{"pageNumber":"336","pageRowStart":"8375","pageSize":"25","recordCount":184769,"records":[{"id":70237910,"text":"sir20225081 - 2022 - Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018","interactions":[],"lastModifiedDate":"2026-04-23T17:19:38.569434","indexId":"sir20225081","displayToPublicDate":"2022-11-08T11:41:15","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":"2022-5081","displayTitle":"Suspended-Sediment Transport and Water Management, Jemez Canyon Dam, New Mexico, 1948–2018","title":"Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018","docAbstract":"<p>Construction and operation of dams provide sources of clean drinking water, support large-scale irrigation, generate hydroelectricity, control floods, and improve river navigation. Yet these benefits are not without cost. Dams affect the natural flow regime, downstream sediment fluxes, and riverine and riparian ecosystems. The Jemez Canyon Dam in New Mexico was constructed in 1953 by the U.S. Army Corps of Engineers with authorizations for flood control and sediment retention. Water managers of the dam use various operational techniques to restore peak streamflow, improve sediment management, and restore altered ecosystem processes, while maintaining the authorized purposes of the dam. This study focuses on four distinct reservoir management operation periods implemented at the Jemez Canyon Dam: (1) predam (pre-1953), (2) a seasonal 24-hour hold pool (1953–79), (3) a permanent pool (1979–2001), and (4) dry reservoir (2001–18).</p><p>Results of this study indicate successful flood control and reduction in peak instantaneous streamflow events following construction of the dam, specifically documented in 1958 and 2013. During the second water management operation period, moderate sediment retention (also defined as trap efficiency, which is the percentage of incoming sediments trapped within a reservoir during a given time) occurred (between 41.0 and 67.0 percent of sediments were retained). During the third period (1979–2001), between 61.2 and 99.8 percent of sediments were retained. During the fourth period (2001–18), at least 1,909 acre-feet of accumulated sediment were remobilized. The estimated dam trap efficiency during the fourth water management operation period was −37.2 percent, indicating that more sediments were being removed from the Jemez Canyon Reservoir than were being deposited. These remobilized sediments supplemented the natural sediment delivery in the Jemez River to the middle Rio Grande. The current (2022) dry reservoir operation allows sediment delivery during periods when flooding is not a concern while still providing flood control when needed.</p><p>Suspended-sediment particle size data indicate potential coarsening of suspended sediments during the fourth water management operation period, likely resulting from erosion of coarse bed sediments deposited in the reservoir. Suspended-sediment particle size data during the first and fourth water management operation periods indicate that finer sediment mobilized during monsoon season than during snowmelt. Also, suspended-sediment concentrations during the predam and post-hold pool periods indicate concentrations were higher during monsoon season than during snowmelt. Seasonal variations in suspended-sediment concentration and particle size may help dam managers make operational decisions by increasing the understanding of particle size, concentration, and variation of suspended sediment during a given year. The seasonality of suspended-sediment transport can also vary, depending not only on concentration and particle size, but on precipitation. The maximum annual suspended-sediment loads occurred during all three seasonal categories analyzed in this study: snowmelt, monsoon, and the remainder of the year. This indicates that, in addition to sediment particle size and concentration, understanding the variability of transport mechanisms of suspended-sediment load can also guide optimal water management operations at a dam.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225081","isbn":"978-1-4113-4481-5","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Brown, J.E., Matherne, A.M., Reale, J.K., and Miltenberger, K.E., 2022, Suspended-sediment transport and water management, Jemez Canyon Dam, New Mexico, 1948–2018: U.S. Geological Survey Scientific Investigations Report 2022–5081, 30 p., https://doi.org/10.3133/sir20225081.","productDescription":"Report: vii, 30 p.; 2 Datasets","numberOfPages":"42","onlineOnly":"N","ipdsId":"IP-107586","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":408905,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":408902,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5081/sir20225081.XML"},{"id":408901,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5081/sir20225081.pdf","text":"Report","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5081"},{"id":408900,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5081/coverthb.jpg"},{"id":503401,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113825.htm","linkFileType":{"id":5,"text":"html"}},{"id":409231,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225081/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":408904,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS Earth Resources Observation and Science Center database","linkHelpText":"—EarthExplorer"},{"id":408903,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5081/images"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Canyon Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -106.61655311950582,\n              35.438783063650746\n            ],\n            [\n              -106.61655311950582,\n              35.32720598341298\n            ],\n            [\n              -106.46641220000733,\n              35.32720598341298\n            ],\n            [\n              -106.46641220000733,\n              35.438783063650746\n            ],\n            [\n              -106.61655311950582,\n              35.438783063650746\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"mailto:dc_nm@usgs.gov\" href=\"mailto:dc_nm@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113 <br></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods of Investigation</li><li>Results</li><li>Discussion</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-11-08","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Jeb E. 0000-0001-7671-2379 jebbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-7671-2379","contributorId":4357,"corporation":false,"usgs":true,"family":"Brown","given":"Jeb","email":"jebbrown@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne-Marie 0000-0002-5873-2226","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":32279,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne-Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reale, Justin K.","contributorId":298654,"corporation":false,"usgs":false,"family":"Reale","given":"Justin","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":856174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miltenberger, K. E. 0000-0002-3874-4609","orcid":"https://orcid.org/0000-0002-3874-4609","contributorId":243647,"corporation":false,"usgs":true,"family":"Miltenberger","given":"K.","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236969,"text":"sir20225078 - 2022 - Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument","interactions":[],"lastModifiedDate":"2022-11-08T17:24:23.036214","indexId":"sir20225078","displayToPublicDate":"2022-11-08T10:27:32","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":"2022-5078","displayTitle":"Vegetation Map for the Seboeis Unit of Katahdin Woods and Waters National Monument","title":"Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument","docAbstract":"<p>The Katahdin Woods and Waters National Monument, located in the forests of central Maine, is a newly (2016) established unit for the National Park Service. To better understand the condition of lands within the monument and inform management planning, Katahdin Woods and Waters National Monument resource managers wanted better information of the vegetation present within the monument. To meet this need, scientists at the U.S. Geological Survey Upper Midwest Environmental Sciences Center worked with ecologists at the Maine Natural Areas Program to catalog and map the vegetation of the Seboeis Unit of the monument. This report details this process, provides results of the survey and mapping efforts, presents results in the form of a vegetation map for the Seboeis Unit, and provides vegetation descriptions and a dichotomous key for the entire Katahdin Woods and Waters National Monument.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225078","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Strassman, A.C., Hop, K.D., Sattler, S.R., Schlawin, J., and Cameron, D., 2022, Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument: U.S. Geological Survey Scientific Investigations Report 2022–5078, 73 p., https://doi.org/10.3133/sir20225078.","productDescription":"Report: x, 73 p.; Data Releases","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-130383","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":407273,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93HGWGB","text":"USGS data release","linkHelpText":"Vegetation map for the Seboeis Unit of Katahdin Woods and Waters National Monument (vector and tabular data)"},{"id":407272,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5078/images"},{"id":407267,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5078/coverthb.jpg"},{"id":407269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5078/sir20225078.pdf","text":"Report","size":"19.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5078"},{"id":407270,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5078/sir20225078.XML"},{"id":409229,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BW6YWP","text":"USGS data release","linkHelpText":"2019 Katahdin Woods and Waters National Monument 4-band imagery products"}],"country":"United States","state":"Maine","otherGeospatial":"Seboeis Unit of Katahdin Woods and Waters National Monument","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -68.82465497885659,\n              46.12747294389601\n            ],\n            [\n              -68.82465497885659,\n              45.82583589711629\n            ],\n            [\n              -68.51101993751016,\n              45.82583589711629\n            ],\n            [\n              -68.51101993751016,\n              46.12747294389601\n            ],\n            [\n              -68.82465497885659,\n              46.12747294389601\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/upper-midwest-environmental-sciences-center\" 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 data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Vegetation Classification</li><li>Vegetation Mapping</li><li>Accuracy Assessment</li><li>Summary</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Field Key to Vegetation Types</li><li>Acknowledgments</li><li>Appendix 2. Descriptions of Vegetation Types</li><li>Appendix 3. Map-Class Descriptions</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2022-11-08","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":852860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":852864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sattler, Stephanie R. 0000-0003-4417-2480 ssattler@usgs.gov","orcid":"https://orcid.org/0000-0003-4417-2480","contributorId":152030,"corporation":false,"usgs":true,"family":"Sattler","given":"Stephanie","email":"ssattler@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":852865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlawin, Justin","contributorId":296928,"corporation":false,"usgs":false,"family":"Schlawin","given":"Justin","email":"","affiliations":[],"preferred":false,"id":852866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cameron, Don","contributorId":296929,"corporation":false,"usgs":false,"family":"Cameron","given":"Don","email":"","affiliations":[],"preferred":false,"id":852867,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70238778,"text":"70238778 - 2022 - Invasive plant hitchhikers: Appalachian Trail thru-hiker knowledge and attitudes of invasive plants and Leave No Trace practices","interactions":[],"lastModifiedDate":"2022-12-12T14:39:28.023077","indexId":"70238778","displayToPublicDate":"2022-11-08T08:34:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5520,"text":"Journal of Outdoor Recreation and Tourism","active":true,"publicationSubtype":{"id":10}},"title":"Invasive plant hitchhikers: Appalachian Trail thru-hiker knowledge and attitudes of invasive plants and Leave No Trace practices","docAbstract":"<p><span>Hiking and backpacking on American National Scenic Trails has increased in popularity in recent years. To encourage responsible and sustainable outdoor recreation on these much-loved trails, direct and indirect management strategies must be employed by managerial agencies. The Leave No Trace (LNT) education program aims to protect natural resources by promoting minimum-impact behaviours that lessen environmental impacts. The accidental introduction and dispersal of non-native invasive flora by hikers is little studied but can have a detrimental environmental impact on protected areas. The purpose of our study was to understand whether Appalachian Trail thru-hikers are: 1) aware of this problem, 2) adhering to LNT principles to reduce this problem, and 3) willing to learn and adopt minimum-impact behaviours to address this problem. We found that thru-hiker knowledge of invasive plants was limited and that very few thru-hikers adopted low-impact practices to minimise plant introduction and spread. Promisingly, we found that most thru-hikers, once aware of the problems, were willing to learn and apply low-impact practices to minimise plant introduction and spread. We discuss the barriers to their adoption of these behaviours and present a comprehensive list of suggested LNT practices to limit invasive plant introduction and spread. We conclude that, whilst challenging, protected area managers can help deter the spread of invasive plants along trails by improving educational messaging, signage, personal communication, and providing supporting infrastructure that encourages visitors to adopt specific practices to minimise invasive plant introduction and spread within protected areas.