We do not know how and why belowground biodiversity may change as soils develop over centuries to millennia, hampering our ability to predict the myriad of ecosystem processes regulated by belowground organisms under changing environments. We conducted a global survey of 16 soil chronosequences spanning a wide range of ecosystem types and found that in less productive ecosystems, increases in belowground biodiversity followed increases in plant cover, but in more productive ecosystems, acidification during soil development was often associated with declines in belowground biodiversity. The biodiversity of multiple soil organisms exhibited similar patterns over time, but in contrast to expectations, changes in plant diversity were not associated with corresponding changes in belowground biodiversity.
","language":"English","publisher":" National Academy of Sciences","doi":"10.1073/pnas.1818400116","usgsCitation":"Delgado-Baquerizo, M., Bardgett, R.D., Vitousek, P.M., Maestre, F.T., Williams, M., Eldridge, D.J., Lambers, H., Neuhauser, S., Gallardo, A., Garcia-Velazquez, L., Sala, O.E., Abades, S.R., Alfaro, F.D., Berhe, A.A., Bowker, M.A., Currier, C.M., Cutler, N.A., Hart, S.C., Hayes, P.E., Hseu, Z., Kirchmair, M., Perez, C.A., Pena-Ramirez, V.M., Reed, S.C., Santos, F., Siebe, C., Sullivan, B.W., Weber-Grullon, L., and Fierer, N., 2019, Changes in belowground biodiversity during ecosystem development: Proceedings of the National Academy of Sciences of the United States of America, v. 116, no. 14, p. 6891-6896, https://doi.org/10.1073/pnas.1818400116.","productDescription":"6 p.","startPage":"6891","endPage":"6896","ipdsId":"IP-102197","costCenters":[{"id":568,"text":"Southwest Biological Science 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Addition of peat-derived humic acid extract (HA) to Sideroxydans lithotrophicus ES-1 liquid cultures led to higher cell numbers and up to 1.4 times higher Fe(II) oxidation rates compared to chemical controls. This effect was positively correlated with increasing HA concentrations. Similar Fe(III) (oxyhydr)oxide mineralogies were formed both abiotically and biotically irrespective of HA amendment, but minerals formed in the presence of ES-1 and HA were smaller. ES-1 growth with HA promoted aggregation of Fe(III) products in agarose-stabilized gradient tubes as shown by voltammetric profiling. In situ voltammetry in an acidic, iron-rich peatland revealed a gap between oxygen penetration and iron reduction that may reflect active Fe(II)-oxidizing microorganisms. The highest abundance of Fe(II) oxidizers Sideroxydans (4.9 x 107 gene copies gww-1) and Gallionella (1.5 x 107 gene copies gww-1) in the upper peat layer coincided with small-sized minerals resembling nanoparticulate ferrihydrite or goethite. Our results suggest that microbially-mediated Fe(II) oxidation dominates in the presence of DOM leading to the formation of nano-sized biogenic Fe(III) (oxyhydr)oxides that might be are readily bioavailable and likely important to iron and carbon cycling.","language":"English","publisher":"Oxford University Press","doi":"10.1093/femsec/fiz034","usgsCitation":"Hadrich, A., Taillefert, M., Akob, D., Cooper, R.E., Litzba, U., Wagner, F.E., Nietzsche, S., Ciobotta, V., Rosch, P., Popp, J., and Küsel, K., 2019, Microbial Fe(II) oxidation by Sideroxydans lithotrophicus ES-1 in the presence of Schlöppnerbrunnen fen derived humic acids: FEMS Microbiology Ecology, v. 94, no. 4, Article fiz034, https://doi.org/10.1093/femsec/fiz034.","productDescription":"Article fiz034","ipdsId":"IP-091923","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":362921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hadrich, Anke","contributorId":214793,"corporation":false,"usgs":false,"family":"Hadrich","given":"Anke","email":"","affiliations":[{"id":39115,"text":"Friedrich-Schiller-University Jena","active":true,"usgs":false}],"preferred":false,"id":760800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taillefert, Martial","contributorId":214794,"corporation":false,"usgs":false,"family":"Taillefert","given":"Martial","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":760801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akob, Denise","contributorId":214792,"corporation":false,"usgs":true,"family":"Akob","given":"Denise","affiliations":[{"id":436,"text":"National Research Program - 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2019 - Detection of Bisgaard taxon 40 in Rhinoceros Auklets (Cerorhinca monocerata) with pneumonia and septicemia from a mortality event in Washington, USA","interactions":[],"lastModifiedDate":"2019-03-15T10:50:12","indexId":"70202645","displayToPublicDate":"2019-03-15T10:50:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Detection of Bisgaard taxon 40 in Rhinoceros Auklets (Cerorhinca monocerata) with pneumonia and septicemia from a mortality event in Washington, USA","title":"Detection of Bisgaard taxon 40 in Rhinoceros Auklets (Cerorhinca monocerata) with pneumonia and septicemia from a mortality event in Washington, USA","docAbstract":"We isolated Bisgaard taxon 40 from Rhinoceros Auklets (Cerorhinca monocerata) with pneumonia and septicemia from Washington, US, found dead in 2016. Previously isolated only from the respiratory tract of a gull (Laridae), little is known about its pathogenic potential and whether it acts as a primary or opportunistic pathogen.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2017-12-309","usgsCitation":"Knowles, S., Bodenstein, B., Berlowski-Zier, B.M., Thomas, S., Pearson, S.F., and Lorch, J.M., 2019, Detection of Bisgaard taxon 40 in Rhinoceros Auklets (Cerorhinca monocerata) with pneumonia and septicemia from a mortality event in Washington, USA: Journal of Wildlife Diseases, v. 55, no. 1, p. 246-249, https://doi.org/10.7589/2017-12-309.","productDescription":"4 p.","startPage":"246","endPage":"249","ipdsId":"IP-092927","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":362093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","volume":"55","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":759340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":759341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berlowski-Zier, Brenda M. 0000-0002-7922-8352 bberlowski-zier@usgs.gov","orcid":"https://orcid.org/0000-0002-7922-8352","contributorId":4288,"corporation":false,"usgs":true,"family":"Berlowski-Zier","given":"Brenda","email":"bberlowski-zier@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":759345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, Susan M","contributorId":191668,"corporation":false,"usgs":false,"family":"Thomas","given":"Susan M","affiliations":[],"preferred":false,"id":759342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pearson, Scott F","contributorId":214201,"corporation":false,"usgs":false,"family":"Pearson","given":"Scott","email":"","middleInitial":"F","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":759343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":759344,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202626,"text":"70202626 - 2019 - Manipulating wild and tamed phytobiomes: Challenges and opportunities","interactions":[],"lastModifiedDate":"2019-06-18T10:56:13","indexId":"70202626","displayToPublicDate":"2019-03-14T16:36:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5816,"text":"Phytobiomes Journal","active":true,"publicationSubtype":{"id":10}},"title":"Manipulating wild and tamed phytobiomes: Challenges and opportunities","docAbstract":"This white paper presents a series of perspectives on current and future phytobiome management, discussed at the Wild and Tamed Phytobiomes Symposium in University Park, PA, USA, in June 2018. To enhance plant productivity and health, and to translate lab- and greenhouse-based phytobiome research to field applications, the academic community and end-users need to address a variety of scientific, practical, and social challenges. Prior discussion of phytobiomes has focused heavily on plant-associated bacterial and fungal assemblages, but the phytobiomes concept covers all factors that influence plant function. Here we discuss various management considerations, including abiotic conditions (e.g. soil, nutrient applications), microorganisms (e.g. bacterial and fungal assemblages, bacterial and fungal inoculants, viruses), macroorganisms (e.g. arthropods, plant genetics), and societal factors (e.g. communication approaches, technology diffusion). An important near-term goal for this field should be to estimate the potential relative contribution of different components of the phytobiome to plant health, as well as the potential and risk of modifying each in the near-future.
