"W.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holnbeck, Stephen R. 0000-0001-7313-9298 holnbeck@usgs.gov","orcid":"https://orcid.org/0000-0001-7313-9298","contributorId":1724,"corporation":false,"usgs":true,"family":"Holnbeck","given":"Stephen","email":"holnbeck@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":844687,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chase, Katherine J. 0000-0002-5796-4148 kchase@usgs.gov","orcid":"https://orcid.org/0000-0002-5796-4148","contributorId":454,"corporation":false,"usgs":true,"family":"Chase","given":"Katherine","email":"kchase@usgs.gov","middleInitial":"J.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":844688,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232367,"text":"70232367 - 2022 - Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi","interactions":[],"lastModifiedDate":"2022-06-29T12:28:54.824391","indexId":"70232367","displayToPublicDate":"2022-06-22T07:26:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0045\"><span>Mauka-to-makai (mountain to sea in the Hawaiian language) hydrologic connectivity – commonly referred to as ridge-to-reef – directly affects biogeochemical processes and socioecological functions across terrestrial, freshwater, and marine systems. The supply of freshwater to estuarine and&nbsp;nearshore environments&nbsp;in a ridge-to-reef system supports the food, water, and habitats utilized by&nbsp;</span>marine fauna<span>. In addition, the ecosystem services derived from this land-to-sea connectivity support social and cultural practices (hereafter referred to as socio-cultural) including fishing,&nbsp;aquaculture,&nbsp;wetland&nbsp;agriculture, religious ceremonies, and recreational activities. To effectively guide island resource management, a better understanding of the linkages from ridge-to-reef across natural and social usages is critical, particularly in the context of climate change, with anticipated increasing temperature and shifting precipitation patterns. The objective of this study was to identify spatial linkages that promote multiple and diverse uses, following the ridge-to-reef concept, at an island-wide scale to identify regions of high conservation importance for aquatic resources. We selected the Island of Maui as a study representative of many Pacific islands. Diverse datasets, including&nbsp;agricultural lands&nbsp;within&nbsp;watersheds, wetland locations, presence of stream species, indicators of&nbsp;freshwater input&nbsp;from streams, coral cover, nearshore fish biomass, socio-cultural data such as fishpond locations, wetland&nbsp;taro&nbsp;cultivation, beach recreation use, and lastly the dynamically downscaled&nbsp;Coupled Model Intercomparison Project&nbsp;Phase (CMIP5) future climate projections scenarios (Representative Concentration Pathway (RCP) 4.5 &amp; 8.5) were used to examine the spatial linkages through hydrological connectivity from land to the sea. Zonation spatial planning software was used to prioritize areas of high management and conservation value and to help inform aquatic resources management. The resulting prioritized areas included many minimally disturbed watersheds in east Maui and western nearshore and coastal zones that are adjacent to diverse coral reefs. These results are driven by the importance of fish biomass and coral reef distribution as well as traditional wetland taro cultivation and coastal access points for recreation. These results underline the importance of examining ridge-to-reef systems for aquatic resource management and including important social and cultural values in resource management upon planning adaptation strategies for climate change. Improving our understanding of diverse natural and socio-cultural influences on habitat conditions and their values in these areas provides an opportunity to strategically plan future management and conservation actions.</span></p></div></div><div id=\"ab0010\" class=\"abstract graphical\" lang=\"en\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2022.101704","usgsCitation":"Wilmot, E., Wong, J.P., Tsang, Y., Lynch, A., Infante, D.M., Oleson, K.L., Strauch, A., and Clilverd, H., 2022, Characterizing mauka-to-makai connections for aquatic ecosystem conservation on Maui, Hawaiʻi: Ecological Informatics, v. 70, 101704, 12 p., https://doi.org/10.1016/j.ecoinf.2022.101704.","productDescription":"101704, 12 p.","ipdsId":"IP-134842","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2022.101704","text":"Publisher Index Page"},{"id":402671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -156.8023681640625,\n              20.53507732696281\n            ],\n            [\n              -155.8905029296875,\n              20.53507732696281\n            ],\n            [\n              -155.8905029296875,\n              21.09475053314019\n            ],\n            [\n              -156.8023681640625,\n              21.09475053314019\n            ],\n            [\n              -156.8023681640625,\n              20.53507732696281\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"70","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wilmot, Ella","contributorId":292646,"corporation":false,"usgs":false,"family":"Wilmot","given":"Ella","email":"","affiliations":[{"id":62956,"text":"University of Hawaii-Manoa","active":true,"usgs":false}],"preferred":false,"id":845364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wong, Jesse P.","contributorId":264850,"corporation":false,"usgs":false,"family":"Wong","given":"Jesse","email":"","middleInitial":"P.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":845365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsang, Yinphan","contributorId":292647,"corporation":false,"usgs":false,"family":"Tsang","given":"Yinphan","affiliations":[],"preferred":false,"id":845372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":207361,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":845366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Infante, Dana M.","contributorId":146114,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":16583,"text":"Department of Fisheries and Wildlife, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":845367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oleson, Kirsten L. L. 0000-0002-7992-5051","orcid":"https://orcid.org/0000-0002-7992-5051","contributorId":211871,"corporation":false,"usgs":false,"family":"Oleson","given":"Kirsten","email":"","middleInitial":"L. L.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":845368,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Strauch, Ayron","contributorId":221124,"corporation":false,"usgs":false,"family":"Strauch","given":"Ayron","email":"","affiliations":[{"id":40327,"text":"State of Hawai‘i, Department of Land and Natural Resources, Commission on Water Resource Management","active":true,"usgs":false}],"preferred":false,"id":845369,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clilverd, Hannah","contributorId":216755,"corporation":false,"usgs":false,"family":"Clilverd","given":"Hannah","email":"","affiliations":[{"id":17202,"text":"University of Hawaii, Manoa","active":true,"usgs":false}],"preferred":false,"id":845370,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232254,"text":"ofr20221039 - 2022 - Ecological status and trends of the Upper Mississippi and Illinois Rivers","interactions":[],"lastModifiedDate":"2026-03-27T20:12:07.279898","indexId":"ofr20221039","displayToPublicDate":"2022-06-22T07:15:30","publicationYear":"2022","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":"2022-1039","displayTitle":"Ecological Status and Trends of the Upper Mississippi and Illinois Rivers","title":"Ecological status and trends of the Upper Mississippi and Illinois Rivers","docAbstract":"<h1>Executive Summary</h1><p>This report assesses the status and trends of selected ecological health indicators of the Upper Mississippi River System (UMRS) based on the data collected and analyzed by the Long Term Resource Monitoring element of the Upper Mississippi River Restoration program, supplemented with data from other sources. This report has four objectives: providing a brief introduction of the UMRS, including its significance, history, modern-day stressors, and recent research; using ecological indicators to describe the status of the river system and where and how it has changed from circa 1993 to 2019; discussing management and restoration implications of these changes; and highlighting the fundamental role of long-term monitoring in the understanding, management, and restoration of large-floodplain rivers.</p><p>The data were collected in the six Long Term Resource Monitoring element study reaches that spanned much of the UMRS and the various gradients contained therein. These study reaches included Navigation Pools 4, 8, 13, and 26; the part of the Unimpounded Reach of the Upper Mississippi River between Grand Tower and Cairo, Illinois; and the La Grange Pool on the Illinois River. The indicators included in this report describe the status and trends for the hydrology, geomorphology, floodplain vegetation, water quality, vegetation, and fishes of the UMRS. Many of the indicators of river ecosystem health changed significantly over the nearly 30 years of our evaluation. However, there was substantial spatial variability in the magnitude and timing of those changes among study reaches. Few indicators changed everywhere or nowhere; most indicators changed in some reaches but not others. The quantitative assessments of these indicators describe how the conditions of the river differ across hydrogeomorphic and climate gradients and through time and are intended to support the restoration and management of the UMRS.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221039","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Species Management Research Program and Land Management Research Program","usgsCitation":"Houser, J.N., ed., 2022, Ecological status and trends of the Upper Mississippi and Illinois Rivers (ver. 1.1, July 2022): U.S. Geological Survey Open-File Report 2022–1039, 199 p., https://doi.org/10.3133/ofr20221039.","productDescription":"xiv, 199 p.","numberOfPages":"220","onlineOnly":"N","ipdsId":"IP-125605","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":402335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1039/coverthb2.jpg"},{"id":402336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1039/ofr20221039.pdf","text":"Report","size":"41.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1039"},{"id":403771,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2022/1039/versionHist.txt","size":"3.11 kB","linkFileType":{"id":2,"text":"txt"}},{"id":501772,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113198.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, North Dakota, South Dakota, Wisconsin","otherGeospatial":"Illinois River, upper Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      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href=\"https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center\" data-mce-href=\"https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center\">Upper Midwest Environmental Sciences Center</a><br>U.S. Geological Survey<br>2630 Fanta Reed Road<br>La Crosse, WI 54603</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgements</li><li>Executive Summary</li><li>Chapter A: Introduction</li><li>Chapter B: Hydrologic Indicators</li><li>Chapter C: Geomorphic Indicators</li><li>Chapter D: Land Cover Indicators</li><li>Chapter E: Water Quality Indicators</li><li>Chapter F: Aquatic Vegetation Indicators</li><li>Chapter G: Fisheries Indicators</li><li>Chapter H: Using Long-Term Data to Understand the Causes and Consequences of Changes in Water Clarity and Aquatic Vegetation in the Upper Impounded Reach of the Upper Mississippi River</li><li>Chapter I: How and Why the Upper Mississippi River Restoration Long Term Resource Monitoring Element Played a Key Role in Understanding Invasive Carp in North America</li><li>Chapter J: Summary and Synthesis</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2022-06-22","revisedDate":"2022-07-14","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"editors":[{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":844836,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}}
