This special issue of Applied Geochemistry honors Dr. D. Kirk Nordstrom, and his influential career spent primarily at the U.S. Geological Survey (USGS). This issue does not herald his retirement or other significant career milestone, but serves as a recognition of the impact his work has had on the field of geochemistry in general. This special issue grew from a symposium in Kirk’s honor (affectionately dubbed “Kirkfest”) at the Geological Society of America’s annual meeting in Denver, Colorado, USA, during October 2013. At GSA, 27 talks and 35 posters showed how Kirk’s work has influenced a wide range of current hydrogeochemical research, from geothermal processes to acid mine drainage to geochemical modeling. The breadth of his knowledge and his many contributions to the published literature have left an indelible mark on the field of geochemistry, and this special issue is a tribute to his experience and contributions.
","language":"English","publisher":"International Association of Geochemistry and Cosmochemistry","publisherLocation":"Oxford","doi":"10.1016/j.apgeochem.2015.04.012","usgsCitation":"Campbell, K.M., Verplanck, P.L., McCleskey, R.B., and Alpers, C.N., 2015, From extreme pH to extreme temperature: An issue in honor of the geochemical contributions of Kirk Nordstrom, USGS hydrogeochemist: Applied Geochemistry, v. 62, p. 1-2, https://doi.org/10.1016/j.apgeochem.2015.04.012.","productDescription":"2 p.","startPage":"1","endPage":"2","ipdsId":"IP-064998","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":330924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58259561e4b01fad86db2415","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":653463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":653464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653465,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159472,"text":"70159472 - 2015 - A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals","interactions":[],"lastModifiedDate":"2015-11-03T11:56:12","indexId":"70159472","displayToPublicDate":"2015-11-03T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals","docAbstract":"While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES15-00180.1","usgsCitation":"Clement, M., O’Keefe, J.M., and Walters, B., 2015, A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals: Ecosphere, v. 6, no. 10, art184; 13 p., https://doi.org/10.1890/ES15-00180.1.","productDescription":"art184; 13 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059014","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es15-00180.1","text":"Publisher Index Page"},{"id":310986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"10","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-22","publicationStatus":"PW","scienceBaseUri":"5639dafde4b0d6133fe732ca","contributors":{"authors":[{"text":"Clement, Matthew mclement@usgs.gov","contributorId":138815,"corporation":false,"usgs":true,"family":"Clement","given":"Matthew","email":"mclement@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Keefe, Joy M","contributorId":149672,"corporation":false,"usgs":false,"family":"O’Keefe","given":"Joy","email":"","middleInitial":"M","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":579115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walters, Brianne","contributorId":149673,"corporation":false,"usgs":false,"family":"Walters","given":"Brianne","email":"","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":579116,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159444,"text":"70159444 - 2015 - Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system","interactions":[],"lastModifiedDate":"2015-12-21T13:37:10","indexId":"70159444","displayToPublicDate":"2015-11-03T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system","docAbstract":"Lake sturgeon (Acipenser fulvescens) populations have suffered precipitous declines in the St. Clair–Detroit River system, following the removal of gravel spawning substrates and overfishing in the late 1800s to mid-1900s. To assist the remediation of lake sturgeon spawning habitat, three hydrodynamic models were integrated into a spatial model to identify areas in two large rivers, where water velocities were appropriate for the restoration of lake sturgeon spawning habitat. Here we use water velocity data collected with an acoustic Doppler current profiler (ADCP) to assess the ability of the spatial model and its sub-models to correctly identify areas where water velocities were deemed suitable for restoration of fish spawning habitat. ArcMap 10.1 was used to create raster grids of water velocity data from model estimates and ADCP measurements which were compared to determine the percentage of cells similarly classified as unsuitable, suitable, or ideal for fish spawning habitat remediation. The spatial model categorized 65% of the raster cells the same as depth-averaged water velocity measurements from the ADCP and 72% of the raster cells the same as surface water velocity measurements from the ADCP. Sub-models focused on depth-averaged velocities categorized the greatest percentage of cells similar to ADCP measurements where 74% and 76% of cells were the same as depth-averaged water velocity measurements. Our results indicate that integrating depth-averaged and surface water velocity hydrodynamic models may have biased the spatial model and overestimated suitable spawning habitat. A model solely integrating depth-averaged velocity models could improve identification of areas suitable for restoration of fish spawning habitat.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.jglr.2015.09.019","usgsCitation":"Fischer, J.L., Bennion, D., Roseman, E., and Manny, B.A., 2015, Validation of a spatial model used to locate fish spawning reef construction sites in the St. Clair–Detroit River system: Journal of Great Lakes Research, v. 41, no. 4, p. 1178-1184, https://doi.org/10.1016/j.jglr.2015.09.019.","productDescription":"7 p.","startPage":"1178","endPage":"1184","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064602","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":310982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Detroit River, Lake St. Clair","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.496337890625,\n 42.81555136172695\n ],\n [\n -82.55126953124999,\n 42.62991729384455\n ],\n [\n -82.6611328125,\n 42.70867781741311\n ],\n [\n -82.8424072265625,\n 42.65820178455667\n ],\n [\n -82.91107177734375,\n 42.48425110546248\n ],\n [\n -82.9742431640625,\n 42.36057345238458\n ],\n [\n -83.14453125,\n 42.285437007491545\n ],\n [\n -83.21868896484375,\n 42.114523952464246\n ],\n [\n -83.2159423828125,\n 42.01869237684385\n ],\n [\n -83.08959960937499,\n 42.05948945192712\n ],\n [\n -83.067626953125,\n 42.28340504748079\n ],\n [\n -82.93853759765625,\n 42.33215399891373\n ],\n [\n -82.74627685546874,\n 42.28340504748079\n ],\n [\n -82.452392578125,\n 42.3037216984154\n ],\n [\n -82.39471435546875,\n 42.36869093640926\n ],\n [\n -82.3919677734375,\n 42.49640294093708\n ],\n [\n -82.49908447265625,\n 42.5995982130586\n ],\n [\n -82.44964599609374,\n 42.817566071581616\n ],\n [\n -82.496337890625,\n 42.81555136172695\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5639db04e4b0d6133fe732d4","contributors":{"authors":[{"text":"Fischer, Jason L. 0000-0001-7226-6500 jfischer@usgs.gov","orcid":"https://orcid.org/0000-0001-7226-6500","contributorId":149532,"corporation":false,"usgs":true,"family":"Fischer","given":"Jason","email":"jfischer@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":578711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennion, David 0000-0003-4927-4195 dbennion@usgs.gov","orcid":"https://orcid.org/0000-0003-4927-4195","contributorId":149533,"corporation":false,"usgs":true,"family":"Bennion","given":"David","email":"dbennion@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":578712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. eroseman@usgs.gov","contributorId":138592,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":578713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manny, Bruce A. 0000-0002-4074-9329 bmanny@usgs.gov","orcid":"https://orcid.org/0000-0002-4074-9329","contributorId":3699,"corporation":false,"usgs":true,"family":"Manny","given":"Bruce","email":"bmanny@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":578714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159459,"text":"70159459 - 2015 - Spatially explicit spectral analysis of point clouds and geospatial data","interactions":[],"lastModifiedDate":"2015-11-02T12:42:30","indexId":"70159459","displayToPublicDate":"2015-11-02T01:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit spectral analysis of point clouds and geospatial data","docAbstract":"The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.
","language":"English","publisher":"Elsevier","publisherLocation":"Oxford, UK","doi":"10.1016/j.cageo.2015.10.004","usgsCitation":"Buscombe, D.D., 2015, Spatially explicit spectral analysis of point clouds and geospatial data: Computers & Geosciences, v. 86, p. 92-108, https://doi.org/10.1016/j.cageo.2015.10.004.","productDescription":"17 p.","startPage":"92","endPage":"108","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065612","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471667,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/wr2pf/","text":"External Repository"},{"id":310911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56388939e4b0d6133fe72f89","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":578929,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70158960,"text":"sir20155146 - 2015 - Climate and streamflow characteristics for selected streamgages in eastern South Dakota, water years 1945–2013","interactions":[],"lastModifiedDate":"2017-10-12T20:01:45","indexId":"sir20155146","displayToPublicDate":"2015-11-02T01:00:00","publicationYear":"2015","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":"2015-5146","title":"Climate and streamflow characteristics for selected streamgages in eastern South Dakota, water years 1945–2013","docAbstract":"Upward trends in precipitation and streamflow have been observed in the northeastern Missouri River Basin during the past century, including the area of eastern South Dakota. Some of the identified upward trends were anomalously large relative to surrounding parts of the northern Great Plains. Forcing factors for streamflow trends in eastern South Dakota are not well understood, and it is not known whether streamflow trends are driven primarily by climatic changes or various land-use changes. Understanding the effects that climate (specifically precipitation and temperature) has on streamflow characteristics within a region will help to better understand additional factors such as land-use alterations that may affect the hydrology of the region. To aid in this understanding, a study was completed by the U.S. Geological Survey, in cooperation with the East Dakota Water Development District and James River Water Development District, to assess trends in climate and streamflow characteristics at 10 selected streamgages in eastern South Dakota for water years (WYs) 1945–2013 (69 years) and WYs 1980–2013 (34 years). A WY is the 12-month period, October 1 through September 30, and is designated by the calendar year in which it ends. One streamgage is on the Whetstone River, a tributary to the Minnesota River, and the other streamgages are in the James, Big Sioux, and Vermillion River Basins. The watersheds for two of the James River streamgages extend into North Dakota, and parts of the watersheds for two of the Big Sioux River streamgages extend into Minnesota and Iowa. The objectives of this study were to document trends in streamflow and precipitation in these watersheds, and characterize the residual streamflow variability that might be attributed to factors other than precipitation. Residuals were computed as the departure from a locally-weighted scatterplot smoothing (LOWESS) model. Significance of trends was based on the Mann-Kendall nonparametric test at a 0.10 significance level.
