{"pageNumber":"90","pageRowStart":"2225","pageSize":"25","recordCount":46630,"records":[{"id":70250456,"text":"70250456 - 2023 - The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management","interactions":[],"lastModifiedDate":"2023-12-12T12:36:33.348716","indexId":"70250456","displayToPublicDate":"2023-12-10T06:34:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5490,"text":"Agricultural & Environmental Letters","onlineIssn":"2471-9625","active":true,"publicationSubtype":{"id":10}},"title":"The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management","docAbstract":"<div class=\"article-section__content en main\"><p>Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision-support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision-support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next-generation tools to support agroecosystem management through the 21st century.</p></div>","language":"English","publisher":"WIley","doi":"10.1002/ael2.20120","usgsCitation":"McCord, S.E., Webb, N.P., Bestelmeyer, B.T., Bonefont, K., Brehm, J.R., Brown, J.R., Courtright, E., Dietrich, C., Duniway, M.C., Edwards, B.L., Fraser, C., Herrick, J.E., Knight, A.C., Metz, L.J., Van Zee, J., and Tweedie, C.E., 2023, The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management: Agricultural & Environmental Letters, v. 8, no. 2, e20120, 11 p., https://doi.org/10.1002/ael2.20120.","productDescription":"e20120, 11 p.","ipdsId":"IP-153652","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":441444,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ael2.20120","text":"Publisher Index Page"},{"id":423431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"McCord, Sarah E.","contributorId":195931,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":889964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Nicholas P.","contributorId":195924,"corporation":false,"usgs":false,"family":"Webb","given":"Nicholas","email":"","middleInitial":"P.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":889965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bestelmeyer, Brandon T.","contributorId":26180,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":889966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonefont, Kristopher","contributorId":332302,"corporation":false,"usgs":false,"family":"Bonefont","given":"Kristopher","email":"","affiliations":[{"id":79445,"text":"USDA-ARS Jornada Experimental Range, PO Box 30003, MSC 3JER, Las Cruces, NM, 88003, USA","active":true,"usgs":false}],"preferred":false,"id":889967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brehm, Joseph R.","contributorId":332303,"corporation":false,"usgs":false,"family":"Brehm","given":"Joseph","email":"","middleInitial":"R.","affiliations":[{"id":79446,"text":"USDA-ARS Jornada Experimental Range, PO Box 30003, MSC 3JER, Las Cruces, NM, 88003, USA; New Mexico State University, PO Box 30003, MSC 3JER, Las Cruces, NM, 88003, USA","active":true,"usgs":false}],"preferred":false,"id":889968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Joel R.","contributorId":177880,"corporation":false,"usgs":false,"family":"Brown","given":"Joel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":889969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Courtright, Ericha M.","contributorId":169759,"corporation":false,"usgs":false,"family":"Courtright","given":"Ericha M.","affiliations":[{"id":25579,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":889970,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dietrich, Christopher","contributorId":200221,"corporation":false,"usgs":false,"family":"Dietrich","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":889971,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":889972,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Edwards, Brandon L.","contributorId":215510,"corporation":false,"usgs":false,"family":"Edwards","given":"Brandon","email":"","middleInitial":"L.","affiliations":[{"id":39270,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":889973,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fraser, Christopher","contributorId":332304,"corporation":false,"usgs":false,"family":"Fraser","given":"Christopher","email":"","affiliations":[{"id":79445,"text":"USDA-ARS Jornada Experimental Range, PO Box 30003, MSC 3JER, Las Cruces, NM, 88003, USA","active":true,"usgs":false}],"preferred":false,"id":889974,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":889975,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"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":889976,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Metz, Loretta J","contributorId":169771,"corporation":false,"usgs":false,"family":"Metz","given":"Loretta","email":"","middleInitial":"J","affiliations":[{"id":25587,"text":"USDA-NRCS, Resource Assessment Division, CEAP Modeling Team, Temple, TX 76502","active":true,"usgs":false}],"preferred":false,"id":889977,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Van Zee, Justin W.","contributorId":169758,"corporation":false,"usgs":false,"family":"Van Zee","given":"Justin W.","affiliations":[{"id":25579,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":889978,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tweedie, Craig E.","contributorId":200176,"corporation":false,"usgs":false,"family":"Tweedie","given":"Craig","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":889979,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
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Despite many negative consequences, barriers can serve to protect native species by limiting the spread of&nbsp;invasive species. For example, in the Laurentian Great Lakes, physical barriers have long been used to control invasive&nbsp;sea lamprey&nbsp;(</span><i>Petromyzon marinus</i><span>) populations by limiting access to potential upstream spawning and rearing habitat. Selective fish passage systems could solve this management trade-off, termed the “connectivity conundrum”, but must efficiently pass multiple native or desirable species while blocking invasive species. Designing such fish passage systems requires an understanding of the attribute dimensions of the fish community, specifically, the&nbsp;phenology, morphology, physiology, and behaviour of each species. Here, we describe the first comprehensive collection of sortable attributes associated with fish passage. The integrated database consists of 21 biological attributes that influence the movement and passage of 220 species in the Great Lakes, including native species, established non-native species, and unestablished but potentially invasive fishes. Data coverage varies with species, taxonomic orders, and attribute dimensions. Behavioural attributes were typically underrepresented in the literature, and the ecology of potential invaders was not well understood. The synthesis described herein is a critical step towards a holistic approach to fish passage design and may help to inform management actions related to population connectivity. The database is openly accessible online and is expected to be updated periodically.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.08.006","usgsCitation":"Benoit, D.M., Zielinski, D.P., Swanson, R.G., McLaughlin, R.L., Castro-Santos, T., Goodwin, R., Pratt, T.C., and Muir, A.M., 2023, FishPass sortable attribute database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Laurentian Great Lakes fishes: Journal of Great Lakes Research, v. 49, no. 6, 102229, 10 p., https://doi.org/10.1016/j.jglr.2023.08.006.","productDescription":"102229, 10 p.","ipdsId":"IP-152464","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":495384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2023.08.006","text":"Publisher Index 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G.","contributorId":360985,"corporation":false,"usgs":false,"family":"Swanson","given":"Reid","middleInitial":"G.","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":948077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McLaughlin, Robert L.","contributorId":360986,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Robert","middleInitial":"L.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":948078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":948079,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goodwin, R. Andrew 0000-0002-6846-0287","orcid":"https://orcid.org/0000-0002-6846-0287","contributorId":352492,"corporation":false,"usgs":false,"family":"Goodwin","given":"R. Andrew","affiliations":[{"id":37304,"text":"U.S. Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":948080,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pratt, Thomas C.","contributorId":360987,"corporation":false,"usgs":false,"family":"Pratt","given":"Thomas","middleInitial":"C.","affiliations":[{"id":86143,"text":"Great Lakes Laboratory for Fisheries and Aquatic Sciences","active":true,"usgs":false}],"preferred":false,"id":948081,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muir, Andrew M.","contributorId":360989,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew","middleInitial":"M.","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":948082,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70250907,"text":"70250907 - 2023 - Comprehensive assessment of macroinvertebrate community condition and sediment toxicity in the Eighteenmile Creek Area of Concern, New York, 2021","interactions":[],"lastModifiedDate":"2024-01-11T14:18:39.001249","indexId":"70250907","displayToPublicDate":"2023-12-09T08:13:41","publicationYear":"2023","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":"Comprehensive assessment of macroinvertebrate community condition and sediment toxicity in the Eighteenmile Creek Area of Concern, New York, 2021","docAbstract":"<p>The degradation of benthic communities (benthos) is one of four remaining beneficial use impairments (BUIs) in the Eighteenmile Creek Area of Concern (AOC), located on the south shore of Lake Ontario in New York. The historical rationale for listing this BUI as impaired relied heavily on inferred or expected impact to benthic communities based on elevated contaminant concentrations in bed sediments from past industrial and municipal discharges, hazardous-waste disposal, and pesticide usage. Previous assessments of macroinvertebrate community condition in the AOC have produced inconclusive results, and it remains unclear if contaminated sediments are impairing benthic communities. In 2021, a comprehensive assessment of macroinvertebrate community condition and sediment toxicity was conducted at eight sites in the AOC and six sites in a reference area on Oak Orchard Creek to determine if the removal criteria for this BUI have been met or if additional remedial measures are needed. The New York multi-metric index of biological integrity classified the mean community condition across AOC sites as slightly impacted, and 10-day toxicity tests with Chironomus dilutus and Hyalella azteca found no evidence of toxicity in AOC sediments. Equivalence testing indicated that community condition, and survival and growth of both test species, were not inferior in the AOC relative to the reference area. The weight of evidence from this study and other relevant datasets indicate that sediment contamination is not causing measurable impairment to benthic communities in the Eighteenmile Creek AOC.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.08.004","usgsCitation":"George, S.D., Baldigo, B., Collins, S.M., Clarke, D.B., and Duffy, B.T., 2023, Comprehensive assessment of macroinvertebrate community condition and sediment toxicity in the Eighteenmile Creek Area of Concern, New York, 2021: Journal of Great Lakes Research, v. 49, no. 6, 102227, 10 p., https://doi.org/10.1016/j.jglr.2023.08.004.","productDescription":"102227, 10 p.","ipdsId":"IP-151185","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":441447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2023.08.004","text":"Publisher Index Page"},{"id":424324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Eighteenmile Creek Area of Concern","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.76802247403678,\n              43.2530939352541\n            ],\n            [\n              -78.15600936774968,\n              43.2530939352541\n            ],\n            [\n              -78.15600936774968,\n              43.399677287114656\n            ],\n            [\n              -78.76802247403678,\n              43.399677287114656\n            ],\n            [\n              -78.76802247403678,\n              43.2530939352541\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":892003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Scott M.","contributorId":333123,"corporation":false,"usgs":false,"family":"Collins","given":"Scott","email":"","middleInitial":"M.","affiliations":[{"id":79737,"text":"Niagara County Soil and Water Conservation District","active":true,"usgs":false}],"preferred":false,"id":892004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clarke, David B.","contributorId":333124,"corporation":false,"usgs":false,"family":"Clarke","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":892005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duffy, Brian T.","contributorId":272971,"corporation":false,"usgs":false,"family":"Duffy","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":892006,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250791,"text":"70250791 - 2023 - Reproducibility starts at the source: R, Python, and Julia Packages for retrieving USGS hydrologic data","interactions":[],"lastModifiedDate":"2024-01-05T12:43:48.278129","indexId":"70250791","displayToPublicDate":"2023-12-09T06:41:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Reproducibility starts at the source: R, Python, and Julia Packages for retrieving USGS hydrologic data","docAbstract":"<div class=\"html-p\">Much of modern science takes place in a computational environment, and, increasingly, that environment is programmed using R, Python, or Julia. Furthermore, most scientific data now live on the cloud, so the first step in many workflows is to query a cloud database and load the response into a computational environment for further analysis. Thus, tools that facilitate programmatic data retrieval represent a critical component in reproducible scientific workflows. Earth science is no different in this regard. To fulfill that basic need, we developed R, Python, and Julia packages providing programmatic access to the U.S. Geological Survey’s National Water Information System database and the multi-agency Water Quality Portal. Together, these packages create a common interface for retrieving hydrologic data in the Jupyter ecosystem, which is widely used in water research, operations, and teaching. Source code, documentation, and tutorials for the packages are available on GitHub. Users can go there to learn, raise issues, or contribute improvements within a single platform, which helps foster better engagement and collaboration between data providers and their users.