Incubating birds must balance the needs of their developing embryos with their own physiological needs, and many birds accomplish this by taking periodic breaks from incubation. Mallard (Anas platyrhynchos) and gadwall (Mareca strepera) hens typically take incubation recesses in the early morning and late afternoon, but recesses can also take place at night. We examined nocturnal incubation recess behavior for mallard and gadwall hens nesting in Suisun Marsh, California, USA, using iButton temperature dataloggers and continuous video monitoring at nests. Fourteen percent of all detected incubation recesses (N = 13,708) were nocturnal and took place on 20% of nest‐days (N = 8,668). Video monitoring showed that hens covered their eggs with down feathers when they initiated a nocturnal recess themselves as they would a diurnal recess, but they left the eggs uncovered in 94% of the nocturnal recesses in which predators appeared at nests. Thus, determining whether or not eggs were left uncovered during a recess can provide strong indication whether the recess was initiated by the hen (eggs covered) or a predator (eggs uncovered). Because nest temperature decreased more rapidly when eggs were left uncovered versus covered, we were able to characterize eggs during nocturnal incubation recesses as covered or uncovered using nest temperature data. Overall, we predicted that 75% of nocturnal recesses were hen‐initiated recesses (eggs covered) whereas 25% of nocturnal recesses were predator‐initiated recesses (eggs uncovered). Of the predator‐initiated nocturnal recesses, 56% were accompanied by evidence of depredation at the nest during the subsequent nest monitoring visit. Hen‐initiated nocturnal recesses began later in the night (closer to morning) and were shorter than predator‐initiated nocturnal recesses. Our results indicate that nocturnal incubation recesses occur regularly (14% of all recesses) and, similar to diurnal recesses, most nocturnal recesses (75%) are initiated by the hen rather than an approaching predator.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7561","usgsCitation":"Croston, R., Peterson, S.H., Hartman, C.A., Herzog, M.P., Feldheim, C.L., Casazza, M.L., and Ackerman, J.T., 2021, Nocturnal incubation recess and flushing behavior by duck hens: Ecology and Evolution, v. 11, no. 12, p. 7292-7301, https://doi.org/10.1002/ece3.7561.","productDescription":"10 p.","startPage":"7292","endPage":"7301","ipdsId":"IP-122856","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":452473,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7561","text":"Publisher Index Page"},{"id":436386,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XG4KSK","text":"USGS data release","linkHelpText":"Nocturnal Incubation Recess and Flushing Behavior by Duck Hens Nesting in Grizzly Island Wildlife Area 2015-2018"},{"id":385762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Croston, Rebecca 0000-0003-4696-0878","orcid":"https://orcid.org/0000-0003-4696-0878","contributorId":256911,"corporation":false,"usgs":false,"family":"Croston","given":"Rebecca","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":815973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feldheim, Cliff L.","contributorId":206561,"corporation":false,"usgs":false,"family":"Feldheim","given":"Cliff","email":"","middleInitial":"L.","affiliations":[{"id":37342,"text":"California Department of Water Resources","active":true,"usgs":false}],"preferred":false,"id":815977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815978,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815979,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224283,"text":"70224283 - 2021 - Habitat heterogeneity, temperature, and primary productivity drive elevational gradients in avian species diversity","interactions":[],"lastModifiedDate":"2021-09-20T13:03:59.742321","indexId":"70224283","displayToPublicDate":"2021-05-01T08:02:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Habitat heterogeneity, temperature, and primary productivity drive elevational gradients in avian species diversity","docAbstract":"Anticipating and mitigating the impacts of climate change on species diversity in montane ecosystems requires a mechanistic understanding of drivers of current patterns of diversity. We documented the shape of elevational gradients in avian species richness in North America and tested a suite of a priori predictions for each of five mechanistic hypotheses to explain those patterns.
United States
We used predicted occupancy maps generated from species distribution models for each of 646 breeding birds to document elevational patterns in avian species richness across the six largest U.S. mountain ranges. We used spatially explicit biotic and abiotic data to test five mechanistic hypotheses proposed to explain geographic variation in species richness.
Elevational gradients in avian species richness followed a consistent pattern of low elevation plateau-mid-elevation peak (as per McCain, 2009). We found support for three of the five hypotheses to explain the underlying cause of this pattern: the habitat heterogeneity, temperature, and primary productivity hypotheses.
Species richness typically decreases with elevation, but the primary cause and precise shape of the relationship remain topics of debate. We used a novel approach to study the richness-elevation relationship and our results are unique in that they show a consistent relationship between species richness and elevation among 6 mountain ranges, and universal support for three hypotheses proposed to explain the underlying cause of the observed relationship. Taken together, these results suggest that elevational variation in food availability may be the ecological process that best explains elevational gradients in avian species richness in North America. Although much attention has focused on the role of abiotic factors, particularly temperature, in limiting species’ ranges, our results offer compelling evidence that other processes also influence (and may better explain) elevational gradients in species richness.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7341","usgsCitation":"Dillon, K., and Conway, C.J., 2021, Habitat heterogeneity, temperature, and primary productivity drive elevational gradients in avian species diversity: Ecology and Evolution, v. 11, no. 11, p. 5985-5997, https://doi.org/10.1002/ece3.7341.","productDescription":"13 p.","startPage":"5985","endPage":"5997","ipdsId":"IP-105630","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":452474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.7341","text":"Publisher Index Page"},{"id":389477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dillon, Kristen G.","contributorId":265813,"corporation":false,"usgs":false,"family":"Dillon","given":"Kristen G.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":823449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":823448,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211231,"text":"70211231 - 2021 - Maximizing the science and resource mapping potential of Orbital VSWIR Spectral measurements of Mars","interactions":[],"lastModifiedDate":"2021-10-12T15:16:37.057653","indexId":"70211231","displayToPublicDate":"2021-04-30T10:10:46","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9373,"text":"Bulletin of the AAS","active":true,"publicationSubtype":{"id":1}},"title":"Maximizing the science and resource mapping potential of Orbital VSWIR Spectral measurements of Mars","docAbstract":"The last 16 years witnessed a rapid growth in understanding the composition and aqueous alteration of Mars’ surface from orbital data from the Observatoire pour la Mineralogie, l’Eau, les Glaces et l’Activité (OMEGA) [1] and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) [2]. Both are sensitive to water-, hydroxyl-, sulfate-, and carbonate-bearing and ferric phases that record past liquid water. As the spatial resolution of such data has improved, and supporting laboratory data have been acquired, the diversity of mineral phases that are recognized has likewise expanded. The same phases typically contain recoverable water, a resource for future human exploration, and are the only near-surface water reservoir in the >50% of Mars over which ice likely does not occur in the shallowest subsurface. Knowledge of the distribution and abundance of these water-bearing phases, and their geologic implications, is limited by spatial resolution of the available data. A revolutionary advance in understanding the inventory, diversity, and stratigraphy of these materials can be obtained from Mars orbit, using two complementary approaches: hyperspectral imaging at ~6 meters per pixel at 0.7–4 µm, and 1 meter-per-pixel imaging at selected VSWIR wavelengths from 0.4–1.7 µm.