Bedload transport of sediment by waves and currents is one of the key physical processes that affect the evolution of coasts, nearshore areas, and the engineering practices there. Wave skewness and asymmetry, both of which increase as waves shoal, result in a net bedload sediment flux over a wave cycle. The impacts of this mechanism on large-scale coastal and shoreline change are investigated in this study, using field observations and Coupled Ocean Atmosphere Wave Sediment Transport (COAWST), a hydrodynamic process-based numerical modeling system (Warner et al., 2010). The study site is Fire Island, New York, located at the Atlantic Coast of the USA, with a focus on the persistent shoreline shape, at the western half of this 50-km-long barrier island, that has been hypothesized to be linked to the sand deposits at the shoreface.
","conferenceTitle":"37th International Conference on Coastal Engineering,","conferenceDate":"July 2-8, 2022","conferenceLocation":"New South Wales, Australia","language":"English","publisher":"Coastal engineering proceedings","doi":"10.9753/icce.v37.sediment.17","usgsCitation":"Parlak, M., Ayhan, B., Warner, J.C., Kalra, T., and Safak, I., 2022, Effect of wave skewness and asymmetry on the evolution of Fire Island, New York, 37th International Conference on Coastal Engineering,, v. 37, New South Wales, Australia, July 2-8, 2022, 1 p., https://doi.org/10.9753/icce.v37.sediment.17.","productDescription":"1 p.","ipdsId":"IP-140577","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445579,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.9753/icce.v37.sediment.17","text":"Publisher Index Page"},{"id":425988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2023-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Parlak, Muhammed","contributorId":304662,"corporation":false,"usgs":false,"family":"Parlak","given":"Muhammed","email":"","affiliations":[{"id":66144,"text":"İstanbul Bilgi University","active":true,"usgs":false}],"preferred":false,"id":871289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayhan, Bilal","contributorId":304663,"corporation":false,"usgs":false,"family":"Ayhan","given":"Bilal","email":"","affiliations":[{"id":66144,"text":"İstanbul Bilgi University","active":true,"usgs":false}],"preferred":false,"id":871290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":871292,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Safak, Ilgar","contributorId":304429,"corporation":false,"usgs":false,"family":"Safak","given":"Ilgar","affiliations":[{"id":66065,"text":"Dept. Civil Engineering, Istanbul Bilgi University, Istanbul, Türkiye","active":true,"usgs":false}],"preferred":false,"id":871293,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240845,"text":"70240845 - 2022 - Storm and tsunami overwash sediment transport inferred from recent deposits","interactions":[],"lastModifiedDate":"2024-02-23T17:13:18.693943","indexId":"70240845","displayToPublicDate":"2023-09-01T11:09:36","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Storm and tsunami overwash sediment transport inferred from recent deposits","docAbstract":"Overwash deposits from storms and tsunamis record information about sediment transport and flow that can be used to inform hazard assessments. Here we explore deposits from two extreme wave events: (1) the 2012 Hurricane Sandy, a Category 5 hurricane that is the largest storm in the Atlantic basin on historical record, and (2) the 2011 Tohoku-oki tsunami, created by a 9.0 Mw earthquake, that was up to 20 m high at the coast.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of 37th conference on coastal engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"37th Conference on Coastal Engineering","conferenceDate":"December 4-9, 2022","conferenceLocation":"Sydney, Australia","language":"English","publisher":"International Conference on Coastal Engineering (ICCE)","doi":"10.9753/icce.v37.sediment.65","usgsCitation":"Jaffe, B.E., and La Selle, S., 2022, Storm and tsunami overwash sediment transport inferred from recent deposits, in Proceedings of 37th conference on coastal engineering, Sydney, Australia, December 4-9, 2022, sediment.65, 1 p., https://doi.org/10.9753/icce.v37.sediment.65.","productDescription":"sediment.65, 1 p.","ipdsId":"IP-144574","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445582,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.9753/icce.v37.sediment.65","text":"Publisher Index Page"},{"id":425950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":865034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":865035,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250096,"text":"70250096 - 2022 - Evaluating the influence of the Forestry Reclamation Approach on throughfall quantity in eastern Kentucky","interactions":[],"lastModifiedDate":"2024-06-03T14:45:20.437591","indexId":"70250096","displayToPublicDate":"2023-08-02T06:32:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17091,"text":"Reclamation Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the influence of the Forestry Reclamation Approach on throughfall quantity in eastern Kentucky","docAbstract":"The Appalachian Region is a rich forested ecosystem that has been impacted by coal mining. The Surface Mining Control and Reclamation Act of 1977 was enacted to resolve many of the environmental problems caused by surface mining. Reclamation practices resulted in excessive soil compaction and use of nonnative grasses and shrubs that have altered hydrologic processes. The Forestry Reclamation Approach (FRA) is a best practice for reestablishing forested ecosystems on mined lands in Appalachia. This project evaluated precipitation throughfall in reforested 10- and 20-year-old FRA sites and unmined 100-year-old forest stands as a metric for evaluating the return of forest hydrologic function after reclamation. Stands of coniferous and deciduous trees were evaluated independently for each age class. Throughfall rates were significantly impacted by tree type and age. Throughfall in coniferous trees was less than in deciduous trees, and throughfall in the 10-year-old deciduous trees tended to be highest. Throughfall was also significantly impacted by storm characteristics. Higher rainfall depth and longer duration resulted in significantly larger throughfall depths under both coniferous and deciduous stands, whereas increased intensity increased throughfall depths for the 10- and 100-year-old plots, but not for the 20-year-old plots. As canopy closure occurs in young FRA forests, throughfall rates resemble those reported for young, naturally regenerating forests in the region. Results may help guide management of forested watershed strategies to reduce surface runoff and local flooding on reclaimed surface mined lands.