</div>","language":"English","publisher":"MDPI","doi":"10.3390/w15244236","usgsCitation":"Hodson, T.O., DeCicco, L.A., Hariharan, J.A., Stanish, L., Black, S., and Horsburgh, J., 2023, Reproducibility starts at the source: R, Python, and Julia Packages for retrieving USGS hydrologic data: Water, v. 15, no. 24, 4236, 10 p., https://doi.org/10.3390/w15244236.","productDescription":"4236, 10 p.","ipdsId":"IP-154080","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":441453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w15244236","text":"Publisher Index Page"},{"id":424128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"24","noUsgsAuthors":false,"publicationDate":"2023-12-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hodson, Timothy O. 0000-0003-0962-5130","orcid":"https://orcid.org/0000-0003-0962-5130","contributorId":78634,"corporation":false,"usgs":true,"family":"Hodson","given":"Timothy","email":"","middleInitial":"O.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":891480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":891481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hariharan, Jayaram Athreya 0000-0002-1343-193X","orcid":"https://orcid.org/0000-0002-1343-193X","contributorId":332949,"corporation":false,"usgs":true,"family":"Hariharan","given":"Jayaram","email":"","middleInitial":"Athreya","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":891482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanish, Lee 0000-0002-9775-6861","orcid":"https://orcid.org/0000-0002-9775-6861","contributorId":332950,"corporation":false,"usgs":true,"family":"Stanish","given":"Lee","email":"","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":891483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Black, Scott","contributorId":195434,"corporation":false,"usgs":false,"family":"Black","given":"Scott","email":"","affiliations":[{"id":34267,"text":"The Xerces Society for Invertebrate Conservation","active":true,"usgs":false}],"preferred":false,"id":891484,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Horsburgh, J. 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,{"id":70250417,"text":"70250417 - 2023 - Mapping high marsh and salt pannes/flats along the northern Gulf of Mexico coast","interactions":[],"lastModifiedDate":"2023-12-08T12:47:07.69081","indexId":"70250417","displayToPublicDate":"2023-12-08T06:39:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1753,"text":"Geocarto International","active":true,"publicationSubtype":{"id":10}},"title":"Mapping high marsh and salt pannes/flats along the northern Gulf of Mexico coast","docAbstract":"<p><span>Coastal wetlands are predicted to undergo extensive transformation due to climate and land use change. Baseline maps of coastal wetlands can be used to help assess changes. Found in the upper portion of the estuarine zone, high marsh and salt pannes/flats provide ecosystem goods and services and are particularly important to fish and wildlife. We developed the first map of high marsh and salt pannes/flats along the northern Gulf of Mexico using regional models that included spectral indices related to greenness and wetness from optical satellite imagery, elevation data, irregularly flooded wetland probability information, and synthetic aperture radar backscatter. We found the greatest relative coverage of high marsh along the Texas coast (30% to 65%) and the Florida Panhandle (40%), whereas the greatest relative coverage of salt pannes/flats was along the lower Texas coast (74%) and the middle Texas coast (15%). As part of this effort, we also developed a map that highlighted irregularly flooded wetlands dominated by&nbsp;</span><i>Juncus roemerianus</i><span>&nbsp;(black needlerush) for part of the study area. Both maps had an overall accuracy of around 80%. 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Conservancy","active":true,"usgs":false}],"preferred":false,"id":889858,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cox, James A.","contributorId":332277,"corporation":false,"usgs":false,"family":"Cox","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":33355,"text":"Tall Timbers Research Station and Land Conservancy","active":true,"usgs":false}],"preferred":false,"id":889859,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kappes, Peter J.","contributorId":275193,"corporation":false,"usgs":false,"family":"Kappes","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":889860,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nyman, John A.","contributorId":215127,"corporation":false,"usgs":false,"family":"Nyman","given":"John A.","affiliations":[{"id":39183,"text":"School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton","active":true,"usgs":false}],"preferred":false,"id":889861,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pitchford, Jonathan L.","contributorId":301251,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":889862,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70250541,"text":"70250541 - 2023 - Satellite telemetry reveals space use of diamondback terrapins","interactions":[],"lastModifiedDate":"2023-12-15T12:39:45.182424","indexId":"70250541","displayToPublicDate":"2023-12-08T06:36:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Satellite telemetry reveals space use of diamondback terrapins","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Movement and space use information of exploited and imperiled coastal species is critical to management and conservation actions. While satellite telemetry has been successfully used to document movements of marine turtles, the large tag sizes available have limited use on smaller turtle species. We used small Argos-based satellite tags to document movement patterns of diamondback terrapins (<i>Malaclemys terrapin</i>), the only estuarine turtle species in North America. Movement data from ten terrapins in St. Joseph Bay, Florida were gathered between July 13, 2018 and July 22, 2021. We estimated seasonal space use using the daily locations generated from a Bayesian hierarchical state-space model to calculate minimum convex polygons (95% MCP) and kernel density estimates (50% and 95% KDE). Mean tracking duration was 125&nbsp;days and mean home range size was 9.4 km<sup>2</sup><span>&nbsp;</span>(95% MCP) and 8.1 km<sup>2</sup><span>&nbsp;</span>(95% KDE). Seagrass habitat comprised 55.8% of all home ranges on average, whereas salt marsh comprised a mean of 3.0%. Mean elevation used by terrapins was −&nbsp;0.13&nbsp;m (95% MCP) and -0.35&nbsp;m (95% KDE). Satellite telemetry provided broad-scale spatiotemporal movement and space use data; however, Argos error produced considerable noise relative to true terrapin movements given their size, speed, and behavior. Terrapin home ranges were greater than previously reported and three of the ten terrapins exhibited repeated long-distance, directed movements within the bay. Small patches of salt marsh habitat were centralized within home ranges, despite comprising only a small percentage for each terrapin. Moreover, the percentage of salt marsh present in each core use area was positively correlated with terrapin mass. Although considered an estuarine species, seagrass habitat comprised a large portion of terrapin home ranges; however, our data did not provide the detail necessary to understand how terrapins were using this habitat. As northward-expanding mangroves continue to infringe upon salt marsh habitat, there is potential for negative impacts to terrapin populations across the northern Gulf of Mexico. As salt marsh habitat continues to be infringed upon by northward-expanding mangroves impacts to terrapins across the northern Gulf of Mexico.</p></div></div><div id=\"Sec1-section\" class=\"c-article-section\"><br></div>","language":"English","publisher":"Springer","doi":"10.1186/s40317-023-00354-x","usgsCitation":"Lamont, M., Price, M.E., and Catizone, D.J., 2023, Satellite telemetry reveals space use of diamondback terrapins: Animal Biotelemetry, v. 11, 42, 12 p., https://doi.org/10.1186/s40317-023-00354-x.","productDescription":"42, 12 p.","ipdsId":"IP-154462","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-023-00354-x","text":"Publisher Index Page"},{"id":423615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Joseph Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.54693854963955,\n              29.97115180299629\n            ],\n            [\n              -85.54693854963955,\n              29.62555557844732\n            ],\n            [\n              -85.19262946760846,\n              29.62555557844732\n            ],\n            [\n              -85.19262946760846,\n              29.97115180299629\n            ],\n            [\n              -85.54693854963955,\n              29.97115180299629\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":890326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Melissa E. 0000-0002-4276-0855 mprice@usgs.gov","orcid":"https://orcid.org/0000-0002-4276-0855","contributorId":5875,"corporation":false,"usgs":true,"family":"Price","given":"Melissa","email":"mprice@usgs.gov","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":890327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catizone, Daniel J. 0000-0002-7030-4208","orcid":"https://orcid.org/0000-0002-7030-4208","contributorId":248817,"corporation":false,"usgs":true,"family":"Catizone","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":890328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70251311,"text":"70251311 - 2023 - Understanding fatality patterns and sex ratios of Brazilian free-tailed bats (Tadarida brasiliensis) at wind energy facilities in western California and Texas","interactions":[],"lastModifiedDate":"2024-02-03T15:04:35.002663","indexId":"70251311","displayToPublicDate":"2023-12-07T09:01:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17148,"text":"PeerJ Life & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Understanding fatality patterns and sex ratios of Brazilian free-tailed bats (Tadarida brasiliensis) at wind energy facilities in western California and Texas","docAbstract":"<h2 class=\"heading\">Background</h2><p>Operation of wind turbines has resulted in collision fatalities for several bat species, and one proven method to reduce these fatalities is to limit wind turbine blade rotation (<i>i.e</i>., curtail turbines) when fatalities are expected to be highest. Implementation of curtailment can potentially be optimized by targeting times when females are most at risk, as the proportion of females limits the growth and stability of many bat populations. The Brazilian free-tailed bat (<i>Tadarida brasiliensis</i>) is the most common bat fatality at wind energy facilities in California and Texas, and yet there are few available data on the sex ratios of the carcasses that are found. Understanding the sex ratios of fatalities in California and Texas could aid in planning population conservation strategies such as informed curtailment.</p><h2 class=\"heading\">Methods</h2><p>We used PCR to determine the sex of bat carcasses collected from wind energy facilities during post-construction monitoring (PCM) studies in California and Texas. In California, we received samples from two locations within the Altamont Pass Wind Resource Area in Alameda County: Golden Hills (GH) (<i>n</i><span>&nbsp;</span>= 212) and Golden Hills North (GHN) (<i>n</i><span>&nbsp;</span>= 312). In Texas, we received samples from three wind energy facilities: Los Mirasoles (LM) (Hidalgo County and Starr County) (<i>n</i><span>&nbsp;</span>= 252), Los Vientos (LV) (Starr County) (<i>n</i><span>&nbsp;</span>= 568), and Wind Farm A (WFA) (San Patricio County and Bee County) (<i>n</i><span>&nbsp;</span>= 393).