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planetary science and astrobiology decadal survey 2023-2032","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"National Academy of Sciences","doi":"10.3847/25c2cfeb.7da7980b","usgsCitation":"Murchie, S.L., Arvidson, R.E., Bishop, J., Calvin, W.M., Carter, J., Christian, J., Clark, R., Dundas, C.M., Ehlmann, B.L., Fox, V.K., Fraeman, A.A., Goudge, T.A., Horgan, B.H., Hughes, M.N., Leask, E.K., McEwen, A.S., Mustard, J., Parente, M., Powell, K.E., Seelos, F.P., Seelos, K.D., Tarnas, J.D., Viviano, C.E., and Wray, J.J., 2021, Maximizing the science and resource mapping potential of Orbital VSWIR Spectral measurements of Mars: Bulletin of the AAS, v. 53, no. 4, Whitepaper #119, 8 p., https://doi.org/10.3847/25c2cfeb.7da7980b.","productDescription":"Whitepaper #119, 8 p.","ipdsId":"IP-119870","costCenters":[{"id":131,"text":"Astrogeology Science 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E.","contributorId":106626,"corporation":false,"usgs":false,"family":"Arvidson","given":"Raymond","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":793293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Janice L","contributorId":156315,"corporation":false,"usgs":false,"family":"Bishop","given":"Janice L","affiliations":[{"id":20310,"text":"SETI Institute, 89 Bernardo Ave, Suite 100, Mountain View, CA, USA 94043","active":true,"usgs":false}],"preferred":false,"id":793294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calvin, Wendy M. 0000-0002-6097-9586","orcid":"https://orcid.org/0000-0002-6097-9586","contributorId":189159,"corporation":false,"usgs":false,"family":"Calvin","given":"Wendy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":793295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carter, John","contributorId":189157,"corporation":false,"usgs":false,"family":"Carter","given":"John","email":"","affiliations":[],"preferred":false,"id":793296,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Christian, John","contributorId":229473,"corporation":false,"usgs":false,"family":"Christian","given":"John","affiliations":[{"id":37383,"text":"Washington University","active":true,"usgs":false}],"preferred":false,"id":793297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clark, Roger N.","contributorId":225047,"corporation":false,"usgs":false,"family":"Clark","given":"Roger N.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":793298,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dundas, Colin M. 0000-0003-2343-7224 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Sciences, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":793301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fraeman, Abigail A.","contributorId":200404,"corporation":false,"usgs":false,"family":"Fraeman","given":"Abigail","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":793302,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Goudge, Timothy A","contributorId":229474,"corporation":false,"usgs":false,"family":"Goudge","given":"Timothy","email":"","middleInitial":"A","affiliations":[{"id":41655,"text":"U. 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Growing evidence indicates that much of this ice is relatively pure, exists within a few meters of the surface, and reaches lower latitudes than previously thought, potentially providing an accessible record of the recent climate and a large in situ resource for future human exploration of Mars. We are reaching the limits of currently available datasets, however, just as we are starting to unlock the climate record and determine the water resources contained within the Martian mid-latitudes. A comprehensive understanding of the nature of this ice would significantly enhance our understanding of Mars’ climate history and total water budget, as well as the effects of orbital/axial forcing on volatiles. In this regard, Mars is a testbed for comparative planetary climate studies, including for exoplanets; these studies are particularly valuable because Mars has many similarities to Earth but lacks the complicating effects of oceans and a biosphere, such that orbital/axial forcing dominates climate variability.
Quantifying the volumes, distribution, and properties of the water ice are crucial for addressing two overarching questions in the next decade:
1. What climate record is preserved in mid-latitude ice deposits on Mars?
2. How accessible is the ice as a resource for future exploration?
New missions will enable us to capitalize on the major discoveries of the last decade and take the next giant leap in the upcoming decade to address these questions.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planetary science and astrobiology decadal survey 2023-2032","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"National Academy of Sciences","doi":"10.3847/25c2cfeb.cc90422d","usgsCitation":"Bramson, A., Andres, C., Bapst, J., Becerra, P., Courville, S.W., Dundas, C.M., Hibbard, S.M., Holt, J.W., Karunatillake, S., Khuller, A., Mellon, M.T., Morgan, G.A., Obbard, R.W., Perry, M.R., Petersen, E.I., Putzig, N.E., Sizemore, H.G., Smith, I.B., Stillman, D.E., and Wooster, P., 2021, Mid-latitude ice on Mars: A science target for planetary climate histories and an exploration target for in situ resources: Bulletin of the AAS, v. 53, no. 4, Whitepaper #115, 8 p., https://doi.org/10.3847/25c2cfeb.cc90422d.","productDescription":"Whitepaper #115, 8 p.","ipdsId":"IP-120079","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":452514,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/25c2cfeb.cc90422d","text":"Publisher Index Page"},{"id":390418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"53","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Bramson, Ali","contributorId":189477,"corporation":false,"usgs":false,"family":"Bramson","given":"Ali","email":"","affiliations":[],"preferred":false,"id":793316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andres, Chimira","contributorId":229481,"corporation":false,"usgs":false,"family":"Andres","given":"Chimira","email":"","affiliations":[{"id":41656,"text":"U. 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Western Ontario","active":true,"usgs":false}],"preferred":false,"id":793322,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holt, John W 0000-0003-1314-7848","orcid":"https://orcid.org/0000-0003-1314-7848","contributorId":237030,"corporation":false,"usgs":false,"family":"Holt","given":"John","email":"","middleInitial":"W","affiliations":[{"id":27205,"text":"U. Arizona","active":true,"usgs":false}],"preferred":false,"id":825047,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Karunatillake, Suniti","contributorId":229485,"corporation":false,"usgs":false,"family":"Karunatillake","given":"Suniti","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":793323,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Khuller, Aditya","contributorId":229486,"corporation":false,"usgs":false,"family":"Khuller","given":"Aditya","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":793324,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mellon, Michael T.","contributorId":8603,"corporation":false,"usgs":false,"family":"Mellon","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7037,"text":"Southwest Research Institute, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":793325,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Morgan, Gareth A 0000-0002-9513-8736","orcid":"https://orcid.org/0000-0002-9513-8736","contributorId":229487,"corporation":false,"usgs":false,"family":"Morgan","given":"Gareth","email":"","middleInitial":"A","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":793326,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Obbard, R. W.","contributorId":241754,"corporation":false,"usgs":false,"family":"Obbard","given":"R.","email":"","middleInitial":"W.","affiliations":[{"id":37319,"text":"SETI Institute","active":true,"usgs":false}],"preferred":false,"id":825048,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Perry, Matthew R","contributorId":229488,"corporation":false,"usgs":false,"family":"Perry","given":"Matthew","email":"","middleInitial":"R","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":793327,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Petersen, Eric I","contributorId":229489,"corporation":false,"usgs":false,"family":"Petersen","given":"Eric","email":"","middleInitial":"I","affiliations":[{"id":41657,"text":"U. Arizona / U. Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":793328,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Putzig, Nathaniel E. 0000-0003-4485-6321","orcid":"https://orcid.org/0000-0003-4485-6321","contributorId":208684,"corporation":false,"usgs":true,"family":"Putzig","given":"Nathaniel","email":"","middleInitial":"E.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":793329,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sizemore, Hanna G 0000-0002-6641-2388","orcid":"https://orcid.org/0000-0002-6641-2388","contributorId":229472,"corporation":false,"usgs":false,"family":"Sizemore","given":"Hanna","email":"","middleInitial":"G","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":793330,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Smith, Isaac B.","contributorId":200695,"corporation":false,"usgs":false,"family":"Smith","given":"Isaac","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":793331,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Stillman, David E","contributorId":141053,"corporation":false,"usgs":false,"family":"Stillman","given":"David","email":"","middleInitial":"E","affiliations":[{"id":13664,"text":"Southwest Research Institute, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":793332,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wooster, Paul","contributorId":229490,"corporation":false,"usgs":false,"family":"Wooster","given":"Paul","email":"","affiliations":[{"id":41658,"text":"Space Exploration Corporation","active":true,"usgs":false}],"preferred":false,"id":793333,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70227011,"text":"70227011 - 2021 - The Preventing Harassment in Science workshop: Summary and best practices for planetary science and astrobiology","interactions":[],"lastModifiedDate":"2021-12-27T15:28:05.536378","indexId":"70227011","displayToPublicDate":"2021-04-30T09:13:52","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9373,"text":"Bulletin of the AAS","active":true,"publicationSubtype":{"id":1}},"title":"The Preventing Harassment in Science workshop: Summary and best practices for planetary science and astrobiology","docAbstract":"The NASA-funded Preventing Harassment in Science workshop took place in June of 2020. Here we describe the workshop and summarize the best practices for reducing harassment that were discussed. We include a list of recommendations that can be used to take steps towards reducing harassment in the planetary science and astrobiology community.