,{"id":70232699,"text":"70232699 - 2022 - River bathymetry retrieval from Landsat-9 images based on neural networks and comparison to SuperDove and Sentinel-2","interactions":[],"lastModifiedDate":"2022-07-12T11:38:24.386488","indexId":"70232699","displayToPublicDate":"2022-06-22T06:37:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10962,"text":"Journal of Selected Topics in Applied Earth Observation and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"River bathymetry retrieval from Landsat-9 images based on neural networks and comparison to SuperDove and Sentinel-2","docAbstract":"<div class=\"abstract-text row\"><div class=\"col-12\"><div class=\"u-mb-1\"><div>The Landsat mission has kept an eye on our planet, including water bodies, for 50 years. With the launch of Landsat-9 and its onboard Operational Land Imager 2 (OLI-2) in September 2021, more subtle variations in brightness (14-bit dynamic range) can be captured than previous sensors in the Landsat series (e.g., 12-bit Landsat-8). The enhanced radiometric resolution of OLI-2 appeals to the aquatic remote sensing community because the instrument might be capable of resolving smaller differences in water-leaving radiance. This study evaluates the potential to map river bathymetry from Landsat-9 imagery. We employ a neural network (NN)-based regression model for bathymetry retrieval and compare the results with optimal band ratio analysis (OBRA). The effect of Landsat-9 pan-sharpening on depth retrieval is also examined. In addition, we perform an intersensor comparison with Sentinel-2 and newly available 8-band SuperDoves from the PlanetScope constellation. Depth retrieval results from the Colorado and Potomac Rivers imply that Landsat-9 provided more accurate bathymetry across a range of depths up to 20 m, particularly when pan-sharpened. Downsampling the SuperDove data improved bathymetry retrieval due to enhanced signal-to-noise ratio, most notably in deep waters (maximum detectable depth increased from ∼15 to ∼20 m). Similarly, the enhanced spectral resolution of 8-band SuperDoves improved depth retrieval relative to 4-band Doves. The NN-based model outperformed OBRA by incorporating more spectral information.</div></div></div></div>","language":"English","publisher":"IEEE","doi":"10.1109/JSTARS.2022.3187179","usgsCitation":"Niroumand-Jadidi, M., Legleiter, C.J., and Bovolo, F., 2022, River bathymetry retrieval from Landsat-9 images based on neural networks and comparison to SuperDove and Sentinel-2: Journal of Selected Topics in Applied Earth Observation and Remote Sensing, v. 15, p. 5250-5260, https://doi.org/10.1109/JSTARS.2022.3187179.","productDescription":"11 p.","startPage":"5250","endPage":"5260","ipdsId":"IP-139718","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":447370,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/jstars.2022.3187179","text":"Publisher Index Page"},{"id":403462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Niroumand-Jadidi, Milad 0000-0002-9432-3032","orcid":"https://orcid.org/0000-0002-9432-3032","contributorId":292943,"corporation":false,"usgs":false,"family":"Niroumand-Jadidi","given":"Milad","email":"","affiliations":[{"id":63082,"text":"Digital Society Center, Fondazione Bruno Kessler, Trento, Italy","active":true,"usgs":false}],"preferred":false,"id":846328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":846329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bovolo, Francesca 0000-0003-3104-7656","orcid":"https://orcid.org/0000-0003-3104-7656","contributorId":292944,"corporation":false,"usgs":false,"family":"Bovolo","given":"Francesca","email":"","affiliations":[{"id":63082,"text":"Digital Society Center, Fondazione Bruno Kessler, Trento, Italy","active":true,"usgs":false}],"preferred":false,"id":846330,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232255,"text":"sir20225032 - 2022 - Volcano and earthquake monitoring plan for the Yellowstone Caldera system, 2022–2032","interactions":[],"lastModifiedDate":"2022-06-27T13:49:17.264155","indexId":"sir20225032","displayToPublicDate":"2022-06-21T08:56:32","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5032","displayTitle":"Volcano and Earthquake Monitoring Plan for the Yellowstone Caldera System, 2022–2032","title":"Volcano and earthquake monitoring plan for the Yellowstone Caldera system, 2022–2032","docAbstract":"<h1>Executive Summary</h1><p>The Yellowstone Volcano Observatory (YVO) is a consortium of nine Federal, State, and academic agencies that: (1) provides timely monitoring and hazards assessment of volcanic, hydrothermal, and earthquake activity in and around Yellowstone National Park, and (2) conducts research to develop new approaches to volcano monitoring and better understand volcanic activity in the Yellowstone region and elsewhere. The U.S. Geological Survey (USGS) arm of YVO is also responsible for monitoring and reporting on volcanic activity in the Intermountain West of the United States.</p><p>The previous YVO monitoring plan for the Yellowstone region spanned 2006–2015 and focused on strengthening the region-wide coverage, or backbone, of monitoring systems (Yellowstone Volcano Observatory, 2006). The goals of that plan have largely been achieved thanks to significant investments in instrumentation and infrastructure, especially by the National Science Foundation EarthScope Plate Boundary Observatory (now known as the Network Of The Americas, or NOTA) and the American Reinvestment and Recovery Act. This revision of the monitoring plan, covering 2022–2032, builds upon these improvements to monitoring systems in the Yellowstone region while also accounting for new insights into the dynamics of the area’s seismic, volcanic, and hydrothermal activity. These additional improvements are designed to fill gaps in the monitoring network and to better understand and track hazards associated with hydrothermal processes. These improvements include:</p><ul><li>Conversion of remaining analog seismic stations to digital,</li><li>Addition of Global Positioning System (GPS) stations in the vicinity of Norris Geyser Basin and other areas where changes in deformation rate and style have been observed,</li><li>Implementation of continuous gas monitoring in several areas of Yellowstone National Park, and</li><li>Improvements to lake, meteorological, and hydrological monitoring to better track hydrothermal activity, including that occurring on lake bottoms, and to aid in understanding of whether such activity might be influenced by external forces, like environmental conditions.</li></ul><p>The 2022–2032 monitoring plan for the Yellowstone volcanic system also proposes to improve monitoring of hydrothermal areas to better understand these dynamic systems and their associated hazards. To date, only a single seismometer has been placed within one of Yellowstone National Park’s geyser basins because seismic noise associated with boiling water can hinder interpretation of overall seismic and magmatic activity, but this concern has been mitigated by improvements to backbone monitoring. Deployment of geophysical, geochemical, hydrological, and geological monitoring instruments in geyser basins will be accompanied by campaigns to measure gas and water chemistry and flux, as well as aerial and satellite surveys of gas and thermal emissions.</p><p>Close collaboration between YVO member institutions and other research agencies is needed to achieve these monitoring goals and to use the derived data to advance understanding of how Yellowstone Caldera and similar volcanic systems work. At the same time, attention must be paid to minimize the impact of monitoring efforts and infrastructure on the environment. YVO thus commits to serving as stewards of the natural, cultural, and historical resources in and around Yellowstone National Park while maximizing scientific gain for the betterment of society.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225032","collaboration":"Prepared in cooperation with Yellowstone National Park, University of Utah, UNAVCO, University of Wyoming, Montana Bureau of Mines and Geology, Idaho Geological Survey, Wyoming State Geological Survey, and Montana State University","usgsCitation":"Yellowstone Volcano Observatory, 2022, Volcano and earthquake monitoring plan for the Yellowstone Caldera system, 2022–2032: U.S. Geological Survey Scientific Investigations Report 2022–5032, 23 p., https://doi.org/10.3133/sir20225032.","productDescription":"v, 23 p.","numberOfPages":"23","onlineOnly":"Y","ipdsId":"IP-120517","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":402337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5032/covrthb.jpg"},{"id":402338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5032/sir20225032.pdf","text":"Report","size":"23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5032"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Caldera, Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.04156494140625,\n              44.24716652494939\n            ],\n            [\n              -110.20111083984375,\n              44.24716652494939\n            ],\n            [\n              -110.20111083984375,\n              44.77111175531263\n            ],\n            [\n              -111.04156494140625,\n              44.77111175531263\n            ],\n            [\n              -111.04156494140625,\n              44.24716652494939\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"https://www.usgs.gov/observatories/yvo/connect\" href=\"https://www.usgs.gov/observatories/yvo/connect\" target=\"_blank\" rel=\"noopener\">Director</a>,<br><a data-mce-href=\"https://www.usgs.gov/observatories/yvo\" href=\"https://www.usgs.gov/observatories/yvo\" target=\"_blank\" rel=\"noopener\">Yellowstone Volcano Observatory</a><br><a data-mce-href=\"https://usgs.gov\" href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a> <br>345 Middlefield Road, MS 910&nbsp; <br>Menlo Park, CA 94025 </p>","tableOfContents":"<ul><li>Executive Summary&nbsp;&nbsp;</li><li>Background and Motivation&nbsp;&nbsp;</li><li>Relation to the National Volcano Early Warning System&nbsp;&nbsp;</li><li>Goals&nbsp;&nbsp;</li><li>Progress made since 2006–2015&nbsp;&nbsp;</li><li>Status of Volcano and Earthquake Monitoring in 2022&nbsp;&nbsp;</li><li>Future Volcano and Earthquake Monitoring Needs&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2022-06-21","noUsgsAuthors":false,"publicationDate":"2022-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Yellowstone Volcano Observatory","contributorId":127797,"corporation":true,"usgs":false,"organization":"Yellowstone Volcano Observatory","id":844837,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70232259,"text":"70232259 - 2022 - Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season","interactions":[],"lastModifiedDate":"2022-06-20T16:34:49.404382","indexId":"70232259","displayToPublicDate":"2022-06-20T11:04:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season","docAbstract":"<p id=\"abspara0010\">Urban street trees are a key part of public green infrastructure in many cities, however,&nbsp;leaf litter&nbsp;on streets is a critical biogenic source of phosphorus (P) in urban&nbsp;stormwater runoff&nbsp;during Fall. This study identified mass of street leaf litter (M<sub>leaf</sub><span>) and antecedent dry days (ADD) as the top two explanatory parameters that have significant predictive power of event end-of-pipe P concentrations through&nbsp;multiple linear regression&nbsp;(MLR) analysis. M</span><sub>leaf</sub><span>&nbsp;</span>and volume of runoff (Vol) were the top two key explanatory parameters of event end-of-pipe P loads. Two-predictor MLR models were developed with these explanatory parameters using a 40-storm dataset derived from six small urban residential watersheds in Wisconsin, USA, and evaluated using storms specific to each study basin. The MLR model validation results indicated sensitivity to storm composition in the datasets. Our analysis shows selected parameters can be used by environmental managers to facilitate end-of-pipe P prediction in urban areas. This information can be used to reduce the amount of P in stormwater runoff by adjusting the timing and frequency of municipal leaf collection and street cleaning programs in urban areas.