Borealization is a type of community reorganization where Arctic specialists are replaced by species with more boreal distributions in response to climatic warming. The process of borealization is often exemplified by the northward range expansions and subsequent proliferation of boreal species on the Pacific and Atlantic inflow Arctic shelves (i.e., Bering/Chukchi and Barents seas, respectively). But the circumpolar nearshore distribution of Arctic-boreal fishes that predates recent warming suggests borealization is possible beyond inflow shelves. To examine this question, we revisited two nearshore lagoons in the eastern Alaska Beaufort Sea (Kaktovik and Jago lagoons, Arctic National Wildlife Refuge, Alaska, USA), a High Arctic interior shelf. We compared summer fish species assemblage, catch rate, and size distribution among three periods that spanned a 30-year record (baseline conditions, 1988–1991; moderate sea ice decline, 2003–2005; rapid sea ice decline, 2017–2019). Fish assemblages differed among periods in both lagoons, consistent with borealization. Among Arctic specialists, a clear decline in fourhorn sculpin (Myoxocephalus quadricornis, Kanayuq in Iñupiaq) occurred in both lagoons with 86%–90% lower catch rates compared with the baseline period. Among the Arctic-boreal species, a dramatic 18- to 19-fold increase in saffron cod (Eleginus gracilis, Uugaq) occurred in both lagoons. Fish size (length) distributions demonstrated increases in the proportion of larger fish for most species examined, consistent with increasing survival and addition of age-classes. These field data illustrate borealization of an Arctic nearshore fish community during a period of rapid warming. Our results agree with predictions that Arctic-boreal fishes (e.g., saffron cod) are well positioned to exploit the changing Arctic ecosystem. Another Arctic-boreal species, Dolly Varden (Salvelinus malma, Iqalukpik), appear to have already responded to warming by shifting from Arctic nearshore to shelf waters. More broadly, our findings suggest that areas of borealization could be widespread in the circumpolar nearshore.
Basin analysis and tectonic reconstructions of the Cenozoic history of the Death Valley region, California, USA, are hindered by a lack of volcanic (tuff) age control in many stratigraphic successions exposed in the Grapevine and Funeral Mountains of California, USA. Although maximum depositional ages (MDAs) interpreted from detrital zircon U-Pb data may be a promising alternative to volcanic ages, arguments remain regarding the calculation of MDAs including, but not limited to, the number of “young” grains to consider (i.e., the spectrum of dates used to calculate the MDA); which grains, if any, should be ignored; which approaches yield results that are statistically rigorous; and ultimately, which approaches result in ages that are geologically reasonable. We compare commonly used metrics of detrital zircon MDA for five sandstone samples from the Cenozoic strata exposed on Bat Mountain in the southern Funeral Mountains of California—i.e., the youngest single grain (YSG), the weighted mean of the youngest grain cluster of two or more grains at 1σ uncertainty (YC1σ(2+)) and of three or more grains at 2σ uncertainty (YC2σ(3+)), the youngest graphical peak (YPP), and the maximum likelihood age (MLA). Every sandstone sample yielded abundant Cenozoic zircon U-Pb dates that formed unimodal, near-normal age distributions that were clearly distinguishable from the next-oldest grains in each sample and showed an apparent up-section decrease in peak age. Benchmarked against published K/Ar and 40Ar/39Ar ages and five new zircon U-Pb ages of ash-fall tuffs, our analysis parallels prior studies and demonstrates that many MDA metrics—YSG, YC1σ(2+), YC2σ(3+), and YPP—drift toward unreasonably young or old values. In contrast, the maximum likelihood estimation approach and the resulting MLA metric consistently produce geologically appropriate estimates of MDA without arbitrary omission of any young (or old) zircon dates. Using the MLAs of sandstones and zircon U-Pb ages of interbedded ash-fall tuffs, we develop a new age model for the Oligocene–Miocene Amargosa Valley Formation (deposited ca. 28.5–18.5 Ma) and the Miocene Bat Mountain Formation (deposited ca. 15.5–13.5 Ma) and revise correlations to Cenozoic strata across the eastern Death Valley region.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02543.1","usgsCitation":"Schwartz, T.M., Souders, A., Lundstern, J., Gilmer, A.K., and Thompson, R., 2023, Revised age and regional correlations of Cenozoic strata on Bat Mountain, Death Valley region, California, USA, from zircon U-Pb geochronology of sandstones and ash-fall tuffs: Geosphere, v. 19, no. 1, p. 235-257, https://doi.org/10.1130/GES02543.1.","productDescription":"23 p.","startPage":"235","endPage":"257","ipdsId":"IP-139248","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":445066,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02543.1","text":"Publisher Index Page"},{"id":435534,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P982KK4D","text":"USGS data release","linkHelpText":"Zircon U-Pb data for ash-fall tuffs and sandstones of the Cenozoic Amargosa Valley and Bat Mountain Formations exposed on Bat Mountain, southern Funeral Mountains, California, USA"},{"id":411342,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bat Mountain, Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.12127468750195,\n 37.16000456147583\n ],\n [\n -117.12127468750195,\n 35.551070951522945\n ],\n [\n -115.75746797181529,\n 35.551070951522945\n ],\n [\n -115.75746797181529,\n 37.16000456147583\n ],\n [\n -117.12127468750195,\n 37.16000456147583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":245180,"corporation":false,"usgs":true,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Souders, Amanda 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":860788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lundstern, Jens-Erik 0000-0003-0000-8013","orcid":"https://orcid.org/0000-0003-0000-8013","contributorId":264189,"corporation":false,"usgs":true,"family":"Lundstern","given":"Jens-Erik","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":860791,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239011,"text":"70239011 - 2023 - Genetic architecture and evolution of color variation in American black bears","interactions":[],"lastModifiedDate":"2023-01-18T17:28:15.216346","indexId":"70239011","displayToPublicDate":"2022-12-16T07:49:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1352,"text":"Current Biology","active":true,"publicationSubtype":{"id":10}},"title":"Genetic architecture and evolution of color variation in American black bears","docAbstract":"Color variation is a frequent evolutionary substrate for camouflage in small mammals, but the underlying genetics and evolutionary forces that drive color variation in natural populations of large mammals are mostly unexplained. The American black bear, Ursus americanus (U. americanus), exhibits a range of colors including the cinnamon morph, which has a similar color to the brown bear, U. arctos, and is found at high frequency in the American southwest. Reflectance and chemical melanin measurements showed little distinction between U. arctos and cinnamon U. americanus individuals. We used a genome-wide association for hair color as a quantitative trait in 151 U. americanus individuals and identified a single major locus (p < 10−13). Additional genomic and functional studies identified a missense alteration (R153C) in Tyrosinase-related protein 1 (TYRP1) that likely affects binding of the zinc cofactor, impairs protein localization, and results in decreased pigment production. Population genetic analyses and demographic modeling indicated that the R153C variant arose 9.36 kya in a southwestern population where it likely provided a selective advantage, spreading both northwards and eastwards by gene flow. A different TYRP1 allele, R114C, contributes to the characteristic brown color of U. arctos but is not fixed across the range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cub.2022.11.042","usgsCitation":"Puckett, E., Davis, I.S., Harper, D.C., Wakamatsu, K., Battu, G., Belant, J., Beyer, D.E., Carpenter, C., Crupi, A., Davidson, M., DePerno, C.S., Forman, N., Fowler, N.L., Garshelis, D.L., Gould, N., Gunther, K., Haroldson, M.A., Ito, S., Kocka, D.M., Lackey, C., Leahy, R., Lee-Roney, C., Lewis, T., Lutto, A., McGowan, K., Olfenbuttel, C., Orlando, M., Platt, A., Pollard, M.D., Ramaker, M., Reich, H., Sajecki, J.L., Sell, S.K., Strules, J., Thompson, S., van