\nOf the 10 streamgages selected, only the Elm River at Westport (in the upper part of James River Basin) did not have a significant upward trend in annual mean streamflow for WYs 1945–2013, whereas only one-half of the streamgages had significant upward trends in annual mean streamflow for WYs 1980–2013. Mean and 7-day minimum streamflows also had upward trends for the spring runoff period (March–May) for most of the streamgages during WYs 1945–2013 and for one streamgage during WYs 1980–2013. Magnitudes of increases in streamflow were as great as 30 cubic feet per second per year for the streamgage on the James River near Scotland during WYs 1980–2013.
\nPrecipitation trends for WYs 1945–2013 were not necessarily significant for the watersheds of streamgages with a significant streamflow trend. Annual total precipitation had a significant upward trend for the watersheds of 4 of the 10 streamgages during WYs 1945–2013 and no significant trends for WYs 1980–2013. The most widespread precipitation increase was for September–November, with significant upward trends for the watersheds of 8 of the 10 streamgages during WYs 1945–2013; however, no trends in September– November precipitation were significant for WYs 1980–2013. The greatest magnitude of increase in precipitation was for the December–May season during WYs 1980–2013, which had a mean increase of 0.106 inch per year in the watersheds of streamgages with significant trends.
\nThe correlation between streamflow and precipitation metrics was low as indicated by the mean coefficient of determination (R2) of 0.18 for all pairs considered. The highest locally-weighed scatterplot smoothing (LOWESS) correlation was between annual precipitation (by water year) and annual mean streamflow (by water year), which had a mean R2 of 0.47 for all streamgages and was as high as 0.72 for one streamgage. The correlation between annual precipitation and March–May mean streamflow had a mean R2 of 0.33 for all streamgages and was as high as 0.52 for one streamgage. Other metrics had R2 values for LOWESS correlations that were less than 0.3 and were not further considered for analyses of residuals. For annual precipitation as a predictor of annual mean flow, precipitation-removed streamflow had significant upward trends during WYs 1945–2013 for one-half of the streamgages. Upward trends in residual annual mean streamflow were indicated for the Whetstone River and lower part of the Big Sioux River Basin, indicating that other factors are contributors to streamflow variability during WYs 1945–2013. In contrast, most of the streamgages in the James and Vermillion River Basins had no trends in residual annual mean streamflow, indicating that streamflow trends can be explained primarily by precipitation. Precipitation-removed streamflow had fewer trends during the more recent analysis period of WYs 1980–2013 than WYs 1945–2013 for all streamgages in eastern South Dakota. Upward trends in residuals for March– May mean streamflow were indicated for Skunk Creek at Sioux Falls and the Big Sioux River at Akron, but trends in residuals were not significant at the remaining streamgages.
\nFor the streamgages with significant trends in residual streamflow (such as the streamgage on the Whetstone River and streamgages in the Big Sioux River Basin), land-use changes likely are minor factors, with the main factors probably being changes in the timing and frequency of large precipitation events and persistently wetter antecedent conditions. Changes in the relation between precipitation and streamflow since 1945 were evident when considering the runoff efficiency of the watershed. For example, the streamflow response to annual precipitation of 25 inches for the James River near Scotland increased from approximately 1,000 cubic feet per second for WYs 1945–1990 to about 2,500 cubic feet per second for WYs 1991–2013. The importance of antecedent conditions on annual mean streamflow also was indicated by the significance of the multiple linear regression coefficients of annual mean streamflow and precipitation from preceding water years for all but one streamgage. In addition, rising groundwater levels are present in wells in eastern South Dakota, particularly since the 1980s.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155146","collaboration":"Prepared in cooperation with the East Dakota Water Development District and James River Water Development District","usgsCitation":"Hoogestraat, G.K., and Stamm, J.F., 2015, Climate and streamflow characteristics for selected streamgages in eastern\nSouth Dakota, water years 1945–2013: U.S. Geological Survey Scientific Investigations Report 2015–5146, 35 p., with\nappendix, https://dx.doi.org/10.3133/sir20155146.","productDescription":"Report: v, 35 p.; Appendix","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1944-10-01","temporalEnd":"2013-09-30","ipdsId":"IP-066397","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":310790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5146/sir20155146.pdf","text":"Report","size":"3.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5146"},{"id":310792,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5146/appendix.xlsx","text":"Appendix","size":"94 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5146 Appendix"},{"id":310789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5146/coverthb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Big Sioux River basin, James River basin, Minnesota River basin, Vermillion River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.8876953125,\n 46.649436163350245\n ],\n [\n -100.17333984375,\n 45.98169518512228\n ],\n [\n -100.2392578125,\n 44.94924926661153\n ],\n [\n -98.8330078125,\n 43.27720532212024\n ],\n [\n -98.59130859375,\n 43.004647127794435\n ],\n [\n -97.88818359375,\n 42.76314586689494\n ],\n [\n -97.44873046875,\n 42.827638636242284\n ],\n [\n -96.45996093749999,\n 42.553080288955826\n ],\n [\n -96.45996093749999,\n 42.956422511073335\n ],\n [\n -95.77880859375,\n 43.42100882994726\n ],\n [\n -95.95458984375,\n 44.11914151643737\n ],\n [\n -96.96533203125,\n 44.793530904744074\n ],\n [\n -96.591796875,\n 45.336701909968106\n ],\n [\n -96.83349609375,\n 45.61403741135093\n ],\n [\n -97.3828125,\n 45.55252525134013\n ],\n [\n -97.91015624999999,\n 45.72152152227954\n ],\n [\n -98.06396484375,\n 46.07323062540838\n ],\n [\n -98.4814453125,\n 46.30140615437332\n ],\n [\n -98.7890625,\n 46.6795944656402\n ],\n [\n -99.25048828124999,\n 46.76996843356982\n ],\n [\n -99.8876953125,\n 46.649436163350245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
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1608 Mountain View Road
Rapid City, South Dakota 57702
http://sd.water.usgs.gov/
The seismic signatures of calving events, i.e., calving icequakes, offer an opportunity to examine calving variability with greater precision than is available with other methods. Here using observations from Yahtse Glacier, Alaska, we describe methods to detect, locate, and characterize calving icequakes. We combine these icequake records with a coincident, manually generated record of observed calving events to develop and validate a statistical model through which we can infer iceberg sizes from the properties of calving icequakes. We find that the icequake duration is the single most significant predictor of an iceberg's size. We then apply this model to 18 months of seismic recordings and find elevated iceberg calving flux during the summer and fall and a pronounced lull in calving during midwinter. Calving flux is sensitive to semidiurnal tidal stage. Large calving events are tens of percent more likely during falling and low tides than during rising and high tides, consistent with a view that deeper water has a stabilizing influence on glacier termini. Multiple factors affect the occurrence of mechanical fractures that ultimately lead to iceberg calving. At Yahtse Glacier, seismology allows us to demonstrate that variations in the rate of submarine melt are a dominant control on iceberg calving rates at seasonal timescales. On hourly to daily timescales, tidal modulation of the normal stress against the glacier terminus reveals the nonlinear glacier response to changes in the near-terminus stress field.
