Oxygen, hydrogen, sulfur, and carbon isotopes have been analyzed in the Pea Ridge magnetite-apatite deposit, the largest historic producer among the known iron deposits in the southeast Missouri portion of the 1.5 to 1.3 Ga eastern granite-rhyolite province. The data were collected to investigate the sources of ore fluids, conditions of ore formation, and provenance of sulfur, and to improve the general understanding of the copper, gold, and rare earth element potential of iron deposits regionally. The δ18O values of Pea Ridge magnetite are 1.9 to 4.0‰, consistent with a model in which some magnetite crystallized from a melt and other magnetite—perhaps the majority—precipitated from an aqueous fluid of magmatic origin. The δ18O values of quartz, apatite, actinolite, K-feldspar, sulfates, and calcite are significantly higher, enough so as to indicate growth or equilibration under cooler conditions than magnetite and/or in the presence of a fluid that was not entirely magmatic. A variety of observations, including stable isotope observations, implicate a second fluid that may ultimately have been meteoric in origin and may have been modified by isotopic exchange with rocks or by evaporation during storage in lakes.
Sulfur isotope analyses of sulfides from Pea Ridge and seven other mineral deposits in the region reveal two distinct populations that average 3 and 13‰. Two sulfur sources are implied. One was probably igneous melts or rocks belonging to the mafic- to intermediate-composition volcanic suite that is present at or near most of the iron deposits; the other was either melts or volcanic rocks that had degassed very extensively, or else volcanic lakes that had trapped rising magmatic gases. The higher δ34S values correspond to deposits or prospects where copper is noteworthy—the Central Dome portion of the Boss deposit, the Bourbon deposit, and the Vilander prospective area. The correspondence suggests that (1) sulfur either limited the deposition of copper or was cotransported with copper, and (2) sulfur isotope analysis may be useful in evaluating southeast Missouri iron deposits for copper and possibly for gold.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.2017","usgsCitation":"Johnson, C.A., Day, W.C., and Rye, R.O., 2016, Oxygen, hydrogen, sulfur, and carbon isotopes in the Pea Ridge magnetite-apatite deposit, southeast Missouri, and sulfur isotope comparisons to other iron deposits in the region: Economic Geology, v. 111, no. 8, p. 2017-2032, https://doi.org/10.2113/econgeo.111.8.2017.","productDescription":"16 p.","startPage":"2017","endPage":"2032","ipdsId":"IP-069800","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":331639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","volume":"111","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58492df2e4b06d80b7b093a0","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":655119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rye, Robert O. rrye@usgs.gov","contributorId":1486,"corporation":false,"usgs":true,"family":"Rye","given":"Robert","email":"rrye@usgs.gov","middleInitial":"O.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655120,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184485,"text":"70184485 - 2016 - New organic reference materials for hydrogen, carbon, and nitrogen stable isotope-ratio measurements: caffeines, n-alkanes, fatty acid methyl esters, glycines, L-valines, polyethylenes, and oils","interactions":[],"lastModifiedDate":"2017-03-10T10:18:34","indexId":"70184485","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":761,"text":"Analytical Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"New organic reference materials for hydrogen, carbon, and nitrogen stable isotope-ratio measurements: caffeines, n-alkanes, fatty acid methyl esters, glycines, L-valines, polyethylenes, and oils","docAbstract":"An international project developed, quality-tested, and determined isotope−δ values of 19 new organic reference materials (RMs) for hydrogen, carbon, and nitrogen stable isotope-ratio measurements, in addition to analyzing pre-existing RMs NBS 22 (oil), IAEA-CH-7 (polyethylene foil), and IAEA-600 (caffeine). These new RMs enable users to normalize measurements of samples to isotope−δ scales. The RMs span a range of δ2HVSMOW-SLAP values from −210.8 to +397.0 mUr or ‰, for δ13CVPDB-LSVEC from −40.81 to +0.49 mUr and for δ15NAir from −5.21 to +61.53 mUr. Many of the new RMs are amenable to gas and liquid chromatography. The RMs include triads of isotopically contrasting caffeines, C16 n-alkanes, n-C20-fatty acid methyl esters (FAMEs), glycines, and l-valines, together with polyethylene powder and string, one n-C17-FAME, a vacuum oil (NBS 22a) to replace NBS 22 oil, and a 2H-enriched vacuum oil. A total of 11 laboratories from 7 countries used multiple analytical approaches and instrumentation for 2-point isotopic normalization against international primary measurement standards. The use of reference waters in silver tubes allowed direct normalization of δ2H values of organic materials against isotopic reference waters following the principle of identical treatment. Bayesian statistical analysis yielded the mean values reported here. New RMs are numbered from USGS61 through USGS78, in addition to NBS 22a. Because of exchangeable hydrogen, amino acid RMs currently are recommended only for carbon- and nitrogen-isotope measurements. Some amino acids contain 13C and carbon-bound organic 2H-enrichments at different molecular sites to provide RMs for potential site-specific isotopic analysis in future studies.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.analchem.5b04392","usgsCitation":"Schimmelmann, A., Qi, H., Coplen, T.B., Brand, W.A., Fong, J., Meier-Augenstein, W., Kemp, H.F., Toman, B., Ackermann, A., Assonov, S., Aerts-Bijma, A., Brejcha, R., Chikaraishi, Y., Darwish, T., Elsner, M., Gehre, M., Geilmann, H., Groning, M., Helie, J., Herrero-Martin, S., Meijer, H.A., Sauer, P.E., Sessions, A.L., and Werner, R.A., 2016, New organic reference materials for hydrogen, carbon, and nitrogen stable isotope-ratio measurements: caffeines, n-alkanes, fatty acid methyl esters, glycines, L-valines, polyethylenes, and oils: Analytical Chemistry, v. 88, no. 8, p. 4294-4302, https://doi.org/10.1021/acs.analchem.5b04392.","productDescription":"9 p.","startPage":"4294","endPage":"4302","ipdsId":"IP-073415","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470392,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research.rug.nl/en/publications/cbe77820-c3cc-4440-b158-d120cd5bd01d","text":"External Repository"},{"id":337298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-31","publicationStatus":"PW","scienceBaseUri":"58c3c937e4b0f37a93ee9ae5","chorus":{"doi":"10.1021/acs.analchem.5b04392","url":"http://dx.doi.org/10.1021/acs.analchem.5b04392","publisher":"American Chemical Society (ACS)","authors":"Schimmelmann Arndt, Qi Haiping, Coplen Tyler B., Brand Willi A., Fong Jon, Meier-Augenstein Wolfram, Kemp Helen F., Toman Blaza, Ackermann Annika, Assonov Sergey, Aerts-Bijma Anita T., Brejcha Ramona, Chikaraishi Yoshito, Darwish Tamim, Elsner Martin, Gehre Matthias, Geilmann Heike, Gröning Manfred, Hélie Jean-François, Herrero-Martín Sara, Meijer Harro A. J., Sauer Peter E., Sessions Alex L., Werner Roland A.","journalName":"Analytical Chemistry","publicationDate":"4/19/2016"},"contributors":{"authors":[{"text":"Schimmelmann, Arndt","contributorId":140051,"corporation":false,"usgs":false,"family":"Schimmelmann","given":"Arndt","affiliations":[{"id":13366,"text":"Indiana University, Bloomington, Indiana, USA","active":true,"usgs":false}],"preferred":false,"id":681679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":681680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 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L.","contributorId":172980,"corporation":false,"usgs":false,"family":"Sessions","given":"Alex","email":"","middleInitial":"L.","affiliations":[{"id":27133,"text":"Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena CA","active":true,"usgs":false}],"preferred":false,"id":681700,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Werner, Roland A.","contributorId":187806,"corporation":false,"usgs":false,"family":"Werner","given":"Roland","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":681701,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70178570,"text":"70178570 - 2016 - Graphical function mapping as a new way to explore cause-and-effect chains","interactions":[],"lastModifiedDate":"2018-02-28T14:36:31","indexId":"70178570","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Graphical function mapping as a new way to explore cause-and-effect chains","docAbstract":"Graphical function mapping provides a simple method for improving communication within interdisciplinary research teams and between scientists and nonscientists. This article introduces graphical function mapping using two examples and discusses its usefulness. Function mapping projects the outcome of one function into another to show the combined effect. Using this mathematical property in a simpler, even cartoon-like, graphical way allows the rapid combination of multiple information sources (models, empirical data, expert judgment, and guesses) in an intuitive visual to promote further discussion, scenario development, and clear communication.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/03632415.2016.1221404","usgsCitation":"Evans, M.A., 2016, Graphical function mapping as a new way to explore cause-and-effect chains: Fisheries, v. 41, no. 11, p. 638-643, https://doi.org/10.1080/03632415.2016.1221404.","productDescription":"6 p.","startPage":"638","endPage":"643","ipdsId":"IP-060085","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":331372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"11","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-04","publicationStatus":"PW","scienceBaseUri":"584144dde4b04fc80e50737f","contributors":{"authors":[{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":4883,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":654409,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185058,"text":"70185058 - 2016 - Avoiding decline: Fostering resilience and sustainability in midsize cities","interactions":[],"lastModifiedDate":"2017-03-13T15:17:51","indexId":"70185058","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Avoiding decline: Fostering resilience and sustainability in midsize cities","docAbstract":"Eighty-five percent of United States citizens live in urban areas. However, research surrounding the resilience and sustainability of complex urban systems focuses largely on coastal megacities (>1 million people). Midsize cities differ from their larger counterparts due to tight urban-rural feedbacks with their immediate natural environments that result from heavy reliance and close management of local ecosystem services. They also may be less path-dependent than larger cities due to shorter average connection length among system components, contributing to higher responsiveness among social, infrastructural, and ecological feedbacks. These distinct midsize city features call for a framework that organizes information and concepts concerning the sustainability of midsize cities specifically. We argue that an integrative approach is necessary to capture properties emergent from the complex interactions of the social, infrastructural, and ecological subsystems that comprise a city system. We suggest approaches to estimate the relative resilience of midsize cities, and include an example assessment to illustrate one such estimation approach. Resilience assessments of a midsize city can be used to examine why some cities end up on sustainable paths while others diverge to unsustainable paths, and which feedbacks may be partially responsible. They also provide insight into how city planners and decision makers can use information about the resilience of midsize cities undergoing growth or shrinkage relative to their larger and smaller counterparts, to transform them into long-term, sustainable social-ecological systems.