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jort.2022.100581","usgsCitation":"Dolman, M., and Marion, J.L., 2022, Invasive plant hitchhikers: Appalachian Trail thru-hiker knowledge and attitudes of invasive plants and Leave No Trace practices: Journal of Outdoor Recreation and Tourism, v. 40, 100581, 12 p., https://doi.org/10.1016/j.jort.2022.100581.","productDescription":"100581, 12 p.","ipdsId":"IP-132845","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":410278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","otherGeospatial":"Appalachian Trail","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.663426481162,\n              39.327334819713826\n            ],\n            [\n              -77.84650013772489,\n              39.352244826545075\n            ],\n            [\n              -80.24694411951128,\n              37.65331631118197\n            ],\n            [\n              -80.62871457673847,\n              37.33610604928302\n            ],\n            [\n              -81.72490463550588,\n              36.63467327613432\n            ],\n            [\n              -80.86786667184651,\n              36.60267551794206\n            ],\n            [\n              -79.06482033698572,\n              37.834500309643815\n            ],\n            [\n              -77.64378265768026,\n              39.08720414992473\n            ],\n            [\n              -77.663426481162,\n              39.327334819713826\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"40","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dolman, Megan","contributorId":298242,"corporation":false,"usgs":false,"family":"Dolman","given":"Megan","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":858566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":858567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70238960,"text":"70238960 - 2022 - Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world","interactions":[],"lastModifiedDate":"2022-12-19T13:43:37.234094","indexId":"70238960","displayToPublicDate":"2022-11-08T07:36:03","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":"Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world","docAbstract":"<p><span>Drylands represent more than 41% of the global land surface and are at degradation risk due to land use and climate change. Developing strategies to mitigate degradation and restore drylands in the face of these threats requires an understanding of how drylands are shaped by not only soils and climate, but also geology and geomorphology. However, few studies have completed such a comprehensive analysis that relates spatial variation in plant communities to all aspects of the geologic–geomorphic–edaphic–plant–climate system. The focus of this study is the Colorado Plateau, a high-elevation dryland in the southwestern United States, which is particularly sensitive to future change due to climate vulnerability and increasing land-use pressure. Here, we examined 135 long-term vegetation-monitoring sites in three national parks and characterized connections between geology, geomorphology, soils, climate, and dryland plant communities. To first understand the geologic and geomorphic influences on soil formation and characteristics, we explore associations between soil pedons, bedrock geology, and geomorphology. Then, we characterize principal axes of variation in plant communities and ascertain controls and linkages between components of the edaphic–geomorphic system and plant community ordinations. Geologic and geomorphic substrate exerted controls on important properties of the soil profile, particularly depth, water-holding capacity, rockiness, salinity, and fine sands. Ordination identified five distinct plant communities and three primary axes of variation, representing gradients of woody- to herbaceous-dominated communities (Axis 1), saline scrublands to C</span><sub>3</sub><span>&nbsp;grasslands (Axis 2), and annual to perennial communities (Axis 3). Geology, geomorphology, and soil explained a large proportion of variation in Axis 1 (74%), while climate variables largely explained Axis 2 (68%), and Axis 3 was not well explained by the random forest models. The variables identified as most influential to each axis were, respectively: (1) soil depth; (2) aridity, lithology, and soil salinity; and (3) temperature and precipitation. We posit that Axis 3 represents a land degradation gradient due to historic grazing, likely exacerbated by dry conditions. Results provide a novel framework that links the geologic and geomorphic evolution of landscapes, with the distribution of soils and plant communities that can guide ecosystem management, exemplifying an approach applicable to drylands globally.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4273","usgsCitation":"Duniway, M.C., Benson, C., Nauman, T.W., Knight, A.C., Bradford, J., Munson, S.M., Witwicki, D.L., Livensperger, C., Van Scoyoc, M.W., Fisk, T.T., Thoma, D., and Miller, M.E., 2022, Geologic, geomorphic, and edaphic underpinnings of dryland ecosystems: Colorado Plateau landscapes in a changing world: Ecosphere, v. 13, no. 11, e4273, 27 p., https://doi.org/10.1002/ecs2.4273.","productDescription":"e4273, 27 p.","ipdsId":"IP-135505","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488760,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4273","text":"Publisher Index Page"},{"id":435625,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92Z8NDP","text":"USGS data release","linkHelpText":"Soil, geologic, geomorphic, climate, and vegetation data from long-term monitoring plots (2009 - 2018) in Arches, Canyonlands, and Capitol Reef National Parks, Utah, USA"},{"id":410697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.63689444724997,\n              36.734805586098716\n            ],\n            [\n              -108.00129122959586,\n              36.72595486884292\n            ],\n            [\n              -107.41606847690218,\n              37.63008491281205\n            ],\n            [\n              -107.57066880734789,\n              38.70708139014661\n            ],\n            [\n              -107.76120496171856,\n              39.973850096503895\n            ],\n            [\n              -108.78556565774403,\n              40.46292505503848\n            ],\n            [\n              -110.23348660705287,\n              40.36792094423029\n            ],\n            [\n              -111.02839675350845,\n              39.403592925523014\n            ],\n            [\n              -111.43291910676305,\n              38.05141646696123\n            ],\n            [\n              -112.77571792678364,\n              37.21069090791468\n            ],\n            [\n              -112.28678230930984,\n              36.79511547655869\n            ],\n            [\n              -111.63689444724997,\n              36.734805586098716\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benson, Christopher","contributorId":296064,"corporation":false,"usgs":false,"family":"Benson","given":"Christopher","email":"","affiliations":[{"id":63978,"text":"formerly) US Geological Survey, Southwest Biological Science Center, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":859391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":859392,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":859393,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Witwicki, Dana L.","contributorId":207763,"corporation":false,"usgs":false,"family":"Witwicki","given":"Dana","email":"","middleInitial":"L.","affiliations":[{"id":37628,"text":"National Park Service Inventory and Monitoring Program, P.O. Box 848, Moab, UT 84532, USA","active":true,"usgs":false}],"preferred":false,"id":859394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Livensperger, Carolyn","contributorId":260927,"corporation":false,"usgs":false,"family":"Livensperger","given":"Carolyn","email":"","affiliations":[{"id":52723,"text":"National Park Service, Capitol Reef National Park, 52 Headquarters Dr., Torrey UT 84775","active":true,"usgs":false}],"preferred":false,"id":859395,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Van Scoyoc, Matthew W. 0000-0001-6821-4476","orcid":"https://orcid.org/0000-0001-6821-4476","contributorId":290213,"corporation":false,"usgs":false,"family":"Van Scoyoc","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":62383,"text":"Southeast Utah Group, National Park Service, Moab, UT","active":true,"usgs":false}],"preferred":false,"id":859396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisk, Terry T","contributorId":289096,"corporation":false,"usgs":false,"family":"Fisk","given":"Terry","email":"","middleInitial":"T","affiliations":[{"id":62042,"text":"Water Resources Division, National Park Service","active":true,"usgs":false}],"preferred":false,"id":859397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Thoma, David","contributorId":265911,"corporation":false,"usgs":false,"family":"Thoma","given":"David","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":859398,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":859399,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70238582,"text":"70238582 - 2022 - Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","interactions":[],"lastModifiedDate":"2022-11-30T12:53:57.31331","indexId":"70238582","displayToPublicDate":"2022-11-08T06:50:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms","docAbstract":"<div class=\"article-section__content en main\"><p>This paper introduces a method for determining spatially-distributed, 2-D bedload rates using repeat, high-resolution surveys of the bed topography. As opposed to existing methods, bedform parameters and bedload rates are computed from bed elevation profiles interpolated along the local bedform velocities. The bedform velocity fields are computed applying Large-Scale Particle Image Velocimetry, initially developed for surface velocity measurements, to pairs of successive Digital Elevation Models (DEMs). The bathymetry data are interpolated along the direction of each bedform velocity and the mean height of the closest bedform is computed. The dune shape factor is also evaluated along each bedform direction of travel. The local bedload fluxes can be computed by multiplying the bedform velocity by its mean height averaged over the successive two DEMs, and they can be time-averaged over a series of DEM pairs. This method is applied to a high-resolution acoustical survey of an approximately 300&nbsp;m long by 40&nbsp;m wide reach of the Colorado River in Grand Canyon upstream from Diamond Creek, USA. The repeat period was about 6–10&nbsp;min and bed elevation was interpolated every 0.25&nbsp;m. The obtained results provide insight to the spatial and temporal variability of bedload rates, bedform parameters and bedload fluxes through cross-sections. The method can be applied to other repeated acoustical surveys of river reaches provided that the space and time resolutions are high enough to capture the local movement of bedforms.