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the Royal Society A: Mathematical, Physical and Engineering Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback","docAbstract":"We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Philosophical transactions of the Royal Society of London A","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Royal Society","publisherLocation":"London","doi":"10.1098/rsta.2014.0423","usgsCitation":"Koven, C., Schuur, E., Schädel, C., Bohn, T.J., Burke, E.J., Chen, G., Chen, X., Ciais, P., Grosse, G., Harden, J., Hayes, D., Hugelius, G., Jafarov, E.E., Krinner, G., Kuhry, P., Lawrence, D., MacDougall, A.H., Marchenko, S., McGuire, A.D., Natali, S.M., Nicolsky, D., Olefeldt, D., Peng, S., Romanovsky, V., Schaefer, K.M., Strauss, J., Treat, C.C., and Turetsky, M., 2015, A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, v. 373, no. 2054, 23 p., https://doi.org/10.1098/rsta.2014.0423.","productDescription":"23 p.","numberOfPages":"23","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065036","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsta.2014.0423","text":"Publisher Index Page"},{"id":319363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Circle","volume":"373","issue":"2054","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-13","publicationStatus":"PW","scienceBaseUri":"56f50face4b0f59b85e1ea6a","contributors":{"authors":[{"text":"Koven, C.D.","contributorId":34017,"corporation":false,"usgs":true,"family":"Koven","given":"C.D.","affiliations":[],"preferred":false,"id":623624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuur, E.A.G.","contributorId":106679,"corporation":false,"usgs":true,"family":"Schuur","given":"E.A.G.","affiliations":[],"preferred":false,"id":623625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schädel, C.","contributorId":14713,"corporation":false,"usgs":true,"family":"Schädel","given":"C.","affiliations":[],"preferred":false,"id":623626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohn, T. 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David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":623376,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Natali, Susan M.","contributorId":103160,"corporation":false,"usgs":true,"family":"Natali","given":"Susan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":623649,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Nicolsky, D.J.","contributorId":51584,"corporation":false,"usgs":true,"family":"Nicolsky","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":623650,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Olefeldt, David","contributorId":37622,"corporation":false,"usgs":true,"family":"Olefeldt","given":"David","email":"","affiliations":[],"preferred":false,"id":623651,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Peng, S.","contributorId":68688,"corporation":false,"usgs":true,"family":"Peng","given":"S.","email":"","affiliations":[],"preferred":false,"id":623652,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Romanovsky, V.E.","contributorId":54721,"corporation":false,"usgs":true,"family":"Romanovsky","given":"V.E.","email":"","affiliations":[],"preferred":false,"id":623653,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Schaefer, Kevin M.","contributorId":89449,"corporation":false,"usgs":true,"family":"Schaefer","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":623654,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Strauss, J.","contributorId":8770,"corporation":false,"usgs":true,"family":"Strauss","given":"J.","affiliations":[],"preferred":false,"id":623655,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Treat, Claire C.","contributorId":96606,"corporation":false,"usgs":true,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":25501,"text":"University of Eastern Finland","active":true,"usgs":false}],"preferred":false,"id":623656,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Turetsky, M.","contributorId":108302,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.","affiliations":[],"preferred":false,"id":623657,"contributorType":{"id":1,"text":"Authors"},"rank":28}]}} ,{"id":70159462,"text":"70159462 - 2015 - The vulnerability of Indo-Pacific mangrove forests to sea-level rise","interactions":[],"lastModifiedDate":"2019-12-11T16:00:31","indexId":"70159462","displayToPublicDate":"2015-11-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"The vulnerability of Indo-Pacific mangrove forests to sea-level rise","docAbstract":"Sea-level rise can threaten the long-term sustainability of coastal communities and valuable ecosystems such as coral reefs, salt marshes and mangroves. Mangrove forests have the capacity to keep pace with sea-level rise and to avoid inundation through vertical accretion of sediments, which allows them to maintain wetland soil elevations suitable for plant growth. The Indo-Pacific region holds most of the world’s mangrove forests, but sediment delivery in this region is declining, owing to anthropogenic activities such as damming of rivers. This decline is of particular concern because the Indo-Pacific region is expected to have variable, but high, rates of future sea-level rise. Here we analyse recent trends in mangrove surface elevation changes across the Indo-Pacific region using data from a network of surface elevation table instruments. We find that sediment availability can enable mangrove forests to maintain rates of soil-surface elevation gain that match or exceed that of sea-level rise, but for 69 per cent of our study sites the current rate of sea-level rise exceeded the soil surface elevation gain. We also present a model based on our field data, which suggests that mangrove forests at sites with low tidal range and low sediment supply could be submerged as early as 2070.
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thermal erosion by turbulent lava in proximal Athabasca Valles, Mars","docAbstract":"The Athabasca Valles flood lava is among the most recent (<50 Ma) and best preserved effusive lava flows on Mars and was probably emplaced turbulently. The Williams et al. (2005) model of thermal erosion by lava has been applied to what we term “proximal Athabasca,” the 75 km long upstream portion of Athabasca Valles. For emplacement volumes of 5000 and 7500 km3and average flow thicknesses of 20 and 30 m, the duration of the eruption varies between ~11 and ~37 days. The erosion of the lava flow substrate is investigated for three eruption temperatures (1270°C, 1260°C, and 1250°C), and volatile contents equivalent to 0–65 vol % bubbles. The largest erosion depths of ~3.8–7.5 m are at the lava source, for 20 m thick and bubble-free flows that erupted at their liquidus temperature (1270°C). A substrate containing 25 vol % ice leads to maximum erosion. A lava temperature 20°C below liquidus reduces erosion depths by a factor of ~2.2. If flow viscosity increases with increasing bubble content in the lava, the presence of 30–50 vol % bubbles leads to erosion depths lower than those relative to bubble-free lava by a factor of ~2.4. The presence of 25 vol % ice in the substrate increases erosion depths by a factor of 1.3. Nevertheless, modeled erosion depths, consistent with the emplacement volume and flow duration constraints, are far less than the depth of the channel (~35–100 m). We conclude that thermal erosion does not appear to have had a major role in excavating Athabasca Valles.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JE004761","usgsCitation":"Cataldo, V., Williams, D., Dundas, C.M., and Keszthelyi, L.P., 2015, Limited role for thermal erosion by turbulent lava in proximal Athabasca Valles, Mars: Journal of Geophysical Research E: Planets, v. 120, no. 11, p. 1800-1819, https://doi.org/10.1002/2014JE004761.","productDescription":"20 p.","startPage":"1800","endPage":"1819","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059899","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":471687,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1002/2014JE004761","text":"Publisher Index Page"},{"id":314324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"120","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-21","publicationStatus":"PW","scienceBaseUri":"5698d4cfe4b0fbd3f7fa4c4a","contributors":{"authors":[{"text":"Cataldo, Vincenzo","contributorId":150474,"corporation":false,"usgs":false,"family":"Cataldo","given":"Vincenzo","email":"","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":581764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, David A.","contributorId":84604,"corporation":false,"usgs":true,"family":"Williams","given":"David A.","affiliations":[],"preferred":false,"id":581765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":581763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":227,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo","email":"laz@usgs.gov","middleInitial":"P.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":581766,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160106,"text":"70160106 - 2015 - LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients","interactions":[],"lastModifiedDate":"2015-12-14T11:10:26","indexId":"70160106","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients","docAbstract":"Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.
","language":"English","publisher":"American Elsevier Pub. Co.","publisherLocation":"New York, NY","doi":"10.1016/j.rse.2015.07.028","usgsCitation":"Babcock, C., Finley, A., Bradford, J.B., Kolka, R.K., Birdsey, R.A., and Ryan, M., 2015, LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients: Remote Sensing of Environment, v. 169, p. 113-127, https://doi.org/10.1016/j.rse.2015.07.028.","productDescription":"15 p.","startPage":"113","endPage":"127","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034289","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2015.07.028","text":"Publisher Index Page"},{"id":312243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Minnesota","otherGeospatial":"Fraser Experimental Forest, Marcell Experimental Forest, Niwot Long Term Ecological Research Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.9,\n 39\n ],\n [\n -105.9,\n 39.1\n ],\n [\n -105.8,\n 39.1\n ],\n [\n -105.8,\n 39\n ],\n [\n -105.9,\n 39\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94,\n 47\n ],\n [\n -94,\n 48\n ],\n [\n -93,\n 48\n ],\n [\n -93,\n 47\n ],\n [\n -94,\n 47\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.6,\n 40\n ],\n [\n -105.6,\n 40.1\n ],\n [\n -105.5,\n 40.1\n ],\n [\n -105.5,\n 40\n ],\n [\n -105.6,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"169","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"566ff652e4b09cfe53ca79a9","contributors":{"authors":[{"text":"Babcock, Chad","contributorId":150502,"corporation":false,"usgs":false,"family":"Babcock","given":"Chad","email":"","affiliations":[{"id":18039,"text":"Department of Geography, Michigan State University, East Lansing, Michigan USA","active":true,"usgs":false}],"preferred":false,"id":581913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finley, Andrew O.","contributorId":70666,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew O.","affiliations":[],"preferred":false,"id":581912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":581911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolka, Randall K.","contributorId":16150,"corporation":false,"usgs":false,"family":"Kolka","given":"Randall","email":"","middleInitial":"K.","affiliations":[{"id":13259,"text":"USDA Forest Service Northern Research Station","active":true,"usgs":false}],"preferred":false,"id":581915,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birdsey, Richard A.","contributorId":17751,"corporation":false,"usgs":true,"family":"Birdsey","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":581916,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ryan, Michael G.","contributorId":101580,"corporation":false,"usgs":true,"family":"Ryan","given":"Michael G.","affiliations":[],"preferred":false,"id":581917,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179124,"text":"70179124 - 2015 - Geochemistry and origin of metamorphosed mafic rocks from the Lower Paleozoic Moretown and Cram Hill Formations of North-Central Vermont: Delamination magmatism in the western New England appalachians","interactions":[],"lastModifiedDate":"2017-01-13T14:39:51","indexId":"70179124","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":732,"text":"American Journal of Science","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and origin of metamorphosed mafic rocks from the Lower Paleozoic Moretown and Cram Hill Formations of North-Central Vermont: Delamination magmatism in the western New England appalachians","docAbstract":"The Moretown Formation, exposed as a north-trending unit that extends from northern Vermont to Connecticut, is located along a critical Appalachian litho-tectonic zone between the paleomargin of Laurentia and accreted oceanic terranes. Remnants of magmatic activity, in part preserved as metamorphosed mafic rocks in the Moretown Formation and the overlying Cram Hill Formation, are a key to further understanding the tectonic history of the northern Appalachians. Field relationships suggest that the metamorphosed mafic rocks might have formed during and after Taconian deformation, which occurred at ca. 470 to 460 Ma. Geochemistry indicates that the sampled metamorphosed mafic rocks were mostly basalts or basaltic andesites. The rocks have moderate TiO2 contents (1–2.5 wt %), are slightly enriched in the light-rare earth elements relative to the heavy rare earths, and have negative Nb-Ta anomalies in MORB-normalized extended rare earth element diagrams. Their chemistry is similar to compositions of basalts from western Pacific extensional basins near volcanic arcs. The metamorphosed mafic rocks of this study are similar in chemistry to both the pre-Silurian Mount Norris Intrusive Suite of northern Vermont, and also to some of Late Silurian rocks within the Lake Memphremagog Intrusive Suite, particularly the Comerford Intrusive Complex of Vermont and New Hampshire. Both suites may be represented among the samples of this study. The geochemistry of all samples indicates that parental magmas were generated in supra-subduction extensional environments during lithospheric delamination.