Manen, F.T., Whitman, C., Williamson, R., Winslow, F., Kaelin, C.B., Marks, M.S., and Barsh, G.S., 2023, Genetic architecture and evolution of color variation in American black bears: Current Biology, v. 33, no. 1, p. 86-97, https://doi.org/10.1016/j.cub.2022.11.042.","productDescription":"12 p.","startPage":"86","endPage":"97","ipdsId":"IP-143084","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":445098,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10039708","text":"Publisher Index Page"},{"id":410793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.85157251445827,\n 25.6211792901653\n ],\n [\n -97.58268484778245,\n 23.084984518665763\n ],\n [\n -96.96832358817309,\n 27.11908661835035\n ],\n [\n -91.54341286821204,\n 29.674296848638633\n ],\n [\n -85.61608647951357,\n 30.00825129481538\n ],\n [\n -81.84087040426968,\n 26.400103408668386\n ],\n [\n -80.18411199752484,\n 26.92465845160062\n ],\n [\n -80.56235407106773,\n 31.76638154317395\n ],\n [\n -75.1885029754967,\n 35.619498983946855\n ],\n [\n -73.82570962813662,\n 39.802245647958785\n ],\n [\n -70.32156080785978,\n 42.731285388995474\n ],\n [\n -65.20253876832015,\n 44.75914396894834\n ],\n [\n -66.18489680108061,\n 43.67486445570324\n ],\n [\n -60.3982413153156,\n 45.77618805411478\n ],\n [\n -52.86860077882844,\n 47.48999714077618\n ],\n [\n -58.66729728770852,\n 55.854592629494135\n ],\n [\n -64.12779841707362,\n 60.11371527907423\n ],\n [\n -76.44848050666239,\n 63.10538026810016\n ],\n [\n -109.48842417309726,\n 66.7498526487866\n ],\n [\n -140.75947552586504,\n 67.40329083145704\n ],\n [\n -166.44571907544412,\n 65.70394653058045\n ],\n [\n -168.00858309753102,\n 60.67622546491444\n ],\n [\n -172.21140880784844,\n 60.83339346513449\n ],\n [\n -166.26803084694873,\n 59.54666069030014\n ],\n [\n -161.89508471831965,\n 58.29760083198573\n ],\n [\n -161.84501939855392,\n 56.218992211277936\n ],\n [\n -163.3965990246336,\n 55.42321766496832\n ],\n [\n -157.95494761717828,\n 55.46465046303916\n ],\n [\n -153.04594629078406,\n 57.78263455069717\n ],\n [\n -150.57652857683686,\n 59.37586371371165\n ],\n [\n -142.645601969195,\n 59.779723448669074\n ],\n [\n -133.62317137693802,\n 54.77924777921652\n ],\n [\n -125.14085680739743,\n 47.78704512961323\n ],\n [\n -124.56418312254539,\n 38.52255897996048\n ],\n [\n -119.5903644515603,\n 33.15932270643472\n ],\n [\n -115.27027549361577,\n 32.79226182167089\n ],\n [\n -107.84109362691999,\n 25.284249601824158\n ],\n [\n -107.85157251445827,\n 25.6211792901653\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Puckett, E.","contributorId":300214,"corporation":false,"usgs":false,"family":"Puckett","given":"E.","email":"","affiliations":[{"id":17864,"text":"University of Memphis","active":true,"usgs":false}],"preferred":false,"id":859684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, I. 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K.","contributorId":300245,"corporation":false,"usgs":false,"family":"Sell","given":"S.","email":"","middleInitial":"K.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":859714,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Strules, J.","contributorId":300246,"corporation":false,"usgs":false,"family":"Strules","given":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":859715,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Thompson, S.","contributorId":77103,"corporation":false,"usgs":false,"family":"Thompson","given":"S.","email":"","affiliations":[],"preferred":false,"id":859737,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859716,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Whitman, Craig 0000-0002-1187-4649 cwhitman@usgs.gov","orcid":"https://orcid.org/0000-0002-1187-4649","contributorId":206044,"corporation":false,"usgs":true,"family":"Whitman","given":"Craig","email":"cwhitman@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859717,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Williamson, R.","contributorId":300247,"corporation":false,"usgs":false,"family":"Williamson","given":"R.","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":859718,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Winslow, F.","contributorId":300248,"corporation":false,"usgs":false,"family":"Winslow","given":"F.","email":"","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":859719,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Kaelin, C. B.","contributorId":300249,"corporation":false,"usgs":false,"family":"Kaelin","given":"C.","email":"","middleInitial":"B.","affiliations":[{"id":65057,"text":"School of Medicine, Stanford","active":true,"usgs":false}],"preferred":false,"id":859720,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Marks, M. S.","contributorId":300250,"corporation":false,"usgs":false,"family":"Marks","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":64596,"text":"Perelman School of Medicine, University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":859721,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Barsh, G. S.","contributorId":300251,"corporation":false,"usgs":false,"family":"Barsh","given":"G.","email":"","middleInitial":"S.","affiliations":[{"id":65054,"text":"HudsonAlpha","active":true,"usgs":false}],"preferred":false,"id":859722,"contributorType":{"id":1,"text":"Authors"},"rank":42}]}} ,{"id":70247517,"text":"70247517 - 2023 - Estimates of k0 and effects on ground motions in the San Francisco Bay area","interactions":[],"lastModifiedDate":"2023-08-11T13:23:21.704651","indexId":"70247517","displayToPublicDate":"2022-12-13T07:00:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Estimates of k0 and effects on ground motions in the San Francisco Bay area","title":"Estimates of k0 and effects on ground motions in the San Francisco Bay area","docAbstract":"Ground‐motion studies are a key component of seismic hazard analyses and often rely on information of the source, path, and site. Extensive research has been done on each of these parameters; however, site‐specific studies are of particular interest to seismic hazard studies, especially in the field of earthquake engineering, as near‐site conditions can have a significant impact on the resulting ground motion at a site. There has been much focus on the constraint of site parameters and their application to seismic hazard studies, especially in the development of ground‐motion models (GMMs). Kappa is an observational parameter describing the high‐frequency attenuation of spectra, and its site contribution (
An essential goal in conservation biology is delineating population units that maximize the probability of species persisting into the future and adapting to future environmental change. However, future-facing conservation concerns are often addressed using retrospective patterns that could be irrelevant. We recommend a novel landscape genomics framework for delineating future “Geminate Evolutionary Units” (GEUs) in a focal species: (1) identify loci under environmental selection, (2) model and map adaptive conservation units that may spawn future lineages, (3) forecast relative selection pressures on each future lineage, and (4) estimate their fitness and likelihood of persistence using geo-genomic simulations. Using this process, we delineated conservation units for the Yosemite toad (Anaxyrus canorus), a U.S. federally threatened species that is highly vulnerable to climate change. We used a genome-wide dataset, redundancy analysis, and Bayesian association methods to identify 24 candidate loci responding to climatic selection (R2 ranging from 0.09 to 0.52), after controlling for demographic structure. Candidate loci included genes such as MAP3K5, involved in cellular response to environmental change. We then forecasted future genomic response to climate change using the multivariate machine learning algorithm Gradient Forests. Based on all available evidence, we found three GEUs in Yosemite National Park, reflecting contrasting adaptive optima: YF-North (high winter snowpack with moderate summer rainfall), YF-East (low to moderate snowpack with high summer rainfall), and YF-Low-Elevation (low snowpack and rainfall). Simulations under the RCP 8.5 climate change scenario suggest that the species will decline by 29% over 90 years, but the highly diverse YF-East lineage will be least impacted for two reasons: (1) geographically it will be sheltered from the largest climatic selection pressures, and (2) its standing genetic diversity will promote a faster adaptive response. Our approach provides a comprehensive strategy for protecting imperiled non-model species with genomic data alone and has wide applicability to other declining species.
