Springs in Black Canyon of the Colorado River, directly south of Hoover Dam in the Lake Mead National Recreation Area, Nevada and Arizona, are important hydrologic features that support a unique riparian ecosystem including habitat for endangered species. Rapid population growth in areas near and surrounding Black Canyon has caused concern among resource managers that such growth could affect the discharge from these springs. The U.S. Geological Survey studied the springs in Black Canyon between January 2008, and May 2014. The purposes of this study were to provide a baseline of discharge and hydrochemical data from selected springs in Black Canyon and to better understand the sources of water to the springs.
\nVarious hydrologic, hydrochemical, geochemical, and geologic data were collected and analyzed during this study. More than 100 hydrologic sites consisting of springs, seeps, pools, rivers, reservoirs, and wells were investigated, and measurements were taken at 75 of these sites. Water levels were measured or compiled for 42 wells and samples of water were collected from 36 unique sites and submitted for laboratory analyses of hydrochemical constituents. Measurements of discrete discharge were made from nine unique spring areas and four sites in Black Canyon were selected for continuous monitoring of discharge. Additionally, samples of rock near Hoover Dam were collected and analyzed to determine the age of spring deposits.
\nResults of hydrochemical analyses indicate that discharge from springs in Black Canyon is from two sources: (1) Lake Mead, and (2) a local and (or) regional source. Discharge from springs closest to Hoover Dam contains a substantial percentage (>50 percent) of water from Lake Mead. This includes springs that are between Hoover Dam and Palm Tree Spring. Discharge from springs south of Palm Tree Spring contains a substantial percentage (>50 percent) of the water that is believed to come from a combination of other local and regional sources, although the exact location and nature of these sources is not clear. The unique hydrochemistry of some springs, such as Bighorn Sheep Spring and Latos Pool, suggests that little if any water discharging from these springs comes from Lake Mead. Geochronological results of spring deposits at several sites near Hoover Dam indicate that most deposits are young and likely formed after the construction of Hoover Dam.
\nSeveral major faults, including the Salt Cedar Fault and the Palm Tree Fault, play an important role in the movement of groundwater. Groundwater may move along these faults and discharge where faults intersect volcanic breccias or fractured rock. Vertical movement of groundwater along faults is suggested as a mechanism for the introduction of heat energy present in groundwater from many of the springs. Groundwater altitudes in the study area indicate a potential for flow from Eldorado Valley to Black Canyon although current interpretations of the geology of this area do not favor such flow. If groundwater from Eldorado Valley discharges at springs in Black Canyon then the development of groundwater resources in Eldorado Valley could result in a decrease in discharge from the springs. Geology and structure indicate that it is not likely that groundwater can move between Detrital Valley and Black Canyon. Thus, the development of groundwater resources in Detrital Valley may not result in a decrease in discharge from springs in Black Canyon.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155130","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Moran, M.J., Wilson, J.W., and Beard, L.S., 2015, Hydrogeology and sources of water to select springs in Black Canyon, south of Hoover Dam, Lake Mead National Recreation Area, Nevada and Arizona: U.S. Geological Survey Scientific Investigations Report 2015–5130, 61 p., https://dx.doi.org/10.3133/sir20155130.","productDescription":"Report: viii, 61 p.; 4 Appendixes","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060431","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":310988,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5130/coverthb.jpg"},{"id":310989,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5130"},{"id":310990,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixa.xlsx","text":"Appendix A","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix A"},{"id":310991,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixb.xlsx","text":"Appendix B","size":"32 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix B"},{"id":310992,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixc.xlsx","text":"Appendix C","size":"36 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix C"},{"id":310993,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5130/sir20155130_appendixd.xlsx","text":"Appendix D","size":"68 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5130 Appendix D"}],"country":"United States","state":"Arizona, Nevada","otherGeospatial":"Black Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.78790283203125,\n 35.8411948281412\n ],\n [\n -114.78790283203125,\n 36.058536144240506\n ],\n [\n -114.62928771972655,\n 36.058536144240506\n ],\n [\n -114.62928771972655,\n 35.8411948281412\n ],\n [\n -114.78790283203125,\n 35.8411948281412\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