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR032434","usgsCitation":"Le Coz, J., Perret, E., Camenen, B., Topping, D.J., Buscombe, D.D., Leary, K., Dramais, G., and Grams, P.E., 2022, Mapping 2-D bedload rates throughout a sand-bed river reach from high-resolution acoustical surveys of migrating bedforms: Water Resources Research, v. 58, no. 11, e2022WR032434, 16 p., https://doi.org/10.1029/2022WR032434.","productDescription":"e2022WR032434, 16 p.","ipdsId":"IP-139516","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":445937,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2022wr032434","text":"External Repository"},{"id":409857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.85660930265428,\n              37.076564530984584\n            ],\n            [\n              -113.84362202724009,\n              37.076564530984584\n            ],\n            [\n              -113.84362202724009,\n              35.44740531531292\n            ],\n            [\n              -110.85660930265428,\n              35.44740531531292\n            ],\n            [\n              -110.85660930265428,\n              37.076564530984584\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"58","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Le Coz, Jérôme","contributorId":299550,"corporation":false,"usgs":false,"family":"Le Coz","given":"Jérôme","affiliations":[{"id":64876,"text":"INRAE, UR RiverLy, centre de Lyon-Villeurbanne, 5 Rue de la Doua, CS 20244, F-69625 Villeurbanne Dedex, France","active":true,"usgs":false}],"preferred":false,"id":858015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perret, Emeline","contributorId":299551,"corporation":false,"usgs":false,"family":"Perret","given":"Emeline","email":"","affiliations":[{"id":64877,"text":"INRAE, UR RiverLy, centre de Lyon-Villeurbanne, 5 Rue de la Doua, CS 20244, F-69625 Villeurbanne Dedex, France; Compagnie nationale du Rhone, Lyon, France","active":true,"usgs":false}],"preferred":false,"id":858016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Camenen, Benoît","contributorId":299552,"corporation":false,"usgs":false,"family":"Camenen","given":"Benoît","affiliations":[{"id":64876,"text":"INRAE, UR RiverLy, centre de Lyon-Villeurbanne, 5 Rue de la Doua, CS 20244, F-69625 Villeurbanne Dedex, France","active":true,"usgs":false}],"preferred":false,"id":858017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Topping, David J. 0000-0002-2104-4577","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":215068,"corporation":false,"usgs":true,"family":"Topping","given":"David","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leary, Kate","contributorId":299553,"corporation":false,"usgs":false,"family":"Leary","given":"Kate","email":"","affiliations":[{"id":64879,"text":"New Mexico Institute of Mining and Technology, Department of Earth and Environmental Sciences, Socorro, NM, 87801 USA","active":true,"usgs":false}],"preferred":false,"id":858020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dramais, Guillaume 0000-0002-2703-9314","orcid":"https://orcid.org/0000-0002-2703-9314","contributorId":238955,"corporation":false,"usgs":false,"family":"Dramais","given":"Guillaume","email":"","affiliations":[{"id":47837,"text":"Ph.D. student, IRSTEA, Flagstaff, Arizona","active":true,"usgs":false}],"preferred":false,"id":858021,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grams, Paul E. 0000-0002-0873-0708","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":216115,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":858022,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70274032,"text":"70274032 - 2022 - Regularizing priors for Bayesian VAR applications to large ecological datasets","interactions":[],"lastModifiedDate":"2026-02-24T16:53:30.35343","indexId":"70274032","displayToPublicDate":"2022-11-08T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Regularizing priors for Bayesian VAR applications to large ecological datasets","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Using multi-species time series data has long been of interest for estimating inter-specific interactions with vector autoregressive models (VAR) and state space VAR models (VARSS); these methods are also described in the ecological literature as multivariate autoregressive models (MAR, MARSS). To date, most studies have used these approaches on relatively small food webs where the total number of interactions to be estimated is relatively small. However, as the number of species or functional groups increases, the length of the time series must also increase to provide enough degrees of freedom with which to estimate the pairwise interactions. To address this issue, we use Bayesian methods to explore the potential benefits of using regularized priors, such as Laplace and regularized horseshoe, on estimating interspecific interactions with VAR and VARSS models. We first perform a large-scale simulation study, examining the performance of alternative priors across various levels of observation error. Results from these simulations show that for sparse matrices, the regularized horseshoe prior minimizes the bias and variance across all inter-specific interactions. We then apply the Bayesian VAR model with regularized priors to a output from a large marine food web model (37 species) from the west coast of the USA. Results from this analysis indicate that regularization improves predictive performance of the VAR model, while still identifying important inter-specific interactions.</span></span></p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.14332","usgsCitation":"Ward, E.J., Marshall, K.N., Scheuerell, M.D., 2022, Regularizing priors for Bayesian VAR applications to large ecological datasets: PeerJ, v. 10, e14332, 18 p., https://doi.org/10.7717/peerj.14332.","productDescription":"e14332, 18 p.","ipdsId":"IP-144838","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500605,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.14332","text":"Publisher Index Page"},{"id":500429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Eric J.","contributorId":366786,"corporation":false,"usgs":false,"family":"Ward","given":"Eric","middleInitial":"J.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":956224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Kristin N.","contributorId":366787,"corporation":false,"usgs":false,"family":"Marshall","given":"Kristin","middleInitial":"N.","affiliations":[{"id":38436,"text":"National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":956225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956226,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70237990,"text":"tm17A1 - 2022 - Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners","interactions":[],"lastModifiedDate":"2022-11-07T17:14:33.667614","indexId":"tm17A1","displayToPublicDate":"2022-11-07T11:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"17-A1","displayTitle":"Rapidly Assessing Social Characteristics of Drought Preparedness and Decision Making: A Guide for Practitioners","title":"Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners","docAbstract":"<h1>Executive Summary</h1><p>This guide is intended to provide managers, decision makers, and other practitioners with advice on conducting a rapid assessment of the social dimensions of drought. Findings from a rapid assessment can provide key social context that may aid in decision making, such as when preparing a drought plan, allocating local drought resilience funding, or gathering the support of local agencies and organizations for collective action related to drought mitigation.</p><p><strong>Part I</strong>—In the introduction to Part I, we describe the unique problems associated with drought—particularly its slow onset and long duration, which make it difficult to define drought—and highlight five major types of drought (see Box 1). We introduce a few social dimensions of drought (such as economic and institutional perspectives), demonstrate how these dimensions can be interrelated, and describe a few of the modern challenges (such as transformational change and cascading risks) that practitioners face.</p><p>We also provide background on the rapid assessment method, first describing it as a “snapshot” of the social landscape, then providing some key advantages of the method (it can be quicker and cheaper than more in-depth methods), and lastly describing how secondary data and other methods can help overcome some of the disadvantages of rapid assessments.</p><p>Then, after summarizing the process of developing this guide, we outline the process of using the guide. Importantly, we compare the guide to a travel guide, which provides many different types of information and is best approached with specific interests in mind. Ultimately, we hope for this guide to be malleable enough that it can be helpful to researchers and practitioners in many different contexts, using many different research methods. Related to how to use the guide, we characterize the type of person who might be motivated to use this guide. We also specify key qualifications for a researcher conducting a rapid assessment, drawing particular attention to training on ethical considerations.</p><p>We sketch out key considerations when choosing social dimensions of drought to focus on, and the type of data used for analysis. First, it is important to note that in this guide we provide nine important social dimensions of drought, but this is by no means a comprehensive list, and a researcher may find that other dimensions better fit their local context. Second, we provide some pros and cons to a narrow (focusing on just a few dimensions or at a smaller scale) versus broad research focus. Lastly, we describe the pros and cons of using primary versus secondary data (one strategy is to use both, sequentially) and qualitative versus quantitative data.</p><p>Ultimately, Part I of this guide functions as an exploration of the various decisions a researcher will make when designing a rapid assessment. These decisions will inform the type of findings and other outcomes that result from the rapid assessment.</p><p><strong>Part II</strong>—Part II of this guide introduces nine key social dimensions of drought: defining the problem of drought, individual perceptions, social relationships, technology, economics and livelihoods, water governance, decision making, information, and social vulnerability. Each section provides background and key considerations related to a particular dimension, as well as ideas for how to explore the dimension via a rapid assessment.</p><p><strong>Part III</strong>—Part III of this guide provides two hypothetical examples of how one might use this guide to aid the practitioner in implementing the lessons learned here. In the first example, a watershed group uses two dimensions, defining the problem of drought and social relationships, to inform a community meeting about protecting fisheries from drought. In the second example, a resource manager uses the economics and livelihoods and social vulnerability dimensions to inform the development of a livestock grazing drought management plan.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm17A1","usgsCitation":"Clifford, K.R., Goolsby, J.B., Cravens, A.E., and Cooper, A.E., 2022, Rapidly assessing social characteristics of drought preparedness and decision making: A guide for practitioners: U.S. Geological Survey Techniques and Methods 17-A1, 41 p., https://doi.org/10.3133/tm17A1.","productDescription":"vii, 41 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":409066,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.xml"},{"id":409065,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/17/a1/images"},{"id":409061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/17/a1/coverthb.jpg"},{"id":409062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/17/a1/tm17a1.pdf","text":"Report","size":"1.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 17-A1"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/fort/\" data-mce-href=\"https://www.usgs.gov/centers/fort/\"> Fort Collins Science Center</a><br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526-8118</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Part I: The Research Guide</li><li>Part II: Social Dimensions of Drought</li><li>Part III: Using the Guide</li><li>References Cited</li><li>Appendix 1. History of Rapid Assessment</li><li>Appendix 2. Rapid Assessment Publications</li></ul>","publishedDate":"2022-11-07","noUsgsAuthors":false,"publicationDate":"2022-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Clifford, Katherine R. 0000-0002-1385-8765","orcid":"https://orcid.org/0000-0002-1385-8765","contributorId":259886,"corporation":false,"usgs":true,"family":"Clifford","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goolsby, Julia B. 0000-0002-2229-5685","orcid":"https://orcid.org/0000-0002-2229-5685","contributorId":269631,"corporation":false,"usgs":true,"family":"Goolsby","given":"Julia","email":"","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cooper, Ashley E. 0000-0001-9817-4444","orcid":"https://orcid.org/0000-0001-9817-4444","contributorId":257654,"corporation":false,"usgs":true,"family":"Cooper","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":856457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70254959,"text":"70254959 - 2022 - Drones and bathymetry show the importance of optimal water depth for nest placement within breeding colonies of Western and Clark’s grebes","interactions":[],"lastModifiedDate":"2024-06-11T16:08:23.717659","indexId":"70254959","displayToPublicDate":"2022-11-07T10:59:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Drones and bathymetry show the importance of optimal water depth for nest placement within breeding colonies of Western and Clark’s grebes","docAbstract":"<p><span>Habitat selection involves a series of decisions that are arguably the most important decisions that animals make and these decisions occur at multiple hierarchical spatial scales. Colonial-nesting birds face a unique challenge when selecting a nest site because each bird’s choices are severely constrained by other birds within their breeding colony. Individuals must seek out optimum nesting locations within the constraint of the colony’s geographic location. We investigated how water depth and proximity to open water affected 4th-order nest-site selection of Western and Clark’s Grebes (</span><i>Aechmophorus occidentalis, Aechmophorus clarkii</i><span>), colonial nesting waterbirds that have declined in abundance across their range. We used an orthomosiac that we created from ~ 500 aerial drone images of a large breeding colony to construct a Resource Selection Function to describe microhabitat features that influence nest-site placement within the colony footprint. Grebes preferred to nest in portions of the colony with intermediate water depths (40-80&nbsp;cm during nest construction) and they preferred to nest in portions of the colony furthest from open water. Understanding how individual birds make use of available microhabitat features within the footprint of their breeding colony can help inform conservation efforts of colonial-nesting birds, particularly for species that nest in wetland habitats whose water levels are managed for human use.