","language":"English","publisher":"Allen Press","doi":"10.21000/rcsc-202200009","usgsCitation":"Gerlitz, M., Agouridis, C.T., Williamson, T.N., and Barton, C.D., 2022, Evaluating the influence of the Forestry Reclamation Approach on throughfall quantity in eastern Kentucky: Reclamation Sciences, v. 1, p. 13-24, https://doi.org/10.21000/rcsc-202200009.","productDescription":"12 p.","startPage":"13","endPage":"24","ipdsId":"IP-122841","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":445584,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21000/rcsc-202200009","text":"Publisher Index Page"},{"id":422673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","county":"Breathitt County, Knott County, Perry County","otherGeospatial":"Laurel Fork Mine, Starfire Mine, Robinson Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.18644168615366,\n 37.484780966469884\n ],\n [\n -83.18644168615366,\n 37.41427280145203\n ],\n [\n -83.08730948291287,\n 37.41427280145203\n ],\n [\n -83.08730948291287,\n 37.484780966469884\n ],\n [\n -83.18644168615366,\n 37.484780966469884\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","noUsgsAuthors":false,"publicationDate":"2023-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Gerlitz, Morgan","contributorId":331640,"corporation":false,"usgs":false,"family":"Gerlitz","given":"Morgan","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":888322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agouridis, Carmen T. 0000-0001-9580-6143","orcid":"https://orcid.org/0000-0001-9580-6143","contributorId":150223,"corporation":false,"usgs":false,"family":"Agouridis","given":"Carmen","email":"","middleInitial":"T.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":888323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barton, Chris D. 0000-0003-0692-3079","orcid":"https://orcid.org/0000-0003-0692-3079","contributorId":236883,"corporation":false,"usgs":false,"family":"Barton","given":"Chris","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":888325,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70245152,"text":"70245152 - 2022 - Salinification of coastal wetlands and freshwater management to support resilience","interactions":[],"lastModifiedDate":"2023-06-19T16:12:15.2962","indexId":"70245152","displayToPublicDate":"2023-06-19T11:07:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5075,"text":"Ecosystem Health and Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Salinification of coastal wetlands and freshwater management to support resilience","docAbstract":"Climates are rapidly changing in wetland ecosystems around the world and historical land-use change is not always given enough consideration in climate adaptation discussions. Historical changes to hydrology and other key environments can exacerbate vegetation stress; e.g., recent drought and flood episodes are likely more extreme because of climate change. The contributions of global and regional changes that affect groundwater and surface water availability all need consideration in conservation planning including sea-level rise, coastal subsidence and compaction, fluid extraction, and floodplain reengineering. Where subsidence is not too extreme, healthy coastal vegetation often can keep ahead of sea-level rise by accreting elevation through sedimentary and/or biogenic processes. Better water conservation and minimum water delivery during drought may support foundational species and avoid wetland collapse. Local approaches have been developed to rewet inland floodplains decades after their reengineering for agricultural and urban development to support biodiversity in salinified coastal wetlands. The purpose of this paper is to describe inland wetland remediation techniques that may also be useful to increase freshwater delivery to coastal wetlands experiencing salinification. While some salinified coastal ecosystems may transition in the future, attempts can be made to remediate salinification related to historical land use in support of wetland conservation, health, and sustainability.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.34133/ehs.0083","usgsCitation":"Middleton, B., and Boudell, J., 2022, Salinification of coastal wetlands and freshwater management to support resilience: Ecosystem Health and Sustainability, v. 9, 0083, 7 p., https://doi.org/10.34133/ehs.0083.","productDescription":"0083, 7 p.","ipdsId":"IP-117863","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":445587,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.34133/ehs.0083","text":"Publisher Index Page"},{"id":418216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":216869,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boudell, Jere","contributorId":181496,"corporation":false,"usgs":false,"family":"Boudell","given":"Jere","affiliations":[],"preferred":false,"id":875692,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70254744,"text":"70254744 - 2022 - Density-dependent processes and population dynamics of native sculpin in a mountain river","interactions":[],"lastModifiedDate":"2024-06-07T11:39:27.018356","indexId":"70254744","displayToPublicDate":"2023-03-29T06:37:01","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Density-dependent processes and population dynamics of native sculpin in a mountain river","docAbstract":"Understanding the processes governing population dynamics is important for effective conservation and environmental management. Disentangling the relative role of density-dependent versus density-independent processes on population dynamics is often made difficult by the inability to control for abiotic or biotic factors, but long-term datasets are invaluable in this pursuit. We used a 14-year dataset from the Logan River, Utah, to assess long-term trends in abundance and evidence of density-dependent and density-independent effects on population dynamics of Paiute sculpin (Cottus beldingii) across six sites. Additionally, we evaluated the feeding ecology of sculpin over 4 years. Sculpin densities generally increased from upstream to downstream, and the annual per capita rate of increase was negatively and significantly correlated with sculpin density at four of six sites. We observed a negative relationship between total gut content and sculpin density but did not observe a negative relationship between relative condition and density. Sculpin displayed a generalist feeding strategy, and interannual differences in diet composition appeared to be influenced by interannual differences in flow, particularly years with higher magnitude flow. The observed spatial patterns in sculpin abundance throughout the watershed matched those of invasive brown trout (Salmo trutta), the top piscivore in the Logan River, and likely represent affinities for the suite of ecological conditions associated with downstream sections of the Logan River. Our results suggest that sculpin populations are regulated largely by density-dependent processes and match those from other studies on sculpin population dynamics including a range of species and habitats that differ vastly in abiotic conditions.
Moose (Alces alces) populations along the southern extent of their range are largely declining, and there is growing evidence that nutritional condition — which influences several vital rates – is a contributing factor. Moose body condition can presently be estimated only when there is measurable subcutaneous rump fat, which equates to animals with >6% ingesta-free body fat (IFBFat). There is need for a technique to allow body fat estimation of animals in poorer body condition (i.e., <6% body fat). We advance current methods for moose, following those used and validated with other ungulate species, by establishing a moose-specific body condition score (BCS) that can be used to estimate IFBFat in the lower range of condition. Our modified BCS was related strongly (r2 = 0.89) to IFBFat estimates based on measurable rump fat. By extending the predicted relationship to individuals without measurable fat, the BCS equated severe emaciation with 0.67% IFBFat, supporting the accuracy of the method. The lower end of nutritional condition is important for identifying relationships involving life-history characteristics because most state-dependent changes occur at lower levels of condition. Therefore, until the BCS can be validated with moose carcasses, we believe our method to estimate body fat across the full range of condition should yield better understanding of the drivers underlying declining moose populations.
","language":"English","publisher":"Lakehead University","usgsCitation":"Levine, R.L., Smiley, R.A., Jesmer, B.R., Oates, B.A., Goheen, J.R., Stephenson, T.R., Kauffman, M., Fralick, G., and Monteith, K., 2022, Extending body condition scoring beyond measurable rump fat to estimate full range of nutritional condition for moose: Alces, v. 58, p. 91-99.","productDescription":"9 p.","startPage":"91","endPage":"99","ipdsId":"IP-141310","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":427211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427210,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://alcesjournal.org/index.php/alces/article/view/1883","linkFileType":{"id":5,"text":"html"}}],"volume":"58","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levine, Rebecca L.","contributorId":296705,"corporation":false,"usgs":false,"family":"Levine","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":852269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smiley, Rachel A.","contributorId":296706,"corporation":false,"usgs":false,"family":"Smiley","given":"Rachel","email":"","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":852270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jesmer, Brett R.","contributorId":296707,"corporation":false,"usgs":false,"family":"Jesmer","given":"Brett","email":"","middleInitial":"R.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":852271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oates, Brendan A.","contributorId":296708,"corporation":false,"usgs":false,"family":"Oates","given":"Brendan","email":"","middleInitial":"A.","affiliations":[{"id":64152,"text":"4Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":852272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goheen, Jacob R.","contributorId":296709,"corporation":false,"usgs":false,"family":"Goheen","given":"Jacob","email":"","middleInitial":"R.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":852273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephenson, Thomas R.","contributorId":296710,"corporation":false,"usgs":false,"family":"Stephenson","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":64153,"text":"Sierra Nevada Bighorn Sheep Recovery Program","active":true,"usgs":false}],"preferred":false,"id":852274,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":852275,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fralick, Gary L.","contributorId":296711,"corporation":false,"usgs":false,"family":"Fralick","given":"Gary L.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":852276,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monteith, Kevin L.","contributorId":296712,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin L.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":852277,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70251553,"text":"70251553 - 2022 - Fisheries research and monitoring activities of the Lake Erie Biological Station, 2022","interactions":[],"lastModifiedDate":"2024-02-16T13:04:06.954115","indexId":"70251553","displayToPublicDate":"2023-02-16T07:02:52","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Fisheries research and monitoring activities of the Lake Erie Biological Station, 2022","docAbstract":"This report presents biomass-based summaries of fish communities in western Lake Erie derived from USGS bottom trawl surveys conducted from 2013 to 2022 in June and September. The survey design compliments the August ODNR- OMNDMNRF effort by reinforcing stock assessments with more robust data. Analyses herein evaluated trends in total biomass, abundance of dominant predator and forage species, non-native species composition, biodiversity and community structure. Data from this effort can be explored interactively online (https://lebs.shinyapps.io/western-basin/) and are accessible for download (Keretz et al. 2023). Annual survey data are added to these sources as data become available.