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2022.115171","usgsCitation":"Wang, Y., Thompson, A., and Selbig, W.R., 2022, Predictive models of phosphorus concentration and load in stormwater runoff from small urban residential watersheds in fall season: Journal of Environmental Management, v. 315, 115171, 8 p., https://doi.org/10.1016/j.jenvman.2022.115171.","productDescription":"115171, 8 p.","ipdsId":"IP-122605","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2022.115171","text":"Publisher Index Page"},{"id":402375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Fond du Lac, Madison, Oshkosh","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.58389282226561,\n              42.97752543508356\n            ],\n            [\n              -89.25018310546875,\n              42.97752543508356\n            ],\n            [\n              -89.25018310546875,\n              43.206176810164784\n            ],\n            [\n              -89.58389282226561,\n              43.206176810164784\n            ],\n            [\n              -89.58389282226561,\n              42.97752543508356\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.62533569335938,\n              43.94042832696309\n            ],\n            [\n              -88.48251342773438,\n              43.94042832696309\n            ],\n            [\n              -88.48251342773438,\n              44.11125397357155\n            ],\n            [\n              -88.62533569335938,\n              44.11125397357155\n            ],\n            [\n              -88.62533569335938,\n              43.94042832696309\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.51066589355469,\n              43.72694838956604\n            ],\n            [\n              -88.36578369140625,\n              43.72694838956604\n            ],\n            [\n              -88.36578369140625,\n              43.823629034783124\n            ],\n            [\n              -88.51066589355469,\n              43.823629034783124\n            ],\n            [\n              -88.51066589355469,\n              43.72694838956604\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yi 0000-0003-3638-7940","orcid":"https://orcid.org/0000-0003-3638-7940","contributorId":236843,"corporation":false,"usgs":false,"family":"Wang","given":"Yi","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":844871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":844872,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844873,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70232552,"text":"70232552 - 2022 - Controlling skewness in MOVE3 peak-flow record extensions","interactions":[],"lastModifiedDate":"2022-07-07T11:49:15.249922","indexId":"70232552","displayToPublicDate":"2022-06-20T06:47:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Controlling skewness in MOVE3 peak-flow record extensions","docAbstract":"<div class=\"NLM_sec NLM_sec_level_1 hlFld-Abstract\"><p>Streamgage record extension methods such as the maintenance of variance Type 3 (MOVE3) method improve flood frequency estimates at a target streamgage by incorporating information from a nearby, hydrologically similar index streamgage. Bulletin 17C recommends using a variation of the MOVE3 method to estimate values at the target streamgage for only a subset of the available data at the index streamgage to account for uncertainty in values estimated using MOVE3. Bulletin 17C recommends the most recent index streamgage data be used for the subset unless these data misrepresent the skewness of the extended record. However, no method is provided to select the subset if the most recent data are inappropriate. The objective of this study is to develop such a method to select the subset of peaks by extending Bulletin 17C’s MOVE3 methodology to control the skewness of the extended streamgage record. The new method allows the extended record skewness to be informed by all available peak-flow data at the index streamgage while accurately computing the variance and resulting confidence intervals for flood frequency estimates. An example is presented comparing three different variations of MOVE3 record extension, which produce extended streamgage records with the same mean and variance, but different values of skewness. In the example, the difference in skewness between the three methods causes the results of flood frequency analysis for the 1% annual exceedance probability flood to differ by about 15%, illustrating the importance of considering skewness when using MOVE3 record extension.</p></div>","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HE.1943-5584.0002192","usgsCitation":"Siefken, S.A., and McCarthy, P.M., 2022, Controlling skewness in MOVE3 peak-flow record extensions: Journal of Hydrologic Engineering, v. 27, no. 9, 04022015, 10 p., https://doi.org/10.1061/(ASCE)HE.1943-5584.0002192.","productDescription":"04022015, 10 p.","ipdsId":"IP-129012","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":403127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Siefken, Seth A. 0000-0001-5502-7903","orcid":"https://orcid.org/0000-0001-5502-7903","contributorId":292861,"corporation":false,"usgs":true,"family":"Siefken","given":"Seth","email":"","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":845941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Peter M. 0000-0003-3194-041X pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-041X","contributorId":203452,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","middleInitial":"M.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":845942,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70239285,"text":"70239285 - 2022 - Geoenvironmental model for roll-type uranium deposits in the Texas Gulf Coast","interactions":[],"lastModifiedDate":"2023-01-06T12:49:39.192331","indexId":"70239285","displayToPublicDate":"2022-06-20T06:46:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5207,"text":"Minerals","active":true,"publicationSubtype":{"id":10}},"title":"Geoenvironmental model for roll-type uranium deposits in the Texas Gulf Coast","docAbstract":"<div class=\"html-p\">Geoenvironmental models were formulated by the U.S. Geological Survey in the 1990s to describe potential environmental effects of extracting different types of ore deposits in different geologic and climatic regions. This paper presents a geoenvironmental model for roll-front (roll-type) uranium deposits in the Texas Coastal Plain. The model reviews descriptive and quantitative information derived from environmental studies and existing databases to depict existing conditions and potential environmental concerns associated with mining this deposit type. This geoenvironmental model describes how features of the deposits including host rock; ore and gangue mineralogy; geologic, hydrologic, and climatic settings; and mining methods (legacy open-pit and in situ recovery [ISR]) influence potential environmental effects from mining. Element concentrations in soil and water are compared to regulatory thresholds to depict ambient surface water and groundwater conditions. Although most open-pit operations in this region have been reclaimed, concerns remain about groundwater quality at three of the four former mills that supported former open-pit mines and are undergoing closure activities. The primary environmental concerns with ISR mining are (1) radon gas at active ISR operations, (2) radiation or contaminant leakage during production and transport of ISR resin or yellowcake, (3) uranium excursions into groundwater surrounding active ISR operations, and (4) contamination of groundwater after ISR mining. Although existing regulations attempt to address these concerns, some problems remain. Researchers suggest that reactive transport modeling and a better understanding of geology, stratigraphy, and geochemistry of ISR production areas could minimize excursions into surrounding aquifers and improve results of groundwater restoration.</div>","language":"English","publisher":"MDPI","doi":"10.3390/min12060780","usgsCitation":"Walton-Day, K., Blake, J., Seal,, R., Gallegos, T., Jean Dupree, and Becher, K.D., 2022, Geoenvironmental model for roll-type uranium deposits in the Texas Gulf Coast: Minerals, v. 12, no. 6, 780, 34 p., https://doi.org/10.3390/min12060780.","productDescription":"780, 34 p.","ipdsId":"IP-136921","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":447387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/min12060780","text":"Publisher Index Page"},{"id":411480,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -99.33528666210017,\n              26.89578699824432\n            ],\n            [\n              -99.11565337352738,\n              26.267254950900764\n            ],\n            [\n              -97.92963361523617,\n              25.872681365510957\n            ],\n            [\n              -96.9632471455172,\n              26.030670273163835\n            ],\n            [\n              -96.91932048780222,\n              26.699741720191838\n            ],\n            [\n              -95.11832752150816,\n              28.3358549338098\n            ],\n            [\n              -93.66874781692972,\n              29.90908880278704\n            ],\n            [\n              -93.58089450150081,\n              30.62990043651834\n            ],\n            [\n              -95.60152075636765,\n              30.59209521003619\n            ],\n            [\n              -98.06141358837951,\n              29.22136658295345\n            ],\n            [\n              -99.33528666210017,\n              26.89578699824432\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seal,, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":141204,"corporation":false,"usgs":true,"family":"Seal,","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":861004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gallegos, Tanya J. 0000-0003-3350-6473","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":206859,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":861005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jean Dupree","contributorId":300633,"corporation":false,"usgs":false,"family":"Jean Dupree","affiliations":[{"id":32931,"text":"USGS - Retired","active":true,"usgs":false}],"preferred":false,"id":861006,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Becher, Kent D 0000-0002-3947-0793","orcid":"https://orcid.org/0000-0002-3947-0793","contributorId":290642,"corporation":false,"usgs":false,"family":"Becher","given":"Kent","email":"","middleInitial":"D","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":861007,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237162,"text":"70237162 - 2022 - Comparison of radium analytical methods for municipal drinking water well operation","interactions":[],"lastModifiedDate":"2022-10-03T11:50:08.043279","indexId":"70237162","displayToPublicDate":"2022-06-20T06:39:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5167,"text":"Water Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of radium analytical methods for municipal drinking water well operation","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Radium (Ra) is a geogenic contaminant that occurs at high levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS), a regionally important sandstone and carbonate drinking water aquifer. Water utilities using the MCOAS often must adopt treatment methods or use alternative water sources to maintain high-quality drinking water. Here, we show that Ra in water obtained from a municipal well in Wisconsin remains consistent despite variation in pumping conditions. However, widely used analytical methods (e.g., scintillation counting) for measuring Ra are less precise for quantifying Ra variability given the site conditions. Although not currently used for EPA compliance, mass spectrometry improves the precision of Ra measurements by an order of magnitude over the currently used counting method (e.g., 95 ± 3 mBq/L vs. 110 ± 30 mBq/L) at the concentrations observed in this study. The use of more precise analytical methods will increase understanding of trends in Ra levels important for operating public water systems.