","language":"English","publisher":"Wiley","doi":"10.1111/eva.13511","usgsCitation":"Maier, P., Vandergast, A.G., and Bohonak, A.J., 2023, Using landscape genomics to delineate future adaptive potential for climate change in the Yosemite toad (Anaxyrus canorus): Evolutionary Applications, v. 16, p. 74-97, https://doi.org/10.1111/eva.13511.","productDescription":"24 p.","startPage":"74","endPage":"97","ipdsId":"IP-147179","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eva.13511","text":"Publisher Index Page"},{"id":414614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Park, Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.85061210634456,\n 36.52123522076397\n ],\n [\n -118.13910750098108,\n 36.616475004823215\n ],\n [\n -118.44742616330538,\n 37.41654854711554\n ],\n [\n -119.44353261081429,\n 38.35710042889701\n ],\n [\n -120.2024708565354,\n 38.166222753255624\n ],\n [\n -120.45742667345743,\n 37.99820964775573\n ],\n [\n -119.61547955711029,\n 37.360016749403826\n ],\n [\n -118.85061210634456,\n 36.52123522076397\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","noUsgsAuthors":false,"publicationDate":"2022-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Maier, Paul A. 0000-0003-0851-8827","orcid":"https://orcid.org/0000-0003-0851-8827","contributorId":221033,"corporation":false,"usgs":false,"family":"Maier","given":"Paul A.","affiliations":[{"id":40313,"text":"Department of Biology, San Diego State","active":true,"usgs":false}],"preferred":false,"id":867267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":867268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohonak, Andrew J.","contributorId":195156,"corporation":false,"usgs":false,"family":"Bohonak","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":867269,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239254,"text":"70239254 - 2023 - Geochemistry and fluxes of gases from hydrothermal features at Newberry Volcano, Oregon, USA","interactions":[],"lastModifiedDate":"2023-01-10T15:16:44.498624","indexId":"70239254","displayToPublicDate":"2022-12-05T09:12:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and fluxes of gases from hydrothermal features at Newberry Volcano, Oregon, USA","docAbstract":"We present the chemical and isotopic compositions of gases and fluxes of CO2 from the hydrothermal features of Newberry Volcano, a large composite volcano located in Oregon's Cascade Range with a summit caldera that hosts two lakes, Paulina and East Lakes. Gas samples were collected from 1982 to 2021 from Paulina Hot Springs (PHS) on the shore of Paulina Lake, East Lake Hot Springs (ELHS) on the shore of East Lake, and Obsidian Flow Gas Seep (OFGS), an area of diffuse gas emissions. Surveys of CO2 flux were conducted in 2020 at OFGS (1400 m2) and East Lake (4.1 km2). Gases from all three sites were CO2-rich (≥79 mol% in dry gas) but showed considerable compositional variability over time due to interaction with ground and surface water. An increase in H2S concentrations and decline in CO2/H2S ratios in ELHS gases coincided with a drop in East Lake water level from 1999 to 2021. ELHS and OFGS gases were high in CH4 relative to PHS and the δ13C of CH4 values for ELHS gases (−72.2 and − 63.6 ‰) reflected a predominantly biogenic origin. The dominant source of N2 and Ar in PHS, ELHS, and OFGS samples was likely groundwater. Helium isotopic ratios (6.47 to 8.02 Rc/Ra) support a persistent source of magmatic He beneath Newberry caldera and consistently high values measured at OFGS and PHS relative to ELHS suggest distinct fluid flow paths from depth to the surface features. The δ13C of CO2 and CO2/3He values (−8.9 to −5.35 ‰ and 1.3 × 109 to 4.6 × 1010, respectively) measured in gases reflect contributions of CO2 from both mantle and crustal sources. Measured CO2 fluxes at OFGS and East Lake ranged from 1 to 8808 and < 1 to 364 g m−2 d−1, respectively. A CO2 emission rate of 0.5 t d−1 was calculated for OFGS. The CO2 emission rate estimated for East Lake was 30 t d−1 and when compared to prior estimates, reflects steady-state lake degassing. An enhanced geochemical monitoring plan, including annual sampling of gases at ELHS, OFGS, and PHS for geochemical analysis, installation of a continuous lake-level monitoring station at East Lake, and annual CO2 flux surveys at OFGS, would provide valuable background data and insights into any precursor volcanic activity. Integrating geochemical data with data from the real-time seismic and GPS network at Newberry Volcano could better resolve and interpret potential changes in its magma-hydrothermal system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107729","usgsCitation":"Lewicki, J.L., Evans, W.C., Ingebritsen, S.E., Clor, L., Kelly, P.J., Peek, S., Jensen, R.A., and Hunt, A., 2023, Geochemistry and fluxes of gases from hydrothermal features at Newberry Volcano, Oregon, USA: Journal of Volcanology and Geothermal Research, v. 433, 107729, 16 p., https://doi.org/10.1016/j.jvolgeores.2022.107729.","productDescription":"107729, 16 p.","ipdsId":"IP-142077","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445171,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2022.107729","text":"Publisher Index Page"},{"id":411629,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Newberry Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.4446630583071,\n 43.958977799999275\n ],\n [\n -121.4446630583071,\n 43.4616991485112\n ],\n [\n -121.0217250470551,\n 43.4616991485112\n ],\n [\n -121.0217250470551,\n 43.958977799999275\n ],\n [\n -121.4446630583071,\n 43.958977799999275\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"433","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":860928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ingebritsen, Steven E. 0000-0001-6917-9369 seingebr@usgs.gov","orcid":"https://orcid.org/0000-0001-6917-9369","contributorId":818,"corporation":false,"usgs":true,"family":"Ingebritsen","given":"Steven","email":"seingebr@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":860929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clor, Laura E. 0000-0003-2633-5100","orcid":"https://orcid.org/0000-0003-2633-5100","contributorId":209969,"corporation":false,"usgs":true,"family":"Clor","given":"Laura E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Peter J. 0000-0002-3868-1046 pkelly@usgs.gov","orcid":"https://orcid.org/0000-0002-3868-1046","contributorId":5931,"corporation":false,"usgs":true,"family":"Kelly","given":"Peter","email":"pkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":860932,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jensen, Robert A.","contributorId":35469,"corporation":false,"usgs":false,"family":"Jensen","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":860933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hunt, Andrew G. 0000-0002-3810-8610","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":206197,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":860934,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70256602,"text":"70256602 - 2023 - Differential hypoxia tolerance of eastern oysters from the northern Gulf of Mexico at elevated temperature","interactions":[],"lastModifiedDate":"2024-08-23T16:39:24.755117","indexId":"70256602","displayToPublicDate":"2022-12-01T11:33:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2277,"text":"Journal of Experimental Marine Biology and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Differential hypoxia tolerance of eastern oysters from the northern Gulf of Mexico at elevated temperature","docAbstract":"Increasing prevalence of hypoxia in shallow waters of U.S. Gulf of Mexico (GoM) estuaries can pose a serious threat to eastern oysters (Crassostrea virginica). Their tolerance to hypoxia, however, is not well characterized, especially