","language":"English","publisher":"American Journal of Science","doi":"10.2475/09.2015.02","usgsCitation":"Coish, R., Kim, J., Twelker, E., Zolkos, S., and Walsh, G.J., 2015, Geochemistry and origin of metamorphosed mafic rocks from the Lower Paleozoic Moretown and Cram Hill Formations of North-Central Vermont: Delamination magmatism in the western New England appalachians: American Journal of Science, v. 315, no. 9, p. 809-845, https://doi.org/10.2475/09.2015.02.","productDescription":"37 p.","startPage":"809","endPage":"845","ipdsId":"IP-068938","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":333204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"315","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-04","publicationStatus":"PW","scienceBaseUri":"5879f5abe4b0847d353f44c2","contributors":{"authors":[{"text":"Coish, Raymond","contributorId":177531,"corporation":false,"usgs":false,"family":"Coish","given":"Raymond","email":"","affiliations":[],"preferred":false,"id":658439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim, Jonathan","contributorId":10900,"corporation":false,"usgs":true,"family":"Kim","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":658440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Twelker, Evan","contributorId":178306,"corporation":false,"usgs":false,"family":"Twelker","given":"Evan","email":"","affiliations":[],"preferred":false,"id":658441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zolkos, Scott P.","contributorId":103946,"corporation":false,"usgs":true,"family":"Zolkos","given":"Scott P.","affiliations":[],"preferred":false,"id":658442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walsh, Gregory J. 0000-0003-4264-8836 gwalsh@usgs.gov","orcid":"https://orcid.org/0000-0003-4264-8836","contributorId":873,"corporation":false,"usgs":true,"family":"Walsh","given":"Gregory","email":"gwalsh@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":658443,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185011,"text":"70185011 - 2015 - Accuracy assessment of NOAA gridded daily reference evapotranspiration for the Texas High Plains","interactions":[],"lastModifiedDate":"2017-05-09T12:55:24","indexId":"70185011","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Accuracy assessment of NOAA gridded daily reference evapotranspiration for the Texas High Plains","docAbstract":"The National Oceanic and Atmospheric Administration (NOAA) provides daily reference evapotranspiration (ETref) maps for the contiguous United States using climatic data from North American Land Data Assimilation System (NLDAS). This data provides large-scale spatial representation of ETref, which is essential for regional scale water resources management. Data used in the development of NOAA daily ETref maps are derived from observations over surfaces that are different from short (grass — ETos) or tall (alfalfa — ETrs) reference crops, often in nonagricultural settings, which carries an unknown discrepancy between assumed and actual conditions. In this study, NOAA daily ETos and ETrs maps were evaluated for accuracy, using observed data from the Texas High Plains Evapotranspiration (TXHPET) network. Daily ETos, ETrs and the climatic data (air temperature, wind speed, and solar radiation) used for calculating ETref were extracted from the NOAA maps for TXHPET locations and compared against ground measurements on reference grass surfaces. NOAA ETrefmaps generally overestimated the TXHPET observations (1.4 and 2.2 mm/day ETos and ETrs, respectively), which may be attributed to errors in the NLDAS modeled air temperature and wind speed, to which reference ETref is most sensitive. Therefore, a bias correction to NLDAS modeled air temperature and wind speed data, or adjustment to the resulting NOAA ETref, may be needed to improve the accuracy of NOAA ETref maps.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12303","usgsCitation":"Moorhead, J., Gowda, P.H., Hobbins, M., Senay, G., Paul, G., Marek, T., and Porter, D., 2015, Accuracy assessment of NOAA gridded daily reference evapotranspiration for the Texas High Plains: Journal of the American Water Resources Association, v. 51, no. 5, p. 1262-1271, https://doi.org/10.1111/1752-1688.12303.","productDescription":"10 p.","startPage":"1262","endPage":"1271","ipdsId":"IP-063403","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":337526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","volume":"51","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-18","publicationStatus":"PW","scienceBaseUri":"58c90128e4b0849ce97abcf1","contributors":{"authors":[{"text":"Moorhead, Jerry","contributorId":189262,"corporation":false,"usgs":false,"family":"Moorhead","given":"Jerry","email":"","affiliations":[],"preferred":false,"id":684270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gowda, Prasanna H.","contributorId":127439,"corporation":false,"usgs":false,"family":"Gowda","given":"Prasanna","email":"","middleInitial":"H.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":684271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobbins, Michael","contributorId":127605,"corporation":false,"usgs":false,"family":"Hobbins","given":"Michael","email":"","affiliations":[{"id":7075,"text":"National Integrated Drought Information System, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":684272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":683951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paul, George","contributorId":189263,"corporation":false,"usgs":false,"family":"Paul","given":"George","email":"","affiliations":[],"preferred":false,"id":684273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marek, Thomas","contributorId":189264,"corporation":false,"usgs":false,"family":"Marek","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":684274,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Porter, Dana","contributorId":189265,"corporation":false,"usgs":false,"family":"Porter","given":"Dana","email":"","affiliations":[],"preferred":false,"id":684275,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70178511,"text":"70178511 - 2015 - Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis","interactions":[],"lastModifiedDate":"2016-11-22T12:24:38","indexId":"70178511","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis","docAbstract":"A Delaware Bay, USA, standardized survey of spawning horseshoe crabs, Limulus polyphemus, was carried out in 1999 − 2013 through a citizen science network. Previous trend analyses of the data were at the state (DE or NJ) or bay-wide levels. Here, an alternative mixed-model regression analysis was used to estimate trends in female and male spawning densities at the beach level (n = 26) with the objective of inferring their causes. For females, there was no overall trend and no single explanation applies to the temporal and spatial patterns in their densities. Individual beaches that initially had higher densities tended to experience a decrease, while beaches that initially had lower densities tended to experience an increase. As a result, densities of spawning females at the end of the study period were relatively similar among beaches, suggesting a redistribution of females among the beaches over the study period. For males, there was a positive overall trend in spawning abundance from 1999 to 2013, and this increase occurred broadly among beaches. Moreover, the beaches with below-average initial male density tended to have the greatest increases. Possible explanations for these patterns include harvest reduction, sampling artifact, habitat change, density-dependent habitat selection, or mate selection. The broad and significant increase in male spawning density, which occurred after enactment of harvest controls, is consistent with the harvest reduction explanation, but there is no single explanation for the temporal or spatial pattern in female densities. These results highlight the continued value of a citizen-science-based spawning survey in understanding horseshoe crab ecology and conservation.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-015-9961-3","usgsCitation":"Smith, D.R., and Robinson, T., 2015, Horseshoe crab spawning activity in Delaware Bay, USA, after harvest reduction: A mixed-model analysis: Estuaries and Coasts, v. 38, no. 6, p. 2345-2354, https://doi.org/10.1007/s12237-015-9961-3.","productDescription":"10 p.","startPage":"2345","endPage":"2354","ipdsId":"IP-057549","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":331187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-27","publicationStatus":"PW","scienceBaseUri":"5835672ce4b0070c0abfb6da","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":654198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Timothy J.","contributorId":171636,"corporation":false,"usgs":false,"family":"Robinson","given":"Timothy J.","affiliations":[],"preferred":false,"id":654199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70173437,"text":"70173437 - 2015 - Density of river otters (Lontra canadensis) in relation to energy development in the Green River Basin, Wyoming","interactions":[],"lastModifiedDate":"2016-06-16T16:42:07","indexId":"70173437","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Density of river otters (Lontra canadensis) in relation to energy development in the Green River Basin, Wyoming","docAbstract":"Exploration and extraction of oil and natural gas have increased in recent years and are expected to expand in the future. Reduction in water quality from energy extraction may negatively affect water supply for agriculture and urban use within catchments as well as down river. We used non-invasive genetic techniques and capture–recapture modeling to estimate the abundance and density of North American river otters (Lontra canadensis), a sentinel species of aquatic ecosystems, in Southwestern Wyoming. While densities in two of three river reaches were similar to those reported in other freshwater systems in the western US (1.45–2.39 km per otter), otters appeared to avoid areas near energy development. We found no strong difference in habitat variables, such as overstory cover, at the site or reach level. Also, fish abundance was similar among the three river reaches. Otter activity in our study area could have been affected by elevated levels of disturbance surrounding the industrial gas fields, and by potential surface water contamination as indicated by patterns in water conductivity. Continued monitoring of surface water quality in Southwestern Wyoming with the aid of continuously recording devices and sentinel species is warranted.