{"pageNumber":"873","pageRowStart":"21800","pageSize":"25","recordCount":184904,"records":[{"id":70196920,"text":"70196920 - 2018 - Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species","interactions":[],"lastModifiedDate":"2018-05-14T13:07:52","indexId":"70196920","displayToPublicDate":"2018-05-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species","docAbstract":"<p><span>A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins&nbsp;(</span><i>Malaclemys terrapin</i><span>) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using<span> population viability analysis&nbsp;</span><span>under simulated management strategies to inform&nbsp;decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.03.023","usgsCitation":"Crawford, B.A., Moore, C.T., Norton, T., and Maerz, J.C., 2018, Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species: Biological Conservation, v. 222, p. 33-43, https://doi.org/10.1016/j.biocon.2018.03.023.","productDescription":"11 p.","startPage":"33","endPage":"43","ipdsId":"IP-083097","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"222","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc0","contributors":{"authors":[{"text":"Crawford, Brian A.","contributorId":204802,"corporation":false,"usgs":false,"family":"Crawford","given":"Brian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Clinton T. 0000-0002-6053-2880 cmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-6053-2880","contributorId":3643,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton","email":"cmoore@usgs.gov","middleInitial":"T.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norton, Terry M.","contributorId":71020,"corporation":false,"usgs":true,"family":"Norton","given":"Terry M.","affiliations":[],"preferred":false,"id":735036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maerz, John C.","contributorId":171763,"corporation":false,"usgs":false,"family":"Maerz","given":"John","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":735037,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196929,"text":"70196929 - 2018 - Phosphorus speciation and solubility in aeolian dust deposited in the interior American West","interactions":[],"lastModifiedDate":"2018-05-10T13:32:59","indexId":"70196929","displayToPublicDate":"2018-05-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Phosphorus speciation and solubility in aeolian dust deposited in the interior American West","docAbstract":"Aeolian dust is a significant source of phosphorus (P) to alpine oligotrophic lakes, but P speciation in dust and source sediments and its release kinetics to lake water remain unknown. Phosphorus K-edge XANES spectroscopy shows that calcium-bound P (Ca−P) is dominant in 10 of 12 dust samples (41−74%) deposited on snow in the central Rocky Mountains and all 42 source sediment samples (the fine fraction) (68−80%), with a lower proportion in dust probably because acidic snowmelt dissolves some Ca−P in dust before collection. Iron-bound P (Fe−P, ∼54%) dominates in the remaining two dust samples. Chemical extractions (SEDEX) on these samples provide inaccurate results because of unselective extraction of targeted species and\nartifacts introduced by the extractions. Dust releases increasingly more P in synthetic lake water within 6−72 h thanks to dissolution of Ca−P, but dust release of P declines afterward due to back adsorption of P onto Fe oxides present in the dust. The back sorption is stronger for the dust with a lower degree of P saturation determined by oxalate extraction. This work suggests\nthat P speciation, poorly crystalline minerals in the dust, and lake acidification all affect the availability and fate of dust-borne P in lakes.","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b04729","usgsCitation":"Zhang, Z., Goldstein, H.L., Reynolds, R.L., Hu, Y., Wang, X., and Zhu, M., 2018, Phosphorus speciation and solubility in aeolian dust deposited in the interior American West: Environmental Science & Technology, v. 52, no. 5, p. 2658-2667, https://doi.org/10.1021/acs.est.7b04729.","productDescription":"10 p.","startPage":"2658","endPage":"2667","ipdsId":"IP-091229","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":437917,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RF5T8B","text":"USGS data release","linkHelpText":"Data Release for Phosphorous speciation and solubility in aeolian dust deposited in the interior American West"},{"id":354056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.7197265625,\n              32.602361666817515\n            ],\n            [\n              -104.65576171875,\n              32.602361666817515\n            ],\n            [\n              -104.65576171875,\n              40.01078714046552\n            ],\n            [\n              -112.7197265625,\n              40.01078714046552\n            ],\n            [\n              -112.7197265625,\n              32.602361666817515\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"52","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-08","publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdbc","contributors":{"authors":[{"text":"Zhang, Zhuojun","contributorId":204798,"corporation":false,"usgs":false,"family":"Zhang","given":"Zhuojun","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":735025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":147881,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":735024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":147880,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":271,"text":"Federal Center","active":false,"usgs":true}],"preferred":true,"id":735026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hu, Yongfeng","contributorId":204799,"corporation":false,"usgs":false,"family":"Hu","given":"Yongfeng","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":735027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Xiaoming","contributorId":204800,"corporation":false,"usgs":false,"family":"Wang","given":"Xiaoming","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":735028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhu, Mengqiang","contributorId":204801,"corporation":false,"usgs":false,"family":"Zhu","given":"Mengqiang","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":735029,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196919,"text":"70196919 - 2018 - Stream permanence is related to crayfish occupancy and abundance in the Ozark Highlands, USA","interactions":[],"lastModifiedDate":"2018-09-12T08:25:57","indexId":"70196919","displayToPublicDate":"2018-05-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Stream permanence is related to crayfish occupancy and abundance in the Ozark Highlands, USA","docAbstract":"<p><span>Crayfish use of intermittent streams is especially important to understand in the face of global climate change. We examined the influence of stream permanence and local habitat on crayfish occupancy and species densities in the Ozark Highlands, USA. We sampled in June and July 2014 and 2015. We used a quantitative kick–seine method to sample crayfish presence and abundance at 20 stream sites with 32 surveys/site in the Upper White River drainage, and we measured associated local environmental variables each year. We modeled site occupancy and detection probabilities with the software PRESENCE, and we used multiple linear regressions to identify relationships between crayfish species densities and environmental variables. Occupancy of all crayfish species was related to stream permanence.&nbsp;</span><i>Faxonius meeki</i><span><span>&nbsp;</span>was found exclusively in intermittent streams, whereas<span>&nbsp;</span></span><i>Faxonius neglectus</i><span><span>&nbsp;</span>and<span>&nbsp;</span></span><i>Faxonius luteus</i><span>had higher occupancy and detection probability in permanent than in intermittent streams, and<span>&nbsp;</span></span><i>Faxonius williamsi</i><span><span>&nbsp;</span>was associated with intermittent streams. Estimates of detection probability ranged from 0.56 to 1, which is high relative to values found by other investigators. With the exception of<span>&nbsp;</span></span><i>F. williamsi</i><span>, species densities were largely related to stream permanence rather than local habitat. Species densities did not differ by year, but total crayfish densities were significantly lower in 2015 than 2014. Increased precipitation and discharge in 2015 probably led to the lower crayfish densities observed during this year. Our study demonstrates that crayfish distribution and abundance is strongly influenced by stream permanence. Some species, including those of conservation concern (i.e.,<span>&nbsp;</span></span><i>F. williamsi</i><span>,<span>&nbsp;</span></span><i>F. meeki</i><span>), appear dependent on intermittent streams, and conservation efforts should include consideration of intermittent streams as an important component of freshwater biodiversity.</span></p>","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/696020","usgsCitation":"Yarra, A.N., and Magoulick, D.D., 2018, Stream permanence is related to crayfish occupancy and abundance in the Ozark Highlands, USA: Freshwater Science, v. 37, no. 1, p. 54-63, https://doi.org/10.1086/696020.","productDescription":"10 p.","startPage":"54","endPage":"63","ipdsId":"IP-082212","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri","otherGeospatial":"Upper White River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -94.37255859375,\n              35.90684930677121\n            ],\n            [\n              -89.9560546875,\n              35.90684930677121\n            ],\n            [\n              -89.9560546875,\n              38.37611542403604\n            ],\n            [\n              -94.37255859375,\n              38.37611542403604\n            ],\n            [\n              -94.37255859375,\n              35.90684930677121\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc2","contributors":{"authors":[{"text":"Yarra, Allyson N.","contributorId":204803,"corporation":false,"usgs":false,"family":"Yarra","given":"Allyson","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":735038,"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":734995,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196155,"text":"sir20185046 - 2018 - Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015","interactions":[],"lastModifiedDate":"2018-09-25T05:33:19","indexId":"sir20185046","displayToPublicDate":"2018-05-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5046","title":"Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015","docAbstract":"<p>This report documents the methods for peak-flow frequency (hereinafter “frequency”) analysis and reporting for streamgages in and near Montana following implementation of the Bulletin 17C guidelines. The methods are used to provide estimates of peak-flow quantiles for 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for selected streamgages operated by the U.S. Geological Survey Wyoming-Montana Water Science Center (WY–MT WSC). These annual exceedance probabilities correspond to 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.</p><p>Standard procedures specific to the WY–MT WSC for implementing the Bulletin 17C guidelines include (1) the use of the Expected Moments Algorithm analysis for fitting the log-Pearson Type III distribution, incorporating historical information where applicable; (2) the use of weighted skew coefficients (based on weighting at-site station skew coefficients with generalized skew coefficients from the Bulletin 17B national skew map); and (3) the use of the Multiple Grubbs-Beck Test for identifying potentially influential low flows. For some streamgages, the peak-flow records are not well represented by the standard procedures and require user-specified adjustments informed by hydrologic judgement. The specific characteristics of peak-flow records addressed by the informed-user adjustments include (1) regulated peak-flow records, (2) atypical upper-tail peak-flow records, and (3) atypical lower-tail peak-flow records. In all cases, the informed-user adjustments use the Expected Moments Algorithm fit of the log-Pearson Type III distribution using the at-site station skew coefficient, a manual potentially influential low flow threshold, or both.</p><p>Appropriate methods can be applied to at-site frequency estimates to provide improved representation of long-term hydroclimatic conditions. The methods for improving at-site frequency estimates by weighting with regional regression equations and by Maintenance of Variance Extension Type III record extension are described.</p><p>Frequency analyses were conducted for 99 example streamgages to indicate various aspects of the frequency-<br>analysis methods described in this report. The frequency analyses and results for the example streamgages are presented in a separate data release associated with this report consisting of tables and graphical plots that are structured to include information concerning the interpretive decisions involved in the frequency analyses. Further, the separate data release includes the input files to the PeakFQ program, version 7.1, including the peak-flow data file and the analysis specification file that were used in the peak-flow frequency analyses. Peak-flow frequencies are also reported in separate data releases for selected streamgages in the Beaverhead River and Clark Fork Basins and also for selected streamgages in the Ruby, Jefferson, and Madison River Basins.