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s13157-022-01602-1","usgsCitation":"Lachman, D.A., Conway, C.J., Vierling, K.T., Matthews, T., and Mack, D., 2022, Drones and bathymetry show the importance of optimal water depth for nest placement within breeding colonies of Western and Clark’s grebes: Wetlands, v. 42, 110, 10 p., https://doi.org/10.1007/s13157-022-01602-1.","productDescription":"110, 10 p.","ipdsId":"IP-132937","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":429886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Valley County","otherGeospatial":"Cascade Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -116.20273923505505,\n              44.769058037542806\n            ],\n            [\n              -116.20273923505505,\n              44.47495390440537\n            ],\n            [\n              -116.01258023679465,\n              44.47495390440537\n            ],\n            [\n              -116.01258023679465,\n              44.769058037542806\n            ],\n            [\n              -116.20273923505505,\n              44.769058037542806\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"42","noUsgsAuthors":false,"publicationDate":"2022-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lachman, Deo A.","contributorId":338149,"corporation":false,"usgs":false,"family":"Lachman","given":"Deo","email":"","middleInitial":"A.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":902975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Kerri T.","contributorId":338150,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":81087,"text":"University of Idaho, Department of Fish and Wildlife Sciences","active":true,"usgs":false}],"preferred":false,"id":902977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, Ty","contributorId":338151,"corporation":false,"usgs":false,"family":"Matthews","given":"Ty","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mack, Diane Evans","contributorId":338152,"corporation":false,"usgs":false,"family":"Mack","given":"Diane Evans","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":902979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70242697,"text":"70242697 - 2022 - Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","interactions":[],"lastModifiedDate":"2023-04-13T12:18:36.893973","indexId":"70242697","displayToPublicDate":"2022-11-06T07:13:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab005\" class=\"abstract author\"><div id=\"as005\"><p id=\"sp0005\">Like many impaired Great Lakes tributaries, Apple Creek, Wisconsin (119&nbsp;km<sup>2</sup><span>) has Total Maximum Daily Load (TMDL) targets for reducing&nbsp;suspended sediment&nbsp;and total phosphorus by 51.2&nbsp;% and 64.2&nbsp;%, respectively. From August 2017 - October 2018, a stream&nbsp;sediment budget&nbsp;and fingerprinting integrated study was conducted to quantify upland and stream corridor sources of suspended sediment and sediment-bound phosphorus. Phosphorus concentrations varied among source groups and fluvial sediments, with higher concentrations among suspended sediment and cropland soils. Eroding streambanks identified in the stream corridor sediment budget accounted for 100&nbsp;% of the TMDL Soil and Water Assessment Tool (SWAT) suspended sediment load but only 20&nbsp;% of the total phosphorus load. Fine-grained streambed sediment equated to approximately-three years of modeled suspended sediment load but only one third of total phosphorus load. The two primary sources of fine-grained streambed sediment were streambanks and cropland, with relative streambank contributions increasing with downstream direction and watershed area. The relative proportion of suspended sediment varied by season and&nbsp;streamflow; however, cropland and streambank erosion accounted for 54&nbsp;% and 23&nbsp;% of the suspended sediment when weighted by of the proportion for representative streamflow. Urban land was a source in the upper watershed, but the signature was sequestered by a mid-watershed detention basin. Contributions from construction sites were higher in the fall 2018, likely corresponding to increased activity following a wet spring. These integrated techniques helped describe sources, transport, and sinks of fluvial sediment and phosphorus throughout the watershed at a range of spatial and temporal scales.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2022.08.024","usgsCitation":"Blount, J.D., Kammel, L., and Fitzpatrick, F., 2022, Stream corridor and upland sources of fluvial sediment and phosphorus from a mixed urban-agricultural tributary to the Great Lakes: Journal of Great Lakes Research, v. 48, no. 6, p. 1536-1549, https://doi.org/10.1016/j.jglr.2022.08.024.","productDescription":"14 p.","startPage":"1536","endPage":"1549","ipdsId":"IP-130233","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":494972,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13USQVX","text":"USGS data release","linkHelpText":"Chemical and Physical Data for Streambed Sediment-Source Fingerprinting in the Apple Creek Watershed, Outagamie County, Wisconsin, 2017-2018"},{"id":445940,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2022.08.024","text":"Publisher Index Page"},{"id":435626,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F8QS08","text":"USGS data release","linkHelpText":"Apple Creek Rapid Geomorphic Assessment, Outagamie County, Wisconsin"},{"id":415706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Appleton","otherGeospatial":"Apple Creek basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.4047337275233,\n              44.361963714867386\n            ],\n            [\n              -88.4047337275233,\n              44.245437009909836\n            ],\n            [\n              -88.17063678311628,\n              44.245437009909836\n            ],\n            [\n              -88.17063678311628,\n              44.361963714867386\n            ],\n            [\n              -88.4047337275233,\n              44.361963714867386\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blount, James D. 0000-0002-0006-3947 jblount@usgs.gov","orcid":"https://orcid.org/0000-0002-0006-3947","contributorId":200231,"corporation":false,"usgs":true,"family":"Blount","given":"James","email":"jblount@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kammel, Leah 0000-0003-4613-0858","orcid":"https://orcid.org/0000-0003-4613-0858","contributorId":211840,"corporation":false,"usgs":true,"family":"Kammel","given":"Leah","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209540,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869397,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70245128,"text":"70245128 - 2022 - Longman's Beaked Whale (Indopacetus pacificus) in Fiji","interactions":[],"lastModifiedDate":"2023-06-16T11:57:55.747939","indexId":"70245128","displayToPublicDate":"2022-11-05T06:55:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":869,"text":"Aquatic Mammals","active":true,"publicationSubtype":{"id":10}},"title":"Longman's Beaked Whale (Indopacetus pacificus) in Fiji","docAbstract":"Beaked whales (Ziphidae) are the second largest family of cetaceans with 23 currently recognized species, and the Longman's beaked whale (Indopacetus pacificus) is one of the least known globally (Reeves et al., 2003; Yamada et al., 2019). Longman's beaked whales occur in tropical waters from the western Indian Ocean to the eastern Pacific (Jefferson et al., 2015), with strandings in the Pacific reported from Hawaii, the Philippines, Taiwan, Japan, and New Caledonia (Figure 1) (West et al., 2013; Garrigue et al., 2016; Acebes et al., 2019; Kobayashi et al., 2021). Here we report the first record of this species in Fiji.","language":"English","publisher":"Aquatic Mammals","doi":"10.1578/AM.48.6.2022.533","usgsCitation":"Fisher, S.R., Anstey, S., Nasaunivalu, I., and Fisher, R., 2022, Longman's Beaked Whale (Indopacetus pacificus) in Fiji: Aquatic Mammals, v. 48, no. 6, p. 533-535, https://doi.org/10.1578/AM.48.6.2022.533.","productDescription":"3 p.","startPage":"533","endPage":"535","ipdsId":"IP-142954","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":418152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Fiji","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              176.1080132050006,\n              -15.617749184970123\n            ],\n            [\n              176.1080132050006,\n              -19.6357124571326\n            ],\n            [\n              180.6763656406087,\n              -19.6357124571326\n            ],\n            [\n              180.6763656406087,\n              -15.617749184970123\n            ],\n            [\n              176.1080132050006,\n              -15.617749184970123\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-11-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fisher, Sam R","contributorId":269385,"corporation":false,"usgs":false,"family":"Fisher","given":"Sam","email":"","middleInitial":"R","affiliations":[{"id":55962,"text":"Southwestern College","active":true,"usgs":false}],"preferred":false,"id":875606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anstey, Steve","contributorId":310418,"corporation":false,"usgs":false,"family":"Anstey","given":"Steve","email":"","affiliations":[{"id":67181,"text":"2Ahura Resorts Conservation Foundation, Nadi, Fiji","active":true,"usgs":false}],"preferred":false,"id":875607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nasaunivalu, Isikeli","contributorId":310419,"corporation":false,"usgs":false,"family":"Nasaunivalu","given":"Isikeli","email":"","affiliations":[{"id":67182,"text":"Likuliku Lagoon Resort, Malolo Levu, Fiji","active":true,"usgs":false}],"preferred":false,"id":875608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":51675,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":875609,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255061,"text":"70255061 - 2022 - Small-scale variation in trap placement affects arthropod capture rates on sticky traps in riparian woodlands","interactions":[],"lastModifiedDate":"2024-06-12T23:39:13.248162","indexId":"70255061","displayToPublicDate":"2022-11-04T18:37:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5991,"text":"The Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Small-scale variation in trap placement affects arthropod capture rates on sticky traps in riparian woodlands","docAbstract":"<p id=\"ID0EF\" class=\"first\">Arthropods are important prey for many avian taxa, particularly during the breeding season. Many studies have used sticky traps to estimate relative abundance of arthropods as avian prey, but we know little about the potential biases associated with sticky traps. We evaluated the effect of small-scale variation in trap placement on the biomass of arthropods caught on sticky traps in six riparian woodlands in southeastern Arizona. We detected differences in arthropod biomass between two height categories (1 and 4 m off the ground) for three insect orders and between two sampling locations (0 and 10 m from the center of the stream bed) for two insect orders. These differences indicate that placement of sticky traps affects arthropod capture rates and, hence, small variation in trap placement can bias investigators' ability to document spatial and temporal differences in arthropod abundance. Investigators who use sticky traps to make comparisons of arthropod abundance need to ensure that placement is consistent over time or across treatments to ensure that comparisons are not biased.