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Dufour, M.R., Hilling, C.D., Keretz, K.R., Kraus, R., Oldham, R.C., Roberts, J., and Schmitt, J., 2022, Fisheries research and monitoring activities of the Lake Erie Biological Station, 2022, 13 p.","productDescription":"13 p.","ipdsId":"IP-150775","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":425721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":425720,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.glfc.org/index.php"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.94328472654291,\n 42.45303920377259\n ],\n [\n -83.94328472654291,\n 41.175748153693036\n ],\n [\n -82.10856792966806,\n 41.175748153693036\n ],\n [\n -82.10856792966806,\n 42.45303920377259\n ],\n [\n -83.94328472654291,\n 42.45303920377259\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":894901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hilling, Corbin David 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":298946,"corporation":false,"usgs":true,"family":"Hilling","given":"Corbin","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":894904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keretz, Kevin R. 0000-0002-4808-8350 kkeretz@usgs.gov","orcid":"https://orcid.org/0000-0002-4808-8350","contributorId":5859,"corporation":false,"usgs":true,"family":"Keretz","given":"Kevin","email":"kkeretz@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":894899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":894900,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oldham, Richard Cole 0000-0002-2331-7612","orcid":"https://orcid.org/0000-0002-2331-7612","contributorId":294345,"corporation":false,"usgs":true,"family":"Oldham","given":"Richard","email":"","middleInitial":"Cole","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":894903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":894905,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":894902,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70240287,"text":"70240287 - 2022 - Sea otters in a California estuary: Detecting temporal and spatial dynamics with volunteer monitoring","interactions":[],"lastModifiedDate":"2023-02-03T15:16:46.34067","indexId":"70240287","displayToPublicDate":"2023-02-03T09:10:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Sea otters in a California estuary: Detecting temporal and spatial dynamics with volunteer monitoring","docAbstract":"Volunteer monitoring can support conservation of imperiled wildlife, by providing higher resolution data in space and time than those available from professional scientists. However, concerns have been raised that data collected by amateurs are inaccurate or inconsistent and thus do not allow for robust detection of spatial or temporal trends. We evaluated the rigor and value of volunteer monitoring data for one iconic wildlife species, the southern sea otter (Enhydra lutris nereis), in Elkhorn Slough estuary in central California, USA, and explored whether volunteer monitoring could provide added value to complement limited professional surveys. First, we compiled and analyzed sea otter counts taken on daily ecotourist boat trips along the estuary, and then compared temporal patterns to data collected by professional scientists tasked with monitoring this federally listed species. Second, we analyzed data on sea otter abundance, habitat use, and behavior collected by a team of trained volunteers, the Elkhorn Slough Reserve Otter Monitoring Program. Overall, we demonstrated the ability to detect important ecological patterns relevant to sea otter conservation and wetland habitat management using volunteer-derived datasets. Long-term trends and inter-annual variability were similar between professional agency monitoring data and volunteer datasets. Moreover, the much higher frequency of volunteer observations allowed for seasonal and tidal dynamics to be detected that could not be revealed by less frequent professional monitoring. We found higher sea otter abundance in the estuary in spring–summer, indicating seasonality in use of the estuary. We detected differences in habitat use of the estuary between higher and lower tides, and greater frequency of foraging at low tide and in certain areas. Volunteer observations revealed fine-scale differences in habitat use: eelgrass beds were used much more heavily than adjacent areas only a few meters away. Volunteer data can thus provide critical information about coastal habitat use and behavior that can improve conservation strategies for threatened wildlife species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4300","usgsCitation":"Eby, R., Rosso, S., Copriviza, J., Scoles, R., Gideon, Y., Mancino, J., Mayer, K.A., Yee, J.L., and Wasson, K., 2022, Sea otters in a California estuary: Detecting temporal and spatial dynamics with volunteer monitoring: Ecosphere, v. 13, no. 11, e4300, 15 p., https://doi.org/10.1002/ecs2.4300.","productDescription":"e4300, 15 p.","ipdsId":"IP-143440","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445592,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4300","text":"Publisher Index Page"},{"id":412675,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Elkhorn Slough","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n 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]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Eby, Ron","contributorId":221790,"corporation":false,"usgs":false,"family":"Eby","given":"Ron","email":"","affiliations":[{"id":40430,"text":"Elkhorn Slough National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":863246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosso, Susan","contributorId":301987,"corporation":false,"usgs":false,"family":"Rosso","given":"Susan","email":"","affiliations":[{"id":40430,"text":"Elkhorn Slough National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":863247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Copriviza, John","contributorId":301989,"corporation":false,"usgs":false,"family":"Copriviza","given":"John","email":"","affiliations":[{"id":40430,"text":"Elkhorn Slough National Estuarine Research 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Safari","active":true,"usgs":false}],"preferred":false,"id":863251,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mayer, Karl A.","contributorId":203504,"corporation":false,"usgs":false,"family":"Mayer","given":"Karl","email":"","middleInitial":"A.","affiliations":[{"id":36639,"text":"University of Wisconsin Zoological Museum, 250 North Mills Street, Madison, WI 53706 (PMH) Sea Otter Research and Conservation Program, Monterey Bay Aquarium, 886 Cannery Row, Monterey, CA 93940","active":true,"usgs":false}],"preferred":false,"id":863252,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research 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A regional water-table map was constructed. Historical water-level data from the USGS National Water Information System (NWIS) database were used to construct water-level hydrographs to show long-term (1917-2014) water-level changes in the Antelope Valley and Fremont Valley groundwater basins.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3420","collaboration":"Prepared in cooperation with the Antelope Valley State Water Contractors Association","usgsCitation":"Dick, M.C., Teague, N.F., 2018, Regional water table in the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014: U.S. Geological Survey Scientific Investigations Map 3420, 2 p., https://doi.org/10.3133/sim3420","productDescription":"Data Release; HTML Document; 2 Sheets: 27.89 × 32.94 inches and 27.89 × 32.94 inches","ipdsId":"IP-075082","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500196,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114336.htm","linkFileType":{"id":5,"text":"html"}},{"id":412692,"rank":6,"type":{"id":18,"text":"Project Site"},"url":"https://ca.water.usgs.gov/projects/antelope-valley/"},{"id":402402,"rank":1,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3420/sim3420_sheet1.pdf","text":"Sheet 1","size":"104 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3420 Sheet 1 of 2","linkHelpText":"- Regional water table in the Antelope Valley and Fremont Valley groundwater basins, southwestern Mojave Desert, California, March 2014"},{"id":402405,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3420/covrthb.jpg"},{"id":402403,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3420/sim3420_sheet2.pdf","text":"Sheet 2","size":"65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3420 Sheet 2 of 2","linkHelpText":"- Regional water-table change in the Antelope Valley and Fremont Valley groundwater basins, southwestern Mojave Desert, California, Spring 1996–2014"},{"id":402404,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3420/versionHist.txt"},{"id":405486,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IQIP0L","text":"Regional water table Contours of the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014","description":"Dick, M.C., Teague, N.F., Fenton, N.C., 2022, Regional water table Contours of the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014: U.S. Geological Survey data release, [available at https://doi.org/10.5066/P9IQIP0L]."}],"country":"United States","state":"California","otherGeospatial":"Mohave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.90567382213953,\n 36.106446138965794\n ],\n [\n -117.90567382213953,\n 34.61990913772064\n ],\n [\n -114.85277111098179,\n 34.61990913772064\n ],\n [\n -114.85277111098179,\n 36.106446138965794\n ],\n [\n -117.90567382213953,\n 36.106446138965794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1: June 2016; Version 2: March 2017; Version. 3: July 2020; Version 4: June 2022","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Ecosystem transformations to altered or novel ecological states are accelerating across the globe. Indicators of ecological resilience to disturbance and resistance to invasion can aid in assessing risks and prioritizing areas for conservation and restoration. The sagebrush biome encompasses parts of 11 western states and is experiencing rapid transformations due to human population growth, invasive species, altered disturbance regimes, and climate change. We built on prior use of static soil moisture and temperature regimes to develop new, ecologically relevant and climate responsive indicators of both resilience and resistance. Our new indicators were based on climate and soil water availability variables derived from process-based ecohydrological models that allow predictions of future conditions. We asked: (1) Which variables best indicate resilience and resistance? (2) What are the relationships among the indicator variables and resilience and resistance categories? (3) How do patterns of resilience and resistance vary across the area? We assembled a large database (n = 24,045) of vegetation sample plots from regional monitoring programs and derived multiple climate and soil water availability variables for each plot from ecohydrological simulations. We used USDA Natural Resources Conservation Service National Soils Survey Information, Ecological Site Descriptions, and expert knowledge to develop and assign ecological types and resilience and resistance categories to each plot. We used random forest models to derive a set of 19 climate and water availability variables that best predicted resilience and resistance categories. Our models had relatively high multiclass accuracy (80% for resilience; 75% for resistance). Top indicator variables for both resilience and resistance included mean temperature, coldest month temperature, climatic water deficit, and summer and driest month precipitation. Variable relationships and patterns differed among ecoregions but reflected environmental gradients; low resilience and resistance were indicated by warm and dry conditions with high climatic water deficits, and moderately high to high resilience and resistance were characterized by cooler and moister conditions with low climatic water deficits. The new, ecologically-relevant indicators provide information on the vulnerability of resources and likely success of management actions, and can be used to develop new approaches and tools for prioritizing areas for conservation and restoration actions.
