{"pageNumber":"345","pageRowStart":"8600","pageSize":"25","recordCount":41079,"records":[{"id":70202797,"text":"ofr20191031 - 2019 - Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide","interactions":[],"lastModifiedDate":"2019-04-05T14:49:39","indexId":"ofr20191031","displayToPublicDate":"2019-04-01T12:03:46","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1031","displayTitle":"Life-History Model for Sockeye Salmon (Oncorhynchus nerka) at Lake Ozette, Northwestern Washington—Users’ Guide","title":"Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide","docAbstract":"

Salmon populations spawning in the Lake Ozette watershed of northwestern Washington were once sufficiently abundant to support traditional Tribal fisheries, and were later harvested by settlers. However, in 1974 and 1975, the sockeye salmon (Oncorhynchus nerka) harvest decreased to 0 from a high of more than 17,500 in 1949, thus stimulating research into the causes of decrease, which resulted in eventual listing of the population as threatened under the Endangered Species Act in 1999. The listing status was upheld in 2005 and 2014 following 5-year reviews. Meanwhile, research results were compiled in a limiting factors analysis (LFA) and a recovery plan was developed. Although there has been some improvement in sockeye abundance since listing, the numbers remain too low to allow harvest and it is not yet clear which of the many potential limiting factors are most consequential.

As part of the LFA process, a population model was developed to determine values of life-history parameters that would enable the population to survive for 100 years. The model was based on the best available data, but data are limited for the Lake Ozette system. Results informed the qualitative assessment of the importance of limiting factors used to develop the recovery plan for Lake Ozette sockeye. The model was built in Microsoft Excel® and is difficult to use. The purpose of the model described herein is to synthesize the results of the LFA in a form that can be manipulated by resource managers and the public to create scenarios, test hypotheses, and observe sensitivities of results to changes in parameters. The goal is to provide a tool that enables research, monitoring and management to be focused on the most impactful elements and processes, including identifying the information gaps that are most critical to fill.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191031","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Woodward, A., Haggerty, M., and Crain, P., 2019, Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide: U.S. Geological Survey Open-File Report 2019-1031, 79 p., https://doi.org/10.3133/ofr20191031.","productDescription":"viii, 79 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-101934","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1031/coverthb.jpg"},{"id":362634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1031/ofr20191031.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1031"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Ozette","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.68074798583986,\n 48.033560004128255\n ],\n [\n -124.59320068359374,\n 48.033560004128255\n ],\n [\n -124.59320068359374,\n 48.15509285476017\n ],\n [\n -124.68074798583986,\n 48.15509285476017\n ],\n [\n -124.68074798583986,\n 48.033560004128255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-04-01","noUsgsAuthors":false,"publicationDate":"2019-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodward, Andrea 0000-0003-0604-9115 awoodward@usgs.gov","orcid":"https://orcid.org/0000-0003-0604-9115","contributorId":3028,"corporation":false,"usgs":true,"family":"Woodward","given":"Andrea","email":"awoodward@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":760058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haggerty, Mike","contributorId":214494,"corporation":false,"usgs":false,"family":"Haggerty","given":"Mike","email":"","affiliations":[{"id":39056,"text":"Haggerty Consulting","active":true,"usgs":false}],"preferred":false,"id":760059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crain, Patrick","contributorId":214495,"corporation":false,"usgs":false,"family":"Crain","given":"Patrick","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":760060,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203433,"text":"70203433 - 2019 - Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem","interactions":[],"lastModifiedDate":"2019-05-14T11:56:23","indexId":"70203433","displayToPublicDate":"2019-04-01T11:56:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem","docAbstract":"Grizzly bear (Ursus arctos) conflicts with humans, including livestock depredation on public\nland grazing allotments, have increased during the last several decades within the Greater Yellowstone Ecosystem (GYE) in the western United States as the grizzly bear population has grown in number and occupied range. Minimizing conflicts and improving conservation efficacy requires information on the relationships between livestock depredations, allotment management, grizzly bear habitat conditions, and their interactions. We used generalized linear mixed models to evaluate spatio-temporal relationships between grizzly bear depredation of livestock and the characteristics of 316 United States Department of Agriculture Forest Service and National Park Service grazing allotments in the GYE during 1992–2014. We evaluated relationships at 2 spatial extents, representing daily and annual grizzly bear activity areas. During the study period, more grazing allotments became occupied by grizzly bears and most livestock depredations were associated with these areas of population expansion. Number of livestock (beta = 1.15 +/- 0.19 [SE]) and grizzly bear density index (beta = 1.13 +/- 0.10) had the greatest effects on the number of livestock depredation events relative to other allotment attributes. Estimated number of depredation events increased by approximately 20% when cow-calf pairs increased by 100 pairs and grizzly bear density index increased by 1 bear/196 km2 (the average annual home-range size of a female grizzly bear in the GYE). Additionally, grazing allotment size was positively related to the number of depredation events (beta = 0.56 +/- 0.16), whereas the presence of bull cattle or horses was associated with an approximately 50% reduction in depredations (beta = -0.71 +/- 0.37). Livestock depredation events were greater for allotments with lower road density (beta = -0.89 +/- 0.28), less rugged terrain (beta = -0.57 +/- 0.25), higher vegetative primary productivity (beta = 0.33 +/- 0.16), and more whitebark pine coverage (beta = 0.30 +/- 0.15). Relationships between depredations and grizzly bear habitat conditions varied across spatial extents. As the grizzly bear population continues to expand, natural resource managers and livestock producers could focus efforts on allotments with a higher density of grizzly bears, fewer roads, and quality grizzly bear habitat, including higher vegetative productivity, when developing cooperative management plans and preventative measures to reduce the likelihood of depredation. The perspectives gained from our analysis provide context for long-term, landscape-level planning to accommodate livestock production on public lands while meeting conservation goals for grizzly bears.","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21618","usgsCitation":"Wells, S.L., McNew, L.B., Tyers, D.B., van Manen, F.T., and Thompson, D.J., 2019, Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem: Journal of Wildlife Management, v. 83, no. 3, p. 556-566, https://doi.org/10.1002/jwmg.21618.","productDescription":"11 p.","startPage":"556","endPage":"566","ipdsId":"IP-096436","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21618","text":"Publisher Index Page"},{"id":363764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.32421875,\n 43.54854811091286\n ],\n [\n -109.0283203125,\n 43.54854811091286\n ],\n [\n -109.0283203125,\n 45.36758436884978\n ],\n [\n -112.32421875,\n 45.36758436884978\n ],\n [\n -112.32421875,\n 43.54854811091286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Smith L.","contributorId":215575,"corporation":false,"usgs":false,"family":"Wells","given":"Smith","email":"","middleInitial":"L.","affiliations":[{"id":39286,"text":"Montana State University, Department of Animal and Range Sciences","active":true,"usgs":false}],"preferred":false,"id":762689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNew, Lance B.","contributorId":190322,"corporation":false,"usgs":false,"family":"McNew","given":"Lance","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":762690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyers, Daniel B.","contributorId":124587,"corporation":false,"usgs":false,"family":"Tyers","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":5129,"text":"U.S. Forest Service, 2327 University Way, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":762691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":762688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":762692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203046,"text":"70203046 - 2019 - Effects of climate, regulation, and urbanization on historical flood trends in the United States","interactions":[],"lastModifiedDate":"2019-04-15T10:57:39","indexId":"70203046","displayToPublicDate":"2019-04-01T10:57:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of climate, regulation, and urbanization on historical flood trends in the United States","docAbstract":"Many studies have analyzed historical trends in annual peak flows in the United States because of the importance of flooding to bridges and other structures, and the concern that human influence may increase flooding. To help attribute causes of historical peak-flow changes, it is important to separate basins by characteristics that have different influences on peak flows. We analyzed historical trends by basin type: minimally altered basins, regulated basins (substantial reservoir storage but low urbanization), and urbanized basins (with low reservoir storage). Although many peak-flow magnitude changes were found in the last century across the conterminous United States, the trend magnitude and direction vary strongly by basin type and region. In general, there was a low percentage of significant increases and decreases for minimally altered basins while many regulated basins had significant decreases and the limited number of urbanized basins with long-term record showed a high percentage of increases. For urbanized basins, which are concentrated in the Northeast and Midwest, trend magnitude was significantly correlated with the amount of basin urbanization. For all basins regardless of type, parts of the Northeast quadrant of the U.S. had high concentrations of basins with large and significant increases while parts of the Southwest quadrant had high concentrations of basins with large and significant decreases. Basin regulation appears to have heavily influenced the decreasing trends in the Southwest quadrant; there were many large decreases for this basin type despite overall increases in heavy precipitation in this area. Changes over time in the number of 2-per-year and 1-per-5-year peaks over threshold are consistent with changes in the magnitude of annual peak flows.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.03.102","usgsCitation":"Hodgkins, G., Dudley, R., Archfield, S., and Renard, B., 2019, Effects of climate, regulation, and urbanization on historical flood trends in the United States: Journal of Hydrology, v. 573, p. 697-709, https://doi.org/10.1016/j.jhydrol.2019.03.102.","productDescription":"13 p.","startPage":"697","endPage":"709","ipdsId":"IP-099282","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":362951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n 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Robert","contributorId":214834,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":214835,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":760922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Renard, Benjamin","contributorId":177291,"corporation":false,"usgs":false,"family":"Renard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":760923,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202863,"text":"70202863 - 2019 - Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?","interactions":[],"lastModifiedDate":"2019-07-23T13:19:12","indexId":"70202863","displayToPublicDate":"2019-04-01T10:52:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?","docAbstract":"