</p></div></div>","language":"English","publisher":"American Water Works Association","doi":"10.1002/aws2.1291","usgsCitation":"Mathews, M.J., Scott, S.R., Hunt, R., and Ginder-Vogel, M., 2022, Comparison of radium analytical methods for municipal drinking water well operation: Water Science and Engineering, v. 4, no. 3, e1291, https://doi.org/10.1002/aws2.1291.","productDescription":"e1291","ipdsId":"IP-131117","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":407781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Mathews, Madeleine J","contributorId":292236,"corporation":false,"usgs":false,"family":"Mathews","given":"Madeleine","email":"","middleInitial":"J","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":853525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, Sean R","contributorId":292237,"corporation":false,"usgs":false,"family":"Scott","given":"Sean","email":"","middleInitial":"R","affiliations":[{"id":17815,"text":"Wisconsin State Laboratory of Hygiene","active":true,"usgs":false}],"preferred":false,"id":853526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ginder-Vogel, Matthew","contributorId":176769,"corporation":false,"usgs":false,"family":"Ginder-Vogel","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":853528,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232266,"text":"70232266 - 2022 - Assessing runoff and erosion on woodland-encroached sagebrush steppe using the Rangeland Hydrology and Erosion Model","interactions":[],"lastModifiedDate":"2022-06-24T17:55:48.310221","indexId":"70232266","displayToPublicDate":"2022-06-19T11:00:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Assessing runoff and erosion on woodland-encroached sagebrush steppe using the Rangeland Hydrology and Erosion Model","docAbstract":"<p><span>The transition of sagebrush-dominated (</span><i>Artemisia</i><span>&nbsp;spp.) shrublands to pinyon (</span><i>Pinus</i><span>&nbsp;spp.) and juniper (</span><i>Juniperus</i><span>&nbsp;spp.) woodlands markedly alters resource-conserving vegetation structure typical of these landscapes. Land managers and scientists in the western United States need knowledge and predictive tools for assessment and effective targeting of tree-removal treatments to conserve or restore sagebrush vegetation and associated hydrologic function. This study developed modeling approaches to quantify the hydrologic vulnerability and erosion potential of sagebrush rangelands in the later stages of woodland encroachment and in response to commonly applied tree-removal treatments. Using experimental data from multiple sites in the Great Basin Region, USA, and process-based knowledge from decade-long vegetation and rainfall simulation studies at those sites, we (1) assessed the capability of the Rangeland Hydrology and Erosion Model (RHEM) to accurately predict patch-scale (12 m</span><sup>2</sup><span>) measured runoff and erosion from tree canopy and intercanopy hydrologic functional units in untreated and burned woodlands 9 years postfire, and (2) developed and evaluated multiple RHEM approaches/frameworks to model aggregated effects of tree canopy and intercanopy areas on patch- and hillslope-scale (50 m length) runoff and erosion processes in untreated and treated (burned, cut, and masticated) woodlands. The RHEM accurately predicted measured runoff and sediment yield from patch-scale rainfall simulations as partitioned on untreated and treated tree canopy and intercanopy areas and effectively parameterized the dominant controls on runoff and erosion process in woodlands. With few exceptions, evaluated hillslope-scale RHEM frameworks similarly predicted reduced hydrologic vulnerability and erosion potential for conditions 9 years following tree removal by burning, cutting, and mastication treatments. Regressions of RHEM-predicted hillslope runoff, sediment, and hydraulic/erosion parameters with bare ground and ground cover attributes indicate all RHEM frameworks effectively represented the dominant controls on hydrologic and erosion processes for rangelands and woodlands. The results provide RHEM frameworks and recommendations for assessing hydrologic vulnerability and erosion potential on woodland-encroached sites and predicting the effectiveness of tree removal to reestablish a water and soil resource-conserving vegetation structure on sagebrush rangelands. We anticipate our RHEM or similar modeling approaches may be applicable to analogous water-limited landscapes elsewhere subject to woody plant encroachment.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4145","usgsCitation":"Williams, C.J., Pierson, F.B., Al-Hamdan, O.Z., Nouwakpo, S.K., Johnson, J.C., Polyakov, V.O., Kormos, P.R., Shaff, S., and Spaeth, K.E., 2022, Assessing runoff and erosion on woodland-encroached sagebrush steppe using the Rangeland Hydrology and Erosion Model: Ecosphere, v. 13, no. 6, e4145, 32 p., https://doi.org/10.1002/ecs2.4145.","productDescription":"e4145, 32 p.","ipdsId":"IP-137960","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":447392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecs2.4145","text":"External Repository"},{"id":402401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.14427185058592,\n              39.44679856427205\n            ],\n            [\n              -115.10032653808594,\n              39.44679856427205\n            ],\n            [\n              -115.10032653808594,\n              39.47807557129829\n            ],\n            [\n              -115.14427185058592,\n              39.47807557129829\n            ],\n            [\n              -115.14427185058592,\n              39.44679856427205\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.47871398925781,\n              40.20824570152502\n            ],\n            [\n              -112.46429443359375,\n              40.20824570152502\n            ],\n            [\n              -112.46429443359375,\n              40.2203056748532\n            ],\n            [\n              -112.47871398925781,\n              40.2203056748532\n            ],\n            [\n              -112.47871398925781,\n              40.20824570152502\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, C. Jason","contributorId":12774,"corporation":false,"usgs":true,"family":"Williams","given":"C.","email":"","middleInitial":"Jason","affiliations":[],"preferred":false,"id":844919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierson, Frederick B.","contributorId":195933,"corporation":false,"usgs":false,"family":"Pierson","given":"Frederick","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":844920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Al-Hamdan, Osama Z.","contributorId":292513,"corporation":false,"usgs":false,"family":"Al-Hamdan","given":"Osama","email":"","middleInitial":"Z.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":844921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nouwakpo, S. Kossi","contributorId":292514,"corporation":false,"usgs":false,"family":"Nouwakpo","given":"S.","email":"","middleInitial":"Kossi","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Justin C.","contributorId":261635,"corporation":false,"usgs":false,"family":"Johnson","given":"Justin","email":"","middleInitial":"C.","affiliations":[{"id":47959,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":844923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Polyakov, Viktor O.","contributorId":292516,"corporation":false,"usgs":false,"family":"Polyakov","given":"Viktor","email":"","middleInitial":"O.","affiliations":[{"id":62926,"text":"Agricultural Research Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":844924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kormos, Patrick R.","contributorId":292517,"corporation":false,"usgs":false,"family":"Kormos","given":"Patrick","email":"","middleInitial":"R.","affiliations":[{"id":62927,"text":"National Oceanic and Atmospheric Administration - National Weather Service, US Department of Commerce","active":true,"usgs":false}],"preferred":false,"id":844925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shaff, Scott 0000-0001-8978-9260 sshaff@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-9260","contributorId":5126,"corporation":false,"usgs":true,"family":"Shaff","given":"Scott","email":"sshaff@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":844926,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spaeth, Kenneth E.","contributorId":9387,"corporation":false,"usgs":true,"family":"Spaeth","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":844927,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70232218,"text":"sir20215143 - 2022 - Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","interactions":[],"lastModifiedDate":"2026-04-08T16:38:21.182332","indexId":"sir20215143","displayToPublicDate":"2022-06-17T10:44:25","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5143","displayTitle":"Application of a Soil-Water-Balance Model to Estimate Annual Groundwater Recharge for Long Island, New York, 1900–2019","title":"Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019","docAbstract":"<p>A soil-water-balance (SWB) model was developed for Long Island, New York, to estimate the potential amount of annual groundwater recharge to the Long Island aquifer system from 1900 to 2019. The SWB model program is a computer code based on a modified Thornthwaite-Mather SWB approach and uses spatially and temporally distributed meteorological, land-cover, and soil properties as input to compute potential daily groundwater recharge. Simulated outputs indicate that island-wide potential groundwater recharge trends, as a percentage of precipitation, have increased approximately 3 percent during the 120-year period. The simulated results account for both climatic and land-cover changes that have occurred during the period. A change from undeveloped (forested land cover) to low- and medium-density residential land cover or land use increased potential groundwater recharge because of a decrease in evapotranspiration. During the 30-year period from 1900 to 1930, the simulated potential average groundwater recharge rate on Long Island was estimated to be 18.50 inches per year (in/yr), or a total of 1,243 million gallons per day, during the 30-year period from 1985 to 2015, the simulated potential average groundwater recharge rate estimate increased to 20.73 in/yr (a total of around 1,393 million gallons per day).</p><p>During the 1900–2019 simulation period, the potential average annual groundwater recharge rate was about 19.24 in/yr. The data for that period included values for a 3-year meteorological drought from 1963 to 1965, where the mean precipitation was about 26.5 percent lower than the long-term average of 46.7 in/yr, and the potential groundwater recharge rate was about 12.3 in/yr. During a 3-year wet period from 1982 to 1984, where mean precipitation was about 19.6 percent higher than the long-term average, the estimated potential groundwater recharge rate was about 26.8 in/yr.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215143","usgsCitation":"Finkelstein, J.S., Monti, J., Jr., Masterson, J.P., and Walter, D.A., 2022, Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019: U.S. Geological Survey Scientific Investigations Report 2021–5143, 25 p., https://doi.org/10.3133/sir20215143.","productDescription":"Report: v, 25 p.; 2 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103053","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":435800,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93Z8Y8L","text":"USGS data release","linkHelpText":"Soil-water-balance model archive for Long Island, NY, 1900-2019"},{"id":402201,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V2NMUB","text":"USGS data release","linkHelpText":"Soil-water-balance groundwater recharge model results for Long Island, NY, 1900-2019"},{"id":402197,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5143/coverthb.jpg"},{"id":402196,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5143/sir20215143.pdf","text":"Report","size":"5.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5143"},{"id":402199,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5143/images/"},{"id":402217,"rank":7,"type":{"id":39,"text":"HTML 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         ],\n            [\n              -74.036865234375,\n              40.55554790286311\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ ny@usgs.gov\" data-mce-href=\"mailto:dc_ ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Previous Studies</li><li>Model Description and Input Requirements</li><li>Recharge Analysis</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-06-17","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Finkelstein, Jason S. 0000-0002-7496-7236","orcid":"https://orcid.org/0000-0002-7496-7236","contributorId":202452,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Jason S.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monti, Jack Jr. 0000-0001-9389-5891","orcid":"https://orcid.org/0000-0001-9389-5891","contributorId":202454,"corporation":false,"usgs":true,"family":"Monti","given":"Jack","suffix":"Jr.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masterson, John P. 0000-0003-3202-4413","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":102516,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":844703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walter, Donald A. 0000-0003-0879-4477 dawalter@usgs.gov","orcid":"https://orcid.org/0000-0003-0879-4477","contributorId":1101,"corporation":false,"usgs":true,"family":"Walter","given":"Donald","email":"dawalter@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844704,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232249,"text":"70232249 - 2022 - Primary production responses to extreme changes in North American Monsoon precipitation vary by elevation and plant functional composition through time","interactions":[],"lastModifiedDate":"2022-09-15T14:09:45.245412","indexId":"70232249","displayToPublicDate":"2022-06-17T09:17:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Primary production responses to extreme changes in North American Monsoon precipitation vary by elevation and plant functional composition through time","docAbstract":"<ol class=\"\"><li>Primary production in dryland ecosystems is limited by water availability and projected to be strongly affected by future shifts in seasonal precipitation. Warm-season precipitation derived from the North American Monsoon contributes 40% of annual precipitation to dryland ecosystems in the southwestern U.S. and is projected to become more variable. However, there is large uncertainty on whether this variability will be expressed as either extreme wet or dry years and how primary production of different plant functional types will respond across widespread elevation gradients in this region.