","language":"English","publisher":"The American Phytopathological Society","doi":"10.1094/PBIOMES-01-19-0006-W","usgsCitation":"Bell, T.H., Hockett, K.L., Alcala-Briseno, R.I., Barbercheck, M., Beattie, G.A., Bruns, M.A., Carlson, J.E., Chung, T., Collins, A., Emmett, B., Esker, P., Garrett, K., Glenna, L., Gugino, B.K., Jimenez-Gasco, M.D., Kinkel, L., Kovac, J., Kowalski, K., Kuldau, G., Leveau, J.H., Michalska-Smith, M.J., Myrick, J., Peter, K., Salazar, M.F., Shade, A., Stopnisek, N., Tan, X., Welty, A.T., Wickings, K., and Yergeau, E., 2019, Manipulating wild and tamed phytobiomes: Challenges and opportunities: Phytobiomes Journal, v. 3, no. 1, p. 3-21, https://doi.org/10.1094/PBIOMES-01-19-0006-W.","productDescription":"19 p.","startPage":"3","endPage":"21","ipdsId":"IP-104782","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Measurement of Pb isotopic compositions in detrital K-feldspar is among the under-utilized approaches available to ascertain sedimentary source regions. While it has been long recognized that common Pb isotope compositions recorded by K-feldspar vary widely and reflect the crustal provinces from which the host basement rocks crystallized, use of the approach has suffered due to a lack of appropriate statistical models and ground truth compositional data from source regions. In this paper, we: (1) present high-throughput LA-ICPMS analysis protocols needed to generate statistically meaningful detrital K-feldspar Pb isotope data sets; (2) develop an interpretative approach based upon 208Pb/206Pb vs. 207Pb/206Pb that incorporate information from the U- and Th-decay systems into one two-dimensional plot that is amenable to analysis using two-dimensional Kolmogorov–Smirnoff statistical tests; (3) generate new Pb isotopic data from basement rocks from southwestern North America to improve knowledge of the Pb isotopic properties of potential source regions; and (4) generate new Pb isotopic data from Lower Eocene to Lower Miocene sedimentary rocks to evaluate changes in drainage patterns that occurred in response to deformation that affected the southern California margin. Through this case study, we demonstrate how our new analytical and interpretative methods could be profitably applied to future geochemical and provenance studies and tectonically driven re-organization of drainage patterns.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.11.040","usgsCitation":"Shulaker, D.Z., Grove, M., Hourigan, J.K., Van Buer, N., Sharman, G.R., Howard, K.A., Miller, J., and Barth, A.P., 2019, Detrital K-feldspar Pb isotopic evaluation of extraregional sediment transported through an Eocene tectonic breach of southern California's Cretaceous batholith: Earth and Planetary Science Letters, v. 508, p. 4-17, https://doi.org/10.1016/j.epsl.2018.11.040.","productDescription":"14 p.","startPage":"4","endPage":"17","ipdsId":"IP-103612","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":362078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"508","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shulaker, Danielle Ziva","contributorId":214181,"corporation":false,"usgs":false,"family":"Shulaker","given":"Danielle","email":"","middleInitial":"Ziva","affiliations":[{"id":38987,"text":"Stanford U.","active":true,"usgs":false}],"preferred":false,"id":759295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grove, Marty","contributorId":211570,"corporation":false,"usgs":false,"family":"Grove","given":"Marty","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":759296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hourigan, Jeremy K.","contributorId":99023,"corporation":false,"usgs":true,"family":"Hourigan","given":"Jeremy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":759297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Buer, Nicholas","contributorId":214183,"corporation":false,"usgs":false,"family":"Van Buer","given":"Nicholas","email":"","affiliations":[{"id":38988,"text":"Cal State Poly Pomona","active":true,"usgs":false}],"preferred":false,"id":759298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sharman, Glenn R.","contributorId":196537,"corporation":false,"usgs":false,"family":"Sharman","given":"Glenn","email":"","middleInitial":"R.","affiliations":[{"id":34621,"text":"Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA","active":true,"usgs":false}],"preferred":false,"id":759299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":759294,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Jonathan","contributorId":214184,"corporation":false,"usgs":false,"family":"Miller","given":"Jonathan","affiliations":[{"id":38989,"text":"San Jose State U.","active":true,"usgs":false}],"preferred":false,"id":759300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barth, Andrew P.","contributorId":214136,"corporation":false,"usgs":false,"family":"Barth","given":"Andrew","email":"","middleInitial":"P.","affiliations":[{"id":38983,"text":"Indiana University - Purdue University","active":true,"usgs":false}],"preferred":false,"id":759301,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202630,"text":"70202630 - 2019 - Modeling elk‐to‐livestock transmission risk to predict hotspots of brucellosis spillover","interactions":[],"lastModifiedDate":"2019-06-18T10:54:15","indexId":"70202630","displayToPublicDate":"2019-03-14T16:27:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Modeling elk‐to‐livestock transmission risk to predict hotspots of brucellosis spillover","docAbstract":"Wildlife reservoirs of infectious disease are a major source of human‐wildlife conflict because of the risk of potential spillover associated with commingling of wildlife and livestock. In the Greater Yellowstone Ecosystem, the presence of brucellosis (Brucella abortus) in free‐ranging elk (Cervus canadensis) populations is of significant management concern because of the risk of disease transmission from elk to livestock. We identified how spillover risk changes through space and time by developing resource selection functions using telemetry data from 223 female elk to predict the relative probability of female elk occurrence daily during the transmission risk period. We combined these spatiotemporal predictions with elk seroprevalence, demography, and transmission timing data to identify when and where abortions (the primary transmission route of brucellosis) were most likely to occur. Additionally, we integrated our predictions of transmission risk with spatiotemporal data on areas of potential livestock use to estimate the daily risk to livestock. We predicted that approximately half of the transmission risk occurred on areas where livestock may be present (i.e., private property or grazing allotments). Of the transmission risk that occurred in livestock areas, 98% of it was on private ranchlands as opposed to state or federal grazing allotments. Disease prevalence, transmission timing, host abundance, and host distribution were all important factors in determining the potential for spillover risk. Our fine‐resolution (250‐m spatial, 1‐day temporal), large‐scale (17,732 km2) predictions of potential elk‐to‐livestock transmission risk provide wildlife and livestock managers with a useful tool to identify higher risk areas in space and time and proactively focus actions in these areas to separate elk and livestock to reduce spillover risk.