at elevated temperatures (>30 °C) typical of GoM estuaries in summer. Moreover, it is unknown whether differences in hypoxia tolerance exist between GoM oyster populations growing in estuaries differing in local environmental conditions. Wild oyster broodstocks were collected from four estuarine sites in Texas (Packery Channel, PC and Aransas Bay, AB) and Louisiana (Calcasieu Lake, CL and Vermilion Bay, VB) and their adult progenies (F1) were tested (Study 1) under continuous hypoxia (<2.0 mg O2 L−1) at 32 °C. Significant differences in hypoxia tolerance were found between F1 populations with calculated median lethal time (LT50) ranging from 3.9 to 12.5 days. PC and CL oysters were the most and least tolerant populations, respectively. The study was repeated twice more (Studies 2 and 3) using PC and CL oysters, and their responses at the organismic, cellular, and biochemical levels were investigated. Valve movement was monitored, and oysters were sampled to measure hemocyte density, plasma protein, calcium and glutathione concentrations, and digestive gland alanine and succinate concentrations after either 3–5 days (Study 2) or 1–3 days (Study 3) of hypoxia exposure. From the onset of hypoxia until their death, oysters stayed opened 13–32% of the time compared to 53–64% under normoxia, but no differences between populations were detected under hypoxia. PC oyster but not CL oyster plasma glutathione concentrations increased significantly in both studies. Under longer (3–5 days) hypoxia exposure, plasma calcium and glutathione concentrations of PC oysters were significantly higher than CL oysters. These results suggest PC oysters were better able to protect tissues against acidosis and oxidative damage during hypoxia and high temperature stress than CL oysters. Overall, our results indicate that oyster populations originating from the GoM vary in their response to hypoxia and high temperature stress and possess differential tolerance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jembe.2022.151840","usgsCitation":"Coxe, N., Casas, S.M., Marshall, D., La Peyre, M., Kelly, M.W., and La Peyre, J.F., 2023, Differential hypoxia tolerance of eastern oysters from the northern Gulf of Mexico at elevated temperature: Journal of Experimental Marine Biology and Ecology, v. 559, 151840, 11 p., https://doi.org/10.1016/j.jembe.2022.151840.","productDescription":"151840, 11 p.","ipdsId":"IP-142239","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499844,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/animalsciences_pubs/2258","text":"External Repository"},{"id":433112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Louisiana, Mississippi, Texas","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.41593828686382,\n 26.24620150154975\n ],\n [\n -87.8147474310154,\n 30.18094270243091\n ],\n [\n -88.19816867786844,\n 31.00775203702119\n ],\n [\n -95.65904444535767,\n 29.715904561157274\n ],\n [\n -98.19488550583708,\n 27.38532092313082\n ],\n [\n -97.41593828686382,\n 26.24620150154975\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"559","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coxe, Nicholas","contributorId":341331,"corporation":false,"usgs":false,"family":"Coxe","given":"Nicholas","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":908246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casas, Sandra M.","contributorId":145452,"corporation":false,"usgs":false,"family":"Casas","given":"Sandra","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":908247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marshall, Danielle A.","contributorId":239867,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle A.","affiliations":[{"id":48014,"text":"School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":908248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Morgan W.","contributorId":341332,"corporation":false,"usgs":false,"family":"Kelly","given":"Morgan","email":"","middleInitial":"W.","affiliations":[{"id":13321,"text":"Texas A & M University","active":true,"usgs":false}],"preferred":false,"id":908250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"La Peyre, Jerome F.","contributorId":177346,"corporation":false,"usgs":false,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":908252,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254592,"text":"70254592 - 2023 - The Far-Field imprint of the late Paleozoic Ice Age, its demise, and the onset of a dust-house climate across the Eastern Shelf of the Midland Basin, Texas","interactions":[],"lastModifiedDate":"2024-06-04T11:38:15.455109","indexId":"70254592","displayToPublicDate":"2022-11-25T06:35:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1848,"text":"Gondwana Research","active":true,"publicationSubtype":{"id":10}},"title":"The Far-Field imprint of the late Paleozoic Ice Age, its demise, and the onset of a dust-house climate across the Eastern Shelf of the Midland Basin, Texas","docAbstract":"The late Paleozoic is a period of pronounced climatic and tectonic change, characterized by the onset and disappearance of continental-scale glaciers across polar Gondwana, the formation of Pangea, and widespread large igneous province volcanism. The low-latitude equatorial tropics are assumed to be places of persistent warm and wet climatic conditions throughout the Phanerozoic, which through intense silicate weathering, exert a major influence on Earth’s climate via the consumption of atmospheric carbon through carbonic hydrolytic weathering, formation of clay minerals and deliverability of alkalinity to ocean basins. Here we investigate the late Paleozoic sedimentary record of the Eastern Shelf of the Midland Basin in order to refine the climatic and provenance record of this region. The Eastern Shelf of the Midland Basin was situated within the equatorial tropics throughout the late Paleozoic and was connected to the open ocean through a network of fluvial systems that drained into the marine Midland Basin. We present new U-Pb zircon geochronology (19 samples, 2591 analyses) and sedimentary petrography (11 samples, 5800 grain counts), which we integrate with previously published paleobotany, paleosol chemistry and clay mineralogy to provide a holistic climate and tectonic record from this region. We observe major changes in sedimentary processes that we attribute to the formation of Pangea, eustatic changes linked to a dynamic high-latitude glaciation and teleconnections with low latitude hydrology, and a long-term shift in the Earth climate system all of which result in a dynamic sediment provenance history. Late Pennsylvanian and earliest Permian deposits are enriched in zircons with local affinity and interpreted to reflect local uplift and repeat incision across the basin margin, the latter a result of glacioeustatic forcing during an “everwet” climate. A major paleoenvironmental shift occurs in the late early Permian, which is reflected by the transition from fluvial to mixed fluvial-aeolian and ultimately aeolian dominant sedimentation by the late Permian. The transition from fluvial to aeolian dominant sedimentation is accompanied by a change in clay chemistry, sedimentary rock textual maturity, paleosol morphology and a threefold increase in Paleozoic zircons in the mid to late Permian strata. Widespread loess deposits across equatorial Pangea during the Permian have been used to argue for the possibility of equatorial glaciers situated in highland settings during the early Permian. Conversely, our data suggest initiation of a substantial component of aeolian deposition across the field areas, which is coincident with widespread ice loss across high latitude Gondwana, and ultimately highlights the teleconnections between high latitude glaciation and the low latitude hydrologic cycle.