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185046","collaboration":"Prepared in cooperation with the Montana Department of Natural Resources and Conservation","usgsCitation":"Sando, S.K., and McCarthy, P.M., 2018, Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015: U.S. Geological Survey Scientific Investigations Report 2018–5046, 39 p., https://doi.org/10.3133/sir20185046.","productDescription":"Report: vi, 39 p.; Data Releases","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082119","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":437916,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J1U1GB","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in the Upper Yellowstone River Basin, based on data through water year 2022"},{"id":437915,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92U1D63","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in Dawson and Richland Counties, and the Powder River Basin, Montana, based on data through water year 2022"},{"id":437914,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L8UM2P","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages on tributaries of the Bighorn, Tongue, and Lower Yellowstone Rivers, based on data through water year 2021"},{"id":437913,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C4K7OS","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages on the Bighorn, Tongue, and Lower Yellowstone Rivers and tributaries and Home Creek, Montana, based on data through water year 2021"},{"id":437912,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAJFPL","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in and near the Milk River Basin, Montana, based on data through water year 2018, part 2"},{"id":437911,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95IFBAH","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in and near Teton County, Montana, based on data through water year 2019"},{"id":437910,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91HB8GI","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in Carbon County, Montana, based on data through water year 2018"},{"id":437909,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y53FX3","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for selected streamgages in and near the Milk River Basin, Montana, based on data through water year 2018, Part 1"},{"id":437908,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JNKYKH","text":"USGS data release","linkHelpText":"Peak-Flow Frequency Analyses for Selected Streamgages in Missoula and Granite Counties, Montana, Based on Data through Water Year 2018"},{"id":437907,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RC008L","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for Elk Creek at Augusta, Montana, based on data through water year 2018"},{"id":437906,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TK3KFE","text":"USGS data release","linkHelpText":"Peak-flow frequency analyses for 11 selected streamgages in Jefferson County, Montana, based on data through water year 2017 (ver. 1.1, September 2019)"},{"id":354044,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JW8C21","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Peak-flow frequency analyses for 14 selected streamgages in the Beaverhead River and Clark Fork Basins Montana, based on data through water year 2016"},{"id":354045,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75Q4V99","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Peak-flow frequency analyses for 14 selected streamgages in the Ruby, Jefferson, and Madison River Basins, Montana, based on data through water year 2016"},{"id":354042,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5046/sir20185046.pdf","text":"Report","size":"2.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5046"},{"id":354041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5046/coverthb2.jpg"},{"id":354043,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7C827GQ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Peak-flow frequency analyses for 99 selected streamgages in or near Montana, based on data through water year 2015"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto: dc_MT@usgs.gov\" data-mce-href=\"mailto: dc_MT@usgs.gov\">Director</a>, <a href=\"https://wy-mt.water.usgs.gov\" data-mce-href=\"https://wy-mt.water.usgs.gov\">Wyoming-Montana Water Science Center</a><br>U.S. Geological Survey<br>3162 Bozeman Avenue <br>Helena, MT 59601&nbsp;</p>","tableOfContents":"<ul><li>Acknowledgments<br></li><li>Abstract<br></li><li>Introduction<br></li><li>Overview of Bulletin 17B and Bulletin 17C Guidelines for Peak-Flow Frequency Analysis<br></li><li>The Expected Moments Algorithm Procedures in Relation to Montana Peak-Flow Datasets<br></li><li>Selected Considerations for Peak-Flow Frequency Analysis<br></li><li>Methods for Peak-Flow Frequency Analysis<br></li><li>Methods for Peak-Flow Frequency Reporting<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2018-05-10","noUsgsAuthors":false,"publicationDate":"2018-05-10","publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc6","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":203451,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"","middleInitial":"K.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":731529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Peter M. 0000-0003-3194-041X pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-041X","contributorId":203452,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","middleInitial":"M.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731530,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196913,"text":"70196913 - 2018 - Capture efficiency and injury rates of band-tailed pigeons using whoosh nets","interactions":[],"lastModifiedDate":"2018-05-14T13:10:33","indexId":"70196913","displayToPublicDate":"2018-05-10T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Capture efficiency and injury rates of band-tailed pigeons using whoosh nets","docAbstract":"<p><span>Catching ground feeding birds has typically been accomplished through small, walk-in funnel-style traps. This approach is limited because it requires a bird to find its way into the trap, is biased toward less wary birds, and does not allow targeted trapping of individual birds. As part of a large study on Band-tailed Pigeons (</span><i>Patagioenas fasciata</i><span>) in New Mexico, we needed a trapping method that would allow more control over the number of birds we could trap at one time, when a trap was deployed, and target trapping of specific individuals. We adopted a relatively novel trapping technique used primarily for shorebirds, whoosh nets, to trap Band-tailed Pigeons at 3 different sites where birds were being fed by local landowners. During 2013–2015, whoosh nets were used to trap 702 Band-tailed Pigeons at 3 different locations in New Mexico. We captured 12.54 ± 8.19 pigeons per shot over 56 capture events across 3 locations (range: 2–39). Some superficial injuries occurred using this technique and typically involved damage to the primary and secondary wing coverts. In 2013, 24% of captured birds had an injury of this nature, but after modifying the net speed, injury rates in 2014 and 2015 dropped to 8% and 7%, respectively. Recaptured previously injured birds showed new feather growth within 2 weeks and showed no signs of injury after 4 weeks. Whoosh nets proved to be a highly effective solution for trapping large numbers of pigeons at baited sites. These systems are easily transported, quickly deployed, and easily adapted to a variety of site conditions.<span>&nbsp;</span></span></p>","language":"English","publisher":"The Wilson Ornithological Society","doi":"10.1676/16-069.1","usgsCitation":"Coxen, C.L., Collins, D.P., and Carleton, S.A., 2018, Capture efficiency and injury rates of band-tailed pigeons using whoosh nets: Wilson Journal of Ornithology, v. 130, no. 1, p. 321-326, https://doi.org/10.1676/16-069.1.","productDescription":"6 p.","startPage":"321","endPage":"326","ipdsId":"IP-076977","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","city":"Los Alamos, Silver City, Weed","volume":"130","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc4","contributors":{"authors":[{"text":"Coxen, Christopher L.","contributorId":198545,"corporation":false,"usgs":false,"family":"Coxen","given":"Christopher","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":735043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Daniel P.","contributorId":198065,"corporation":false,"usgs":false,"family":"Collins","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":735044,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carleton, Scott A. 0000-0001-9609-650X scarleton@usgs.gov","orcid":"https://orcid.org/0000-0001-9609-650X","contributorId":4060,"corporation":false,"usgs":true,"family":"Carleton","given":"Scott","email":"scarleton@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734983,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196685,"text":"70196685 - 2018 - Seismicity in the Challis, Idaho region, January 2014 - May 2017: Late aftershocks of the 1983 Ms 7.3 Borah Peak earthquake","interactions":[],"lastModifiedDate":"2018-11-02T14:54:58","indexId":"70196685","displayToPublicDate":"2018-05-09T14:54:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Seismicity in the Challis, Idaho region, January 2014 - May 2017: Late aftershocks of the 1983 Ms 7.3 Borah Peak earthquake","docAbstract":"<p><span>In April 2014, after about 20 yrs of relatively low seismicity, an energetic earthquake sequence (maximum&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>L</mi></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><i><span id=\"MathJax-Span-14\" class=\"mi\">M</span></i><sub><span id=\"MathJax-Span-15\" class=\"mi\">L</span></sub></span></span></span></span></span></span><span>&nbsp;4.8) began 25–30&nbsp;km northwest of the 1983&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>s</mi></msub></math>\"><span id=\"MathJax-Span-16\" class=\"math\"><span><span id=\"MathJax-Span-17\" class=\"mrow\"><span id=\"MathJax-Span-18\" class=\"msub\"><i><span id=\"MathJax-Span-19\" class=\"mi\">M</span></i><sub><span id=\"MathJax-Span-20\" class=\"mi\">s</span></sub></span></span></span></span></span></span><span>&nbsp;7.3 Borah Peak earthquake rupture area near the town of Challis, Idaho. This sequence ended in the fall of 2014, but in January 2015, a second energetic sequence (maximum <span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>L</mi></msub></math>\"><span id=\"MathJax-Span-11\" class=\"math\"><span id=\"MathJax-Span-12\" class=\"mrow\"><span id=\"MathJax-Span-13\" class=\"msub\"><i><span id=\"MathJax-Span-14\" class=\"mi\">M</span></i><sub><span id=\"MathJax-Span-15\" class=\"mi\">L</span></sub></span></span></span></span></span></span><span>&nbsp;5.0) began about 20&nbsp;km to the southeast. Modest seismicity has continued in both regions with&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot;>&amp;#x223C;</mo><mn xmlns=&quot;&quot;>1000</mn></math>\"><span id=\"MathJax-Span-26\" class=\"math\"><span><span id=\"MathJax-Span-27\" class=\"mrow\"><span id=\"MathJax-Span-28\" class=\"mo\">∼</span><span id=\"MathJax-Span-29\" class=\"mn\">1000</span></span></span></span></span></span><span>&nbsp;earthquakes detected and located through May 2017. To better characterize the seismicity in the area, we deployed a seven‐station local seismometer network during April–October 2014; one of the stations remained active until July 2015. Here, we report updated locations for earthquakes in the Challis area for 1 January 2014–31 May 2017. Using a combination of absolute and differential arrival times, we generated a catalog of high‐accuracy relocations. The earthquakes clustered into four primary groups, three of them with strikes similar to the Lost River fault—the fault responsible for the 1983 Borah Peak event. We used a modified cut‐and‐paste method to determine moment tensors for 15 of the largest events. All of the moment tensors showed normal faulting with nodal plane strikes consistent with the trend of the relocated seismicity and the regional stress field. We suggest that the recent seismicity near Challis is best interpreted as a continuation of the 1983&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>s</mi></msub></math>\"><span id=\"MathJax-Span-30\" class=\"math\"><span><span id=\"MathJax-Span-31\" class=\"mrow\"><span id=\"MathJax-Span-32\" class=\"msub\"><span id=\"MathJax-Span-33\" class=\"mi\">M</span><span id=\"MathJax-Span-34\" class=\"mi\">s</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Ms</span></span></span><span>&nbsp;7.3 Borah Peak aftershock sequence, which is unusually long compared to plate boundary aftershock sequences because of the lower regional strain rate.</span></p>","language":"English","publisher":"SSA","doi":"10.1785/0220180058","usgsCitation":"Pang, G., Koper, K.D., Stickney, M.C., Pechmann, J.C., Burlacu, R., Pankow, K.L., Payne, S., and Benz, H.M., 2018, Seismicity in the Challis, Idaho region, January 2014 - May 2017: Late aftershocks of the 1983 Ms 7.3 Borah Peak earthquake: Seismological Research Letters, v. 89, no. 4, p. 1366-1378, https://doi.org/10.1785/0220180058.","productDescription":"13 p.","startPage":"1366","endPage":"1378","ipdsId":"IP-096774","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":359131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.8,\n              43.8\n            ],\n            [\n              -113.4,\n              43.8\n            ],\n            [\n              -113.4,\n              44.8\n            ],\n            [\n              -114.8,\n              44.8\n            ],\n            [\n              -114.8,\n              43.8\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"89","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5c10a9c4e4b034bf6a7e5448","contributors":{"authors":[{"text":"Pang, Guanning","contributorId":204444,"corporation":false,"usgs":false,"family":"Pang","given":"Guanning","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":733963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koper, Keith D.","contributorId":175489,"corporation":false,"usgs":false,"family":"Koper","given":"Keith","email":"","middleInitial":"D.","affiliations":[{"id":27579,"text":"Swiss Federal Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":733964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stickney, Michael C.","contributorId":204445,"corporation":false,"usgs":false,"family":"Stickney","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":733965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pechmann, James C.","contributorId":152323,"corporation":false,"usgs":false,"family":"Pechmann","given":"James","email":"","middleInitial":"C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":733966,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burlacu, Relu","contributorId":204446,"corporation":false,"usgs":false,"family":"Burlacu","given":"Relu","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":733967,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pankow, Kristine L.","contributorId":204447,"corporation":false,"usgs":false,"family":"Pankow","given":"Kristine","email":"","middleInitial":"L.