","language":"English","publisher":"MDPI","doi":"10.3390/su8090844","usgsCitation":"Allen, C.R., Birge, H.E., Bartelt-Hunt, S., Bevans, R.A., Burnett, J., Cosens, B., Cai, X., Garmestani, A.S., Linkov, I., Scott, E.A., Solomon, M.D., and Uden, D.R., 2016, Avoiding decline: Fostering resilience and sustainability in midsize cities: Sustainability, v. 8, no. 9, https://doi.org/10.3390/su8090844.","ipdsId":"IP-076510","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470367,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su8090844","text":"Publisher Index Page"},{"id":337457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-26","publicationStatus":"PW","scienceBaseUri":"58c7af9be4b0849ce9795e76","contributors":{"authors":[{"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":684108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birge, Hannah E.","contributorId":166737,"corporation":false,"usgs":false,"family":"Birge","given":"Hannah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartelt-Hunt, Shannon","contributorId":189223,"corporation":false,"usgs":false,"family":"Bartelt-Hunt","given":"Shannon","email":"","affiliations":[],"preferred":false,"id":684142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bevans, Rebecca A.","contributorId":189134,"corporation":false,"usgs":false,"family":"Bevans","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burnett, Jessica","contributorId":189224,"corporation":false,"usgs":false,"family":"Burnett","given":"Jessica","affiliations":[],"preferred":false,"id":684144,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cosens, Barbara","contributorId":166744,"corporation":false,"usgs":false,"family":"Cosens","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":684145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cai, Ximing","contributorId":149230,"corporation":false,"usgs":false,"family":"Cai","given":"Ximing","email":"","affiliations":[{"id":17685,"text":"University of Illinois, Champagne-Urbana","active":true,"usgs":false}],"preferred":false,"id":684146,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garmestani, Ahjond S.","contributorId":77285,"corporation":false,"usgs":true,"family":"Garmestani","given":"Ahjond","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":684147,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Linkov, Igor","contributorId":172407,"corporation":false,"usgs":false,"family":"Linkov","given":"Igor","email":"","affiliations":[],"preferred":false,"id":684148,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Scott, Elizabeth A.","contributorId":189225,"corporation":false,"usgs":false,"family":"Scott","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684149,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Solomon, Mark D.","contributorId":189226,"corporation":false,"usgs":false,"family":"Solomon","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":684150,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":684151,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70178359,"text":"sir20165163 - 2016 - Borehole deviation and correction factor data for selected wells in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2016-11-30T10:35:45","indexId":"sir20165163","displayToPublicDate":"2016-11-29T00:00:00","publicationYear":"2016","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":"2016-5163","title":"Borehole deviation and correction factor data for selected wells in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, has maintained a water-level monitoring program at the Idaho National Laboratory (INL) since 1949. The purpose of the program is to systematically measure and report water-level data to assess the eastern Snake River Plain aquifer and long term changes in groundwater recharge, discharge, movement, and storage. Water-level data are commonly used to generate potentiometric maps and used to infer increases and (or) decreases in the regional groundwater system. Well deviation is one component of water-level data that is often overlooked and is the result of the well construction and the well not being plumb. Depending on measured slant angle, where well deviation generally increases linearly with increasing slant angle, well deviation can suggest artificial anomalies in the water table. To remove the effects of well deviation, the USGS INL Project Office applies a correction factor to water-level data when a well deviation survey indicates a change in the reference elevation of greater than or equal to 0.2 ft.
Borehole well deviation survey data were considered for 177 wells completed within the eastern Snake River Plain aquifer, but not all wells had deviation survey data available. As of 2016, USGS INL Project Office database includes: 57 wells with gyroscopic survey data; 100 wells with magnetic deviation survey data; 11 wells with erroneous gyroscopic data that were excluded; and, 68 wells with no deviation survey data available. Of the 57 wells with gyroscopic deviation surveys, correction factors for 16 wells ranged from 0.20 to 6.07 ft and inclination angles (SANG) ranged from 1.6 to 16.0 degrees. Of the 100 wells with magnetic deviation surveys, a correction factor for 21 wells ranged from 0.20 to 5.78 ft and SANG ranged from 1.0 to 13.8 degrees, not including the wells that did not meet the correction factor criteria of greater than or equal to 0.20 ft.
Forty-seven wells had gyroscopic and magnetic deviation survey data for the same well. Datasets for both survey types were compared for the same well to determine whether magnetic survey data were consistent with gyroscopic survey data. Of those 47 wells, 96 percent showed similar correction factor estimates (≤ 0.20 ft) for both magnetic and gyroscopic well deviation surveys. A linear comparison of correction factor estimates for both magnetic and gyroscopic deviation well surveys for all 47 wells indicate good linear correlation, represented by an r-squared of 0.88. The correction factor difference between the gyroscopic and magnetic surveys for 45 of 47 wells ranged from 0.00 to 0.18 ft, not including USGS 57 and USGS 125. Wells USGS 57 and USGS 125 show a correction factor difference of 2.16 and 0.36 ft, respectively; however, review of the data files suggest erroneous SANG data for both magnetic deviation well surveys. The difference in magnetic and gyroscopic well deviation SANG measurements, for all wells, ranged from 0.0 to 0.9 degrees. These data indicate good agreement between SANG data measured using the magnetic deviation survey methods and SANG data measured using gyroscopic deviation survey methods, even for surveys collected years apart.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165163","collaboration":"DOE/ID-22241Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all available clear Landsat 5–8 observations with the new Continuous Change Detection and Classification (CCDC) algorithm was very effective for illuminating vegetation trends. There are a number of potential challenges for assessing gradual changes, including atmospheric impacts, algorithm development and visualization of the changes. One of the biggest challenges for studying gradual change will be the lack of appropriate data for validating results and products.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.02.060","usgsCitation":"Vogelmann, J., Gallant, A.L., Shi, H., and Zhu, Z., 2016, Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data: Remote Sensing of Environment, v. 185, p. 258-270, https://doi.org/10.1016/j.rse.2016.02.060.","productDescription":"13 p.","startPage":"258","endPage":"270","ipdsId":"IP-066052","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470406,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2016.02.060","text":"Publisher Index Page"},{"id":341856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84b8e4b092b266f10d2c","contributors":{"authors":[{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":696377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","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":696379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696380,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178535,"text":"70178535 - 2016 - Projected gains and losses of wildlife habitat from bioenergy-induced landscape change","interactions":[],"lastModifiedDate":"2018-12-20T13:08:40","indexId":"70178535","displayToPublicDate":"2016-11-23T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1718,"text":"GCB Bioenergy","active":true,"publicationSubtype":{"id":10}},"title":"Projected gains and losses of wildlife habitat from bioenergy-induced landscape change","docAbstract":"Domestic and foreign renewable energy targets and financial incentives have increased demand for woody biomass and bioenergy in the southeastern United States. This demand is expected to be met through purpose-grown agricultural bioenergy crops, short-rotation tree plantations, thinning and harvest of planted and natural forests, and forest harvest residues. With results from a forest economics model, spatially explicit state-and-transition simulation models, and species–habitat models, we projected change in habitat amount for 16 wildlife species caused by meeting a renewable fuel target and expected demand for wood pellets in North Carolina, USA. We projected changes over 40 years under a baseline ‘business-as-usual’ scenario without bioenergy production and five scenarios with unique feedstock portfolios. Bioenergy demand had potential to influence trends in habitat availability for some species in our study area. We found variation in impacts among species, and no scenario was the ‘best’ or ‘worst’ across all species. Our models projected that shrub-associated species would gain habitat under some scenarios because of increases in the amount of regenerating forests on the landscape, while species restricted to mature forests would lose habitat. Some forest species could also lose habitat from the conversion of forests on marginal soils to purpose-grown feedstocks. The conversion of agricultural lands on marginal soils to purpose-grown feedstocks increased habitat losses for one species with strong associations with pasture, which is being lost to urbanization in our study region. Our results indicate that landscape-scale impacts on wildlife habitat will vary among species and depend upon the bioenergy feedstock portfolio. Therefore, decisions about bioenergy and wildlife will likely involve trade-offs among wildlife species, and the choice of focal species is likely to affect the results of landscape-scale assessments. We offer general principals to consider when crafting lists of focal species for bioenergy impact assessments at the landscape scale.
Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi, constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the conservation status of pelagophils.
Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1582","usgsCitation":"Byrd, K.B., Windham-Myers, L., Leeuw, T., Downing, B.D., Morris, J.T., and Ferner, M.C., 2016, Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model: Ecosphere, v. 7, no. 11, e01582; 27 p., https://doi.org/10.1002/ecs2.1582.","productDescription":"e01582; 27 p.","ipdsId":"IP-073438","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470411,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1582","text":"Publisher Index Page"},{"id":438505,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76M34Z1","text":"USGS data release","linkHelpText":"Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model"},{"id":331164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335610,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F76M34Z1","text":"Data release for journal article titled, \"Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model\""}],"country":"United States","state":"California","otherGeospatial":"Rush Ranch Open Space Preserve, Suisun Slough, Suisun Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05501556396483,\n 38.17802085110361\n ],\n [\n -122.05501556396483,\n 38.212288054388175\n ],\n [\n -121.99802398681642,\n 38.212288054388175\n ],\n [\n -121.99802398681642,\n 38.17802085110361\n ],\n [\n -122.05501556396483,\n 38.17802085110361\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-14","publicationStatus":"PW","scienceBaseUri":"583415ade4b0070c0abed81a","chorus":{"doi":"10.1002/ecs2.1582","url":"http://dx.doi.org/10.1002/ecs2.1582","publisher":"Wiley-Blackwell","authors":"Byrd Kristin B., Windham-Myers Lisamarie, Leeuw Thomas, Downing Bryan, Morris James T., Ferner Matthew C.","journalName":"Ecosphere","publicationDate":"11/2016","auditedOn":"11/29/2016"},"contributors":{"authors":[{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":654113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leeuw, Thomas","contributorId":176970,"corporation":false,"usgs":false,"family":"Leeuw","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":654115,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morris, James T.","contributorId":29118,"corporation":false,"usgs":true,"family":"Morris","given":"James","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":654117,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ferner, Matthew C.","contributorId":176972,"corporation":false,"usgs":false,"family":"Ferner","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":654118,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178405,"text":"70178405 - 2016 - Comparison of the mineral composition of the sediment found in two Mars dunefields: Ogygis Undae and Gale crater – three distinct endmembers identified","interactions":[],"lastModifiedDate":"2016-12-16T13:06:00","indexId":"70178405","displayToPublicDate":"2016-11-17T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of the mineral composition of the sediment found in two Mars dunefields: Ogygis Undae and Gale crater – three distinct endmembers identified","docAbstract":"The composition of two dune fields, Ogygis Undae and the NE–SW trending dune field in Gale crater (the “Bagnold Dune Field” and “Western Dune Field”), were analyzed using thermal emission spectra from the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) and the Mars Odyssey Thermal Emission Imaging System (THEMIS). The Gale crater dune field was used as a baseline as other orbital compositional analyses have been conducted, and in situ sampling results will soon be available.
Results from unmixing thermal emission spectra showed a spatial variation between feldspar mineral abundances and pyroxene mineral abundances in Ogygis Undae. Other datasets, including nighttime thermal inertia values, also showed variation throughout the dune field. One explanation proposed for this variation is a bimodal distribution of two sand populations. This distribution is seen in some terrestrial dune fields.
The two dune fields varied in both mineral types present and in uniformity of composition. These differences point to different source lithologies and different distances travelled from source material. Examining these differences further will allow for a greater understanding of aeolian processes on Mars.
","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.epsl.2016.10.022","usgsCitation":"Charles, H., Titus, T.N., Hayward, R., Edwards, C., and Ahrens, C., 2016, Comparison of the mineral composition of the sediment found in two Mars dunefields: Ogygis Undae and Gale crater – three distinct endmembers identified: Earth and Planetary Science Letters, v. 458, no. 15, p. 152-160, https://doi.org/10.1016/j.epsl.2016.10.022.","productDescription":"9 p.","startPage":"152","endPage":"160","ipdsId":"IP-071753","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":331096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"458","issue":"15","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582ecfece4b04d580bd43528","contributors":{"authors":[{"text":"Charles, Heather hcharles@usgs.gov","contributorId":176924,"corporation":false,"usgs":true,"family":"Charles","given":"Heather","email":"hcharles@usgs.gov","affiliations":[],"preferred":true,"id":653991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":653992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayward, Rosalyn rhayward@usgs.gov","contributorId":176925,"corporation":false,"usgs":true,"family":"Hayward","given":"Rosalyn","email":"rhayward@usgs.gov","affiliations":[],"preferred":true,"id":653994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Christopher cedwards@usgs.gov","contributorId":147768,"corporation":false,"usgs":true,"family":"Edwards","given":"Christopher","email":"cedwards@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":653993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ahrens, Caitlin","contributorId":176926,"corporation":false,"usgs":false,"family":"Ahrens","given":"Caitlin","email":"","affiliations":[],"preferred":false,"id":653995,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178387,"text":"70178387 - 2016 - Interannual water-level fluctuations and the vegetation of prairie potholes: Potential impacts of climate change","interactions":[],"lastModifiedDate":"2017-01-03T16:05:22","indexId":"70178387","displayToPublicDate":"2016-11-16T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Interannual water-level fluctuations and the vegetation of prairie potholes: Potential impacts of climate change","docAbstract":"Mean water depth and range of interannual water-level fluctuations over wet-dry cycles in precipitation are major drivers of vegetation zone formation in North American prairie potholes. We used harmonic hydrological models, which require only mean interannual water depth and amplitude of water-level fluctuations over a wet–dry cycle, to examine how the vegetation zones in a pothole would respond to small changes in water depth and/or amplitude of water-level fluctuations. Field data from wetlands in Saskatchewan, North Dakota, and South Dakota were used to parameterize harmonic models for four pothole classes. Six scenarios in which small negative or positive changes in either mean water depth, amplitude of interannual fluctuations, or both, were modeled to predict if they would affect the number of zones in each wetland class. The results indicated that, in some cases, even small changes in mean water depth when coupled with a small change in amplitude of water-level fluctuations can shift a prairie pothole wetland from one class to another. Our results suggest that climate change could alter the relative proportion of different wetland classes in the prairie pothole region.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0850-8","usgsCitation":"van der Valk, A., and Mushet, D.M., 2016, Interannual water-level fluctuations and the vegetation of prairie potholes: Potential impacts of climate change: Wetlands, v. 36, no. 2, p. 397-406, https://doi.org/10.1007/s13157-016-0850-8.","productDescription":"10 p.","startPage":"397","endPage":"406","ipdsId":"IP-072077","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470416,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1303&context=eeob_ag_pubs","text":"External Repository"},{"id":331061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-14","publicationStatus":"PW","scienceBaseUri":"582dd8e9e4b04d580bd3fa87","contributors":{"authors":[{"text":"van der Valk, Arnold","contributorId":145612,"corporation":false,"usgs":false,"family":"van der Valk","given":"Arnold","affiliations":[{"id":15296,"text":"Iowa State University, Ames, IA, USA","active":true,"usgs":false}],"preferred":false,"id":653912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":653911,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178390,"text":"70178390 - 2016 - Midcontinent Prairie-Pothole wetlands and climate change: An Introduction to the Supplemental Issue","interactions":[],"lastModifiedDate":"2017-01-03T16:06:01","indexId":"70178390","displayToPublicDate":"2016-11-16T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Midcontinent Prairie-Pothole wetlands and climate change: An Introduction to the Supplemental Issue","docAbstract":"The multitude of wetlands in the Prairie Pothole Region of North America forms one of Earth’s largest wetland complexes. The midcontinent location exposes this ecologically and economically important wetland system to a highly variable climate, markedly influencing ponded-water levels, hydroperiods, chemical characteristics, and biota of individual basins. Given their dominance on the landscape and recognized value, great interest in how projected future changes in climate will affect prairie-pothole wetlands has developed and spawned much scientific research. On June 2, 2015, a special symposium, “Midcontinent Prairie-Pothole Wetlands: Influence of a Changed Climate,” was held at the annual meeting of the Society of Wetland Scientists in Providence, Rhode Island, USA. The symposium’s twelve presenters covered a wide range of relevant topics delivered to a standing-room-only audience. Following the symposium, the presenters recognized the need to publish their presented papers as a combined product to facilitate widespread distribution. The need for additional papers to more fully cover the topic of prairie-pothole wetlands and climate change was also identified. This supplemental issue of Wetlands is the realization of that vision.