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.06.058","usgsCitation":"Godwin, B., Albeke, S., Bergman, H., Walters, A.W., and Ben-David, M., 2015, Density of river otters (Lontra canadensis) in relation to energy development in the Green River Basin, Wyoming: Science of the Total Environment, v. 532, p. 780-790, https://doi.org/10.1016/j.scitotenv.2015.06.058.","productDescription":"11 p.","startPage":"780","endPage":"790","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060619","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Green River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.73556518554688,\n 42.703632059618045\n ],\n [\n -109.8193359375,\n 42.67536823702857\n ],\n [\n -109.90859985351561,\n 42.62385465855651\n ],\n [\n -110.07064819335938,\n 42.53689200787317\n ],\n [\n -110.14068603515625,\n 42.48728928565912\n ],\n [\n -110.12763977050781,\n 42.407234661551875\n ],\n [\n -110.14892578125,\n 42.36158819524629\n ],\n [\n -110.2313232421875,\n 42.259016415705766\n ],\n [\n -110.20111083984375,\n 42.18579390537848\n ],\n [\n -110.20523071289061,\n 42.12674735753131\n ],\n [\n -110.14892578125,\n 41.98603585974727\n ],\n [\n -109.92095947265625,\n 41.90636538970964\n ],\n [\n -109.77539062499999,\n 41.72828028223453\n ],\n [\n -109.5391845703125,\n 41.45301999377133\n ],\n [\n -109.54193115234374,\n 41.3500103516271\n ],\n [\n -109.4073486328125,\n 41.29431726315258\n ],\n [\n -109.28375244140625,\n 41.413895564677304\n ],\n [\n -109.5611572265625,\n 41.84910468610387\n ],\n [\n -110.04180908203124,\n 42.338244963350846\n ],\n [\n -109.86328125,\n 42.559149812115876\n ],\n [\n -109.6490478515625,\n 42.68041629144619\n ],\n [\n -109.73556518554688,\n 42.703632059618045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"532","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5763cdb3e4b07657d19ba761","contributors":{"authors":[{"text":"Godwin, B.L.","contributorId":172057,"corporation":false,"usgs":false,"family":"Godwin","given":"B.L.","email":"","affiliations":[],"preferred":false,"id":639468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albeke, S.E.","contributorId":172058,"corporation":false,"usgs":false,"family":"Albeke","given":"S.E.","affiliations":[],"preferred":false,"id":639469,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergman, H.L.","contributorId":73553,"corporation":false,"usgs":true,"family":"Bergman","given":"H.L.","email":"","affiliations":[],"preferred":false,"id":639470,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637131,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ben-David, M.","contributorId":11563,"corporation":false,"usgs":true,"family":"Ben-David","given":"M.","email":"","affiliations":[],"preferred":false,"id":639471,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186870,"text":"70186870 - 2015 - Interpretation of hydraulic conductivity in a fractured-rock aquifer over increasingly larger length dimensions","interactions":[],"lastModifiedDate":"2018-08-09T12:34:17","indexId":"70186870","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Interpretation of hydraulic conductivity in a fractured-rock aquifer over increasingly larger length dimensions","docAbstract":"A comparison of the hydraulic conductivity over increasingly larger volumes of crystalline rock was conducted in the Piedmont physiographic region near Bethesda, Maryland, USA. Fluid-injection tests were conducted on intervals of boreholes isolating closely spaced fractures. Single-hole tests were conducted by pumping in open boreholes for approximately 30 min, and an interference test was conducted by pumping a single borehole over 3 days while monitoring nearby boreholes. An estimate of the hydraulic conductivity of the rock over hundreds of meters was inferred from simulating groundwater inflow into a kilometer-long section of a Washington Metropolitan Area Transit Authority tunnel in the study area, and a groundwater modeling investigation over the Rock Creek watershed provided an estimate of the hydraulic conductivity over kilometers. The majority of groundwater flow is confined to relatively few fractures at a given location. Boreholes installed to depths of approximately 50 m have one or two highly transmissive fractures; the transmissivity of the remaining fractures ranges over five orders of magnitude. Estimates of hydraulic conductivity over increasingly larger rock volumes varied by less than half an order of magnitude. While many investigations point to increasing hydraulic conductivity as a function of the measurement scale, a comparison with selected investigations shows that the effective hydraulic conductivity estimated over larger volumes of rock can either increase, decrease, or remain stable as a function of the measurement scale. Caution needs to be exhibited in characterizing effective hydraulic properties in fractured rock for the purposes of groundwater management.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-015-1285-7","usgsCitation":"Shapiro, A.M., Ladderud, J., and Yager, R.M., 2015, Interpretation of hydraulic conductivity in a fractured-rock aquifer over increasingly larger length dimensions: Hydrogeology Journal, v. 23, no. 7, p. 1319-1339, https://doi.org/10.1007/s10040-015-1285-7.","productDescription":"21 p.","startPage":"1319","endPage":"1339","ipdsId":"IP-065461","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":339622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-23","publicationStatus":"PW","scienceBaseUri":"58ef3dace4b0eed1ab8e3be4","contributors":{"authors":[{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":690742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ladderud, Jeffery","contributorId":190799,"corporation":false,"usgs":false,"family":"Ladderud","given":"Jeffery","email":"","affiliations":[],"preferred":false,"id":690743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Richard M. 0000-0001-7725-1148 ryager@usgs.gov","orcid":"https://orcid.org/0000-0001-7725-1148","contributorId":950,"corporation":false,"usgs":true,"family":"Yager","given":"Richard","email":"ryager@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":690744,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168392,"text":"70168392 - 2015 - Predictions of future ephemeral springtime waterbird stopover habitat availability under global change","interactions":[],"lastModifiedDate":"2016-02-11T09:52:01","indexId":"70168392","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Predictions of future ephemeral springtime waterbird stopover habitat availability under global change","docAbstract":"In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES15-00256.1","usgsCitation":"Uden, D.R., Allen, C.R., Bishop, A.A., Grosse, R., Jorgensen, C.F., LaGrange, T.G., Stutheit, R.G., and Vrtiska, M.P., 2015, Predictions of future ephemeral springtime waterbird stopover habitat availability under global change: Ecosphere, v. 6, no. 11, p. 1-26, https://doi.org/10.1890/ES15-00256.1.","productDescription":"26 p.","startPage":"1","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067091","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es15-00256.1","text":"Publisher Index Page"},{"id":317932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Rainwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.77783203125,\n 40.22921818870117\n ],\n [\n -99.77783203125,\n 41.541477666790286\n ],\n [\n -96.591796875,\n 41.541477666790286\n ],\n [\n -96.591796875,\n 40.22921818870117\n ],\n [\n -99.77783203125,\n 40.22921818870117\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-09","publicationStatus":"PW","scienceBaseUri":"56bdbec8e4b06458514aeed9","contributors":{"authors":[{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":619874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":619858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Andrew A.","contributorId":93323,"corporation":false,"usgs":true,"family":"Bishop","given":"Andrew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":619875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grosse, Roger","contributorId":166720,"corporation":false,"usgs":false,"family":"Grosse","given":"Roger","email":"","affiliations":[],"preferred":false,"id":619876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jorgensen, Christopher F.","contributorId":87444,"corporation":false,"usgs":true,"family":"Jorgensen","given":"Christopher","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":619877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaGrange, Theodore G.","contributorId":166721,"corporation":false,"usgs":false,"family":"LaGrange","given":"Theodore","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":619878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stutheit, Randy G.","contributorId":166722,"corporation":false,"usgs":false,"family":"Stutheit","given":"Randy","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":619879,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vrtiska, Mark P.","contributorId":54008,"corporation":false,"usgs":true,"family":"Vrtiska","given":"Mark","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619880,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70161997,"text":"70161997 - 2015 - Imaging the magmatic system of Mono Basin, California with magnetotellurics in three--dimensions","interactions":[],"lastModifiedDate":"2016-01-13T09:58:17","indexId":"70161997","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Imaging the magmatic system of Mono Basin, California with magnetotellurics in three--dimensions","docAbstract":"A three–dimensional (3D) electrical resistivity model of Mono Basin in eastern