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":733968,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Payne, Suzette","contributorId":204448,"corporation":false,"usgs":false,"family":"Payne","given":"Suzette","email":"","affiliations":[{"id":27243,"text":"Idaho National Laboratory","active":true,"usgs":false}],"preferred":false,"id":733969,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":733970,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70227678,"text":"70227678 - 2018 - Incorporating road crossing data into vehicle collision risk models for moose (Alces americanus) in Massachusetts, USA","interactions":[],"lastModifiedDate":"2022-01-26T16:42:09.642427","indexId":"70227678","displayToPublicDate":"2018-05-09T10:37:51","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Incorporating road crossing data into vehicle collision risk models for moose (<i>Alces americanus</i>) in Massachusetts, USA","title":"Incorporating road crossing data into vehicle collision risk models for moose (Alces americanus) in Massachusetts, USA","docAbstract":"<p><span>Wildlife–vehicle collisions are a human safety issue and may negatively impact wildlife populations. Most wildlife–vehicle collision studies predict high-risk road segments using only collision data. However, these data lack biologically relevant information such as wildlife population densities and successful road-crossing locations. We overcome this shortcoming with a new method that combines successful road crossings with vehicle collision data, to identify road segments that have both high biological relevance and high risk. We used moose (</span><i>Alces americanus</i><span>) road-crossing locations from 20 moose collared with Global Positioning Systems as well as moose–vehicle collision (MVC) data in the state of Massachusetts, USA, to create multi-scale resource selection functions. We predicted the probability of moose road crossings and MVCs across the road network and combined these surfaces to identify road segments that met the dual criteria of having high biological relevance and high risk for MVCs. These road segments occurred mostly on larger roadways in natural areas and were surrounded by forests, wetlands, and a heterogenous mix of land cover types. We found MVCs resulted in the mortality of 3% of the moose population in Massachusetts annually. Although there have been only three human fatalities related to MVCs in Massachusetts since 2003, the human fatality rate was one of the highest reported in the literature. The rate of MVCs relative to the size of the moose population and the risk to human safety suggest a need for road mitigation measures, such as fencing, animal detection systems, and large mammal-crossing structures on roadways in Massachusetts.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s00267-018-1058-x","usgsCitation":"Zeller, K., Wattles, D., and Destefano, S., 2018, Incorporating road crossing data into vehicle collision risk models for moose (Alces americanus) in Massachusetts, USA: Environmental Management, v. 62, p. 518-528, https://doi.org/10.1007/s00267-018-1058-x.","productDescription":"11 p.","startPage":"518","endPage":"528","ipdsId":"IP-068512","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":394877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"62","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeller, Katherine 0000-0002-2913-6660","orcid":"https://orcid.org/0000-0002-2913-6660","contributorId":255403,"corporation":false,"usgs":false,"family":"Zeller","given":"Katherine","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":831702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wattles, David","contributorId":255402,"corporation":false,"usgs":false,"family":"Wattles","given":"David","affiliations":[{"id":51525,"text":"Massachusetts Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":831703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Destefano, Stephen 0000-0003-2472-8373","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":272197,"corporation":false,"usgs":true,"family":"Destefano","given":"Stephen","email":"","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831701,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70271969,"text":"70271969 - 2018 - Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction","interactions":[],"lastModifiedDate":"2025-09-29T14:56:13.497511","indexId":"70271969","displayToPublicDate":"2018-05-09T09:50:05","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5098,"text":"Remote Sensing Applications: Society and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction","docAbstract":"<p><span>To protect ecosystem services and the increasing&nbsp;wildland urban interface&nbsp;in a world with fire, comprehensive maps of wildland fuels are needed to predict fire behavior and effects. Traditionally, fuels have been categorized into a classification scheme whereby a single metric represents vegetation composition and structure, which can then be parameterized based on variable vegetation amount and condition.&nbsp;Remote sensing&nbsp;has been used to extrapolate between known field plots across the landscape, however until recently, those technologies have had limited ability to characterize fuels (e.g., composition, horizontal and vertical connectivity). Using new technologies (imaging spectroscopy and LIDAR), the objectives of this study are to assess: 1) how fuel characteristics observed from remote sensing affect categorical fuel classifications, and 2) how fuel characteristics affect landscape-scale fire behavior (spread rate, areal extent and perimeter). The analysis was conducted over the 2014 California King Fire that burned ~40,000 ha over lands with varying use and history and has unique remote sensing observations from before and after the fire. This analysis compares fuel classifications from a synergistic field, model, and&nbsp;Landsat&nbsp;approach (LANDFIRE) and products derived from the Airborne Visible/Infrared Imaging Spectrometer and LIDAR (MapFUELS). Each classification focuses on different fuel characteristics, which were then used to compare differences in a fire simulation model (CAWFE) and actual fire behavior. The results show that fuel characteristic inputs such as horizontal connectivity or fuel type and vertical structure affect fire spread rate and final fire extent (respectively). These results present the opportunity for future integration of fuel characteristics observed at coarser resolutions (900 m</span><sup>2</sup><span>) into predictions of fire behavior a similar spatial resolutions (as opposed to the current standard based on empirical relationships between fuel and fire behavior at ~12 m</span><sup>2</sup><span>&nbsp;resolution).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsase.2018.04.010","usgsCitation":"Stavros, E.N., Coen, J., Peterson, B., Singh, H., Kennedy, K., Ramirez, C., and Schimel, D., 2018, Use of imaging spectroscopy and LIDAR to characterize fuels for fire behavior prediction: Remote Sensing Applications: Society and Environment, v. 11, p. 41-50, https://doi.org/10.1016/j.rsase.2018.04.010.","productDescription":"10 p.","startPage":"41","endPage":"50","ipdsId":"IP-097303","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":496224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stavros, E. Natasha","contributorId":361822,"corporation":false,"usgs":false,"family":"Stavros","given":"E.","middleInitial":"Natasha","affiliations":[{"id":27365,"text":"NASA Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":949522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coen, Janice","contributorId":361823,"corporation":false,"usgs":false,"family":"Coen","given":"Janice","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":949523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":949524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singh, Harshvardhan","contributorId":361826,"corporation":false,"usgs":false,"family":"Singh","given":"Harshvardhan","affiliations":[{"id":86363,"text":"Indian Institute of Space Science and Technology","active":true,"usgs":false}],"preferred":false,"id":949525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Kama","contributorId":361827,"corporation":false,"usgs":false,"family":"Kennedy","given":"Kama","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":949526,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramirez, Carlos","contributorId":177061,"corporation":false,"usgs":false,"family":"Ramirez","given":"Carlos","email":"","affiliations":[],"preferred":false,"id":949527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schimel, David","contributorId":146637,"corporation":false,"usgs":false,"family":"Schimel","given":"David","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":949528,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70198061,"text":"70198061 - 2018 - Ecological genomics predicts climate vulnerability in an endangered southwestern songbird","interactions":[],"lastModifiedDate":"2018-07-16T11:21:43","indexId":"70198061","displayToPublicDate":"2018-05-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ecological genomics predicts climate vulnerability in an endangered southwestern songbird","docAbstract":"<p>Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (<i>Empidonax traillii</i>), and find the endangered desert southwestern subspecies (<i>E. t. extimus</i>) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability – the mismatch between current and predicted future genotype–environment relationships – indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate‐associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype–environment relationships into landscape‐scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups.</p>","language":"English","publisher":"Wiley","doi":"10.1111/ele.12977","usgsCitation":"Ruegg, K., Bay, R.A., Anderson, E.C., Saracco, J.F., Harrigan, R.J., Whitfield, M.J., Paxton, E., and Smith, T.B., 2018, Ecological genomics predicts climate vulnerability in an endangered southwestern songbird: Ecology Letters, v. 21, p. 1085-1096, https://doi.org/10.1111/ele.12977.","productDescription":"12 p.","startPage":"1085","endPage":"1096","ipdsId":"IP-095047","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":355634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5b46e58de4b060350a15d1cc","contributors":{"authors":[{"text":"Ruegg, Kristin","contributorId":206224,"corporation":false,"usgs":false,"family":"Ruegg","given":"Kristin","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bay, Rachael A.","contributorId":206219,"corporation":false,"usgs":false,"family":"Bay","given":"Rachael","email":"","middleInitial":"A.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Eric C.","contributorId":206220,"corporation":false,"usgs":false,"family":"Anderson","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":37289,"text":"Southwest Fisheries Science Center, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":739825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saracco, James F.","contributorId":206221,"corporation":false,"usgs":false,"family":"Saracco","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":739826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harrigan, Ryan J.","contributorId":206222,"corporation":false,"usgs":false,"family":"Harrigan","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739827,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitfield, Mary J.","contributorId":174933,"corporation":false,"usgs":false,"family":"Whitfield","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":739828,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","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":false,"id":739829,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Thomas B.","contributorId":206223,"corporation":false,"usgs":false,"family":"Smith","given":"Thomas","email":"","middleInitial":"B.","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":739830,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70196839,"text":"ofr20181079 - 2018 - Compilation and analysis of multiple groundwater-quality datasets for Idaho","interactions":[],"lastModifiedDate":"2018-05-14T10:25:12","indexId":"ofr20181079","displayToPublicDate":"2018-05-09T00:00:00","publicationYear":"2018","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":"2018-1079","title":"Compilation and analysis of multiple groundwater-quality datasets for Idaho","docAbstract":"<p class=\"p1\">Groundwater is an important source of drinking and irrigation water throughout Idaho, and groundwater quality is monitored by various Federal, State, and local agencies. The historical, multi-agency records of groundwater quality include a valuable dataset that has yet to be compiled or analyzed on a statewide level. The purpose of this study is to combine groundwater-quality data from multiple sources into a single database, to summarize this dataset, and to perform bulk analyses to reveal spatial and temporal patterns of water quality throughout Idaho. Data were retrieved from the Water Quality Portal (<span class=\"s1\"><a href=\"https://www.waterqualitydata.us/\" target=\"blank\" data-mce-href=\"https://www.waterqualitydata.us/\">https://www.waterqualitydata.us/</a></span>), the Idaho Department of Environmental Quality, and the Idaho Department of Water Resources. Analyses included counting the number of times a sample location had concentrations above Maximum Contaminant Levels (MCL), performing trends tests, and calculating correlations between water-quality analytes. The water-quality database and the analysis results are available through USGS ScienceBase (<span class=\"s1\"><a href=\"https://doi.org/10.5066/F72V2FBG\" target=\"blank\" data-mce-href=\"https://doi.org/10.5066/F72V2FBG\">https://doi.org/10.5066/F72V2FBG</a></span>).