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":70159473,"text":"70159473 - 2015 - Discovering loose group movement patterns from animal trajectories","interactions":[],"lastModifiedDate":"2017-07-26T17:13:13","indexId":"70159473","displayToPublicDate":"2015-11-03T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Discovering loose group movement patterns from animal trajectories","docAbstract":"The technical advances of positioning technologies enable us to track animal movements at finer spatial and temporal scales, and further help to discover a variety of complex interactive relationships. In this paper, considering the loose gathering characteristics of the real-life groups' members during the movements, we propose two kinds of loose group movement patterns and corresponding discovery algorithms. Firstly, we propose the weakly consistent group movement pattern which allows the gathering of a part of the members and individual temporary leave from the whole during the movements. To tolerate the high dispersion of the group at some moments (i.e. to adapt the discontinuity of the group's gatherings), we further scheme the weakly consistent and continuous group movement pattern. The extensive experimental analysis and comparison with the real and synthetic data shows that the group pattern discovery algorithms proposed in this paper are similar to the the real-life frequent divergences of the members during the movements, can discover more complete memberships, and have considerable performance.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"2015 IEEE 11th International Conference on e-Science","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"2015 IEEE 11th International Conference on e-Science","conferenceDate":"August 31, 2015","conferenceLocation":"Munich, Germany","language":"English","publisher":"IEEE","doi":"10.1109/eScience.2015.30","usgsCitation":"Wang, Y., Luo, Z., Xiong, Y., Prosser, D.J., Newman, S.H., Takekawa, J.Y., and Yan, B., 2015, Discovering loose group movement patterns from animal trajectories, in 2015 IEEE 11th International Conference on e-Science, Munich, Germany, August 31, 2015, p. 196-206, https://doi.org/10.1109/eScience.2015.30.","productDescription":"11 p.","startPage":"196","endPage":"206","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066587","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":310978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5639daffe4b0d6133fe732cc","contributors":{"authors":[{"text":"Wang, Yuwei","contributorId":149674,"corporation":false,"usgs":false,"family":"Wang","given":"Yuwei","email":"","affiliations":[],"preferred":false,"id":579119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luo, Ze","contributorId":41307,"corporation":false,"usgs":true,"family":"Luo","given":"Ze","affiliations":[],"preferred":false,"id":579120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xiong, Yan","contributorId":102764,"corporation":false,"usgs":true,"family":"Xiong","given":"Yan","email":"","affiliations":[],"preferred":false,"id":579121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":579117,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newman, Scott H.","contributorId":101372,"corporation":false,"usgs":true,"family":"Newman","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":579122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":579123,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yan, Baoping","contributorId":76871,"corporation":false,"usgs":true,"family":"Yan","given":"Baoping","affiliations":[],"preferred":false,"id":579124,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157227,"text":"ofr20151174 - 2015 - An overview of the National Earthquake Information Center acquisition software system, Edge/Continuous Waveform Buffer","interactions":[],"lastModifiedDate":"2015-11-03T09:08:39","indexId":"ofr20151174","displayToPublicDate":"2015-11-02T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1174","title":"An overview of the National Earthquake Information Center acquisition software system, Edge/Continuous Waveform Buffer","docAbstract":"This document provides an overview of the capabilities, design, and use cases of the data acquisition and archiving subsystem at the U.S. Geological Survey National Earthquake Information Center. The Edge and Continuous Waveform Buffer software supports the National Earthquake Information Center’s worldwide earthquake monitoring mission in direct station data acquisition, data import, short- and long-term data archiving, data distribution, query services, and playback, among other capabilities. The software design and architecture can be configured to support acquisition and (or) archiving use cases. The software continues to be developed in order to expand the acquisition, storage, and distribution capabilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151174","usgsCitation":"Patton, J.M., Ketchum, D.C., and Guy, M.R., 2015, An overview of the National Earthquake Information Center acquisition software system, Edge/Continuous Waveform Buffer: U.S. Geological Survey Open-File Report 2015–1174, 10 p., https://dx.doi.org/10.3133/ofr20151174.","productDescription":"iv, 10 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067426","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":310780,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1174/ofr20151174.pdf","text":"Report","size":"688 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1174"},{"id":310779,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1174/coverthb.jpg"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS–966
Denver, CO 80225-0046
http://geohazards.cr.usgs.gov/
In this study, the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, quantified the potential for landward migration of tidal saline wetlands along the U.S. Gulf of Mexico coast under alternative future sea-level rise and urbanization scenarios. Our analyses focused exclusively on tidal saline wetlands (that is, mangrove forests, salt marshes, and salt flats), and we combined these diverse tidal saline wetland ecosystems into a single grouping, “tidal saline wetland.” Collectively, our approach and findings can provide useful information for scientists and environmental planners working to develop future-focused adaptation strategies for conserving coastal landscapes and the ecosystem goods and services provided by tidal saline wetlands. The primary product of this work is a public dataset that identifies locations where landward migration of tidal saline wetlands is expected to occur under alternative future sea-level rise and urbanization scenarios. In addition to identifying areas where landward migration of tidal saline wetlands is possible because of the absence of barriers, these data also identify locations where landward migration of these wetlands could be prevented by barriers associated with current urbanization, future urbanization, and levees.