</p><h2 class=\"heading\">Results</h2><p>In California, the sex ratios of fatalities did not differ from 50:50, and the sex ratio remained stable over the survey years, but the seasonal timing of peak fatalities was inconsistent. In 2017 and 2018, fatalities peaked between September and October, whereas in 2019 and 2020 fatalities peaked between May and June. In Texas, sex ratios of fatalities varied between locations, with Los Vientos being female-skewed and Wind Farm A being male-skewed. The sex ratio of fatalities was also inconsistent over time. Lastly, for each location in Texas with multiple years studied, we observed a decrease in the proportion of female fatalities over time.</p><h2 class=\"heading\">Discussion</h2><p>We observed unexpected variation in the seasonal timing of peak fatalities in California and differences in the sex ratio of fatalities across time and facility location in Texas. In Texas, proximity to different roost types (bridge or cave) likely influenced the sex ratio of fatalities at wind energy facilities. Due to the inconsistencies in the timing of peak female fatalities, we were unable to determine an optimum curtailment period; however, there may be location-specific trends that warrant future investigation. More research should be done over the entirety of the bat active season to better understand these trends in Texas. In addition, standardization of PCM studies could assist future research efforts, enhance current monitoring efforts, and facilitate research on post-construction monitoring studies.</p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.16580","usgsCitation":"Licari, S., Hale, A., Weaver, S., Fritts, S., Katzner, T., Nelson, D.H., and Williams, D., 2023, Understanding fatality patterns and sex ratios of Brazilian free-tailed bats (Tadarida brasiliensis) at wind energy facilities in western California and Texas: PeerJ Life & Environment, v. 11, e16580, 24 p., https://doi.org/10.7717/peerj.16580.","productDescription":"e16580, 24 p.","ipdsId":"IP-156861","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":441463,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.16580","text":"Publisher Index 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Consulting","active":true,"usgs":false}],"preferred":false,"id":893995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritts, Sarah R.","contributorId":171485,"corporation":false,"usgs":false,"family":"Fritts","given":"Sarah R.","affiliations":[],"preferred":false,"id":893996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":893997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelson, David H.","contributorId":174918,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":893998,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Dean","contributorId":333825,"corporation":false,"usgs":false,"family":"Williams","given":"Dean","email":"","affiliations":[{"id":79989,"text":"TCU","active":true,"usgs":false}],"preferred":false,"id":893999,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250634,"text":"70250634 - 2023 - Chromosome-level genome assembly of the blacktail brush lizard, Urosaurus nigricaudus, reveals dosage compensation in an endemic lizard","interactions":[],"lastModifiedDate":"2023-12-21T12:48:14.338615","indexId":"70250634","displayToPublicDate":"2023-12-06T06:46:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3832,"text":"Genome Biology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Chromosome-level genome assembly of the blacktail brush lizard, Urosaurus nigricaudus, reveals dosage compensation in an endemic lizard","docAbstract":"<p class=\"chapter-para\"><i>Urosaurus nigricaudus</i><span>&nbsp;</span>is a phrynosomatid lizard endemic to the Baja California Peninsula in Mexico. This work presents a chromosome-level genome assembly and annotation from a male individual. We used PacBio long reads and HiRise scaffolding to generate a high-quality genomic assembly of 1.87 Gb distributed in 327 scaffolds, with an N50 of 279 Mb and an L50 of 3. Approximately 98.4% of the genome is contained in 14 scaffolds, with 6 large scaffolds (334–127 Mb) representing macrochromosomes and 8 small scaffolds (63–22 Mb) representing microchromosomes. Using standard gene modeling and transcriptomic data, we predicted 17,902 protein-coding genes on the genome. The repeat content is characterized by a large proportion of long interspersed nuclear elements that are relatively old. Synteny analysis revealed some microchromosomes with high repeat content are more prone to rearrangements but that both macro- and microchromosomes are well conserved across reptiles. We identified scaffold 14 as the X chromosome. This microchromosome presents perfect dosage compensation where the single X of males has the same expression levels as two X chromosomes in females. Finally, we estimated the effective population size for<span>&nbsp;</span><i>U. nigricaudus</i><span>&nbsp;</span>was extremely low, which may reflect a reduction in polymorphism related to it becoming a peninsular endemic.</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gbe/evad210","usgsCitation":"Davalos-Dehullu, E., Baty, S.M., Fisher, R., Scott, P.A., Dolby, G.A., Munguia-Vega, A., and Cortez, D., 2023, Chromosome-level genome assembly of the blacktail brush lizard, Urosaurus nigricaudus, reveals dosage compensation in an endemic lizard: Genome Biology and Evolution, v. 15, no. 12, evad210, 14 p., https://doi.org/10.1093/gbe/evad210.","productDescription":"evad210, 14 p.","ipdsId":"IP-159626","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gbe/evad210","text":"Publisher Index Page"},{"id":423832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Davalos-Dehullu, Elizabeth","contributorId":332610,"corporation":false,"usgs":false,"family":"Davalos-Dehullu","given":"Elizabeth","email":"","affiliations":[{"id":79515,"text":"Centro de Ciencias Genómicas, UNAM, Mexico","active":true,"usgs":false}],"preferred":false,"id":890659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baty, Sarah M.","contributorId":332611,"corporation":false,"usgs":false,"family":"Baty","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":890660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":890661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scott, Peter A.","contributorId":258813,"corporation":false,"usgs":false,"family":"Scott","given":"Peter","email":"","middleInitial":"A.","affiliations":[{"id":52299,"text":"Dept of Ecology and Evolutionary Biology & La Kretz Center for Calif Conservation Science, Institute of the Environ & Sustainability, UCLA, 90095; West Texas A&M Univ, Dept of Life, Earth, and Environ Sciences. Canyon, Texas 79016","active":true,"usgs":false}],"preferred":false,"id":890662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dolby, Greer A. 0000-0002-5923-0690","orcid":"https://orcid.org/0000-0002-5923-0690","contributorId":222726,"corporation":false,"usgs":false,"family":"Dolby","given":"Greer","email":"","middleInitial":"A.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":890663,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munguia-Vega, Adrian","contributorId":264559,"corporation":false,"usgs":false,"family":"Munguia-Vega","given":"Adrian","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":890664,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cortez, Diego","contributorId":332612,"corporation":false,"usgs":false,"family":"Cortez","given":"Diego","email":"","affiliations":[{"id":79515,"text":"Centro de Ciencias Genómicas, UNAM, Mexico","active":true,"usgs":false}],"preferred":false,"id":890665,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250930,"text":"70250930 - 2023 - A review of natural and managed revegetation responses in two de-watered reservoirs after large dam removals on the Elwha River, Washington, USA","interactions":[],"lastModifiedDate":"2024-01-12T13:41:54.607074","indexId":"70250930","displayToPublicDate":"2023-12-05T07:38:30","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"A review of natural and managed revegetation responses in two de-watered reservoirs after large dam removals on the Elwha River, Washington, USA","docAbstract":"<div class=\"JournalAbstract\"><p>Large dam removals are increasing in frequency and the response of natural and managed revegetation is a critical consideration for managed restoration of dewatered reservoir landscapes post dam removal. The removal of two large dams on the Elwha River in 2011-2014 provides insight into reservoir revegetation. We review literature and datasets from 2012 through 2018, 1-6 years since reservoir dewatering, to compare pre-dam removal predictions on the Elwha to post-dam removal of natural revegetation, managed revegetation effects and invasive non-native vegetation response. Pre-dam removal hypotheses about natural revegetation did not predict species performance on reservoir sediments, seed rain patterns, or seed bank response. Sediment texture and landform affected multiple aspects of revegetation, including vegetation cover, species richness, woody stem densities and species composition. Reservoir drawdown timing influenced species composition and seedling densities. Predictions about managed revegetation effects were mixed. Planting trees and shrubs did not accelerate woody cover but did increase species richness. Seeding reduced non-native vegetation frequency and species richness, had no effect on vegetation cover on fine sediments, but increased vegetation cover on coarse sediments. Planting trees and shrubs during drawdown appeared to result in higher survival rates compared to plantings installed 1+ years post drawdown. Seeding<span>&nbsp;</span><i>Lupinus rivularis</i><span>&nbsp;</span>(riverbank lupine) on coarse sediments was successful and increased foliar nitrogen in planted conifers. Invasive non-native vegetation was correctly predicted to be more abundant in the Aldwell reservoir but did not preclude native species establishment in either reservoir, likely due to rapid establishment of native species and robust management that occurred before, during and after dam removal.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.1268969","usgsCitation":"Chenoweth, J., Shafroth, P., Brown, R.L., Helfield, J.M., Bauman, J.M., Cendejas-Zarelli, S., Werner, C.M., Schuster, J.L., and Morgan, O.A., 2023, A review of natural and managed revegetation responses in two de-watered reservoirs after large dam removals on the Elwha River, Washington, USA: Frontiers in Ecology and Evolution, v. 11, 1268969, 15 p., https://doi.org/10.3389/fevo.2023.1268969.","productDescription":"1268969, 15 p.","ipdsId":"IP-153783","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":441473,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1268969","text":"Publisher Index Page"},{"id":424375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.84520392809796,\n              48.219529839093354\n            ],\n            [\n              -123.84520392809796,\n              47.45073186245261\n            ],\n            [\n              -123.2272229710666,\n              47.45073186245261\n            ],\n            [\n              -123.2272229710666,\n              48.219529839093354\n            ],\n            [\n              -123.84520392809796,\n              48.219529839093354\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Chenoweth, Joshua","contributorId":333248,"corporation":false,"usgs":false,"family":"Chenoweth","given":"Joshua","affiliations":[{"id":38097,"text":"Yurok Tribe","active":true,"usgs":false}],"preferred":false,"id":892255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":892256,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Rebecca L.","contributorId":290763,"corporation":false,"usgs":false,"family":"Brown","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":36876,"text":"Eastern Washington University","active":true,"usgs":false}],"preferred":false,"id":892257,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helfield, James M.","contributorId":333249,"corporation":false,"usgs":false,"family":"Helfield","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":892258,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauman, Jenise M.","contributorId":333250,"corporation":false,"usgs":false,"family":"Bauman","given":"Jenise","email":"","middleInitial":"M.","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":892259,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cendejas-Zarelli, Sara","contributorId":257040,"corporation":false,"usgs":false,"family":"Cendejas-Zarelli","given":"Sara","email":"","affiliations":[{"id":39680,"text":"Lower Elwha Klallam Tribe","active":true,"usgs":false}],"preferred":false,"id":892260,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Werner, Chhaya M.","contributorId":333251,"corporation":false,"usgs":false,"family":"Werner","given":"Chhaya","email":"","middleInitial":"M.","affiliations":[{"id":41707,"text":"Southern Oregon University","active":true,"usgs":false}],"preferred":false,"id":892261,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schuster, Jarrett