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21645","usgsCitation":"Rayl, N., Proffitt, K., Almberg, E.S., Jones, J.D., Merkle, J., Gude, J., and Cross, P.C., 2019, Modeling elk‐to‐livestock transmission risk to predict hotspots of brucellosis spillover: Journal of Wildlife Management, v. 83, no. 4, p. 817-829, https://doi.org/10.1002/jwmg.21645.","productDescription":"13 p.","startPage":"817","endPage":"829","ipdsId":"IP-100336","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21645","text":"Publisher Index Page"},{"id":362077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","volume":"83","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rayl, Nathaniel D.","contributorId":199082,"corporation":false,"usgs":false,"family":"Rayl","given":"Nathaniel D.","affiliations":[],"preferred":false,"id":759303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Proffitt, Kelly 0000-0001-5528-3309","orcid":"https://orcid.org/0000-0001-5528-3309","contributorId":210093,"corporation":false,"usgs":false,"family":"Proffitt","given":"Kelly","email":"","affiliations":[{"id":38065,"text":"Montana Fish, Wildlife and Parks, Bozeman, Montana","active":true,"usgs":false}],"preferred":false,"id":759305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Almberg, Emily S.","contributorId":207014,"corporation":false,"usgs":false,"family":"Almberg","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":37431,"text":"Montana Fish, Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":759304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Jennifer D.","contributorId":145754,"corporation":false,"usgs":false,"family":"Jones","given":"Jennifer","email":"","middleInitial":"D.","affiliations":[{"id":16227,"text":"Institute on Ecosystems,Montana State University MT, 59715 USA","active":true,"usgs":false}],"preferred":false,"id":759308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Merkle, Jerod","contributorId":172972,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod","affiliations":[{"id":35288,"text":"Wyoming Cooperative Fish and Wildlife Research Unit, University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":759306,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gude, Justin A.","contributorId":210094,"corporation":false,"usgs":false,"family":"Gude","given":"Justin A.","affiliations":[{"id":38066,"text":"Montana Fish, Wildlife and Parks,","active":true,"usgs":false}],"preferred":false,"id":759307,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":759302,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202298,"text":"sir20195003 - 2019 - Climate, streamflow, and lake-level trends in the Great Lakes Basin of the United States and Canada, water years 1960–2015","interactions":[],"lastModifiedDate":"2019-03-15T16:14:59","indexId":"sir20195003","displayToPublicDate":"2019-03-14T16:15:18","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5003","displayTitle":"Climate, Streamflow, and Lake-Level Trends in the Great Lakes Basin of the United States and Canada, Water Years 1960–2015","title":"Climate, streamflow, and lake-level trends in the Great Lakes Basin of the United States and Canada, water years 1960–2015","docAbstract":"Water levels in the Great Lakes fluctuate substantially because of complex interactions among inputs (precipitation and streamflow), outputs (evaporation and outflow), and other factors. This report by the U.S. Geological Survey in cooperation with the Great Lakes Restoration Initiative was completed to describe trends in climate, streamflow, lake levels, and major water-budget components within the Great Lakes Basin for water years (WYs) 1960–2015 (study period). Resulting trends are applicable only to the study period and should not be considered indicative of longer-term trends.
Analyses of climate trends used monthly data from the Parameter-elevation Regressions on Independent Slopes Model, which are available only for the United States. Trend tests were completed for annual and seasonal time series of monthly means for total precipitation, daily minimum air temperature (Tmin), and daily maximum air temperature (Tmax). Statistical significance for all time-trend tests (climate, streamflow, and lake levels) was determined using the Mann‑Kendall test for probability values less than or equal to 0.10. Trend analyses were completed without adjustments for serial correlation; however, a modified Mann-Kendall test was subsequently used to examine potential effects of short-term persistence in time-series data. Effects of short-term persistence were considered inconsequential for climate data and minor for streamflow data; however, the presence of short-term persistence in water-budget components had more substantial effects on trend analyses.
Spatial distributions of trends in climatic data for WYs 1960–2015 for the U.S. part of the Great Lakes Basin (land only) indicate (1) generally ubiquitous upward trends in Tmin and (2) a sharp transition from neutral or downward trends in precipitation northwest of Lake Michigan to generally upward trends east of Lake Michigan. Trends in Tmax were not statistically significant. Analyses of annual climatic data aggregated for the U.S. land part of the Great Lakes Basin indicated statistically significant upward trends for precipitation and Tmin, and similar statistically significant trends existed for all the individual lake subbasins except Lake Superior.
Of 103 U.S. Geological Survey streamgages analyzed for streamflow trends, 71 had significant annual trends (54 upward and 17 downward). Downward trends in annual streamflow are concentrated northwest of Lake Michigan (16 streamgages), and upward trends are concentrated east of Lake Michigan (53 streamgages). Of the 71 streamgages with significant annual trends, 70 had at least one season with a significant trend that matched the annual trend direction.
Of 35 Environment and Climate Change Canada streamgages analyzed, 22 had significant upward trends in annual streamflow, and all but 1 of these 22 had at least one season with a significant upward trend. None of the Environment and Climate Change Canada streamgages had significant downward annual trends, and only one had a significant downward seasonal trend.
Trends in lake levels and several major water-budget components affecting lake levels were analyzed for the study period. Significant downward trends in lake level and outflow for Lake Superior are driven primarily by low lake levels and outflows during WYs 1998–2014. A significant downward trend in runoff from the contributing drainage area also is indicated, which is consistent with numerous streamgages northwest of Lake Michigan with significant downward trends in annual streamflow. A significant upward trend in annual overlake evaporation also is indicated, which is consistent with the spatially distributed upward trends in annual Tmin.