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planetary science and astrobiology decadal survey 2023-2032","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"National Academy of Sciences","doi":"10.3847/25c2cfeb.2b4fd379","usgsCitation":"Bennett, K.A., McAdam, M., Milazzo, M., Garcia, P.A., Shelton, J., Gardiner, P.J., Diniega, S., Martinez, C., Etheridge, A.B., Rutledge, A., and Richey, C., 2021, The Preventing Harassment in Science workshop: Summary and best practices for planetary science and astrobiology: Bulletin of the AAS, v. 53, no. 4, Whitepaper #474, 8 p., https://doi.org/10.3847/25c2cfeb.2b4fd379.","productDescription":"Whitepaper #474, 8 p.","ipdsId":"IP-122198","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":452523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/25c2cfeb.2b4fd379","text":"Publisher 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Moses","contributorId":270380,"corporation":false,"usgs":false,"family":"Milazzo","given":"Moses","affiliations":[{"id":56159,"text":"OtherOrb","active":true,"usgs":false}],"preferred":false,"id":829191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Patricia A. 0000-0002-9857-5835 pgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-9857-5835","contributorId":270381,"corporation":false,"usgs":true,"family":"Garcia","given":"Patricia","email":"pgarcia@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":829192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shelton, Jenna L. 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":5025,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna L.","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":829193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gardiner, Peggy J. 0000-0002-2715-9607","orcid":"https://orcid.org/0000-0002-2715-9607","contributorId":270382,"corporation":false,"usgs":true,"family":"Gardiner","given":"Peggy","email":"","middleInitial":"J.","affiliations":[{"id":5070,"text":"Office of the AD Human Capital","active":true,"usgs":true}],"preferred":true,"id":829194,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Diniega, Serina","contributorId":212017,"corporation":false,"usgs":false,"family":"Diniega","given":"Serina","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":829196,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martinez, Catalina","contributorId":270384,"corporation":false,"usgs":false,"family":"Martinez","given":"Catalina","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":829197,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Etheridge, Alexandra B. 0000-0003-1282-7315 aetherid@usgs.gov","orcid":"https://orcid.org/0000-0003-1282-7315","contributorId":3542,"corporation":false,"usgs":true,"family":"Etheridge","given":"Alexandra","email":"aetherid@usgs.gov","middleInitial":"B.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829198,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rutledge, Alicia","contributorId":270385,"corporation":false,"usgs":false,"family":"Rutledge","given":"Alicia","email":"","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":829199,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Richey, C.","contributorId":101903,"corporation":false,"usgs":false,"family":"Richey","given":"C.","email":"","affiliations":[],"preferred":false,"id":829235,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70220376,"text":"70220376 - 2021 - Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis","interactions":[],"lastModifiedDate":"2021-05-10T11:50:30.413554","indexId":"70220376","displayToPublicDate":"2021-04-30T06:47:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis","docAbstract":"Coal mine gas originates from the gas emission zone (GEZ) of the mine, as well as the longwall face and pillars. Gas emissions are controlled directly at the sources using horizontal or vertical boreholes drilled from surface or from the entries in advance of mining, or it is captured from the fractured and caved zones (gob) using ventholes during mining. The rest of the gas, especially that gas that originates from the longwall face and caved zone, mixes with the ventilation air and travels through bleeder and return entries before being exhausted to atmosphere from air shafts.
Although the gas associated with mining mostly focuses on methane, the gas is not pure methane but is a mixture (where both the components and their quantities vary depending on the sampling location). Understanding the evolution of the composition of the gas from source to different sampling and evaluation points in mines using proper statistical analysis and interpretation methods can lead to better designed degasification and ventilation systems and the selection of the most adequate utilization method for generating energy from the gas.
In this work, we present the results of compositional data analysis (CoDa) of gases sampled at different locations in a longwall mine operating in Pennsylvanian coal-bearing strata in the Northern Appalachian coal basin. Sampling locations were from accessible parts of the bleeder entries, returns, bleeder evaluation points and shafts within the mine, and also from gob gas ventholes (GGV) and coal degasification boreholes drilled in the panel areas. In addition, desorbed gas samples from seams that are important for the mine were included in the analyses for comparison. The compositional data analysis showed that the gas composition shifts based on the sampling location, putting in-mine and pure coalbed gases on the opposite ends. Removal of air from the samples did not change this observation suggesting that oxygen is depleted especially for in-mine samples, which is due to oxidation. Results also suggested that desorbed gas samples may not represent the composition of the coal seam gas.
The Community for Data Integration is a community of practice whose purpose is to advance the U.S. Geological Survey’s data integration capabilities. In fiscal year 2019, the Community for Data Integration held 9 monthly forums, facilitated 11 collaboration areas, held several workshops and training events, and funded 14 projects. The activities supported the U.S. Geological Survey priorities of enabling integrated predictive science, producing FAIR (Findable, Accessible, Interoperable, Reusable) data, building modular and reusable tools, building authoritative national datasets for hazards or assets, and developing tools and methods for biosurveillance of emerging invasive species and health threats. Through these efforts, community members were informed of new and emerging technologies and data topics that helped them in their professional responsibilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20211016","usgsCitation":"Hsu, L., and Liford, A.N., 2021, Community for Data Integration 2019 Annual Report: U.S. Geological Survey Open-File Report 2021–1016, 19 p., https://doi.org/10.3133/ofr20211016.","productDescription":"iv, 19 p.","onlineOnly":"Y","ipdsId":"IP-119547","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":385363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1016/ofr20211016.pdf","text":"Report","size":"2.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1016"},{"id":385362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1016/coverthb.jpg"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, used noninvasive surface geophysics in the investigation of the distribution of saline groundwater in the valley-fill aquifer system of the Genesee River Valley near the former Retsof salt mine in western New York. In 1994, the Retsof salt mine, the largest of its kind in the western hemisphere, underwent a catastrophic roof collapse that resulted in groundwater inflow from the valley-fill aquifer system and bedrock fracture zones into the mine through two bedrock-rubble chimneys and the subsequent dissolution and filling of the mine with saturated brine. Since the early 2000s, except for a period of remedial pumping in 2006 to 2013, high-salinity water has migrated upward through the rubble chimneys into the basal part the aquifer system. The extent of saline-water migration within the aquifer system had not been evaluated since the end of remedial pumping when all the monitoring wells were grouted shut and abandoned. Installation of a monitoring-well network would be expensive and difficult given the thickness and heterogeneous character of valley fill. An investigation of the current extent of saline water in the aquifer system was warranted because the basal part of the aquifer is shallow to the north and it is used for water supply.