Occupancy models are widely applied to estimate species distributions, but few methods exist for model checking. Thorough model assessments can uncover inadequacies and allow for deeper ecological insight by exploring structure in the observed data not accounted for by a model. We introduce occupancy model residual definitions that utilize the posterior distribution of the partially latent occupancy states. Residual‐based assessments are valuable because they can target specific assumptions and identify ways to improve a model, such as adding spatial correlation or meaningful covariates. Our approach defines separate residuals for occupancy and detection, and we use simulation to examine whether missing structure for modeling detection probabilities can be distinguished from that for occupancy probabilities. In many scenarios, our residual diagnostics were able to successfully separate inadequacies at the different model levels, but we describe other situations when this may not be the case. Applying Moran's I residual diagnostics to assess models for silver‐haired (Lasionycteris noctivagans) and little brown (Myotis lucifugus) bats only provided evidence of residual spatial correlation among detections. Targeting specific model assumptions using carefully chosen residual diagnostics is valuable for any analysis, and we remove previous barriers for occupancy analyses — lack of examples and practical advice.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2703","usgsCitation":"Wright, W., Irvine, K., and Higgs, M.D., 2019, Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?: Ecology, v. 100, no. 6, e02703, https://doi.org/10.1002/ecy.2703.","productDescription":"e02703","ipdsId":"IP-088414","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467749,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.2703","text":"External Repository"},{"id":362650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Wilson 0000-0003-4276-3850","orcid":"https://orcid.org/0000-0003-4276-3850","contributorId":214592,"corporation":false,"usgs":true,"family":"Wright","given":"Wilson","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":760332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":214591,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":760331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgs, Megan D.","contributorId":127365,"corporation":false,"usgs":false,"family":"Higgs","given":"Megan","email":"","middleInitial":"D.","affiliations":[{"id":6916,"text":"Department of Mathematical Sciences, Montana State University, Bozeman, USA","active":true,"usgs":false}],"preferred":false,"id":760333,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199964,"text":"70199964 - 2019 - Geospatial data mining for digital raster mapping","interactions":[],"lastModifiedDate":"2024-05-17T15:09:45.727773","indexId":"70199964","displayToPublicDate":"2019-04-01T10:38:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Geospatial data mining for digital raster mapping","docAbstract":"