</p>","language":"English","publisher":"BioOne","doi":"10.1894/0038-4909-66.4.275","usgsCitation":"LaRoche, D.D., Kirkpatrick, C., and Conway, C.J., 2022, Small-scale variation in trap placement affects arthropod capture rates on sticky traps in riparian woodlands: The Southwestern Naturalist, v. 66, no. 4, p. 275-279, https://doi.org/10.1894/0038-4909-66.4.275.","productDescription":"5 p.","startPage":"275","endPage":"279","ipdsId":"IP-123873","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":430057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"LaRoche, Dominic D.","contributorId":338468,"corporation":false,"usgs":false,"family":"LaRoche","given":"Dominic","email":"","middleInitial":"D.","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":903288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirkpatrick, Chris","contributorId":338469,"corporation":false,"usgs":false,"family":"Kirkpatrick","given":"Chris","email":"","affiliations":[{"id":81133,"text":"Arizona Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":903289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903287,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238042,"text":"ofr20221083 - 2022 - Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","interactions":[],"lastModifiedDate":"2022-12-08T18:11:30.705283","indexId":"ofr20221083","displayToPublicDate":"2022-11-04T11:13:16","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":"2022-1083","displayTitle":"Passage of Adult Coho Salmon (<em>Oncorhynchus kisutch</em>) over Lake Creek Falls, Oregon, 2019","title":"Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019","docAbstract":"<p class=\"p1\">Across the Pacific Northwest, there are many examples of artificial structures created to allow passage of upstream-migrating salmon over natural barriers. We studied upstream passage across three structures installed in 1989 to allow passage of salmon over Lake Creek Falls, a series of three natural waterfalls at the outlet of Triangle Lake on Lake Creek, in the central Oregon Coast Range (lat 123.57508°; long 44.15735°). To track upstream passage by adult coho salmon (<i>Oncorhynchus kisutch</i>), 87 fish were tagged using gastrically implanted radio tags. Tracking was accomplished with a series of stationary receivers installed to detect crossings at each of three structures—over Lake Creek Falls using two upstream Denil-type ladders and a bypass downstream constructed to mimic a natural side channel. Tracking spanned the upstream migration and spawn timing for adult coho salmon in the basin and extended from October 2019 to February 2020. A total of 15 coho salmon (17 percent) were tagged in October, 30 coho salmon (35 percent) were tagged in November, and 42 coho salmon (48 percent) were tagged in December. Later-than-normal precipitation and associated low discharge delayed upstream migrations. Accordingly, most fish arrived late in the season (late November and December) and in sudden flushes with the erratic rain events. Fish that were tagged earlier were more likely to cross all three ladders, with more than 93 percent of fish tagged in October compared to 46.7 and 19.0 percent of November and December fish passing, respectively. The decline in passage rate could be attributed to the overlapping influences of stream discharge and advanced stage of maturation (lower energy reserves) of fish later in the season. Near the end of the study, both fish that crossed and fish obstructed by barriers were observed in tributaries known to be used for spawning by coho salmon. Without a much longer-term study involving many more fish than the current study, more intensive tracking, and coverage of different flow years, firm conclusions are difficult to draw regarding the overall influences of the passage structures on the likelihood of upstream passage by adult coho salmon. However, substantial numbers of fish are capable of crossing during certain conditions. The population-level consequences of the barriers on spawning distribution and the production of coho salmon in the watershed are not clear. Additional empirical study or population modeling could be used to address this question in more detail.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221083","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Fischer, R.B., Dunham, J., Scheidt, N., Hansen, A.C., and Heaston, E.D., 2022, Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019: U.S. Geological Survey Open-File Report 2022–1083, 19 p., https://doi.org/10.3133/ofr20221083.","productDescription":"vii, 19 p.","onlineOnly":"Y","ipdsId":"IP-130393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1083/coverthb.jpg"},{"id":409181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.XML"},{"id":409180,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1083/images"},{"id":409179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1083"},{"id":409178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1083"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Creek Falls","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.61844237310005,\n              44.17170307975459\n            ],\n            [\n              -123.61844237310005,\n              44.131057340436286\n            ],\n            [\n              -123.5593908594283,\n              44.131057340436286\n            ],\n            [\n              -123.5593908594283,\n              44.17170307975459\n            ],\n            [\n              -123.61844237310005,\n              44.17170307975459\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/forest-and-rangeland-ecosystem-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/forest-and-rangeland-ecosystem-science-center\">Forest and Rangeland Ecosystem Science Center</a><br>777 NW 9th Street, Suite 400<br>Corvallis, OR 97330</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Data Analysis</li><li>Results</li><li>Discussion</li><li>References Cited</li><li>Appendix 1</li></ul>","publishedDate":"2022-11-04","noUsgsAuthors":false,"publicationDate":"2022-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Fischer, Reed B.","contributorId":298909,"corporation":false,"usgs":false,"family":"Fischer","given":"Reed","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":856685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheidt, Nicholas","contributorId":298910,"corporation":false,"usgs":false,"family":"Scheidt","given":"Nicholas","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":856687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Amy C. 0000-0002-0298-9137 achansen@usgs.gov","orcid":"https://orcid.org/0000-0002-0298-9137","contributorId":4350,"corporation":false,"usgs":true,"family":"Hansen","given":"Amy","email":"achansen@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heaston, Emily D. 0000-0002-3949-391X","orcid":"https://orcid.org/0000-0002-3949-391X","contributorId":236919,"corporation":false,"usgs":false,"family":"Heaston","given":"Emily","email":"","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":856689,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259480,"text":"70259480 - 2022 - Pyroclastic deposits of Ubehebe Crater, Death Valley, California, USA: Ballistics, pyroclastic surges, and dry granular flows","interactions":[],"lastModifiedDate":"2024-10-09T11:55:32.620604","indexId":"70259480","displayToPublicDate":"2022-11-04T06:51:31","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":"Pyroclastic deposits of Ubehebe Crater, Death Valley, California, USA: Ballistics, pyroclastic surges, and dry granular flows","docAbstract":"<div id=\"135204479\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>We describe and interpret deposits associated with the final Ubehebe Crater-forming, phreatomagmatic explosive phase of the multivent, monogenetic Ubehebe volcanic center. Ubehebe volcano is located in Death Valley, California, USA. Pyroclastic deposits occur in four main facies: (1) lapilli- and blockdominated beds, (2) thinly bedded lapilli tuff, (3) laminated and cross-laminated ash, and (4) massive lapilli ash/tuff. Lapilli- and block-dominated beds are found mostly within several hundred meters of the crater and transition outward into discontinuous lenses of lapilli and blocks; they are interpreted to have been deposited by ballistic processes associated with crater-forming explosions. Thinly bedded lapilli tuff is found mainly within several hundred meters, and laminated and cross-laminated ash extends at least 9 km from the crater center. Dune forms are common within ~2 km of the crater center, while finer-grained, distal deposits tend to exhibit planar lamination. These two facies (thinly bedded lapilli tuff and laminated and cross-laminated ash) are interpreted to record multiple pyroclastic surges (dilute pyroclastic currents). Repeated couplets of coarse layers overlain by finer-grained, laminated horizons suggest that many or most of the surges were transient, likely recording individual explosions, and they traveled over complex topography in some areas. These two factors complicate the application of classical sediment-transport theory to quantify surge properties. However, dune-form data provide possible constraints on the relationships between suspended load sedimentation and bed-load transport that are consistent using two independent approaches. Massive lapilli ash/tuff beds occur in drainages below steep slopes and can extend up to ~1 km onto adjacent valley floors beneath large catchments. Although they are massive in texture, their grain-size characteristics are shared with laminated and cross-laminated ash facies, with which they are locally interbedded. These are interpreted to record concentrated granular flows sourced by remobilized pyroclastic surge deposits, either during surge transport or shortly after, while the surge deposits retained their elevated initial pore-gas pressures. Although similar surge-derived concentrated flows have been described elsewhere (e.g., Mount St. Helens, Washington, USA, and Soufriére Hills, Montserrat, West Indies), to our knowledge Ubehebe is the first case where such processes have been identified at a maar volcano. These concentrated flows followed paths that were independent of the pyroclastic surges and represent a potential hazard at similar maar volcanoes in areas with complex terrain.</p></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02526.1","usgsCitation":"Valentine, G., Fierstein, J., and White, J.D., 2022, Pyroclastic deposits of Ubehebe Crater, Death Valley, California, USA: Ballistics, pyroclastic surges, and dry granular flows: Geosphere, v. 18, no. 6, p. 1926-1957, https://doi.org/10.1130/GES02526.1.","productDescription":"32 p.","startPage":"1926","endPage":"1957","ipdsId":"IP-138511","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467149,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02526.1","text":"Publisher Index Page"},{"id":462735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Ubehebe Crater, Death Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.33005115760992,\n              36.776109047649626\n            ],\n            [\n              -117.33005115760992,\n              36.46766275537365\n            ],\n            [\n              -116.85668632295284,\n              36.46766275537365\n            ],\n            [\n              -116.85668632295284,\n              36.776109047649626\n            ],\n            [\n              -117.33005115760992,\n              36.776109047649626\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentine, Gregory","contributorId":317825,"corporation":false,"usgs":false,"family":"Valentine","given":"Gregory","email":"","affiliations":[{"id":37970,"text":"State University of New York, Buffalo","active":true,"usgs":false}],"preferred":false,"id":915443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fierstein, Judith E. 0000-0001-8024-1426","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":329988,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, James D L","contributorId":345055,"corporation":false,"usgs":false,"family":"White","given":"James","email":"","middleInitial":"D L","affiliations":[{"id":13378,"text":"University of Otago, New Zealand","active":true,"usgs":false}],"preferred":false,"id":915445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238045,"text":"70238045 - 2022 - Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging","interactions":[],"lastModifiedDate":"2022-11-07T12:50:24.402862","indexId":"70238045","displayToPublicDate":"2022-11-04T06:42:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0065\">Diagnostic absorption features in hyperspectral data can be used to identify a specific mineral or mineral associations. However, it is unknown how accurate hyperspectral mapping can be for identifying alteration mineral compositions at the resolution required to describe structures such as fossil intrusions, or whether it can accurately quantify the alteration present. This study compared petrographic observation with visible, near-infrared (VNIR), and shortwave infrared (SWIR) hyperspectral remote sensing at laboratory- (centimetre-scale) and aerial- (metre-scale) scales to characterise the abundance of surface hydrothermal rock alteration in and around a shallow fossil intrusion on Pinnacle Ridge, Mt. Ruapehu, New Zealand. We classified a high-resolution aerial hyperspectral image to develop a new surface alteration map using Spectral Angle Mapper (SAM) algorithm. The petrographic thin-section and the laboratory and aerial hyperspectral imaging revealed a spectrum of hydrous alteration phases as indicated by the presence of an absorption feature at 2207&nbsp;nm. Moderate correlation exists between the depth of the absorption feature at 2207&nbsp;nm and the point counting-derived alteration percent values, indicating reliability of laboratory-based hyperspectral analytical methods. In contrast, aerial hyperspectral data failed to provide any clear correlations to field-mapped alteration using a band-depth approach, and we interpret this due to ‘oversampling’ of surface (supergene) alteration, spectral mixing, and sensor limitations (e.g., bandwidth, signal-to-noise ratio). The hyperspectral image-derived alteration map, created using supervised image classification, can loosely be translated to a geotechnical map where porosity and permeability play a major role in localizing hydrothermal fluid flow and the formation of alteration mineral associations.