In fall 2016 and fall 2017, the U.S. Geological Survey collected time-domain electromagnetic soundings at 105 sites along 13 cross-valley transects north and south of the mine-collapse area, east of Piffard, and on the Fowlerville Moraine. The time-domain electromagnetic soundings were colocated with passive-seismic measurements to estimate the bedrock-surface elevation through use of a regression equation developed from measurements at well sites with reported bedrock depths in the study area. An integrated analysis of the time-domain electromagnetic soundings with the depth-to-bedrock estimates, well logs, and past chloride-monitoring data suggests the presence of a zone of high electrical conductivity associated with saline water in the confined lower part of the valley-fill aquifer system. This high-salinity zone delineated in the lower confined aquifer extends from the mine-collapse area northward for more than 2.5 miles (4.0 kilometers). The chloride concentration in groundwater within this high-conductivity zone may be about 20,000 milligrams per liter. Saline water flowing upward through the bedrock-rubble chimneys and mixing with northward groundwater flow in the lower confined aquifer likely is a major source of chlorides for this high-conductivity zone. The northern extent of the zone is unclear because of the presence of highly saline water zones that were delineated by time-domain electromagnetic soundings in the lower confined aquifer and uppermost bedrock and are probably associated with historic salt-solution wells in Piffard or possibly sourced from natural brine pools.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215008","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Williams, J.H., Kappel, W.M., Johnson, C.D., White, E.A., Heisig, P.M., and Lane, J.W., Jr., 2021, Time-domain electromagnetic soundings and passive-seismic measurements for delineation of saline groundwater in the Genesee valley-fill aquifer system, western New York, 2016–17: U.S. Geological Survey Scientific Investigations Report 2021–5008, 25 p., https://doi.org/10.3133/sir20215008.","productDescription":"Report: vii, 25 p.; 1 Plate: 49.96 x 35.95 inches; 3 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-108173","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":385251,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5008/coverthb.jpg"},{"id":385369,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VQOCRZ","text":"USGS data release","linkHelpText":"Time-domain electromagnetic soundings to delineate saline groundwater in the Genesee valley-fill aquifer system, New York (2016-2017)"},{"id":385368,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J354SU","text":"USGS data release","linkHelpText":"Chloride concentrations from wells in the Genesee River Valley, Livingston County, New York"},{"id":385367,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LI7CCR","text":"USGS data release","linkHelpText":"Horizontal-to-vertical spectral ratio and depth-to-bedrock data for saline-groundwater investigation in the Genesee valley, New York, October-November 2016 and 2017"},{"id":385366,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5008/sir20215008_plate1.pdf","text":"Plate 1","size":"59.4 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Electrical-conductivity transects from time-domain electromagnetic soundings, top of bedrock estimated from passive-seismic measurements, and lithostratigraphic logs of selected boreholes along 13 transects in the Genesee River Valley, western New York, 2016–17"},{"id":385365,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5008/sir20215008.pdf","text":"Report","size":"3.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5008"}],"country":"United States","state":"New York","otherGeospatial":"Genesee Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.93701171875,\n 42.54397489736545\n ],\n [\n -77.68363952636719,\n 42.54397489736545\n ],\n [\n -77.68363952636719,\n 42.97802779741624\n ],\n [\n -77.93701171875,\n 42.97802779741624\n ],\n [\n -77.93701171875,\n 42.54397489736545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Despite limitations in reproducing complex bedload sediment transport processes in rivers, formulas have been preferred over collection and analysis of field data due to the high cost and time-consuming nature of bedload discharge measurements. However, the performance of such formulas depends on the hydraulic and sedimentological conditions they attempt to describe. The availability of field measurements provides a unique opportunity to test bedload transport formulas to better guide formula selection. Hydraulic parameters and bedload discharge data from the Lower Minnesota River and two of its tributaries were used to evaluate nine bedload transport formulas using three different indices. The bedload data for the different sites were collected by the United States Geological Survey (USGS) from 2011 through 2014, with bed material varying from very coarse to medium sand. The formulas calculated higher bedload rates than were measured due to a combination of site-specific physical characteristics, including the presence of bed forms (dunes), and sampling uncertainties. Because of the lack of reproducibility of the tested formulas, five power functions, based on the relation between the specific unit power (independent hydraulic variable) and the USGS measured data (dependent variable), were derived as provisional equations to estimate the bedload discharge on the Lower Minnesota River and tributaries.
Reservoir properties of coal seams such as gas and water effective permeabilities and gas content, as well as spatial distributions thereof, affect the success of gas production and CO2-enhanced gas recovery (EGR) with simultaneous CO2 sequestration. These properties change during production and injection operations due to variations in reservoir pressure, matrix shrinkage/swelling, and water saturation and are therefore referred to as dynamic properties. Predicting distribution of such important reservoir properties and how they evolve during production, or injection, at unsampled locations can be particularly important for field development and project economics.
In this work, dynamic properties of Black Creek coal seam of Black Warrior Basin, Alabama were mapped using pointwise results from single-well production history matching of 45 wells and classical geostatistics. It is explored if this approach can be a proxy, with its limitations, to multi-well reservoir simulation. For this purpose, a reservoir model was built using available reservoir, well and production data to compare its results with those of the geostatistical maps for the same properties. Despite the expected local discrepancies due to differences between the two approaches, the results showed similar patterns and global distributions. Specific results showed that despite long-time operation of the wells in this area, there were still areas with high gas content and low gas effective permeability within the modeled time interval that might have benefited from further development using additional wells.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2021.103766","usgsCitation":"Karacan, C.O., 2021, Single-well production history matching and geostatistical modeling as proxy to multi-well reservoir simulation for evaluating dynamic reservoir properties of coal seams: International Journal of Coal Geology, v. 241, 103766, 10 p., https://doi.org/10.1016/j.coal.2021.103766.","productDescription":"103766, 10 p.","ipdsId":"IP-124559","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":385530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","city":"Tuscaloosa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.8082275390625,\n 32.9764120829052\n ],\n [\n -86.912841796875,\n 32.9764120829052\n ],\n [\n -86.912841796875,\n 33.669496972795535\n ],\n [\n -87.8082275390625,\n 33.669496972795535\n ],\n [\n -87.8082275390625,\n 32.9764120829052\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"241","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":815294,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70222454,"text":"70222454 - 2021 - lsforce: A Python-based single-force seismic inversion framework for massive landslides","interactions":[],"lastModifiedDate":"2021-07-30T14:01:26.407941","indexId":"70222454","displayToPublicDate":"2021-04-28T09:00:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"lsforce: A Python-based single-force seismic inversion framework for massive landslides","docAbstract":"We present an open‐source Python package, lsforce, for performing single‐force source inversions of long‐period (tens to hundreds of seconds) seismic signals. Although the software is designed primarily for landslides, it can be used for any single‐force seismic source. The package allows users to produce estimates of the three‐component time series of forces exerted on the Earth by a landslide with postprocessing options to estimate the trajectory of its center of mass. Green’s functions for a user‐selected 1D Earth model are obtained automatically from the Incorporated Research Institutions for Seismology Synthetics Engine webservice or can be computed for custom 1D Earth models using Computer Programs in Seismology. lsforce implements the two most commonly used source parameterizations: a fully flexible, high‐resolution approach and a more stable but lower‐resolution method of overlapping triangle sources. Regularization options include a blended zeroth‐, first‐, and second‐order semiautomated Tikhonov regularization scheme, as well as additional optional constraints on start times, end times, and on the sum of forces. Uncertainty due to data selection can be assessed using either a leave‐one‐out approach or a modified jackknife technique that randomly excludes subsets of the data for multiple re‐inversions. Numerous built‐in plotting methods allow for easy quality control and assessment of results. In this article, we briefly outline the theory and methodology, describe our implementation, and demonstrate the usage of lsforce using the well‐studied 28 June 2016 Lamplugh rock avalanche in Alaska. Despite the rapidly increasing prevalence of landslide single‐force inversions in the landslide and seismology literature over the past decade, to our knowledge this is the first open‐source code for performing such inversions.