We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2018.1517445","usgsCitation":"Wylie, B.K., Pastick, N.J., Picotte, J.J., and Deering, C., 2019, Geospatial data mining for digital raster mapping: GIScience and Remote Sensing, v. 56, no. 3, p. 406-429, https://doi.org/10.1080/15481603.2018.1517445.","productDescription":"14 p.","startPage":"406","endPage":"429","ipdsId":"IP-094736","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499974,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/7c16e86b33fd456cb54a7bd63a3e2985","text":"External Repository"},{"id":358204,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f76e4b0fc368eb53837","contributors":{"authors":[{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":747499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":747500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","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":747501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deering, Carol 0000-0003-3565-6264 cdeering@usgs.gov","orcid":"https://orcid.org/0000-0003-3565-6264","contributorId":3001,"corporation":false,"usgs":true,"family":"Deering","given":"Carol","email":"cdeering@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":747502,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203004,"text":"70203004 - 2019 - Diverse late‐stage crystallization and storage conditions in melt domains from the Youngest Toba Tuff revealed by age and compositional heterogeneity in the last increment of accessory phase growth","interactions":[],"lastModifiedDate":"2019-08-15T11:55:37","indexId":"70203004","displayToPublicDate":"2019-04-01T10:18:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Diverse late‐stage crystallization and storage conditions in melt domains from the Youngest Toba Tuff revealed by age and compositional heterogeneity in the last increment of accessory phase growth","docAbstract":"The chemical record contained within the nal increment of growth on crystals is utilized to reveal the dynamics and time- scales of magma assembly and storage before eruption of the cataclysmic 2800 km3 Youngest Toba Tu (YTT), Indonesia. In situ U–Th disequilibrium dates and trace element concentrations were obtained via secondary ionization mass spectrometry (SIMS) on unsectioned and unpolished faces of individual zircon and allanite crystals. The six high-silica (> 73 wt% SiO2) pumices from which crystals were derived are among the more evolved and lower crystallinity (< 25 wt%) pumices from the YTT eruption, and likely represent the melt-dominated portion of the magma system. Discrete SIMS measurement cycles were coupled with statistical treatments to detect zircon and allanite surface zoning domains at the ~ 1 μm scale. Coupled r-MELTS and accessory phase saturation modeling indicates that at the granite ternary minimum or ‘eutectoid’ conditions that de ne this portion of the YTT, zircon and allanite crystallization is dependent on and proportionate to major phase crystallization, and is more limited than at pre-eutectoid conditions. A lower proportion of near-eruption zircon surface ages in the comparatively cool and wet YTT relative to other hotter and drier voluminous silicic eruptions could re ect the in u- ence of eutectoid storage conditions on magmatic responses to remobilization-related magmatic recharge.","language":"English","publisher":"Springer","doi":"10.1007/s00410-019-1566-6","usgsCitation":"Tierney, C.R., Reid, M.R., Vazquez, J.A., and Chesner, C.A., 2019, Diverse late‐stage crystallization and storage conditions in melt domains from the Youngest Toba Tuff revealed by age and compositional heterogeneity in the last increment of accessory phase growth: Contributions to Mineralogy and Petrology, v. 174, 31, 21 p., https://doi.org/10.1007/s00410-019-1566-6.","productDescription":"31, 21 p.","ipdsId":"IP-106418","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":362910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Youngest Toba Tuff","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 98.41827392578125,\n 2.2324061399778894\n ],\n [\n 99.30816650390625,\n 2.2324061399778894\n ],\n [\n 99.30816650390625,\n 2.981441678317486\n ],\n [\n 98.41827392578125,\n 2.981441678317486\n ],\n [\n 98.41827392578125,\n 2.2324061399778894\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"174","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Tierney, Casey R.","contributorId":214772,"corporation":false,"usgs":false,"family":"Tierney","given":"Casey","email":"","middleInitial":"R.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":760745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mary R.","contributorId":192856,"corporation":false,"usgs":false,"family":"Reid","given":"Mary","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":760746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":760744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chesner, Craig A.","contributorId":214773,"corporation":false,"usgs":false,"family":"Chesner","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":760747,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203198,"text":"70203198 - 2019 - Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps","interactions":[],"lastModifiedDate":"2019-04-29T08:57:06","indexId":"70203198","displayToPublicDate":"2019-04-01T08:56:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps","docAbstract":"Monitoring ichthyoplankton is useful for identifying reproductive fronts and spawning locations of bigheaded carps (Hypophthalmichthys spp.). Unfortunately, sorting and identifying ichthyoplankton to monitor for bigheaded carp reproduction is time consuming and expensive. Traditional methods require frequent egg-larvae sampling, sorting of all samples to obtain presumptively identified bigheaded carp, and genetic validation of presumptively identified eggs. Quantitative PCR (qPCR) has the potential to streamline this process by identifying samples that likely do or do not contain a target species. Our objective was to develop a genetic screening tool using qPCR with the duplex assays SCTM4/5 and BHTM1/2 to prioritize samples that have a higher likelihood of containing bigheaded carp eggs or larvae. We used tandem ichthyoplankton samples collected for monitoring bigheaded carps in the Upper Mississippi, Illinois, and St. Croix rivers to evaluate the effectiveness of qPCR as a screening tool. Samples with > 10,000 copies of DNA had 100% occurrence of bigheaded carp eggs or larvae in the traditionally sorted samples, whereas samples with < 10 copies of DNA had 0% occurrence of ichthyoplankton from these invasive species. We used a logistic regression model to calculate the probability of finding bigheaded carp eggs or larvae based upon the number of DNA copies; 406 copies corresponded with a 50% probability of having bigheaded carp ichthyoplankton present in a sample. These data can be used to inform management actions (i.e., control, containment) for these invasive fishes, and this tool could be adapted for monitoring for reproduction of other aquatic invasive species.","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1887-9","usgsCitation":"Fritts, A.K., Knights, B.C., Larson, J.H., Amberg, J., Merkes, C.M., Tajjioui, T., Butler, S.E., Diana, M.J., Wahl, D.H., Weber, M.J., and Waters, J.D., 2019, Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps: Biological Invasions, v. 21, no. 4, p. 1143-1153, https://doi.org/10.1007/s10530-018-1887-9.","productDescription":"11 p.","startPage":"1143","endPage":"1153","ipdsId":"IP-100744","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467750,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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]\n}","volume":"21","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Fritts, Andrea K. 0000-0003-2142-3339","orcid":"https://orcid.org/0000-0003-2142-3339","contributorId":204594,"corporation":false,"usgs":true,"family":"Fritts","given":"Andrea","email":"","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences 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0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tajjioui, Tariq 0000-0002-0113-0451","orcid":"https://orcid.org/0000-0002-0113-0451","contributorId":215091,"corporation":false,"usgs":true,"family":"Tajjioui","given":"Tariq","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Butler, Steven E.","contributorId":206527,"corporation":false,"usgs":false,"family":"Butler","given":"Steven","email":"","middleInitial":"E.","affiliations":[{"id":37336,"text":"Illinois Natural History Survey, Kaskaskia Biological Station","active":true,"usgs":false}],"preferred":false,"id":761607,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Diana, Matthew J.","contributorId":206528,"corporation":false,"usgs":false,"family":"Diana","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":761608,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wahl, David H.","contributorId":206529,"corporation":false,"usgs":false,"family":"Wahl","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37336,"text":"Illinois Natural History Survey, Kaskaskia Biological Station","active":true,"usgs":false}],"preferred":false,"id":761609,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weber, Michael J. 0000-0003-0430-3087","orcid":"https://orcid.org/0000-0003-0430-3087","contributorId":210835,"corporation":false,"usgs":false,"family":"Weber","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":761610,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Waters, John D.","contributorId":215092,"corporation":false,"usgs":false,"family":"Waters","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":761611,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70210142,"text":"70210142 - 2019 - Increased nesting success of Hawaii Elepaio in response to the removal of invasive black rats","interactions":[],"lastModifiedDate":"2020-05-15T13:45:50.949288","indexId":"70210142","displayToPublicDate":"2019-04-01T08:39:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Increased nesting success of Hawaii Elepaio in response to the removal of invasive black rats","docAbstract":"In Hawaii and other oceanic islands with few native land mammals, black rats (Rattus rattus) are among the most damaging invasive vertebrate species to native forest bird populations and habitats, due to their arboreal behavior and generalist foraging habits and habitat use. We evaluated the nesting response of Hawaii Elepaio (Chasiempis sandwichensis; Monarchidae), a generalist insectivore, to the removal of black rats using rodenticide in a before-after-control-impact study in high- and low-elevation mesic montane habitat recovering from long-term damage from introduced ungulates and weeds. We monitored nesting success and rat abundance during 2015–2016 before applying rodenticide bait in 2017 to remove rats from two 700 × 700 m treatment plots that were paired with 2 nontreatment plots of the same size. Rat abundance was reduced by 90% during treatment, with combined variables treatment and elevation best explaining the change using GLM methods and AIC model selection. The daily survival rate (DSR) of nests (n = 191) was greater on treated plots after rodenticide application (mean ± SE = 0.980 ± 0.004 treatment; 0.964 ± 0.004 nontreatment), modeled nest success increased from 29% to 50%, and apparent nest success (number of successful nests per total nests) increased from 37% to 52%. The most informative model for predicting DSR included the effect of treatment. Predation by rats was documented at 3 of 16 nests using video surveillance, and we observed additional evidence of rat predation during in-person nest monitoring. Rats targeted adults on the nest and sometimes removed intact eggs, leaving little trace of their activity. Our results demonstrate that reducing rat predation can immediately improve the nesting success of even a common bird species in habitat with a long history of forest restoration. Sustained predator control may be critical to accelerating the recovery of native forest bird communities.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duz003","collaboration":"","usgsCitation":"Banko, P.C., Jaenecke, K., Peck, R., and Brinck, K.W., 2019, Increased nesting success of Hawaii Elepaio in response to the removal of invasive black rats: Condor, v. 121, no. 2, duz003, 12 p., https://doi.org/10.1093/condor/duz003.","productDescription":"duz003, 12 p.","ipdsId":"IP-080105","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":467752,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duz003","text":"Publisher Index Page"},{"id":437519,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93TOM58","text":"USGS data release","linkHelpText":"Hawaii Volcanoes National Park Elepaio nest monitoring and black rat mark recapture data 2015-2017"},{"id":374869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.46728515625,\n 18.87510275035649\n ],\n [\n -154.75341796875,\n 18.87510275035649\n ],\n [\n -154.75341796875,\n 20.365227537412434\n ],\n [\n -156.46728515625,\n 20.365227537412434\n ],\n [\n -156.46728515625,\n 18.87510275035649\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":789282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaenecke, Kelly 0000-0002-7124-4788","orcid":"https://orcid.org/0000-0002-7124-4788","contributorId":211063,"corporation":false,"usgs":false,"family":"Jaenecke","given":"Kelly","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":789283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":789284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":150936,"corporation":false,"usgs":false,"family":"Brinck","given":"Kevin","email":"kbrinck@usgs.gov","middleInitial":"W.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":789285,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203203,"text":"70203203 - 2019 - Consequences of ignoring spatial variation in population trend when conducting a power analysis","interactions":[],"lastModifiedDate":"2019-04-29T08:39:06","indexId":"70203203","displayToPublicDate":"2019-04-01T08:38:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of ignoring spatial variation in population trend when conducting a power analysis","docAbstract":"Long-term, large-scale monitoring programs are becoming increasingly common to document status and trends of wild populations. A successful program for monitoring population trend hinges on the ability to detect the trend of interest. Power analyses are useful for quantifying the sample size needed for trend detection, given expected variation in the population. Four components of variation (within-year variation at a given site, interannual variation within a site, variation among sites in the interannual variation, and variation among sites in mean abundance or density) are commonly considered in power analyses for population trend, but a fifth is not: variation among sites in the local trend. Spatial variation in trend is expected to reduce statistical power, but the magnitude of this reduction has not been fully explored. We used computer simulations to evaluate the consequences of ignoring spatial variation in trend under a variety of sampling designs and wide ranges of other components of variation. The effect of spatial variation in trend on power was minor when other input parameters took extreme values that made the trend either very difficult or very easy to detect. However, at moderate values of the other parameters, spatial variation in trend had a strong effect, reducing statistical power by up to 60%. In some cases, ignoring spatial variation in trend resulted in an 80% probability of a Type I error (falsely detecting a trend in a stable population). Spatial variation in trend is therefore an important consideration when designing a long-term monitoring program for many species, especially those affected by local conditions at sites that are repeatedly surveyed. If variation in trend is ignored, as in most previous power analyses, the recommended sampling design will likely be insufficient to detect the trend of interest and lead to potentially false conclusions of a stable population.","language":"English","publisher":"Wiley-Blackwell","doi":"10.1111/ecog.04093","usgsCitation":"Weiser, E.L., Diffendorfer, J., Lopez-Hoffman, L., Semmens, D.J., and Thogmartin, W.E., 2019, Consequences of ignoring spatial variation in population trend when conducting a power analysis: Ecography, v. 42, no. 4, p. 836-844, https://doi.org/10.1111/ecog.04093.","productDescription":"9 p.","startPage":"836","endPage":"844","ipdsId":"IP-091066","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437520,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SFUH2K","text":"USGS data release","linkHelpText":"Power analysis code"},{"id":363285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":761631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":761632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":761633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":761634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":761635,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203136,"text":"70203136 - 2019 - AVO-G2S: A modified, open-source Ground-to-Space atmospheric specification for infrasound modeling","interactions":[],"lastModifiedDate":"2019-04-24T08:16:39","indexId":"70203136","displayToPublicDate":"2019-04-01T08:16:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"AVO-G2S: A modified, open-source Ground-to-Space atmospheric specification for infrasound modeling","docAbstract":"To facilitate infrasound propagation studies, we present AVO-G2S, an open-source, Ground-to-Space model which provides temperature and wind specifications from the surface to an altitude of 225 km. This model provides a means of smoothly characterizing atmospheric conditions using multiple numerical weather prediction forecast and reanalysis products, along with upper-atmospheric empirical models. Regional atmospheric reconstructions only require a limited domain and can utilize high-resolution numerical weather prediction forecasts typically provided\non a projected grid. The use of a projected grid allows for faster spectral transform libraries to be\nemployed. The AVO-G2S software can also provide global reconstructions that rely on global\nnumerical weather prediction products and spherical harmonic decompositions. AVO-G2S is inspired by a global Ground-to-Space model developed by the Naval Research Laboratory, and relies on their empirical descriptions of upper-atmospheric conditions. Alaska Volcano Observatory has implemented this model for near-real-time infrasound monitoring of volcanic eruptions and historical research projects.","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2018.12.013","usgsCitation":"Schwaiger, H., Iezzi, A., and Fee, D., 2019, AVO-G2S: A modified, open-source Ground-to-Space atmospheric specification for infrasound modeling: Computers & Geosciences, v. 125, p. 90-97, https://doi.org/10.1016/j.cageo.2018.12.013.","productDescription":"8 p.","startPage":"90","endPage":"97","ipdsId":"IP-091624","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cageo.2018.12.013","text":"Publisher Index Page"},{"id":363165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schwaiger, Hans 0000-0001-7397-8833","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":214983,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":761353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":761354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fee, David","contributorId":199660,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[],"preferred":false,"id":761355,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203230,"text":"70203230 - 2019 - Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2019-05-02T08:07:59","indexId":"70203230","displayToPublicDate":"2019-04-01T07:46:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","docAbstract":"

Understanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota.