The sum of overlake precipitation and runoff from the contributing drainage area for each of the Great Lakes, less overlake evaporation, composes a variable called net basin supply (NBS). A significant downward trend in NBS is indicated for Lake Superior, which is consistent with significant trends for individual components of runoff (downward) and evaporation (upward) that contributed to a significant downward trend for lake outflow. Statistically significant upward trends in NBS for Lake Saint Clair and Lake Ontario offset the downward trend for Lake Superior and combine with nonsignificant upward trends in NBS for Lakes Michigan and Huron and Lake Erie to produce a neutral trend in NBS for the basin.
A predictable pattern in monthly mean lake levels is noted for Lake Superior, with the minimum for each year usually during or near March and the maximum commonly during or near September or October. When an October lake level is in a period of substantial decline, potential for an ensuing short-term period of below-mean lake levels is enhanced. Downstream from Lake Superior, monthly lake levels have sawtooth patterns that somewhat resemble those for Lake Superior but with decreased predictability in timing.
Similar to Lake Superior, Lakes Michigan and Huron, Lake Saint Clair, and Lake Erie all have a prolonged period of low lake levels around WYs 1998–2014; however, a significant downward trend is indicated only for Lakes Michigan and Huron. All these lakes also have a period of low lake levels before about WY 1968, when minimum lake levels were lower than during WYs 1998–2014. The significant downward trend of outflow from Lake Superior is carried downstream into Lakes Michigan and Huron; however, trends in outflow from the next three lakes downstream (Lakes Saint Clair, Erie, and Ontario) are offset by increased precipitation and runoff and are not significant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195003","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Norton, P.A., Driscoll, D.G., and Carter, J.M., 2019, Climate, streamflow, and lake-level trends in the Great Lakes Basin of the United States and Canada, water years 1960–2015: Scientific Investigations Report 2019–5003, 47 p., https://doi.org/10.3133/sir20195003.","productDescription":"Report: vi, 47 p.; Appendix Figures; Appendix Tables: 5","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-089551","costCenters":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":362031,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5003/coverthb.jpg"},{"id":362032,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5003/sir20195003.pdf","text":"Report","size":"22.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5003"},{"id":362033,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5003/sir20195003_appendix_figs_1.1_to_1.103.pdf","text":"Appendix figures 1.1–1.103","size":"940 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5003"},{"id":362034,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5003/sir20195003_appendix_figs_1.104_to_1.138.pdf","text":"Appendix figures 1.104–1.138","size":"333 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5003"},{"id":362035,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5003/sir20195003_appendix_tables_1.1_to_1.5.xlsx","text":"Appendix tables 1.1–1.5","size":"132 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019–5003"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.4716796875,\n 41.44272637767212\n ],\n [\n -75.7177734375,\n 41.44272637767212\n ],\n [\n -75.7177734375,\n 50.035973672195496\n ],\n [\n -93.4716796875,\n 50.035973672195496\n ],\n [\n -93.4716796875,\n 41.44272637767212\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
About one-quarter of the water supply for the Village of Ruidoso, New Mexico, is derived from groundwater pumping along North Fork Eagle Creek in the Eagle Creek Basin near Alto, New Mexico. Because of concerns regarding the effects of groundwater pumping on surface-water hydrology in the Eagle Creek Basin and the effects of the 2012 Little Bear Fire, which resulted in substantial losses of vegetation in the basin, the monitoring of North Fork Eagle Creek for short-term geomorphic change has been required by the U.S. Department of Agriculture Forest Service, Lincoln National Forest, as part of the permitting decision that allows for the continued pumping of the production wells. The monitoring of short-term geomorphic change in North Fork Eagle Creek began in June 2017 with a geomorphic survey of the stream reach located between the North Fork Eagle Creek near Alto, New Mexico, streamflow-gaging station (USGS site 08387550) and the Eagle Creek below South Fork near Alto, New Mexico, streamflow-gaging station (USGS site 08387600). The 2017 geomorphic survey was conducted by the U.S. Geological Survey (USGS), in cooperation with the Village of Ruidoso, and was the first in a planned series of five annual geomorphic surveys. The results of the 2017 geomorphic survey are summarized and interpreted in this report and are provided in their entirety in its companion data release.
The study reach is 1.86 miles long, and large sections of the reach are characterized by intermittent streamflow. Where water is normally present (including at the upper and lower portions of the reach near the streamflow-gaging stations), the discharge typically remains below 2 cubic feet per second throughout the year. Therefore, if geomorphic change is to occur, it will likely be driven by seasonal high-flow events. Discharge records from streamflow-gaging stations in the Eagle Creek Basin indicated that high-flow events in the basin (with peaks above 50 cubic feet per second) typically occurred during the North American monsoon months of July, August, and September. Additionally, the records appear to indicate that, as expected, overland runoff and “flashy” responses to rainfall have increased in the 5 years since the 2012 Little Bear Fire.