The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5–11 years on COVID-19 burden and resilience against variant strains.
Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5–11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses.
Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5–11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880–0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834–0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797–1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed.
Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5–11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.
Various (see acknowledgments).
Understanding species' associations with physical habitat conditions is a fundamental goal of ecology. For organisms that occupy lotic ecosystems, relationships to streamflow are of particular importance, but these associations are unstudied for most species. We tested the predictability of fish–microhabitat relationships in river shoals (shallow, rocky areas with relatively swift water flow) using a large data set from the Conasauga River in Georgia, USA. Our objective was to assess the consistency of species-specific relationships with flow-dependent variables (depth, velocity, Reynolds number and Froude number) while accounting for other microhabitat variables (e.g. vegetation). We used data from 8285 seine-sets collected during late summer or autumn at 26 sites over 12 years to relate occurrence and counts of 22 fish species to habitat variables using generalised linear multiple regression models. Results showed that microhabitat models explained a substantial amount of the variation in counts for some species, although other species were poorly predicted. We classified 16 species as velocity specialists and nine species as depth specialists, with six species specialised for depth and velocity and three species classified as depth and velocity generalists. The variability in habitat associations that we observed suggests that species will be unevenly affected by anthropogenic activities that alter flows.
Best management practices (BMPs) have been predominantly used throughout the Chesapeake Bay watershed (CBW) to reduce nutrients and sediments entering streams, rivers, and the bay. These practices have been successful in reducing loads entering the estuary and have shown the potential to reduce other contaminants (pesticides, hormonally active compounds, pathogens) in localized studies and modeled load estimates. However, further understanding of relationships between BMPs and non-nutrient contaminant reductions at regional scales using sampled data would be beneficial. Total estrogenic activity was measured in surface water samples collected over a decade (2008–2018) in 211 undeveloped NHDPlus V2.1 watersheds within the CBW. Bayesian hierarchical modeling between total estrogenic activity and landscape predictors including landcover, runoff, BMP intensity, and a BMP*agriculture intensity interaction term indicates a 96% posterior probability that BMP intensity on agricultural land is reducing total estrogenic activity. Additionally, watersheds with high agriculture and low BMPs had a 49% posterior probability of exceeding an effects-based threshold in aquatic organisms of 1 ng/L but only a 1% posterior probability of exceeding this threshold in high-agriculture, high-BMP watersheds.
Geologic carbon storage (GCS) is likely to be an important part of global efforts to decarbonize the energy industry. Widespread deployment of GCS relies on strategies to maximize CO2 injection rates while minimizing reservoir pressurization that could induce seismicity and/or fluid leakage into groundwater resources. Brine extraction from CO2 storage formations with subsurface reinjection elsewhere could mitigate pressure buildup associated with GCS. Therefore, evaluation of CO2 storage resources should consider the injectivity of produced brine in geologic layers above or below the CO2 storage formation. For this study, a methodology was developed to estimate brine injectivity from formation depth and thickness using flow modeling and optimization techniques. The methodology was demonstrated in the Illinois Basin, where GCS in the Mt. Simon Sandstone is ongoing. Based on pressure constraints and considering only regions of the shallower units where salinity and sealing conditions were met, maximum brine injection rates were estimated within the Mt. Simon and three overlying hydrostratigraphic layers. Results indicate that a large area exists where CO2 injectivity could be optimized by brine extraction and reinjection.
As climate change alters the global environment, it is critical to understand the relationship between shifting climate suitability and species distributions. Key questions include whether observed changes in population abundance are aligned with the velocity and direction of shifts predicted by climate suitability models and if the responses are consistent among species with similar ecological traits. We examined the direction and velocity of the observed abundance-based distribution centroids compared with the model-predicted bioclimatic distribution centroids of 250 bird species across the United States from 1969 to 2011. We hypothesized that there is a significant positive correlation in both direction and velocity between the observed and the modeled shifts. We then tested five additional hypotheses that predicted differential shifting velocity based on ecological adaptability and climate change exposure. Contrary to our hypotheses, we found large differences between the observed and modeled shifts among all studied bird species and within specific ecological guilds. However, temperate migrants and habitat generalist species tended to have higher velocity of observed shifts than other species. Neotropical migratory and wetland birds also had significantly different observed velocities than their counterparts, which may be due to their climate change exposure. The velocity based on modeled bioclimatic suitability did not exhibit significant differences among most guilds. Boreal forest birds were the only guild with significantly faster modeled-shifts than the other groups, suggesting an elevated conservation risk for high latitude and altitude species. The highly idiosyncratic species responses to climate and the mismatch between shifts in modeled and observed distribution centroids highlight the challenge of predicting species distribution change based solely on climate suitability and the importance of non-climatic factors traits in shaping species distributions.
A multi-omics approach was utilized to identify altered biological responses and functions, and to prioritize contaminants to assess the risks of chemical mixtures in the Maumee Area of Concern (AOC), Maumee River, OH, USA. The Maumee AOC is designated by the United States Environmental Protection Agency as having significant beneficial use impairments, including degradation of fish and wildlife populations, bird or animal deformities or reproduction problems, and loss of fish and wildlife habitat. Tree swallow (Tachycineta bicolor) nestlings were collected at five sites along the Maumee River, which included wastewater treatment plants (WWTPs) and industrial land-use sites. Polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), polycyclic aromatic hydrocarbons (PAHs), polychlorinated dibenzo p dioxins and furans (PCDD/Fs), and chlorinated pesticide concentrations were elevated in Maumee tree swallows, relative to a remote reference site, Star Lake, WI, USA. Liver tissue was utilized for non-targeted transcriptome and targeted metabolome evaluation. A significantly differentially expressed gene cluster related to a downregulation in cell growth and cell cycle regulation was identified when comparing all Maumee River sites with the reference site. There was an upregulation of lipogenesis genes, such as PPAR signaling (HMGCS2, SLC22A5), biosynthesis of unsaturated fatty acids (FASN, SCD, ELOVL2, and FADS2), and higher lipogenesis related metabolites, such as docosapentaenoic acid (DPA), docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and arachidonic acid (AA) at two industrial land-use sites, Ironhead and Maumee, relative to WWTP sites (Perrysburg and SideCut), and the reference site. Toledo Water, in the vicinity of the other two industrial sites and also adjacent to a WWTP, showed a mix of signals between industrial land-use and WWTP land-use. PAHs, oxychlordane, and PBDEs were determined to be the most likely causes of the differentiation in biological responses, including de novo lipogenesis and biosynthesis of unsaturated fatty acids.