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181079","collaboration":"Prepared in cooperation with the Idaho Department of Environmental Quality","usgsCitation":"Hundt, S.A., and Hopkins, C.B., 2018, Compilation and analysis of multiple groundwater-quality datasets for Idaho: U.S. Geological Survey Open-File Report 2018-1079, 3 p., plus presentation, https://doi.org/10.3133/ofr20181079.","productDescription":"Report: iv, 3 p.; Presentation: 46 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088346","costCenters":[{"id":343,"text":"Idaho Water Science 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 \"}}]}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"http://id.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://id.water.usgs.gov\">Idaho Water Science Center</a><br> U.S. Geological Survey<br> 230 Collins Road<br> Boise, Idaho 83702</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Results<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-05-09","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdcc","contributors":{"authors":[{"text":"Hundt, Stephen A. 0000-0002-6484-0637 shundt@usgs.gov","orcid":"https://orcid.org/0000-0002-6484-0637","contributorId":204779,"corporation":false,"usgs":true,"family":"Hundt","given":"Stephen A.","email":"shundt@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":734663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopkins, Candice B. 0000-0003-3207-7267 chopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-3207-7267","contributorId":1379,"corporation":false,"usgs":true,"family":"Hopkins","given":"Candice","email":"chopkins@usgs.gov","middleInitial":"B.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734664,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196848,"text":"fs20183030 - 2018 - Ecosystems science: Genes to landscapes","interactions":[{"subject":{"id":70156264,"text":"fs20153057 - 2015 - Science from genes to landscapes","indexId":"fs20153057","publicationYear":"2015","noYear":false,"title":"Science from genes to landscapes"},"predicate":"SUPERSEDED_BY","object":{"id":70196848,"text":"fs20183030 - 2018 - Ecosystems science: Genes to landscapes","indexId":"fs20183030","publicationYear":"2018","noYear":false,"title":"Ecosystems science: Genes to landscapes"},"id":1}],"lastModifiedDate":"2018-05-14T11:32:31","indexId":"fs20183030","displayToPublicDate":"2018-05-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3030","title":"Ecosystems science: Genes to landscapes","docAbstract":"<p>Bountiful fisheries, healthy and resilient wildlife, flourishing forests and vibrant grasslands are coveted resources that benefit all Americans. U.S. Geological Survey (USGS) science supports the conservation and management of the Nation’s fish and wildlife, and the landscapes they inhabit. Our biological resources—ecosystems and the wild things that live in them—are the foundation of our conservation heritage and an economic asset to current and future generations of Americans.</p><p>The USGS Ecosystems Mission Area, the biological research arm of the Department of the Interior (DOI), provides science to help America achieve sustainable management and conservation of its biological resources. This work is done within the broader mission of the USGS—to serve the Nation with science that advances understanding of our natural resources, informs land and water stewardship, and helps safeguard communities from natural and environmental hazards. The Ecosystems Mission Area provides research, technical assistance, and education conducted by Cooperative Research Units and Science Centers located in nearly every State.</p><p>The quality of life and economic strength in America hinges on healthy ecosystems that support living things and natural processes. Ecosystem science better enables society to understand how and why ecosystems change and to guide actions that can prevent damage to, and restore and sustain ecosystems. It is through this knowledge that informed decisions are made about natural resources that can enhance our Nation’s economic and environmental well-being.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183030","usgsCitation":"U.S. Geological Survey, 2018, Ecosystems science--Genes to landscapes: U.S. Geological Survey Fact Sheet 2018-3030, 4 p., https://doi.org/10.3133/fs20183030.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-094067","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":354024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3030/fs20183030.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3030"},{"id":354023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3030/coverthb.jpg"}],"country":"United 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States\"}}]}","contact":"<p><a href=\"http://www.usgs.gov/ecosystems/\" target=\"blank\" data-mce-href=\"http://www.usgs.gov/ecosystems/\">Ecosystems Mission Area</a><br> <a target=\"blank\">http://www.usgs.gov/ask/</a><br> 1-888-ASK-USGS (1-888-275-8747)</p>","tableOfContents":"<ul><li>Ecosystems Core Priorities and Examples of USGS Science<br></li><li>Natural Resource Stewardship<br></li><li>Advances in National Energy and Security<br></li><li>Invasive Species and Wildlife Disease<br></li><li>Emerging and Existing Threats<br></li><li>USGS Science at Work<br></li><li>Infrastructure Development<br></li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2018-05-09","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdca","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":127955,"corporation":true,"usgs":false,"organization":"U.S. Geological 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,{"id":70195729,"text":"ofr20181013 - 2018 - Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River Valley, Washington","interactions":[],"lastModifiedDate":"2018-05-14T10:33:56","indexId":"ofr20181013","displayToPublicDate":"2018-05-09T00:00:00","publicationYear":"2018","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":"2018-1013","title":"Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River Valley, Washington","docAbstract":"<p>Lahars large enough to reach populated areas are a hazard at Mount Adams, a massive volcano in the southern Cascade Range of Washington State (fig. 1). It is considered to be still active and has the potential to erupt again. By definition, lahars are gravity-driven flows of water-saturated mixtures of mud and rock (plus or minus ice, wood, and other debris), which originate from volcanoes and have a variety of potential triggering mechanisms (Vallance, 2000; Vallance and Iverson, 2015). Flowing mixtures can range in fluid consistency from something like a milkshake to something more like wet concrete, and they behave like flash floods, in that they can appear suddenly in river channels with little warning and commonly have boulder- or log-choked flow fronts. Lahars are hazardous because they can flow rapidly in confined valleys (commonly 20–35 miles per hour [mph] or 9–16 meters per second [m/s]), can travel more than 100 miles (mi) (161 kilometers [km]) from a source volcano, and can move with incredible destructive force, carrying multi-ton boulders and logs that can act as battering rams (Pierson, 1998). The biggest threats from lahars to downstream communities are present during eruptive activity, and impacts to communities can be dire. For example, a very large eruption-triggered lahar in Colombia in 1985 surprised and killed more than 20,000 people in a large town located about 45 mi (72 km) downstream and out of sight of the volcano that produced it (Pierson and others, 1990).</p><p>Mount Adams, one of the largest volcanoes in the Cascade Range, is a composite stratocone composed primarily of andesite lava flows. It has been the most continuously active volcano within the 480-mi<sup>2</sup> Mount Adams volcanic field—a region covering parts of Klickitat, Skamania, Yakima, andLewis Counties and part of the Yakama Nation Reservation in Washington State (Hildreth and Fierstein,1995, 1997). About 500,000 years in age, Mount Adams reached its present size by about 15,000 years ago, primarily through the episodic effusion of lava flows; it has not had a history of major explosive eruptions like Mount St. Helens, its neighbor to the west. Timing of the most recent eruptive activity (recorded by four thin tephra layers) is on the order of 1,000 years ago; the tephras are bracketed by 2,500-year-old and 500-year-old ash layers from Mount St. Helens (Hildreth and Fierstein, 1995, 1997). Mount Adams currently shows no signs of renewed unrest.</p><p>Eruptive history does not tell us everything we need to know about hazards at Mount Adams, however, which are fully addressed in the volcano hazard assessment for Mount Adams (W.E. Scott and others, 1995). This volcano has had a long-active hydrothermal system that circulated acidic hydrothermal fluids, formed by the solution of volcanic gases in heated groundwater, through fractures and permeable zones into upper parts of the volcanic cone. Acid sulfate leaching of rocks in the summit area may still be occurring, but chemical and thermal evidence suggests that the main hydrothermal system is no longer active at Mount Adams (Nathenson and Mariner, 2013). However, these rock-weakening chemical reactions have operated long enough to change about 0.4 cubic miles (mi<sup>3</sup>) (1.7 cubic kilometers [km<sup>3</sup>]) of the hard lava rock in the volcano’s upper cone to a much weaker clay-rich rock, thus significantly reducing rock strength and thereby slope stability in parts of the cone (Finn and others, 2007). The two largest previous lahars from Mount Adams were triggered by landslides of hydrothermally altered rock from the upper southwestern flank of the cone, and any future large lahars are likely to be triggered by the same mechanism. Mount Rainier also has had extensive hydrothermal alteration of rock in its upper edifice, and it also has a history of large landslides that transform into lahars (K.M. Scott and others, 1995; Vallance and Scott, 1997; Reid and others, 2001).</p><p>The spatial depiction of modeled lahar inundation zones accompanying this report, shown in two different map perspectives, is intended to augment (not replace) the existing hazard maps for Mount Adams (W.E. Scott and others, 1995; Vallance, 1999). The maps in this report show potential areas of inundation by lahars of different initial volumes, which are determined by a computer model, LAHARZ (Iverson and others, 1998; Schilling, 1998). One map sheet presents LAHARZ-determined inundation areas on a normal plan-view shaded-relief map of the study area; the other gives an oblique perspective of the landscape with raised topography, as if one were viewing the landscape at an angle from an aircraft (Jenny and Patterson, 2007). LAHARZ was developed after the original hazard maps (based only on mapping of geologic deposits) were made. Predicted inundation zones on these maps provide an alternative approach to estimation of areas that could be inundated as lahars of different volumes pass through the valley. However, there is considerable uncertainty in the exact location of the hazard-zone boundaries shown on these maps, as well as on earlier maps.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181013","usgsCitation":"Griswold, J.P., Pierson, T.C., and Bard J.A., 2018, Modeled inundation limits of potential lahars from Mount Adams in the White Salmon River valley, Washington: U.S. Geological Survey Open-File Report 2018–1013, scale 1:75,000, 14 p., https://doi.org/10.3133/ofr20181013.","productDescription":"Sheet: 42.0 x 42.0 inches; Pamphlet: iii, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078093","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353953,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1013/ofr20181013_pamphlet.pdf","text":"Pamphlet","size":"18.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1013 Pamphlet"},{"id":353952,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1013/ofr20181013_sheet_.pdf","size":"41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1013"},{"id":353951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1013/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Adams, While Salmon River Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.8333,\n              45.682198608003404\n            ],\n            [\n              -121.25,\n              45.682198608003404\n            ],\n            [\n              -121.25,\n              46.25\n            ],\n            [\n              -121.8333,\n              46.25\n            ],\n            [\n              -121.8333,\n              45.682198608003404\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://volcanoes.