For the 2017 geomorphic survey of North Fork Eagle Creek, cross sections were established and surveyed at 14 locations along the study reach. Cross-section survey results indicated that channel characteristics (including channel width and area) varied widely along the study reach. Also, as part of the survey, woody debris accumulations and pools in the channel of the study reach were identified, cataloged, photographed, and surveyed for location. There were 58 woody debris accumulations and 14 pools found in the study reach. On the basis that debris jams could be a driver of geomorphic change in North Fork Eagle Creek, woody debris accumulations were classified according to their debris jam potential. The burn marks found on some woody debris indicated that the 2012 Little Bear Fire may be a contributing factor to the volume of debris in North Fork Eagle Creek. However, the woody debris present at the time of the survey did not appear to have substantially affected the geomorphic state of the study reach. Further, the structure and composition of the woody debris accumulations indicated that, under high-flow conditions, most woody debris would likely be transported downstream and out of the study reach without causing substantial geomorphic change through further jamming.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181187","collaboration":"Prepared in cooperation with the Village of Ruidoso, New Mexico","usgsCitation":"Graziano, A.P., 2019, Geomorphic survey of North Fork Eagle Creek, New Mexico, 2017: U.S. Geological Survey Open-File Report 2018–1187, 28 p., https://doi.org/10.3133/ofr20181187.","productDescription":"Report: v., 28 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","ipdsId":"IP-093851","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":362041,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PR7TX3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data supporting the 2017 geomorphic survey of North Fork Eagle Creek, New Mexico"},{"id":362039,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1187/coverthb.jpg"},{"id":362040,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1187/ofr20181187.pdf","text":"Report","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1187"}],"country":"United States","state":"New Mexico","otherGeospatial":"North Fork Eagle Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.98236083984375,\n 33.02939031998959\n ],\n [\n -104.98260498046875,\n 33.02939031998959\n ],\n [\n -104.98260498046875,\n 33.68549637289138\n ],\n [\n -105.98236083984375,\n 33.68549637289138\n ],\n [\n -105.98236083984375,\n 33.02939031998959\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd NE
Albuquerque, NM 87113
The three-part method for quantitative mineral resource assessment is used by the U.S. Geological Survey to predict, within a specified assessment area, the number of undiscovered mineral deposits and the quantity of mineral resources in those undiscovered deposits. The effects of size-biased sampling on such predictions are evaluated in a case study that involves gold mines from the Timmins-Kirkland Lake area of the Abitibi greenstone belt, Canada. The gold mines are divided, based upon the time of the assessment, into two groups: existing mines and future mines. The total produced gold for the existing mines are used to predict, with the three-part method, the total produced gold for the future mines. Then the predictions are compared to the known, total produced gold for the future mines. For comparisons using the mean, the predictions are 1.6 to 12 times too high, depending upon the time of the assessment and the probability density function characterizing the total produced gold in the existing mines. For comparisons using the median, the predictions are 1.3 to 10 times too high, depending upon the time of the assessment. The reason for these excessively high predictions is that the three-part method is based on the assumption that the total produced gold from the existing mines is representative of the total produced gold in the future mines; this assumption is inappropriate because of size-biased sampling. There is reason to be concerned that size-biased sampling adversely affected the resource predictions of previous U.S. Geological Survey assessments that were conducted with the three-part method.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185149","usgsCitation":"Ellefsen, K.J., 2019, Effect of size-biased sampling on resource predictions from the three-part method for quantita-tive mineral resource assessment—A case study of the gold mines in the Timmins-Kirkland Lake area of the Abitibi greenstone belt, Canada: U.S. Geological Scientific Investigations Report 2018–5149, 15 p., https://doi.org/10.3133/sir20185149.","productDescription":"Report: v, 15 p.; Companion File","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-096776","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":362017,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5149/sir20185149.pdf","text":"Report ","size":"872 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5149"},{"id":362019,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm7C15","text":"Techniques and Methods 7-C15: ","linkHelpText":"Probability calculations for three-part mineral resource assessments"},{"id":362016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5149/coverthb.jpg"},{"id":362018,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2018/5149/sir20185149_reportscripts.zip","text":"Scripts","size":"1.31 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2018–5149 Scripts"},{"id":362020,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm7C14","text":"Techniques and Methods 7-C14: ","linkHelpText":"User’s guide for MapMark4—An R package for the probability calculations in three-part mineral resource assessments"}],"country":"Canada","otherGeospatial":"Ontario Province, Quebec Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.50732421875,\n 47.487513008956554\n ],\n [\n -78.06884765624999,\n 47.487513008956554\n ],\n [\n -78.06884765624999,\n 49.681846899401286\n ],\n [\n -82.50732421875,\n 49.681846899401286\n ],\n [\n -82.50732421875,\n 47.487513008956554\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 964
Denver, CO 80225
Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Geochemical compositions of fine-grained stream sediment from four drainages on the north shore of the island of Kauai, Hawaii, west of Hanalei and two back-beach sites were explored to increase understanding about land-based runoff and ecological risk from runoff to nearshore coral communities. Stream and beach sediment were collected between July 30 and August 2, 2016, and major, minor, and trace elements in the less than 63 micrometer-diameter fraction were analyzed by inductively coupled plasma optical emission spectroscopy and mass spectroscopy. The potentially toxic metals Cr, Cu, Ni, and Zn exceeded levels at which adverse biological effects could be observed; however, these metals seemed to be largely mineral-bound and thus were unlikely to harm organisms. Cd and Pb were below levels of ecological concern. Only a small amount of fine-grained sediment was retained on beaches west of Hanalei sampled in summer 2016 (mean=8.8 percent, median=0.4 percent, range=0–92.8 percent, n=41). Although the scarcity of fine-grained sediment precluded land-based runoff sourcing to the nearshore region, it did indicate that fine-grained sediment and associated contaminants did not accumulate over the long term in the sampled intertidal, subtidal, and reef-flat environments, which would reduce sediment-related pressures on coral communities there.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191007","usgsCitation":"Takesue, R.K., and Storlazzi, C.D., 2018, Stream sediment geochemistry of four small drainages on the north shore of Kauai west of Hanalei: U.S. Geological Survey Open-File Report 2019–1007, 11 p., https://doi.org/10.3133/ofr20191007.","productDescription":"iv, 11 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-101369","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":362068,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1007/ofr20191007.