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds969","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Enwright, N.M., Griffith, K.T., and Osland, M.J., 2015, Incorporating future change into current conservation planning—Evaluating tidal saline wetland migration along the U.S. Gulf of Mexico coast under alternative sea-level rise and urbanization scenarios: U.S. Geological Survey Data Series 969, https://dx.doi.org/10.3133/ds969.","productDescription":"HTML Document; Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069118","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":310970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":310664,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0969/ds969.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 969 HTML"},{"id":310665,"rank":2,"type":{"id":28,"text":"Dataset"},"url":"https://www.sciencebase.gov/catalog/item/55f742a8e4b0477df11c0a2b","text":"Dataset"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.44873046875,\n 25.859223554761407\n ],\n [\n -97.75634765625,\n 27.293689224852407\n ],\n [\n -97.0751953125,\n 28.555576049185973\n ],\n [\n -94.04296874999999,\n 30.012030680358613\n ],\n [\n -92.4169921875,\n 30.012030680358613\n ],\n [\n -90.24169921875,\n 29.821582720575016\n ],\n [\n -89.53857421875,\n 30.524413269923986\n ],\n [\n -85.869140625,\n 30.637912028341123\n ],\n [\n -85.0341796875,\n 30.012030680358613\n ],\n [\n -83.8916015625,\n 30.4297295750316\n ],\n [\n -82.37548828125,\n 29.113775395114416\n ],\n [\n -82.28759765625,\n 27.371767300523047\n ],\n [\n -80.7275390625,\n 25.383735254706867\n ],\n [\n -80.9033203125,\n 24.806681353851964\n ],\n [\n -83.14453125,\n 27.293689224852407\n ],\n [\n -83.056640625,\n 28.767659105691255\n ],\n [\n -84.24316406249999,\n 29.84064389983441\n ],\n [\n -85.23193359375,\n 29.267232865200878\n ],\n [\n -86.59423828125,\n 30.164126343161097\n ],\n [\n -89.01123046875,\n 29.897805610155874\n ],\n [\n -89.01123046875,\n 28.94086176940557\n ],\n [\n -92.52685546875,\n 29.209713225868185\n ],\n [\n -94.04296874999999,\n 29.420460341013133\n ],\n [\n -96.85546875,\n 27.68352808378776\n ],\n [\n -96.96533203125,\n 25.93828707492375\n ],\n [\n -97.44873046875,\n 25.859223554761407\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
http://www.nwrc.usgs.gov/
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":70169238,"text":"70169238 - 2015 - A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback","interactions":[],"lastModifiedDate":"2016-03-24T11:53:16","indexId":"70169238","displayToPublicDate":"2015-11-01T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3047,"text":"Philosophical Transactions of 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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H.","contributorId":167817,"corporation":false,"usgs":false,"family":"MacDougall","given":"A.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":623647,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Marchenko, Sergey S.","contributorId":93368,"corporation":false,"usgs":true,"family":"Marchenko","given":"Sergey S.","affiliations":[],"preferred":false,"id":623648,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"McGuire, A. 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.
","language":"English","publisher":"Macmillan Journals Ltd.","publisherLocation":"London, UK","doi":"10.1038/nature15538","usgsCitation":"Lovelock, C.E., Cahoon, D.R., Friess, D., Guntenspergen, G.R., Krauss, K.W., Reef, R., Rogers, K., Saunders, M.L., Sidik, F., Swales, A., Saintilan, N., Thuyen, L.X., and Triet, T., 2015, The vulnerability of Indo-Pacific mangrove forests to sea-level rise: Nature, v. 526, no. 7574, p. 559-563, https://doi.org/10.1038/nature15538.","productDescription":"5 p.","startPage":"559","endPage":"563","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065063","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488708,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Aluminosilicate melts and glasses at 1 to 3 GPa: Temperature and pressure effects on recovered structural and density changes","docAbstract":"In the pressure range in the Earth’s mantle where many basaltic magmas are generated (1 to 3 GPa) (Stolper et al. 1981), increases in the coordination numbers of the network-forming cations in aluminosilicate melts have generally been considered to be minor, although effects on silicon and particularly on aluminum coordination in non-bridging oxygen-rich glasses from the higher, 5 to 12 GPa range, are now well known. Most high-precision measurements of network cation coordination in such samples have been made by spectroscopy (notably 27Al and 29Si NMR) on glasses quenched from high-temperature, high-pressure melts synthesized in solid-media apparatuses and decompressed to room temperature and 1 bar pressure. There are several effects that could lead to the underestimation of the extent of actual structural (and density) changes in high-pressure/temperature melts from such data. For non-bridging oxygen-rich sodium and calcium aluminosilicate compositions in the 1 to 3 GPa range, we show here that glasses annealed near to their glass transition temperatures systematically record higher recovered increases in aluminum coordination and in density than samples quenched from high-temperature melts. In the piston-cylinder apparatus used, rates of cooling through the glass transition are measured as very similar for both higher and lower initial temperatures, indicating that fictive temperature effects are not the likely explanation of these differences. Instead, transient decreases in melt pressure during thermal quenching, which may be especially large for high initial run temperatures, of as much as 0.5 to 1 GPa, may be responsible. As a result, the equilibrium proportion of high-coordinated Al in this pressure range may be 50 to 90% greater than previously estimated, reaching mean coordination numbers (e.g., 4.5) that are probably high enough to significantly affect melt properties. New data on jadeite (NaAlSi2O6) glass confirm that aluminum coordination increase with pressure is inhibited in compositions low in non-bridging O atoms.