</li><li>We experimentally imposed extreme drought and water addition treatments from 2016 – 2020, during which ambient warm-season precipitation declined to reach historic lows, to understand production sensitivity of dominant plant functional types along a 1,000 m elevation gradient.</li><li>We found that the production responses of plant functional types to monsoon precipitation extremes were dependent on the number of treatment years that occurred across sites along the elevation gradient. C<sub>4</sub><span>&nbsp;</span>perennial grasses were most responsive to precipitation manipulation treatments, followed by C<sub>3</sub><span>&nbsp;</span>perennial grasses and annuals, while perennial forbs and shrubs had weak or no responses. C<sub>4</sub><span>&nbsp;</span>perennial grass reductions due to extreme drought were generally stronger or occurred earlier at low elevation sites, while multi-year extreme drought extended negative effects to C<sub>3</sub><span>&nbsp;</span>perennial grasses at high elevation, and all sites showed delayed responses to multi-year water addition. We found that the sensitivity of C<sub>3</sub><span>&nbsp;</span>perennial grass production differed for extreme drought and water addition compared to ambient precipitation at one site, but other sites and plant functional types had similar sensitivities to the different treatment types.</li><li><i>Synthesis</i>. The upward advance of primary production responsiveness from single- to multi-year extreme changes in warm-season precipitation suggests more immediate shifts in functional composition and carbon cycling at low elevation, while high elevation ecosystems may become less resistant as the effects of extreme precipitation compound through time.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2745.13947","usgsCitation":"Munson, S.M., Bradford, J., Butterfield, B.J., and Gremer, J., 2022, Primary production responses to extreme changes in North American Monsoon precipitation vary by elevation and plant functional composition through time: Journal of Ecology, v. 110, no. 9, p. 2232-2245, https://doi.org/10.1111/1365-2745.13947.","productDescription":"14 p.","startPage":"2232","endPage":"2245","ipdsId":"IP-134154","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":402327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"San Francisco Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.15118408203125,\n              35.20186696142873\n            ],\n            [\n              -111.22421264648438,\n              35.20186696142873\n            ],\n            [\n              -111.22421264648438,\n              35.68295607559029\n            ],\n            [\n              -112.15118408203125,\n              35.68295607559029\n            ],\n            [\n              -112.15118408203125,\n              35.20186696142873\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"110","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":844802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":844803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gremer, Jennifer R.","contributorId":181751,"corporation":false,"usgs":false,"family":"Gremer","given":"Jennifer R.","affiliations":[],"preferred":false,"id":844804,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232341,"text":"70232341 - 2022 - Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines","interactions":[],"lastModifiedDate":"2022-06-28T12:44:32.089718","indexId":"70232341","displayToPublicDate":"2022-06-17T07:39:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10939,"text":"Frontiers in Built Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.</p></div>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fbuil.2022.884849","usgsCitation":"Salatin, R., Wang, H., Chen, Q., and Zhu, L., 2022, Assessing wave attenuation with rising sea levels for sustainable oyster reef-based living shorelines: Frontiers in Built Environment, v. 8, 884849, 16 p., https://doi.org/10.3389/fbuil.2022.884849.","productDescription":"884849, 16 p.","ipdsId":"IP-138476","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":447401,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fbuil.2022.884849","text":"Publisher Index Page"},{"id":402591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.849609375,\n              38.496593518947584\n            ],\n            [\n              -74.5751953125,\n              38.496593518947584\n            ],\n            [\n              -74.5751953125,\n              40.019201307686785\n            ],\n            [\n              -75.849609375,\n              40.019201307686785\n            ],\n            [\n              -75.849609375,\n              38.496593518947584\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Salatin, Reza 0000-0001-5372-3948","orcid":"https://orcid.org/0000-0001-5372-3948","contributorId":292618,"corporation":false,"usgs":false,"family":"Salatin","given":"Reza","email":"","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":845285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Hongqing 0000-0002-2977-7732","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":221902,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":845286,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Q. 0000-0002-6540-8758","orcid":"https://orcid.org/0000-0002-6540-8758","contributorId":56532,"corporation":false,"usgs":false,"family":"Chen","given":"Q.","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":true,"id":845287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Ling 0000-0003-0261-6848","orcid":"https://orcid.org/0000-0003-0261-6848","contributorId":222169,"corporation":false,"usgs":false,"family":"Zhu","given":"Ling","affiliations":[{"id":38331,"text":"Northeastern University","active":true,"usgs":false}],"preferred":false,"id":845288,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70232243,"text":"sir20225055 - 2022 - Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","interactions":[],"lastModifiedDate":"2022-09-27T12:37:10.865008","indexId":"sir20225055","displayToPublicDate":"2022-06-17T07:23:22","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5055","displayTitle":"Assessment of Streamflow Trends in the Eastern Dakotas, Water Years 1960–2019","title":"Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019","docAbstract":"<p>Hydrologic extremes, whether periods of drought or flooding, are occurring more frequently with greater severity and can have substantial economic impacts. Along with flooding, the timing and volume of streamflow also is changing across the United States. The focus of this report is to characterize a unique trend in mean annual streamflow occurring in eastern North and South Dakota, hereafter referred to as the eastern Dakotas, that is not being observed anywhere else in the conterminous United States.</p><p>Streamflow records for 1,853 U.S. Geological Survey streamgages obtained from the U.S. Geological Survey National Water Information System database with a continuous record of mean annual streamflow during water years 1960–2019 were included in this study. Using a Kendall tau statistical test (<i>p</i>-value less than or equal to 0.10), 573 streamgages had a statistically significant upward trend in mean annual streamflow and are primarily located in the Midwest and northeastern United States. Of the streamgages, 182 had a statistically significant downward trend and are located primarily in the western and southeastern States. Several sites had increases in streamflow between 100 and 500 percent. Most of the streamgages with the highest increases in mean annual streamflow are along the same rivers in the eastern Dakotas, regardless of basin size.</p><p>A comparison of mean annual streamflow of the last decade (2010–19) to the first decade (1960–69) of the study period shows that the largest increases in annual streamflow volumes in the United States also are in the eastern Dakotas. Among all 1,853 streamgages in the United States, the Sheyenne River near Warwick, North Dakota (U.S. Geological Survey station 05056000), has the greatest percent change, with an increase of 486 percent. Several factors may be contributing to increasing trends in streamflow in the eastern Dakotas and may include, in part, precipitation changes owing to climatic variation within the region, geologic makeup of the subsurface, and land-use changes. A better understanding of these research areas will help producers, resource managers, and infrastructure engineers to make more informed environmental and economic decisions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225055","usgsCitation":"Norton, P.A., Delzer, G.C., Valder, J.F., Tatge, W.S., and Ryberg, K.R., 2022, Assessment of streamflow trends in the eastern Dakotas, water years 1960–2019: U.S. Geological Survey Scientific Investigations Report 2022–5055, 11 p., https://doi.org/10.3133/sir20225055.","productDescription":"Report: iv, 11 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-134818","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":402316,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225055/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402286,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5055/images"},{"id":402284,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5055"},{"id":402285,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5055/sir20225055.XML"},{"id":402283,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5055/coverthb.jpg"},{"id":402287,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"North Dakota, South Dakota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.7666015625,\n              42.90816007196054\n            ],\n            [\n              -96.50390625,\n              42.90816007196054\n            ],\n            [\n              -96.50390625,\n              48.980216985374994\n            ],\n            [\n              -100.7666015625,\n              48.980216985374994\n            ],\n            [\n              -100.7666015625,\n              42.90816007196054\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/dakota-water\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water\">Dakota Water Science Center</a> <br>U.S. Geological Survey <br>821 East Interstate Avenue, Bismarck, ND 58503 <br>1608 Mountain View Road, Rapid City, SD 57702</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods of Analysis Used in Assessing Streamflow Trends</li><li>Spatial Analysis of Streamflow Trends</li><li>Potential Factors Contributing to Increasing Streamflow Trends</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-17","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Delzer, Gregory C. 0000-0002-7077-4963 gcdelzer@usgs.gov","orcid":"https://orcid.org/0000-0002-7077-4963","contributorId":986,"corporation":false,"usgs":true,"family":"Delzer","given":"Gregory","email":"gcdelzer@usgs.gov","middleInitial":"C.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valder, Joshua F. 0000-0003-3733-8868","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":220912,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844775,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tatge, Wyatt S. 0000-0003-4414-2492","orcid":"https://orcid.org/0000-0003-4414-2492","contributorId":239544,"corporation":false,"usgs":true,"family":"Tatge","given":"Wyatt","email":"","middleInitial":"S.