Water, bed sediment, and invertebrate tissue were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the Clark Fork Basin. The sampling program was completed by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin and monitor trace elements associated with historical mining and smelting activities. Sampling sites were on the river and tributaries of the Clark Fork. Water samples were collected periodically at 20 sites from October 2018 through September 2019. Bed-sediment and tissue samples were collected once at 13 sites during July 2019.
Water-quality data included concentrations of major ions, dissolved organic carbon, nitrogen (nitrate plus nitrite), trace elements, and suspended sediment. Daily values of turbidity were determined at four sites. Bed-sediment data included trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data included trace-element concentrations in whole-body tissue of aquatic benthic invertebrates. Statistical summaries of water-quality, bed-sediment, and invertebrate tissue trace-element data for sites in the Clark Fork Basin were provided for the period of record: March 1985–September 2019.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211027","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Clark, G.D., Hornberger, M.I., Hepler, E.J., Cleasby, T.E., and Heinert, T.L., 2021, Water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2018–September 2019: U.S. Geological Survey Open-File Report 2021–1027, 16 p., https://doi.org/10.3133/ofr20211027.","productDescription":"Report: vi, 16 p.; Data Release; Dataset","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-122934","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":385286,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1027/coverthb.jpg"},{"id":385287,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1027/ofr20211027.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 1027–1027"},{"id":385288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GKHL8W","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2018–September 2019"},{"id":385289,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.13421630859374,\n 47.10565336099383\n ],\n [\n -114.39788818359375,\n 47.025206001585396\n ],\n [\n -114.25506591796875,\n 46.613601326659726\n ],\n [\n -114.00238037109375,\n 46.58718152732907\n ],\n [\n -113.15917968749999,\n 46.15890744507131\n ],\n [\n -112.69775390625,\n 45.84793427349226\n ],\n [\n -112.00836181640625,\n 46.15319980124842\n ],\n [\n -111.88201904296875,\n 46.428392162921234\n ],\n [\n -113.00262451171875,\n 46.848921470800455\n ],\n [\n -113.631591796875,\n 47.13368783277605\n ],\n [\n -114.13421630859374,\n 47.10565336099383\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
In August 2019, the U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, conducted a bathymetric survey of Lago Patillas to update stage-volume data in order to determine the sediment infill rates and to generate a bathymetry map. Water-depth data were collected along predefined lines using single-beam depth sounder and Differential Global Positioning System technology. The study also included delineating a new reservoir shoreline based on 2016–17 light detection and ranging data and the establishment of a new official vertical datum at the reservoir referenced to the Puerto Rico Vertical Datum of 2002 (PRVD02). Survey results indicated that the storage capacity was 12.96 million cubic meters in 2019 at an elevation of 67.55 meters above PRVD02. The mean annual loss of capacity from 1961 to 2019 is 0.08 million cubic meters per year. The point of zero remaining storage of Lago Patillas is projected to be 161 years, ending in 2180.
The new vertical datum referenced to PRVD02 was established at Lago Patillas by conducting a Global Navigation Satellite System static observation in March 2019, which indicated that the spillway elevation is 67.55 meters. The new spillway elevation datum supersedes the previous datum (mean sea level) used on the island of Puerto Rico.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3471","collaboration":"Prepared in cooperation with the Puerto Rico Electric Power Authority","usgsCitation":"Gómez-Fragoso, J.M., 2021, Bathymetric survey and sedimentation analysis of Lago Patillas, Puerto Rico, August 2019: U.S. Geological Survey Scientific Investigations Map 3471, 1 sheet, https://doi.org/10.3133/sim3471.","productDescription":"1 Sheet: 45.00 x 3.6.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-122145","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":385306,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3471/sim3471.pdf","text":"Sheet","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3471"},{"id":385307,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y2SCY1","text":"USGS data release","description":"USGS data release","linkHelpText":"Spatial and bathymetric data for Lago Patillas, Puerto Rico, August 2019"},{"id":385305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3471/coverthb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico, Lago Patillas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.0446548461914,\n 18.005998640427865\n ],\n [\n -65.9974479675293,\n 18.005998640427865\n ],\n [\n -65.9974479675293,\n 18.039625778656163\n ],\n [\n -66.0446548461914,\n 18.039625778656163\n ],\n [\n -66.0446548461914,\n 18.005998640427865\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Lutz, FL 33559
From the iconic skyline of New York City to the forested landscapes of the Adirondack Mountains and the countryside of the Allegheny Plateau, the State of New York is overflowing with diversity and life. Bordered by the Atlantic Ocean on the east and two of the Great Lakes to the north and west, New York has more than 7,600 lakes, ponds, and reservoirs and more than 70,000 miles of rivers and streams. New York’s stewardship of its freshwater resources is fundamental to the health and well-being of all who work at, reside in, and visit the State’s landmarks and places.
Harmful algal blooms in the State’s waterbodies are a growing concern and threaten the health of the region and its inhabitants. Images and data from Landsat satellites continue to provide critical information to scientists, public health officials, and resource managers who are studying the effects and risks of the problem.
Here is a closer look at just a few examples of the value of Landsat to New York.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213020","usgsCitation":"U.S. Geological Survey, 2021, New York and Landsat (ver. 1.1, January 2023): U.S. Geological Survey Fact Sheet 2021–3020, 2 p., https://doi.org/10.3133/fs20213020.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-126002","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":412235,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20213020/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412178,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2021/3020/images"},{"id":412177,"rank":4,"type":{"id":31,"text":"Publication 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York\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: April 26, 2021; Version 1.1: January 23, 2023","contact":"Program Coordinator, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
A numerical surface-water/groundwater model was developed for the lower San Antonio River Basin to evaluate the responses of low base flows and groundwater levels within the basin under conditions of reduced recharge and increased groundwater withdrawals. Batch data assimilation through history matching used a simulation of historical conditions (2006-2013); this process included history-matching to groundwater levels and base-flow estimates at several gages, and was completed in a high-dimensional (highly parameterized) framework. The model was developed in an uncertainty framework such that parameters, observations, and scenarios of interest are envisioned stochastically as distributions of potential values. Results indicate that groundwater contributions to surface water during periods of low flow may be reduced from 6% to 25% with a corresponding 25% reduction in recharge and a 25% increase in groundwater pumping over an 8-year planning period. Furthermore, results indicate groundwater-level reductions in some hydrostratigraphic units are more likely than in other hydrostratigraphic units over an 8-year period under drought conditions with the higher groundwater withdrawal scenario.
During the past half century or so diverse histories of Great Salt Lake have been written from differing perspectives and all of them have contributed ideas and essential data. The published literature, however, can be confusing and misleading. In this chapter, we review and provide context for a number of those publications. This chapter is intended as a summary of what is known, what is not known, and what cannot be known with precision about the history of the lake.