L.","contributorId":333252,"corporation":false,"usgs":false,"family":"Schuster","given":"Jarrett","email":"","middleInitial":"L.","affiliations":[{"id":36876,"text":"Eastern Washington University","active":true,"usgs":false}],"preferred":false,"id":892262,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morgan, Olivia A.","contributorId":333253,"corporation":false,"usgs":false,"family":"Morgan","given":"Olivia","email":"","middleInitial":"A.","affiliations":[{"id":36876,"text":"Eastern Washington University","active":true,"usgs":false}],"preferred":false,"id":892263,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250339,"text":"70250339 - 2023 - An interoperability strategy for the next generation of SEEA accounting","interactions":[],"lastModifiedDate":"2023-12-05T14:44:39.985748","indexId":"70250339","displayToPublicDate":"2023-12-04T08:31:51","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"An interoperability strategy for the next generation of SEEA accounting","docAbstract":"The System of Environmental-Economic Accounting (SEEA) is a set of international environmental-economic standards, adopted by the UN Statistical Commission in 2012 (SEEA Central Framework) and 2021 (SEEA Ecosystem Accounting); the latter in particular requires the integration of large and diverse data streams. These include geospatial and other data sources, which have proven challenging for some National Statistical Offices (NSOs) to implement. Although a variety of ecosystem service modelling platforms have been built over the last 15 years to meet various user demands, they often duplicate efforts, rely on data that are siloed, and rarely effectively reuse the knowledge gained from past modelling efforts. \n\nBy making the data and models that underlie SEEA interoperable, NSOs and the scientific community can advance the accessibility, speed, quality, and transparency of SEEA accounts by making it possible to rapidly integrate and share new scientific data and models. Doing so requires an understanding of the benefits of interoperability, the costs of the status quo, and concrete pathways toward community-endorsed approaches for interoperability. The ARIES Network, which powers the ARIES for SEEA Explorer web application, offers such a path toward interoperability, providing substantial benefits to NSOs and scientific and policy communities.","language":"English","publisher":"Basque Center for Climate Change","usgsCitation":"Villa, F., Balbi, S., Bagstad, K.J., and Bulckaen, A., 2023, An interoperability strategy for the next generation of SEEA accounting, 14 p.","productDescription":"14 p.","ipdsId":"IP-153533","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":423242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423213,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.bc3research.org/index.php?option=com_wpapers&task=showdetails&idwpaper=108&Itemid=279"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":889507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":889508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":889509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bulckaen, Alessio","contributorId":332129,"corporation":false,"usgs":false,"family":"Bulckaen","given":"Alessio","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":889510,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70251890,"text":"70251890 - 2023 - Monitoring interdecadal coastal change along dissipative beaches via satellite imagery at regional scale","interactions":[],"lastModifiedDate":"2024-03-05T12:43:10.38955","indexId":"70251890","displayToPublicDate":"2023-12-04T06:40:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13436,"text":"Coastal Futures","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring interdecadal coastal change along dissipative beaches via satellite imagery at regional scale","docAbstract":"<div class=\"abstract-content\"><div class=\"abstract\" data-abstract-type=\"normal\"><p>Coastal morphological changes can be assessed using shoreline position observations from space. However, satellite-derived waterline (SDW) and shoreline (SDS; SDW corrected for hydrodynamic contributions and outliers) detection methods are subject to several sources of uncertainty and inaccuracy. We extracted high-spatiotemporal-resolution (~50&nbsp;m-monthly) time series of mean high water shoreline position along the Columbia River Littoral Cell (CRLC), located on the US Pacific Northwest coast, from Landsat missions (1984–2021). We examined the accuracy of the SDS time series along the mesotidal, mildly sloping, high-energy wave climate and dissipative beaches of the CRLC by validating them against 20&nbsp;years of quarterly<span>&nbsp;</span><span class=\"italic\">in situ</span><span>&nbsp;</span>beach elevation profiles. We found that the accuracy of the SDS time series heavily depends on the capability to identify and remove outliers and correct the biases stemming from tides and wave runup. However, we show that only correcting the SDW data for outliers is sufficient to accurately measure shoreline change trends along the CRLC. Ultimately, the SDS change trends show strong agreement with<span>&nbsp;</span><span class=\"italic\">in situ</span><span>&nbsp;</span>data, facilitating the spatiotemporal analysis of coastal change and highlighting an overall accretion signal along the CRLC during the past four decades.</p></div></div>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/cft.2023.30","usgsCitation":"Graffin, M., Taherkhani, M., Leung, M., Vitousek, S., Kaminsky, G., and Ruggiero, P., 2023, Monitoring interdecadal coastal change along dissipative beaches via satellite imagery at regional scale: Coastal Futures, v. 1, e42, 14 p., https://doi.org/10.1017/cft.2023.30.","productDescription":"e42, 14 p.","ipdsId":"IP-153838","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":441484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/cft.2023.30","text":"Publisher Index Page"},{"id":426310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -127.68460964603779,\n              41.83307709136193\n            ],\n            [\n              -118.89554714603788,\n              41.83307709136193\n            ],\n            [\n              -118.89554714603788,\n              49.43628341268192\n            ],\n            [\n              -127.68460964603779,\n              49.43628341268192\n            ],\n            [\n              -127.68460964603779,\n              41.83307709136193\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"1","noUsgsAuthors":false,"publicationDate":"2023-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Graffin, Marcan","contributorId":334554,"corporation":false,"usgs":false,"family":"Graffin","given":"Marcan","email":"","affiliations":[{"id":80177,"text":"LEGOS, Toulouse University, Lab’OT","active":true,"usgs":false}],"preferred":false,"id":895925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taherkhani, Mohsen","contributorId":334555,"corporation":false,"usgs":false,"family":"Taherkhani","given":"Mohsen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":895926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leung, Meredith","contributorId":334556,"corporation":false,"usgs":false,"family":"Leung","given":"Meredith","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":895927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":895928,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaminsky, George","contributorId":334557,"corporation":false,"usgs":false,"family":"Kaminsky","given":"George","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":895929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruggiero, Peter","contributorId":334558,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":895930,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70255197,"text":"70255197 - 2023 - Leveraging angler effort to inform fisheries management: Using harvest and harvest rate to estimate abundance of White Sturgeon","interactions":[],"lastModifiedDate":"2024-06-13T15:57:16.479341","indexId":"70255197","displayToPublicDate":"2023-12-01T10:53:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging angler effort to inform fisheries management: Using harvest and harvest rate to estimate abundance of White Sturgeon","docAbstract":"<p><span>Traditional methods for estimating abundance of fish populations are not feasible in some systems due to complex population structure and constraints on sampling effort. Lincoln’s estimator provides a technique that uses harvest and harvest rate to estimate abundance. Using angler catch data allows assumptions of the estimator to be addressed without relying on methods that could be prohibitively field-intensive or costly. Historic estimates of White Sturgeon&nbsp;</span><i>Acipenser transmontanus</i><span>&nbsp;abundance in the Sacramento–San Joaquin River basin have been obtained using mark–recapture methods; however, White Sturgeon population characteristics often cause violations of model assumptions, such as population closure and independent capture probabilities. We developed a version of Lincoln’s estimator using a joint likelihood, estimated abundance of White Sturgeon in the Sacramento–San Joaquin River basin in 2015 using this method and empirical data and assessed accuracy and precision of estimates in a simulation study. Estimating abundance using harvest and harvest rate, as represented by our model framework, has the potential to be precise and accurate. The joint likelihood–based approach fitted using Bayesian methods is advantageous because it includes all sources of variation in a single model. Precision of abundance estimates was low with application of the model to White Sturgeon in the Sacramento–San Joaquin River basin and to similar conditions in a simulated dataset. Using simulation, precision and accuracy increased with increases in the number of high-reward and standard tags released, tag reporting rate, tag retention rate, and harvest rate. Results demonstrate potential sources of error when using this approach and suggest that increasing the number of tagged fish and tag reporting rate are potential actions to improve precision and accuracy of abundance estimates of the model.</span></p>","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-22-057","usgsCitation":"Ulaski, M., McCormick, J., Quist, M.C., and Jackson, Z., 2023, Leveraging angler effort to inform fisheries management: Using harvest and harvest rate to estimate abundance of White Sturgeon: Journal of Fish and Wildlife Management, v. 14, no. 2, p. 324-336, https://doi.org/10.3996/JFWM-22-057.","productDescription":"13 p.","startPage":"324","endPage":"336","ipdsId":"IP-132349","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":441490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-22-057","text":"Publisher Index Page"},{"id":430146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.73722335339393,\n              38.33070681831987\n            ],\n            [\n              -122.73722335339393,\n              37.37437014467528\n            ],\n            [\n              -121.27664864102258,\n              37.37437014467528\n            ],\n            [\n              -121.27664864102258,\n              38.33070681831987\n            ],\n            [\n              -122.73722335339393,\n              38.33070681831987\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ulaski, Marta","contributorId":280108,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":903714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Joshua","contributorId":337819,"corporation":false,"usgs":false,"family":"McCormick","given":"Joshua","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":903715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary","contributorId":338597,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":903717,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70256468,"text":"70256468 - 2023 - Evidence of a load-lightening helper effect in Florida Scrub-Jays: Implications for translocation","interactions":[],"lastModifiedDate":"2024-08-06T15:54:31.101349","indexId":"70256468","displayToPublicDate":"2023-12-01T10:47:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Evidence of a load-lightening helper effect in Florida Scrub-Jays: Implications for translocation","docAbstract":"<p><span>The Florida Scrub-Jay (</span><i>Aphelocoma coerulescens</i><span>) is an imperiled cooperatively breeding species endemic to Florida scrub habitats. Translocation of non-reproductive helpers has been proposed as a conservation tool to increase population size and connectivity. However, the potential consequences of helper removal on the source population remain unclear because the benefits provided by helpers are complex and not consistently observed. We used nest monitoring and nest camera data to examine the effects of helpers on provisioning rates, nestling mass, nest survival, and productivity for 111 family groups at Ocala National Forest, which supports the largest remaining population of Florida Scrub-Jays. In groups with helpers, male breeders and helpers provisioned nestlings at higher rates than did female breeders. In contrast, provisioning rate of female breeders was reduced by half in groups with helpers compared to groups without helpers, revealing a load-lightening helper effect in this population. The compensatory benefit of helpers on maternal provisioning rates in this study may have easily been overlooked without the use of nest cameras. Helpers provisioned less and nestling mass was lower in 2019 than 2018. Helpers did not influence nestling mass, nest survival, or nest productivity, suggesting that the effect of helpers on these metrics is either minimal or masked by other environmental factors. Future study is needed to understand how indirect helper benefits may affect female breeder survival and future productivity. In the meantime, the load-lightening effect of helpers on maternal provisioning and its potential effect on the donor population should be acknowledged when evaluating the net benefits of future translocation projects proposing the removal of helpers.