This 1:24,000-scale geologic map of the Silver Zone Pass quadrangle lies in the southern Toano Range in Elko County, Nevada. Metamorphic and sedimentary strata of the quadrangle range from Neoproterozoic to Permian in age. Important intrusions include the Late Jurassic (ca. 159 Ma) Silver Zone Pass pluton and Cretaceous Toano Spring pluton. In particular, the Silver Zone Pass pluton involves undeformed dikes that crosscut metamorphic foliations and the pluton is associated with pluton-margin anticlines. Interpretation of these characteristics suggests that the pluton was syn-kinematic with respect to metamorphism and strain, thus requiring a phase of Late Jurassic deformation. A Miocene rhyolite lava is of particular interest as one of the few topaz-bearing volcanic rocks in Nevada. A major detachment fault places non-metamorphosed Paleozoic rocks over low-grade Paleozoic and Proterozoic rocks. High-angle normal faults tilted the range in several blocks, and Miocene Humboldt Formation were deposited on, and faulted against, bedrock. Rocks of the Toano Range are bounded by broad valleys on the east and west, with the eastern basin being at much lower elevation than the western basin. Pleistocene lakes, which created distinctive beach deposits, occupied both basins, with Lake Bonneville on the east and Lake Waring on the west. Silver Zone Pass owes its low relief to the enhanced weathering and erosion of the rock within the pass, a granodiorite pluton. The weathering has created some unusual landforms such as tors.
The diffusion of molecular water (H2Om) from the environment into volcanic glass can hydrate the glass up to several wt% at low temperature over long timescales. During this process, the water imprints its hydrogen isotope composition (δDH2O) to the glass (δDgl) offset by a glass-H2O fractionation factor (ΔDgl-H2O = δDgl – δDH2O) which is approximately −33‰ at Earth surface temperatures. Glasses hydrate much more rapidly at higher, sub-magmatic temperatures as they interact with H2O during eruption, transport, and emplacement. To aid in the interpretation of δDgl in natural samples, we present hydrogen isotope results from vapor hydration experiments conducted at 175–375 °C for durations of hours to months using natural volcanic glasses. The results can be divided into two thermal regimes: above 250 °C and below 250 °C. Lower temperature experiments yield raw ΔDgl-H2O values in the range of −33 ± 11‰. Experiments at 225 °C using both positive and negative initial ΔDgl-H2O values converge on this range of values, suggesting this range represents the approximate equilibrium fractionation for H isotopes between glass and H2O vapor (103lnαgl-H2O) below 250 °C. Variation in ΔDgl-H2O (−33 ± 11‰) between different experiments and glasses may arise from incomplete hydration, analytical uncertainty, differences in glass chemistry, and/or subordinate kinetic isotope effects. Experiments above 250 °C yield unexpectedly low δDgl values with ΔDgl-H2O values of ≤–85‰. While alteration alone is incapable of explaining the data, these run products have more extensive surface alteration and are not interpreted to reflect equilibrium fractionation between glass and H2O vapor. Fourier transform infrared spectroscopy (FTIR) shows that glass can hydrate with as much as 5.9 wt% H2Om and 1.0 wt% hydroxl (OH−) in the highest P-T experiment at 375 °C and 21.1 MPa. Therefore, we employ a 1D isotope diffusion–reaction model of glass hydration to evaluate the roles of equilibrium fractionation, isotope diffusion, water speciation reactions internal to the glass, and changing boundary conditions (e.g. alteration and dissolution). At lower temperatures, the best fitting model results to experimental data for low silica rhyolite (LSR) glasses require only an equilibrium fractionation factor and yield 103lnαgl-H2O values of −33‰ ± 5‰ and −25‰ ± 5‰ at 175 °C and 225 °C, respectively. At higher temperatures, ΔDgl-H2O is dominated by boundary layer effects during glass hydration and glass surface alteration. The modeled bulk δDgl value is highly responsive to changes in the δDgl boundary condition regardless of the magnitude of other kinetic effects. Observed glass dissolution and surficial secondary mineral formation are likely to impose a disequilibrium boundary layer that drives extreme δDgl fractionation with progressive glass hydration. These results indicate that the observed ΔDgl-H2O of ∼−33 ± 11‰ can be cautiously applied as an equilibrium 103lnαgl-H2O value to natural silicic glasses hydrated below 250 °C to identify hydration sources. This approximate ΔDgl-H2O may be applicable to even higher temperature glasses hydrated on short timescales (of seconds to minutes) in phreatomagmatic or submarine eruptions before H2O in the glass is primarily affected by boundary layer effects associated with alteration on the glass surface.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2022.09.032","usgsCitation":"Hudak, M.R., Bindeman, I.N., Watkins, J.M., and Lowenstern, J.B., 2022, Hydrogen isotope behavior during rhyolite glass hydration under hydrothermal conditions: Geochimica et Cosmochimica Acta, v. 337, p. 33-48, https://doi.org/10.1016/j.gca.2022.09.032.","productDescription":"16 p.","startPage":"33","endPage":"48","ipdsId":"IP-125992","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2022.09.032","text":"Publisher Index Page"},{"id":411968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"337","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hudak, Michael R. 0000-0002-0583-5424","orcid":"https://orcid.org/0000-0002-0583-5424","contributorId":287589,"corporation":false,"usgs":false,"family":"Hudak","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":861684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":861685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watkins, James M.","contributorId":189286,"corporation":false,"usgs":false,"family":"Watkins","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":861686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":861687,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239744,"text":"70239744 - 2022 - Characterization of a small population of the orangeblack Hawaiian damselfly (Megalagrion xanthomelas) in anchialine pools at Kaloko-Honokōhau National Historical Park, Hawai‘i Island","interactions":[],"lastModifiedDate":"2023-01-16T18:44:21.138296","indexId":"70239744","displayToPublicDate":"2023-01-16T12:31:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5449,"text":"Proceedings of the Hawaiian Entomological Society","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Characterization of a small population of the orangeblack Hawaiian damselfly (Megalagrion xanthomelas) in anchialine pools at Kaloko-Honokōhau National Historical Park, Hawai‘i Island","title":"Characterization of a small population of the orangeblack Hawaiian damselfly (Megalagrion xanthomelas) in anchialine pools