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1007"},{"id":362067,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1007/coverthb.jpg"}],"country":"United States","state":"Hawaii","city":"Hanalei","otherGeospatial":"Kauai","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.6086883544922,\n 22.19233236966165\n ],\n [\n -159.49607849121094,\n 22.19233236966165\n ],\n [\n -159.49607849121094,\n 22.226978081564294\n ],\n [\n -159.6086883544922,\n 22.226978081564294\n ],\n [\n -159.6086883544922,\n 22.19233236966165\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Marbled murrelets (Brachyramphus marmoratus) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet Federal- and State-mandated recovery efforts for this species. During June–August 2018, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1999–2018), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). Using conventional distance sampling methods, we estimated marbled murrelet abundance using 137 detections of 227 individuals observed on 9 surveys. The abundance estimated for the entire study area using all surveys in 2018 was 370 birds (95-percent confidence interval, 250–546 birds). Estimated abundance from 2018 is comparable to most prior years of study, except for 2001–03, when greater abundances were estimated. In 2018, we estimated reproductive productivity (calculated as the hatch-year [HY] to after-hatch-year [AHY] ratio) using four detections of four HY individuals observed on six surveys. After date-correcting HY and AHY counts to account for birds expected to be absent from the water while inland at nests, the date-corrected juvenile ratio was 0.047 ± 0.024 standard error. We updated a synthesized database of all Zone 6 marbled murrelet survey data since 1999 with 2018 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1107","usgsCitation":"Felis, J.J., Kelsey, E.C., and Adams, J., 2019, Abundance and productivity of marbled murrelets (Brachyramphus marmoratus) off central California during the 2018 breeding season: U.S. Geological Survey Data Series 1107, 10 p., https://doi.org/10.3133/ds1107.","productDescription":"Report: v, 10 p.; Data release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-103980","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":362066,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B01RW","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2018 (ver. 2.0, March 2019)"},{"id":362050,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1107/coverthb.jpg"},{"id":362051,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1107/ds1107.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1107"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.52090454101564,\n 36.923547681089296\n ],\n [\n -122.02102661132814,\n 36.923547681089296\n ],\n [\n -122.02102661132814,\n 37.52279705525959\n ],\n [\n -122.52090454101564,\n 37.52279705525959\n ],\n [\n -122.52090454101564,\n 36.923547681089296\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) in cooperation with the U.S. Army Corps of Engineers along Bull Creek, Haskell Creek, and the Los Angeles River (Sepulveda Dam project area) in Los Angeles County, California, in 2018. Four vireo surveys were conducted between April 27 and July 18, 2018, and three flycatcher surveys were conducted between May 24 and July 18, 2018. We found 14 territorial male vireos, 7 of which were confirmed as paired. Sixty-four percent of vireos were detected along the Los Angeles River, 21 percent along Haskell Creek, and 14 percent along Bull Creek. Eighty-six percent of vireos were detected in habitat characterized as mixed willow, and all vireos were detected in habitat with greater than 50 percent native plant cover. No flycatchers were observed in the survey area in 2018.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1105","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Pottinger, R.E., and Kus, B.E., 2019, Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Sepulveda Dam Basin, Los Angeles County, California—2018 data summary: U.S. Geological Survey Data Series 1105, 10 p., https://doi.org/10.3133/ds1105. ","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-103359","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":362053,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1105/coverthb.jpg"},{"id":362054,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1105/ds1105.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1105"}],"country":"United States","state":"California","county":"Los Angles County","otherGeospatial":"Sepulveda Dam Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.49387884140015,\n 34.16423284168825\n ],\n [\n -118.47091913223267,\n 34.16423284168825\n ],\n [\n -118.47091913223267,\n 34.1809029051214\n ],\n [\n -118.49387884140015,\n 34.1809029051214\n ],\n [\n -118.49387884140015,\n 34.16423284168825\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Consistency in stratigraphic nomenclature enables communication among scientists both regionally and globally, thus requiring the North American Stratigraphic Code, as presented by the North American Commission on Stratigraphic Nomenclature, to follow international convention. The ratification of three subseries of the Holocene by the InternationalUnion of Geological Sciences (IUGS) in June 2018 warrants the integration of subseries among formal chronostratigraphic ranks in the Code. The purpose ofmaking subseries a formal rank is that it aligns the Code with the International StratigraphicGuide, and establishes the option of using the prefixes super- and sub- for other chronostratigraphic and geochronologic ranks. This is in accordance with the guiding principle of the Code to make it as consistent as possible with international usage and to foster innovations to meet the expanding and changing needs of earth scientists.
","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Aubry, M., Fluegeman, R.H., Edwards, L.E., Pratt, B.R., and Brett, C.E., 2019, North American Commission on Stratigraphic Nomenclature Note 69 – Application for addition of subseries/subepoch to the North American Stratigraphic Code: Stratigraphy, v. 15, no. 4, p. 261-263.","productDescription":"3 p.","startPage":"261","endPage":"263","ipdsId":"IP-104235","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":362045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":362023,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/stratigraphy/issue-345/article-2113"}],"volume":"15","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aubry, Marie-Pierre","contributorId":174332,"corporation":false,"usgs":false,"family":"Aubry","given":"Marie-Pierre","email":"","affiliations":[{"id":27421,"text":"Department of Earth and Planetary Sciences Rutgers University 610 Taylor Road Piscataway NJ 08854-8066, USA","active":true,"usgs":false}],"preferred":false,"id":759216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fluegeman, Richard H.","contributorId":139942,"corporation":false,"usgs":false,"family":"Fluegeman","given":"Richard","email":"","middleInitial":"H.","affiliations":[{"id":13322,"text":"Ball State University","active":true,"usgs":false}],"preferred":false,"id":759217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":759215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Brian R.","contributorId":214140,"corporation":false,"usgs":false,"family":"Pratt","given":"Brian","email":"","middleInitial":"R.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":759218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brett, Carlton E.","contributorId":214141,"corporation":false,"usgs":false,"family":"Brett","given":"Carlton","email":"","middleInitial":"E.","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":759219,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202590,"text":"70202590 - 2019 - Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA","interactions":[],"lastModifiedDate":"2019-03-13T15:20:06","indexId":"70202590","displayToPublicDate":"2019-03-13T15:20:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA","docAbstract":"The enrichment factor (EF) is a widely used metric for determining how much the presence of an element in a sampling media has increased relative to average natural abundance because of human activity. Calculation of an EF requires the selection of both a background composition and a reference element, choices that can strongly influence the result of the calculation. Here, it is shown how carefully applied, classical principal component analysis (PCA) examined via biplots can guide the selections of background compositions and reference elements. Elemental data were treated using the centered log ratio (CLR) transformation, and multiple subsets of major and trace elements were examined to gain different perspectives. The methodology was applied to a dataset of elemental soil concentrations from around breccia pipe uranium mines in Arizona, U.S.A., with most samples collected via incremental sampling methodology. Storage of ore at the surface creates the potential for wind dispersal of ore-derived material. Uranium was found to be the best individual tracer of dispersal of ore-derived material to nearby soils, with EF values up to 75. Sulfur, As, Mo, and Cu were also enriched but to lesser degrees. The results demonstrate several practical benefits of a PCA in these situations: (1) the ability to identify one or more elements best suited to distinguish a specific source of enrichment from background composition; (2) understanding how background compositions vary within and between sites; (3) identification of samples containing enriched or anthropogenic materials based upon their integrated, multi-element composition. Calculating the most representative EF values is useful for numerical assessment of enrichment, whether anthropogenic or natural. As shown here, however, the PCA and biplot method provide a visual approach that integrates information from all elements for a given subset of data in a manner that yields geochemical insights beyond the power of the EF.