","language":"English","publisher":"Mineralogical Society of America","publisherLocation":"Washington, D.C.","usgsCitation":"Bista, S., Stebbins, J., Hankins, W.B., and Sisson, T.W., 2015, Aluminosilicate melts and glasses at 1 to 3 GPa: Temperature and pressure effects on recovered structural and density changes: American Mineralogist, v. 100, p. 2298-2307.","productDescription":"10 p.","startPage":"2298","endPage":"2307","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063165","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":311676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311675,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.minsocam.org/msa/ammin/toc/2015/index.html?issue_number=10"}],"volume":"100","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56559839e4b071e7ea53def4","contributors":{"authors":[{"text":"Bista, S","contributorId":146238,"corporation":false,"usgs":false,"family":"Bista","given":"S","email":"","affiliations":[{"id":6705,"text":"Stanford Synchrotron Radiation Lightsource, Menlo Park CA","active":true,"usgs":false}],"preferred":false,"id":566716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stebbins, Jonathan","contributorId":146239,"corporation":false,"usgs":false,"family":"Stebbins","given":"Jonathan","email":"","affiliations":[{"id":6705,"text":"Stanford Synchrotron Radiation Lightsource, Menlo Park CA","active":true,"usgs":false}],"preferred":false,"id":566717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hankins, William B. 0000-0001-9881-9468 bhankins@usgs.gov","orcid":"https://orcid.org/0000-0001-9881-9468","contributorId":5326,"corporation":false,"usgs":true,"family":"Hankins","given":"William","email":"bhankins@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":566718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sisson, Thomas W. 0000-0003-3380-6425 tsisson@usgs.gov","orcid":"https://orcid.org/0000-0003-3380-6425","contributorId":2341,"corporation":false,"usgs":true,"family":"Sisson","given":"Thomas","email":"tsisson@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":566715,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186009,"text":"70186009 - 2015 - LIMS for Lasers 2015 for achieving long-term accuracy and precision of δ2H, δ17O, and δ18O of waters using laser absorption spectrometry","interactions":[],"lastModifiedDate":"2021-04-27T18:27:34.728232","indexId":"70186009","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3233,"text":"Rapid Communications in Mass Spectrometry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"LIMS for Lasers 2015 for achieving long-term accuracy and precision of δ2H, δ17O, and δ18O of waters using laser absorption spectrometry","title":"LIMS for Lasers 2015 for achieving long-term accuracy and precision of δ2H, δ17O, and δ18O of waters using laser absorption spectrometry","docAbstract":"Rationale
Although laser absorption spectrometry (LAS) instrumentation is easy to use, its incorporation into laboratory operations is not easy, owing to extensive offline manipulation of comma-separated-values files for outlier detection, between-sample memory correction, nonlinearity (δ-variation with water amount) correction, drift correction, normalization to VSMOW-SLAP scales, and difficulty in performing long-term QA/QC audits.
Methods
A Microsoft Access relational-database application, LIMS (Laboratory Information Management System) for Lasers 2015, was developed. It automates LAS data corrections and manages clients, projects, samples, instrument-sample lists, and triple-isotope (δ17O, δ18O, and δ2H values) instrumental data for liquid-water samples. It enables users to (1) graphically evaluate sample injections for variable water yields and high isotope-delta variance; (2) correct for between-sample carryover, instrumental drift, and δ nonlinearity; and (3) normalize final results to VSMOW-SLAP scales.
Results
Cost-free LIMS for Lasers 2015 enables users to obtain improved δ17O, δ18O, and δ2H values with liquid-water LAS instruments, even those with under-performing syringes. For example, LAS δ2HVSMOW measurements of USGS50 Lake Kyoga (Uganda) water using an under-performing syringe having ±10 % variation in water concentration gave +31.7 ± 1.6 ‰ (2-σ standard deviation), compared with the reference value of +32.8 ± 0.4 ‰, after correction for variation in δ value with water concentration, between-sample memory, and normalization to the VSMOW-SLAP scale.