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0852-6","usgsCitation":"Mushet, D.M., 2016, Midcontinent Prairie-Pothole wetlands and climate change: An Introduction to the Supplemental Issue: Wetlands, v. 36, no. s2, p. 223-228, https://doi.org/10.1007/s13157-016-0852-6.","productDescription":"6 p.","startPage":"223","endPage":"228","ipdsId":"IP-076703","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488540,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13157-016-0852-6","text":"Publisher Index Page"},{"id":331060,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","volume":"36","issue":"s2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-09","publicationStatus":"PW","scienceBaseUri":"582dd8e9e4b04d580bd3fa8b","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":653918,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70178361,"text":"70178361 - 2016 - Defining ecosystem assets for natural capital accounting","interactions":[],"lastModifiedDate":"2016-11-16T10:52:32","indexId":"70178361","displayToPublicDate":"2016-11-09T00:00:00","publicationYear":"2016","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":"Defining ecosystem assets for natural capital accounting","docAbstract":"In natural capital accounting, ecosystems are assets that provide ecosystem services to people. Assets can be measured using both physical and monetary units. In the international System of Environmental-Economic Accounting, ecosystem assets are generally valued on the basis of the net present value of the expected flow of ecosystem services. In this paper we argue that several additional conceptualisations of ecosystem assets are needed to understand ecosystems as assets, in support of ecosystem assessments, ecosystem accounting and ecosystem management. In particular, we define ecosystems’ capacity and capability to supply ecosystem services, as well as the potential supply of ecosystem services. Capacity relates to sustainable use levels of multiple ecosystem services, capability involves prioritising the use of one ecosystem service over a basket of services, and potential supply considers the ability of ecosystems to generate services regardless of demand for these services. We ground our definitions in the ecosystem services and accounting literature, and illustrate and compare the concepts of flow, capacity, capability, and potential supply with a range of conceptual and real-world examples drawn from case studies in Europe and North America. Our paper contributes to the development of measurement frameworks for natural capital to support environmental accounting and other assessment frameworks.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0164460","usgsCitation":"Hein, L., Bagstad, K.J., Edens, B., Obst, C., de Jong, R., and Lesschen, J.P., 2016, Defining ecosystem assets for natural capital accounting: PLoS ONE, v. 11, no. 11, e0164460; 25 p., https://doi.org/10.1371/journal.pone.0164460.","productDescription":"e0164460; 25 p.","ipdsId":"IP-075433","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":470429,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0164460","text":"Publisher Index Page"},{"id":331071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-09","publicationStatus":"PW","scienceBaseUri":"582dd8eae4b04d580bd3fa91","contributors":{"authors":[{"text":"Hein, Lars","contributorId":176849,"corporation":false,"usgs":false,"family":"Hein","given":"Lars","email":"","affiliations":[],"preferred":false,"id":653773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":653772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edens, Bram","contributorId":176850,"corporation":false,"usgs":false,"family":"Edens","given":"Bram","email":"","affiliations":[],"preferred":false,"id":653774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Obst, Carl","contributorId":176851,"corporation":false,"usgs":false,"family":"Obst","given":"Carl","email":"","affiliations":[],"preferred":false,"id":653775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Jong, Rixt","contributorId":176852,"corporation":false,"usgs":false,"family":"de Jong","given":"Rixt","email":"","affiliations":[],"preferred":false,"id":653776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lesschen, Jan Peter","contributorId":176853,"corporation":false,"usgs":false,"family":"Lesschen","given":"Jan","email":"","middleInitial":"Peter","affiliations":[],"preferred":false,"id":653777,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178123,"text":"70178123 - 2016 - Spatial and temporal variability of contaminants within estuarine sediments and native Olympia oysters: A contrast between a developed and an undeveloped estuary","interactions":[],"lastModifiedDate":"2016-11-03T11:36:54","indexId":"70178123","displayToPublicDate":"2016-11-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variability of contaminants within estuarine sediments and native Olympia oysters: A contrast between a developed and an undeveloped estuary","docAbstract":"Chemical contaminants can be introduced into estuarine and marine ecosystems from a variety of sources including wastewater, agriculture and forestry practices, point and non-point discharges, runoff from industrial, municipal, and urban lands, accidental spills, and atmospheric deposition. The diversity of potential sources contributes to the likelihood of contaminated marine waters and sediments and increases the probability of uptake by marine organisms. Despite widespread recognition of direct and indirect pathways for contaminant deposition and organismal exposure in coastal systems, spatial and temporal variability in contaminant composition, deposition, and uptake patterns are still poorly known. We investigated these patterns for a suite of persistent legacy contaminants including polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) and chemicals of emerging concern including pharmaceuticals within two Oregon coastal estuaries (Coos and Netarts Bays). In the more urbanized Coos Bay, native Olympia oyster (Ostrea lurida) tissue had approximately twice the number of PCB congeners at over seven times the total concentration, yet fewer PBDEs at one-tenth the concentration as compared to the more rural Netarts Bay. Different pharmaceutical suites were detected during each sampling season. Variability in contaminant types and concentrations across seasons and between species and media (organisms versus sediment) indicates the limitation of using indicator species and/or sampling annually to determine contaminant loads at a site or for specific species. The results indicate the prevalence of legacy contaminants and CECs in relatively undeveloped coastal environments highlighting the need to improve policy and management actions to reduce contaminant releases into estuarine and marine waters and to deal with legacy compounds that remain long after prohibition of use. Our results point to the need for better understanding of the ecological and human health risks of exposure to the diverse cocktail of pollutants and harmful compounds that will continue to leach from estuarine sediments over time.