California unveils a complex subsurface filled with zones of partial melt, fluid–filled fracture networks, cold plutons, and regional faults. In 2013, 62 broadband magnetotelluric (MT) stations were collected in an array around southeastern Mono Basin from which a 3D electrical resistivity model was created with a resolvable depth of 35 km. Multiple robust electrical resistivity features were found that correlate with existing geophysical observations. The most robust features are two 300 ± 50 km3 near-vertical conductive bodies (3–10 Ω·m) that underlie the southeast and north-eastern margin of Mono Craters below 10 km depth. These features are interpreted as magmatic crystal–melt mush zones of 15 ± 5% interstitial melt surrounded by hydrothermal fluids and are likely sources for Holocene eruptions. Two conductive east–dipping structures appear to connect each magma source region to the surface. A conductive arc–like structure (< 0.9 Ω·m) links the northernmost mush column at 10 km depth to just below vents near Panum Crater, where the high conductivity suggests the presence of hydrothermal fluids. The connection from the southernmost mush column at 10 km depth to below South Coulée is less obvious with higher resistivity (200 Ω·m) suggestive of a cooled connection. A third, less constrained conductive feature (4–10 Ω·m) 15 km deep extending to 35 km is located west of Mono Craters near the eastern front of the Sierra Nevada escarpment, and is coincident with a zone of sporadic, long–period earthquakes that are characteristic of a fluid-filled (magmatic or metamorphic) fracture network. A resistive feature (103–105 Ω·m) located under Aeolian Buttes contains a deep root down to 25 km. The eastern edge of this resistor appears to structurally control the arcuate shape of Mono Craters. These observations have been combined to form a new conceptual model of the magmatic system beneath Mono Craters to a depth of 30 km.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012071","usgsCitation":"Peacock, J.R., Mangan, M.T., McPhee, D., and Ponce, D.A., 2015, Imaging the magmatic system of Mono Basin, California with magnetotellurics in three--dimensions: Journal of Geophysical Research, v. 120, no. 11, p. 7273-7289, https://doi.org/10.1002/2015JB012071.","productDescription":"17 p.","startPage":"7273","endPage":"7289","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064799","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012071","text":"Publisher Index Page"},{"id":314262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mono Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.6136474609375,\n 37.89219554724437\n ],\n [\n -119.6136474609375,\n 38.39764411353181\n ],\n [\n -118.60290527343749,\n 38.39764411353181\n ],\n [\n -118.60290527343749,\n 37.89219554724437\n ],\n [\n -119.6136474609375,\n 37.89219554724437\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"11","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-07","publicationStatus":"PW","scienceBaseUri":"5697833ce4b039675d00a6e7","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":588286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mangan, Margaret T. 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":3343,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":588287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McPhee, Darcy 0000-0002-5177-3068 dmcphee@usgs.gov","orcid":"https://orcid.org/0000-0002-5177-3068","contributorId":2621,"corporation":false,"usgs":true,"family":"McPhee","given":"Darcy","email":"dmcphee@usgs.gov","affiliations":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"preferred":true,"id":588288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":588289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160055,"text":"70160055 - 2015 - Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA","interactions":[],"lastModifiedDate":"2015-12-10T09:12:15","indexId":"70160055","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA","docAbstract":"Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire–weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/10/11/114013","usgsCitation":"Urbieta, I.R., Zavala, G., Bedia, J., Gutierrez, J.M., San Miguel-Ayanz, J., Camia, A., Keeley, J.E., and Moreno, J.M., 2015, Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA: Environmental Research Letters, v. 10, no. 11, art11431: 11 p., https://doi.org/10.1088/1748-9326/10/11/114013.","productDescription":"art11431: 11 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059299","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/10/11/114013","text":"Publisher Index 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Joaquin","contributorId":150460,"corporation":false,"usgs":false,"family":"Bedia","given":"Joaquin","email":"","affiliations":[{"id":18030,"text":"Grupo de Meteorologia, Instituto de Fisica de Cantabria, U de Cantabria, Santander, Spain","active":true,"usgs":false}],"preferred":false,"id":581735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gutierrez, Jose M.","contributorId":150461,"corporation":false,"usgs":false,"family":"Gutierrez","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":18031,"text":"G Meteorologia, I Fisica de Cantabria, U de Cantabria, Santander, Spain","active":true,"usgs":false}],"preferred":false,"id":581736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"San Miguel-Ayanz, Jesus","contributorId":150463,"corporation":false,"usgs":false,"family":"San Miguel-Ayanz","given":"Jesus","email":"","affiliations":[{"id":18033,"text":"European Commission, JRC, I for Environment and Sustainability, Ispra Varese, Italy","active":true,"usgs":false}],"preferred":false,"id":581738,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Camia, Andrea","contributorId":150462,"corporation":false,"usgs":false,"family":"Camia","given":"Andrea","email":"","affiliations":[{"id":18032,"text":"European Commission, Joint Research Centere, Institute for Environment and Sustainability, Ispra Varese, Italy","active":true,"usgs":false}],"preferred":false,"id":581737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":581732,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moreno, Jose M.","contributorId":150464,"corporation":false,"usgs":false,"family":"Moreno","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":18029,"text":"D Ciencias Ambientales, U Castilla La Mancha, Toledo, Spain","active":true,"usgs":false}],"preferred":false,"id":581739,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70176528,"text":"70176528 - 2015 - A bootstrap method for estimating uncertainty of water quality trends","interactions":[],"lastModifiedDate":"2016-09-20T15:20:55","indexId":"70176528","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A bootstrap method for estimating uncertainty of water quality trends","docAbstract":"Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction of the WRTDS Bootstrap Test (WBT), an extension of WRTDS that quantifies the uncertainty in WRTDS-estimates of water quality trends and offers various ways to visualize and communicate these uncertainties. Monte Carlo experiments are applied to estimate the Type I error probabilities for this method. WBT is compared to other water-quality trend-testing methods appropriate for data sets of one to three decades in length with sampling frequencies of 6–24 observations per year. The software to conduct the test is in the EGRETci R-package.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2015.07.017","usgsCitation":"Hirsch, R.M., Archfield, S.A., and DeCicco, L.A., 2015, A bootstrap method for estimating uncertainty of water quality trends: Environmental Modelling and Software, v. 73, p. 148-166, https://doi.org/10.1016/j.envsoft.2015.07.017.","productDescription":"19 p.","startPage":"148","endPage":"166","ipdsId":"IP-067558","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":482080,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2015.07.017","text":"Publisher Index Page"},{"id":328774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7ee36e4b0bc0bec09e90b","contributors":{"authors":[{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":649115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":649116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649117,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159661,"text":"70159661 - 2015 - Global climate simulations at 3000-year intervals for the last 21 000 years with the GENMOM coupled atmosphere–ocean model","interactions":[],"lastModifiedDate":"2015-11-17T14:03:23","indexId":"70159661","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"Global climate simulations at 3000-year intervals for the last 21 000 years with the GENMOM coupled atmosphere–ocean model","docAbstract":"We apply GENMOM, a coupled atmosphere–ocean climate model, to simulate eight equilibrium time slices at 3000-year intervals for the past 21 000 years forced by changes in Earth–Sun geometry, atmospheric greenhouse gases (GHGs), continental ice sheets, and sea level. Simulated global cooling during the Last Glacial Maximum (LGM) is 3.8 ◦C and the rate of post-glacial warming is in overall agreement with recently published temperature reconstructions. The greatest rate of warming occurs between 15 and 12 ka (2.4 ◦C over land, 0.7 ◦C over oceans, and 1.4 ◦C globally) in response to changes in radiative forcing from the diminished extent of the Northern Hemisphere (NH) ice sheets and increases in GHGs and NH summer insolation. The modeled LGM and 6 ka temperature and precipitation climatologies are generally consistent with proxy reconstructions, the PMIP2 and PMIP3 simulations, and other paleoclimate data–model analyses. The model does not capture the mid-Holocene “thermal maximum” and gradual cooling to preindustrial (PI) global temperature found in the data. Simulated monsoonal precipitation in North Africa peaks between 12 and 9 ka at values ∼ 50 % greater than those of the PI, and Indian monsoonal precipitation peaks at 12 and 9 ka at values ∼ 45 % greater than the PI. GENMOM captures the reconstructed LGM extent of NH and Southern Hemisphere (SH) sea ice. The simulated present-day Antarctica Circumpolar Current (ACC) is ∼ 48 % weaker than the observed (62 versus 119 Sv). The simulated present-day Atlantic Meridional Overturning Circulation (AMOC) of 19.3 ± 1.4 Sv on the Bermuda Rise (33◦ N) is comparable with observed value of 18.7 ± 4.8 Sv. AMOC at 33◦ N is reduced by ∼ 15 % during the LGM, and the largest post-glacial increase (∼ 11 %) occurs during the 15 ka time slice.