Conclusions
LIMS for Lasers 2015 enables users to create systematic, well-founded instrument templates, import δ2H, δ17O, and δ18O results, evaluate performance with automatic graphical plots, correct for δ nonlinearity due to variable water concentration, correct for between-sample memory, adjust for drift, perform VSMOW-SLAP normalization, and perform long-term QA/QC audits easily. Published in 2015. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/rcm.7372","usgsCitation":"Coplen, T.B., and Wassenaar, L.I., 2015, LIMS for Lasers 2015 for achieving long-term accuracy and precision of δ2H, δ17O, and δ18O of waters using laser absorption spectrometry: Rapid Communications in Mass Spectrometry, v. 29, no. 22, p. 2122-2130, https://doi.org/10.1002/rcm.7372.","productDescription":"9 p.","startPage":"2122","endPage":"2130","ipdsId":"IP-052265","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":338849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-13","publicationStatus":"PW","scienceBaseUri":"58de1950e4b02ff32c699ca9","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":687333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wassenaar, Leonard I","contributorId":150277,"corporation":false,"usgs":false,"family":"Wassenaar","given":"Leonard","email":"","middleInitial":"I","affiliations":[{"id":17954,"text":"International Atomic Energy Agency, Vienna, Austria","active":true,"usgs":false}],"preferred":false,"id":687334,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":70160049,"text":"70160049 - 2015 - The surface elevation table and marker horizon technique: A protocol for monitoring wetland elevation dynamics","interactions":[],"lastModifiedDate":"2019-07-01T12:08:34","indexId":"70160049","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NCBN/NRR—2015/1078","title":"The surface elevation table and marker horizon technique: A protocol for monitoring wetland elevation dynamics","docAbstract":"The National Park Service, in response to the growing evidence and awareness of the effects of climate change on federal lands, determined that monitoring wetland elevation change is a top priority in North Atlantic Coastal parks (Stevens et al, 2010). As a result, the NPS Northeast Coastal and Barrier Network (NCBN) in collaboration with colleagues from the U.S. Geological Survey (USGS) and The National Oceanic and Atmospheric Administration (NOAA) have developed a protocol for monitoring wetland elevation change and other processes important for determining the viability of wetland communities. Although focused on North Atlantic Coastal parks, this document is applicable to all coastal and inland wetland regions. Wetlands exist within a narrow range of elevation which is influenced by local hydrologic conditions. For coastal wetlands in particular, local hydrologic conditions may be changing as sea levels continue to rise. As sea level rises, coastal wetland systems may respond by building elevation to maintain favorable hydrologic conditions for their survival. This protocol provides the reader with instructions and guidelines on designing a monitoring plan or study to: A) Quantify elevation change in wetlands with the Surface Elevation Table (SET). B) Understand the processes that influence elevation change, including vertical accretion (SET and Marker Horizon methods). C) Survey the wetland surface and SET mark to a common reference datum to allow for comparing sample stations to each other and to local tidal datums. D) Survey the SET mark to monitor its relative stability. This document is divided into two parts; the main body that presents an overview of all aspects of monitoring wetland elevation dynamics, and a collection of Standard Operating Procedures (SOP) that describes in detail how to perform or execute each step of the methodology. Detailed instruction on the installation, data collection, data management and analysis are provided in this report and associated SOP’s. A better understanding of these processes will help to determine the present and future viability of coastal wetlands managed by NPS and can help address measures that will ensure these communities exist into the future.
","language":"English","publisher":"National Park Service","collaboration":"National Park Service; National Oceanic and Atmospheric Administration","usgsCitation":"James C. Lynch, Hensel, P., and Cahoon, D.R., 2015, The surface elevation table and marker horizon technique: A protocol for monitoring wetland elevation dynamics: Natural Resource Report NPS/NCBN/NRR—2015/1078, xviii., 62 p., SOP 1-1-10-3.","productDescription":"xviii., 62 p., SOP 1-1-10-3","ipdsId":"IP-070057","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":328459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365251,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2225005"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d3dd3de4b0571647d19adf","contributors":{"authors":[{"text":"James C. Lynch","contributorId":150450,"corporation":false,"usgs":false,"family":"James C. Lynch","affiliations":[{"id":13367,"text":"National Parks Service","active":true,"usgs":false}],"preferred":false,"id":581715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hensel, Phillippe","contributorId":150451,"corporation":false,"usgs":false,"family":"Hensel","given":"Phillippe","email":"","affiliations":[{"id":13367,"text":"National Parks Service","active":true,"usgs":false}],"preferred":false,"id":581716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":581714,"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":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":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"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":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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":687786,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192848,"text":"70192848 - 2015 - The Open Water Data Initiative: Water information for a thirsty nation","interactions":[],"lastModifiedDate":"2017-11-21T15:34:15","indexId":"70192848","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3720,"text":"Water Resources Impact","printIssn":"1522-3175","active":true,"publicationSubtype":{"id":10}},"title":"The Open Water Data Initiative: Water information for a thirsty nation","docAbstract":"Initial efforts of the Open Water Data Initiative have focused on three use cases covering flooding, drought, and contaminant spill response, with a goal of identifying critical water data resources and making them more accessible. Significant progress has been made in the past year, although much remains to be done.