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2016.03.043","collaboration":"Portland State University, Oregon Water Science Center, Oregon Department of Environmental Quality","usgsCitation":"Granek, E.F., Conn, K., Nilsen, E.B., Pillsbury, L., Strecker, A.L., Rumrill, S., and Fish, W., 2016, Spatial and temporal variability of contaminants within estuarine sediments and native Olympia oysters: A contrast between a developed and an undeveloped estuary: Science of the Total Environment, v. 557-558, p. 869-879, https://doi.org/10.1016/j.scitotenv.2016.03.043.","productDescription":"11 p.","startPage":"869","endPage":"879","ipdsId":"IP-070780","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":488517,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pdxscholar.library.pdx.edu/esm_fac/144","text":"External Repository"},{"id":330690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.57809448242186,\n 43.15159875016117\n ],\n [\n -124.57809448242186,\n 43.555515149559746\n ],\n [\n -123.760986328125,\n 43.555515149559746\n ],\n [\n -123.760986328125,\n 43.15159875016117\n ],\n [\n -124.57809448242186,\n 43.15159875016117\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.26773071289062,\n 45.15686396890044\n ],\n [\n -124.26773071289062,\n 45.47939202177826\n ],\n [\n -123.52409362792969,\n 45.47939202177826\n ],\n [\n -123.52409362792969,\n 45.15686396890044\n ],\n [\n -124.26773071289062,\n 45.15686396890044\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"557-558","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"581c4cc1e4b09688d6e90fa1","contributors":{"authors":[{"text":"Granek, Elise F.","contributorId":176630,"corporation":false,"usgs":false,"family":"Granek","given":"Elise","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":652867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nilsen, Elena B. 0000-0002-0104-6321 enilsen@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-6321","contributorId":923,"corporation":false,"usgs":true,"family":"Nilsen","given":"Elena","email":"enilsen@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pillsbury, Lori","contributorId":176618,"corporation":false,"usgs":false,"family":"Pillsbury","given":"Lori","email":"","affiliations":[],"preferred":false,"id":652893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Strecker, Angela L.","contributorId":43256,"corporation":false,"usgs":true,"family":"Strecker","given":"Angela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":652870,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rumrill, Steve","contributorId":176620,"corporation":false,"usgs":false,"family":"Rumrill","given":"Steve","email":"","affiliations":[],"preferred":false,"id":652894,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fish, William","contributorId":176621,"corporation":false,"usgs":false,"family":"Fish","given":"William","email":"","affiliations":[],"preferred":false,"id":652872,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70177969,"text":"70177969 - 2016 - Bounded fractional diffusion in geological media: Definition and Lagrangian approximation","interactions":[],"lastModifiedDate":"2018-08-09T12:27:12","indexId":"70177969","displayToPublicDate":"2016-11-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Bounded fractional diffusion in geological media: Definition and Lagrangian approximation","docAbstract":"Spatiotemporal Fractional-Derivative Models (FDMs) have been increasingly used to simulate non-Fickian diffusion, but methods have not been available to define boundary conditions for FDMs in bounded domains. This study defines boundary conditions and then develops a Lagrangian solver to approximate bounded, one-dimensional fractional diffusion. Both the zero-value and non-zero-value Dirichlet, Neumann, and mixed Robin boundary conditions are defined, where the sign of Riemann-Liouville fractional derivative (capturing non-zero-value spatial-nonlocal boundary conditions with directional super-diffusion) remains consistent with the sign of the fractional-diffusive flux term in the FDMs. New Lagrangian schemes are then proposed to track solute particles moving in bounded domains, where the solutions are checked against analytical or Eularian solutions available for simplified FDMs. Numerical experiments show that the particle-tracking algorithm for non-Fickian diffusion differs from Fickian diffusion in relocating the particle position around the reflective boundary, likely due to the non-local and non-symmetric fractional diffusion. For a non-zero-value Neumann or Robin boundary, a source cell with a reflective face can be applied to define the release rate of random-walking particles at the specified flux boundary. Mathematical definitions of physically meaningful nonlocal boundaries combined with bounded Lagrangian solvers in this study may provide the only viable techniques at present to quantify the impact of boundaries on anomalous diffusion, expanding the applicability of FDMs from infinite do mains to those with any size and boundary conditions.","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2016WR019178","usgsCitation":"Zhang, Y., Green, C.T., LaBolle, E.M., Neupauer, R.M., and Sun, H., 2016, Bounded fractional diffusion in geological media: Definition and Lagrangian approximation: Water Resources Research, v. 52, no. 11, p. 8561-8577, https://doi.org/10.1002/2016WR019178.","productDescription":"17 p.","startPage":"8561","endPage":"8577","ipdsId":"IP-075843","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470444,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019178","text":"Publisher Index Page"},{"id":330678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-12","publicationStatus":"PW","scienceBaseUri":"581c4cc2e4b09688d6e90fb1","contributors":{"authors":[{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":652794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":652795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaBolle, Eric M.","contributorId":176579,"corporation":false,"usgs":false,"family":"LaBolle","given":"Eric","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neupauer, Roseanna M.","contributorId":176580,"corporation":false,"usgs":false,"family":"Neupauer","given":"Roseanna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Hong-Guang 0000-0002-8422-3871","orcid":"https://orcid.org/0000-0002-8422-3871","contributorId":176581,"corporation":false,"usgs":false,"family":"Sun","given":"Hong-Guang","email":"","affiliations":[],"preferred":false,"id":652798,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178081,"text":"70178081 - 2016 - Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico","interactions":[],"lastModifiedDate":"2016-11-02T10:55:52","indexId":"70178081","displayToPublicDate":"2016-11-02T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico","docAbstract":"We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8110889","usgsCitation":"Dye, D.G., Middleton, B.R., Vogel, J.M., Wu, Z., and Velasco, M.G., 2016, Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico: Remote Sensing, v. 8, no. 11, p. 1-33, https://doi.org/10.3390/rs8110889.","productDescription":"Article 889; 33 p.","startPage":"1","endPage":"33","ipdsId":"IP-069667","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470445,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8110889","text":"Publisher Index Page"},{"id":330648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112,\n 31\n ],\n [\n -112,\n 33\n ],\n [\n -110,\n 33\n ],\n [\n -110,\n 31\n ],\n [\n -112,\n 31\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-28","publicationStatus":"PW","scienceBaseUri":"581afb64e4b0bb36a4ca664b","contributors":{"authors":[{"text":"Dye, Dennis G. 0000-0002-7100-272X ddye@usgs.gov","orcid":"https://orcid.org/0000-0002-7100-272X","contributorId":4233,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","email":"ddye@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":652712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, Barry R. 0000-0001-8924-4121 bmiddleton@usgs.gov","orcid":"https://orcid.org/0000-0001-8924-4121","contributorId":3947,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","email":"bmiddleton@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":652713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vogel, John M. 0000-0002-8226-1188 jvogel@usgs.gov","orcid":"https://orcid.org/0000-0002-8226-1188","contributorId":3167,"corporation":false,"usgs":true,"family":"Vogel","given":"John","email":"jvogel@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":652714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":652715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Velasco, Miguel G. 0000-0003-2559-7934 mvelasco@usgs.gov","orcid":"https://orcid.org/0000-0003-2559-7934","contributorId":2103,"corporation":false,"usgs":true,"family":"Velasco","given":"Miguel","email":"mvelasco@usgs.gov","middleInitial":"G.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":652716,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185036,"text":"70185036 - 2016 - Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2017-03-13T16:56:17","indexId":"70185036","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report)","docAbstract":"The Commission on Isotopic Abundances and Atomic Weights uses annotations given in footnotes that are an integral part of the Tables of Standard Atomic Weights to alert users to the possibilities of quite extraordinary occurrences, as well as sources with abnormal atomic-weight values outside an otherwise acceptable range. The basic need for footnotes to the Standard Atomic Weights Table and equivalent annotations to the Table of Isotopic Compositions of the Elements arises from the necessity to provide users with information that is relevant to one or more elements, but that cannot be provided using numerical data in columns. Any desire to increase additional information conveyed by annotations to these Tables is tempered by the need to preserve a compact format and a style that can alert users, who would not be inclined to consult either the last full element-by-element review or the full text of a current Standard Atomic Weights of the Elements report. Since 1989, the footnotes of the Tables of Standard Atomic Weights and the annotations in column 5 of the Table of Isotopic Compositions of the Elements have been harmonized by use of three lowercase footnotes, “g”, “m”, and “r”, that signify geologically exceptionally specimens (“g”), modified isotopic compositions in material subjected to undisclosed or inadvertent isotopic fractionation (“m”), and the range in isotopic composition of normal terrestrial material prevents more precise atomic-weight value being given (“r”). As some elements are assigned intervals for their standard atomic-weight values (applies to 12 elements since 2009), footnotes “g” and “r” are no longer needed for these elements.