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":844777,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70236046,"text":"70236046 - 2022 - Seismostratigraphic analysis of Lake Cahuilla sedimentation cycles and fault displacement history beneath the Salton Sea, California, USA","interactions":[],"lastModifiedDate":"2022-08-26T12:16:47.972733","indexId":"70236046","displayToPublicDate":"2022-06-17T07:10:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Seismostratigraphic analysis of Lake Cahuilla sedimentation cycles and fault displacement history beneath the Salton Sea, California, USA","docAbstract":"<div id=\"134024229\" class=\"article-section-wrapper js-article-section js-content-section  \"><p>The Salton Trough (southeastern California, USA) is the northernmost transtensional stepover of the Gulf of California oblique-divergent plate boundary and is also where the southern terminus of the San Andreas fault occurs. Until recently, the distribution of active faults in and around the Salton Sea and their displacement histories were largely unknown. Subbottom CHIRP (compressed high-intensity radar pulse) surveys in the Salton Sea are used to develop a seismic facies model for ancient Lake Cahuilla deposits, a detailed map of submerged active faults, and reconstructed fault displacement histories during the late Holocene. We observe as many as fourteen Lake Cahuilla sequences in the Salton Sea (last ~3 k.y.) and develop a chronostratigraphic framework for the last six sequences (last ~1200 yr) by integrating CHIRP data and cone penetrometer logs with radiocarbon-dated stratigraphy at an onshore paleoseismic site. The Salton Sea contains northern and southern subbasins that appear to be separated by a tectonic hinge zone, and a subsidence signal across hinge-zone faults of 6–9 mm/yr (since ca. A.D. 940) increases toward the south to &gt;15 mm/yr. The faults mapped to the south of the hinge zone appear to accommodate transtension within the San Andreas–Imperial fault stepover. We identify 8–15 distinct growth events across hinge-zone faults, meaning growth occurred at least once every 100 yr since Lake Cahuilla sedimentation began. Several faults offset the top of the most recent Lake Cahuilla highstand deposits, and at least two faults have offset the Salton Sea flood deposits. Active faults and folds were also mapped to a limited extent within the northern subbasin and display growth, but their kinematics and rupture histories require further study. The broad distribution of active faulting suggests that strain between the San Andreas, San Jacinto, and Imperial faults is highly distributed, thus discrepancies between geologic and geodetic slip-rate estimates from these major fault systems are to be expected.</p></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02468.1","usgsCitation":"Brothers, D., Driscoll, N.W., Kent, G., Baskin, R.L., Harding, A.J., and Kell, A., 2022, Seismostratigraphic analysis of Lake Cahuilla sedimentation cycles and fault displacement history beneath the Salton Sea, California, USA: Geosphere, v. 18, no. 4, p. 1354-1376, https://doi.org/10.1130/GES02468.1.","productDescription":"23 p.","startPage":"1354","endPage":"1376","ipdsId":"IP-138899","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":447403,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02468.1","text":"Publisher Index Page"},{"id":405678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salton Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.5,\n               32.5\n            ],\n            [\n              -115,\n               32.5\n            ],\n            [\n              -115,\n              34\n            ],\n            [\n              -116.5,\n              34\n            ],\n            [\n              -116.5,\n               32.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-06-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Brothers, Daniel","contributorId":295722,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":849801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Neal W.","contributorId":63266,"corporation":false,"usgs":true,"family":"Driscoll","given":"Neal","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":849802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kent, Graham","contributorId":7608,"corporation":false,"usgs":true,"family":"Kent","given":"Graham","affiliations":[],"preferred":false,"id":849803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baskin, Robert L. 0000-0002-2175-8502 rbaskin@usgs.gov","orcid":"https://orcid.org/0000-0002-2175-8502","contributorId":360,"corporation":false,"usgs":true,"family":"Baskin","given":"Robert","email":"rbaskin@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":849804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harding, Alistair J.","contributorId":53270,"corporation":false,"usgs":true,"family":"Harding","given":"Alistair","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":849805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kell, Annie","contributorId":68176,"corporation":false,"usgs":true,"family":"Kell","given":"Annie","affiliations":[],"preferred":false,"id":849806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237244,"text":"70237244 - 2022 - Long-term ice phenology records spanning up to 578 years for 78 lakes around the Northern Hemisphere","interactions":[],"lastModifiedDate":"2022-10-05T13:43:53.372572","indexId":"70237244","displayToPublicDate":"2022-06-16T08:33:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Long-term ice phenology records spanning up to 578 years for 78 lakes around the Northern Hemisphere","docAbstract":"<p><span>In recent decades, lakes have experienced unprecedented ice loss with widespread ramifications for winter ecological processes. The rapid loss of ice, resurgence of winter biology, and proliferation of remote sensing technologies, presents a unique opportunity to integrate disciplines to further understand the broad spatial and temporal patterns in ice loss and its consequences. Here, we summarize ice phenology records for 78 lakes in 12 countries across North America, Europe, and Asia to permit the inclusion and harmonization of&nbsp;</span><i>in situ</i><span>&nbsp;ice phenology observations in future interdisciplinary studies. These ice records represent some of the longest climate observations directly collected by people. We highlight the importance of applying the same definition of ice-on and ice-off within a lake across the time-series, regardless of how the ice is observed, to broaden our understanding of ice loss across vast spatial and temporal scales.</span></p>","language":"English","publisher":"Scientific Data","doi":"10.1038/s41597-022-01391-6","usgsCitation":"Sharma, S., Filazzola, A., Nguyen, T., Imrit, M., Blagrave, K., Bouffard, D., Daly, J., Feldman, H., Feldsine, N., Hendricks-Franssen, H., Granin, N., Hecock, R., L'Abee-Lund, J., Hopkins, E., Howk, N., Iacono, M., Knoll, L.B., Korhonen, J., Malmquist, H., Marszelewski, W., Matsuzaki, S.S., Miyabara, Y., Miyasaka, K., Mills, A., Olson, L., Peters, T., Richardson, D., Robertson, D., Rudstam, L., Wain, D., Waterfield, H., Weyhenmeyer, G.A., Wiltse, B., Yao, H., Zhdanov, A., and Magnuson, J.J., 2022, Long-term ice phenology records spanning up to 578 years for 78 lakes around the Northern Hemisphere: Scientific Data, v. 9, 318, 15 p., https://doi.org/10.1038/s41597-022-01391-6.","productDescription":"318, 15 p.","ipdsId":"IP-133292","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447414,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-022-01391-6","text":"Publisher Index Page"},{"id":407956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2022-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Sharma, Sapna","contributorId":150332,"corporation":false,"usgs":false,"family":"Sharma","given":"Sapna","email":"","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":853786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Filazzola, Alessnadro","contributorId":297297,"corporation":false,"usgs":false,"family":"Filazzola","given":"Alessnadro","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":853787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nguyen, Thi","contributorId":297298,"corporation":false,"usgs":false,"family":"Nguyen","given":"Thi","email":"","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":853788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imrit, Mohammad","contributorId":297299,"corporation":false,"usgs":false,"family":"Imrit","given":"Mohammad","email":"","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":853789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blagrave, Kevin","contributorId":211887,"corporation":false,"usgs":false,"family":"Blagrave","given":"Kevin","email":"","affiliations":[{"id":38342,"text":"Department of Biology, York University, Toronto, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":853790,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bouffard, Damien","contributorId":297301,"corporation":false,"usgs":false,"family":"Bouffard","given":"Damien","affiliations":[{"id":64357,"text":"EAWAG, Swiss Federal Institute","active":true,"usgs":false}],"preferred":false,"id":853791,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daly, Julia","contributorId":297305,"corporation":false,"usgs":false,"family":"Daly","given":"Julia","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":853792,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Feldman, Harley","contributorId":297308,"corporation":false,"usgs":false,"family":"Feldman","given":"Harley","email":"","affiliations":[{"id":64358,"text":"Chanhassen, Minnesota","active":true,"usgs":false}],"preferred":false,"id":853793,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Feldsine, Natalie","contributorId":297309,"corporation":false,"usgs":false,"family":"Feldsine","given":"Natalie","email":"","affiliations":[{"id":64360,"text":"Mohonk Preserve","active":true,"usgs":false}],"preferred":false,"id":853794,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hendricks-Franssen, Harrie-Jan","contributorId":297310,"corporation":false,"usgs":false,"family":"Hendricks-Franssen","given":"Harrie-Jan","email":"","affiliations":[{"id":64362,"text":"Forschungszentrum Julich","active":true,"usgs":false}],"preferred":false,"id":853795,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Granin, Nikolay","contributorId":297311,"corporation":false,"usgs":false,"family":"Granin","given":"Nikolay","email":"","affiliations":[{"id":64363,"text":"Siberian Branch of Russian Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":853796,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hecock, Richard","contributorId":297312,"corporation":false,"usgs":false,"family":"Hecock","given":"Richard","email":"","affiliations":[{"id":64364,"text":"Lake Detroiters Association","active":true,"usgs":false}],"preferred":false,"id":853797,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"L'Abee-Lund, Jan Henning","contributorId":297313,"corporation":false,"usgs":false,"family":"L'Abee-Lund","given":"Jan Henning","affiliations":[{"id":64365,"text":"Norwegian Water Resources and Energy Directorate","active":true,"usgs":false}],"preferred":false,"id":853798,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hopkins, 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Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5</span><span class=\"inline-formula\"><sup>∘</sup></span><span> </span><span class=\"inline-formula\">×</span><span> 0.5</span><span class=\"inline-formula\"><sup>∘</sup></span><span>&nbsp;global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/gmd-15-4597-2022","usgsCitation":"Golub, M., Thiery, W., Marce, R., Pierson, D., Vanderkelen, I., Mercado-Bettin, D., Woolway, R., Grant, L., Jennings, E., Kraemer, B., Schewe, J., Zhao, F., Frieler, K., Mengel, M., Bogomolov, V.Y., Bouffard, D., Cote, M., Couture, R., Debolskiy, A.V., Droppers, B., Gal, G., Guo, M., Janssen, A.B., Kirillin, G., Ladwig, R., Magee, M., Moore, T., Perroud, M., Piccolroaz, S., Raaman Vinnea, L., Schmid, M., Shatwell, T., Stepanenko, V.M., Tan, Z., Woodward, B., Yao, H., Adrian, R., Allan, M., Anneville, O., Arvola, L., Atkins, K., Boegman, L., Carey, C.C., Christianson, K., de Eyto, E., DeGasperi, C.L., Grechushnikova, M., Hejzlar, J., Joehnk, K., Jones, I.D., Laas, A., MacKay, E.B., Mammarella, I., Markensten, H., McBride, C.G., Özkundakci, D., Potes, M., Rinke, K., Robertson, D., Rusak, J.A., Salgado, R., van der Linden, L., Verburg, P., Wain, D., Ward, N.K., Wollrab, S., and Zdorovennova, G., 2022, A framework for ensemble modelling of climate change impacts on lakes worldwide: The ISIMIP lake sector.: Geoscientific Model Development, v. 15, p. 4297-4623, https://doi.org/10.5194/gmd-15-4597-2022.","productDescription":"27 p.","startPage":"4297","endPage":"4623","ipdsId":"IP-136556","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-15-4597-2022","text":"Publisher Index Page"},{"id":407955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2022-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Golub, Malgorzata","contributorId":297257,"corporation":false,"usgs":false,"family":"Golub","given":"Malgorzata","email":"","affiliations":[{"id":35850,"text":"Uppsala University, Sweden","active":true,"usgs":false}],"preferred":false,"id":853719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thiery, Wim","contributorId":223158,"corporation":false,"usgs":false,"family":"Thiery","given":"Wim","email":"","affiliations":[],"preferred":false,"id":853720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marce, Rafael","contributorId":297259,"corporation":false,"usgs":false,"family":"Marce","given":"Rafael","email":"","affiliations":[{"id":64329,"text":"Catalan Institute for Water Research (ICRA), Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":853721,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierson, Don","contributorId":194465,"corporation":false,"usgs":false,"family":"Pierson","given":"Don","email":"","affiliations":[],"preferred":false,"id":853722,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanderkelen, Inne","contributorId":297260,"corporation":false,"usgs":false,"family":"Vanderkelen","given":"Inne","email":"","affiliations":[{"id":64331,"text":"Vrije Universiteit Brussel, Department of Hydrology and Hydraulic Engineering, Brussels, Belgium","active":true,"usgs":false}],"preferred":false,"id":853723,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mercado-Bettin, Daniel","contributorId":297261,"corporation":false,"usgs":false,"family":"Mercado-Bettin","given":"Daniel","affiliations":[{"id":64329,"text":"Catalan Institute for Water Research (ICRA), Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":853724,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Woolway, R. 