Wastewater treatment plant (WWTP) effluent-dominated streams provide critical habitat for aquatic and terrestrial organisms but also continually expose them to complex mixtures of pharmaceuticals that can potentially impair growth, behavior, and reproduction. Currently, few biomarkers are available that relate to pharmaceutical-specific mechanisms of action. In the experiment reported in this paper, zebrafish (Danio rerio) embryos at two developmental stages were exposed to water samples from three sampling sites (0.1 km upstream of the outfall, at the effluent outfall, and 0.1 km below the outfall) during base-flow conditions from two months (January and May) of a temperate-region effluent-dominated stream containing a complex mixture of pharmaceuticals and other contaminants of emerging concern. RNA-sequencing identified potential biological impacts and biomarkers of WWTP effluent exposure that extend past traditional markers of endocrine disruption. Transcriptomics revealed changes to a wide range of biological functions and pathways including cardiac, neurological, visual, metabolic, and signaling pathways. These transcriptomic changes varied by developmental stage and displayed sensitivity to variable chemical composition and concentration of effluent, thus indicating a need for stage-specific biomarkers. Some transcripts are known to be associated with genes related to pharmaceuticals that were present in the collected samples. Although traditional biomarkers of endocrine disruption were not enriched in either month, a high estrogenicity signal was detected upstream in May and implicates the presence of unidentified chemical inputs not captured by the targeted chemical analysis. This work reveals associations between bioeffects of exposure, stage of development, and the composition of chemical mixtures in effluent-dominated surface water. The work underscores the importance of measuring effects beyond the endocrine system when assessing the impact of bioactive chemicals in WWTP effluent and identifies a need for non-targeted chemical analysis when bioeffects are not explained by the targeted analysis.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.159069","usgsCitation":"Meade, E.B., Iwanowicz, L., Neureuther, N., LeFevre, G.H., Kolpin, D., Zhi, H., Meppelink, S.M., Lane, R.F., Schmoldt, A., Mohaimani, A., Mueller, O., and Klaper, R.D., 2023, Transcriptome signatures of wastewater effluent exposure in larval zebrafish vary with seasonal mixture composition in an effluent-dominated stream: Science of the Total Environment, v. 856, no. Part 2, 159069, 12 p., https://doi.org/10.1016/j.scitotenv.2022.159069.","productDescription":"159069, 12 p.","ipdsId":"IP-128563","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445405,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12503111/","text":"Publisher Index Page"},{"id":408539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","city":"North Liberty","otherGeospatial":"Muddy Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.59782409667969,\n 41.70624114327587\n ],\n [\n -91.5216064453125,\n 41.70624114327587\n ],\n [\n -91.5216064453125,\n 41.75236092824208\n ],\n [\n -91.59782409667969,\n 41.75236092824208\n ],\n [\n -91.59782409667969,\n 41.70624114327587\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"856","issue":"Part 2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Meade, Emma B.","contributorId":298074,"corporation":false,"usgs":false,"family":"Meade","given":"Emma","email":"","middleInitial":"B.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":855054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":855055,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neureuther, Nicklaus","contributorId":298075,"corporation":false,"usgs":false,"family":"Neureuther","given":"Nicklaus","email":"","affiliations":[],"preferred":false,"id":855056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":855057,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":247493,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855058,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhi, Hui","contributorId":225502,"corporation":false,"usgs":false,"family":"Zhi","given":"Hui","email":"","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":855059,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meppelink, Shannon M. 0000-0003-1294-7878","orcid":"https://orcid.org/0000-0003-1294-7878","contributorId":205653,"corporation":false,"usgs":true,"family":"Meppelink","given":"Shannon","email":"","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":855060,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lane, Rachael F. 0000-0001-9202-0612","orcid":"https://orcid.org/0000-0001-9202-0612","contributorId":222471,"corporation":false,"usgs":true,"family":"Lane","given":"Rachael","email":"","middleInitial":"F.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":855061,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schmoldt, Angela","contributorId":298078,"corporation":false,"usgs":false,"family":"Schmoldt","given":"Angela","email":"","affiliations":[{"id":64490,"text":"Great Lakes Genomics Center","active":true,"usgs":false}],"preferred":false,"id":855062,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mohaimani, Aurash","contributorId":298079,"corporation":false,"usgs":false,"family":"Mohaimani","given":"Aurash","email":"","affiliations":[{"id":64490,"text":"Great Lakes Genomics Center","active":true,"usgs":false}],"preferred":false,"id":855063,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mueller, Olaf","contributorId":298080,"corporation":false,"usgs":false,"family":"Mueller","given":"Olaf","email":"","affiliations":[{"id":64490,"text":"Great Lakes Genomics Center","active":true,"usgs":false}],"preferred":false,"id":855064,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Klaper, Rebecca D.","contributorId":218114,"corporation":false,"usgs":false,"family":"Klaper","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":855065,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70236439,"text":"70236439 - 2023 - Range-wide sources of variation in reproductive rates of northern spotted owls","interactions":[],"lastModifiedDate":"2023-01-18T16:01:33.826947","indexId":"70236439","displayToPublicDate":"2022-08-25T06:36:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Range-wide sources of variation in reproductive rates of northern spotted owls","docAbstract":"We conducted a range-wide investigation of the dynamics of site level reproductive rate of northern spotted owls using survey data from 11 study areas across the sub-species geographic range collected during 1993–2018. Our analytical approach accounted for imperfect detection of owl pairs and misclassification of successful reproduction (i.e., at least one young fledged) and contributed further insights into northern spotted owl population ecology and dynamics. Both nondetection and state misclassification were important, especially because factors affecting these sources of error also affected focal ecological parameters. Annual probabilities of site occupancy were greatest at sites with successful reproduction in the previous year and lowest for sites not occupied by a pair in the previous year. Site-specific occupancy transition probabilities declined over time and were negatively affected by barred owl presence. Overall, the site-specific probability of successful reproduction showed substantial year-to-year fluctuations and was similar for occupied sites that did and did not experience successful reproduction the previous year. Site-specific probabilities for successful reproduction were very small for sites that were unoccupied the previous year. Barred owl presence negatively affected the probability of successful reproduction by northern spotted owls in Washington and California, as predicted, but the effect in Oregon was mixed. The proportions of sites occupied by northern spotted owl pairs showed steep, near-monotonic declines over the study period, with all study areas showing the lowest observed levels of occupancy to date. If trends continue it is likely that northern spotted owls will become extirpated throughout large portions of their range in the coming decades.