","language":"English","publisher":"IUPAC","doi":"10.1515/pac-2016-0203","usgsCitation":"Coplen, T.B., and Holden, N.E., 2016, Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report): Pure and Applied Chemistry, v. 88, no. 7, p. 689-699, https://doi.org/10.1515/pac-2016-0203.","productDescription":"11 p.","startPage":"689","endPage":"699","ipdsId":"IP-072769","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2016-0203","text":"Publisher Index Page"},{"id":337476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c7af9fe4b0849ce9795e94","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":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":684029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holden, Norman E.","contributorId":189167,"corporation":false,"usgs":false,"family":"Holden","given":"Norman","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684030,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178341,"text":"70178341 - 2016 - Prediction of pesticide toxicity in Midwest streams","interactions":[],"lastModifiedDate":"2018-09-26T12:40:43","indexId":"70178341","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Prediction of pesticide toxicity in Midwest streams","docAbstract":"The occurrence of pesticide mixtures is common in stream waters of the United States, and the impact of multiple compounds on aquatic organisms is not well understood. Watershed Regressions for Pesticides (WARP) models were developed to predict Pesticide Toxicity Index (PTI) values in unmonitored streams in the Midwest and are referred to as WARP-PTI models. The PTI is a tool for assessing the relative toxicity of pesticide mixtures to fish, benthic invertebrates, and cladocera in stream water. One hundred stream sites in the Midwest were sampled weekly in May through August 2013, and the highest calculated PTI for each site was used as the WARP-PTI model response variable. Watershed characteristics that represent pesticide sources and transport were used as the WARP-PTI model explanatory variables. Three WARP-PTI models—fish, benthic invertebrates, and cladocera—were developed that include watershed characteristics describing toxicity-weighted agricultural use intensity, land use, agricultural management practices, soil properties, precipitation, and hydrologic properties. The models explained between 41 and 48% of the variability in the measured PTI values. WARP-PTI model evaluation with independent data showed reasonable performance with no clear bias. The models were applied to streams in the Midwest to demonstrate extrapolation for a regional assessment to indicate vulnerable streams and to guide more intensive monitoring.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2015.12.0624","usgsCitation":"Shoda, M.E., Stone, W.W., and Nowell, L.H., 2016, Prediction of pesticide toxicity in Midwest streams: Journal of Environmental Quality, v. 45, no. 6, p. 1856-1864, https://doi.org/10.2134/jeq2015.12.0624.","productDescription":"9 p.","startPage":"1856","endPage":"1864","ipdsId":"IP-064521","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":470462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2015.12.0624","text":"Publisher Index Page"},{"id":330980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Midwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.41552734375,\n 36.65079252503471\n ],\n [\n -98.41552734375,\n 45.336701909968134\n ],\n [\n -81.71630859375,\n 45.336701909968134\n ],\n [\n -81.71630859375,\n 36.65079252503471\n ],\n [\n -98.41552734375,\n 36.65079252503471\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582adb45e4b0c253bdfff0af","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":653654,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70193716,"text":"70193716 - 2016 - Holocene volcanism of the upper McKenzie River catchment, central Oregon Cascades, USA","interactions":[],"lastModifiedDate":"2017-11-05T17:41:42","indexId":"70193716","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Holocene volcanism of the upper McKenzie River catchment, central Oregon Cascades, USA","docAbstract":"To assess the complexity of eruptive activity within mafic volcanic fields, we present a detailed geologic investigation of Holocene volcanism in the upper McKenzie River catchment in the central Oregon Cascades, United States. We focus on the Sand Mountain volcanic field, which covers 76 km2 and consists of 23 vents, associated tephra deposits, and lava fields. We find that the Sand Mountain volcanic field was active for a few decades around 3 ka and involved at least 13 eruptive units. Despite the small total volume erupted (∼1 km3 dense rock equivalent [DRE]), Sand Mountain volcanic field lava geochemistry indicates that erupted magmas were derived from at least two, and likely three, different magma sources. Single units erupted from one or more vents, and field data provide evidence of both vent migration and reoccupation. Overall, our study shows that mafic volcanism was clustered in space and time, involved both explosive and effusive behavior, and tapped several magma sources. These observations provide important insights on possible future hazards from mafic volcanism in the central Oregon Cascades.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31405.1","usgsCitation":"Deligne, N.I., Conrey, R.M., Cashman, K.V., Champion, D.E., and Amidon, W.H., 2016, Holocene volcanism of the upper McKenzie River catchment, central Oregon Cascades, USA: Geological Society of America Bulletin, v. 128, no. 11-12, p. 1618-1635, https://doi.org/10.1130/B31405.1.","productDescription":"17 p.","startPage":"1618","endPage":"1635","ipdsId":"IP-069303","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"11-12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-11","publicationStatus":"PW","scienceBaseUri":"5a003151e4b0531197b5a752","contributors":{"authors":[{"text":"Deligne, Natalia I.","contributorId":194343,"corporation":false,"usgs":false,"family":"Deligne","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":720031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":720032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, Katharine V.","contributorId":199542,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine","email":"","middleInitial":"V.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":720033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amidon, William H.","contributorId":199781,"corporation":false,"usgs":false,"family":"Amidon","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":27844,"text":"Middlebury College","active":true,"usgs":false}],"preferred":false,"id":720034,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191088,"text":"70191088 - 2016 - Metabarcoding of fecal samples to determine herbivore diets: A case study of the endangered Pacific pocket mouse","interactions":[],"lastModifiedDate":"2018-03-28T11:35:41","indexId":"70191088","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","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":"Metabarcoding of fecal samples to determine herbivore diets: A case study of the endangered Pacific pocket mouse","docAbstract":"Understanding the diet of an endangered species illuminates the animal’s ecology, habitat requirements, and conservation needs. However, direct observation of diet can be difficult, particularly for small, nocturnal animals such as the Pacific pocket mouse (Heteromyidae: Perognathus longimembris pacificus). Very little is known of the dietary habits of this federally endangered rodent, hindering management and restoration efforts. We used a metabarcoding approach to identify source plants in fecal samples (N = 52) from the three remaining populations known. The internal transcribed spacers (ITS) of the nuclear ribosomal loci were sequenced following the Illumina MiSeq amplicon strategy and processed reads were mapped to reference databases. We evaluated a range of threshold mapping criteria and found the best-performing setting generally recovered two distinct mock communities in proportions similar to expectation. We tested our method on captive animals fed a known diet and recovered almost all plant sources, but found substantial heterogeneity among fecal pellets collected from the same individual at the same time. Observed richness did not increase with pooling of pellets from the same individual. In field-collected samples, we identified 4–14 plant genera in individual samples and 74 genera overall, but over 50 percent of reads mapped to just six species in five genera. We simulated the effects of sequencing error, variable read length, and chimera formation to infer taxon-specific rates of misassignment for the local flora, which were generally low with some exceptions. Richness at the species and genus levels did not reach a clear asymptote, suggesting that diet breadth remained underestimated in the current pool of samples. Large numbers of scat samples are therefore needed to make inferences about diet and resource selection in future studies of the Pacific pocket mouse. We conclude that our minimally invasive method is promising for determining herbivore diets given a library of sequences from local plants.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0165366","usgsCitation":"Iwanowicz, D.D., Vandergast, A.G., Cornman, R.S., Adams, C.R., Kohn, J.R., Fisher, R.N., and Brehme, C.S., 2016, Metabarcoding of fecal samples to determine herbivore diets: A case study of the endangered Pacific pocket mouse: PLoS ONE, v. 11, no. 11, p. 1-23, https://doi.org/10.1371/journal.pone.0165366.","productDescription":"e0165366; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-079368","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":462041,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0165366","text":"Publisher Index Page"},{"id":346056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.72949218749999,\n 33.20939299295216\n ],\n [\n -117.38754272460936,\n 33.20939299295216\n ],\n [\n -117.38754272460936,\n 33.47727218776036\n ],\n [\n -117.72949218749999,\n 33.47727218776036\n ],\n [\n -117.72949218749999,\n 33.20939299295216\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"59ca15b0e4b017cf314041d2","contributors":{"authors":[{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":711128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":711129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":711130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Cynthia R. 0000-0003-4383-530X cradams@usgs.gov","orcid":"https://orcid.org/0000-0003-4383-530X","contributorId":176965,"corporation":false,"usgs":true,"family":"Adams","given":"Cynthia","email":"cradams@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":711131,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kohn, Joshua R.","contributorId":196689,"corporation":false,"usgs":false,"family":"Kohn","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":711132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":711133,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brehme, Cheryl S. 0000-0001-8904-3354 cbrehme@usgs.gov","orcid":"https://orcid.org/0000-0001-8904-3354","contributorId":3419,"corporation":false,"usgs":true,"family":"Brehme","given":"Cheryl","email":"cbrehme@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":711134,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70185048,"text":"70185048 - 2016 - Comment on “Reconciliation of the Devils Hole climate record with orbital forcing”","interactions":[],"lastModifiedDate":"2017-03-13T16:12:26","indexId":"70185048","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Comment on “Reconciliation of the Devils Hole climate record with orbital forcing”","docAbstract":"Moseley et al.’s (Reports, 8 January 2016, p. 165) preferred-Termination-II age is subjective, as evidenced by variation in their Termination-II ages of 2500 years per meter. Termination-II-age bias decreases to zero at ~1.5 meters below the present-day water table, if one assumes linear variation with core-sample height. Maintaining the required gradient of thorium isotope 230Th over 3.6 meters for 1000 years, much less 10,000 years, seems exceedingly unlikely.