Great Salt Lake is the largest hydrographically closed lake in the Bonneville basin of northwestern Utah. It responds to both short-term weather and long-term climate. In the Lake Bonneville/Great Salt Lake lacustrine system, the end of Lake Bonneville at 13,000 yr BP marks the beginning of Great Salt Lake. The much larger and deeper lakes of the Bonneville lake cycle responded to the pluvial climate of oxygen isotope stage 2, but the warmer, drier climate of oxygen isotope stage 1 led to rapid fluctuations within a relatively narrow, well-documented elevation range, 5 m above and 9 m below the historical mean elevation of ~1280 m. Two exceptional but short-lived rises of Great Salt Lake to elevations higher than 5 m above ~1280 m have been documented —one during the Gilbert episode, which peaked about 11,600 yr BP near an elevation of 1295 m, and one to about 1289 m sometime after about 11,000 yr BP.
The historical Great Salt Lake hydrograph (the past 150 years) shows its labile behavior. Smooth-curve hydrographs based on estimates of lake level at time scales of decades, centuries, or millennia, such as those presented in previous publications, do not accurately portray the way lake level rises and falls, and a precise plot of post-Bonneville changes in level of Great Salt Lake would resemble the “jagged” historical record. The available sedimentary and geomorphic data are not conducive at this time to the production of a highly precise hydrograph, so we suggest that post-Bonneville lake-level history be portrayed, imprecisely but accurately, as confined generally between the elevation limits of 1285 and 1271 m, with an indication of the exceptional spikes in the lake level.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-66576-0_8","usgsCitation":"Oviatt, C.G., Atwood, G., and Thompson, R.S., 2021, History of Great Salt Lake, Utah, USA: Since the termination of Lake Bonneville, chap. of Limnogeology: Progress, challenges and opportunities: A tribute to Elizabeth Gierlowski-Kordesch, p. 233-271, https://doi.org/10.1007/978-3-030-66576-0_8.","productDescription":"39 p.","startPage":"233","endPage":"271","ipdsId":"IP-107807","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":397595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Bonneville basin, Great Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.8623046875,\n 40.59727063442024\n ],\n [\n -111.939697265625,\n 40.59727063442024\n ],\n [\n -111.939697265625,\n 41.812267143599804\n ],\n [\n -113.8623046875,\n 41.812267143599804\n ],\n [\n -113.8623046875,\n 40.59727063442024\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2021-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Oviatt, Charles G.","contributorId":36580,"corporation":false,"usgs":false,"family":"Oviatt","given":"Charles","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":838824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwood, Genevieve","contributorId":289265,"corporation":false,"usgs":false,"family":"Atwood","given":"Genevieve","email":"","affiliations":[{"id":62089,"text":"Earth Science Education","active":true,"usgs":false}],"preferred":false,"id":838825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838826,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223116,"text":"70223116 - 2021 - What can commercial fishery data in the Great Lakes reveal about juvenile sea lamprey (Petromyzon marinus) ecology and management?","interactions":[],"lastModifiedDate":"2022-01-06T17:54:36.553996","indexId":"70223116","displayToPublicDate":"2021-04-24T07:40:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"What can commercial fishery data in the Great Lakes reveal about juvenile sea lamprey (Petromyzon marinus) ecology and management?","title":"What can commercial fishery data in the Great Lakes reveal about juvenile sea lamprey (Petromyzon marinus) ecology and management?","docAbstract":"The Laurentian Great Lakes of North America support a large and profitable freshwater fishery, but one continuously beset by parasitism from the invasive sea lamprey (Petromyzon marinus). Despite being the life stage that inflicts damage to the fishery, therefore necessitating a bi-national control program, our knowledge of juvenile sea lamprey ecology is poor and their response to control efforts are not assessed. Incidental capture of juvenile sea lamprey by commercial fishers is one means to collect data on this enigmatic life stage, and in Lake Huron such data have been collated since 1967. Here, we explore incidental captures of juvenile sea lamprey and their hosts from northern Lake Huron between 1987 and 2017 (n = 33,246 observations) to address four objectives. Firstly, we document collection efforts by fishers to provide historical context to the dataset. Secondly, we pose and test a series of questions related to fishery encounter, host selection, growth, distribution, and sex ratio to highlight how these types of data can be informative regarding juvenile sea lamprey ecology. Results presented here could be used to develop biological hypotheses to be addressed in future work. Thirdly, we directly assessed whether juvenile sea lamprey capture data could be useful in corroborating trends observed in adult sea lamprey abundance and wounding, as well as in identifying abundance and wounding hotspots. Lastly, we summarize research and outreach efforts that have benefited from the capture of juvenile sea lamprey in recent years.
We use ground and space geodetic data to study surface deformation at Kīlauea Volcano from January to September 2015. This period includes an episode of heightened activity in April and May 2015 that culminated in a magmatic intrusion beneath the volcano's summit. The data set consists of Global Navigation Satellite System (GNSS), tilt, visual and seismic time series along with 25 descending and 15 ascending acquisitions of the Sentinel-1 satellite. We identify four different stages of surface deformation and volcanic activity, which we attribute to pressure changes and the movement of magma in response to an imbalance between magma supply and withdrawal in the shallow plumbing system, eventually leading to an intrusion beneath the summit area. In particular, we model the deformation as due to pressure changes in two subsurface magma bodies: the Halema‘uma‘u Reservoir (HMMR) and South Caldera Reservoir (SCR). The SCR was best described by an ellipsoidal source at 2.8 (2.65–3.07 at 95% confidence) km depth below the south caldera region. The HMMR was modeled as a point source located just east of Halema‘uma‘u crater at 1.5 (0.95–2.62) km depth. We suggest that a short-term increase in the magma supply rate to the volcano is a potential mechanisms for the intrusion, although other factors, like the filling of available void space or a reduced efficiency of magma transport through the volcano's East Rift Zone, may also play a role.