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://volcanoes.usgs.gov/\">Volcano Science Center</a><br><a href=\"https://volcanoes.usgs.gov/observatories/cvo/\" target=\"_blank\" data-mce-href=\"https://volcanoes.usgs.gov/observatories/cvo/\">Cascades Volcano Observatory</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>1300 SE Cardinal Court<br>Vancouver, WA, 98683</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-05-09","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdce","contributors":{"authors":[{"text":"Griswold, Julia P. 0000-0001-5597-5030 griswold@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-5030","contributorId":202823,"corporation":false,"usgs":true,"family":"Griswold","given":"Julia","email":"griswold@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":729785,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierson, Thomas C. 0000-0001-9002-4273 tpierson@usgs.gov","orcid":"https://orcid.org/0000-0001-9002-4273","contributorId":2498,"corporation":false,"usgs":true,"family":"Pierson","given":"Thomas","email":"tpierson@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":729786,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bard, Joseph A. 0000-0003-3143-4007","orcid":"https://orcid.org/0000-0003-3143-4007","contributorId":202824,"corporation":false,"usgs":true,"family":"Bard","given":"Joseph A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":729787,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70196909,"text":"fs20183024 - 2018 - Lahar—River of volcanic mud and debris","interactions":[],"lastModifiedDate":"2018-05-14T10:23:05","indexId":"fs20183024","displayToPublicDate":"2018-05-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3024","title":"Lahar—River of volcanic mud and debris","docAbstract":"<p>Lahar, an Indonesian word for volcanic mudflow, is a mixture of water, mud, and volcanic rock flowing swiftly along a channel draining a volcano. Lahars can form during or after eruptions, or even during periods of inactivity. They are among the greatest threats volcanoes pose to people and property. Lahars can occur with little to no warning, and may travel great distances at high speeds, destroying or burying everything in their paths.</p><p>Lahars form in many ways. They commonly occur when eruptions melt snow and ice on snow-clad volcanoes; when rains fall on steep slopes covered with fresh volcanic ash; when crater lakes, volcano glaciers or lakes dammed by volcanic debris suddenly release water; and when volcanic landslides evolve into flowing debris. Lahars are especially likely to occur at erupting or recently active volcanoes.</p><p>Because lahars are so hazardous, U.S. Geological Survey scientists pay them close attention. They study lahar deposits and limits of inundation, model flow behavior, develop lahar-hazard maps, and work with community leaders and governmental authorities to help them understand and minimize the risks of devastating lahars.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183024","usgsCitation":"Major, J.J., Pierson, T.C., and Vallance, J.W., 2018, Lahar—River of volcanic mud and debris: U.S. Geological Survey Fact Sheet 2018–3024, 6 p., https://doi.org/10.3133/fs20183024.","productDescription":"Report: 6 p.; Video","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-090719","costCenters":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"links":[{"id":354035,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3024/fs20183024.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3024"},{"id":354036,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/fs/2018/3024/fs20183024_laharvideo.mp4","text":"Video","size":"18 MB","description":"Fact Sheet 2018-3024 Video"},{"id":354034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3024/coverthb_.jpg"}],"contact":"<p><a href=\"https://volcanoes.usgs.gov/\" target=\"_blank\" data-mce-href=\"https://volcanoes.usgs.gov/\">Volcano Science Center</a><br><a href=\"https://volcanoes.usgs.gov/observatories/cvo/\" target=\"_blank\" data-mce-href=\"https://volcanoes.usgs.gov/observatories/cvo/\">Cascades Volcano Observatory</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>1300 SE Cardinal Court<br>Vancouver, WA, 98683</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-05-09","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5afee6c1e4b0da30c1bfbdc8","contributors":{"authors":[{"text":"Major, Jon J. 0000-0003-2449-4466 jjmajor@usgs.gov","orcid":"https://orcid.org/0000-0003-2449-4466","contributorId":439,"corporation":false,"usgs":true,"family":"Major","given":"Jon","email":"jjmajor@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":734977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierson, Thomas C. 0000-0001-9002-4273 tpierson@usgs.gov","orcid":"https://orcid.org/0000-0001-9002-4273","contributorId":2498,"corporation":false,"usgs":true,"family":"Pierson","given":"Thomas","email":"tpierson@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":734978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":734979,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70201480,"text":"70201480 - 2018 - Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow","interactions":[],"lastModifiedDate":"2018-12-14T14:24:18","indexId":"70201480","displayToPublicDate":"2018-05-08T14:24:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow","docAbstract":"<p><span>Submarine groundwater fluxes across the seafloor facilitate important hydrological and biogeochemical exchanges between oceans and seabed sediment, yet few studies have investigated spatially distributed groundwater fluxes in deep‐ocean environments such as continental slopes. Heat has been previously applied as a submarine groundwater tracer using an analytical solution to a heat flow equation assuming steady state conditions and homogeneous thermal conductivity. These assumptions are often violated in shallow seabeds due to ocean bottom temperature changes or sediment property variations. Here heat tracing analysis techniques recently developed for terrestrial settings are applied in concert to examine the influences of groundwater flow, ocean temperature changes, and seabed thermal conductivity variations on deep‐ocean sediment temperature profiles. Temperature observations from the sediment and bottom ocean water on the Scotian Slope off eastern Canada are used to demonstrate how simple thermal methods for tracing groundwater can be employed if more comprehensive techniques indicate that the simplifying assumptions are valid. The spatial distribution of the inferred groundwater fluxes on the slope suggests a downward groundwater flow system with recharge occurring over the upper‐middle slope and discharge on the lower slope. We speculate that the downward groundwater flow inferred on the Scotian Slope is due to density‐driven processes arising from underlying salt domes, in contrast with upward slope systems driven by geothermal convection. Improvements in the design of future submarine hydrogeological studies are proposed for thermal data collection and groundwater flow analysis, including new equations that quantify the minimum detectable flux magnitude for a given sensor accuracy and profile length.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2017WR022353","usgsCitation":"Kurylyk, B.L., Irvine, D.J., Mohammed, A., Bense, V.F., Briggs, M.A., Loder, J., and Geshelin, Y., 2018, Rethinking the use of seabed sediment temperature profiles to trace submarine groundwater flow: Water Resources Research, v. 54, no. 7, p. 4595-4614, https://doi.org/10.1029/2017WR022353.","productDescription":"20 p.","startPage":"4595","endPage":"4614","ipdsId":"IP-095613","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022353","text":"Publisher Index Page"},{"id":360328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Scotian Slope","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -63,\n              41\n            ],\n            [\n              -60,\n              41\n            ],\n            [\n              -60,\n              43\n            ],\n            [\n              -63,\n              43\n            ],\n            [\n              -63,\n              41\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"54","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-07","publicationStatus":"PW","scienceBaseUri":"5c14cfb8e4b006c4f8545d3f","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":754277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Dylan J.","contributorId":190404,"corporation":false,"usgs":false,"family":"Irvine","given":"Dylan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":754278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohammed, A.A.","contributorId":211492,"corporation":false,"usgs":false,"family":"Mohammed","given":"A.A.","email":"","affiliations":[{"id":16660,"text":"University of Calgary","active":true,"usgs":false}],"preferred":false,"id":754279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bense, V. F.","contributorId":211493,"corporation":false,"usgs":false,"family":"Bense","given":"V.","email":"","middleInitial":"F.","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":754280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":754276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loder, J.W.","contributorId":211494,"corporation":false,"usgs":false,"family":"Loder","given":"J.W.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754281,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Geshelin, Y.","contributorId":211495,"corporation":false,"usgs":false,"family":"Geshelin","given":"Y.","email":"","affiliations":[{"id":38259,"text":"Bedford Institute of Oceanography, Dartmouth, Canada","active":true,"usgs":false}],"preferred":false,"id":754282,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70198904,"text":"70198904 - 2018 - Acquisition and dissemination of cephalosporin-resistant E. coli in migratory birds sampled at an Alaska landfill as inferred through genomic analysis","interactions":[],"lastModifiedDate":"2018-08-27T14:31:18","indexId":"70198904","displayToPublicDate":"2018-05-08T13:17:31","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Acquisition and dissemination of cephalosporin-resistant E. coli in migratory birds sampled at an Alaska landfill as inferred through genomic analysis","docAbstract":"<p>Antimicrobial resistance (AMR) in bacterial pathogens threatens global health, though the spread of AMR bacteria and AMR genes between humans, animals, and the environment is still largely unknown. Here, we investigated the role of wild birds in the epidemiology of AMR Escherichia coli. Using next-generation sequencing, we characterized cephalosporin-resistant E. coli cultured from sympatric gulls and bald eagles inhabiting a landfill habitat in Alaska to identify genetic determinants conferring AMR, explore potential transmission pathways of AMR bacteria and genes at this site, and investigate how their genetic diversity compares to isolates reported in other taxa. We found genetically diverse E. coli isolates with sequence types previously associated with human infections and resistance genes of clinical importance, including blaCTX-M and blaCMY. Identical resistance profiles were observed in genetically unrelated E. coli isolates from both gulls and bald eagles. Conversely, isolates with indistinguishable core-genomes were found to have different resistance profiles. Our findings support complex epidemiological interactions including bacterial strain sharing between gulls and bald eagles and horizontal gene transfer among E. coli harboured by birds. Results suggest that landfills may serve as a source for AMR acquisition and/or maintenance, including bacterial sequence types and AMR genes relevant to human health.</p>","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-018-25474-w","usgsCitation":"Ahlstrom, C., Bonnedahl, J., Woksepp, H., Hernandez, J., Bjorn, O., and Ramey, A.M., 2018, Acquisition and dissemination of cephalosporin-resistant E. coli in migratory birds sampled at an Alaska landfill as inferred through genomic analysis: Scientific Reports, v. 8, no. 1, 7361, https://doi.org/10.1038/s41598-018-25474-w.","productDescription":"7361","ipdsId":"IP-093073","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468771,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-25474-w","text":"Publisher Index Page"},{"id":437918,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70V8C2Q","text":"USGS data release","linkHelpText":"Sampling and Resistance and Genomic Typing of Cephalosporin-resistant E. coli in Gulls (Larus spp.) and Bald Eagles (Haliaeetus leucocephalus) in Southcentral Alaska, 2016"},{"id":356734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-05-09","publicationStatus":"PW","scienceBaseUri":"5b98a2c6e4b0702d0e842fe6","contributors":{"authors":[{"text":"Ahlstrom, Christina Ann 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":207262,"corporation":false,"usgs":false,"family":"Ahlstrom","given":"Christina Ann","affiliations":[],"preferred":false,"id":743366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonnedahl, Jonas","contributorId":181800,"corporation":false,"usgs":false,"family":"Bonnedahl","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":743364,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woksepp, Hanna","contributorId":207263,"corporation":false,"usgs":false,"family":"Woksepp","given":"Hanna","email":"","affiliations":[],"preferred":false,"id":743365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hernandez, Jorge","contributorId":203652,"corporation":false,"usgs":false,"family":"Hernandez","given":"Jorge","affiliations":[{"id":36674,"text":"Department of Microbiology, Kalmar County Hospital, Kalmar, Sweden","active":true,"usgs":false}],"preferred":false,"id":743363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjorn, Olsen","contributorId":207264,"corporation":false,"usgs":false,"family":"Bjorn","given":"Olsen","email":"","affiliations":[],"preferred":false,"id":743367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":743362,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196871,"text":"70196871 - 2018 - Application of microtremor horizontal-to-vertical spectral ratio (MHVSR) analysis for site characterization: State of the art","interactions":[],"lastModifiedDate":"2018-05-08T10:13:33","indexId":"70196871","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3503,"text":"Surveys in Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Application of microtremor horizontal-to-vertical spectral ratio (MHVSR) analysis for site characterization: State of the art","docAbstract":"<p><span>Nakamura (Q Rep Railway Tech Res Inst 30:25–33, 1989) p</span><span>opularized the application of the horizontal-to-vertical spectral ratio (HVSR) analysis of microtremor (seismic noise or ambient vibration) recordings to estimate the predominant frequency and amplification factor of earthquake shaking. During the following quarter century, popularity in the microtremor HVSR (MHVSR) method grew; studies have verified the stability of a site’s MHVSR response over time and validated the MHVSR response with that of earthquake HVSR response. Today, MHVSR analysis is a popular reconnaissance tool used worldwide for seismic microzonation and earthquake site characterization in numerous regions, specifically, in the mapping of site period or fundamental frequency and inverted for shear-wave velocity depth profiles, respectively. However, the ubiquity of MHVSR analysis is predominantly a consequence of its ease in application rather than our full understanding of its theory. We present the state of the art in MHVSR analyses in terms of the development of its theoretical basis, current state of practice, and we comment on its future for applications in earthquake site characterization.