at Kaloko-Honokōhau National Historical Park, Hawai‘i Island","docAbstract":"The endangered orangeblack Hawaiian damselfly (Megalagrion xanthomelas) is a lowland inhabitant of freshwater and brackish wetland environments. Formerly one of the most widely distributed native insects in Hawai‘i, it now appears restricted to small populations on the islands of O‘ahu, Moloka‘i, Maui, and Hawai‘i. On Hawai‘i island, anchialine pools provide important habitat for M. xanthomelas, and Kaloko-Honokōhau National Historical Park (Park) supports one of only a few documented populations on the western side of the island. This study aimed to estimate the population size of M. xanthomelas at this Park, characterize its habitat, and identify substrates on which females oviposit eggs. We conducted visual surveys for adult M. xanthomelas at anchialine pools during June 2016–August 2017. On average, the observed population was 10.7 individuals per month (range = 5–20; standard error = 1.3). Males were observed 6.1 times more frequently than females, likely reflecting the less cryptic nature of males compared to females. Females exhibited oviposition behavior on a variety of substrates, but small branches were used most frequently. Factors restricting this population are poorly known, but invasive fish may limit its distribution across the Park. Removal of invasive fishes from anchialine pools and ‘Aimakapā Fishpond may restore much habitat for this rare species in the Park.","language":"English","publisher":"Hawaiian Entomological Society","usgsCitation":"Peck, R., and Nash, S., 2022, Characterization of a small population of the orangeblack Hawaiian damselfly (Megalagrion xanthomelas) in anchialine pools at Kaloko-Honokōhau National Historical Park, Hawai‘i Island: Proceedings of the Hawaiian Entomological Society, v. 54, p. 93-109.","productDescription":"17 p.","startPage":"93","endPage":"109","ipdsId":"IP-142579","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":411961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411957,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/10125/104348"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hawai'i Island, Kaloko-Honokōhau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.03574097933657,\n 19.690219512683953\n ],\n [\n -156.03672808794715,\n 19.68935431489419\n ],\n [\n -156.03424155189794,\n 19.667113870170397\n ],\n [\n -156.0322385926034,\n 19.667409979952993\n ],\n [\n -156.02907150202884,\n 19.668276577239155\n ],\n [\n -156.02753670960968,\n 19.670494777392406\n ],\n [\n -156.016194709686,\n 19.672532283100267\n ],\n [\n -156.01925935377082,\n 19.67807076874334\n ],\n [\n -156.02172677579534,\n 19.687723149358902\n ],\n [\n -156.02455699944343,\n 19.69328357483691\n ],\n [\n -156.03574097933657,\n 19.690219512683953\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":861706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nash, Sarah","contributorId":300993,"corporation":false,"usgs":false,"family":"Nash","given":"Sarah","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":861707,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70255292,"text":"70255292 - 2022 - Inferring hatchery effects using spawner-recruit data: Comment on Courter et al. (2022)","interactions":[],"lastModifiedDate":"2024-06-14T16:23:38.832598","indexId":"70255292","displayToPublicDate":"2023-01-11T11:21:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Inferring hatchery effects using spawner-recruit data: Comment on Courter et al. (2022)","docAbstract":"No abstract available.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0158","usgsCitation":"Falcy, M.R., 2022, Inferring hatchery effects using spawner-recruit data: Comment on Courter et al. (2022): Canadian Journal Fisheries and Aquatic Sciences, v. 80, no. 2, p. 420-421, https://doi.org/10.1139/cjfas-2022-0158.","productDescription":"2 p.","startPage":"420","endPage":"421","ipdsId":"IP-142908","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445601,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2022-0158","text":"Publisher Index Page"},{"id":430216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Falcy, Matthew Richard 0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":904111,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238786,"text":"70238786 - 2022 - The source, fate, and transport of arsenic in the Yellowstone hydrothermal system - An overview","interactions":[],"lastModifiedDate":"2022-12-12T14:28:56.322416","indexId":"70238786","displayToPublicDate":"2023-01-09T08:21:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"The source, fate, and transport of arsenic in the Yellowstone hydrothermal system - An overview","docAbstract":"The Yellowstone Plateau Volcanic Field (YPVF) contains >10,000 thermal features including hot springs, pools, geysers, mud pots, and fumaroles with diverse chemical compositions. Arsenic (As) concentrations in YPVF thermal waters typically range from 0.005 to 4 mg/L, but an As concentration of 17 mg/L has been reported. Arsenic data from thermal springs, outflow drainages, rivers, and from volcanic rocks and silica sinter were used to identify the sources, characterize geochemical and microbial processes affecting As, and quantify As fluvial transport. Arsenic in YPVF thermal waters is mainly derived from high temperature leaching of rhyolites. Arsenic concentrations in thermal waters primarily depend on water type, which is controlled by boiling, evaporation, mixing, and mineral precipitation and dissolution. Springs with low As concentrations include acid-SO4 (0.1 ± 0.1 mg/L), NH4-SO4 rich (0.003 ± 0.007 mg/L), and dilute thermal waters (0.1 ± 0.1 mg/L); travertine-forming waters have moderate As concentrations (0.4 ± 0.2 mg/L); and neutral- Cl waters (1.2 ± 0.8 mg/L) common in the western portion of the Yellowstone Caldera and Cl-rich waters (1.9 ± 1.2 mg/L) primarily from Basins near the Caldera boundary have elevated As concentrations. Reduced As species (arsenite and thiolated-As species) are most prevalent near the orifice of hot springs, and then As rapidly oxidizes to arsenate along drainages. Previously published cultivation-based studies and metagenomic data from microbial communities inhabiting a variety of hot springs indicate a widespread distribution of arsenite oxidation and arsenate reduction capabilities among the hot springs. Widespread use and transformation of As by thermophilic microorganisms promotes more soluble and toxic forms. Most of the water discharged from thermal springs eventually ends up in a nearby river where As remains soluble and exhibits little attenuation during downstream transport. Since 2010, 183 ± 10 metric tons/year of As were transported from Yellowstone National Park (YNP) via rivers. The discharge from YPVF thermal features impairs river water quality whereby As concentrations exceed 10 μg/L for many rivers reaches within and downstream from YNP.