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Alliance, Belgrade Lakes, Maine, USA 04901","active":true,"usgs":false}],"preferred":false,"id":853782,"contributorType":{"id":1,"text":"Authors"},"rank":64},{"text":"Ward, Nicole K.","contributorId":297294,"corporation":false,"usgs":false,"family":"Ward","given":"Nicole","email":"","middleInitial":"K.","affiliations":[{"id":64354,"text":"Virginia Tech, Department of Biological Sciences & Forest Resources & Environmental Conservation, Blacksburg, Virginia, USA","active":true,"usgs":false}],"preferred":false,"id":853783,"contributorType":{"id":1,"text":"Authors"},"rank":65},{"text":"Wollrab, Sabine","contributorId":297295,"corporation":false,"usgs":false,"family":"Wollrab","given":"Sabine","email":"","affiliations":[{"id":64355,"text":"Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":853784,"contributorType":{"id":1,"text":"Authors"},"rank":66},{"text":"Zdorovennova, 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,{"id":70254299,"text":"70254299 - 2022 - Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region","interactions":[],"lastModifiedDate":"2024-05-17T13:58:51.399871","indexId":"70254299","displayToPublicDate":"2022-06-15T08:54:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region","docAbstract":"<p><span>For agricultural areas facing water scarcity, sustainable water use policy relies on irrigation information that is timely and at a high resolution, but existing publicly available water use data are often insufficient for monitoring compliance or understanding the influence of policy on individual farmer decisions. This study attempts to fill this data gap by using remote sensing to map annual irrigation quantity at the field-scale within the central Ogallala aquifer region of the United States. We compiled in situ annual irrigation volume data at the field scale in the Republican River Basin of Colorado for 2015–2018 and at the Public Land Survey System (PLSS) section scale in western Kansas for 2000–2016, which served as reference data in random forest models that relied on Landsat-based actual evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop) along with maps of irrigated area, Landsat spectral indices, climate, soils, and derived hydrologic variables. The models explained 87% of the variability in irrigation volume in Colorado and 75% in Kansas, but accuracy declined when transferring the models in spatial cross-validation (Colorado R</span><sup>2</sup><span>&nbsp;=0.81; Kansas R</span><sup>2</sup><span>&nbsp;=0.51) and temporal cross-validation (Colorado R</span><sup>2</sup><span>&nbsp;=0.82; Kansas R</span><sup>2</sup><span>&nbsp;=0.68). Predicted annual totals of irrigation volume in western Kansas had a mean absolute error of 11.9%, which was slightly higher than the average annual change of 11%. Use of predicted irrigation maps also lead to an underestimated effect size for a water use restriction policy in Kansas. These results indicate that field- and section-scale irrigation can be mapped with reasonable accuracy within a region and time period that has adequate sample data, but that methods may need to be improved for applying the models more broadly in areas that lack extensive in situ irrigation data to support further research on water use and aid in structuring policy.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2022.107764","usgsCitation":"Filippelli, S.S., Sloggy, M.R., Vogeler, J.C., Manning, D.T., Goemans, C., and Senay, G.B., 2022, Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region: Agricultural Water Management, v. 271, 107764, 15 p., https://doi.org/10.1016/j.agwat.2022.107764.","productDescription":"107764, 15 p.","ipdsId":"IP-137832","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":488115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2022.107764","text":"Publisher Index Page"},{"id":428798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado Kansas","otherGeospatial":"Ogallala aquifer, Republican River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -102.00825131829713,\n              36.98969791337646\n            ],\n            [\n              -97.51352205922755,\n              36.9837502608661\n            ],\n            [\n              -97.3406085961385,\n              38.44391430535899\n            ],\n            [\n              -98.0932074623356,\n              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Service","active":true,"usgs":false}],"preferred":false,"id":900930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogeler, Jody C.","contributorId":264796,"corporation":false,"usgs":false,"family":"Vogeler","given":"Jody","email":"","middleInitial":"C.","affiliations":[{"id":54555,"text":"umn","active":true,"usgs":false}],"preferred":false,"id":900931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manning, Dale T 0000-0001-6465-5530","orcid":"https://orcid.org/0000-0001-6465-5530","contributorId":336735,"corporation":false,"usgs":false,"family":"Manning","given":"Dale","email":"","middleInitial":"T","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goemans, Christopher 0000-0003-4930-4278","orcid":"https://orcid.org/0000-0003-4930-4278","contributorId":336736,"corporation":false,"usgs":false,"family":"Goemans","given":"Christopher","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":900934,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70232417,"text":"70232417 - 2022 - The consequences of climate change for dryland biogeochemistry","interactions":[],"lastModifiedDate":"2022-09-15T14:13:41.119439","indexId":"70232417","displayToPublicDate":"2022-06-15T07:20:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10948,"text":"New Phytologist Foundation","active":true,"publicationSubtype":{"id":10}},"title":"The consequences of climate change for dryland biogeochemistry","docAbstract":"<div id=\"article__content\" class=\"col-sm-12 col-md-8 col-lg-8 article__content article-row-left\"><div class=\"article__body \"><div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Drylands, which cover more than 40% of Earth’s terrestrial surface, are dominant drivers of global biogeochemical cycling and home to more than one third of the human population. Climate projections predict warming, drought frequency and severity, and evaporative demand will increase in drylands at faster rates than global means. Due to extreme temperatures and high biological dependency on limited water availability, drylands are predicted to be exceptionally sensitive to climate change and, indeed, significant climate impacts are already being observed. Yet our understanding and ability to forecast climate change effects on dryland biogeochemistry and ecosystem functions lag behind many mesic systems. To improve our capacity to forecast ecosystem change, we propose focusing on the controls and consequences of two key characteristics affecting dryland biogeochemistry: i) high spatial and temporal heterogeneity in environmental conditions and ii) generalized resource scarcity. In addition to climate change, drylands are experiencing accelerating land use change. Building our understanding of dryland biogeochemistry in both intact and disturbed systems will better equip us to address the interacting effects of climate change and landscape degradation. Responding to these challenges will require a diverse, globally distributed, and interdisciplinary community of dryland experts united towards better understanding these vast and important ecosystems.</p></div></div></div></div>","language":"English","publisher":"New Phytologist Foundation","doi":"10.1111/nph.18312","usgsCitation":"Osborne, B.B., Bestelmeyer, B.T., Currier, C.M., Homyak, P.M., Throop, H.L., Young, K., and Reed, S., 2022, The consequences of climate change for dryland biogeochemistry: New Phytologist Foundation, v. 236, no. 1, p. 15-20, https://doi.org/10.1111/nph.18312.","productDescription":"6 p.","startPage":"15","endPage":"20","ipdsId":"IP-136307","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":447429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.18312","text":"Publisher Index Page"},{"id":402816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"236","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Osborne, Brooke Bossert 0000-0003-4771-7677","orcid":"https://orcid.org/0000-0003-4771-7677","contributorId":247600,"corporation":false,"usgs":true,"family":"Osborne","given":"Brooke","email":"","middleInitial":"Bossert","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bestelmeyer, Brandon T.","contributorId":26180,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":845479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Currier, Courtney M.","contributorId":214702,"corporation":false,"usgs":false,"family":"Currier","given":"Courtney","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":845480,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homyak, Peter M 0000-0003-0671-8358","orcid":"https://orcid.org/0000-0003-0671-8358","contributorId":292686,"corporation":false,"usgs":false,"family":"Homyak","given":"Peter","email":"","middleInitial":"M","affiliations":[{"id":62973,"text":"Department of Environmental Sciences, University of California, Riverside, CA 92521","active":true,"usgs":false}],"preferred":false,"id":845481,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":845482,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Kristina E.","contributorId":195945,"corporation":false,"usgs":false,"family":"Young","given":"Kristina E.","affiliations":[],"preferred":false,"id":845483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":845484,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70232208,"text":"ofr20221043 - 2022 - Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data","interactions":[],"lastModifiedDate":"2022-06-15T14:11:27.09211","indexId":"ofr20221043","displayToPublicDate":"2022-06-14T14:20:00","publicationYear":"2022","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":"2022-1043","displayTitle":"Opportunities To Improve Alignment With the FAIR Principles for U.S. Geological Survey Data","title":"Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data","docAbstract":"<p>In 2016, an interdisciplinary, international group of 53 scientists introduced a framework named “the FAIR Principles” for addressing 21st century scientific data challenges. The FAIR Principles are increasingly used as a guide for producing digital scientific products that are findable, accessible, interoperable, and reusable (FAIR), especially to enable use of such products in automated systems. Data aligned with the FAIR Principles can increase the efficiency of science integration capabilities such as those envisioned for the U.S. Geological Survey (USGS) Earth Monitoring, Analyses, and Projections (EarthMAP) initiative.</p><p>The FAIR Principles clearly define the characteristics of reusable scientific products, but it is less clear how to facilitate consistency in achieving these characteristics across the Bureau. USGS data are produced by local research projects distributed over more than 100 centers in 7 regions. After data are approved for release, they could be managed in numerous repositories and online data systems. The diversity of USGS data is illustrated by the topical range of the USGS mission areas: Core Science Systems, Ecosystems, Energy and Minerals, Natural Hazards, and Water Resources. In the USGS context, realizing the EarthMAP vision for automated, predictive, integrated science that provides timely and actionable results involves providing knowledge and support services and developing the skills, infrastructure, and culture to enable Bureau-wide implementation of the FAIR Principles.