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10712-018-9464-4","usgsCitation":"Molnar, S., Cassidy, J.F., Castellaro, S., Cornou, C., Crow, H., Hunter, J.A., Matsushima, S., Sanchez-Sesma, F.J., and Yong, A., 2018, Application of microtremor horizontal-to-vertical spectral ratio (MHVSR) analysis for site characterization: State of the art: Surveys in Geophysics, no. Online First, https://doi.org/10.1007/s10712-018-9464-4.","ipdsId":"IP-097849","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":353984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"Online First","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-06","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd2","contributors":{"authors":[{"text":"Molnar, S.","contributorId":203574,"corporation":false,"usgs":false,"family":"Molnar","given":"S.","email":"","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":734821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassidy, J. F.","contributorId":203575,"corporation":false,"usgs":false,"family":"Cassidy","given":"J.","email":"","middleInitial":"F.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":734823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castellaro, S.","contributorId":203576,"corporation":false,"usgs":false,"family":"Castellaro","given":"S.","email":"","affiliations":[{"id":36660,"text":"Università di Bologna","active":true,"usgs":false}],"preferred":false,"id":734822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornou, C.","contributorId":203577,"corporation":false,"usgs":false,"family":"Cornou","given":"C.","affiliations":[{"id":36661,"text":"Université Grenoble Alpes","active":true,"usgs":false}],"preferred":false,"id":734824,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crow, H.","contributorId":203578,"corporation":false,"usgs":false,"family":"Crow","given":"H.","email":"","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":734825,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, J. A.","contributorId":203579,"corporation":false,"usgs":false,"family":"Hunter","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":7219,"text":"Natural Resources Canada","active":true,"usgs":false}],"preferred":false,"id":734826,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matsushima, S.","contributorId":203580,"corporation":false,"usgs":false,"family":"Matsushima","given":"S.","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":734827,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sanchez-Sesma, F. J.","contributorId":204731,"corporation":false,"usgs":false,"family":"Sanchez-Sesma","given":"F.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":734828,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":734820,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196867,"text":"70196867 - 2018 - Strategies for effective collaborative manuscript development in interdisciplinary science teams","interactions":[],"lastModifiedDate":"2018-05-08T11:31:29","indexId":"70196867","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Strategies for effective collaborative manuscript development in interdisciplinary science teams","docAbstract":"<p><span>Science is increasingly being conducted in large, interdisciplinary teams. As team size increases, challenges can arise during manuscript development, where achieving one team goal (e.g., inclusivity) may be in direct conflict with other goals (e.g., efficiency). Here, we present strategies for effective collaborative manuscript development that draw from our experiences in an interdisciplinary science team writing collaborative manuscripts for six years. These strategies are rooted in six guiding principles that were important to our team: to create a transparent, inclusive, and accountable research team that promotes and protects team members who have less power to influence decision‐making while fostering creativity and productivity. To help alleviate the conflicts that can arise in collaborative manuscript development, we present the following strategies: understand your team composition, create an authorship policy and discuss authorship early and often, openly announce manuscript ideas, identify and communicate the type of manuscript and lead author management style, and document and describe authorship contributions. These strategies can help reduce the probability of group conflict, uphold individual and team values, achieve fair authorship practices, and increase science productivity.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2206","usgsCitation":"Oliver, S., Fergus, C.E., Skaff, N.K., Wagner, T., Tan, P., Cheruvelil, K.S., and Soranno, P.A., 2018, Strategies for effective collaborative manuscript development in interdisciplinary science teams: Ecosphere, v. 9, no. 4, p. 1-13, https://doi.org/10.1002/ecs2.2206.","productDescription":"e02206; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-090031","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468773,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2206","text":"Publisher Index Page"},{"id":354006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-24","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd6","contributors":{"authors":[{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":734883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skaff, Nicholas K.","contributorId":204098,"corporation":false,"usgs":false,"family":"Skaff","given":"Nicholas","email":"","middleInitial":"K.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":734886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheruvelil, Kendra Spence","contributorId":150607,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"Spence","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734887,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734888,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196872,"text":"70196872 - 2018 - Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section","interactions":[],"lastModifiedDate":"2018-05-08T10:10:22","indexId":"70196872","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section","docAbstract":"<p><span>Hotter droughts are becoming more common as climate change progresses, and they may already have caused instances of forest dieback on all forested continents. Learning from hotter droughts, including where on the landscape forests are more or less vulnerable to these events, is critical to help resource managers proactively prepare for the future. As part of our Leaf to Landscape Project, we measured the response of giant sequoia, the world’s largest tree species, to the extreme 2012–2016 hotter drought in California. The project integrated leaf-level physiology&nbsp;measurements, crown-level foliage dieback surveys, and remotely sensed canopy water content (CWC) to shed light on mechanisms and spatial patterns in drought response. Here we summarize initial findings, present a conceptual model of drought response, and discuss management implications; details are presented in the other four articles of the special section on Giant Sequoias and Drought. Giant sequoias exhibited both leaf- and canopy-level responses that were effective in protecting whole-tree hydraulic integrity for the vast majority of individual sequoias. Very few giant sequoias died during the drought compared to other mixed conifer&nbsp;tree species; however, the magnitude of sequoia drought response varied across the landscape. This variability was partially explained by local site characteristics, including variables related to site water balance</span><span>. We found that low CWC is an indicator of recent foliage dieback, which occurs when stress levels are high enough that leaf-level adjustments alone are insufficient for giant sequoias to maintain hydraulic integrity. CWC or change in CWC may be useful indicators of<span> drought stress</span><span>&nbsp;</span>that reveal patterns of vulnerability to future hotter droughts. Future work will measure recovery from the drought and strengthen our ability to interpret CWC maps. Our ultimate goal is to produce giant sequoia vulnerability maps to help target management actions, such as reducing other stressors, increasing resistance to hotter drought through prescribed fire or mechanical thinning, and planting sequoias in projected future suitable habitat, which may occur outside current grove distributions. We suggest that managers compare different types of vulnerability assessments and combine vulnerability maps with other sources of information to inform decisions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.03.028","usgsCitation":"Nydick, K.R., Stephenson, N.L., Ambrose, A.R., Asner, G.P., Baxter, W.L., Das, A., Dawson, T.E., Martin, R.E., and Paz-Kagan, T., 2018, Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section: Forest Ecology and Management, v. 419-420, p. 249-256, https://doi.org/10.1016/j.foreco.2018.03.028.","productDescription":"8 p.","startPage":"249","endPage":"256","ipdsId":"IP-091082","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.03.028","text":"Publisher Index Page"},{"id":353982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"419-420","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd0","contributors":{"authors":[{"text":"Nydick, Koren R.","contributorId":196601,"corporation":false,"usgs":false,"family":"Nydick","given":"Koren","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":734830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ambrose, Anthony R.","contributorId":204732,"corporation":false,"usgs":false,"family":"Ambrose","given":"Anthony","email":"","middleInitial":"R.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":734832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baxter, Wendy L.","contributorId":204733,"corporation":false,"usgs":false,"family":"Baxter","given":"Wendy","email":"","middleInitial":"L.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":734833,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734834,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dawson, Todd E.","contributorId":176594,"corporation":false,"usgs":false,"family":"Dawson","given":"Todd","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734835,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Roberta E.","contributorId":201234,"corporation":false,"usgs":false,"family":"Martin","given":"Roberta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734836,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paz-Kagan, Tarin","contributorId":196597,"corporation":false,"usgs":false,"family":"Paz-Kagan","given":"Tarin","email":"","affiliations":[],"preferred":false,"id":734837,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70196868,"text":"70196868 - 2018 - Downstream impacts of dams: shifts in benthic invertivorous fish assemblages","interactions":[],"lastModifiedDate":"2018-05-14T13:12:42","indexId":"70196868","displayToPublicDate":"2018-05-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Downstream impacts of dams: shifts in benthic invertivorous fish assemblages","docAbstract":"<p><span>Impoundments alter connectivity, sediment transport and water discharge in rivers and floodplains, affecting recruitment, habitat and resource availability for fish including benthic invertivorous fish, which represent an important link between primary producers and higher trophic levels in tropical aquatic ecosystems. We investigated long-term changes to water regime, water quality, and invertivorous fish assemblages pre and post impoundment in three rivers downstream of Porto Primavera Reservoir in south Brazil: Paraná, Baía and Ivinhema rivers. Impacts were distinct in the Paraná River, which is fully obstructed by the dam, less evident in the Baía River which is partially obstructed by the dam, but absent in the unimpounded Ivinhema River. Changes in water regime were reflected mainly as changes in water-level fluctuation with little effect on timing. Water transparency increased in the Paraná River post impoundment but did not change in the Baía and Ivinhema rivers. Changes in fish assemblages included a decrease in benthic invertivorous fish in the Paraná River and a shift in invertivorous fish assemblage structure in the Baía and Paraná rivers but not in the unimpounded Ivinhema River. Changes in water regime and water transparency, caused by impoundment, directly or indirectly impacted invertivorous fish assemblages. Alterations of fish assemblages following environmental changes have consequences over the entire ecosystem, including a potential decrease in the diversity of mechanisms for energy flow. We suggest that keeping existing unimpounded tributaries free of dams, engineering artificial floods, and intensive management of fish habitat within the floodplain may preserve native fish assemblages and help maintain functionality and ecosystem services in highly impounded rivers.