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2019.01.122","usgsCitation":"Bern, C.R., Walton-Day, K., and Naftz, D.L., 2019, Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA: Environmental Pollution, v. 248, p. 90-100, https://doi.org/10.1016/j.envpol.2019.01.122.","productDescription":"11 p.","startPage":"90","endPage":"100","ipdsId":"IP-102119","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":467818,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2019.01.122","text":"Publisher Index Page"},{"id":437543,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KTLXL8","text":"USGS data release","linkHelpText":"Surface Materials Data from Breccia-Pipe Uranium Mine and Reference Sites, Arizona, USA"},{"id":362042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.04907226562499,\n 35.5\n ],\n [\n -111,\n 35.5\n ],\n [\n -111,\n 37\n ],\n [\n -114.04907226562499,\n 37\n ],\n [\n -114.04907226562499,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"248","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759222,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202253,"text":"ofr20191014 - 2019 - Assessment of skin and liver neoplasms in white sucker (Catostomus commersonii) collected in the Sheboygan River Area of Concern, Wisconsin, in 2017","interactions":[],"lastModifiedDate":"2024-03-04T19:11:14.877436","indexId":"ofr20191014","displayToPublicDate":"2019-03-13T14:00:00","publicationYear":"2019","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":"2019-1014","displayTitle":"Assessment of Skin and Liver Neoplasms in White Sucker (Catostomus commersonii) Collected at the Sheboygan River Area of Concern, Wisconsin, in 2017","title":"Assessment of skin and liver neoplasms in white sucker (Catostomus commersonii) collected in the Sheboygan River Area of Concern, Wisconsin, in 2017","docAbstract":"Two hundred adult white sucker (Catostomus commersonii), age 3 years and older, were collected from the lower Sheboygan River Area of Concern in 2017, during the spring spawning run. Fish were euthanized, weighed, and measured, and any visible abnormalities were documented. Pieces of raised skin lesions as well as five to eight pieces of liver were removed and preserved for histopathological analyses. Skin and liver neoplasm prevalence was determined for assessment of the Fish Tumors or Other Deformities Beneficial Use Impairment. Although 45.5 percent of the suckers had raised skin lesions, the prevalence of skin neoplasms, either papilloma or squamous cell carcinoma, was 29.5 percent. This observation was similar to the prevalence (32.6 percent) of skin neoplasms in 2012; however, the percentage of squamous cell carcinoma was higher in 2017 (9.5 percent) than in 2012 (2.1 percent). The prevalence of liver neoplasms in 2017 (8.5 percent) was similar to that in 2012 (8.3 percent).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191014","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Blazer, V.S., Walsh, H.L., Braham, R.P., and Mazik, P.M., 2019, Assessment of skin and liver neoplasms in white sucker (Catostomus commersonii) collected in the Sheboygan River Area of Concern, Wisconsin, in 2017: U.S. Geological Survey Open-File Report 2019–1014, 18 p., https://doi.org/10.3133/ofr20191014.","productDescription":"vi, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103639","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":361922,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1014/ofr20191014.pdf","text":"Report","size":"4.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1014"},{"id":361921,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1014/coverthb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lower Sheboygan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.82230377197266,\n 43.71801614233635\n ],\n [\n -87.69132614135742,\n 43.71801614233635\n ],\n [\n -87.69132614135742,\n 43.7596885685863\n ],\n [\n -87.82230377197266,\n 43.7596885685863\n ],\n [\n -87.82230377197266,\n 43.71801614233635\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The putative respiratory selenite [Se(IV)] reductase (Srr) from Bacillus selenitireducens MLS10 has been identified through a polyphasic approach involving genomics, proteomics, and enzymology. Nondenaturing gel assays were used to identify Srr in cell fractions, and the active band was shown to contain a single protein of 80 kDa. The protein was identified through liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a homolog of the catalytic subunit of polysulfide reductase (PsrA). It was found to be encoded as part of an operon that contains six genes that we designated srrE, srrA, srrB, srrC, srrD, and srrF. SrrA is the catalytic subunit (80 kDa), with a twin-arginine translocation (TAT) leader sequence indicative of a periplasmic protein and one putative 4Fe-4S binding site. SrrB is a small subunit (17 kDa) with four putative 4Fe-4S binding sites, SrrC (43 kDa) is an anchoring subunit, and SrrD (24 kDa) is a chaperon protein. Both SrrE (38 kDa) and SrrF (45 kDa) were annotated as rhodanese domain-containing proteins. Phylogenetic analysis revealed that SrrA belonged to the PsrA/PhsA clade but that it did not define a distinct subgroup, based on the putative homologs that were subsequently identified from other known selenite-respiring bacteria (e.g., Desulfurispirillum indicum and Pyrobaculum aerophilum). The enzyme appeared to be specific for Se(IV), showing no activity with selenate, arsenate, or thiosulfate, with a Km of 145 ± 53 μM, a Vmax of 23 ± 2.5 μM min−1, and a kcat of 23 ± 2.68 s−1. These results further our understanding of the mechanisms of selenium biotransformation and its biogeochemical cycle.
","language":"English","publisher":"American Chemical Society","doi":"10.1128/JB.00614-18","usgsCitation":"Wells, M.L., McGarry, J., Gaye, M.M., Basu, P., Oremland, R.S., and Stolz, J.F., 2019, Respiratory selenite reductase from Bacillus selenitireducens strain MLS10: Journal of Bacteriology, v. 201, no. 7, e00614-18, 13 p., https://doi.org/10.1128/JB.00614-18.","productDescription":"e00614-18, 13 p.","ipdsId":"IP-102359","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467819,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/jb.00614-18","text":"External Repository"},{"id":379726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"201","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Michael L.","contributorId":194318,"corporation":false,"usgs":false,"family":"Wells","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":802929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGarry, Jennifer","contributorId":243983,"corporation":false,"usgs":false,"family":"McGarry","given":"Jennifer","email":"","affiliations":[{"id":48783,"text":"Purdue","active":true,"usgs":false}],"preferred":false,"id":802930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaye, Maissa M","contributorId":243984,"corporation":false,"usgs":false,"family":"Gaye","given":"Maissa","email":"","middleInitial":"M","affiliations":[{"id":48783,"text":"Purdue","active":true,"usgs":false}],"preferred":false,"id":802931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Basu, Partha","contributorId":189834,"corporation":false,"usgs":false,"family":"Basu","given":"Partha","email":"","affiliations":[],"preferred":false,"id":802932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"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":802933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stolz, John F.","contributorId":179305,"corporation":false,"usgs":false,"family":"Stolz","given":"John","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":802934,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203101,"text":"70203101 - 2019 - Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland","interactions":[],"lastModifiedDate":"2019-04-22T11:18:36","indexId":"70203101","displayToPublicDate":"2019-03-13T11:18:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland","docAbstract":"With warmer springs, herbivores migrating to Arctic breeding grounds may experience phenological mismatches between their energy demands and the availability of high quality forage. However, the timing of high quality forage relative to the timing of grazing is often unknown. In coastal western Alaska, approximately one million migratory geese arrive each spring to breed where foliar %N and C:N ratios are linked to gosling survival and population growth. We conducted a three-year experiment where we manipulated the start of the growing season using warming chambers and grazing times using captive Pacific black brant (Branta bernicla nigricans) to examine how the timing of these events influences the quality of an important forage species. Our results suggest that grazing timing plays a much greater role than an advanced growing season in determining forage quality. Both top models included grazing timing, and suggested that compared to typical grazing timing, early grazing significantly reduced foliar %C by 6% and C:N ratios by 16%, while late goose grazing significantly reduced foliar %N by 15% and increased foliar C:N ratios by 21%. While the second-ranking top model included the effect of season, the advanced growing season only reduced %N by 4%, increased %C by <1%, and increased C:N ratios by 5% compared to an ambient growing season. In summary, in years where geese arrive early, they will consume higher quality forage when they arrive and throughout the season, while in years that geese arrive late they will consume lower quality forage when they arrive and for the remainder of the season. When the growing season starts has only a minor influence on this pattern. Our findings suggest that cues determining migration and arrival times to breeding areas are important factors influencing forage quality for geese in western Alaska.