","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2711","usgsCitation":"Mcintyre, N., Liu, G., Gorzo, J., Wright, C., Guntenspergen, G.R., and Schwartz, F., 2019, Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region: Ecosphere, v. 10, no. 4, p. 1-18, https://doi.org/10.1002/ecs2.2711.","productDescription":"e02711, 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-101250","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467755,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2711","text":"Publisher Index Page"},{"id":363417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.2669,47.3268],[-98.8466,47.327],[-98.8392,47.327],[-98.8232,47.3272],[-98.8152,47.3271],[-98.4991,47.327],[-98.467,47.3266],[-98.4677,47.2402],[-98.4685,46.9788],[-98.4412,46.9789],[-98.4396,46.6296],[-98.7894,46.6294],[-99.0379,46.6309],[-99.1616,46.6317],[-99.4122,46.6316],[-99.4498,46.6319],[-99.4477,46.8044],[-99.4476,46.9788],[-99.4821,46.9795],[-99.4824,47.0089],[-99.4822,47.0162],[-99.4821,47.0249],[-99.4826,47.0396],[-99.4827,47.1558],[-99.4801,47.3267],[-99.2669,47.3268]]]},\"properties\":{\"name\":\"Stutsman\",\"state\":\"ND\"}}]}","volume":"10","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcintyre, N.E.","contributorId":215186,"corporation":false,"usgs":false,"family":"Mcintyre","given":"N.E.","email":"","affiliations":[{"id":39194,"text":"Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409-3131 USA","active":true,"usgs":false}],"preferred":false,"id":761798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, G.","contributorId":215187,"corporation":false,"usgs":false,"family":"Liu","given":"G.","email":"","affiliations":[{"id":39195,"text":"School of Earth, Environment and Society, Bowling Green State University, 190 Overman Hall, Bowling Green, OH 43403 USA","active":true,"usgs":false}],"preferred":false,"id":761799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorzo, J.","contributorId":215188,"corporation":false,"usgs":false,"family":"Gorzo","given":"J.","affiliations":[{"id":39196,"text":"Natural Resources Research Institute, University of Minnesota-Duluth, 5013 Miller Trunk Hwy., Duluth, MN 55811 USA","active":true,"usgs":false}],"preferred":false,"id":761800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, C.K.","contributorId":215189,"corporation":false,"usgs":false,"family":"Wright","given":"C.K.","email":"","affiliations":[{"id":39196,"text":"Natural Resources Research Institute, University of Minnesota-Duluth, 5013 Miller Trunk Hwy., Duluth, MN 55811 USA","active":true,"usgs":false}],"preferred":false,"id":761801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":761797,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, F.","contributorId":215190,"corporation":false,"usgs":false,"family":"Schwartz","given":"F.","email":"","affiliations":[{"id":39197,"text":"School of Earth Sciences, 275 Mendenhall Laboratory, 125 S. Oval Mall, Ohio State University, Columbus, OH 43210 USA","active":true,"usgs":false}],"preferred":false,"id":761802,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203279,"text":"70203279 - 2019 - Investigation of recent decadal-scale cyclical fluctuations in salinity in the lower Colorado river","interactions":[],"lastModifiedDate":"2020-12-10T13:17:05.905551","indexId":"70203279","displayToPublicDate":"2019-04-01T07:07:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Investigation of recent decadal-scale cyclical fluctuations in salinity in the lower Colorado river","docAbstract":"

Beginning in the late 1970s, 10- to 15-year cyclical oscillations in salinity were observed at lower Colorado River monitoring sites, moving upstream from the international border with Mexico, above Imperial Dam, below Hoover Dam, and at Lees Ferry. The cause of these cyclical trends in salinity was unknown. These salinity cycles complicate the U.S. Bureau of Reclamation's (Reclamation) responsibility for managing salinity in the river for delivery of water to Mexico to meet treaty obligations. This study develops a conceptual model of the salinity cycles from time-series water quality, streamflow, and precipitation data in both the lower and upper Colorado River Basins in order to provide Reclamation the ability to understand, anticipate, and manage future salinity cycles in the lower river. Compared with the Lees Ferry record, both maximum and minimum salinity levels increase downstream by about 25% at Hoover Dam, by about 49% at Imperial Dam, and by about 69% at the northern international boundary with Mexico. In the upper basin, cyclical salinity trends are evident at the outflow of three major tributaries, where salinity is also noted to be inversely related to streamflow. Time series trends in precipitation within the catchments of the three upper basin tributaries indicate cyclical periods with above normal precipitation and periods with below normal precipitation. Periods of greater than normal precipitation in the contributing areas correspond with declines in salinity at the catchment monitoring sites and periods of less than normal precipitation correspond with rising salinity at the sites. Based on the conceptual model developed in this investigation, a multiple linear regression model was developed using a stepwise variable selection procedure to simulate salinity in Lake Powell inflow. Important variables in the explanation of salinity entering Lake Powell include flow from the three upper basin tributaries, seasonality, and mean precipitation in the upper basin, among others. The root mean square error of prediction for the MLR model was 31.48 mg/L (5.7%).