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-11-449-2015","usgsCitation":"Alder, J.R., and Hostetler, S.W., 2015, Global climate simulations at 3000-year intervals for the last 21 000 years with the GENMOM coupled atmosphere–ocean model: Climate of the Past, v. 11, p. 449-471, https://doi.org/10.5194/cp-11-449-2015.","productDescription":"23 p.","startPage":"449","endPage":"471","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049480","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471673,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-11-449-2015","text":"Publisher Index Page"},{"id":311436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-17","publicationStatus":"PW","scienceBaseUri":"564c5dd0e4b0ebfbef0d347b","contributors":{"authors":[{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":579958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155230,"text":"70155230 - 2015 - Stable carbon isotope fractionation during bacterial acetylene fermentation: Potential for life detection in hydrocarbon-rich volatiles of icy planet(oid)s","interactions":[],"lastModifiedDate":"2018-09-04T15:45:53","indexId":"70155230","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":912,"text":"Astrobiology","active":true,"publicationSubtype":{"id":10}},"title":"Stable carbon isotope fractionation during bacterial acetylene fermentation: Potential for life detection in hydrocarbon-rich volatiles of icy planet(oid)s","docAbstract":"We report the first study of stable carbon isotope fractionation during microbial fermentation of acetylene (C2H2) in sediments, sediment enrichments, and bacterial cultures. Kinetic isotope effects (KIEs) averaged 3.7 ± 0.5‰ for slurries prepared with sediment collected at an intertidal mudflat in San Francisco Bay and 2.7 ± 0.2‰ for a pure culture of Pelobacter sp. isolated from these sediments. A similar KIE of 1.8 ± 0.7‰ was obtained for methanogenic enrichments derived from sediment collected at freshwater Searsville Lake, California. However, C2H2 uptake by a highly enriched mixed culture (strain SV7) obtained from Searsville Lake sediments resulted in a larger KIE of 9.0 ± 0.7‰. These are modest KIEs when compared with fractionation observed during oxidation of C1 compounds such as methane and methyl halides but are comparable to results obtained with other C2compounds. These observations may be useful in distinguishing biologically active processes operating at distant locales in the Solar System where C2H2 is present. These locales include the surface of Saturn's largest moon Titan and the vaporous water- and hydrocarbon-rich jets emanating from Enceladus.
","language":"English","publisher":"Mary Ann Liebert, Inc.","doi":"10.1089/ast.2015.1355","usgsCitation":"Miller, L., Baesman, S., and Oremland, R., 2015, Stable carbon isotope fractionation during bacterial acetylene fermentation: Potential for life detection in hydrocarbon-rich volatiles of icy planet(oid)s: Astrobiology, v. 15, no. 11, p. 977-986, https://doi.org/10.1089/ast.2015.1355.","productDescription":"10 p.","startPage":"977","endPage":"986","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065877","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1089/ast.2015.1355","text":"Publisher Index Page"},{"id":324709,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57779435e4b07dd077c9062c","contributors":{"authors":[{"text":"Miller, Laurence lgmiller@usgs.gov","contributorId":145772,"corporation":false,"usgs":true,"family":"Miller","given":"Laurence","email":"lgmiller@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":565211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baesman, Shaun 0000-0003-0741-8269 sbaesman@usgs.gov","orcid":"https://orcid.org/0000-0003-0741-8269","contributorId":3478,"corporation":false,"usgs":true,"family":"Baesman","given":"Shaun","email":"sbaesman@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":565212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oremland, Ron roremlan@usgs.gov","contributorId":145773,"corporation":false,"usgs":true,"family":"Oremland","given":"Ron","email":"roremlan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":565213,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186185,"text":"70186185 - 2015 - Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices","interactions":[],"lastModifiedDate":"2017-03-31T10:20:53","indexId":"70186185","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices","docAbstract":"Climate change is expected to modify the timing of seasonal transitions this century, impacting wildlife migrations, ecosystem function, and agricultural activity. Tracking seasonal transitions in a consistent manner across space and through time requires indices that can be used for monitoring and managing biophysical and ecological systems during the coming decades. Here a new gridded dataset of spring indices is described and used to understand interannual, decadal, and secular trends across the coterminous United States. This dataset is derived from daily interpolated meteorological data, and the results are compared with historical station data to ensure the trends and variations are robust. Regional trends in the first leaf index range from 20.8 to 21.6 days decade21, while first bloom index trends are between20.4 and 21.2 for most regions. However, these trends are modulated by interannual to multidecadal variations, which are substantial throughout the regions considered here. These findings emphasize the important role large-scale climate modes of variability play in modulating spring onset on interannual to multidecadal time scales. Finally, there is some potential for successful subseasonal forecasts of spring onset, as indices from most regions are significantly correlated with antecedent large-scale modes of variability.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JCLI-D-14-00736.1","usgsCitation":"Ault, T.R., Schwartz, M.D., Zurita-Milla, R., Weltzin, J.F., and Betancourt, J.L., 2015, Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices: Journal of Climate, v. 28, no. 21, p. 8363-8378, https://doi.org/10.1175/JCLI-D-14-00736.1.","productDescription":"15 p.","startPage":"8363","endPage":"8378","ipdsId":"IP-064784","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":471671,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.utwente.nl/en/publications/0858f753-4773-4800-b11e-86d3513ced55","text":"External Repository"},{"id":338921,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"21","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-30","publicationStatus":"PW","scienceBaseUri":"58df6ac2e4b02ff32c6aea43","contributors":{"authors":[{"text":"Ault, Toby R.","contributorId":146164,"corporation":false,"usgs":false,"family":"Ault","given":"Toby","email":"","middleInitial":"R.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":687787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, Mark D.","contributorId":175228,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":687788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zurita-Milla, Raul","contributorId":146213,"corporation":false,"usgs":false,"family":"Zurita-Milla","given":"Raul","email":"","affiliations":[{"id":16630,"text":"Department of Geo-Information Processing, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":687789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weltzin, Jake F. 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":189061,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake","email":"jweltzin@usgs.gov","middleInitial":"F.","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":false,"id":687790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":687786,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170064,"text":"70170064 - 2015 - Earthquake rupture process recreated from a natural fault surface","interactions":[],"lastModifiedDate":"2016-04-07T09:52:02","indexId":"70170064","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake rupture process recreated from a natural fault surface","docAbstract":"What exactly happens on the rupture surface as an earthquake nucleates, spreads, and stops? We cannot observe this directly, and models depend on assumptions about physical conditions and geometry at depth. We thus measure a natural fault surface and use its 3D coordinates to construct a replica at 0.1 m resolution to obviate geometry uncertainty. We can recreate stick-slip behavior on the resulting finite element model that depends solely on observed fault geometry. We clamp the fault together and apply steady state tectonic stress until seismic slip initiates and terminates. Our recreated M~1 earthquake initiates at contact points where there are steep surface gradients because infinitesimal lateral displacements reduce clamping stress most efficiently there. Unclamping enables accelerating slip to spread across the surface, but the fault soon jams up because its uneven, anisotropic shape begins to juxtapose new high-relief sticking points. These contacts would ultimately need to be sheared off or strongly deformed before another similar earthquake could occur. Our model shows that an important role is played by fault-wall geometry, though we do not include effects of varying fluid pressure or exotic rheologies on the fault surfaces. We extrapolate our results to large fault systems using observed self-similarity properties, and suggest that larger ruptures might begin and end in a similar way, though the scale of geometrical variation in fault shape that can arrest a rupture necessarily scales with magnitude. In other words, fault segmentation may be a magnitude dependent phenomenon and could vary with each subsequent rupture.