","language":"English","publisher":"Science","doi":"10.1126/science.aaf8074","usgsCitation":"Coplen, T.B., 2016, Comment on “Reconciliation of the Devils Hole climate record with orbital forcing”: Science, v. 354, no. 6310, p. 296-296, https://doi.org/10.1126/science.aaf8074.","productDescription":"1 p.","startPage":"296","endPage":"296","ipdsId":"IP-074724","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":337467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"354","issue":"6310","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e90","chorus":{"doi":"10.1126/science.aaf8074","url":"http://dx.doi.org/10.1126/science.aaf8074","publisher":"American Association for the Advancement of Science (AAAS)","authors":"Coplen Tyler B.","journalName":"Science","publicationDate":"10/20/2016","publiclyAccessibleDate":"9/10/2018"},"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":684073,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185046,"text":"70185046 - 2016 - Spatio-temporal variation in age structure and abundance of the endangered snail kite: Pooling across regions masks a declining and aging population","interactions":[],"lastModifiedDate":"2017-03-13T16:31:18","indexId":"70185046","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","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":"Spatio-temporal variation in age structure and abundance of the endangered snail kite: Pooling across regions masks a declining and aging population","docAbstract":"While variation in age structure over time and space has long been considered important for population dynamics and conservation, reliable estimates of such spatio-temporal variation in age structure have been elusive for wild vertebrate populations. This limitation has arisen because of problems of imperfect detection, the potential for temporary emigration impacting assessments of age structure, and limited information on age. However, identifying patterns in age structure is important for making reliable predictions of both short- and long-term dynamics of populations of conservation concern. Using a multistate superpopulation estimator, we estimated region-specific abundance and age structure (the proportion of individuals within each age class) of a highly endangered population of snail kites for two separate regions in Florida over 17 years (1997–2013). We find that in the southern region of the snail kite—a region known to be critical for the long-term persistence of the species—the population has declined significantly since 1997, and during this time, it has increasingly become dominated by older snail kites (> 12 years old). In contrast, in the northern region—a region historically thought to serve primarily as drought refugia—the population has increased significantly since 2007 and age structure is more evenly distributed among age classes. Given that snail kites show senescence at approximately 13 years of age, where individuals suffer higher mortality rates and lower breeding rates, these results reveal an alarming trend for the southern region. Our work illustrates the importance of accounting for spatial structure when assessing changes in abundance and age distribution and the need for monitoring of age structure in imperiled species.
","language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0162690","usgsCitation":"Reichert, B.E., Kendall, W., Fletcher, R.J., and Kitchens, W.M., 2016, Spatio-temporal variation in age structure and abundance of the endangered snail kite: Pooling across regions masks a declining and aging population: PLoS ONE, v. 11, no. 9, p. 1-18, https://doi.org/10.1371/journal.pone.0162690.","productDescription":"e0162690; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-074516","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470451,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0162690","text":"Publisher Index Page"},{"id":337473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.24365234375,\n 25.512700007620513\n ],\n [\n -80.09033203125,\n 25.512700007620513\n ],\n [\n -80.09033203125,\n 28.5941685062326\n ],\n [\n -82.24365234375,\n 28.5941685062326\n ],\n [\n -82.24365234375,\n 25.512700007620513\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e92","contributors":{"authors":[{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":22166,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":684162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891 wkendall@usgs.gov","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":166709,"corporation":false,"usgs":true,"family":"Kendall","given":"William L.","email":"wkendall@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":684064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fletcher, Robert J. Jr.","contributorId":41294,"corporation":false,"usgs":true,"family":"Fletcher","given":"Robert","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":684163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kitchens, Wiley M. kitchensw@usgs.gov","contributorId":2851,"corporation":false,"usgs":true,"family":"Kitchens","given":"Wiley","email":"kitchensw@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":684164,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70177937,"text":"70177937 - 2016 - Nuclear and mitochondrial DNA analyses of golden eagles (Aquila chrysaetos canadensis) from three areas in western North America; initial results and conservation implications","interactions":[],"lastModifiedDate":"2021-08-24T14:35:14.757537","indexId":"70177937","displayToPublicDate":"2016-10-31T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Nuclear and mitochondrial DNA analyses of golden eagles (Aquila chrysaetos canadensis) from three areas in western North America; initial results and conservation implications","title":"Nuclear and mitochondrial DNA analyses of golden eagles (Aquila chrysaetos canadensis) from three areas in western North America; initial results and conservation implications","docAbstract":"Understanding the genetics of a population is a critical component of developing conservation strategies. We used archived tissue samples from golden eagles (Aquila chrysaetos canadensis) in three geographic regions of western North America to conduct a preliminary study of the genetics of the North American subspecies, and to provide data for United States Fish and Wildlife Service (USFWS) decision-making for golden eagle management. We used a combination of mitochondrial DNA (mtDNA) D-loop sequences and 16 nuclear DNA (nDNA) microsatellite loci to investigate the extent of gene flow among our sampling areas in Idaho, California and Alaska and to determine if we could distinguish birds from the different geographic regions based on their genetic profiles. Our results indicate high genetic diversity, low genetic structure and high connectivity. Nuclear DNA Fst values between Idaho and California were low but significantly different from zero (0.026). Bayesian clustering methods indicated a single population, and we were unable to distinguish summer breeding residents from different regions. Results of the mtDNA AMOVA showed that most of the haplotype variation (97%) was within the geographic populations while 3% variation was partitioned among them. One haplotype was common to all three areas. One region-specific haplotype was detected in California and one in Idaho, but additional sampling is required to determine if these haplotypes are unique to those geographic areas or a sampling artifact. We discuss potential sources of the high gene flow for this species including natal and breeding dispersal, floaters, and changes in migratory behavior as a result of environmental factors such as climate change and habitat alteration. Our preliminary findings can help inform the USFWS in development of golden eagle management strategies and provide a basis for additional research into the complex dynamics of the North American subspecies.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0164248","usgsCitation":"Craig, E.H., Adams, J.R., Waits, L.P., Fuller, M.R., and Whittington, D.M., 2016, Nuclear and mitochondrial DNA analyses of golden eagles (Aquila chrysaetos canadensis) from three areas in western North America; initial results and conservation implications: PLoS ONE, v. 11, no. 10, e0164248; 15 p., https://doi.org/10.1371/journal.pone.0164248.","productDescription":"e0164248; 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066818","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470478,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0164248","text":"Publisher Index Page"},{"id":330571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, California, Idaho, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7734375,\n 42.22851735620852\n ],\n [\n -114.08203125,\n 42.22851735620852\n ],\n [\n -114.08203125,\n 45.27488643704891\n ],\n [\n -117.7734375,\n 45.27488643704891\n ],\n [\n -117.7734375,\n 42.22851735620852\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.607421875,\n 35.10193405724606\n ],\n [\n -117.94921874999999,\n 35.10193405724606\n ],\n [\n -117.94921874999999,\n 38.41055825094609\n ],\n [\n -122.607421875,\n 38.41055825094609\n ],\n [\n -122.607421875,\n 35.10193405724606\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.322265625,\n 67.7760253890732\n ],\n [\n -141.240234375,\n 67.7760253890732\n ],\n [\n -141.240234375,\n 71.10254274232307\n ],\n [\n -165.322265625,\n 71.10254274232307\n ],\n [\n -165.322265625,\n 67.7760253890732\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-26","publicationStatus":"PW","scienceBaseUri":"5818582ce4b0bb36a4c6fa07","contributors":{"authors":[{"text":"Craig, Erica H.","contributorId":176469,"corporation":false,"usgs":false,"family":"Craig","given":"Erica","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":652482,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jennifer R.","contributorId":21404,"corporation":false,"usgs":true,"family":"Adams","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":652483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waits, Lisette P.","contributorId":87673,"corporation":false,"usgs":true,"family":"Waits","given":"Lisette","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":652484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuller, Mark