Spatiotemporal constraints for Late Cretaceous tectonism across the Colorado Plateau and southern Rocky Mountains (northern Arizona−New Mexico, USA) are interpreted in regards to Laramide orogenic mechanisms. Onset of Laramide arch development is estimated from cooling recorded in representative thermochronologic samples in a three-step process of initial forward models, secondary HeFTy inverse models with informed constraint boxes, and a custom script to statistically estimate timing of rapid cooling from inverse model results. Onset of Laramide basin development is interpreted from increased rates of tectonic subsidence. Onset estimates are compared to published estimates for Laramide timing, and together suggest tectonism commenced ca. 90 Ma in northwestern Arizona and progressed eastward with later onset in north-central New Mexico by ca. 75−70 Ma. The interpreted sweep of onset progressed at a rate of ∼50 km/m.y. and was approximately half the 100−150 km/m.y. rate estimated for Late Cretaceous Farallon-North America convergence during the same timeframe. Previous suggestions that the Laramide tectonic front progressed at a rate similar to convergence via basal traction are not supported by our results. We thereby suggest that (1) a plate margin end load established far field compression and that (2) sequential Laramide-style strain was facilitated by progressive weakening of North American lithosphere from the dehydrating Farallon flat slab. Results are compared to models of sweeping tectonism and magmatism in other parts of the Laramide foreland. Discussions of the utility of the custom script and the potential for stratigraphic constraints to represent only minimum onset estimates are also presented.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B36245.1","usgsCitation":"Thacker, J., Karlstrom, K., Kelley, S., Crow, R.S., and Kendall, J., 2023, Late Cretaceous time-transgressive onset of Laramide arch exhumation and basin subsidence across northern Arizona−New Mexico, USA, and the role of a dehydrating Farallon flat slab: GSA Bulletin, v. 135, no. 1-2, p. 389-406, https://doi.org/10.1130/B36245.1.","productDescription":"18 p.","startPage":"389","endPage":"406","ipdsId":"IP-122202","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":445525,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/gsab.s.19362371","text":"External Repository"},{"id":401533,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.818359375,\n 33.90689555128866\n ],\n [\n -103.447265625,\n 33.90689555128866\n ],\n [\n -103.447265625,\n 37.020098201368114\n ],\n [\n -113.818359375,\n 37.020098201368114\n ],\n [\n -113.818359375,\n 33.90689555128866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"135","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2022-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Thacker, Jacob","contributorId":292189,"corporation":false,"usgs":false,"family":"Thacker","given":"Jacob","affiliations":[{"id":62838,"text":"NMBG","active":true,"usgs":false}],"preferred":false,"id":844026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karlstrom, Karl","contributorId":292190,"corporation":false,"usgs":false,"family":"Karlstrom","given":"Karl","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":844027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Shari","contributorId":292191,"corporation":false,"usgs":false,"family":"Kelley","given":"Shari","affiliations":[{"id":62838,"text":"NMBG","active":true,"usgs":false}],"preferred":false,"id":844028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crow, Ryan S. 0000-0002-2403-6361 rcrow@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-6361","contributorId":5792,"corporation":false,"usgs":true,"family":"Crow","given":"Ryan","email":"rcrow@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":844029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, Jerry","contributorId":292192,"corporation":false,"usgs":false,"family":"Kendall","given":"Jerry","email":"","affiliations":[{"id":16658,"text":"UNM","active":true,"usgs":false}],"preferred":false,"id":844030,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70229514,"text":"70229514 - 2023 - Using genetic data to advance stream fish reintroduction science: A case study in brook trout","interactions":[],"lastModifiedDate":"2023-01-18T15:46:36.932566","indexId":"70229514","displayToPublicDate":"2022-03-03T07:12:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using genetic data to advance stream fish reintroduction science: A case study in brook trout","docAbstract":"Widespread extirpation of native fish populations has led to a rise in species reintroduction efforts worldwide. Most efforts have relied on demographic data alone to guide project design and evaluate success. However, the genetic characteristics of many imperiled fish populations including low diversity, local adaptation, and hatchery introgression emphasize the importance of genetic data in the design and monitoring of reintroduction efforts. Focusing on a case study of brook trout (Salvelinus fontinalis) in North Carolina, USA, we show how the combined use of genetic and demographic data can support reintroduction efforts by improving source population selection and providing opportunities to evaluate genetic viability and adaptive potential in restored populations. Using this combined approach, we reintroduced brook trout into a restored stream from two source populations and monitored changes in genetic diversity and population size in source and recipient populations. Three years after the initial translocation, the reintroduced population had comparable density, but higher genetic diversity, than either source population. This study demonstrates the utility of genetic and demographic data for reintroduction efforts, particularly when extant populations are genetically depauperate and maintaining adaptive potential is a primary restoration goal. However, we emphasize the value of continued monitoring at longer temporal and spatial scales to determine the effects of stochastic process on the long-term adaptive capacity and persistence of reintroduced populations. Overall, inclusion of genetic data in reintroduction efforts offers increased ability to meet project goals while simultaneously conserving critical sources of adaptive variation that exist across the landscape.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.13662","usgsCitation":"White, S.L., Johnson, T.C., Rash, J.M., Lubinski, B.A., and Kazyak, D., 2023, Using genetic data to advance stream fish reintroduction science: A case study in brook trout: Restoration Ecology, v. 31, no. 1, e13662, 13 p., https://doi.org/10.1111/rec.13662.","productDescription":"e13662, 13 p.","ipdsId":"IP-131735","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":397018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North 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Carolina\",\"nation\":\"USA \"}}]}","volume":"31","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":837716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Thomas C","contributorId":245999,"corporation":false,"usgs":false,"family":"Johnson","given":"Thomas","email":"","middleInitial":"C","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":837717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rash, Jacob M","contributorId":218128,"corporation":false,"usgs":false,"family":"Rash","given":"Jacob","email":"","middleInitial":"M","affiliations":[{"id":39760,"text":"Division of Inland Fisheries, North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":837718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":837719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":837720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250096,"text":"70250096 - 2022 - Evaluating the influence of the Forestry Reclamation Approach on throughfall quantity in eastern Kentucky","interactions":[],"lastModifiedDate":"2024-06-03T14:45:20.437591","indexId":"70250096","displayToPublicDate":"2023-08-02T06:32:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17091,"text":"Reclamation Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the influence of the Forestry Reclamation Approach on throughfall quantity in eastern Kentucky","docAbstract":"The Appalachian Region is a rich forested ecosystem that has been impacted by coal mining. The Surface Mining Control and Reclamation Act of 1977 was enacted to resolve many of the environmental problems caused by surface mining. Reclamation practices resulted in excessive soil compaction and use of nonnative grasses and shrubs that have altered hydrologic processes. The Forestry Reclamation Approach (FRA) is a best practice for reestablishing forested ecosystems on mined lands in Appalachia. This project evaluated precipitation throughfall in reforested 10- and 20-year-old FRA sites and unmined 100-year-old forest stands as a metric for evaluating the return of forest hydrologic function after reclamation. Stands of coniferous and deciduous trees were evaluated independently for each age class. Throughfall rates were significantly impacted by tree type and age. Throughfall in coniferous trees was less than in deciduous trees, and throughfall in the 10-year-old deciduous trees tended to be highest. Throughfall was also significantly impacted by storm characteristics. Higher rainfall depth and longer duration resulted in significantly larger throughfall depths under both coniferous and deciduous stands, whereas increased intensity increased throughfall depths for the 10- and 100-year-old plots, but not for the 20-year-old plots. As canopy closure occurs in young FRA forests, throughfall rates resemble those reported for young, naturally regenerating forests in the region. Results may help guide management of forested watershed strategies to reduce surface runoff and local flooding on reclaimed surface mined lands.