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Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":858703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":858704,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colman, Daniel R. 0000-0002-3253-6833","orcid":"https://orcid.org/0000-0002-3253-6833","contributorId":299802,"corporation":false,"usgs":false,"family":"Colman","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":64955,"text":"Department of Microbiology and Cell Biology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":858705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, David A. 0000-0002-7515-3533 daroth@usgs.gov","orcid":"https://orcid.org/0000-0002-7515-3533","contributorId":2340,"corporation":false,"usgs":true,"family":"Roth","given":"David","email":"daroth@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858706,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Madeline Oxner 0000-0001-7661-9748","orcid":"https://orcid.org/0000-0001-7661-9748","contributorId":299803,"corporation":false,"usgs":true,"family":"Johnson","given":"Madeline","email":"","middleInitial":"Oxner","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":858707,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boyd, Eric S. 0000-0003-4436-5856","orcid":"https://orcid.org/0000-0003-4436-5856","contributorId":299804,"corporation":false,"usgs":false,"family":"Boyd","given":"Eric S.","affiliations":[{"id":64955,"text":"Department of Microbiology and Cell Biology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":858708,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239344,"text":"70239344 - 2022 - Water and endangered fish in the Klamath River Basin: Do Upper Klamath Lake surface elevation and water quality affect adult Lost River and Shortnose Sucker survival?","interactions":[],"lastModifiedDate":"2023-01-10T13:02:51.552487","indexId":"70239344","displayToPublicDate":"2023-01-06T07:00:27","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Water and endangered fish in the Klamath River Basin: Do Upper Klamath Lake surface elevation and water quality affect adult Lost River and Shortnose Sucker survival?","docAbstract":"In the western United States, water allocation decisions often incorporate the needs of endangered fish. In the Klamath River basin, an understanding of temporal variation in annual survival rates of Shortnose Suckers Chasmistes brevirostris and Lost River Suckers Deltistes luxatus and their relation to environmental drivers is critical to water management and sucker recovery. Extinction risk is high for these fish because most individuals in the populations are approaching their maximum life span and recruitment of new fish into the adult populations has never exceeded mortality losses in the past 22 years. We used a time series of mark–recapture data from the years 1999–2021 to analyze the relationship between lake level, water quality covariates, and survival of adult Shortnose Suckers and two spawning populations of Lost River Suckers in Upper Klamath Lake, Oregon. We compared competing model hypotheses in a maximum likelihood framework using Akaike's information criterion and then ran the top environmental covariates in a Bayesian framework to estimate how much of the variation in survival was explained by these covariates as compared to random variation. The complementary analyses found almost unequivocal support for our base model without environmental covariates. Estimated adult sucker survival was high across the time series and consistent with sucker life history (mean annual survival = 0.82–0.91). This suggests that adult suckers were generally robust to interannual variation in lake levels as well as consistently poor water quality within the years of our data set. Recovery time is limited, as a declining survival trend for adult suckers in recent years may be due to the onset of senescence. The successful recovery of suckers in Upper Klamath Lake may rely on shifting research from the causes of adult mortality and its relationship with lake surface elevation to the causes of poor recruitment into adult populations.
This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological dynamics across space, time, or hypothetical scenarios; vetting and distilling raw data for further modeling or analysis; generating and exploring hypotheses; estimating physically or biologically meaningful parameters for use in further modeling; and revealing patterns in complex, multidimensional data or model outputs. An important research frontier is the injection of limnological knowledge into machine-learning models, which has shown great promise for increasing such models’ accuracy, trustworthiness, and interpretability. Here we describe a few of the most powerful machine learning tools, describe best practices for employing these tools and injecting knowledge guidance, and give examples of their applications to advance understanding of inland waters.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of inland waters","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-819166-8.00121-3","usgsCitation":"Appling, A.P., Oliver, S.K., Read, J., Sadler, J.M., and Zwart, J.A., 2022, Machine learning for understanding inland water quantity, quality, and ecology, chap. of Encyclopedia of inland waters, v. 4, p. 585-606, https://doi.org/10.1016/B978-0-12-819166-8.00121-3.","productDescription":"22 p.","startPage":"585","endPage":"606","ipdsId":"IP-122850","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":445607,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.31223/x5964s","text":"External Repository"},{"id":411277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Mehner, Thomas","contributorId":272917,"corporation":false,"usgs":false,"family":"Mehner","given":"Thomas","email":"","affiliations":[{"id":38332,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":860710,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Tockner, Klement","contributorId":224174,"corporation":false,"usgs":false,"family":"Tockner","given":"Klement","email":"","affiliations":[{"id":40838,"text":"FWF Austrian Science Fund","active":true,"usgs":false}],"preferred":false,"id":860711,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":860690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":860692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sadler, Jeffrey Michael 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":260092,"corporation":false,"usgs":true,"family":"Sadler","given":"Jeffrey","email":"","middleInitial":"Michael","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":860693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":860694,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239174,"text":"70239174 - 2022 - Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA","interactions":[],"lastModifiedDate":"2023-01-02T19:23:03.108814","indexId":"70239174","displayToPublicDate":"2023-01-02T13:16:33","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA","docAbstract":"The 2002 M 7.9 Denali earthquake in Alaska, USA, was the largest inland earthquake in North America in nearly 150 years. The earthquake involved oblique thrusting but mostly strike-slip motion, and faults ruptured the ground surface over 330 km. Fault rupture occurred in a rugged, mountainous, subarctic environment with extensive permafrost and variable glaciation, geology, and groundwater presence, and many triggered landslides mobilized into avalanches that traversed varied physiographic settings, some moving farther than 11 km. However, only several thousand landslides were triggered, and these occurred in a narrow zone along the fault rupture. These characteristics of the event provide ample opportunities to improve understanding of controls on coseismic landsliding and avalanching mechanisms. The paucity and limited extent of landslides likely resulted from high directivity of seismic energy and relatively low levels of high-amplitude, high-frequency ground motion; glacial damping of seismic energy was likely not a factor. Landslides preferentially occurred on hillslopes steeper and higher than average. Meteorological conditions were near historical averages at the time of the event, although the region has experienced gradual warming historically that appears to have resulted in increased landslide occurrence in other parts of Alaska during recent years. Inherent susceptibility of geological formations to landsliding was not apparent with the available data, although discontinuities created dip-slope conditions for the five largest slides. Historical thinning of glaciers and consequent slope debuttressing may have been a factor in aiding occurrence of some of the earthquake-induced landslides, particularly some of the largest. Mobility of the largest avalanches was above average compared to global data, and mobility of all sizes of avalanches was apparently aided by movement over glacial ice. Avalanche deposits displayed characteristics indicative of turbulent flow on steeper slopes and laminar plug flow in flatter areas, where sliding also likely occurred.