</span></p>","language":"English","publisher":"Resilience Alliance","doi":"10.5751/ACE-02552-180217","usgsCitation":"Cardas, A., Ragheb, E.H., Miller, K., and Powell, A., 2023, Evidence of a load-lightening helper effect in Florida Scrub-Jays: Implications for translocation, v. 18, no. 2, 17, 15 p., https://doi.org/10.5751/ACE-02552-180217.","productDescription":"17, 15 p.","ipdsId":"IP-154615","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":441492,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-02552-180217","text":"Publisher Index Page"},{"id":432290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Ocala National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.98188458377028,\n              29.47665328838552\n            ],\n            [\n              -81.87527572210423,\n              28.955339743537138\n            ],\n            [\n              -81.60364218416092,\n              28.968118511641634\n            ],\n            [\n              -81.6211669285447,\n              29.47665328838552\n            ],\n            [\n              -81.98188458377028,\n              29.47665328838552\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cardas, Alexis","contributorId":340744,"corporation":false,"usgs":false,"family":"Cardas","given":"Alexis","email":"","affiliations":[{"id":81657,"text":"Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":907505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ragheb, Erin Hewett","contributorId":270650,"corporation":false,"usgs":false,"family":"Ragheb","given":"Erin","email":"","middleInitial":"Hewett","affiliations":[],"preferred":false,"id":907506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Karl E.","contributorId":20280,"corporation":false,"usgs":true,"family":"Miller","given":"Karl E.","affiliations":[],"preferred":false,"id":907507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":907508,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70260942,"text":"70260942 - 2023 - Assessment of a new GeoAI foundation model for floodinundation mapping","interactions":[],"lastModifiedDate":"2024-11-18T16:40:32.912016","indexId":"70260942","displayToPublicDate":"2023-12-01T10:26:12","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessment of a new GeoAI foundation model for floodinundation mapping","docAbstract":"Vision foundation models are a new frontier in GeoAI research because of their potential to enable powerful image analysis by analyzing and extracting important image features from vast amounts of geospatial data. This paper evaluates the performance of the first-of-its-kind geospatial foundation model, IBM-NASA’s Prithvi, to support a crucial geospatial analysis task: flood inundation mapping. This model is compared with popular convolutional neural networks and vision transformer-based architectures regarding mapping accuracy for flooded areas. A benchmark dataset, Sen1Floods11, is used in the experiments, and the models' predictability, generalizability, and transferability are evaluated based on both validation datasets and datasets completely unseen by the model. Results show the impressive transferability of the Prithvi model, highlighting its performance advantages in segmenting flooded areas in previously unseen regions. The findings also suggest areas for improvement for the Prithvi model in adopting multi-scale representation learning, developing more end-to-end pipelines for high-level image analysis tasks, and offering more flexibility in allowable input data bands.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI '23)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI '23)","conferenceDate":"November 13, 2023","conferenceLocation":"Hamburg Germany","language":"English","publisher":"Association for Computing Machinery","doi":"10.1145/3615886.3627747","usgsCitation":"Li, W., Lee, H., Wang, S., Hsu, C., and Arundel, S., 2023, Assessment of a new GeoAI foundation model for floodinundation mapping, <i>in</i> Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI '23), Hamburg Germany, November 13, 2023, p. 102-109, https://doi.org/10.1145/3615886.3627747.","productDescription":"8 p.","startPage":"102","endPage":"109","ipdsId":"IP-157614","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":467071,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/2309.14500","text":"External Repository"},{"id":464232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Wenwen 0000-0003-2237-9499","orcid":"https://orcid.org/0000-0003-2237-9499","contributorId":219356,"corporation":false,"usgs":false,"family":"Li","given":"Wenwen","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":918647,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Hyunho","contributorId":346310,"corporation":false,"usgs":false,"family":"Lee","given":"Hyunho","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":918648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Sizhe","contributorId":242975,"corporation":false,"usgs":false,"family":"Wang","given":"Sizhe","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":918649,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hsu, Chia-Yu","contributorId":302720,"corporation":false,"usgs":false,"family":"Hsu","given":"Chia-Yu","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":918650,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":918651,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259400,"text":"70259400 - 2023 - A proposed methodology for conducting threats assessments within the Great Lakes Coregonines restoration framework","interactions":[],"lastModifiedDate":"2024-10-07T15:11:26.345198","indexId":"70259400","displayToPublicDate":"2023-12-01T10:02:12","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"A proposed methodology for conducting threats assessments within the Great Lakes Coregonines restoration framework","docAbstract":"<p>This document serves to fulfill the Coregonine Threats Assessment Science Team’s charge of providing a written recommendation for a methodology to conduct threats assessments for Great Lakes coregonines within the Coregonine Restoration Framework (CRF). Through a series of team meetings that included presentations by experts on five candidate threats assessment frameworks followed by structured deliberations, we came to consensus to recommend the threats assessment framework used by Fisheries and Oceans Canada under Canada’s Species at Risk Act, with three modifications: (1) a conceptual modeling step, (2) the use of a “point spreading” approach to incorporate uncertainty when scoring threats, and (3) the use of a modified Delphi or “estimate-talk-estimate” approach when scoring key elements in the assessment. We recommend that this approach be applied to the spatial units delineated by the CRF Resolve Taxonomy and Gap Analysis science teams. In brief, the assessment process includes providing background information on the spatial unit and threats under assessment, constructing a conceptual model linking threats to key processes and vital rates, and scoring or ranking threats across six elements: likelihood of occurrence, level of impact, strength of evidence, unit-level threat occurrence, unit-level threat frequency, and unit-level threat extent. We provide detailed instructions for completing each step of the assessment and generating associated results, with particular attention paid to our suggested modifications. </p><p>The Coregonine Threats Assessment Science Team also conducted two test runs to assess the applicability and effectiveness of our recommended framework for Great Lakes coregonine populations and their threats. We conducted these test runs on two examples of Great Lakes coregonines that represented two extremes of data availability, as well as two different management contexts. We chose Kiyi (Coregonus kiyi) in Lake Ontario as an example of a data-poor, extirpated population, and we chose Cisco (Coregonus artedi) in Lake Superior as an example of a data-rich, extant population. We provide the results of these test runs in Appendices 1-2. We also describe the lessons we learned from these test runs throughout this document and highlighted them in the “Recommendations for avoiding challenges during application” section.</p>","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Honsey, A.E., Smith, D.R., Bronte, C.R., Cook, A., Drake, D.A., Gorsky, D., Johnson, T., Mandrak, N.E., Roberts, J., and Sitar, S.P., 2023, A proposed methodology for conducting threats assessments within the Great Lakes Coregonines restoration framework, 67 p.","productDescription":"67 p.","ipdsId":"IP-170470","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":462644,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.greatlakesciscoes.org/restoration-framework/planning","linkFileType":{"id":5,"text":"html"}},{"id":462665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Honsey, Andrew Edgar 0000-0001-7535-1321","orcid":"https://orcid.org/0000-0001-7535-1321","contributorId":295468,"corporation":false,"usgs":true,"family":"Honsey","given":"Andrew","email":"","middleInitial":"Edgar","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":915155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":915156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bronte, Charles R.","contributorId":190727,"corporation":false,"usgs":false,"family":"Bronte","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":915157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Andy","contributorId":344968,"corporation":false,"usgs":false,"family":"Cook","given":"Andy","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":915158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drake, D. Andrew R.","contributorId":272033,"corporation":false,"usgs":false,"family":"Drake","given":"D.","email":"","middleInitial":"Andrew R.","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":915159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gorsky, Dimitry","contributorId":251650,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitry","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":915160,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Timothy B.","contributorId":251690,"corporation":false,"usgs":false,"family":"Johnson","given":"Timothy B.","affiliations":[{"id":50374,"text":"Ontario Ministry of Natural Resources and Forests (OMNRF)","active":true,"usgs":false}],"preferred":false,"id":915161,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mandrak, Nicholas E.","contributorId":177869,"corporation":false,"usgs":false,"family":"Mandrak","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":915162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":915163,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sitar, Shawn P.","contributorId":181529,"corporation":false,"usgs":false,"family":"Sitar","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":915164,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70250242,"text":"dr1183 - 2023 - An inventory of three-dimensional geologic models—U.S. Geological Survey, 2004–22","interactions":[],"lastModifiedDate":"2026-02-04T20:17:58.789811","indexId":"dr1183","displayToPublicDate":"2023-12-01T10:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1183","displayTitle":"An Inventory of Three-Dimensional Geologic Models—U.S. Geological Survey, 2004–22","title":"An inventory of three-dimensional geologic models—U.S. Geological Survey, 2004–22","docAbstract":"<p>A database of spatial footprints and characteristics of three-dimensional geological models that were constructed by the U.S. Geological Survey between 2004 and 2022 was compiled as part of ongoing development of subsurface geologic information by the USGS National Cooperative Geologic Mapping Program. 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           37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              ],\n              [\n                -124.17886,\n                41.14202\n              ],\n              [\n                -124.2137,\n                41.99964\n              ],\n              [\n                -124.53284,\n                42.76599\n              ],\n              [\n                -124.14214,\n                43.70838\n              ],\n              [\n                -124.02053,\n                44.6159\n              ],\n              [\n                -123.89893,\n                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 -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/geosciences-and-environmental-change-science-center/\" data-mce-href=\"https://www.usgs.gov/centers/geosciences-and-environmental-change-science-center/\">Geosciences and Environmental Change Science Center</a><br>U.S. Geological Survey<br>Box 25046, Mail Stop 980<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction&nbsp;&nbsp;</li><li>What is a 3D Geologic Model?