","language":"English","publisher":"Allen Press","doi":"10.21000/rcsc-202200009","usgsCitation":"Gerlitz, M., Agouridis, C.T., Williamson, T.N., and Barton, C.D., 2022, Evaluating the influence of the Forestry Reclamation Approach on throughfall quantity in eastern Kentucky: Reclamation Sciences, v. 1, p. 13-24, https://doi.org/10.21000/rcsc-202200009.","productDescription":"12 p.","startPage":"13","endPage":"24","ipdsId":"IP-122841","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":445584,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21000/rcsc-202200009","text":"Publisher Index Page"},{"id":422673,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","county":"Breathitt County, Knott County, Perry County","otherGeospatial":"Laurel Fork Mine, Starfire Mine, Robinson Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.18644168615366,\n 37.484780966469884\n ],\n [\n -83.18644168615366,\n 37.41427280145203\n ],\n [\n -83.08730948291287,\n 37.41427280145203\n ],\n [\n -83.08730948291287,\n 37.484780966469884\n ],\n [\n -83.18644168615366,\n 37.484780966469884\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","noUsgsAuthors":false,"publicationDate":"2023-08-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Gerlitz, Morgan","contributorId":331640,"corporation":false,"usgs":false,"family":"Gerlitz","given":"Morgan","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":888322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Agouridis, Carmen T. 0000-0001-9580-6143","orcid":"https://orcid.org/0000-0001-9580-6143","contributorId":150223,"corporation":false,"usgs":false,"family":"Agouridis","given":"Carmen","email":"","middleInitial":"T.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":888323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barton, Chris D. 0000-0003-0692-3079","orcid":"https://orcid.org/0000-0003-0692-3079","contributorId":236883,"corporation":false,"usgs":false,"family":"Barton","given":"Chris","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":888325,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70208532,"text":"sim3420 - 2022 - Regional water table in the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014","interactions":[],"lastModifiedDate":"2026-02-19T17:29:40.380597","indexId":"sim3420","displayToPublicDate":"2023-02-03T06:58:34","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3420","displayTitle":"Regional Water Table in the Antelope Valley and Fremont Valley Groundwater Basins, Southwestern Mojave Desert, California, March 2014","title":"Regional water table in the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014","docAbstract":"Water levels were measured during March 2014 in wells in the Antelope Valley and Fremont Valley groundwater basins, southwestern Mojave Desert, California, in cooperation with the Antelope Valley-East Kern Water District, Palmdale Water District, and Littlerock Creek Irrigation District. A regional water-table map was constructed. Historical water-level data from the USGS National Water Information System (NWIS) database were used to construct water-level hydrographs to show long-term (1917-2014) water-level changes in the Antelope Valley and Fremont Valley groundwater basins.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sim3420","collaboration":"Prepared in cooperation with the Antelope Valley State Water Contractors Association","usgsCitation":"Dick, M.C., Teague, N.F., 2018, Regional water table in the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014: U.S. Geological Survey Scientific Investigations Map 3420, 2 p., https://doi.org/10.3133/sim3420","productDescription":"Data Release; HTML Document; 2 Sheets: 27.89 × 32.94 inches and 27.89 × 32.94 inches","ipdsId":"IP-075082","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":500196,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114336.htm","linkFileType":{"id":5,"text":"html"}},{"id":412692,"rank":6,"type":{"id":18,"text":"Project Site"},"url":"https://ca.water.usgs.gov/projects/antelope-valley/"},{"id":402402,"rank":1,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3420/sim3420_sheet1.pdf","text":"Sheet 1","size":"104 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3420 Sheet 1 of 2","linkHelpText":"- Regional water table in the Antelope Valley and Fremont Valley groundwater basins, southwestern Mojave Desert, California, March 2014"},{"id":402405,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3420/covrthb.jpg"},{"id":402403,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3420/sim3420_sheet2.pdf","text":"Sheet 2","size":"65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3420 Sheet 2 of 2","linkHelpText":"- Regional water-table change in the Antelope Valley and Fremont Valley groundwater basins, southwestern Mojave Desert, California, Spring 1996–2014"},{"id":402404,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sim/3420/versionHist.txt"},{"id":405486,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IQIP0L","text":"Regional water table Contours of the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014","description":"Dick, M.C., Teague, N.F., Fenton, N.C., 2022, Regional water table Contours of the Antelope Valley and Fremont Valley groundwater basins, Southwestern Mojave Desert, California, March 2014: U.S. Geological Survey data release, [available at https://doi.org/10.5066/P9IQIP0L]."}],"country":"United States","state":"California","otherGeospatial":"Mohave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.90567382213953,\n 36.106446138965794\n ],\n [\n -117.90567382213953,\n 34.61990913772064\n ],\n [\n -114.85277111098179,\n 34.61990913772064\n ],\n [\n -114.85277111098179,\n 36.106446138965794\n ],\n [\n -117.90567382213953,\n 36.106446138965794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1: June 2016; Version 2: March 2017; Version. 3: July 2020; Version 4: June 2022","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
This 1:24,000-scale geologic map of the Silver Zone Pass quadrangle lies in the southern Toano Range in Elko County, Nevada. Metamorphic and sedimentary strata of the quadrangle range from Neoproterozoic to Permian in age. Important intrusions include the Late Jurassic (ca. 159 Ma) Silver Zone Pass pluton and Cretaceous Toano Spring pluton. In particular, the Silver Zone Pass pluton involves undeformed dikes that crosscut metamorphic foliations and the pluton is associated with pluton-margin anticlines. Interpretation of these characteristics suggests that the pluton was syn-kinematic with respect to metamorphism and strain, thus requiring a phase of Late Jurassic deformation. A Miocene rhyolite lava is of particular interest as one of the few topaz-bearing volcanic rocks in Nevada. A major detachment fault places non-metamorphosed Paleozoic rocks over low-grade Paleozoic and Proterozoic rocks. High-angle normal faults tilted the range in several blocks, and Miocene Humboldt Formation were deposited on, and faulted against, bedrock. Rocks of the Toano Range are bounded by broad valleys on the east and west, with the eastern basin being at much lower elevation than the western basin. Pleistocene lakes, which created distinctive beach deposits, occupied both basins, with Lake Bonneville on the east and Lake Waring on the west. Silver Zone Pass owes its low relief to the enhanced weathering and erosion of the rock within the pass, a granodiorite pluton. The weathering has created some unusual landforms such as tors.
As North Carolina’s only native salmonid, Brook Trout Salvelinus fontinalis is a fish of considerable ecological and cultural significance in the state, but anthropogenic alterations to the landscape and introductions of nonnative salmonids have fragmented and reduced its native range. As a result, the North Carolina Wildlife Resources Commission (NCWRC) has enacted numerous efforts to help conserve the species. Annual demographic surveys of self-sustaining Brook Trout populations have been on-going since 1978, which have also included successful efforts to document previously unidentified populations. Beginning in earnest during the 1990s, allozyme testing was used to assess patterns of hatchery introgression, with over 480 collections genotyped at the creatine kinase locus. In 2010, the NCWRC began using microsatellite markers to conduct an extensive survey of Brook Trout genetic diversity and variation. To date, 541 Brook Trout collections representing 11,090 individuals have been genotyped at 12 microsatellite loci. These data have provided insights into evolutionary relationships among populations, spatial patterns of genetic diversity, and the extent of hatchery introgression within populations. Ultimately, increased understanding of genetic diversity and relatedness have been informative for determining that Brook Trout management in North Carolina is likely best enacted at the level of individual populations. Moreover, we have used these data to actively guide stream restoration and population reintroduction activities. Over the last 15 years, NCWRC and its partners have used genetic data to prioritize habitat enhancement activities and guide 17 Brook Trout population reintroduction projects. In the future, we plan to continue expanding the microsatellite genetic baseline while also exploring the utility of phylogenomic analyses to inform Brook Trout conservation activities. Genetic and genomic approaches have great potential to improve the efficacy of conservation actions for Brook Trout in North Carolina and throughout its native range.
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