Scavenging is an important function within ecosystems where scavengers remove organic matter, reduce disease, stabilize food webs, and generally make ecosystems more resilient to environmental changes. Global change (i.e., changing climate and increasing human impact) is currently influencing scavenger communities. Thus, understanding what promotes species richness in scavenger communities can help prioritize management actions. Using a long-term dataset from camera traps deployed with animal carcasses as bait along a 1881 km latitudinal gradient in the Appalachian Mountains of eastern USA, we investigated the relative impact of climate and humans on the species richness and diversity of vertebrate scavengers. Our most supported models for both mammalian and avian scavengers included climatic, but not human, variables. The richness of mammalian and avian scavengers detected was highest during relatively warm (5–10°C) and dry (100–150 mm precipitation) winters, when food was likely limited and both reliance on and detection of carrion was high. The diversity of mammalian and avian scavengers detected was highest under drier conditions. We then used these results to project the future species richness of scavengers that would be detected within our sampling area and under the climate scenario of 2070 (emissions level RCP8.5). Our predictions suggest up to 80% and 67% reductions, respectively, in the richness of avian and mammalian scavengers that would be detected at baited sites. Climate-induced shifts in behavior (i.e., reduction in scavenging, even if present) at this scale could have cascading implications for ecosystem function, resilience, and human health. Further, our study highlights the importance of conducting studies of scavenger community dynamics within ecosystems across wide spatial gradients within temperate environments. More broadly, these findings build upon our understanding of the impacts of climate-induced adjustments in behavior that can likely have negative impacts on systems at a large scale.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15653","usgsCitation":"Marneweck, C.J., Katzner, T., and Jachowski, D., 2021, Predicted climate-induced reductions in scavenging in eastern North America: Global Change Biology, v. 27, no. 14, p. 3383-3394, https://doi.org/10.1111/gcb.15653.","productDescription":"12 p.","startPage":"3383","endPage":"3394","ipdsId":"IP-125016","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":387282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.48828125,\n 45.27488643704891\n ],\n [\n -75.673828125,\n 43.26120612479979\n ],\n [\n -80.8154296875,\n 40.34654412118006\n ],\n [\n -83.75976562499999,\n 38.06539235133249\n ],\n [\n -81.8701171875,\n 36.94989178681327\n ],\n [\n -77.0361328125,\n 39.027718840211605\n ],\n [\n -72.0703125,\n 42.48830197960227\n ],\n [\n -69.60937499999999,\n 44.68427737181225\n ],\n [\n -70.48828125,\n 45.27488643704891\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"14","noUsgsAuthors":false,"publicationDate":"2021-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Marneweck, Courtney J. 0000-0002-5064-1979","orcid":"https://orcid.org/0000-0002-5064-1979","contributorId":261261,"corporation":false,"usgs":false,"family":"Marneweck","given":"Courtney","email":"","middleInitial":"J.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":819615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":819616,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jachowski, David S.","contributorId":228814,"corporation":false,"usgs":false,"family":"Jachowski","given":"David S.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":819617,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70222508,"text":"70222508 - 2021 - Mercury and water level management in lakes of northern Minnesota","interactions":[],"lastModifiedDate":"2021-08-02T15:30:54.462657","indexId":"70222508","displayToPublicDate":"2021-04-23T10:26:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Mercury and water level management in lakes of northern Minnesota","docAbstract":"Water level (WL) fluctuations substantially alter the fauna, flora, and microbial community of nearshore aquatic ecosystems. Water level management therefore has the potential to strongly influence a wide variety of ecosystem processes. Many northern temperate lake food webs experience substantial methylmercury contamination, which is partially mediated by the action of sulfate-reducing bacteria occurring in sediments that are periodically inundated. For lakes with elevated methylmercury, WL management could be designed to reduce methylmercury contamination. At the lake scale, this concept is supported by studies that identified statistical associations between fish mercury content and water level (WL) fluctuations. Here, we compiled a long-term dataset (1997–2015) of mercury content in young-of-year Yellow Perch (Perca flavescens) from six lakes on the border of the United States and Canada and examined whether mercury content was associated with WL fluctuation. Many WL metrics covary and appear to have strong associations with Yellow Perch mercury. However, these associations appear to vary by lake, and lake-specific models are needed to identify relationships between WL fluctuation and Yellow Perch mercury content. We used partial least-squares regression (PLSR) to identify the associations between Yellow Perch mercury content and WL metrics, temperature, and annual deposition data for lakes in northern Minnesota. These PLSR models not only showed some variation among lakes, but also supported strong associations between WL fluctuations and annual variation in Yellow Perch mercury content. The study lakes underwent a change in WL management in 2000, when winter WL minimums were increased by about 1 m in five of the six study lakes, which reduced annual WL fluctuation on those lakes. Using the PLSR models, we estimated how this change in WL management would have affected Yellow Perch mercury content. In four of the five study lakes in which annual WL fluctuation was reduced in 2000, the change in WL management likely reduced Yellow Perch mercury content, relative to the previous WL management regime.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3465","usgsCitation":"Larson, J.H., Maki, R., Christensen, V., Hlavacek, E., Sandheinrich, M.B., LeDuc, J.F., Kissane, C., and Knights, B.C., 2021, Mercury and water level management in lakes of northern Minnesota: Ecosphere, v. 12, no. 4, e03465, 17 p., https://doi.org/10.1002/ecs2.3465.","productDescription":"e03465, 17 p.","ipdsId":"IP-119750","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":489137,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3465","text":"Publisher Index Page"},{"id":436398,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96TWNJL","text":"USGS data release","linkHelpText":"Mercury and water level fluctuations in lakes of northern Minnesota - sampling site land cover and inundated area data"},{"id":387629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.240966796875,\n 48.16058943132621\n ],\n [\n -92.37991333007812,\n 48.16058943132621\n ],\n [\n -92.37991333007812,\n 48.62383195130112\n ],\n [\n -93.240966796875,\n 48.62383195130112\n ],\n [\n -93.240966796875,\n 48.16058943132621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, Ryan P.","contributorId":190131,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":820352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandheinrich, Mark B.","contributorId":149084,"corporation":false,"usgs":false,"family":"Sandheinrich","given":"Mark","email":"","middleInitial":"B.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":820355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeDuc, Jaime F.","contributorId":190132,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":820356,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kissane, Claire","contributorId":178240,"corporation":false,"usgs":false,"family":"Kissane","given":"Claire","email":"","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":820357,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":820358,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70220198,"text":"70220198 - 2021 - West-wide drought analysis","interactions":[],"lastModifiedDate":"2021-04-27T12:40:24.30458","indexId":"70220198","displayToPublicDate":"2021-04-23T07:33:53","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"chapter":"4","title":"West-wide drought analysis","docAbstract":"This chapter describes analyses of the variability and characteristics of drought for historical and future projected climate conditions across the Western United States. The analyses are performed using the Palmer Drought Severity Index (PDSI; Palmer, 1965) to define drought events. The advantage of using PDSI to define droughts is that it focuses explicitly on droughts driven by hydroclimate variability. The PDSI does not include anthropogenic effects, such as water management, including the effects of reservoirs and diversions. Thus, PDSI is well-suited to examine natural climate-driven drought characteristics (i.e., drought duration, severity, and frequency).\nThe next section (Section 4.1) describes the PDSI dataset and how it is used in the analyses. Section 4.2 describes the methodologies used to identify and analyze drought events. Section 4.3 presents results, along with considerations regarding the interpretations of the results. Summary and next steps emerging from the analyses are described in Section 4.4. Lastly, a listing of key findings is given in Section 4.5.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"West-Wide Climate and Hydrology Assessment, Technical Memorandum No. ENV-2021-001","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"U.S. Bureau of Reclamation","collaboration":"U.S. Bureau of Reclamation","usgsCitation":"Gangopadhyay, S., McCabe, G.J., Pruitt, T., and House, B., 2021, West-wide drought analysis, 54 p.","productDescription":"54 p.","startPage":"129","endPage":"182","ipdsId":"IP-125638","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":385318,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385309,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/climate/secure/2021secure.