","language":"English","publisher":"AWRA","usgsCitation":"Rea, A., Clark, E., Adams, A., and Samuels, W.B., 2015, The Open Water Data Initiative: Water information for a thirsty nation: Water Resources Impact, v. 17, no. 6, p. 7-10.","productDescription":"4 p.","startPage":"7","endPage":"10","ipdsId":"IP-068712","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":349236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fe57e4b06e28e9c252ea","contributors":{"authors":[{"text":"Rea, Alan ahrea@usgs.gov","contributorId":198813,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","email":"ahrea@usgs.gov","affiliations":[],"preferred":false,"id":717186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Edward","contributorId":198814,"corporation":false,"usgs":false,"family":"Clark","given":"Edward","email":"","affiliations":[],"preferred":false,"id":717188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Angela","contributorId":198815,"corporation":false,"usgs":false,"family":"Adams","given":"Angela","email":"","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":717189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Samuels, William B.","contributorId":198816,"corporation":false,"usgs":false,"family":"Samuels","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":717190,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70147802,"text":"70147802 - 2015 - Landsat Science Team meeting: Winter 2015","interactions":[],"lastModifiedDate":"2017-04-21T15:47:52","indexId":"70147802","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3555,"text":"The Earth Observer","active":true,"publicationSubtype":{"id":10}},"title":"Landsat Science Team meeting: Winter 2015","docAbstract":"The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023.
With over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at landsat.usgs.gov/science_LST_Team_ Meetings.php.
","language":"English","publisher":"NASA","usgsCitation":"Schroeder, T.A., Loveland, T., Wulder, M.A., and Irons, J.R., 2015, Landsat Science Team meeting: Winter 2015: The Earth Observer, v. 27, no. 6, p. 12-17.","productDescription":"6 p.","startPage":"12","endPage":"17","ipdsId":"IP-065489","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":340094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340093,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://eospso.nasa.gov/sites/default/files/eo_pdfs/Nov%20Dec%202015_508_col.pdf"}],"volume":"27","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58fb1a4ee4b0c3010a8087d1","contributors":{"authors":[{"text":"Schroeder, Todd A. taschroeder@fs.fed.us","contributorId":190802,"corporation":false,"usgs":false,"family":"Schroeder","given":"Todd","email":"taschroeder@fs.fed.us","middleInitial":"A.","affiliations":[],"preferred":false,"id":692438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":546324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wulder, Michael A.","contributorId":103584,"corporation":false,"usgs":true,"family":"Wulder","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":546325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irons, James R.","contributorId":59284,"corporation":false,"usgs":false,"family":"Irons","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":546326,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158955,"text":"70158955 - 2015 - Landsat science team meeting: Summer 2015","interactions":[],"lastModifiedDate":"2017-01-18T09:56:24","indexId":"70158955","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3555,"text":"The Earth Observer","active":true,"publicationSubtype":{"id":10}},"title":"Landsat science team meeting: Summer 2015","docAbstract":"The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023.
\nWith over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at landsat.usgs.gov/science_LST_Team_ Meetings.php.
","language":"English","publisher":"NASA","usgsCitation":"Schroeder, T., Loveland, T., Wulder, M.A., and Irons, J.R., 2015, Landsat science team meeting: Summer 2015: The Earth Observer, v. 27, no. 6, p. 12-17.","productDescription":"6 p.","startPage":"12","endPage":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068875","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":324704,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://eospso.nasa.gov/sites/default/files/eo_pdfs/Nov%20Dec%202015_508_col.pdf"},{"id":324705,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57779432e4b07dd077c905f2","contributors":{"authors":[{"text":"Schroeder, Todd tschroeder@usgs.gov","contributorId":149137,"corporation":false,"usgs":true,"family":"Schroeder","given":"Todd","email":"tschroeder@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":577035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":577036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wulder, Michael A.","contributorId":103584,"corporation":false,"usgs":true,"family":"Wulder","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":577037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irons, James R.","contributorId":59284,"corporation":false,"usgs":false,"family":"Irons","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":577038,"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.
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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":70159630,"text":"70159630 - 2015 - Remote sensing to monitor cover crop adoption in southeastern Pennsylvania","interactions":[],"lastModifiedDate":"2015-11-13T16:07:41","indexId":"70159630","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing to monitor cover crop adoption in southeastern Pennsylvania","docAbstract":"In the Chesapeake Bay Watershed, winter cereal cover crops are often planted in rotation with summer crops to reduce the loss of nutrients and sediment from agricultural systems. Cover crops can also improve soil health, control weeds and pests, supplement forage needs, and support resilient cropping systems. In southeastern Pennsylvania, cover crops can be successfully established following corn (Zea mays L.) silage harvest and are strongly promoted for use in this niche. They are also planted following corn grain, soybean (Glycine max L.), and vegetable harvest. In Pennsylvania, the use of winter cover crops for agricultural conservation has been supported through a combination of outreach, regulation, and incentives. On-farm implementation is thought to be increasing, but the actual extent of cover crops is not well quantified. Satellite imagery can be used to map green winter cover crop vegetation on agricultural fields and, when integrated with additional remote sensing data products, can be used to evaluate wintertime vegetative groundcover following specific summer crops. This study used Landsat and SPOT (System Probatoire d’ Observation de la Terre) satellite imagery, in combination with the USDA National Agricultural Statistics Service Cropland Data Layer, to evaluate the extent and amount of green wintertime vegetation on agricultural fields in four Pennsylvania counties (Berks, Lebanon, Lancaster, and York) from 2010 to 2013. In December of 2010, a windshield survey was conducted to collect baseline data on winter cover crop implementation, with particular focus on identifying corn harvested for silage (expected earlier harvest date and lower levels of crop residue), versus for grain (expected later harvest date and higher levels of crop residue). Satellite spectral indices were successfully used to detect both the amount of green vegetative groundcover and the amount of crop residue on the surveyed fields. Analysis of wintertime satellite imagery showed consistent increases in vegetative groundcover over the four-year study period and determined that trends did not result from annual weather variability, indicating that farmers are increasing adoption of practices such as cover cropping that promote wintertime vegetation. Between 2010 and 2013, the occurrence of wintertime vegetation on agricultural fields increased from 36% to 67% of corn fields in Berks County, from 53% to 75% in Lancaster County, from 42% to 65% in Lebanon County, and from 26% to 52% in York County. Apparently, efforts to promote cover crop use in the Chesapeake Bay Watershed have coincided with a rapid increase in the occurrence of wintertime vegetation following corn harvest in southeastern Pennsylvania. However, despite these increases, between 25% and 48% of corn fields remained without substantial green vegetation over the wintertime, indicating further opportunity for cover crop adoption.