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00027-018-0579-y","usgsCitation":"Granzotti, R.V., Miranda, L.E., Agostinho, A.A., and Gomes, L.C., 2018, Downstream impacts of dams: shifts in benthic invertivorous fish assemblages: Aquatic Sciences, v. 80, p. 1-14, https://doi.org/10.1007/s00027-018-0579-y.","productDescription":"Article 28; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-090186","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":354005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Baía River; Ivinhema River; Paraná River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -53,\n              -23\n            ],\n            [\n              -53.66,\n              -23\n            ],\n            [\n              -53.66,\n              -22.33\n            ],\n            [\n              -53,\n              -22.33\n            ],\n            [\n              -53,\n              -23\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"80","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-23","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd4","contributors":{"authors":[{"text":"Granzotti, Rafaela Vendrametto","contributorId":204754,"corporation":false,"usgs":false,"family":"Granzotti","given":"Rafaela","email":"","middleInitial":"Vendrametto","affiliations":[],"preferred":false,"id":734880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agostinho, Angelo A.","contributorId":204501,"corporation":false,"usgs":false,"family":"Agostinho","given":"Angelo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gomes, Luiz Carlos","contributorId":88227,"corporation":false,"usgs":true,"family":"Gomes","given":"Luiz","email":"","middleInitial":"Carlos","affiliations":[],"preferred":false,"id":734882,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206538,"text":"70206538 - 2018 - A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling","interactions":[],"lastModifiedDate":"2020-06-19T16:12:17.863811","indexId":"70206538","displayToPublicDate":"2018-05-07T10:04:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling","docAbstract":"<p><span>The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m</span><sup>−3</sup><span>&nbsp;with a standard deviation of 44 kg m</span><sup>−3</sup><span>, and has an insignificant annual air temperature dependency. We demonstrate that two widely-used surface snow density parameterizations dependent on temperature systematically overestimate surface snow density over the Greenland ice sheet by 17–19%, and that using a constant density of 315 kg m</span><sup>−3</sup><span>&nbsp;may give superior results when applied in surface mass budget modeling.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2018.00051","usgsCitation":"Fausto, R., Box, J.E., Baptiste Vandecrux, van As, D., Steffen, K., MacFerrin, M.J., Machguth, H., Colgan, W., Mcgrath, D., Koenig, L.S., Charalampidis, C., and Braithwaite, R.J., 2018, A snow density dataset for improving surface boundary conditions in Greenland ice sheet firn modeling: Frontiers in Earth Science, v. 6, 51, 10 p., https://doi.org/10.3389/feart.2018.00051.","productDescription":"51, 10 p.","ipdsId":"IP-082355","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science 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Page"},{"id":369087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-46.76379,82.62796],[-43.40644,83.22516],[-39.89753,83.18018],[-38.62214,83.54905],[-35.08787,83.64513],[-27.10046,83.51966],[-20.84539,82.72669],[-22.69182,82.34165],[-26.51753,82.29765],[-31.9,82.2],[-31.39646,82.02154],[-27.85666,82.13178],[-24.84448,81.78697],[-22.90328,82.09317],[-22.07175,81.73449],[-23.16961,81.15271],[-20.62363,81.52462],[-15.76818,81.91245],[-12.77018,81.71885],[-12.20855,81.29154],[-16.28533,80.58004],[-16.85,80.35],[-20.04624,80.17708],[-17.73035,80.12912],[-18.9,79.4],[-19.70499,78.75128],[-19.67353,77.63859],[-18.47285,76.98565],[-20.03503,76.94434],[-21.67944,76.62795],[-19.83407,76.09808],[-19.59896,75.24838],[-20.66818,75.15585],[-19.37281,74.29561],[-21.59422,74.22382],[-20.43454,73.81713],[-20.76234,73.46436],[-22.17221,73.30955],[-23.56593,73.30663],[-22.31311,72.62928],[-22.29954,72.18409],[-24.27834,72.59788],[-24.79296,72.3302],[-23.44296,72.08016],[-22.13281,71.46898],[-21.75356,70.66369],[-23.53603,70.471],[-24.30702,70.85649],[-25.54341,71.43094],[-25.20135,70.75226],[-26.36276,70.22646],[-23.72742,70.18401],[-22.34902,70.12946],[-25.02927,69.2588],[-27.74737,68.47046],[-30.67371,68.12503],[-31.77665,68.12078],[-32.81105,67.73547],[-34.20196,66.67974],[-36.35284,65.9789],[-37.04378,65.93768],[-38.37505,65.69213],[-39.81222,65.45848],[-40.66899,64.83997],[-40.68281,64.13902],[-41.1887,63.48246],[-42.81938,62.68233],[-42.41666,61.90093],[-42.86619,61.07404],[-43.3784,60.09772],[-44.7875,60.03676],[-46.26364,60.85328],[-48.26294,60.85843],[-49.23308,61.40681],[-49.90039,62.38336],[-51.63325,63.62691],[-52.14014,64.27842],[-52.27659,65.1767],[-53.66166,66.09957],[-53.30161,66.8365],[-53.96911,67.18899],[-52.9804,68.35759],[-51.47536,68.72958],[-51.08041,69.14781],[-50.87122,69.9291],[-52.01358,69.57492],[-52.55792,69.42616],[-53.45629,69.28363],[-54.68336,69.61003],[-54.75001,70.28932],[-54.35884,70.82131],[-53.43131,70.83576],[-51.39014,70.56978],[-53.10937,71.20485],[-54.00422,71.54719],[-55,71.40654],[-55.83468,71.65444],[-54.71819,72.58625],[-55.32634,72.95861],[-56.12003,73.64977],[-57.32363,74.71026],[-58.59679,75.09861],[-58.58516,75.51727],[-61.26861,76.10238],[-63.39165,76.1752],[-66.06427,76.13486],[-68.50438,76.06141],[-69.66485,76.37975],[-71.40257,77.00857],[-68.77671,77.32312],[-66.76397,77.37595],[-71.04293,77.63595],[-73.297,78.04419],[-73.15938,78.43271],[-69.37345,78.91388],[-65.7107,79.39436],[-65.3239,79.75814],[-68.02298,80.11721],[-67.15129,80.51582],[-63.68925,81.21396],[-62.23444,81.3211],[-62.65116,81.77042],[-60.28249,82.03363],[-57.20744,82.19074],[-54.13442,82.19962],[-53.04328,81.88833],[-50.39061,82.43883],[-48.00386,82.06481],[-46.59984,81.98595],[-44.523,81.6607],[-46.9007,82.19979],[-46.76379,82.62796]]]},\"properties\":{\"name\":\"Greenland\"}}]}","volume":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Fausto, Robert","contributorId":220400,"corporation":false,"usgs":false,"family":"Fausto","given":"Robert","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":774905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Box, Jason E.","contributorId":198809,"corporation":false,"usgs":false,"family":"Box","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":774906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baptiste Vandecrux","contributorId":220401,"corporation":false,"usgs":false,"family":"Baptiste Vandecrux","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":774907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van As, Dirk","contributorId":220402,"corporation":false,"usgs":false,"family":"van As","given":"Dirk","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":774908,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steffen, Konrad","contributorId":220461,"corporation":false,"usgs":false,"family":"Steffen","given":"Konrad","email":"","affiliations":[],"preferred":false,"id":774970,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"MacFerrin, Michael J.","contributorId":220462,"corporation":false,"usgs":false,"family":"MacFerrin","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":774971,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Machguth, Horst","contributorId":220463,"corporation":false,"usgs":false,"family":"Machguth","given":"Horst","email":"","affiliations":[],"preferred":false,"id":774972,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Colgan, William","contributorId":220464,"corporation":false,"usgs":false,"family":"Colgan","given":"William","affiliations":[],"preferred":false,"id":774973,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mcgrath, Daniel 0000-0002-9462-6842 dmcgrath@usgs.gov","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":145635,"corporation":false,"usgs":true,"family":"Mcgrath","given":"Daniel","email":"dmcgrath@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":774904,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Koenig, Lora S.","contributorId":220465,"corporation":false,"usgs":false,"family":"Koenig","given":"Lora","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":774974,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Charalampidis, Charalampos","contributorId":220466,"corporation":false,"usgs":false,"family":"Charalampidis","given":"Charalampos","email":"","affiliations":[],"preferred":false,"id":774975,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Braithwaite, Roger J.","contributorId":220467,"corporation":false,"usgs":false,"family":"Braithwaite","given":"Roger","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":774976,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70195939,"text":"cir1439 - 2018 - Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities","interactions":[],"lastModifiedDate":"2018-05-07T13:34:22","indexId":"cir1439","displayToPublicDate":"2018-05-07T10:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1439","title":"Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities","docAbstract":"<h1>Executive Summary—Overview</h1><p>Natural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans.</p><p>This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts.</p><p>Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on resource systems, both must confront the analytical challenges of systems modeling—in terms of complexity, dynamics, and uncertainty.</p><p>Given this affinity, the integration of ecosystem services analysis and adaptive management poses few conceptual hurdles. In this report, we synthesize discussions from two workshops that considered ways in which adaptive management approaches and ecosystem service concepts may be complementary, such that integrating them into a common framework may lead to improved natural resource management outcomes. Although the literature on adaptive management and ecosystem services is vast and growing, the report focuses specifically on the integration of these two concepts rather than aiming to provide new definitions or an indepth review or primer of the concepts individually.</p><p>Key issues considered include the bidirectional links between adaptive decision making and ecosystem services, as well as the potential benefits and inevitable challenges arising in the development and use of an integrated framework. Specifically, the workshops addressed the following questions:</p><ul><li>How can application of ecosystem service analysis within an adaptive decision process improve the outcomes of management and advance understanding of ecosystem service identification, production, and valuation?</li><li>How can these concepts be integrated in concept and practice?</li><li>What are the constraints and challenges to integrating adaptive management and ecosystem services?</li><li>And, should the integration of these concepts be moved forward to wider application—and if so, how?</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1439","isbn":"978-1-4113-4221-7","collaboration":"Prepared in cooperation with Resources for the Future","usgsCitation":"Epanchin-Niell, R.S., Boyd, J.W., Macauley, M.K., Scarlett, Lynn, Shapiro, C.D., and Williams, B.K., 2018, Integrating adaptive management and ecosystem services concepts to improve natural resource management—Challenges and opportunities: U.S. Geological Survey Circular 1439, 62 p., https://doi.org/10.3133/cir1439.","productDescription":"v, 61 p.","numberOfPages":"72","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088968","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":353742,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1439/circ1439.pdf","text":"Report","size":"20.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1439"},{"id":353741,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1439/coverthb.jpg"}],"contact":"<p>Director, <a href=\" https://www.usgs.gov/sdc/\" data-mce-href=\"https://www.usgs.gov/sdc/\">Science and Decisions Center</a><br> U.S. Geological Survey<br> 913 National Center<br> 12201 Sunrise Valley Drive<br> Reston, VA 20192</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Anticipated Benefits of Integration</li><li>Relevant Contexts for Application of an Integrated Approach</li><li>Conceptual Framework for Integration</li><li>Four Example Case Studies: An Empirical Evaluation</li><li>Reflections on Adaptive Management-Ecosystem Services Integration: Case Study Evaluation</li><li>Challenges to Adaptive Management-Ecosystem Services Integration</li><li>Future Directions and Needs</li><li>Conclusion</li><li>References Cited</li><li>Appendix 1. List of Workshop Participants</li><li>Photograph Credits</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-05-07","noUsgsAuthors":false,"publicationDate":"2018-05-07","publicationStatus":"PW","scienceBaseUri":"5afee6c2e4b0da30c1bfbdd8","contributors":{"authors":[{"text":"Epanchin-Niell, Rebecca S.","contributorId":175364,"corporation":false,"usgs":false,"family":"Epanchin-Niell","given":"Rebecca","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":730568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, James W.","contributorId":203180,"corporation":false,"usgs":false,"family":"Boyd","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":36572,"text":"Resources for the Future","active":true,"usgs":false}],"preferred":false,"id":730569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macauley, Molly K.","contributorId":167525,"corporation":false,"usgs":false,"family":"Macauley","given":"Molly","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":730570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scarlett, Lynn","contributorId":203181,"corporation":false,"usgs":false,"family":"Scarlett","given":"Lynn","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":730571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":730567,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Williams, Byron K.","contributorId":203182,"corporation":false,"usgs":false,"family":"Williams","given":"Byron K.","affiliations":[{"id":12801,"text":"The Wildlife Society","active":true,"usgs":false}],"preferred":false,"id":730572,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70255991,"text":"70255991 - 2018 - Separable correlation and maximum likelihood","interactions":[],"lastModifiedDate":"2024-07-12T11:46:44.505225","indexId":"70255991","displayToPublicDate":"2018-05-07T06:45:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18005,"text":"arXiv","active":true,"publicationSubtype":{"id":10}},"title":"Separable correlation and maximum likelihood","docAbstract":"<p>We consider estimation of the covariance matrix of a multivariate normal distribution when the correlation matrix is separable in the sense that it factors as a Kronecker product of two smaller matrices. A computationally convenient coordinate descent-type algorithm is developed for maximum likelihood estimation. Simulations indicate our method often gives smaller estimation error than some common alternatives when correlation is separable, and that correctly sized tests for correlation separability can be obtained using a parametric bootstrap. Using dissolved oxygen data from the Upper Mississippi River, we illustrate how our model can lead to interesting scientific findings that may be missed when using competing models.