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107700","usgsCitation":"Douglas, A., Kereszturi, G., Schaefer, L.N., and Kennedy, B.M., 2022, Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging: Journal of Volcanology and Geothermal Research, 107700, 15 p., https://doi.org/10.1016/j.jvolgeores.2022.107700.","productDescription":"107700, 15 p.","ipdsId":"IP-141155","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":409188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Mt. Ruapehu","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              175.18450850284427,\n              -38.81524047528322\n            ],\n            [\n              175.18450850284427,\n              -39.6149627891337\n            ],\n            [\n              176.05242842471847,\n              -39.6149627891337\n            ],\n            [\n              176.05242842471847,\n              -38.81524047528322\n            ],\n            [\n              175.18450850284427,\n              -38.81524047528322\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Douglas, Abbey","contributorId":298912,"corporation":false,"usgs":false,"family":"Douglas","given":"Abbey","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":856697,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kereszturi, Gabor 0000-0003-4336-2012","orcid":"https://orcid.org/0000-0003-4336-2012","contributorId":247601,"corporation":false,"usgs":false,"family":"Kereszturi","given":"Gabor","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":856698,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":856699,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":856700,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238436,"text":"70238436 - 2022 - Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017","interactions":[],"lastModifiedDate":"2022-11-23T12:37:26.148964","indexId":"70238436","displayToPublicDate":"2022-11-04T06:33:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10778,"text":"Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017","docAbstract":"<div class=\"html-p\">The Precipitation-Runoff Modeling System (PRMS) was used to develop a simulation of watershed hydrology on the island of Puerto Rico for the period 1981–2017, concentrating on the Río Grande de Arecibo, a river with some of the highest streamflows on the island. This development is part of the U.S. Geological Survey’s (USGS) National Hydrologic Model (NHM) infrastructure which supports coordinated, comprehensive, and consistent hydrologic modeling at the watershed scale for the coterminous United States (CONUS). A goal of the NHM program is to expand the domain outside of CONUS, leading to a PRMS application in Puerto Rico. This model was used to simulate the effects of Hurricane Maria on daily streamflow and provide information at locations where streamgages were damaged by the hurricane. Comparisons with streamflow estimates made by indirect methods in the field, up to ten times higher than simulated values, lends insight into the uncertainties in both the indirect methods and model simulated values and helps to identify potential error in the daily streamflow estimates. The PRMS can be applied to look at the effects of changes in climate and land use, water management, industrial and public water usage, and many other factors that affect hydrology on the island of Puerto Rico. The model is also designed as a support tool for the USGS National Water Census which provides comprehensive reporting of national information on withdrawal, conveyance, consumptive use, and return flow by water-use category.</div><div id=\"html-keywords\"><br></div>","language":"English","publisher":"MDPI","doi":"10.3390/hydrology9110205","usgsCitation":"Swain, E., and Bellino, J.C., 2022, Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017: Hydrology, v. 11, no. 9, 205, 27 p., https://doi.org/10.3390/hydrology9110205.","productDescription":"205, 27 p.","ipdsId":"IP-124891","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":445945,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology9110205","text":"Publisher Index 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,{"id":70237995,"text":"70237995 - 2022 - Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability","interactions":[],"lastModifiedDate":"2022-11-03T17:07:22.337181","indexId":"70237995","displayToPublicDate":"2022-11-03T12:01:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability","docAbstract":"<p><span>Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5&nbsp;m). These BNs were then linked to another BN to predict habitat availability for piping plovers (</span><i>Charadrius melodus</i><span>), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully-linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario-based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022EA002286","usgsCitation":"Gutierrez, B.T., Zeigler, S., Lentz, E.E., Sturdivant, E., and Plant, N., 2022, Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability: Earth and Space Science, v. 9, no. 11, e2022EA002286, 24 p., https://doi.org/10.1029/2022EA002286.","productDescription":"e2022EA002286, 24 p.","ipdsId":"IP-133519","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445946,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022ea002286","text":"Publisher Index Page"},{"id":435628,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R63EMY","text":"USGS data release","linkHelpText":"LinkedBNs_4Habitat - Matlab files to link Bayesian networks to generate habitat predictions"},{"id":409116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.29594026716985,\n              40.63299474223902\n            ],\n            [\n              -73.3215230252425,\n              40.62686351437537\n            ],\n            [\n              -73.31075133763278,\n              40.61664355031391\n            ],\n            [\n              -73.26429843481641,\n              40.61766561708444\n            ],\n            [\n              -73.18687693012288,\n              40.63299474223902\n            ],\n            [\n              -73.03405361216147,\n              40.66823837708819\n            ],\n            [\n              -72.97548256078474,\n              40.69019238633578\n            ],\n            [\n              -72.90142720846879,\n              40.71673176155275\n            ],\n            [\n              -72.75498136755509,\n              40.76126281049005\n            ],\n            [\n              -72.75113811514511,\n              40.771161378285385\n            ],\n            [\n              -72.79008117864493,\n              40.76709873688291\n            ],\n            [\n              -72.82145002511935,\n              40.7537050773594\n            ],\n            [\n              -72.84023809567569,\n              40.75014350867727\n            ],\n            [\n              -72.87497858406178,\n              40.735821347504924\n            ],\n            [\n              -72.91489181798045,\n              40.735609108172895\n            ],\n            [\n              -72.93239581034598,\n              40.71979331664596\n            ],\n            [\n              -72.98894717029637,\n              40.70040108981058\n            ],\n            [\n              -73.00241177980864,\n              40.69019238633578\n            ],\n            [\n              -73.07512067117331,\n              40.66977028676959\n            ],\n            [\n              -73.19495569582996,\n              40.64729875129544\n            ],\n            [\n              -73.26631812624335,\n              40.628907319545874\n            ],\n            [\n              -73.29594026716985,\n              40.63299474223902\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zeigler, Sara 0000-0002-5472-769X","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":222703,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sturdivant, Emily J.","contributorId":297196,"corporation":false,"usgs":false,"family":"Sturdivant","given":"Emily J.","affiliations":[{"id":56085,"text":"Woodwell Climate Research Center","active":true,"usgs":false}],"preferred":false,"id":856472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plant, Nathaniel 0000-0002-5703-5672","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":81234,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856473,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70237998,"text":"70237998 - 2022 - CoastalImageLib: An open-source Python package for creating common coastal image products","interactions":[],"lastModifiedDate":"2022-11-03T16:54:01.037543","indexId":"70237998","displayToPublicDate":"2022-11-03T11:51:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5923,"text":"SoftwareX","active":true,"publicationSubtype":{"id":10}},"title":"CoastalImageLib: An open-source Python package for creating common coastal image products","docAbstract":"<p id=\"d1e241\"><i>CoastalImageLib</i><span>&nbsp;</span>is a Python library that produces common coastal image products intended for quantitative analysis of coastal environments. This library contains functions to georectify and merge multiple oblique camera views, produce statistical image products for a given set of images, and create subsampled pixel instruments for use in bathymetric inversion, surface current estimation, run-up calculations, and other quantitative analyses. This package intends to be an open-source broadly generalizable front end to future coastal imaging applications, ultimately expanding user accessibility to optical remote sensing of coastal environments. This package was developed and tested on data collected from the Argus Tower, a 43&nbsp;m tall observation structure in Duck, North Carolina at the US Army Engineer Research and Development Center’s Field Research Facility that holds six stationary cameras which collect twice-hourly coastal image products. Thus,<span>&nbsp;</span><i>CoastalImageLib</i><span>&nbsp;</span>also contains functions designed to interface with the file storage and collection system implemented at the Argus Tower.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.softx.2022.101215","usgsCitation":"McCann, M., Anderson, D.L., Sherwood, C.R., Bruder, B., Bak, A.S., and Brodie, K., 2022, CoastalImageLib: An open-source Python package for creating common coastal image products: SoftwareX, v. 20, 101215, 7 p., https://doi.org/10.1016/j.softx.2022.101215.","productDescription":"101215, 7 p.","ipdsId":"IP-132131","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":489196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.softx.2022.101215","text":"Publisher Index Page"},{"id":409114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCann, Maile","contributorId":298807,"corporation":false,"usgs":false,"family":"McCann","given":"Maile","email":"","affiliations":[{"id":64688,"text":"Sonny Astani Department of Civil & Environmental Engineering University of Southern California","active":true,"usgs":false}],"preferred":false,"id":856486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Dylan L.","contributorId":187533,"corporation":false,"usgs":false,"family":"Anderson","given":"Dylan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":856487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":856488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bruder, Brittany","contributorId":298808,"corporation":false,"usgs":false,"family":"Bruder","given":"Brittany","email":"","affiliations":[{"id":64689,"text":"Coastal and Hydraulics Laboratory, US Army Engineer Research and Development Center, Kitty Hawk, NC","active":true,"usgs":false}],"preferred":false,"id":856489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bak, A. Spicer","contributorId":298809,"corporation":false,"usgs":false,"family":"Bak","given":"A.","email":"","middleInitial":"Spicer","affiliations":[{"id":64689,"text":"Coastal and Hydraulics Laboratory, US Army Engineer Research and Development Center, Kitty Hawk, NC","active":true,"usgs":false}],"preferred":false,"id":856490,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brodie, Katherine","contributorId":266146,"corporation":false,"usgs":false,"family":"Brodie","given":"Katherine","affiliations":[{"id":13502,"text":"US Army Corps of Engineers","active":true,"usgs":false}],"preferred":false,"id":856491,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237895,"text":"70237895 - 2022 - Klamath natural flow study, Upper Klamath Basin groundwater flow model","interactions":[],"lastModifiedDate":"2023-08-23T13:26:00.51571","indexId":"70237895","displayToPublicDate":"2022-11-03T09:13:58","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":21,"text":"Fact Sheet","active":false,"publicationSubtype":{"id":1}},"displayTitle":"Klamath Natural Flow Study, Upper Klamath Basin Groundwater Flow Model","title":"Klamath natural flow study, Upper Klamath Basin groundwater flow model","docAbstract":"<p>The purpose of the Upper Klamath Basin Groundwater Flow Model (UKBGFM) is to simulate groundwater conditions in the Upper Klamath Basin under historical and predevelopment conditions. The UKBGFM quantifies estimates of and changes in groundwater levels, storage, pumping, drainage flow to tile drains, evapotranspiration, and flow between the Upper Klamath Basin and neighboring basins. The quantifications of base flow to streams and seepage to and from lakes and reservoirs can be used as inputs to the RiverWare Mass Balance Model (Zagona and others, 2001), a companion model being developed as part of the Klamath Natural Flow Study (KNFS). </p>","language":"English","publisher":"U.S. Bureau of Reclamation","usgsCitation":"Traum, J.A., and Boyce, S.E., 2022, Klamath natural flow study, Upper Klamath Basin groundwater flow model: Fact Sheet, 2 p.","productDescription":"2 p.","ipdsId":"IP-145778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":418055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://www.usbr.gov/mp/kbao/docs/04-factsheet-gwmodeling-final.pdf"},{"id":418057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.54532325728275,\n              42.588031447169925\n            ],\n            [\n              -124.57092240453784,\n              