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2019.01.072","usgsCitation":"Tillman, F.D., Coes, A.L., Anning, D., Mason, J.P., and Coplen, T.B., 2019, Investigation of recent decadal-scale cyclical fluctuations in salinity in the lower Colorado river: Journal of Environmental Management, no. 235, p. 442-452, https://doi.org/10.1016/j.jenvman.2019.01.072.","productDescription":"11 p.","startPage":"442","endPage":"452","ipdsId":"IP-099744","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":363467,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.10400390625,\n 30.751277776257812\n ],\n [\n -104.91943359374999,\n 30.751277776257812\n ],\n [\n -104.91943359374999,\n 42.69858589169842\n ],\n [\n -114.10400390625,\n 42.69858589169842\n ],\n [\n -114.10400390625,\n 30.751277776257812\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"235","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coes, Alissa L. 0000-0001-6682-5417 alcoes@usgs.gov","orcid":"https://orcid.org/0000-0001-6682-5417","contributorId":4231,"corporation":false,"usgs":true,"family":"Coes","given":"Alissa","email":"alcoes@usgs.gov","middleInitial":"L.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anning, David W. 0000-0002-4470-3387","orcid":"https://orcid.org/0000-0002-4470-3387","contributorId":202783,"corporation":false,"usgs":true,"family":"Anning","given":"David W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mason, Jon P. 0000-0003-0576-5494 jmason@usgs.gov","orcid":"https://orcid.org/0000-0003-0576-5494","contributorId":196854,"corporation":false,"usgs":true,"family":"Mason","given":"Jon","email":"jmason@usgs.gov","middleInitial":"P.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":762020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":762021,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206198,"text":"70206198 - 2019 - Patterns of primary production and ecological drought in Yellowstone","interactions":[],"lastModifiedDate":"2019-10-25T07:06:17","indexId":"70206198","displayToPublicDate":"2019-04-01T07:05:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3802,"text":"Yellowstone Science","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of primary production and ecological drought in Yellowstone","docAbstract":"Introduction: Photosynthesis converts sunlight into stored energy in millions of leaves, flowers and seeds that maintain the web of life in Yellowstone. This transformation of energy fixes carbon, supplies organic matter to soils, and can become fuel for wildfire. As the first link of the food chain, new plant biomass is called primary production and provides energy to consumers, including wildlife. While Yellowstone is a mountain environment with deep winter snowpack, the park can get very dry in some years as evidenced by massive wildfires in 1988 and 2016. Droughts like these not only contribute to fire potential, but they affect primary production, the food chain and likely will play an increasingly important role in transforming vegetation structure and composition in the future. Meteorological, agricultural, and hydrological drought have been assessed quantitatively for many years, but key indicators of drought in wildland ecosystems have not been formally defined until recently (Crausbay et al., 2017). One promising new method to do this is by measuring how vegetation responds to negative effects of drought, and positive effects of favorable conditions that offset negative effects of drought. The balance of drought stress and growth has important implications for future vegetation condition as the climate of Yellowstone changes. \nMonitoring primary production, and predicting future vegetation changes are needed to provide a comprehensive view of park health and anticipate future ecosystem changes (Crabtree et al. 2009, Nemani et al. 2009). Although an important indicator of ecosystem condition, primary production can be time and resource-intensive to monitor in wildland settings using traditional ground-based methods such as clipping and weighing. Fortunately, ground-based methods can be complemented and enhanced by monitoring primary production with satellite imagery. Measurements of solar radiation reflectance in visible and near infra-red wavelengths can indicate primary production at frequent weekly intervals from the Moderate Resolution Imaging Spectrometer (MODIS) on satellites operated by NASA. The Greater Yellowstone Inventory and Monitoring Network (GRYN) uses this information to track changes in primary production across Yellowstone over time. They link these measurements to vegetation types, soils, and climate to understand where and when changes in production have occurred and may occur in the future.","language":"English","publisher":"National Park Service","usgsCitation":"Thoma, D.P., Munson, S.M., Rodman, A.W., Renkin, R., Anderson, H.M., and Wacker, S.D., 2019, Patterns of primary production and ecological drought in Yellowstone: Yellowstone Science, v. 27, no. 1, p. 34-39.","productDescription":"6 p.","startPage":"34","endPage":"39","ipdsId":"IP-112293","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":368590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368571,"type":{"id":11,"text":"Document"},"url":"https://www.nps.gov/articles/patterns-of-primary-production-ecological-drought-in-yellowstone.htm"}],"country":"United States","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.09374999999999,\n 43.76712702120528\n ],\n [\n -109.1766357421875,\n 43.76712702120528\n ],\n [\n -109.1766357421875,\n 45.05412098425883\n ],\n [\n -111.09374999999999,\n 45.05412098425883\n ],\n [\n -111.09374999999999,\n 43.76712702120528\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thoma, David P.","contributorId":197256,"corporation":false,"usgs":false,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":773824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":220026,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":773823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodman, Ann W.","contributorId":220027,"corporation":false,"usgs":false,"family":"Rodman","given":"Ann","email":"","middleInitial":"W.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":773825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Renkin, Roy","contributorId":220028,"corporation":false,"usgs":false,"family":"Renkin","given":"Roy","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":773826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Heidi M.","contributorId":220029,"corporation":false,"usgs":false,"family":"Anderson","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":773827,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wacker, Stephanie D.","contributorId":220030,"corporation":false,"usgs":false,"family":"Wacker","given":"Stephanie","email":"","middleInitial":"D.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":773828,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206399,"text":"70206399 - 2019 - Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook Salmon ESU","interactions":[],"lastModifiedDate":"2019-11-04T11:01:15","indexId":"70206399","displayToPublicDate":"2019-04-01T07:05:17","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook Salmon ESU","docAbstract":"The portion of the Snake River fall Chinook Salmon Oncorhynchus tshawytscha ESU that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2018 in association with U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, and (3) use of a small unmanned aerial system (sUAS) to search for fall Chinook salmon redds and carcasses. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence has been relatively stable, but effects of density dependence are evident in juvenile life stages. Apparent abundance of juvenile fall Chinook salmon has increased and we noted the following responses: parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier; growth rate (g/d) and dispersal size of parr declined; and passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use this information in a comprehensive modeling effort to conduct action-effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management Research, Monitoring, and Evaluation (RM&E).\n\nIn 2018, the U.S. Geological Survey (USGS) searched 10 shallow-water spawning sites and 25 deepwater spawning sites in conjunction with the Idaho Power Company (IPC). A total of 103 redds were counted at shallow-water sites and 61 redds were counted at deepwater sites. We recovered 17 carcasses and 13 live fish, which were spawned out, and collected biological information and tissue samples that are currently being analyzed for parentage to determine the percentage of hatchery-origin spawners on the spawning grounds.","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K.F., Perry, R., Plumb, J., Hance, D., Bickford, B., and Rhodes, T., 2019, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook Salmon ESU, iii, 54 p.","productDescription":"iii, 54 p.","ipdsId":"IP-109440","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":368864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368853,"type":{"id":11,"text":"Document"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P166057/79371-1.pdf"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.32226562500001,\n 41.80407814427234\n ],\n [\n -111.005859375,\n 41.80407814427234\n ],\n [\n -111.005859375,\n 46.9502622421856\n ],\n [\n -120.32226562500001,\n 46.9502622421856\n ],\n [\n -120.32226562500001,\n 41.80407814427234\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":220176,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220177,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumb, John M. 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hance, Dalton 0000-0002-4475-706X","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":220179,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bickford, Brad 0000-0003-3756-6588","orcid":"https://orcid.org/0000-0003-3756-6588","contributorId":220180,"corporation":false,"usgs":true,"family":"Bickford","given":"Brad","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rhodes, Tobyn 0000-0002-4023-4827","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":220181,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774405,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70204109,"text":"70204109 - 2019 - Geology of the Mineral and Lake Anna West Quadrangles, Virginia","interactions":[],"lastModifiedDate":"2019-07-10T09:20:59","indexId":"70204109","displayToPublicDate":"2019-03-31T17:04:09","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5845,"text":"Virginia Division of Geology and Mineral Resources Publication","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"189","title":"Geology of the Mineral and Lake Anna West Quadrangles, Virginia","docAbstract":"This map product is a cooperator series publication and, as such, does not have a specific abstract.\n\nGeologic mapping for this map product was completed between 2014 and 2017, with most of the field work occurring between January 2016 and May 2017. Numerous foot traverses were completed along creeks and roads throughout the field area; the shore of Lake Anna was accessed by kayak to provide additional data. Distributions of soil units were considered when assigning bedrock type in areas where outcrop was lacking and helped to distinguish fluvial terrace deposits. Hill-shade raster images created from LiDAR datasets and geophysical data sets proved useful in the field to trace bedrock and surficial units. GPS location control and field data were collected and recorded in digital databases using a variety of geologic mapping applications for an iPad 3rd Gen Model A1403 and Motion C5v tablet using Fieldmove 2013.1. Structural measurements were also plotted on field maps. Data collected included lithology and the orientation of foliations, folds, lineations, joints, and faults. Representative rock samples of significant formations were thin-sectioned for petrographic analysis; a few samples from these and surrounding quadrangles were analyzed for zircon U-Pb geochronology and geochemistry.","language":"English","publisher":"Virginia Department of Mines Minerals and Energy, Division of Geology and Mineral Resources","usgsCitation":"Carter, M.W., Burton, W.C., McAleer, R.J., DiGiacomo-Cohen, M., and Sauer, R.T., 2019, Geology of the Mineral and Lake Anna West Quadrangles, Virginia: Virginia Division of Geology and Mineral Resources Publication 189, Pamphlet: iv, 41 p.; 2 Plates: 37 x 59 and 32 x 47 inches.","productDescription":"Pamphlet: iv, 41 p.; 2 Plates: 37 x 59 and 32 x 47 inches","onlineOnly":"Y","ipdsId":"IP-099519","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":365402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365401,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.dmme.virginia.gov/commerce/ProductDetails.aspx?productID=3026"}],"country":"United States","state":"Virginia","county":"Louisa County, Orange County, Spotsylvania County","otherGeospatial":"Lake Anna Quadrangle, Mineral Quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.96585083007812,\n 37.93444993515032\n ],\n [\n -77.65960693359375,\n 37.93444993515032\n ],\n [\n -77.65960693359375,\n 38.1334763895322\n ],\n [\n -77.96585083007812,\n 38.1334763895322\n ],\n [\n -77.96585083007812,\n 37.93444993515032\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":765553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burton, William C. 0000-0001-7519-5787 bburton@usgs.gov","orcid":"https://orcid.org/0000-0001-7519-5787","contributorId":1293,"corporation":false,"usgs":true,"family":"Burton","given":"William","email":"bburton@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":765554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":765555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiGiacomo-Cohen, Mary 0000-0003-2384-8912","orcid":"https://orcid.org/0000-0003-2384-8912","contributorId":211592,"corporation":false,"usgs":true,"family":"DiGiacomo-Cohen","given":"Mary","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":765557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sauer, R. Tyler","contributorId":216797,"corporation":false,"usgs":false,"family":"Sauer","given":"R.","email":"","middleInitial":"Tyler","affiliations":[{"id":39519,"text":"C.F. Sauer Company","active":true,"usgs":false}],"preferred":false,"id":765556,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204415,"text":"70204415 - 2019 - A revised continuous surface elevation model for modeling","interactions":[],"lastModifiedDate":"2019-09-20T12:48:37","indexId":"70204415","displayToPublicDate":"2019-03-31T12:48:27","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"title":"A revised continuous surface elevation model for modeling","docAbstract":"A digital elevation model (DEM) is an essential component of any hydrodynamic model. The Delta Modeling Section (Section) has maintained a database of bathymetry soundings and levee surveys for decades and published a 10-meter (10m) DEM for the San Francisco Bay and Sacramento-San Joaquin Delta (Delta) (California Department of Water Resources 2012). In collaboration with the U.S. Geological Survey (USGS) Pacific Coastal and Marine Science Center, the California Department of Water Resources (DWR) has continued to upgrade these DEMs based on newer survey data and improved interpolation methodologies. An updated San Francisco Bay-Delta bathymetric/topographic digital elevation model was published by the USGS (Fregoso, Wang, Ateljevich, and Jaffe 2017). \n\nBoth DWR and USGS continue to work on the elevation models for several reasons. First, high-resolution multibeam bathymetry data continues to become available. A good portion of the newer collections are performed at locations where bathymetry data is lacking, or of poor quality, or where model sensitivity to bathymetry is known to be high, so the effort has a high return on investment. Recent high-resolution multibeam datasets easily support the development of accurate 2-meter (2m) DEMs, although shallow water, turbidity, vegetation, and the gap between the multibeam data and terrestrial data from light detection and ranging (LiDAR) remain vexing issues that fuel development of enhanced techniques. \n\nIn some locations, migration toward 2m resolution models is motivated by geographical structure even where there has been little improvement in the underlying data. DEMs at 10m resolution are insufficient to adequately describe small-scale terrain features, such as levee crests or the main conveyance channel through a narrow reach, such as Middle River. As a result, elevation modelers have traditionally needed to perform feature enforcement for 10m DEMs, but not for the Section’s 2m DEMs which do resolve these features (California Department of Resources 2012). There are several other problems associated with a coarse target resolution, including reduced conveyance and rough contours where channels run oblique to the elevation model. In places where the topography demands a finer elevation model, the Section and others have adopted improved interpolation techniques for single-beam data to produce reasonable 2m DEMs that preserve features on appropriate scales.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Methodology for flow and salinity estimates in the Sacramento-San Joaquin Delta and Suisun Marsh, 39th Annual Progress Report to the State Water Resources Control Board","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"California Department of Water Resources, Bay-Delta Office","usgsCitation":"Wang, R., Ateljevich, E., Fregoso, T.A., and Jaffe, B.E., 2019, A revised continuous surface elevation model for modeling, chap. of Methodology for flow and salinity estimates in the Sacramento-San Joaquin Delta and Suisun Marsh, 39th Annual Progress Report to the State Water Resources Control Board, v. 39, p. 5-1-5-40.","productDescription":"40 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range","interactions":[],"lastModifiedDate":"2019-09-25T09:44:38","indexId":"70204441","displayToPublicDate":"2019-03-31T12:18:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":718,"text":"American Fisheries Society Symposium","active":true,"publicationSubtype":{"id":10}},"title":"Changes in body condition and diet of lotic Smallmouth Bass across two flow regimes during summer months at the southern extent of their native range","docAbstract":"