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.70.6.340","usgsCitation":"Hively, W., Duiker, S., Greg McCarty, and Prabhakara, K., 2015, Remote sensing to monitor cover crop adoption in southeastern Pennsylvania: Journal of Soil and Water Conservation, v. 70, no. 6, p. 340-352, https://doi.org/10.2489/jswc.70.6.340.","productDescription":"13 p.","startPage":"340","endPage":"352","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061440","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2489/jswc.70.6.340","text":"Publisher Index Page"},{"id":311303,"type":{"id":15,"text":"Index Page"},"url":"https://www.jswconline.org/content/70/6/340.full.pdf"},{"id":311321,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Southeastern and Central Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.2176513671875,\n 39.73253798438173\n ],\n [\n -76.48681640625,\n 40.0360265298117\n ],\n [\n -76.22314453125,\n 40.12429084831405\n ],\n [\n -76.3275146484375,\n 40.32141999593439\n ],\n [\n -76.08032226562499,\n 40.35073056591789\n ],\n [\n -76.08032226562499,\n 40.32560799973207\n ],\n [\n -75.78369140625,\n 40.41767833585551\n ],\n [\n -75.5474853515625,\n 40.27533480732468\n ],\n [\n -75.860595703125,\n 39.757879992021756\n ],\n [\n -75.8660888671875,\n 39.72831341029745\n ],\n [\n -76.2176513671875,\n 39.73253798438173\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.9754638671875,\n 41.31907562295136\n ],\n [\n -77.9425048828125,\n 40.61812224225511\n ],\n [\n -77.0306396484375,\n 40.6723059714534\n ],\n [\n -77.0965576171875,\n 41.36031866306708\n ],\n [\n -77.9754638671875,\n 41.31907562295136\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"70","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-06","publicationStatus":"PW","scienceBaseUri":"564717d7e4b0e2669b313129","contributors":{"authors":[{"text":"Hively, Wells whively@usgs.gov","contributorId":149843,"corporation":false,"usgs":true,"family":"Hively","given":"Wells","email":"whively@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":579787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duiker, Sjoerd","contributorId":149844,"corporation":false,"usgs":false,"family":"Duiker","given":"Sjoerd","email":"","affiliations":[{"id":17838,"text":"Dep. of Crop and Soil Sciences, The Pennsylvania State University, 116 ASI Building, University Park, PA 16802-3504","active":true,"usgs":false}],"preferred":false,"id":579788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greg McCarty","contributorId":149845,"corporation":false,"usgs":false,"family":"Greg McCarty","affiliations":[{"id":17839,"text":"USDA-Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Building 007 Room 104 BARC-West, 10300 Baltimore Avenue, Beltsville, MD","active":true,"usgs":false}],"preferred":false,"id":579789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prabhakara, Kusuma","contributorId":6313,"corporation":false,"usgs":true,"family":"Prabhakara","given":"Kusuma","email":"","affiliations":[],"preferred":false,"id":579790,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178692,"text":"70178692 - 2015 - Trends in publications in fluvial geomorphology over two decades: A truly new era in the discipline owing to recent technological revolution?","interactions":[],"lastModifiedDate":"2016-12-05T10:33:16","indexId":"70178692","displayToPublicDate":"2015-11-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Trends in publications in fluvial geomorphology over two decades: A truly new era in the discipline owing to recent technological revolution?","docAbstract":"Trends in the field of fluvial geomorphology have been reviewed by a number of authors, who have emphasized the dramatic change occuring in the field in the last two decades of the twentieth century, largely as a result of technological advances. Nevertheless, no prior authors have systematically compiled data on publications in fluvial geomorphology over a long period and statistically analyzed the resulting data set. In this contribution we present a quantitative analysis of fluvial geomorphology papers published in the twenty-two-year period 1987–2009 in five journals of the discipline with a more specific focus on Geomorphology and Earth Surface Processes and Landforms (ESPL), identifying authorships, geographic origin of authors, and spatial and temporal scales covered. We also documented the tools employed, demonstrating the transformation of the field with the emergence of new tools over this period, and conducted a cluster to highlight links between tools and a set of factors (country of author's origin, journals, time, and spatial and temporal scales). Of the 1717 papers published in the five journals during this period, the results showed an increased diversity in the nationality of the first author, mainly when dealing with present time scale, and channel feature. Our data show a significant change in methods used in the field as a result of the increase in data availability and new sources of information from remote sensing (ground, airborne and, satellite). Clearly, a new era in knowledge production is observed since 2000, showing the emergence of a second period of active quantification and an internationalization of the fields.