42.588031447169925\n            ],\n            [\n              -124.57092240453784,\n              41.175\n            ],\n            [\n              -121.54532325728275,\n              41.175\n            ],\n            [\n              -121.54532325728275,\n              42.588031447169925\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Traum, Jonathan A. 0000-0002-4787-3680 jtraum@usgs.gov","orcid":"https://orcid.org/0000-0002-4787-3680","contributorId":4780,"corporation":false,"usgs":true,"family":"Traum","given":"Jonathan","email":"jtraum@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856126,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237966,"text":"ofr20221004 - 2022 - Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000","interactions":[],"lastModifiedDate":"2023-09-18T20:03:29.19242","indexId":"ofr20221004","displayToPublicDate":"2022-11-03T07:52:07","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":"2022-1004","displayTitle":"Spatial Extent of Seagrasses (<em>Zostera marina</em> and <em>Ruppia maritima</em>) along the Central Pacific Coast of Baja California, Mexico, 1999–2000","title":"Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000","docAbstract":"<p class=\"p1\">The seagrasses eelgrass (<i>Zostera marina</i>) and widgeongrass (<i>Ruppia maritima</i>) are prominent features of coastal lagoons along the Pacific coast of Baja California, Mexico, supporting a rich diversity of marine life. Yet little is known about their spatial distribution in this region. This is a concern because of declining trends in the abundance and distribution of seagrass in parts of northern Baja California and southern California. We used 7-band satellite imagery, 4-band digital multispectral videography, and 3-band color aerial photography to map the distribution of eelgrass and widgeongrass in six embayments along the central Pacific coast of Baja California. The total spatial extent of seagrass was estimated to be 42,697 hectares, of which about 70 percent was eelgrass. This seagrass was primarily lower in the intertidal than widgeongrass in all embayments. Eelgrass and widgeongrass composed the greatest proportion (47 percent) of the spatial extent in the two largest embayments, Lagunas Ojo de Liebre and San Ignacio, and these two embayments accounted for 85 percent of all seagrass in the study area. The native cordgrass (<i>Spartina foliosa</i>) and pickleweed (<i>Salicornia spp</i>.) were the predominate vegetation cover type of marshes in the three northern and three southern embayments, respectively. The three southern embayments contained mangrove (<i>Rhizophora </i>spp.) and the three northern embayments did not, thus marking the northern edge of mangroves along the Pacific coast of North America. This study establishes an embayment-wide baseline for continuing investigations and monitoring future changes in the spatial abundance of seagrasses in central Baja California.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., Morton, A., Markon, C.J., and Hogrefe, K.R., 2022, Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000: U.S. Geological Survey Open-File Report 2022–1004, 13 p., https://doi.org/10.3133/ofr20221004.","productDescription":"Report: vi, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128315","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409029,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (<em>Zostera marina</em>) and widgeongrass (<em>Ruppia maritima</em>) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409030,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (<em>Zostera marina</em>) distribution, Alaska and Baja California, Mexico"},{"id":409032,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1004/ofr20221004.XML"},{"id":409031,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1004/images"},{"id":409026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1004/coverthb.jpg"},{"id":409041,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221078","text":"OFR 2022-1078 —","description":"OFR 2022-1078","linkHelpText":"Abundance of eelgrass (<em>Zostera marina</em>) at key Black Brant (<em>Branta bernicla nigricans</em>) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409028,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221004/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1004"},{"id":409027,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1004/ofr20221004.pdf","text":"Report","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1004"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.34490212994275,\n              28.246325178662076\n            ],\n            [\n              -115.34490212994275,\n              26.352495017715754\n            ],\n            [\n              -111.76335916119284,\n              26.352495017715754\n            ],\n            [\n              -111.76335916119284,\n              28.246325178662076\n            ],\n            [\n              -115.34490212994275,\n              28.246325178662076\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>References Cited</li></ul>","publishedDate":"2022-11-03","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":856398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morton, Alexandra","contributorId":42323,"corporation":false,"usgs":true,"family":"Morton","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":856399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markon, Carl J. markon@usgs.gov","contributorId":2499,"corporation":false,"usgs":true,"family":"Markon","given":"Carl","email":"markon@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":856400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hogrefe, Kyle R. khogrefe@usgs.gov","contributorId":4264,"corporation":false,"usgs":true,"family":"Hogrefe","given":"Kyle","email":"khogrefe@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":856401,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238104,"text":"70238104 - 2022 - Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe","interactions":[],"lastModifiedDate":"2022-12-15T15:37:49.27015","indexId":"70238104","displayToPublicDate":"2022-11-03T07:25:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5803,"text":"Conservation Science and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Adjustments or complete withdrawal of livestock grazing are among the most common conservation actions in semiarid uplands, but outcomes can vary considerably with ecological context. Invasion by exotic annual grasses and the excessive wildfire they promote are increasing threats to semiarid shrub-steppe, and plant-community response to livestock exclusion in these areas may be complicated by the rapid colonization ability of invaders. We evaluated vegetation-community changes over 14-year interval (2007–2021) in a shrub-steppe landscape where a &gt;100-year history of livestock grazing had been terminated in 1996. Field surveys revealed that bare-soil exposure decreased &gt;20% over the 14 years owing to biomass accumulation, but this was primarily due to large increases in exotic annual “cheatgrass” (<i>Bromus tectorum</i>, +1.8-fold) and the litter it produces (+1.5-fold). Soil biocrusts increased 11.9% and perennial bunchgrasses increased 3% over the 14 years. These community changes varied at the patch scale and entailed inverse relationships of (1) both cheatgrass and biocrusts to plant-community basal cover, (2) cheatgrass to both biocrusts and perennial grasses, and (3) biocrusts to cheatgrass and litter. The spatiotemporal variability in vegetation constituted changes in plant-community states, according to cluster analysis. The modeled probability of a community transitioning to a cheatgrass state was (1) strongly and positively related to the initial (2007) cover of cheatgrass in hotspots where initial cheatgrass cover was &gt;20%, and (2) negatively related to biocrust cover where initial biocrust cover was &gt;4% of ground area. The decision space for this landscape can be framed as a shifting from acceptance towards resisting further degradation by removing livestock and their trampling of soil surfaces and utilization of perennial herbs. However, cheatgrass appears to be the most impactful agent of change and continued invasion appears imminent. Active restoration may help resist further degradation and direct change towards tolerable conditions.</p></div></div>","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/csp2.12838","usgsCitation":"Germino, M., Kluender, C.R., and Anthony, C.R., 2022, Plant community trajectories following livestock exclusion for conservation vary and hinge on initial invasion and soil-biocrust conditions in shrub steppe: Conservation Science and Practice, v. 4, no. 12, e12838, 14 p., https://doi.org/10.1111/csp2.12838.","productDescription":"e12838, 14 p.","ipdsId":"IP-138776","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":445949,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/csp2.12838","text":"Publisher Index Page"},{"id":435629,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SO99W8","text":"USGS data release","linkHelpText":"Vegetation and soil cover data for long-term monitoring plots within Browns Park National Wildlife Refuge, Colorado, USA"},{"id":409290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","county":"Moffat County","otherGeospatial":"Browns Park National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109.04917851176388,\n              40.831912228720284\n            ],\n            [\n              -109.0482710374729,\n              40.80650230407173\n            ],\n            [\n              -109.04010376885081,\n              40.802380858575475\n            ],\n            [\n              -109.02513044304374,\n              40.79001498646366\n            ],\n        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   [\n              -109.04917851176388,\n              40.831912228720284\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"4","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":856869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kluender, Chad Raymond 0000-0002-4108-4437","orcid":"https://orcid.org/0000-0002-4108-4437","contributorId":296077,"corporation":false,"usgs":true,"family":"Kluender","given":"Chad","email":"","middleInitial":"Raymond","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anthony, Christopher R. 0000-0003-0968-224X","orcid":"https://orcid.org/0000-0003-0968-224X","contributorId":296314,"corporation":false,"usgs":true,"family":"Anthony","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":856871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70237965,"text":"ofr20221078 - 2022 - Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012","interactions":[],"lastModifiedDate":"2023-09-18T20:02:25.588335","indexId":"ofr20221078","displayToPublicDate":"2022-11-03T07:10:46","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":"2022-1078","displayTitle":"Abundance of Eelgrass (<em>Zostera marina</em>) at Key Black Brant (<em>Branta bernicla nigricans</em>) Wintering Sites Along the Northern Pacific Coast of Baja California, Mexico, 1998–2012","title":"Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012","docAbstract":"<p class=\"p1\">Trends in the abundance and distribution of eelgrass (<i>Zostera marina</i>), the primary winter forage of black brant (<i>Branta bernicla nigricans</i>), was evaluated at three major wintering sites for black brant along the northern Pacific coast of Baja California, Mexico. This region of northwestern Mexico contains significant beds of eelgrass that were showing signs of decline, which may negatively affect the Pacific flyway population of black brant. Embayment-wide surveys of eelgrass were conducted at Bahia San Quintin (BSQ), Laguna Ojo de Liebre (LOL), and Laguna San Ignacio (LSI) between 1998 and 2012 to estimate baselines and trends in the distribution and abundance of this seagrass in Mexico. Eelgrass was the most abundant and frequently encountered seagrass in each site across survey years. Density and aboveground biomass of eelgrass was greater in BSQ than in LOL and LSI while abundance of widgeongrass (<i>Ruppia maritima</i>), a secondary source of food for brant, was greatest in LSI across survey years. Widgeongrass occurred higher in the intertidal zone than did eelgrass in all embayments, and both seagrasses generally shifted to lower water depths along a southward latitudinal gradient. A negative temporal trend in abundance of seagrasses was detected in BSQ that appeared linked to impacts of climate warming and an increase in macroalgae populations. Decreases in abundance of seagrasses were also detected in LOL and LSI, although long-term trends were less certain in LOL. Overall, declines in abundance of eelgrass in Baja California may be influencing the ongoing shift in the winter distribution of brant to areas north of the Mexican border.