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0213037","usgsCitation":"Beard, K.H., Choi, R.T., Leffer, A.J., Carlson, L., Kelsey, K.C., Schmutz, J.A., and Welker, J., 2019, Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland: PLoS ONE, v. 14, no. 3, 21 p., https://doi.org/10.1371/journal.pone.0213037.","productDescription":"21 p.","ipdsId":"IP-103582","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467820,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0213037","text":"Publisher Index Page"},{"id":363103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.4705810546875,\n 60.66510605284197\n ],\n [\n -165.25634765625,\n 59.78128682109904\n ],\n [\n -162.916259765625,\n 59.678835236960765\n ],\n [\n -162.916259765625,\n 61.65598732543086\n ],\n [\n -166.34948730468747,\n 61.65598732543086\n ],\n [\n -165.4705810546875,\n 60.66510605284197\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Beard, Karen H.","contributorId":205934,"corporation":false,"usgs":false,"family":"Beard","given":"Karen","email":"","middleInitial":"H.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":761171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choi, Ryan T.","contributorId":205936,"corporation":false,"usgs":false,"family":"Choi","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":761172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leffer, A. Joshua","contributorId":214925,"corporation":false,"usgs":false,"family":"Leffer","given":"A.","email":"","middleInitial":"Joshua","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":761174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Lindsay","contributorId":214924,"corporation":false,"usgs":false,"family":"Carlson","given":"Lindsay","email":"","affiliations":[{"id":39139,"text":"Utah State University and the Ecology Center","active":true,"usgs":false}],"preferred":false,"id":761173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelsey, Katharine C.","contributorId":195397,"corporation":false,"usgs":false,"family":"Kelsey","given":"Katharine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":761175,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":761170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Welker, Jeffrey","contributorId":214926,"corporation":false,"usgs":false,"family":"Welker","given":"Jeffrey","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":761176,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228343,"text":"70228343 - 2019 - Antipredator response diminishes during periods of resource deficit for a large herbivore","interactions":[],"lastModifiedDate":"2022-02-09T17:21:24.143256","indexId":"70228343","displayToPublicDate":"2019-03-13T11:12:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Antipredator response diminishes during periods of resource deficit for a large herbivore","docAbstract":"The starvation-predation hypothesis predicts that, during resource shortages, prey forego antipredator behavior and forage as much as possible to avoid starvation, even when risk of predation is high. We tested this hypothesis using GPS locations collected simultaneously from moose (Alces alces) and wolves (Canis lupus) in the Greater Yellowstone Ecosystem of North America. We assessed shifts in the speed, displacement, and habitat selection of moose 24 hours following encounter with wolves (0–1500 m distance). We examined whether the strength of antipredator behaviors would weaken as winter progressed and the nutritional condition of moose declined. Moose responded to wolf encounters by increasing their rate of movement in early winter, but only within 500 m distance. Importantly, these responses attenuated as winter progressed. Moose did not avoid their preferred foraging habitat (riparian areas) following encounters with wolves at any distance, and instead they more strongly selected riparian areas, especially in early winter. Our findings support theoretical predictions that resource deficits should dampen prey antipredator behavior, and suggest that nutritional condition of prey may buffer against run-away risk effects in food webs involving large mammalian predators and prey.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2618","usgsCitation":"Oates, B.A., Merkle, J., Kauffman, M., Dewey, S., Jimenez, M., Vartanian, J., Becker, S., and Goheen, J., 2019, Antipredator response diminishes during periods of resource deficit for a large herbivore: Ecology, v. 100, no. 4, e02618, 8 p., https://doi.org/10.1002/ecy.2618.","productDescription":"e02618, 8 p.","ipdsId":"IP-098231","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest, Grand Teton National Park,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.9674072265625,\n 42.85985981506279\n ],\n [\n -110.2972412109375,\n 42.85985981506279\n ],\n [\n -110.2972412109375,\n 43.95328204198018\n ],\n [\n -110.9674072265625,\n 43.95328204198018\n ],\n [\n -110.9674072265625,\n 42.85985981506279\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Oates, Brendan A.","contributorId":275241,"corporation":false,"usgs":false,"family":"Oates","given":"Brendan","email":"","middleInitial":"A.","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":833868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, J.A.","contributorId":275242,"corporation":false,"usgs":false,"family":"Merkle","given":"J.A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dewey, S.R.","contributorId":275243,"corporation":false,"usgs":false,"family":"Dewey","given":"S.R.","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":833871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jimenez, M.D.","contributorId":275244,"corporation":false,"usgs":false,"family":"Jimenez","given":"M.D.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vartanian, J.M.","contributorId":275245,"corporation":false,"usgs":false,"family":"Vartanian","given":"J.M.","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Becker, S.A.","contributorId":275246,"corporation":false,"usgs":false,"family":"Becker","given":"S.A.","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833874,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goheen, J.R.","contributorId":275247,"corporation":false,"usgs":false,"family":"Goheen","given":"J.R.","email":"","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833875,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227949,"text":"70227949 - 2019 - Winter precipitation and summer temperature predict lake water quality at macroscales","interactions":[],"lastModifiedDate":"2022-02-02T16:04:07.07506","indexId":"70227949","displayToPublicDate":"2019-03-13T09:52:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Winter precipitation and summer temperature predict lake water quality at macroscales","docAbstract":"Climate change can have strong effects on aquatic ecosystems, including disrupting nutrient cycling and mediating processes that affect primary production. Past studies have been conducted mostly on individual or small groups of ecosystems, making it challenging to predict how future climate change will affect water quality at broad scales. We used a subcontinental-scale database to address three objectives: (1) identify which climate metrics best predict lake water quality, (2) examine whether climate influences different nutrient and productivity measures similarly, and (3) quantify the potential effects of a changing climate on lakes. We used climate data to predict lake water quality in ~11,000 north temperate lakes across 17 U.S. states. We developed a novel machine learning method that jointly models different measures of water quality using 48 climate metrics and accounts for properties inherent in macroscale data (e.g., spatial autocorrelation). Our results suggest that climate metrics related to winter precipitation and summer temperature were strong predictors of lake nutrients and productivity. However, we found variation in the magnitude and direction of the relationship between climate and water quality. We predict that a likely future climate change scenario of warmer summer temperatures will lead to increased nutrient concentrations and algal biomass across lakes (median ~3%–9% increase), whereas increased winter precipitation will have highly variable effects. Our results emphasize the importance of heterogeneity in the response of individual ecosystems to climate and are a caution to extrapolating relationships across space.
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