The Ozark Plateau is located at the southern extent of native Smallmouth Bass Micropterus dolomieu range and water temperature and drought conditions during summer months may potentially affect growth of Smallmouth Bass in this region. Groundwater streams in the region do not warm to the same extent as runoff streams during summer months and could provide a thermal refuge habitat for Smallmouth Bass from high summer temperatures and drought conditions. Our study objective was to examine differences in body condition and diet of Small-mouth Bass through summer months between groundwater and runoff streams. We sampled Smallmouth Bass from eight streams across two the flow regimes monthly from June-September from 2014 to 2016 in the Ozark Plateau of Arkansas and Missouri. Relative weights were calculated and diet contents were examined for each fish. Linear mixed model analyses indicated that relative weights declined in both stream types in 2014 and 2015, but not in 2016. Surprisingly, there was no significant difference in change in relative weights between runoff and groundwater streams in any year. No diet shifts over the course of the summer were noted in any year, and no differences were seen between stream types. Our results suggest that further work should investigate the refuge qualities of groundwater streams for Smallmouth Bass in this region as Smallmouth Bass from both stream types may currently respond similarly to summer conditions.. Middaugh, Chris & Magoulick, Daniel. (2019). Changes in Body Condition and Diet of Lotic Smallmouth Bass across Two Flow Regimes during Summer Months at the Southern Extent of Their Native Range. The Ozark Plateau is located at the southern extent of native Smallmouth Bass Micropterus dolomieu range and water temperature and drought conditions during summer months may potentially affect growth of Smallmouth Bass in this region. Groundwater streams in the region do not warm to the same extent as runoff streams during summer months and could provide a thermal refuge habitat for Smallmouth Bass from high summer temperatures and drought conditions. Our study objective was to examine differences in body condition and diet of Small-mouth Bass through summer months between groundwater and runoff streams. We sampled Smallmouth Bass from eight streams across two the flow regimes monthly from June-September from 2014 to 2016 in the Ozark Plateau of Arkansas and Missouri. Relative weights were calculated and diet contents were examined for each fish. Linear mixed model analyses indicated that relative weights declined in both stream types in 2014 and 2015, but not in 2016. Surprisingly, there was no significant difference in change in relative weights between runoff and groundwater streams in any year. No diet shifts over the course of the summer were noted in any year, and no differences were seen between stream types. Our results suggest that further work should investigate the refuge qualities of groundwater streams for Smallmouth Bass in this region as Smallmouth Bass from both stream types may currently respond similarly to summer conditions.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Managing Centrarchid Fisheries in Rivers and Streams","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","isbn":"9781934874523","usgsCitation":"Middaugh, C.R., and Magoulick, D.D., 2019, Changes in body condition and diet of lotic Smallmouth Bass across two flow regimes during summer months at the southern extent of their native range: American Fisheries Society Symposium, v. 87, p. 93-110.","productDescription":"18 p.","startPage":"93","endPage":"110","ipdsId":"IP-083988","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":367606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367605,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/afs-symposia/54087p/"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Ozark Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.6142578125,\n 34.84085858477277\n ],\n [\n -91.669921875,\n 34.84085858477277\n ],\n [\n -91.669921875,\n 37.21283151445594\n ],\n [\n -94.6142578125,\n 37.21283151445594\n ],\n [\n -94.6142578125,\n 34.84085858477277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Middaugh, Christopher R.","contributorId":177019,"corporation":false,"usgs":false,"family":"Middaugh","given":"Christopher","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":771488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":766920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210717,"text":"70210717 - 2019 - Report of the technical expert workshop: Developing recommendations for field response, captive management, and rehabilitation of sea turtles with fibropapillomatosis","interactions":[],"lastModifiedDate":"2020-06-19T15:36:59.23505","indexId":"70210717","displayToPublicDate":"2019-03-31T10:36:21","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NMFS-OPR-60","title":"Report of the technical expert workshop: Developing recommendations for field response, captive management, and rehabilitation of sea turtles with fibropapillomatosis","docAbstract":"

Fibropapillomatosis (FP) is a disease of sea turtles that primarily manifests as tumors of the skin. Strandings of green turtles with this disease have dramatically increased in the Southeast U.S. over the last decade, necessitating a review of various practices related to the capture, handling, and treatment of afflicted turtles. NOAA and USFWS hosted a workshop in St. Petersburg, Florida on September 6, 2017 to seek input on the development of recommendations to address the following key issues regarding green turtles with FP: 1) disposition when encountered under various circumstances (e.g., strandings, research activities, incidental capture, opportunistic observations); 2) rehabilitation and release; 3) response options if rehabilitation capacity is exceeded; and 4) biosecurity measures to prevent anthropogenic spread of the disease. Federal and state resource agency staff and rehabilitation veterinarians were invited to this workshop to provide input for these recommendations. A review of rehabilitation practices and outcome was shared with participants to inform discussions related to rehabilitation and stranding response. Draft recommendations were prepared for the meeting and participants were asked to share their opinions during moderated discussions and via a written feedback instrument. This input was considered and applied to amend the recommendations, which were also peer-reviewed by six additional veterinarians and a stranding biologist with expertise in sea turtles,rehabilitation medicine, and fibropapillomatosis. The intended use for the completed Fibropapillomatosis and Sea Turtles: Recommendations for Field Response, Captive Management, and Rehabilitation is to assist resource agencies with management planning and decisions related to green turtles with FP and to inform relevant aspects of policy, permits, and authorizations under federal and state regulations.

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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stacy, Brian","contributorId":174822,"corporation":false,"usgs":false,"family":"Stacy","given":"Brian","affiliations":[],"preferred":false,"id":791088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Allen M.","contributorId":195874,"corporation":false,"usgs":false,"family":"Foley","given":"Allen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":791089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":791090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauritsen, Anne","contributorId":225409,"corporation":false,"usgs":false,"family":"Lauritsen","given":"Anne","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":791092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schroeder, Barbara","contributorId":225410,"corporation":false,"usgs":false,"family":"Schroeder","given":"Barbara","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":791093,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hargrove, Stacy A.","contributorId":190643,"corporation":false,"usgs":false,"family":"Hargrove","given":"Stacy","email":"","middleInitial":"A.","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":false,"id":791091,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keene, Jennifer L.","contributorId":225425,"corporation":false,"usgs":false,"family":"Keene","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":791094,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70234300,"text":"70234300 - 2019 - Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration","interactions":[],"lastModifiedDate":"2022-08-08T13:21:37.152162","indexId":"70234300","displayToPublicDate":"2019-03-31T08:15:30","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration","docAbstract":"

This chapter discusses an interdisciplinary and transdisciplinary project to understand the interactions of agriculture, climate, and water resources in the Central Great Plains as a coupled natural-human system. We focus on the Smoky Hills Watershed in Kansas, where we gathered socioeconomic, hydrological, and climatic data, along with ecological data on fish species. The project involved substantial stakeholder engagement, which was complicated by post-truth attitudes about climate science and environmental regulation by some groups. We discuss the challenges of team management, stakeholder engagement, and data integration for modeling, notably the incorporation of stakeholder support for environmental policy in the context of extreme climatic events. We conclude by offering a framework for good collaborative practice to manage the complications of crossing boundaries in transdisciplinary research and outreach.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Collaboration across boundaries for social-ecological systems science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-13827-1_8","usgsCitation":"Caldas, M.M., Mather, M.E., Bergtold, J.S., Daniels, M., Granco, G., Aistrup, J., Haukos, D.A., Sheshukov, A.Y., Sanderson, M.R., and Heier Stamm, J.L., 2019, Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration, chap. of Collaboration across boundaries for social-ecological systems science, p. 265-294, https://doi.org/10.1007/978-3-030-13827-1_8.","productDescription":"30 p.","startPage":"265","endPage":"294","ipdsId":"IP-102166","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":404915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Smoky Hills Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.942138671875,\n 38.35888785866677\n ],\n [\n -97.261962890625,\n 38.35888785866677\n ],\n [\n -97.261962890625,\n 39.67337039176558\n ],\n [\n -101.942138671875,\n 39.67337039176558\n ],\n [\n -101.942138671875,\n 38.35888785866677\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2019-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldas, Marcellus M.","contributorId":200844,"corporation":false,"usgs":false,"family":"Caldas","given":"Marcellus","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":848494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","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":848493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergtold, Jason S.","contributorId":200846,"corporation":false,"usgs":false,"family":"Bergtold","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":848495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniels, Melinda","contributorId":294671,"corporation":false,"usgs":false,"family":"Daniels","given":"Melinda","affiliations":[],"preferred":false,"id":848496,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Granco, Gabriel","contributorId":242802,"corporation":false,"usgs":false,"family":"Granco","given":"Gabriel","affiliations":[{"id":48532,"text":"swrc","active":true,"usgs":false}],"preferred":false,"id":848497,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aistrup, Joseph","contributorId":200847,"corporation":false,"usgs":false,"family":"Aistrup","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":848498,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","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":848492,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sheshukov, Aleksey Y.","contributorId":172092,"corporation":false,"usgs":false,"family":"Sheshukov","given":"Aleksey","email":"","middleInitial":"Y.","affiliations":[],"preferred":false,"id":848499,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sanderson, Matthew R.","contributorId":200845,"corporation":false,"usgs":false,"family":"Sanderson","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":848500,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heier Stamm, Jessica L.","contributorId":200848,"corporation":false,"usgs":false,"family":"Heier Stamm","given":"Jessica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":848501,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70203550,"text":"70203550 - 2019 - Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system","interactions":[],"lastModifiedDate":"2019-11-14T13:45:05","indexId":"70203550","displayToPublicDate":"2019-03-30T16:38:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system","docAbstract":"In an aquifer system with complex hydrogeology, mixing of groundwater with different ages could occur associated with various flow pathways. In this study, we applied different groundwater age estimation techniques (lumped parameter model, and numerical model) to characterize groundwater age distributions and the major pathways of nitrate contamination in the Gosan agricultural field, Jeju Island. According to the lumped parameter model, groundwater age in the study area could be explained by the binary mixing of the young groundwater (4-33 years) and the old water component (>60 years). The complex hydrogeologic regimes and local heterogeneity observed in the study area (multi-layered aquifer, well leakage hydraulics) were particularly well reflected in the numerical model. The numerical model predicted that the regional aquifer of Gosan responded to the fertilizer applications more rapidly (mean age: 9.7-22.3 years) than as estimated by other models. Our study results demonstrated that application and comparison of multiple age estimation methods can be useful to understand better the flow regimes and the mixing characteristics of groundwater with different ages (pathways), hence, to reduce the risk of improper groundwater management plan arising from the aquifer heterogeneity.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11465","usgsCitation":"Koh, E., Lee, E., Kaown, D., Green, C., Koh, D., Lee, K., and Lee, S., 2019, Comparison of groundwater age models for assessing nitrate loading, transport pathways, and management options in a complex aquifer system: Hydrological Processes, v. 32, p. 923-938, https://doi.org/10.1002/hyp.11465.","productDescription":"16 p.","startPage":"923","endPage":"938","ipdsId":"IP-086017","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":364068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"South Korea","otherGeospatial":"Jeju Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 125.9527587890625,\n 33.10534697199519\n ],\n [\n 127.0458984375,\n 33.10534697199519\n ],\n [\n 127.0458984375,\n 33.69235234723729\n ],\n [\n 125.9527587890625,\n 33.69235234723729\n ],\n [\n 125.9527587890625,\n 33.10534697199519\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Koh, E.H.","contributorId":215736,"corporation":false,"usgs":false,"family":"Koh","given":"E.H.","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, E.","contributorId":215737,"corporation":false,"usgs":false,"family":"Lee","given":"E.","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763107,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaown, D.","contributorId":215738,"corporation":false,"usgs":false,"family":"Kaown","given":"D.","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":763105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koh, D.C.","contributorId":215739,"corporation":false,"usgs":false,"family":"Koh","given":"D.C.","affiliations":[{"id":24820,"text":"Korea Institute of Geoscience and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":763109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, K.K","contributorId":215740,"corporation":false,"usgs":false,"family":"Lee","given":"K.K","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":763110,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lee, Sangil","contributorId":215741,"corporation":false,"usgs":false,"family":"Lee","given":"Sangil","affiliations":[{"id":39310,"text":"Korea Polar Research Institute","active":true,"usgs":false}],"preferred":false,"id":763111,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228106,"text":"70228106 - 2019 - The accuracy of ecological flow metrics derived using a physics-based distributed rainfall-runoff model in the Great Plains, USA","interactions":[],"lastModifiedDate":"2022-02-07T14:40:52.157488","indexId":"70228106","displayToPublicDate":"2019-03-30T14:46:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"The accuracy of ecological flow metrics derived using a physics-based distributed rainfall-runoff model in the Great Plains, USA","docAbstract":"