</p><p>In 2019, the USGS Community for Data Integration funded a project to convene a broadly representative workshop and produce recommendations to enable consistency with the FAIR Principles across the USGS. The workshop, held in Fort Collins, Colorado, in September 2019, brought together 28 participants for 3 days to engage with the FAIR Principles, analyze USGS use cases, and discuss the roles of data producers and managers, data storage and catalogs, value-added services, and policy makers in implementing the FAIR Principles. Workshop participants agreed that scientific reproducibility requires the extension of the FAIR Principles beyond measured data to include physical samples, research methods, software, and tools at the USGS. Workshop discussions focused on how the USGS can implement the FAIR Principles by supporting research teams in creating data, metadata, and other scientific products and also by supporting enterprise systems that maintain and leverage the products’ consistency with the FAIR Principles.</p><p>The resulting FAIR roadmap of recommendations describes nine proposed interdependent strategies that could be achieved by coordinated actions taken by different parts of the USGS. A proposed early action would be the creation of a coordinating council that includes representatives from the groups engaged in activities consistent with better alignment with the FAIR Principles. The nine proposed strategies, which are presented in more detail in this roadmap report, focus on enabling improvements to individual data products, providing infrastructure, and structuring administrative activities to support an organizational culture that values the FAIR Principles.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221043","usgsCitation":"Lightsom, F.L., Hutchison, V.B., Bishop, B., Debrewer, L.M., Govoni, D.L., Latysh, N., and Stall, S., 2022, Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data: U.S. Geological Survey Open-File Report 2022–1043, 23 p., https://doi.org/10.3133/ofr20221043.","productDescription":"vi, 23 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125836","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":402133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1043/coverthb.jpg"},{"id":402134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1043/ofr20221043.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1043"},{"id":402135,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1043/images/"},{"id":402136,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1043/ofr20221043.XML"}],"contact":"<p><a href=\"mailto:WHSC_science_director@usgs.gov\" data-mce-href=\"mailto:WHSC_science_director@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/whcmsc\" data-mce-href=\"https://www.usgs.gov/centers/whcmsc\">Woods Hole Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>384 Woods Hole Road<br>Quissett Campus<br>Woods Hole, MA 02543–1598</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Background: The FAIR Principles</li><li>Background: Data Management at the U.S. Geological Survey</li><li>Current U.S. Geological Survey Practices Relative to the FAIR Principles</li><li>Goals of the Roadmap for Enabling the FAIR Principles</li><li>Strategies for Enabling Better Alignment With the FAIR Principles</li><li>First Steps Toward Better U.S. Geological Survey Alignment With the FAIR Principles</li><li>Conclusion</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. FAIR Workshop Participants</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2022-06-14","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Lightsom, Frances L. 0000-0003-4043-3639 flightsom@usgs.gov","orcid":"https://orcid.org/0000-0003-4043-3639","contributorId":1535,"corporation":false,"usgs":true,"family":"Lightsom","given":"Frances","email":"flightsom@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":844641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 vhutchison@usgs.gov","orcid":"https://orcid.org/0000-0001-5301-3698","contributorId":173674,"corporation":false,"usgs":true,"family":"Hutchison","given":"Vivian","email":"vhutchison@usgs.gov","middleInitial":"B.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":844642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Bradley","contributorId":292462,"corporation":false,"usgs":false,"family":"Bishop","given":"Bradley","email":"","affiliations":[{"id":62912,"text":"University of Tennessee School of Information Sciences","active":true,"usgs":false}],"preferred":false,"id":844643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Debrewer, Linda M. 0000-0002-0511-4010 lmdebrew@usgs.gov","orcid":"https://orcid.org/0000-0002-0511-4010","contributorId":5713,"corporation":false,"usgs":true,"family":"Debrewer","given":"Linda","email":"lmdebrew@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":844644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Govoni, David L. 0000-0002-2707-0098 dgovoni@usgs.gov","orcid":"https://orcid.org/0000-0002-2707-0098","contributorId":292463,"corporation":false,"usgs":true,"family":"Govoni","given":"David","email":"dgovoni@usgs.gov","middleInitial":"L.","affiliations":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true}],"preferred":true,"id":844645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Latysh, Natalie 0000-0003-0149-3962","orcid":"https://orcid.org/0000-0003-0149-3962","contributorId":215667,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","affiliations":[{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true}],"preferred":true,"id":844646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stall, Shelley","contributorId":292464,"corporation":false,"usgs":false,"family":"Stall","given":"Shelley","email":"","affiliations":[{"id":35616,"text":"American Geophysical Union","active":true,"usgs":false}],"preferred":false,"id":844647,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70232209,"text":"fs20223042 - 2022 - Arkansas and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:06:03.914652","indexId":"fs20223042","displayToPublicDate":"2022-06-14T09:25:10","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3042","displayTitle":"Arkansas and Landsat","title":"Arkansas and Landsat","docAbstract":"<p>Scenic Arkansas certainly lives up to its nickname, “The Natural State.” The Ozark Plateau and Ouachita Mountains boast stunning views, vast resources, and recreation. Hardwood and pine forests cover one-half of the State. The major rivers—Arkansas, Ouachita, Red, and White—offer recreation and navigation as they drain toward the Mississippi River, which forms the State’s eastern border. Smaller streams and rivers, reservoirs, and rice fields serve as homes for wildlife as well, including birds migrating along the Mississippi Flyway.</p><p>Agriculture has always been a key industry in Arkansas, which is the top rice producer in the United States. Poultry, soybeans, cotton, cattle, and timber are among other agricultural products that contribute to the State’s economy. The aquaculture industry has diversified from just goldfish to more than 20 species of fish and crustaceans.</p><p>Geological features include waterfalls, limestone caves, and the country’s only active diamond mine, Crater of Diamonds State Park, where visitors can keep any rock or mineral they find in the volcanic crater. Hot Springs National Park—within the city of Hot Springs—features thermal springs of water heated deep belowground that follow a fault line of the Ouachita Mountains up to the surface.</p><p>Here are a few ways Landsat has benefited Arkansas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223042","usgsCitation":"U.S. Geological Survey, 2022, Arkansas and Landsat: U.S. Geological Survey Fact Sheet 2022–3042, 2 p., https://doi.org/10.3133/fs20223042.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-139117","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":402141,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223042/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":402139,"rank":3,"type":{"id":31,"text":"Publication 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/programs/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/programs/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Monitoring Farm Reservoirs</li><li>Tracking Crops</li><li>Understanding Urban Growth</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-06-14","noUsgsAuthors":false,"publicationDate":"2022-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":128240,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":844649,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70232200,"text":"70232200 - 2022 - Thirteen novel ideas and underutilized resources to support progress towards a range-wide American eel stock assessment","interactions":[],"lastModifiedDate":"2022-09-15T14:08:12.517171","indexId":"70232200","displayToPublicDate":"2022-06-13T10:49:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Thirteen novel ideas and underutilized resources to support progress towards a range-wide American eel stock assessment","docAbstract":"<p>A robust assessment of the American eel (<i>Anguilla rostrata</i>) stock, required to guide conservation efforts, is challenged by the species’ vast range, high variability in demographic parameters and data inadequacies. Novel ideas and underutilised resources that may assist both analytic assessments and spatially oriented modelling include (1)&nbsp;species and environmental databases; (2) mining of data from scattered sources; (3)&nbsp;infilling of data gaps by spatial analysis; (4) age estimation from measurements of DNA methylation; evaluation of eel abundance by (5) larval, (6) glass-bottom boat, (7)&nbsp;net enclosure and (8) eDNA surveys; (9) accounting for dam-induced habitat increases in eel watercourse modelling; (10) spatially oriented modelling with and without temporal components; (11) geographically nested modelling of glass eel recruitment; (12)&nbsp;spawner per recruit modelling and (13) life cycle modelling to examine larval allocation effects. Eel biologists are too few to gather the required assessment data across all of the species’ range. Public posting of electrofishing and eDNA metabarcoding data sets and the use of machine learning techniques to comprehensively inventory small dams will help meet some data needs. These approaches address only a small proportion of the assessment challenges that face American eels. Worldwide collaboration amongst<span>&nbsp;</span><i>Anguilla</i><span>&nbsp;</span>scientists is a key enabler of progress towards stock assessment goals.</p>","language":"English","publisher":"Wiley","doi":"10.1111/fme.12572","usgsCitation":"Cairns, D., Benchetrit, J., Bernatchez, L., Bornarel, V., Casselman, J., Castonguay, M., Charsley, A., Dorrow, M., Drouineau, H., Frankowski, J., Haro, A., Hoyle, S., Knickle, D.C., Koops, M.A., Poirier, L.A., Thorson, J.T., Young, J.A., and Zhu, X., 2022, Thirteen novel ideas and underutilized resources to support progress towards a range-wide American eel stock assessment: Fisheries Management and Ecology, v. 29, no. 5, p. 516-541, https://doi.org/10.1111/fme.12572.","productDescription":"26 p.","startPage":"516","endPage":"541","ipdsId":"IP-135604","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447439,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70232199,"text":"70232199 - 2022 - Quantifying relations between altered hydrology and fish community responses for streams in Minnesota","interactions":[],"lastModifiedDate":"2022-06-13T15:49:06.160966","indexId":"70232199","displayToPublicDate":"2022-06-13T10:45:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1460,"text":"Ecological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying relations between altered hydrology and fish community responses for streams in Minnesota","docAbstract":"Altered hydrology is a stressor on aquatic life for several streams in Minnesota, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota.  Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic explanatory metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological response metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to the an impairment threshold of the corresponding stream class (FIBI_BCG4).  Three hydrologic datasets were used to examine rRelations between altered hydrology and fish community responses were examined at three different temporal scalesusing three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.","language":"English","publisher":"Springer","doi":"10.1186/s13717-022-00383-z","usgsCitation":"Ziegeweid, J.R., Johnson, G.D., Krall, A.L., Fitzpatrick, K., and Levin, S., 2022, Quantifying relations between altered hydrology and fish community responses for streams in Minnesota: Ecological Processes, v. 11, 41, 25 p., https://doi.org/10.1186/s13717-022-00383-z.","productDescription":"41, 25 p.","ipdsId":"IP-125704","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":447443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13717-022-00383-z","text":"Publisher Index Page"},{"id":402091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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