R. 0000-0001-7459-1729 mark_fuller@usgs.gov","orcid":"https://orcid.org/0000-0001-7459-1729","contributorId":2296,"corporation":false,"usgs":true,"family":"Fuller","given":"Mark","email":"mark_fuller@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":652485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whittington, Diana M.","contributorId":176489,"corporation":false,"usgs":false,"family":"Whittington","given":"Diana","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652486,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177987,"text":"70177987 - 2016 - Differential heating in the Indian Ocean differentially modulates precipitation in the Ganges and Brahmaputra basins","interactions":[],"lastModifiedDate":"2017-03-08T14:37:46","indexId":"70177987","displayToPublicDate":"2016-10-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Differential heating in the Indian Ocean differentially modulates precipitation in the Ganges and Brahmaputra basins","docAbstract":"Indo-Pacific sea surface temperature dynamics play a prominent role in Asian summer monsoon variability. Two interactive climate modes of the Indo-Pacific—the El Niño/Southern Oscillation (ENSO) and the Indian Ocean dipole mode—modulate the amount of precipitation over India, in addition to precipitation over Africa, Indonesia, and Australia. However, this modulation is not spatially uniform. The precipitation in southern India is strongly forced by the Indian Ocean dipole mode and ENSO. In contrast, across northern India, encompassing the Ganges and Brahmaputra basins, the climate mode influence on precipitation is much less. Understanding the forcing of precipitation in these river basins is vital for food security and ecosystem services for over half a billion people. Using 28 years of remote sensing observations, we demonstrate that (i) the tropical west-east differential heating in the Indian Ocean influences the Ganges precipitation and (ii) the north-south differential heating in the Indian Ocean influences the Brahmaputra precipitation. The El Niño phase induces warming in the warm pool of the Indian Ocean and exerts more influence on Ganges precipitation than Brahmaputra precipitation. The analyses indicate that both the magnitude and position of the sea surface temperature anomalies in the Indian Ocean are important drivers for precipitation dynamics that can be effectively summarized using two new indices, one tuned for each basin. These new indices have the potential to aid forecasting of drought and flooding, to contextualize land cover and land use change, and to assess the regional impacts of climate change.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8110901","usgsCitation":"Pervez, M., and Henebry, G.M., 2016, Differential heating in the Indian Ocean differentially modulates precipitation in the Ganges and Brahmaputra basins: Remote Sensing, v. 8, no. 11, p. 1-16, https://doi.org/10.3390/rs8110901.","productDescription":"Article 901; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-080231","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470480,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8110901","text":"Publisher Index Page"},{"id":438523,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77P8WH6","text":"USGS data release","linkHelpText":"Differential heating in the Indian Ocean differentially modulates precipitation in the Ganges and Brahmaputra basins"},{"id":330570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":337120,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F77P8WH6","text":"Differential heating in the Indian Ocean differentially modulates precipitation in the Ganges and Brahmaputra Basins"}],"otherGeospatial":"Indian Ocean","volume":"8","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-31","publicationStatus":"PW","scienceBaseUri":"5818582de4b0bb36a4c6fa0b","contributors":{"authors":[{"text":"Pervez, Md Shahriar 0000-0003-3417-1871 spervez@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":3099,"corporation":false,"usgs":true,"family":"Pervez","given":"Md Shahriar","email":"spervez@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":652473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henebry, Geoffrey M.","contributorId":124528,"corporation":false,"usgs":false,"family":"Henebry","given":"Geoffrey","email":"","middleInitial":"M.","affiliations":[{"id":5087,"text":"Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Brookings, USA","active":true,"usgs":false}],"preferred":false,"id":652474,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192472,"text":"70192472 - 2016 - Continental rupture and the creation of new crust in the Salton Trough rift, southern California and northern Mexico: Results from the Salton Seismic Imaging Project","interactions":[],"lastModifiedDate":"2017-10-26T16:55:24","indexId":"70192472","displayToPublicDate":"2016-10-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Continental rupture and the creation of new crust in the Salton Trough rift, southern California and northern Mexico: Results from the Salton Seismic Imaging Project","docAbstract":"A refraction and wide-angle reflection seismic profile along the axis of the Salton Trough, California and Mexico, was analyzed to constrain crustal and upper mantle seismic velocity structure during active continental rifting. From the northern Salton Sea to the southern Imperial Valley, the crust is 17-18 km thick and approximately one-dimensional. The transition at depth from Colorado River sediment to underlying crystalline rock is gradual and is not a depositional surface. The crystalline rock from ~3 to ~8 km depth is interpreted as sediment metamorphosed by high heat flow. Deeper felsic crystalline rock could be stretched pre-existing crust or higher grade metamorphosed sediment. The lower crust below ~12 km depth is interpreted to be gabbro emplaced by rift-related magmatic intrusion by underplating. Low upper-mantle velocity indicates high temperature and partial melting. Under the Coachella Valley, sediment thins to the north and the underlying crystalline rock is interpreted as granitic basement. Mafic rock does not exist at 12-18 depth as it does to the south, and a weak reflection suggests Moho at ~28 km depth. Structure in adjacent Mexico has slower mid-crustal velocity and rocks with mantle velocity must be much deeper than in the Imperial Valley. Slower velocity and thicker crust in the Coachella and Mexicali valleys define the rift zone between them to be >100 km wide in the direction of plate motion. North American lithosphere in the central Salton Trough has been rifted apart and is being replaced by new crust created by magmatism, sedimentation, and metamorphism.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JB013139","usgsCitation":"Han, L., Hole, J.A., Stock, J.M., Fuis, G.S., Kell, A., Driscoll, N.W., Kent, G.M., Rymer, M.J., Gonzalez-Fernandez, A., and Aburto-Oropeza, O., 2016, Continental rupture and the creation of new crust in the Salton Trough rift, southern California and northern Mexico: Results from the Salton Seismic Imaging Project: Journal of Geophysical Research, v. 121, no. 10, p. 7469-7489, https://doi.org/10.1002/2016JB013139.","productDescription":"21 p.","startPage":"7469","endPage":"7489","ipdsId":"IP-078823","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470481,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jb013139","text":"Publisher Index Page"},{"id":347515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.3946533203125,\n 33.815666308702774\n ],\n [\n -115.28503417968751,\n 31.611287945395063\n ],\n [\n -114.14794921875,\n 31.695455797778713\n ],\n [\n -115.15869140624999,\n 32.7503226078097\n ],\n [\n -115.28503417968751,\n 33.31216783738619\n ],\n [\n -116.3946533203125,\n 33.815666308702774\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-30","publicationStatus":"PW","scienceBaseUri":"5a07e9bce4b09af898c8cc45","contributors":{"authors":[{"text":"Han, Liang","contributorId":49690,"corporation":false,"usgs":true,"family":"Han","given":"Liang","email":"","affiliations":[],"preferred":false,"id":716014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hole, John A.","contributorId":104801,"corporation":false,"usgs":true,"family":"Hole","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":716015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Joann M.","contributorId":21057,"corporation":false,"usgs":true,"family":"Stock","given":"Joann","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuis, Gary S. 0000-0002-3078-1544 fuis@usgs.gov","orcid":"https://orcid.org/0000-0002-3078-1544","contributorId":2639,"corporation":false,"usgs":true,"family":"Fuis","given":"Gary","email":"fuis@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":716013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kell, Annie","contributorId":68176,"corporation":false,"usgs":true,"family":"Kell","given":"Annie","affiliations":[],"preferred":false,"id":716017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Driscoll, Neal W.","contributorId":63266,"corporation":false,"usgs":true,"family":"Driscoll","given":"Neal","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":716019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kent, Graham M.","contributorId":75819,"corporation":false,"usgs":true,"family":"Kent","given":"Graham","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716018,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rymer, Michael J. mrymer@usgs.gov","contributorId":1522,"corporation":false,"usgs":true,"family":"Rymer","given":"Michael","email":"mrymer@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":716020,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gonzalez-Fernandez, Antonio","contributorId":84648,"corporation":false,"usgs":true,"family":"Gonzalez-Fernandez","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":716021,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Aburto-Oropeza, Octavio","contributorId":91784,"corporation":false,"usgs":true,"family":"Aburto-Oropeza","given":"Octavio","email":"","affiliations":[],"preferred":false,"id":716022,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}