</li><li>Methodology</li><li>Results</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2023-12-01","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Sweetkind, Donald S. 0000-0003-0892-4796","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":210808,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":889030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zellman, Kristine L. 0000-0002-7088-429X kzellman@usgs.gov","orcid":"https://orcid.org/0000-0002-7088-429X","contributorId":4849,"corporation":false,"usgs":true,"family":"Zellman","given":"Kristine","email":"kzellman@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":889031,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70271309,"text":"70271309 - 2023 - Hidden system identification: Basin modeling as a tool for examining sedimentary geothermal resource potential","interactions":[],"lastModifiedDate":"2025-09-08T14:58:24.487775","indexId":"70271309","displayToPublicDate":"2023-12-01T09:50:13","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Hidden system identification: Basin modeling as a tool for examining sedimentary geothermal resource potential","docAbstract":"<p>Three-dimensional (3D) geologic and temperature models have been developed for the onshore U.S. Gulf Coast. The results from these models identify areas of moderate- to high-temperature (90°-150°C and &gt;150°C; respectively) geothermal resources at depths &lt;6 km. This modeling study addresses the fundamental challenge of predicting where opportune temperature and lithology coincide. Unlike traditional geothermal systems with surface expressions of hydrothermal circulation (e.g., hot springs, fumaroles, sinter), sedimentary geothermal systems (SGS) are generally hidden. Historically, simplified efforts to predict subsurface temperatures in sedimentary basins have focused on linear temperature extrapolation that does not consider the variable thermal properties of different lithologies or lithologic changes with depth (e.g., compaction, lithification). Therefore, the need to understand basin architecture and predict temperatures in 3D within SGS is paramount to identifying geothermal resources and determining economic feasibility. Basin modeling software has long been used to characterize the subsurface conditions of sedimentary basins, including temperature, in the pursuit of finding hydrocarbons. This tool can also be adapted to evaluate the potential of geothermal resources in a sedimentary basin by predicting the confluence of desirable temperatures and reservoir lithologies. In this work, PetroMod basin modeling software was used to create a regional geologic model of the onshore U.S. Gulf Coast, covering over 500,000 km<sup>2</sup> calibrated to temperature data from wells. Inputs include structural surfaces from commercial databases, lithology information derived from published literature, and corrected bottom-hole temperatures (BHT) from over 6,000 wells. The resulting 3D geologic model can be used to predict temperatures throughout the basin. Maps were exported showing the depth, depositional unit, and reservoir lithology at which temperatures of 90°C and 150°C were reached, revealing over 400,000 km<sup>2</sup> of moderate- to high-temperature resources at depths &lt;6 km. These maps function as a first-order screening tool to identify areas where low-, moderate-, or high-grade resource potential may exist, based on temperature and if optimal reservoir lithologies or depositional units of interest are present. Depending on the success criteria of a project, the same maps can be exported for any isotherm or incorporate other 1407 Gardner and Birdwell subsurface properties. The methodology employed in this work can be applied in any sedimentary basin with available subsurface data. Further calibration incorporating other data, including pressure and porosity, can expand the utility of basin modeling for geothermal evaluations. Basin modeling is a powerful but underutilized tool for identifying prospective geothermal resources in sedimentary basins.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Using the Earth to save the Earth","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Geothermal Rising Conference","conferenceDate":"October 1-3, 2023","conferenceLocation":"Reno, NV","language":"English","publisher":"Geothermal Rising","usgsCitation":"Gardner, R., and Birdwell, J.E., 2023, Hidden system identification: Basin modeling as a tool for examining sedimentary geothermal resource potential, <i>in</i> Using the Earth to save the Earth, v. 47, Reno, NV, October 1-3, 2023, p. 1407-1414.","productDescription":"8 p.","startPage":"1407","endPage":"1414","ipdsId":"IP-155363","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":495157,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034802","linkFileType":{"id":5,"text":"html"}},{"id":495216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gardner, Rand 0000-0001-8711-5334","orcid":"https://orcid.org/0000-0001-8711-5334","contributorId":316831,"corporation":false,"usgs":true,"family":"Gardner","given":"Rand","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":947935,"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":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":947936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261284,"text":"70261284 - 2023 - Geophysical mapping of the Great Lakes Tectonic Zone and surrounding Precambrian geology in the central Upper Peninsula, Michigan","interactions":[],"lastModifiedDate":"2024-12-04T15:39:20.098701","indexId":"70261284","displayToPublicDate":"2023-12-01T09:33:40","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geophysical mapping of the Great Lakes Tectonic Zone and surrounding Precambrian geology in the central Upper Peninsula, Michigan","docAbstract":"<p>The Great Lakes Tectonic Zone (GLTZ) forms the boundary between the Wawa-Abitibi subprovince (north side) and Minnesota River Valley subprovince (south side) within the Archean Superior Province. The GLTZ is concealed for all of its 1100 km length, except south of Marquette in the central Upper Peninsula of Michigan (Sims, 1991; Sims and Day, 1993). Near KI Sawyer, it is exposed as a NW-striking, 2.3 km wide mylonite zone along a strike length of about 11 km, with a mylonitic foliation that dips steeply to the SW (Sims, 1993). The location extent of the GLTZ is unknown to the east where it is concealed beneath Paleozoic sedimentary rocks. We use legacy aeromagnetic data (Daniels et al., 2009) in combination with modern aeromagnetic data (Drenth and Brown, 2020) and ground gravity data to geophysically characterize the GLTZ and map its eastward extent under cover and map additional nearby covered Precambrian tectonic elements. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology proceedings, 69th annual meeting, Eau Claire, Wisconsin, part 1 - Abstracts and proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute on Lake Superior Geology","usgsCitation":"Drenth, B.J., and Cannon, W.F., 2023, Geophysical mapping of the Great Lakes Tectonic Zone and surrounding Precambrian geology in the central Upper Peninsula, Michigan, <i>in</i> Institute on Lake Superior Geology proceedings, 69th annual meeting, Eau Claire, Wisconsin, part 1 - Abstracts and proceedings, p. 27-28.","productDescription":"2 p.","startPage":"27","endPage":"28","ipdsId":"IP-151526","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":464752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464741,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/exhibits/show/ilsg/item/8207"}],"country":"United States","state":"Michigan","otherGeospatial":"Upper Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.6,\n              46.5\n            ],\n            [\n              -87.6,\n              46\n            ],\n            [\n              -86.5,\n              46\n            ],\n            [\n              -86.5,\n              46.5\n            ],\n            [\n              -87.6,\n              46.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":920217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cannon, William F. 0000-0002-2699-8118","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":201972,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":920218,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250279,"text":"ofr20231078 - 2023 - Documentation of a pilot workflow for reanalyzing the U.S. Geological Survey principal aquifers datasets and prototype principal aquifer version 2 dataset for three aquifer systems","interactions":[],"lastModifiedDate":"2026-02-18T21:56:06.736865","indexId":"ofr20231078","displayToPublicDate":"2023-12-01T09:18:12","publicationYear":"2023","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":"2023-1078","displayTitle":"Documentation of a Pilot Workflow for Reanalyzing the U.S. Geological Survey Principal Aquifers Datasets and Prototype Principal Aquifer Version 2 Dataset for Three Aquifer Systems","title":"Documentation of a pilot workflow for reanalyzing the U.S. Geological Survey principal aquifers datasets and prototype principal aquifer version 2 dataset for three aquifer systems","docAbstract":"A pilot workflow to refine the principal aquifers of the United States as defined in the Ground Water Atlas of the United States and create a new version of the principal aquifers (referred to as “version 2”) is documented in this report. The workflow incorporates decision points for creating finer scale spatial data for the principal aquifers and refining the original principal aquifer definitions if warranted. This workflow was applied to four principal aquifers in the upper Midwest region of the United States that were not previously refined as part of a U.S. Geological Survey regional groundwater availability study: the Cambrian-Ordovician aquifer system, the Jacobsville aquifer, the Silurian-Devonian aquifer, and the upper carbonate aquifer. The refinement resulted in the consolidation of two of these aquifers (the Silurian-Devonian and upper carbonate aquifers), an expansion of the Jacobsville aquifer into a larger newly defined Midcontinent Rift sandstone aquifers unit, and a slight refinement of the Cambrian-Ordovician aquifer system to exclude Precambrian units. The U.S. Geological Survey State Geologic Map Compilation geodatabase provided the base data used in the refined version 2 dataset, which are published in an accompanying U.S. Geological Survey data release as a prototype version 2 shapefile and include attributes describing the aquifer, data lineage, and source of the originally defined principal aquifer.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231078","programNote":"Water Availability and Use Science Program","usgsCitation":"Nielsen, M.G., 2023, Documentation of a pilot workflow for reanalyzing the U.S. Geological Survey principal aquifers datasets and prototype principal aquifer version 2 dataset for three aquifer systems: U.S. Geological Survey Open-File Report 2023–1078, 23 p., https://doi.org/10.3133/ofr20231078.","productDescription":"Report: iv, 23 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-142146","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500153,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115642.htm","text":"Pre-Cambrian and lower Paleozoic aquifer systems, upper mid-west, US."},{"id":500152,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115641.htm","text":"Contiguous United States"},{"id":423101,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231078/full"},{"id":423100,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PF3PSM","text":"USGS data release","linkHelpText":"Prototype updated principal aquifer datasets for three aquifer systems in the Upper Midwest, USA"},{"id":423099,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1078/images/"},{"id":423098,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1078/ofr20231078.XML"},{"id":423097,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1078/ofr20231078.