The development of a hydrologic foundation, essential for advancing our understanding of flow-ecology relationships, was developed using the high-resolution physics-based distributed rainfall–runoff model Vflo in a semi-arid region. We compared the accuracy and bias associated with flow metrics that were generated using Vflo, gauge data, and drainage area ratios at both a daily and monthly time step in the Canadian River basin, USA. First, we calibrated and applied bias correction to the Vflo model to simulate streamflow at ungauged catchment locations. Next, flow metrics were calculated using simulated and observed data from stream gauge locations. We found discharge predictions using Vflo were more accurate than drainage area ratios. General correspondence between predicted discharge and the gauge data was apparent; however, flow metrics calculated using the Vflo output did not accurately represent flow variability. Results from the Vflo model showed systematic discharge over-predictions in the upper basin and isolated over-predictions in the lower basin, likely due to hail events and sparse rainfall data across the large catchment. Goodness-of-fit statistics (Nash–Sutcliffe efficiency, root-mean square error, and the coefficient of variation) indicated the drainage area ratio and Vflo were more accurate at a monthly rather than daily time step, even after quantile mapping. This finding limits the number of streamflow metrics available to develop ecological models, but more importantly, the coarser resolution may hinder our understanding of ecological processes that occur at a submonthly time step. Our approach provides a framework for selecting flow metrics that best represent hydrologic patterns across a large semi-arid catchment with the necessary accuracy to address the ecological questions of interest.

","language":"English","publisher":"Wiley","doi":"10.1002/eco.2090","usgsCitation":"Worthington, T.A., Brewer, S.K., Viex, B., and Kennen, J., 2019, The accuracy of ecological flow metrics derived using a physics-based distributed rainfall-runoff model in the Great Plains, USA: Ecohydrology, v. 12, no. 5, e2090, 17 p., https://doi.org/10.1002/eco.2090.","productDescription":"e2090, 17 p.","ipdsId":"IP-097660","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Oklahoma, Texas","otherGeospatial":"Canadian River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.447021484375,\n 34.615126683462194\n ],\n [\n -95.00976562499999,\n 34.615126683462194\n ],\n [\n -95.00976562499999,\n 35.39800594715108\n ],\n [\n -104.447021484375,\n 35.39800594715108\n ],\n [\n -104.447021484375,\n 34.615126683462194\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-04-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Worthington, Thomas A.","contributorId":140662,"corporation":false,"usgs":false,"family":"Worthington","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":833135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viex, Baxter","contributorId":274567,"corporation":false,"usgs":false,"family":"Viex","given":"Baxter","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":833136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":833137,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203415,"text":"70203415 - 2019 - Factors controlling landslide frequency-area distributions","interactions":[],"lastModifiedDate":"2019-05-14T13:39:44","indexId":"70203415","displayToPublicDate":"2019-03-30T13:38:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Factors controlling landslide frequency-area distributions","docAbstract":"

A power‐law relation for the frequency–area distribution (FAD) of medium and large landslides (e.g. tens to millions of square meters) has been observed by numerous authors. But the FAD of small landslides diverges from the power‐law distribution, with a rollover point below which frequencies decrease for smaller landslides. Some studies conclude that this divergence is an artifact of unmapped small landslides due to lack of spatial or temporal resolution; others posit that it is caused by the change in the underlying failure process. An explanation for this dilemma is essential both to evaluate the factors controlling FADs of landslides and power‐law scaling, which is a crucial factor regarding both landscape evolution and landslide hazard assessment. This study examines the FADs of 45 earthquake‐induced landslide inventories from around the world in the context of the proposed explanations. We show that each inventory probably involves some combination of the proposed explanations, though not all explanations contribute to each case. We propose an alternative explanation to understand the reason for the divergence from a power‐law. We suggest that the geometry of a landslide at the time of mapping reflects not just one single movement but many, including the propagation of numerous smaller landslides before and after the main failure. Because only the resulting combination of these landslides can be observed due to a lack of temporal resolution, many smaller landslides are not taken into account in the inventory. This reveals that the divergence from the power‐law is not necessarily attributed to the incompleteness of an inventory. This conceptual model will need to be validated by ongoing observation and analysis. Also, we show that because of the subjectivity of mapping procedures, the total number of landslides and total landslide areas in inventories differ significantly, and therefore the shapes of FADs also differ considerably.