<br></p>","language":"English","publisher":"Cornell University Library","doi":"10.48550/arXiv.1805.00318","usgsCitation":"Ekvall, K.O., and Gray, B.R., 2018, Separable correlation and maximum likelihood: arXiv, 14 p., https://doi.org/10.48550/arXiv.1805.00318.","productDescription":"14 p.","ipdsId":"IP-091199","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":430997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ekvall, Karl Oskar","contributorId":340126,"corporation":false,"usgs":false,"family":"Ekvall","given":"Karl","email":"","middleInitial":"Oskar","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":906272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, Brian R. 0000-0001-7682-9550 brgray@usgs.gov","orcid":"https://orcid.org/0000-0001-7682-9550","contributorId":2615,"corporation":false,"usgs":true,"family":"Gray","given":"Brian","email":"brgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":906273,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196861,"text":"70196861 - 2018 - Response to comment by Walker et al. on “From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments”","interactions":[],"lastModifiedDate":"2018-07-03T11:20:55","indexId":"70196861","displayToPublicDate":"2018-05-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Response to comment by Walker et al. on “From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments”","docAbstract":"<p><span>Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). The comment by Walker et al. (2018,&nbsp;</span><a class=\"linkBehavior\" href=\"https://doi.org/10.1002/2017EF000750\" data-mce-href=\"https://doi.org/10.1002/2017EF000750\">https://doi.org/10.1002/2017EF000750</a><span>) illustrates several points made by Glynn et al. (2017,<span>&nbsp;</span></span><a class=\"linkBehavior\" href=\"https://doi.org/10.1002/2016EF000487\" data-mce-href=\"https://doi.org/10.1002/2016EF000487\">https://doi.org/10.1002/2016EF000487</a><span>) and many other articles. Namely, biases and beliefs often drive scientific reasoning, and scientists, just like other humans, are intimately attached to their values and heuristics. Scientists, just like many other people, also tend to read and interpret text in ways that best match their individual perceptions of a problem or issue: in many cases paraphrasing and changing the meaning of what they read to better match their initial ideas. Walker et al. are doing interesting and important research on uncertainty. Nonetheless, they misinterpret the work, assumptions, and conclusions brought forth by Glynn et al. (2017,<span>&nbsp;</span></span><a class=\"linkBehavior\" href=\"https://doi.org/10.1002/2016EF000487\" data-mce-href=\"https://doi.org/10.1002/2016EF000487\">https://doi.org/10.1002/2016EF000487</a><span>).</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2018EF000819","usgsCitation":"Glynn, P.D., Voinov, A.A., Shapiro, C.D., and White, P.A., 2018, Response to comment by Walker et al. on “From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments”: Earth's Future, v. 6, no. 5, p. 762-769, https://doi.org/10.1002/2018EF000819.","productDescription":"8 p.","startPage":"762","endPage":"769","ipdsId":"IP-094986","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468776,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2018ef000819","text":"Publisher Index Page"},{"id":353976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-06","publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbdda","contributors":{"authors":[{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":734795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voinov, Alexey A.","contributorId":197796,"corporation":false,"usgs":false,"family":"Voinov","given":"Alexey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":734797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Paul A.","contributorId":197797,"corporation":false,"usgs":false,"family":"White","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":734798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70198090,"text":"70198090 - 2018 - Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds","interactions":[],"lastModifiedDate":"2018-07-23T12:52:42","indexId":"70198090","displayToPublicDate":"2018-05-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds","docAbstract":"<p><span>Post‐Miocene tectonic uplift along fault‐cored anticlines within central Washington produced the Yakima Fold Province, a region of active NNE‐SSW shortening in the Cascadian backarc. The relative timing and rate of deformation along individual structures is coarsely defined yet imperative for seismic hazard assessment. In this work, we use geomorphic and geophysical mapping, stream profile inversion, and balanced cross‐section methods to constrain fault geometries and slip rates in the Yakima Canyon region. We extract stream profiles from LiDAR data and analytically solve for the rate of relative rock uplift along several active fault‐cored anticlines. To constrain the fault geometries at depth and the long‐term magnitude of deformation, we constructed two line‐balanced cross sections across the folds with forward‐modeled magnetic and gravity anomaly data. Our stream profile results indicate an increase of incision rates in the Pleistocene, and we infer the increase is tectonically controlled. We estimate modern slip rates between 0.4 and 0.6&nbsp;mm/year accommodated on reverse faults that core the Manastash Ridge, Umtanum Ridge, and Selah Butte anticlines and establish that these faults reactivate and invert older normal faults in basement rocks. Finally, we calculate the time required to accumulate sufficient strain energy for a large magnitude earthquake (M&nbsp;≥&nbsp;7) along individual structures in the Yakima Fold Province. Results show that the Yakima folds likely accommodate large magnitude earthquakes and that it takes several hundred to several thousand years to accumulate sufficient strain energy for an M&nbsp;≥&nbsp;7 earthquake.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017TC004916","usgsCitation":"Staisch, L.M., Blakely, R.J., Kelsey, H., Styron, R., and Sherrod, B.L., 2018, Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds: Tectonics, v. 37, no. 6, p. 1750-1770, https://doi.org/10.1029/2017TC004916.","productDescription":"21 p.","startPage":"1750","endPage":"1770","ipdsId":"IP-092865","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017tc004916","text":"Publisher Index Page"},{"id":355670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima Folds","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.364990234375,\n              45.40616374516014\n            ],\n            [\n              -117.7734375,\n              45.40616374516014\n            ],\n            [\n              -117.7734375,\n              49.0738659012854\n            ],\n            [\n              -125.364990234375,\n              49.0738659012854\n            ],\n            [\n              -125.364990234375,\n              45.40616374516014\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"37","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-06","publicationStatus":"PW","scienceBaseUri":"5b6fc450e4b0f5d57878ea4f","contributors":{"authors":[{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":739972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":739973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelsey, Harvey","contributorId":106978,"corporation":false,"usgs":true,"family":"Kelsey","given":"Harvey","affiliations":[],"preferred":false,"id":739976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Styron, Richard","contributorId":201082,"corporation":false,"usgs":false,"family":"Styron","given":"Richard","email":"","affiliations":[],"preferred":false,"id":739974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":739975,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196859,"text":"70196859 - 2018 - Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream","interactions":[],"lastModifiedDate":"2018-05-07T11:13:53","indexId":"70196859","displayToPublicDate":"2018-05-07T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\"><p id=\"sp0045\">Management actions aimed at eradicating exotic fish species from riverine ecosystems can be better informed by forecasting abilities of mechanistic models. We illustrate this point with an example of the Logan River, Utah, originally populated with endemic cutthroat trout (<i>Oncorhynchus clarkii utah</i>), which compete with exotic brown trout (<i>Salmo trutta</i>). The coexistence equilibrium was disrupted by a large scale, experimental removal of the exotic species in 2009–2011 (on average, 8.2% of the stock each year), followed by an increase in the density of the native species. We built a spatially-explicit, reaction-diffusion model encompassing four key processes: population growth in heterogeneous habitat, competition, dispersal, and a management action. We calibrated the model with detailed long-term monitoring data (2001–2016) collected along the 35.4-km long river main channel. Our model, although simple, did a remarkable job reproducing the system steady state prior to the management action. Insights gained from the model independent predictions are consistent with available knowledge and indicate that the exotic species is more competitive; however, the native species still occupies more favorable habitat upstream. Dynamic runs of the model also recreated the observed increase of the native species following the management action. The model can simulate two possible distinct long-term outcomes: recovery or eradication of the exotic species. The processing of available knowledge using Bayesian methods allowed us to conclude that the chance for eradication of the invader was low at the beginning of the experimental removal (0.7% in 2009) and increased (20.5% in 2016) by using more recent monitoring data. We show that accessible mathematical and numerical tools can provide highly informative insights for managers (e.g., outcome of their conservation actions), identify knowledge gaps, and provide testable theory for researchers.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.04.024","usgsCitation":"Laplanche, C., Elger, A., Santoul, F., Thiede, G.P., and Budy, P., 2018, Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream: Biological Conservation, v. 223, p. 34-46, https://doi.org/10.1016/j.biocon.2018.04.024.","productDescription":"13 p.","startPage":"34","endPage":"46","ipdsId":"IP-088496","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"text":"Publisher Index Page"},{"id":353974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Logan River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.79962158203125,\n              41.73237975329554\n            ],\n            [\n              -111.52496337890625,\n              41.73237975329554\n            ],\n            [\n              -111.52496337890625,\n              41.94519164538106\n            ],\n            [\n              -111.79962158203125,\n              41.94519164538106\n            ],\n            [\n              -111.79962158203125,\n              41.73237975329554\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"223","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbddc","contributors":{"authors":[{"text":"Laplanche, Christophe","contributorId":204719,"corporation":false,"usgs":false,"family":"Laplanche","given":"Christophe","email":"","affiliations":[],"preferred":false,"id":734791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elger, Arnaud","contributorId":204720,"corporation":false,"usgs":false,"family":"Elger","given":"Arnaud","email":"","affiliations":[],"preferred":false,"id":734792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santoul, Frederic","contributorId":204721,"corporation":false,"usgs":false,"family":"Santoul","given":"Frederic","email":"","affiliations":[],"preferred":false,"id":734793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiede, Gary P.","contributorId":9154,"corporation":false,"usgs":true,"family":"Thiede","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":734794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734786,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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