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1078"},{"id":423096,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1078/coverthb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, Tennessee, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.7305859564595,\n              35.22068769740886\n            ],\n            [\n              -83.69485342904211,\n              39.32676189210625\n            ],\n            [\n              -82.43609088688153,\n              43.576327709341456\n            ],\n            [\n              -83.98279835997307,\n              46.28057130333451\n            ],\n            [\n              -87.90194001961994,\n              48.2723026998373\n            ],\n            [\n              -89.88542930731663,\n              47.961488287177445\n            ],\n            [\n              -93.34876958344479,\n              47.330935123186606\n            ],\n            [\n              -94.69038320347006,\n              43.86819196616244\n            ],\n            [\n              -93.23439439792311,\n              38.975215510546434\n            ],\n            [\n              -89.77908047690332,\n              37.73301765122889\n            ],\n            [\n              -89.7305859564595,\n              35.22068769740886\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/umid-water\" data-mce-href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive<br>Madison, WI 53726</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Analysis of Aquifer Boundaries in the Pilot Study Area</li><li>Considerations for Future Analysis of Updated Principal Aquifers</li><li>Prototype Version 2 Principal Aquifer Dataset</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-12-01","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":889258,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70264392,"text":"70264392 - 2023 - A management-focused population viability analysis for North Atlantic right whales","interactions":[],"lastModifiedDate":"2025-03-14T14:18:14.086582","indexId":"70264392","displayToPublicDate":"2023-12-01T09:10:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NMFS-NEFSC 307","title":"A management-focused population viability analysis for North Atlantic right whales","docAbstract":"<p>The North Atlantic right whale (<i>Eubalaena glacialis</i>) is among the most endangered whale species in the world and has been in decline since 2010. Considerable effort is directed toward its recovery by striving to remove threats. In this report, we describe the development of a population viability analysis for right whales that is designed to assess the current status, evaluate the contributions of various threats, and explore the management interventions needed to achieve recovery. The individual-based model that underlies this analysis accounts for age- and stagespecific survival and reproductive rates, the effects of severe injury from entanglement or vessel strike, and future changes in prey availability and accessibility. Several new or updated empirical analyses supplied parameter estimates, and parametric uncertainty was carefully incorporated into the model results. </p><p>We find that under the status quo conditions of 2019, prior to the enactment of new regulations by the U.S. and Canada after 2020, the North Atlantic right whale population would be expected to continue to fall, with a median decline of 75% in 100 years (95% projection interval, –98% to +9% change) and a probability of falling below 50 proven females of 0.934 in 100 years. If the recently enacted regulations reduce entanglement risk by 25%, however, the population would be expected to decrease by 42% over 100 years (95% projection interval –92% to +154% change), with a risk of falling below 50 proven females in 100 years of 0.705. If, instead, the recently enacted regulations reduce entanglement risk by 50%, the population would be expected to increase by 52% in 100 years (95% projection interval –83% to +497% change), with a probability of falling below 50 proven females of 0.349. </p><p>Of the 3 primary threats explored in this analysis, the risk of entanglement contributes the most to the long-term risk of quasi-extinction, followed closely by the risk of vessel strike, and much more distantly by a decrease in prey availability. In hypothetical scenarios that fully remove one threat at a time, removal of the entanglement threat alone reduces the probability of falling below 50 proven females in 100 years from 0.934 to 0.053; removal of the vessel strike threat alone reduces it to 0.343; and a return to higher prey conditions, but with both human-related threats still in place, reduces it to 0.875. </p><p>We explored a wide range of management intervention scenarios that changed the rate of entanglement risk (e.g., endline reductions, closures, implementation of ropeless/on-demand gear); the effect of entanglement (through use of weak rope technology); the rate of vessel traffic increase over time; and the severity of vessel strike risk through speed restrictions. We found, for example, that reducing entanglement risk alone by 25% reduces the risk of quasi-extinction from 0.934 to 0.705; reducing vessel strike risk alone by 25% reduces the risk of quasi-extinction from 0.934 to 0.846; but the combination of reducing both entanglement risk and vessel strike risk by 25% reduces the risk of quasi-extinction to 0.528. </p><p>This model and the results it produced are meant to represent an assessment of the current status of North Atlantic right whales using the best available scientific and commercial data and state-of-the-art analytical tools. Our knowledge of the future of the right whale population, however, has limitations. We have endeavored to fully incorporate uncertainty into this model, but there are many areas for continued improvement. We view this model as a living tool that can be improved, adapted, and extended as new data, new methods, and new questions arise. </p>","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.25923/dqp2-2r71","usgsCitation":"Runge, M.C., Linden, D., Hostetler, J.A., Borggaard, D., Garrison, L.P., Knowlton, A., Lesage, V., Williams, R., and Pace, R., 2023, A management-focused population viability analysis for North Atlantic right whales: NOAA Technical Memorandum NMFS-NEFSC 307, 93 p., https://doi.org/10.25923/dqp2-2r71.","productDescription":"93 p.","ipdsId":"IP-144310","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":930629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linden, Daniel W.","contributorId":229525,"corporation":false,"usgs":false,"family":"Linden","given":"Daniel W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":930630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":930631,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borggaard, Diane L","contributorId":352275,"corporation":false,"usgs":false,"family":"Borggaard","given":"Diane L","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":930632,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrison, Lance P.","contributorId":296893,"corporation":false,"usgs":false,"family":"Garrison","given":"Lance","email":"","middleInitial":"P.","affiliations":[{"id":64230,"text":"NOAA-NMFS Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":930633,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knowlton, Amy R.","contributorId":352046,"corporation":false,"usgs":false,"family":"Knowlton","given":"Amy R.","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":930634,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lesage, Véronique","contributorId":352276,"corporation":false,"usgs":false,"family":"Lesage","given":"Véronique","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":930635,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Robert A. 0000-0002-2973-8493","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":203802,"corporation":false,"usgs":false,"family":"Williams","given":"Robert A.","affiliations":[{"id":36721,"text":"USGS-Emeritus","active":true,"usgs":false}],"preferred":false,"id":930636,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pace, Richard M III","contributorId":352277,"corporation":false,"usgs":false,"family":"Pace","given":"Richard M","suffix":"III","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":930637,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70267462,"text":"70267462 - 2023 - Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria","interactions":[],"lastModifiedDate":"2025-05-23T14:09:15.876291","indexId":"70267462","displayToPublicDate":"2023-12-01T09:08:54","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria","docAbstract":"Identifying and analyzing closed depressions in karst areas is important for sinkhole hazard evaluation and land management. We created a sinkhole inventory in the karst region of northwest Puerto Rico using a lidar-derived elevation model acquired in 2018 approximately eleven months after Hurricane Maria. The goal of this project is to develop a geodatabase of sinkhole feature classes (polygons and points), relevant geometric attributes of each feature, and a density raster to portray areas of greater clustering of sinkholes as an input for future sinkhole susceptibility assessment. We used ArcGIS Pro® v3.0 to create closed depression polygons using two semi-automated extraction methods. A fill-difference method was used to capture depressions nine square meters and larger, and a contour tree method was used to capture nested depressions larger than one hundred square meters. Quality checks were conducted to eliminate non-karst depressions, such as human-made depressions and those resulting as artifacts from the automated methods. Geospatial data of land cover, soils, and geology helped to refine the results and improve quality control. The most challenging aspect of this effort was determining a true karst sinkhole from other depressions extracted from the lidar-derived elevation model. Limitations of this semi-automated method include false-positive depressions in the automated results and the exclusion of sinkholes in conducting large-scale eliminations based on landscape attributes. We approached this challenge by combining layers of other geospatial information to evaluate the type of process that could result in a closed depression. This project will help develop an efficient method to visualize karst hazards utilizing lidar-derived elevation models and sinkhole geomorphic expressions. The resulting geodatabase can be used to efficiently identify sinkhole susceptibility and support land management decision-making in karst areas.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th multidisciplinary conference on sinkholes and the engineering and environmental impacts of karst","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"National Cave and Karst Research Institute","usgsCitation":"Smith, L., Doctor, D.H., and Cox, C., 2023, Mapping closed depressions in the karst region of northwest Puerto Rico using lidar-derived elevation data obtained in 2018 after Hurricane Maria, <i>in</i> Proceedings of the 17th multidisciplinary conference on sinkholes and the engineering and environmental impacts of karst, v. 17, p. 239-248.","productDescription":"10 p.","startPage":"239","endPage":"248","ipdsId":"IP-148086","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":486487,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.usf.edu/sinkhole_2022/ProceedingswithProgram/"},{"id":486498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -67.30291697689199,\n              18.559923243339426\n            ],\n            [\n              -67.30291697689199,\n              18.330982046375794\n            ],\n            [\n              -66.86489408952299,\n              18.228131112250153\n            ],\n            [\n              -66.11901997545601,\n              18.330982046375794\n            ],\n            [\n              -66.11901997545601,\n              18.559923243339426\n            ],\n            [\n              -67.30291697689199,\n              18.559923243339426\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Lillian G.","contributorId":355868,"corporation":false,"usgs":false,"family":"Smith","given":"Lillian G.","affiliations":[{"id":36213,"text":"University of Redlands","active":true,"usgs":false}],"preferred":false,"id":938308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":938309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cox, Cheyenne L.","contributorId":355869,"corporation":false,"usgs":false,"family":"Cox","given":"Cheyenne L.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":938310,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250953,"text":"70250953 - 2023 - Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies","interactions":[],"lastModifiedDate":"2024-01-13T14:57:56.409648","indexId":"70250953","displayToPublicDate":"2023-12-01T08:55:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The associated uncertainties of future climate projections are one of the biggest obstacles to overcome in studies exploring the potential regional impacts of future climate shifts. In remote and climatically complex regions, the limited number of available downscaled projections may not provide an accurate representation of the underlying uncertainty in future climate or the possible range of potential scenarios. Consequently, global downscaled projections are now some of the most widely used climate datasets in the world. However, they are rarely examined for representativeness of local climate or the plausibility of their projected changes. Here we explore the utility of two such global datasets (CHELSA and WorldClim2) in providing plausible future climate scenarios for regional climate change impact studies. Our analysis was based on three steps: (1) standardizing a baseline period to compare available global downscaled projections with regional observation-based datasets and regional downscaled datasets; (2) bias correcting projections using a single observation-based baseline; and (3) having controlled differences in baselines between datasets, exploring the patterns and magnitude of projected climate shifts from these datasets to determine their plausibility as future climate scenarios, using Hawaiʻi as an example region. Focusing on mean annual temperature and precipitation, we show projected climate shifts from these commonly used global datasets not only may vary significantly from one another but may also fall well outside the range of future scenarios derived from regional downscaling efforts. As species distribution models are commonly created from these datasets, we further illustrate how a substantial portion of variability in future species distribution shifts can arise from the choice of global dataset used. Hence, projected shifts between baseline and future scenarios from these global downscaled projections warrant careful evaluation before use in climate impact studies, something rarely done in the existing literature.