","language":"English","publisher":"AGU","doi":"10.1002/2015JB012448","usgsCitation":"Parsons, T.E., and Minasian, D.L., 2015, Earthquake rupture process recreated from a natural fault surface: Journal of Geophysical Research B: Solid Earth, v. 120, no. 11, p. 7852-7862, https://doi.org/10.1002/2015JB012448.","productDescription":"11 p.","startPage":"7852","endPage":"7862","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070265","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471683,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012448","text":"Publisher Index Page"},{"id":319884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-27","publicationStatus":"PW","scienceBaseUri":"572485f6e4b0b13d39159416","contributors":{"authors":[{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":625977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minasian, Diane L. dminasian@usgs.gov","contributorId":3232,"corporation":false,"usgs":true,"family":"Minasian","given":"Diane","email":"dminasian@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":626231,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159427,"text":"70159427 - 2015 - Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study","interactions":[],"lastModifiedDate":"2015-11-09T09:07:29","indexId":"70159427","displayToPublicDate":"2015-10-29T12:45:00","publicationYear":"2015","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":"Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study","docAbstract":"Recent improvements in online information communication and mobile location-aware technologies have led to the production of large volumes of volunteered geographic information. Widespread, large-scale efforts by volunteers to collect data can inform and drive scientific advances in diverse fields, including ecology and climatology. Traditional workflows to check the quality of such volunteered information can be costly and time consuming as they heavily rely on human interventions. However, identifying factors that can influence data quality, such as inconsistency, is crucial when these data are used in modeling and decision-making frameworks. Recently developed workflows use simple statistical approaches that assume that the majority of the information is consistent. However, this assumption is not generalizable, and ignores underlying geographic and environmental contextual variability that may explain apparent inconsistencies. Here we describe an automated workflow to check inconsistency based on the availability of contextual environmental information for sampling locations. The workflow consists of three steps: (1) dimensionality reduction to facilitate further analysis and interpretation of results, (2) model-based clustering to group observations according to their contextual conditions, and (3) identification of inconsistent observations within each cluster. The workflow was applied to volunteered observations of flowering in common and cloned lilac plants (Syringa vulgaris and Syringa x chinensis) in the United States for the period 1980 to 2013. About 97% of the observations for both common and cloned lilacs were flagged as consistent, indicating that volunteers provided reliable information for this case study. Relative to the original dataset, the exclusion of inconsistent observations changed the apparent rate of change in lilac bloom dates by two days per decade, indicating the importance of inconsistency checking as a key step in data quality assessment for volunteered geographic information. Initiatives that leverage volunteered geographic information can adapt this workflow to improve the quality of their datasets and the robustness of their scientific analyses.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0140811","usgsCitation":"Mehdipoor, H., Zurita-Milla, R., Rosemartin, A., Gerst, K., and Weltzin, J., 2015, Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study: PLoS ONE, v. 10, no. 10, e0140811: 14 p., https://doi.org/10.1371/journal.pone.0140811.","productDescription":"e0140811: 14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065123","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"links":[{"id":471696,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0140811","text":"Publisher Index Page"},{"id":310762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-20","publicationStatus":"PW","scienceBaseUri":"56333584e4b048076347ee9d","contributors":{"authors":[{"text":"Mehdipoor, Hamed","contributorId":146212,"corporation":false,"usgs":false,"family":"Mehdipoor","given":"Hamed","email":"","affiliations":[{"id":16630,"text":"Department of Geo-Information Processing, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":578558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zurita-Milla, Raul","contributorId":146213,"corporation":false,"usgs":false,"family":"Zurita-Milla","given":"Raul","email":"","affiliations":[{"id":16630,"text":"Department of Geo-Information Processing, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":578559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosemartin, Alyssa","contributorId":29766,"corporation":false,"usgs":true,"family":"Rosemartin","given":"Alyssa","affiliations":[],"preferred":false,"id":578560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerst, Katharine L.","contributorId":29739,"corporation":false,"usgs":true,"family":"Gerst","given":"Katharine L.","affiliations":[],"preferred":false,"id":578561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weltzin, Jake F. jweltzin@usgs.gov","contributorId":149476,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake F.","email":"jweltzin@usgs.gov","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":false,"id":578557,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70159437,"text":"70159437 - 2015 - Component-specific dynamics of riverine mangrove CO2 efflux in the Florida coastal Everglades","interactions":[],"lastModifiedDate":"2016-07-17T23:42:12","indexId":"70159437","displayToPublicDate":"2015-10-29T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Component-specific dynamics of riverine mangrove CO2 efflux in the Florida coastal Everglades","docAbstract":"Carbon cycling in mangrove forests represents a significant portion of the coastal wetland carbon (C) budget across the latitudes of the tropics and subtropics. Previous research suggests fluctuations in tidal inundation, temperature and salinity can influence forest metabolism and C cycling. Carbon dioxide (CO2) from respiration that occurs from below the canopy is contributed from different components. In this study, we investigated variation in CO2 flux among different below-canopy components (soil, leaf litter, course woody debris, soil including pneumatophores, prop roots, and surface water) in a riverine mangrove forest of Shark River Slough estuary, Everglades National Park (Florida, USA). The range in CO2 flux from different components exceeded that measured among sites along the oligohaline-saline gradient. Black mangrove (Avicennia germinans) pneumatophores contributed the largest average CO2 flux. Over a narrow range of estuarine salinity (25–35 practical salinity units (PSU)), increased salinity resulted in lower CO2 flux to the atmosphere. Tidal inundation reduced soil CO2 flux overall but increased the partial pressure of CO2 (pCO2) observed in the overlying surface water upon flooding. Higher pCO2 in surface water is then subject to tidally driven export, largely as HCO3. Integration and scaling of CO2 flux rates to forest scale allowed for improved understanding of the relative contribution of different below-canopy components to mangrove forest ecosystem respiration (ER). Summing component CO2fluxes suggests a more significant contribution of below-canopy respiration to ER than previously considered. An understanding of below-canopy CO2 component fluxes and their contributions to ER can help to elucidate how C cycling will change with discrete disturbance events (e.g., hurricanes) and long-term change, including sea-level rise, and potential impact mangrove forests. As such, key controls on below-canopy ER must be taken into consideration when developing and modeling mangrove forest C budgets.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2014.12.012","usgsCitation":"Troxler, T.G., Barr, J.G., Fuentes, J.D., Engel, V.C., Anderson, G.H., Sanchez, C., Lagomosino, D., Price, R., and Davis, S., 2015, Component-specific dynamics of riverine mangrove CO2 efflux in the Florida coastal Everglades: Agricultural and Forest Meteorology, v. 213, p. 273-282, https://doi.org/10.1016/j.agrformet.2014.12.012.","productDescription":"10 p.","startPage":"273","endPage":"282","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059705","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471698,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2014.12.012","text":"Publisher Index Page"},{"id":310747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Shark River Slough","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.8701171875,\n 24.886436490787688\n ],\n [\n -81.8701171875,\n 26.165298896316042\n ],\n [\n -80.00244140625,\n 26.165298896316042\n ],\n [\n -80.00244140625,\n 24.886436490787688\n ],\n [\n -81.8701171875,\n 24.886436490787688\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"213","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56333581e4b048076347ee97","contributors":{"authors":[{"text":"Troxler, Tiffany G.","contributorId":140212,"corporation":false,"usgs":false,"family":"Troxler","given":"Tiffany","email":"","middleInitial":"G.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":578646,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barr, Jordan G.","contributorId":85809,"corporation":false,"usgs":false,"family":"Barr","given":"Jordan","email":"","middleInitial":"G.","affiliations":[{"id":13531,"text":"South Florida Natural Resource Center, Everglades National Park","active":true,"usgs":false}],"preferred":false,"id":578647,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuentes, Jose D.","contributorId":97231,"corporation":false,"usgs":true,"family":"Fuentes","given":"Jose","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":578648,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engel, Victor C. 0000-0002-3858-7308 vengel@usgs.gov","orcid":"https://orcid.org/0000-0002-3858-7308","contributorId":2329,"corporation":false,"usgs":true,"family":"Engel","given":"Victor","email":"vengel@usgs.gov","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":578645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Gordon H. 0000-0003-1675-8329 gordon_anderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1675-8329","contributorId":2771,"corporation":false,"usgs":true,"family":"Anderson","given":"Gordon","email":"gordon_anderson@usgs.gov","middleInitial":"H.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":578649,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanchez, Christopher","contributorId":149511,"corporation":false,"usgs":false,"family":"Sanchez","given":"Christopher","email":"","affiliations":[{"id":17759,"text":"Univ. of Miami","active":true,"usgs":false}],"preferred":false,"id":578650,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lagomosino, David","contributorId":149512,"corporation":false,"usgs":false,"family":"Lagomosino","given":"David","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":578651,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Price, Rene","contributorId":149513,"corporation":false,"usgs":false,"family":"Price","given":"Rene","affiliations":[{"id":17760,"text":"Florida International Univ.","active":true,"usgs":false}],"preferred":false,"id":578652,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davis, Stephen E.","contributorId":73494,"corporation":false,"usgs":true,"family":"Davis","given":"Stephen E.","affiliations":[],"preferred":false,"id":578653,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ]}