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221078","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., 2022, Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012: U.S. Geological Survey Open-File Report 2022–1078, 15 p., https://doi.org/10.3133/ofr20221078.","productDescription":"Report: vi, 15 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-135227","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409019,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (<em>Zostera marina</em>) distribution, Alaska and Baja California, Mexico"},{"id":409018,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (<em>Zostera marina</em>) and widgeongrass (<em>Ruppia maritima</em>) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409021,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.XML"},{"id":409020,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1078/images"},{"id":409042,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221004","text":"OFR 2022-1004 —","description":"OFR 2022-1004","linkHelpText":"Spatial extent of seagrasses (<em>Zostera marina</em> and <em>Ruppia maritima</em>) along the central Pacific coast of Baja California, Mexico, 1999–2000"},{"id":409015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1078/coverthb2.jpg"},{"id":409017,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221078/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1078"},{"id":409016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1078"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -115.34490212994275,\n              28.246325178662076\n            ],\n            [\n              -115.34490212994275,\n              26.352495017715754\n            ],\n            [\n              -111.76335916119284,\n              26.352495017715754\n            ],\n            [\n              -111.76335916119284,\n              28.246325178662076\n            ],\n            [\n              -115.34490212994275,\n              28.246325178662076\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>Conclusion</li><li>References Cited</li></ul>","publishedDate":"2022-11-03","noUsgsAuthors":false,"publicationDate":"2022-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":856397,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70238071,"text":"70238071 - 2022 - Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens","interactions":[],"lastModifiedDate":"2022-11-08T12:56:15.194903","indexId":"70238071","displayToPublicDate":"2022-11-03T06:49:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0085\">Evaluation of intramolecular isotope distributions within organic compounds can provide important insights into gas formation processes and structural properties of gas-generating precursors, such as kerogen, bitumen, and oil, in natural reservoirs. Until recently, little has been known about the intramolecular isotope distributions within kerogens. In this study, we conducted systematic pyrolysis experiments of gas generation from a lacustrine oil shale of the Eocene Green River Formation under hydrous and anhydrous conditions (equivalent maturity or Easy %R<sub>o</sub>: 0.76 to 3.27 at 310 to 480&nbsp;°C for 3 to 50&nbsp;days), measuring gas yields and compositions, as well as bulk and position-specific (PS) carbon isotope compositions. Gas generation processes were investigated in combination with kinetic Monte Carlo (kMC) simulations on a model Type I kerogen based on the chemical structures of oil shale of the Green River Formation. The comparison of our experimental results with kMC modelling indicates a series of β-scission, radical isomerization, and recombination reactions better represent the bulk isotope compositions of propane in the pyrolysis of the oil shale of the Green River Formation, but the ΔC<sub>c-t</sub><span>&nbsp;</span>(= δ<sup>13</sup>C<sub>cen</sub><span>&nbsp;</span>– δ<sup>13</sup>C<sub>ter</sub>) values of propane at Easy %R<sub>o</sub>&nbsp;&gt;&nbsp;1.5 can be better simulated by a simple combination of propyl groups with H radicals. Combining our previous works on marine shale of the Woodford Formation and Springfield Coal Member of the Carbondale Formation, PS carbon isotopes of propane indicate that in the lacustrine shales of the Green River Formation and the marine Woodford Shale, propane is sourced from C<img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\">C bond cleavage, while C<img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\">O bond cracking generates propane from coal at the initial kerogen cracking stage. At high maturity, the differences of late-stage propane production among the source rocks lead to the different bulk and PS C kinetic isotope effects of propane. Our findings suggest that the δ<sup>13</sup>C at the terminal position of propane precursors is likely up to 3.6‰ higher than at the central position in the Green River kerogen, while they are similar in the marine shale of Woodford Formation. In addition, the δ<sup>13</sup>C at the central position of propyl groups attached to heteroatom compounds is relatively more positive in the Springfield Coal Member of the Carbondale Formation than in Green River kerogen. A comparison of intramolecular C isotopes of propyl groups in the kerogens with their bulk δ<sup>13</sup>C, based on the PS δ<sup>13</sup>C of early-generated propane, contributes to our understanding of heterogeneities of isotopic structures of sedimentary organic matter.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104141","usgsCitation":"Li, X., Birdwell, J.E., and Horita, J., 2022, Bulk and intramolecular carbon isotopic compositions of hydrocarbon gases from laboratory pyrolysis of oil shale of the Green River Formation: Implications for isotope structures of kerogens: International Journal of Coal Geology, v. 264, 104141, 14 p., https://doi.org/10.1016/j.coal.2022.104141.","productDescription":"104141, 14 p.","ipdsId":"IP-142309","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":409228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"264","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Xiaoqiang","contributorId":298943,"corporation":false,"usgs":false,"family":"Li","given":"Xiaoqiang","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":856753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":856754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horita, Juske","contributorId":146205,"corporation":false,"usgs":false,"family":"Horita","given":"Juske","email":"","affiliations":[{"id":16625,"text":"Department of Geosciences, Texas Tech University, Lubbock, Texas","active":true,"usgs":false}],"preferred":false,"id":856755,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238002,"text":"70238002 - 2022 - Backpack electrofishing does not contribute to external signs of gas bubble trauma in sculpins","interactions":[],"lastModifiedDate":"2022-12-15T15:13:37.966307","indexId":"70238002","displayToPublicDate":"2022-11-02T17:07:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12812,"text":"Aquaculture, Fish and Fisheries","onlineIssn":"2693-8847","active":true,"publicationSubtype":{"id":10}},"title":"Backpack electrofishing does not contribute to external signs of gas bubble trauma in sculpins","docAbstract":"<p><span>We exposed prickly sculpin&nbsp;</span><i>Cottus asper</i><span>&nbsp;and reticulate sculpin&nbsp;</span><i>Cottus perplexus</i><span>&nbsp;to electroshock and sham treatments in a controlled laboratory setting to determine if backpack electrofishing contributed to or exacerbated external signs of gas bubble trauma (GBT) in fish exposed to elevated total dissolved gas (TDG) levels. Fish were exposed to 115, 120 and 125% TDG (measured as percent of saturation) for various amounts of time (24–144&nbsp;h) then subjected to a 5-s electroshock or sham treatment of no electroshock. Fish were examined to determine the incidence of GBT pre- and post-treatment, and all aspects (i.e., dorsal, ventral, left and right sides) of each fish were photographed. Across all TDG levels in all trials, no sculpin showed any change in GBT incidence following treatment. Analysis of GBT signs evident in photographs of 68 fish found no evidence of change in mean pre- and post-treatment gas bubble sizes in fish in any TDG trial, nor were any new gas bubbles found following treatment. We are aware of no physiological mechanism by which backpack electrofishing can cause GBT in sculpin, and as such, we believe using this gear should not increase GBT incidence rates in sculpin.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/aff2.81","usgsCitation":"Tiffan, K.F., and Eller, N.J., 2022, Backpack electrofishing does not contribute to external signs of gas bubble trauma in sculpins: Aquaculture, Fish and Fisheries, v. 2, no. 6, p. 572-577, https://doi.org/10.1002/aff2.81.","productDescription":"6 p.","startPage":"572","endPage":"577","ipdsId":"IP-138493","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":445954,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aff2.81","text":"Publisher Index Page"},{"id":409136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":220176,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eller, Nicole Joy 0000-0001-8760-8884","orcid":"https://orcid.org/0000-0001-8760-8884","contributorId":265130,"corporation":false,"usgs":true,"family":"Eller","given":"Nicole","email":"","middleInitial":"Joy","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":856526,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70256714,"text":"70256714 - 2022 - Availability of lesser prairie-chicken nesting habitat impairs restoration success","interactions":[],"lastModifiedDate":"2024-09-03T15:50:06.338446","indexId":"70256714","displayToPublicDate":"2022-11-02T10:44:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Availability of lesser prairie-chicken nesting habitat impairs restoration success","docAbstract":"<p><span>Regional populations of lesser prairie-chickens (</span><i>Tympanuchus pallidicinctus</i><span>) have been declining irregularly since the early 1900s (Jensen et al. 2000). Populations in the Sand Sagebrush Prairie Ecoregion of Kansas and Colorado, USA, have been experiencing declines during the last 2 decades. Ecoregion-wide declines included the Cimarron and Comanche National Grasslands in southwestern Kansas and southeastern Colorado, respectively, from which lesser prairie-chickens were nearly extirpated by 2016. In 2014, the United States Department of Agriculture (USDA)–Forest Service created a vegetation management plan to restore lesser prairie-chicken nesting habitat on the National Grasslands. We used management plan recommendations to evaluate available nesting habitat on National Grasslands and surrounding areas for 394 transmitter-marked lesser prairie-chickens translocated to the Sand Sagebrush Prairie Ecoregion during 2016–2019. We found that a small proportion of vegetation measurements met the USDA–Forest Service's 100% visual obstruction guidelines of 25.4 to 38.1 cm (Cimarron: 5.3–21.8% of observations among cover types; Comanche: 1.5–3.0%), and grass species with a high value for nesting were rare (Cimarron: 0.5–20.1% of observations within each cover type; Comanche: 1.5–3.0%). Lesser prairie-chickens selected for 2 of the 10 National Grasslands' cover types (shrubland state and warm season shortgrass state) during breeding season movements, but only shrubland state was selected for during nesting. Our results indicate that nesting habitat for lesser prairie-chickens is limited on Cimarron and Comanche National Grasslands. As private grassland was also avoided during nesting, lesser prairie-chickens in Baca and Morton counties are currently primarily relying on Conservation Reserve Program (CRP) grasslands to meet nesting habitat thresholds (Morton, KS: 17.7% CRP; Baca, CO: 16.6% CRP), which may be insufficient to sustain a viable population. Due to the impermanence of CRP, efforts to sustain local populations are likely to depend on increased improved lesser prairie-chicken nesting habitat on National Grasslands. Grazing strategies such as rest-rotation and year-long deferments may provide opportunities to restore lesser prairie-chicken habitat on sand sagebrush prairie.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1379","usgsCitation":"Berigan, L.A., Aulicky, C., Teige, E.C., Sullins, D., Haukos, D.A., Fricke, K.A., Reitz, J.H., Rossi, L.G., Schultz, K., and Ricketts, A., 2022, Availability of lesser prairie-chicken nesting habitat impairs restoration success: Wildlife Society Bulletin, v. 46, no. 5, e1379, 20 p., https://doi.org/10.1002/wsb.1379.","productDescription":"e1379, 20 p.","ipdsId":"IP-124181","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1379","text":"Publisher Index Page"},{"id":433411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Oklahoma, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.67738861641666,\n              32.42366747604686\n            ],\n            [\n              -101.99410350476236,\n              31.953220584250772\n            ],\n            [\n              -99.72460785351899,\n              34.75966422315135\n            ],\n            [\n              -97.12004323111174,\n              37.918001462360536\n            ],\n            [\n              -98.77719995504461,\n              39.82230052761457\n            ],\n            [\n              -102.81137263180054,\n              39.830766635473395\n            ],\n            [\n              -103.74257069017122,\n              38.89525754328761\n            ],\n            [\n              -103.0389680340239,\n              36.79263140774131\n            ],\n            [\n              -105.67738861641666,\n              32.42366747604686\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"46","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Berigan, Liam A.","contributorId":341138,"corporation":false,"usgs":false,"family":"Berigan","given":"Liam","email":"","middleInitial":"A.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aulicky, Carly S. 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