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gangopadhyay, Subhrendu","contributorId":257611,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":814724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":814725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pruitt, Tom","contributorId":257612,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":814726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"House, Brandon","contributorId":257613,"corporation":false,"usgs":false,"family":"House","given":"Brandon","email":"","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":814727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222120,"text":"70222120 - 2021 - Sagebrush recovery patterns after fuel treatments mediated by disturbance type and plant functional group interactions","interactions":[],"lastModifiedDate":"2021-07-20T11:46:05.454447","indexId":"70222120","displayToPublicDate":"2021-04-23T06:43:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Sagebrush recovery patterns after fuel treatments mediated by disturbance type and plant functional group interactions","docAbstract":"Fire and fuel management is a high priority in North American sagebrush ecosystems where the expansion of piñon and juniper trees and the invasion of nonnative annual grasses are altering fire regimes and resulting in loss of sagebrush species and habitat. We evaluated 10-yr effects of woody fuel treatments on sagebrush recruitment and plant functional group interactions using Sagebrush Steppe Treatment Evaluation Project data. We used mixed-effects ANOVAs to examine treatment effects on sagebrush density and cover and perennial and annual grass cover in expansion woodlands (prescribed fire and cut-and-leave) and annual grass invasion areas (prescribed fire, mowing, tebuthiuron herbicide application). We used piecewise structural equation models to evaluate interactions among sagebrush seedling density, juvenile and adult density, and cover and perennial and annual grass cover. Fuel treatments were equated to pulse or press disturbances varying in resource release and subsequent intra- and interspecific interactions. Prescribed fire, a high magnitude pulse disturbance with more severe effects in warm and dry sites, reduced sagebrush cover and decoupled associations among sagebrush seedlings, juvenile and adult density, and cover indicating changed population structure. Cutting and leaving trees, a low magnitude pulse disturbance in cooler and moister woodlands, increased sagebrush density and cover and generally had lesser effects on sagebrush intraspecific associations. Mowing, a moderate magnitude pulse disturbance, and tebuthiuron herbicide application, a multiyear press disturbance, reduced sagebrush cover and disrupted intraspecific relationships. Competitive release increased cover of perennial grass in all treatments but tebuthiuron. Annual grass increased in all treatments, especially prescribed fire and tebuthiuron. Annual and perennial grass interactions with sagebrush were generally rare, but in woodland treatments perennial grass suppressed annual grass through year 6. Treatments in cooler and moister woodland sites had more positive effects on sagebrush recruitment and perennial grass cover, less negative effects on sagebrush intraspecific interactions, and smaller increases in annual grass cover indicating potential increases in resilience to fire. In warmer and drier invasion sites, reductions in woody fuels resulted in lack of sagebrush recruitment, disruption of sagebrush intraspecific interactions, and progressive increases in annual grass indicating reduced resilience to fire and resistance to invaders.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3450","usgsCitation":"Chambers, J., Urza, A.K., Board, D.I., Miller, R.F., Pyke, D.A., Roundy, B.A., Schupp, E.W., and Tausch, R.J., 2021, Sagebrush recovery patterns after fuel treatments mediated by disturbance type and plant functional group interactions: Ecosphere, v. 12, no. 4, e03450, 22 p., https://doi.org/10.1002/ecs2.3450.","productDescription":"e03450, 22 p.","ipdsId":"IP-123790","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":489091,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3450","text":"Publisher Index Page"},{"id":387283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Chambers, Jeanne C.","contributorId":75889,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne C.","affiliations":[],"preferred":false,"id":819607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Urza, Alexandra K. 0000-0001-9795-6735","orcid":"https://orcid.org/0000-0001-9795-6735","contributorId":261259,"corporation":false,"usgs":false,"family":"Urza","given":"Alexandra","email":"","middleInitial":"K.","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":819608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Board, David I.","contributorId":261260,"corporation":false,"usgs":false,"family":"Board","given":"David","email":"","middleInitial":"I.","affiliations":[{"id":16848,"text":"USDA Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":819609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Richard F.","contributorId":178258,"corporation":false,"usgs":false,"family":"Miller","given":"Richard","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":819610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":819611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roundy, Bruce A.","contributorId":178261,"corporation":false,"usgs":false,"family":"Roundy","given":"Bruce","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":819612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schupp, Eugene W.","contributorId":178262,"corporation":false,"usgs":false,"family":"Schupp","given":"Eugene","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":819613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tausch, Robin J.","contributorId":213637,"corporation":false,"usgs":false,"family":"Tausch","given":"Robin","email":"","middleInitial":"J.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":819614,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70222089,"text":"70222089 - 2021 - Quantifying diagenesis, contributing factors, and resulting isotopic bias in benthic foraminifera using the Foraminiferal Preservation Index: Implications for geochemical proxy records","interactions":[],"lastModifiedDate":"2021-07-19T23:24:09.565365","indexId":"70222089","displayToPublicDate":"2021-04-22T18:19:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying diagenesis, contributing factors, and resulting isotopic bias in benthic foraminifera using the Foraminiferal Preservation Index: Implications for geochemical proxy records","docAbstract":"Geochemical records generated from the calcite tests of benthic foraminifera, especially those of the genera Cibicidoides and Uvigerina, provide the basis for proxy reconstructions of past climate. However, the extent to which benthic foraminifera are affected by postdepositional alteration is poorly constrained. Furthermore, how diagenesis may alter the geochemical composition of benthic foraminiferal tests, and thereby biasing a variety of proxy-based climate records, is also poorly constrained. We present the Foraminiferal Preservation Index (FPI) as a new metric to quantify preservation quality based on objective, well-defined criteria. The FPI is used to identify and quantify trends in diagenesis temporally, from late Pliocene to modern coretop samples (3.3–0 Ma), as well as spatially in the deep ocean. The FPI identifies the chemical composition of deep-ocean water masses to be the primary driver of diagenesis through time, while also serving as a supplementary method of identifying periods of changing water mass influence at a given site. Additionally, we present stable isotope data (δ18O, δ13C) generated from individual Cibicidoides specimens of various preservation quality that demonstrate the likelihood of significant biasing in a variety of geochemical proxy records, especially those used to reconstruct past changes in ice volume and sea level. These single-test data further demonstrate that when incorporating carefully selected tests of only the highest preservation quality, robust paleorecords can be generated.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020PA004110","usgsCitation":"Poirier, R., Gaetano, M.Q., Acevedo, K., Morgan F. Schaller, M.F., Raymo, M.E., and Kozdon, R., 2021, Quantifying diagenesis, contributing factors, and resulting isotopic bias in benthic foraminifera using the Foraminiferal Preservation Index: Implications for geochemical proxy records: Paleoceanography and Paleoclimatology, v. 36, no. 5, e2020PA004110, 32 p., https://doi.org/10.1029/2020PA004110.","productDescription":"e2020PA004110, 32 p.","ipdsId":"IP-121944","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":387257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Poirier, Robert 0000-0001-5380-4545","orcid":"https://orcid.org/0000-0001-5380-4545","contributorId":261201,"corporation":false,"usgs":true,"family":"Poirier","given":"Robert","email":"","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":819465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaetano, Madison Q.","contributorId":261202,"corporation":false,"usgs":false,"family":"Gaetano","given":"Madison","email":"","middleInitial":"Q.","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":819466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Acevedo, Kimberly","contributorId":261203,"corporation":false,"usgs":false,"family":"Acevedo","given":"Kimberly","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":819467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Morgan F. Schaller, Morgan F. 0000-0003-2742-2126","orcid":"https://orcid.org/0000-0003-2742-2126","contributorId":261204,"corporation":false,"usgs":false,"family":"Morgan F. Schaller","given":"Morgan","email":"","middleInitial":"F.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":819468,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymo, Maureen E.","contributorId":261205,"corporation":false,"usgs":false,"family":"Raymo","given":"Maureen","email":"","middleInitial":"E.","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":819469,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kozdon, Reinhard 0000-0001-6347-456X","orcid":"https://orcid.org/0000-0001-6347-456X","contributorId":261206,"corporation":false,"usgs":false,"family":"Kozdon","given":"Reinhard","email":"","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":819470,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70220145,"text":"ofr20211020 - 2021 - Triangle Area Water Supply Monitoring Project, North Carolina—Summary of monitoring activities, quality assurance, and data, October 2017–September 2019","interactions":[],"lastModifiedDate":"2021-04-23T11:41:39.898363","indexId":"ofr20211020","displayToPublicDate":"2021-04-22T14:50:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1020","displayTitle":"Triangle Area Water Supply Monitoring Project, North Carolina—Summary of Monitoring Activities, Quality Assurance, and Data, October 2017–September 2019","title":"Triangle Area Water Supply Monitoring Project, North Carolina—Summary of monitoring activities, quality assurance, and data, October 2017–September 2019","docAbstract":"Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, from October 2017 through September 2018 (water year 2018) and from October 2018 through September 2019 (water year 2019). Major findings for this period include the following:
Director, South Atlantic Water Science Center
U.S. Geological Survey
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