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coseismic landslides: Phenomena, long-term effects and mitigation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-981-19-6597-5_4","usgsCitation":"Schulz, W.H., 2022, Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA, chap. of Coseismic landslides: Phenomena, long-term effects and mitigation, p. 83-114, https://doi.org/10.1007/978-981-19-6597-5_4.","productDescription":"32 p.","startPage":"83","endPage":"114","ipdsId":"IP-118114","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411276,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Denali Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.29368601014386,\n 59.11878225343841\n ],\n [\n -156.0264002993337,\n 58.779813559186465\n ],\n [\n -152.25996460189066,\n 61.06590743096231\n ],\n [\n -149.1643813809494,\n 62.16054388876884\n ],\n [\n -140.9851481053823,\n 61.673553940907254\n ],\n [\n -140.98590984229733,\n 63.075995036970994\n ],\n [\n -148.91306197242972,\n 64.36320333772588\n ],\n [\n -155.3934657440926,\n 62.81575979286217\n ],\n [\n -159.29368601014386,\n 59.11878225343841\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-11-04","publicationStatus":"PW","contributors":{"editors":[{"text":"Towhata, Ikuo","contributorId":300539,"corporation":false,"usgs":false,"family":"Towhata","given":"Ikuo","email":"","affiliations":[],"preferred":false,"id":860706,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Wang, Gonghui","contributorId":99452,"corporation":false,"usgs":true,"family":"Wang","given":"Gonghui","affiliations":[],"preferred":false,"id":860707,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Xu, Qiang","contributorId":214818,"corporation":false,"usgs":false,"family":"Xu","given":"Qiang","email":"","affiliations":[{"id":39123,"text":"Key Laboratory of Continental Collision and Plateau Uplift, Institute of Tibetan Plateau Research and Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":860708,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Massey, Chris","contributorId":206127,"corporation":false,"usgs":false,"family":"Massey","given":"Chris","email":"","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":860709,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":860684,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239182,"text":"70239182 - 2022 - Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature","interactions":[],"lastModifiedDate":"2023-01-02T19:15:38.169222","indexId":"70239182","displayToPublicDate":"2023-01-02T13:08:22","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature","docAbstract":"This paper proposes a new data-driven method for predicting water temperature in stream networks with reservoirs. The water flows released from reservoirs greatly affect the water temperature of downstream river segments. However, the information of released water flow is often not available for many reservoirs, which makes it difficult for data-driven models to capture the impact to downstream river segments. In this paper, we first build a state-aware graph model to represent the interactions amongst streams and reservoirs, and then propose a parallel learning structure to extract the reservoir release information and use it to improve the prediction. In particular, for reservoirs with no available release information, we mimic the water managers' release decision process through a pseudo-prospective learning method, which infers the release information from anticipated water temperature dynamics. For reservoirs with the release information, we leverage a physics-based model to simulate the water release temperature and transfer such information to guide the learning process for other reservoirs. The evaluation for the Delaware River Basin shows that the proposed method brings over 10% accuracy improvement over existing data-driven models for stream temperature prediction when the release data is not available for any reservoirs. The performance is further improved after we incorporate the release data and physical simulations for a subset of reservoirs.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 2022 SIAM International Conference on Data Mining (SDM)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2022 SIAM International Conference on Data Mining (SDM)","conferenceDate":"April 28-30, 2022","conferenceLocation":"Alexandria, Virginia, United States","language":"English","publisher":"Society for Industrial and Applied Mathematics","doi":"10.1137/1.9781611977172.11","usgsCitation":"Jia, X., Chen, S., Xie, Y., Yang, H., Appling, A.P., Oliver, S.K., and Jiang, Z., 2022, Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature, in Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), Alexandria, Virginia, United States, April 28-30, 2022, p. 91-99, https://doi.org/10.1137/1.9781611977172.11.","productDescription":"9 p.","startPage":"91","endPage":"99","ipdsId":"IP-134356","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":445610,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/2202.05714","text":"External Repository"},{"id":411275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-04-20","publicationStatus":"PW","contributors":{"editors":[{"text":"Banerjee, Arindam","contributorId":300535,"corporation":false,"usgs":false,"family":"Banerjee","given":"Arindam","email":"","affiliations":[],"preferred":false,"id":860702,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Zhou, Zhi-Hua","contributorId":300536,"corporation":false,"usgs":false,"family":"Zhou","given":"Zhi-Hua","email":"","affiliations":[],"preferred":false,"id":860703,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Papalexakis, Evangelos E.","contributorId":300537,"corporation":false,"usgs":false,"family":"Papalexakis","given":"Evangelos","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":860704,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Riondato, Matteo","contributorId":300538,"corporation":false,"usgs":false,"family":"Riondato","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":860705,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":860695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Shengyu","contributorId":297452,"corporation":false,"usgs":false,"family":"Chen","given":"Shengyu","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":860696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":860697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yang, Haoyu","contributorId":298611,"corporation":false,"usgs":false,"family":"Yang","given":"Haoyu","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":860698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":860699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jiang, Zhe","contributorId":267317,"corporation":false,"usgs":false,"family":"Jiang","given":"Zhe","email":"","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":860701,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230419,"text":"70230419 - 2022 - Ground motion selection for nonlinear response history analyses of concrete dams","interactions":[],"lastModifiedDate":"2023-05-16T18:48:59.636551","indexId":"70230419","displayToPublicDate":"2022-12-31T13:45:28","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Ground motion selection for nonlinear response history analyses of concrete dams","docAbstract":"Evaluating the seismic performance of a 3D concrete dam using nonlinear response history analysis (NLRHA) requires three orthogonal components of ground acceleration histories, or ground motions (GMs) for brevity. Although much progress has been made for the topic of ground motion selection and modification (GMSM) in the context of multistory buildings, NLRHA of dams requires at least two additional considerations: (i) accounting for multiple modes of vibration and (ii) including three orthogonal components of GMs. To convey the key ideas in developing an ensemble of multicomponent GMs for this context, the fundamentals of GMSM are first briefly reviewed using a case study. Then, special considerations for concrete dams are highlighted. Finally, a practical method for developing target spectra and selecting multicomponent GMs is presented.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2022 USSD annual conference & exhibition","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"United States Society on Dams (USSD)","usgsCitation":"Kwong, N.S., 2022, Ground motion selection for nonlinear response history analyses of concrete dams, in 2022 USSD annual conference & exhibition, 15 p.","productDescription":"15 p.","ipdsId":"IP-135268","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":417105,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398526,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ussd.conferencespot.org/2022/bio/bmt3b25ndXNnc2dvdg%3D%3D","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. 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The sites include both previously-oiled and un-oiled locations that were the subject of repeated annual photos beginning in 1990, one year after the March 24, 1989 Exxon Valdez Oil Spill. Photos from summer 2021 were compared with those available from the previous 31 years, visually revealing multi-year cycles of variation in the cover of dominant intertidal community organisms, mainly rockweed (Fucus distichus) and mussels (Mytilus trossulus). The repeated photos, together with basic time series graphs of percent cover estimated from many photos, provide a visual sense of major year-to-year variations in the cover of rockweed, mussels and to some extent, barnacles. In summer 2021 the cover of rockweed at five of the seven sites was low compared to recent previous years. The entire photo-timeseries shows that during the last three decades there have been four or five episodes of growth and senescence of rockweed and mussels. This variability shows how difficult it is to define “recovery” and supports the idea that recovery is a return to the natural range of variability, not necessarily the condition that prevailed immediately before the disturbance.","largerWorkTitle":"Proceedings of the forty-forth AMOP technical seminar","language":"English","publisher":"Environment and Climate Change Canada","usgsCitation":"Mearns, A., Janka, D., Pegau, S., Campbell, R., and Robinson, B.H., 2022, Three-decades of Rocky Intertidal Photo Series Documenting interannual variability in western Prince William Sound, in Proceedings of the forty-forth AMOP technical seminar, v. 44, p. 230-242.","productDescription":"13 p.","startPage":"230","endPage":"242","ipdsId":"IP-139662","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":426034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mearns, Alan","contributorId":316283,"corporation":false,"usgs":false,"family":"Mearns","given":"Alan","email":"","affiliations":[{"id":68546,"text":"NOAA - Retired","active":true,"usgs":false}],"preferred":false,"id":877305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janka, Dave","contributorId":316284,"corporation":false,"usgs":false,"family":"Janka","given":"Dave","email":"","affiliations":[{"id":68547,"text":"Auklet Charter