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2015.07.039","usgsCitation":"Piégay, H., Kondolf, G.M., Minear, J., and Vaudor, L., 2015, Trends in publications in fluvial geomorphology over two decades: A truly new era in the discipline owing to recent technological revolution?: Geomorphology, v. 248, p. 489-500, https://doi.org/10.1016/j.geomorph.2015.07.039.","productDescription":"12 p.","startPage":"489","endPage":"500","ipdsId":"IP-064788","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":331453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"248","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58468aeae4b04fc80e5236c9","contributors":{"authors":[{"text":"Piégay, Hervé","contributorId":147605,"corporation":false,"usgs":false,"family":"Piégay","given":"Hervé","affiliations":[],"preferred":false,"id":654826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kondolf, G. Mathias","contributorId":146516,"corporation":false,"usgs":false,"family":"Kondolf","given":"G.","email":"","middleInitial":"Mathias","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":654827,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minear, J. Toby","contributorId":9938,"corporation":false,"usgs":true,"family":"Minear","given":"J. Toby","affiliations":[],"preferred":false,"id":654825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vaudor, Lise","contributorId":177159,"corporation":false,"usgs":false,"family":"Vaudor","given":"Lise","email":"","affiliations":[],"preferred":false,"id":654828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"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":70156184,"text":"sir20155115 - 2015 - Hydrology of and Current Monitoring Issues for the Chicago Area Waterway System, Northeastern Illinois","interactions":[],"lastModifiedDate":"2015-12-17T07:36:24","indexId":"sir20155115","displayToPublicDate":"2015-10-28T09:45:00","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":"2015-5115","title":"Hydrology of and Current Monitoring Issues for the Chicago Area Waterway System, Northeastern Illinois","docAbstract":"The Chicago Area Waterway System (CAWS) consists of a combination of natural and manmade channels that form an interconnected navigable waterway of approximately 90-plus miles in the metropolitan Chicago area of northeastern Illinois. The CAWS serves the area as the primary drainage feature, a waterway transportation corridor, and recreational waterbody. The CAWS was constructed by the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC). Completion of the Chicago Sanitary and Ship Canal (initial portion of the CAWS) in 1900 breached a low drainage divide and resulted in a diversion of water from the Lake Michigan Basin. A U.S. Supreme Court decree (Consent Decree 388 U.S. 426 [1967] Modified 449 U.S. 48 [1980]) limits the annual diversion from Lake Michigan. While the State of Illinois is responsible for the diversion, the MWRDGC regulates and maintains water level and water quality within the CAWS by using several waterway control structures. The operation and control of water levels in the CAWS results in a very complex hydraulic setting characterized by highly unsteady flows. The complexity leads to unique gaging requirements and monitoring issues. This report provides a general discussion of the complex hydraulic setting within the CAWS and quantifies this information with examples of data collected at a range of flow conditions from U.S. Geological Survey streamflow gaging stations and other locations within the CAWS. Monitoring to address longstanding issues of waterway operation, as well as current (2014) emerging issues such as wastewater disinfection and the threat from aquatic invasive species, is included in the discussion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155115","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency– Great Lakes Restoration Initiative","usgsCitation":"Duncker, J.J. and Johnson, K.K., 2015, Hydrology of and current monitoring issues for the Chicago Area Waterway\nSystem, northeastern Illinois: U.S. Geological Survey Scientific Investigations Report 2015–5115, 48 p., https://dx.doi.\norg/10.3133/sir20155115.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-038442","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":310678,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5115/sir20155115.pdf","text":"Report","size":"9.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5115"},{"id":310677,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5115/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Chicago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.099365234375,\n 41.57847058443442\n ],\n [\n -88.099365234375,\n 42.18579390537848\n ],\n [\n -87.47039794921874,\n 42.18579390537848\n ],\n [\n -87.47039794921874,\n 41.57847058443442\n ],\n [\n -88.099365234375,\n 41.57847058443442\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N. Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov/
The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects – as well as the continued development of common methodologies and protocols for sensor use – will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013–5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En
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