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10584-023-03623-z","usgsCitation":"Fortini, L., Kaiser, L.R., Frazier, A.G., and Giambelluca, T.W., 2023, Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies: Climatic Change, v. 176, https://doi.org/10.1007/s10584-023-03623-z.","productDescription":"169, 21 p.","startPage":"169","ipdsId":"IP-136355","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":441499,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10584-023-03623-z","text":"Publisher Index 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 \"}}]}","volume":"176","noUsgsAuthors":false,"publicationDate":"2023-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":892396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaiser, Lauren R.","contributorId":200422,"corporation":false,"usgs":false,"family":"Kaiser","given":"Lauren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":892397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frazier, Abby G.","contributorId":221112,"corporation":false,"usgs":false,"family":"Frazier","given":"Abby","email":"","middleInitial":"G.","affiliations":[{"id":40321,"text":"USDA Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":892398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giambelluca, Thomas W","contributorId":296956,"corporation":false,"usgs":false,"family":"Giambelluca","given":"Thomas","email":"","middleInitial":"W","affiliations":[{"id":64253,"text":"University of Hawaiʻi at Mānoa","active":true,"usgs":false}],"preferred":false,"id":892399,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261199,"text":"70261199 - 2023 - New high resolution airborne geophysical surveys in Nevada And California for geothermal and mineral resource studies","interactions":[],"lastModifiedDate":"2024-11-29T14:54:09.70735","indexId":"70261199","displayToPublicDate":"2023-12-01T08:53:31","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"New high resolution airborne geophysical surveys in Nevada And California for geothermal and mineral resource studies","docAbstract":"The U.S. Geological Survey (USGS) and the Department of Energy (DOE) are collaborating to acquire high-resolution airborne magnetic and radiometric data to support geologic and geophysical mapping and modeling that will assist geothermal and critical mineral studies. Coordinated with these efforts are programs supporting geologic mapping and airborne LiDAR (light detection and ranging) surveys that yield detailed surface topographic models of the terrain over the same regions spanned by the geophysical surveys. The collaboration leverages resources from the USGS and DOE to acquire large regional datasets that will provide fundamental data necessary to map surface and subsurface geology and structure to benefit mineral and resource program objectives of both agencies. Such regionally uniform datasets are important for geothermal research to assist in identifying geologically favorable settings and as invaluable inputs in predictive models targeting undiscovered resources that use knowledge-driven (e.g., play fairway analysis) or data-driven approaches (e.g., machine-learning methods) to reduce risk associated with resource exploration. These data will also serve a wide range of other related activities from hazard (earthquake, volcano, landslide, environmental) and resource (water, mineral, energy) studies, to mapping and land management.\n\nSurveys were conducted in two areas that were selected because they host substantial geothermal and mineral potential in California and Nevada. The data will aid several ongoing USGS and DOE projects aimed at characterizing geothermal and mineral systems, understanding the factors controlling their occurrence, and improving future national resource assessments. The first of these surveys (referred to as GeoDAWN) was collected over northern and western Nevada and eastern California and spans areas of major resource potential associated with the Walker Lane and western Great Basin. This includes Clayton Valley, which hosts substantial lithium brine and clay resources, and the Humboldt Mafic Complex, which constitutes a potentially important resource of critical minerals (including cobalt, rare earth elements, platinum group elements, iron, chromium, nickel, and copper). The second survey area (referred to as GeoFlight) is focused over\n\nthe Salton Trough in southern California that contains some of the largest and hottest known hydrothermal systems in the world, as well as a substantial lithium brine resource that could potentially meet the nation’s lithium demand for electric vehicles. Data from both surveys will be made publicly available through USGS publications and online data repositories. Future efforts under this collaboration are presently being evaluated and may involve acquisition of other data sets such as airborne gravity, electromagnetic or hyperspectral data to address research targets.","language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Glen, J.M., and Earney, T.E., 2023, New high resolution airborne geophysical surveys in Nevada And California for geothermal and mineral resource studies, v. 47, p. 1738-1762.","productDescription":"25 p.","startPage":"1738","endPage":"1762","ipdsId":"IP-156123","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":464588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464580,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034804","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":919604,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250443,"text":"70250443 - 2023 - Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska","interactions":[],"lastModifiedDate":"2023-12-09T14:53:33.90405","indexId":"70250443","displayToPublicDate":"2023-12-01T08:48:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska","docAbstract":"<p><span>This map of fractures, scarps, faults, and landslides was completed to identify areas in Glacier Bay National Park and Preserve that may present a landslide-generated tsunami hazard. To address the potential of landslide and tsunami hazards in the park, the National Park Service (NPS) and the US Geological Survey (USGS) partnered to conduct a multi-year hazard assessment of Glacier Bay National Park and Preserve. To produce the map described in this report, we used the newly acquired (2019-2020) light detection and ranging (LiDAR) 0.5 to 1.0 m digital elevation models (DEMs) that cover all the coastal areas of the park and extend up to the ridgetops in places with steep slopes. A bare earth DEM was used to identify and map areas of incipient landslides (i.e., fractures and scarps), fault scarps, and areas where landslides have clearly occurred in the past (i.e., areas where scars and deposits are clearly visible). This map provides a baseline data set that can be used to aid forecasts of where landslides are most likely to occur in the future.</span></p>","language":"English","publisher":"National Park Service","doi":"10.36967/2300706","collaboration":"National Park Service","usgsCitation":"Hults, C., Coe, J.A., and Avdievitch, N.N., 2023, Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska, iv, 14 p., https://doi.org/10.36967/2300706.","productDescription":"iv, 14 p.","ipdsId":"IP-147660","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":423385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park and Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -139.23040794383448,\n              59.9305550708161\n            ],\n            [\n              -139.23040794383448,\n              57.252640525398476\n            ],\n            [\n              -134.22064231883454,\n              57.252640525398476\n            ],\n            [\n              -134.22064231883454,\n              59.9305550708161\n            ],\n            [\n              -139.23040794383448,\n              59.9305550708161\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hults, Chad","contributorId":332290,"corporation":false,"usgs":false,"family":"Hults","given":"Chad","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":889926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":889927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avdievitch, Nikita N. 0000-0002-2507-2962","orcid":"https://orcid.org/0000-0002-2507-2962","contributorId":225492,"corporation":false,"usgs":true,"family":"Avdievitch","given":"Nikita","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":889928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250639,"text":"70250639 - 2023 - Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability","interactions":[],"lastModifiedDate":"2024-10-15T17:20:38.127462","indexId":"70250639","displayToPublicDate":"2023-12-01T07:22:20","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesTitle":{"id":18745,"text":"Geothermal Resources Council Transactions","active":true,"publicationSubtype":{"id":19}},"title":"Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability","docAbstract":"Topography provides information about the structural controls of the Great Basin and therefore information that may be used to identify favorable structural settings for geothermal systems. The Nevada Machine Learning Project (NVML) tested the use of a digital elevation map (DEM) of topography as an input feature to predict geothermal system favorability. A recent study re-examines the NVML data, identifying the DEM as the most important feature, showing a broad uniform pattern of high-favorability in the lower-elevation west and low-favorability in the higher elevation east of their study area in north-central Nevada. This regional elevation trend conflicts with the geologic notion that local relative topography should be used to identify geologic structures associated with favorable structural settings for hydrothermal upflow. Specifically, local relative topography gives information about position in the mountains, in the valleys, or at the transitions between, aiding in identification of faults and fault intersections. As part of U.S. Geological Survey efforts to engineer features that are useful for predicting geothermal resources, we construct a detrended elevation map that emphasizes local relative topography and highlights features that geologists use for identifying geothermal systems (i.e., providing machine learning algorithms with features that may improve predictive skill by emphasizing the information used by geologists). Herein, we describe the removal of the regional trend in elevation to emphasize the basin-and-range scale structural features, creating detrended elevation maps.\nRegional elevation trends were estimated using a local linear regression and subtracted from the actual elevation using a 30-m DEM. In an effort to optimize the detrended surface, alternate versions were produced with different rates of smoothness resulting in three detrended elevation maps. The resulting elevation trend surfaces (a proxy for crustal thickness) are compared with conductive heat flow maps, and a general pattern was observed of a negative correlation between heat flow and regional elevation in many areas, indicating that thinner crust may be causing elevated heat flow in some areas and thicker crust may cause the observed heat flow lows. Because these detrended elevation maps emphasize geologic structure and relative displacement, these products may also be useful for other geologic research including mineral exploration, hydrologic research, and defining geologic provinces.","language":"English","publisher":"Geothermal Rising","usgsCitation":"DeAngelo, J., Burns, E.R., Mordensky, S.P., and Lindsey, C.R., 2023, Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability, v. 47, p. 1694-1702.","productDescription":"9 p.","startPage":"1694","endPage":"1702","ipdsId":"IP-155138","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":423865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423843,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1034786","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890683,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindsey, Cary Ruth 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":292016,"corporation":false,"usgs":true,"family":"Lindsey","given":"Cary","email":"","middleInitial":"Ruth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890685,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}