Services","active":true,"usgs":false}],"preferred":false,"id":877306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pegau, Scott","contributorId":316285,"corporation":false,"usgs":false,"family":"Pegau","given":"Scott","email":"","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":877307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Robert","contributorId":316286,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":877308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robinson, Brian H. 0000-0001-8588-7162 brobinson@usgs.gov","orcid":"https://orcid.org/0000-0001-8588-7162","contributorId":191406,"corporation":false,"usgs":true,"family":"Robinson","given":"Brian","email":"brobinson@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":877309,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236479,"text":"70236479 - 2022 - Assessing the efficacy of oblique bubble screens for control of aquatic invasive species","interactions":[],"lastModifiedDate":"2024-02-22T17:08:42.891975","indexId":"70236479","displayToPublicDate":"2022-12-31T11:06:29","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Assessing the efficacy of oblique bubble screens for control of aquatic invasive species","docAbstract":"Non-physical barriers, such as bubble screens (or curtains), are promising low-impact strategies to deter the spread of Aquatic Invasive Species (AIS) in streams. Bubble screens have been successfully implemented to redirect and/or deter adult fish and to capture plastics in some rivers, but their efficacy on invasive fish at multiple life stages (eggs, larvae, and adult fish) is not yet known. Air bubbles rising from a diffuser placed at the bottom of a stream generate counterrotating eddies that interact with the mean flow. Understanding such interactions allows us to design an Oblique Bubble Screen (OBS), a system able to direct drifting particles (i.e., eggs and larvae) towards the banks of a stream for potential capture, based on the water velocity, river morphology, orientation of the OBS, diffuser material, and air flow rate. We present the results from a series of laboratory experiments at the Ecohydraulics and Ecomorphodynamics Laboratory at the University of Illinois at Urbana-Champaign, using positively buoyant (specific gravity SG=0.9, and diameter d=7.09mm) and negatively buoyant (SG=1.04, d=5.9mm) spherical particles to represent the range of size and density of developing Grass carp eggs, an invasive species in North America (Ctenopharyngodon idella). An air compressor was connected to a porous tube laid at the bottom of a recirculating flume, with a regulator and a flow meter to control air pressure and air flow rate. Acoustic Doppler Velocimeters (ADV) and Surface Particle Image Velocimetry (PIV) were used to measure the effect of the OBS on the velocity field. Our collected data showed that: (1) a single OBS is able to direct drifting particles towards the bank at the downstream end of the OBS, (2) adjusting orientation angle and air flow rate of the diffuser can increase capture efficacy under different flow conditions, reaching up to a 100% of capture for buoyant particles, and (3) the ratio between lateral velocity generated by the OBS (as a function of air flow rate) and the mean longitudinal flow velocities, can be used as an indicator to predict whether the OBS will be able to carry the particles all along the length of the diffuser in wider and deeper streams. The optimal configurations from our study will be tested with live Grass carp eggs and larvae, as well as with upstream-swimming adult carp to assess its potential as a two-way barrier, and to provide design parameters to set the air-flow rate and diffuser type needed for field deployments, according to width-to-depth ratios and stream morphology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 39th IAHR World Congress, Granada, Spain","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Association for Hydro-Environment Engineering and Research","doi":"10.3850/IAHR-39WC2521711920221833","usgsCitation":"Prasad, V., Suski, C., Jackson, P.R., George, A.E., Chapman, D., Fischer, J., and Tinoco, R.O., 2022, Assessing the efficacy of oblique bubble screens for control of aquatic invasive species, in Proceedings of the 39th IAHR World Congress, Granada, Spain, v. 39, p. 1565-1570, https://doi.org/10.3850/IAHR-39WC2521711920221833.","productDescription":"6 p.","startPage":"1565","endPage":"1570","ipdsId":"IP-135122","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":445612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3850/iahr-39wc2521711920221833","text":"Publisher Index Page"},{"id":425879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Prasad, Vindhyawasini 0000-0003-0585-7217","orcid":"https://orcid.org/0000-0003-0585-7217","contributorId":296287,"corporation":false,"usgs":false,"family":"Prasad","given":"Vindhyawasini","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":851177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suski, C. D.","contributorId":190151,"corporation":false,"usgs":false,"family":"Suski","given":"C.","middleInitial":"D.","affiliations":[],"preferred":false,"id":851178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. 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The 45 locations sampled were long-term monitoring sites that had been annually sampled since 1978. All comparisons to 2021 results were limited to past collections from USA waters, as compared to previous years, where comparisons included USA and Canadian sites. In 2021, the number of species collected at each site ranged from 0 to 15, with a median of 5 species. Average fish biomass was 6.3 kg/ha, which was higher than the average observed over the past 10 years (4.7 kg/ha), similar to the average observed from 2001-10 (6.7 kg/ha), and less than the averages observed in 1991-2000 (14.8 kg/ha), and 1981-1990 (11.9 kg/ha), but higher than the average from 1978-1980 (5.2 kg/ha). Average biomass in 2021 was highest for Lake Whitefish (Coregonus clupeaformis, 3.2 kg/ha), Bloater (C. hoyi, 1.4 kg/ha), Rainbow Smelt (Osmerus mordax, 0.5 kg/ha), and Cisco (C. artedi, 0.3 kg/ha). Coregonus spp. year-class strength, as measured by densities of age-1 fish, was 8 fish/ha for Bloater, 11 fish/ha for Cisco, and 41 fish/ha for Lake Whitefish. The age-1 Bloater estimate was in the range observed for the 2014, 2015, and 2016 year-classes (7-9 age-1 fish/ha) and greater than that observed in other years over the past decade (<1 age-1 fish/ha). The age-1 Cisco estimate was the highest estimate since the 2009 year-class. Average Lake Whitefish age-1 density was the second highest estimate observed over the past 44-years. Cisco survival to age-1 has been low since 2009 and near zero since the 2014- and 2015-year classes. This lack of survival has yet to be adequately explained and continues to be a major concern of fishery managers due to Cisco’s importance in ecosystem dynamics and value to the commercial fishery.
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Center","active":true,"usgs":true}],"preferred":true,"id":863413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yule, Daniel L. 0000-0002-0117-5115","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":248693,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evrard, Lori M. 0000-0001-8582-5818 levrard@usgs.gov","orcid":"https://orcid.org/0000-0001-8582-5818","contributorId":2720,"corporation":false,"usgs":true,"family":"Evrard","given":"Lori","email":"levrard@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman, Owen T. 0000-0003-0451-110X","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":302070,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, Sydney B 0000-0003-0179-6533","orcid":"https://orcid.org/0000-0003-0179-6533","contributorId":302071,"corporation":false,"usgs":true,"family":"Phillips","given":"Sydney","email":"","middleInitial":"B","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":863417,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240325,"text":"70240325 - 2022 - Status and trends in the Lake Superior fish community, 2020","interactions":[],"lastModifiedDate":"2023-03-30T16:34:40.032501","indexId":"70240325","displayToPublicDate":"2022-12-31T10:48:06","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Status and trends in the Lake Superior fish community, 2020","docAbstract":"The Lake Superior fish community within Management Unit WI-2 was sampled in July 2020 with daytime bottom trawls at 11 nearshore stations. The 11 locations sampled were long-term monitoring sites that had been annually sampled since 1974. In 2020, the number of species collected at each site ranged from 0 to 13, with a mean of 6.3 and median of six. All comparisons to 2020 results were limited to past collections from Management Unit WI-2. Mean total biomass was 10.5 kg/ha which was similar to the average observed over the past 10 years (10.3 kg/ha), less than averages over the past 20 and 30-years, 15.3 and 19.8 kg/ha respectively, and higher than the average observed from 1974-84 (4.7 kg/ha). Average biomass in 2020 was highest for Bloater (6.2 kg/ha), Lake Whitefish (2.3 kg/ha), and Cisco (0.9 kg/ha). Rainbow Smelt biomass averaged 0.3 kg/ha. Year-class strength, as measured by age-1 densities, was well below the 5, 10, and 25-year averages for Bloater, Cisco, Lake Whitefish and Rainbow Smelt. Bloater averaged 1 age-1 fish/ha, Cisco, 0.2 age-1 fish/ha, Lake Whitefish, 15 age-1 fish/ha, and Rainbow Smelt 6 age-1 fish/ha. Cisco survival to age-1 has been near non-existent since the 2014- and 2015-year classes and the last moderate sized year class was in 2009. This lack of survival has yet to be adequately explained and continues to be a major concern of fishery managers due to Cisco’s importance in ecosystem dynamics and value to the commercial fishery.","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Vinson, M., Evrard, L.M., Gorman, O., and Yule, D.L., 2022, Status and trends in the Lake Superior fish community, 2020, 21 p.","productDescription":"21 p.","ipdsId":"IP-128615","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":412747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412746,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/publication-media-search.php","linkFileType":{"id":5,"text":"html"}}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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