","language":"English","publisher":"Wiley","doi":"10.1002/esp.4543","usgsCitation":"Tanyas, H., van Westen, C.J., Allstadt, K.E., and Jibson, R.W., 2019, Factors controlling landslide frequency-area distributions: Earth Surface Processes and Landforms, v. 44, no. 4, p. 900-917, https://doi.org/10.1002/esp.4543.","productDescription":"18 p.","startPage":"900","endPage":"917","ipdsId":"IP-101359","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467758,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.4543","text":"Publisher Index Page"},{"id":363784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":363723,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1002/esp.4543"}],"volume":"44","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Tanyas, Hakan","contributorId":215531,"corporation":false,"usgs":false,"family":"Tanyas","given":"Hakan","email":"","affiliations":[{"id":39272,"text":"University of Twente","active":true,"usgs":false}],"preferred":false,"id":762598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Westen, Cees J.","contributorId":196188,"corporation":false,"usgs":false,"family":"van Westen","given":"Cees","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":762599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248 kallstadt@usgs.gov","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":167684,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"kallstadt@usgs.gov","middleInitial":"E.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":762600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jibson, Randall W. 0000-0003-3399-0875 jibson@usgs.gov","orcid":"https://orcid.org/0000-0003-3399-0875","contributorId":2985,"corporation":false,"usgs":true,"family":"Jibson","given":"Randall","email":"jibson@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":762601,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204471,"text":"70204471 - 2019 - Prominence of the tropics in the recent rise of global nitrogen pollution","interactions":[],"lastModifiedDate":"2019-07-26T10:15:49","indexId":"70204471","displayToPublicDate":"2019-03-29T11:05:31","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Prominence of the tropics in the recent rise of global nitrogen pollution","docAbstract":"Nitrogen (N) pollution is shaped by multiple processes, the combined effects of which remain uncertain, particularly in the tropics. We use a global land biosphere model to analyze historical terrestrial-freshwater N budgets, considering the effects of anthropogenic N inputs, atmospheric CO2, land use, and climate. We estimate that globally, land currently sequesters 11 (10–13)% of annual N inputs. Some river basins, however, sequester >50% of their N inputs, buffering coastal waters against eutrophication and society against greenhouse gas-induced warming. Other basins, releasing >25% more than they receive, are mostly located in the tropics, where recent deforestation, agricultural intensification, and/or exports of land N storage can create large N pollution sources. The tropics produce 56 ± 6% of global land N pollution despite covering only 34% of global land area and receiving far lower amounts of fertilizers than the extratropics. Tropical land use should thus be thoroughly considered in managing global N pollution.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41467-019-09468-4","usgsCitation":"Lee, M., Shevliakova, E., Stock, C., Malyshev, S., and Milly, P.C., 2019, Prominence of the tropics in the recent rise of global nitrogen pollution: Nature Communications, v. 10, 1437, 11 p., https://doi.org/10.1038/s41467-019-09468-4.","productDescription":"1437, 11 p.","ipdsId":"IP-102668","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":460425,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-019-09468-4","text":"Publisher Index Page"},{"id":365932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365925,"type":{"id":15,"text":"Index Page"},"url":"https://www.nature.com/articles/s41467-019-09468-4"}],"volume":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lee, Minjin","contributorId":177261,"corporation":false,"usgs":false,"family":"Lee","given":"Minjin","email":"","affiliations":[],"preferred":false,"id":767115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shevliakova, Elena","contributorId":201589,"corporation":false,"usgs":false,"family":"Shevliakova","given":"Elena","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":767116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Charles A.","contributorId":217586,"corporation":false,"usgs":false,"family":"Stock","given":"Charles A.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":767117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":201588,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":767118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":767114,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202853,"text":"70202853 - 2019 - Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy)","interactions":[],"lastModifiedDate":"2019-06-18T11:14:23","indexId":"70202853","displayToPublicDate":"2019-03-29T09:47:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy)","docAbstract":"Small lakes in low relief areas are atypical candidates for studies on paleoseismicity, but their sediments can contain seismically induced event layers (seismites) generated through strong ground shaking, sediment transport, hydrological reorganization and/or changes in groundwater chemistry and flow. Lakes Lungo and Ripasottile are shallow lakes (<10m deep) located in the tectonically active Rieti Basin in the central Apennines, Italy, where strong normal faulting earthquakes (Mw 6.5 to 7.0) regularly occur. Sediment cores from these lakes provide paleoseismic indicators for the past ~1000 years. Sedimentological and geochemical analysis reveals four event layers identified in both lakes that correspond with documented large-scale earthquakes in 1298, 1349, 1639, and 1703 AD. Chronological correlation between earthquakes and possible seismites is reliable because of the unusually high resolution of sediment dating available for the studied cores. The common physical structure is a physically homogenous bed (homogenite) of re-suspended sediment consisting of a denser, high magnetic susceptibility (MS) clastic base, with organic matter concentrated above. Chemical signatures are associated with some event layers and may represent abrupt or transient shifts to a groundwater-dominated system, or permanent changes in groundwater flow and/or spring discharge. Excursions in δ13Corg may represent disruptions or changes in carbon source. Not all event layers show the same features, a result attributed to differences in seismic processes as well as the lake attributes, and anthropogenic modification. The observations made here may provide a new means of detecting paleoseismicity and may be applied to other low relief lakes in seismically active areas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2019.03.004","usgsCitation":"Archer, C., Noble, P., Rosen, M.R., Sagnotti, L., Fiorindo, F., Piovesan, G., Mensing, S., and Michetti, A., 2019, Lakes as paleoseismic records in a seismically-active, low-relief area (Rieti Basin, central Italy): Quaternary Science Reviews, v. 211, p. 186-207, https://doi.org/10.1016/j.quascirev.2019.03.004.","productDescription":"22 p.","startPage":"186","endPage":"207","ipdsId":"IP-098465","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2019.03.004","text":"Publisher Index Page"},{"id":362567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Rieti Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 12.677536010742188,\n 42.30727643850873\n ],\n [\n 13.454132080078125,\n 42.30727643850873\n ],\n [\n 13.454132080078125,\n 42.628906895633456\n ],\n [\n 12.677536010742188,\n 42.628906895633456\n ],\n [\n 12.677536010742188,\n 42.30727643850873\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"211","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Archer, Claire","contributorId":198952,"corporation":false,"usgs":false,"family":"Archer","given":"Claire","email":"","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":760267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noble, Paula","contributorId":198953,"corporation":false,"usgs":false,"family":"Noble","given":"Paula","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":760268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":760266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sagnotti, Leonardo","contributorId":214577,"corporation":false,"usgs":false,"family":"Sagnotti","given":"Leonardo","email":"","affiliations":[{"id":39077,"text":"National Institute of Geophysics and Volcanology; Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":760269,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fiorindo, Fabio","contributorId":214578,"corporation":false,"usgs":false,"family":"Fiorindo","given":"Fabio","email":"","affiliations":[{"id":39077,"text":"National Institute of Geophysics and Volcanology; Rome, Italy","active":true,"usgs":false}],"preferred":false,"id":760270,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piovesan, Gianluca","contributorId":198957,"corporation":false,"usgs":false,"family":"Piovesan","given":"Gianluca","email":"","affiliations":[{"id":35390,"text":"Tuscia University","active":true,"usgs":false}],"preferred":false,"id":760271,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mensing, Scott","contributorId":198958,"corporation":false,"usgs":false,"family":"Mensing","given":"Scott","affiliations":[{"id":33212,"text":"Department of Geography, University of NV","active":true,"usgs":false}],"preferred":false,"id":760273,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Michetti, Alessandro 0000-0002-1775-1340","orcid":"https://orcid.org/0000-0002-1775-1340","contributorId":206792,"corporation":false,"usgs":false,"family":"Michetti","given":"Alessandro","email":"","affiliations":[{"id":37402,"text":"Università degli Studi dell’Insubria","active":true,"usgs":false}],"preferred":false,"id":760272,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203069,"text":"70203069 - 2019 - Assessing patterns of annual change to permafrost bluffs along the North Slope coast of Alaska using high-resolution imagery and elevation models","interactions":[],"lastModifiedDate":"2019-06-18T11:40:43","indexId":"70203069","displayToPublicDate":"2019-03-29T08:54:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing patterns of annual change to permafrost bluffs along the North Slope coast of Alaska using high-resolution imagery and elevation models","docAbstract":"Coastal permafrost bluffs at Barter Island, on the North Slope, Beaufort Sea Coast of Alaska are among the most rapidly eroding along Alaska’s coast, having retreated up to 132 m between 1955 and 2015. Here we quantify rates and patterns of change over a single year using very-high resolution orthophotomosaics and co-registered surface elevation models derived from a survey-grade form of structure-from-motion photogrammetry from a fixed-wing, manned aircraft. The resulting elevation models were validated with over 10,000 ground check points and found that 95% agreed to within 20 cm, before accounting for real differences in the ground surface due to seasonality, vegetation, and checkpoint acquisition errors. This data set provides the most detailed and accurate measurements of coastal change to date along the Alaskan coast and the method is scaleable to more extensive coastlines. Between July 2014 and July 2015, the bluffs retreated an average of 1.3 m, and a maximum of 8.1 m, with an associated net volume loss of 38,100 ± 300 m3 (1.3 m3/m). This average retreat over this single year was slightly less than the 60-year mean rate of change of -1.5±0.1 m/yr, suggesting the 2014-2015 year represented relatively typical to slightly below average conditions. Most of the bluff material (70%) was lost during the 3 summer months (July to Sept) of 2014 and the remaining 30% between the late-summer and following winter-spring. The pattern of change was predominantly landward retreat of the top of the bluffs, removal of the debris apron and subsequent niching at the base of the bluffs during mid to late summer (July to Sept) followed by erosion of the bluff face and deposition of debris at the base of the bluff through the remainder of the year (Sept to the following July). Drivers of the observed change are likely a combination of thermal erosion on the bluff face throughout the summer and episodic thermo-mechanical removal of material, niching, and undercutting of the base associated with high-water levels driven by low-pressure storms and westerly winds. These patterns and high rates of change are believed to be broadly representative of coastal permafrost bluffs found along many high-latitude coastlines worldwide.","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2019.03.029","usgsCitation":"Gibbs, A.E., Nolan, M., Richmond, B.M., Snyder, A.G., and Erikson, L., 2019, Assessing patterns of annual change to permafrost bluffs along the North Slope coast of Alaska using high-resolution imagery and elevation models: Geomorphology, v. 336, p. 152-164, https://doi.org/10.1016/j.geomorph.2019.03.029.","productDescription":"13 p.","startPage":"152","endPage":"164","ipdsId":"IP-091185","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467763,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2019.03.029","text":"Publisher Index Page"},{"id":362994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -151.171875,\n 68.64055504059381\n ],\n [\n -141.240234375,\n 68.64055504059381\n ],\n [\n -141.240234375,\n 71.13098770917023\n ],\n [\n -151.171875,\n 71.13098770917023\n ],\n [\n -151.171875,\n 68.64055504059381\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"336","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":761026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, Matt","contributorId":146230,"corporation":false,"usgs":false,"family":"Nolan","given":"Matt","affiliations":[{"id":16761,"text":"Institute of Northern Engineering, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":761027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":761029,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snyder, Alexander G. 0000-0001-6250-4827 agsnyder@usgs.gov","orcid":"https://orcid.org/0000-0001-6250-4827","contributorId":171654,"corporation":false,"usgs":true,"family":"Snyder","given":"Alexander","email":"agsnyder@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":761028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":214865,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":761030,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}