{"pageNumber":"325","pageRowStart":"8100","pageSize":"25","recordCount":41075,"records":[{"id":70204621,"text":"cir1457 - 2019 - National earthquake information center strategic plan, 2019–23","interactions":[],"lastModifiedDate":"2020-09-01T13:55:24.927546","indexId":"cir1457","displayToPublicDate":"2019-09-13T10:30:00","publicationYear":"2019","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":"1457","displayTitle":"National Earthquake Information Center Strategic Plan, 2019–23","title":"National earthquake information center strategic plan, 2019–23","docAbstract":"<h1>Executive Summary</h1><p>Damaging earthquakes occur regularly around the world; since the turn of the 20th century, hundreds of earthquakes have caused significant loss of life and (or) millions of dollars or more in economic losses. While most of these did not directly affect the United States and its Territories, by studying worldwide seismicity we can better understand how to mitigate the effects of earthquakes when they do occur within U.S. borders. Within the U.S. Government, this mandate falls on the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC), which has the statutory responsibility for monitoring and reporting on earthquakes domestically and globally.</p><p>The NEIC has been operating since 1966, and throughout its history has been recognized as a world leader for earthquake information. For much of this time, NEIC has been cooperating with a number of regional seismic networks (RSNs) which operate in areas of heightened seismicity in the United States. In 2000, the Advanced National Seismic System (ANSS) was founded as a cooperative umbrella for earthquake-related data collection, analysis, and dissemination in the United States, thereby promoting advanced interoperability between the NEIC and RSN partners. The NEIC also cooperates and coordinates with dozens of global seismic networks. At present (2019), NEIC acquires real-time waveform data from more than 2,000 seismic stations worldwide, contributed from more than 130 seismic networks.</p><p>Since 2006, the NEIC has operated on a 24-hour, 7-days per week (24/7) basis, and reports on about 30,000 earthquakes per year. Soon after the occurrence of a significant global earthquake, notifications are issued to government representatives, aid agencies, the press, and members of the general public by the Earthquake Notification Service (ENS), electronic feeds, and through the USGS Earthquake Hazards Program (EHP) website. Event-specific web pages provide detailed source parameter information outlining the location and magnitude of the earthquake, including more detailed source characteristics like moment magnitude and focal mechanisms and finite fault solutions. Further, NEIC produces a suite of real-time situational awareness products, including ShakeMap, ShakeCast, Did-You-Feel-It? (DYFI?), and Prompt Assessment of&nbsp;Global Earthquakes for Response (PAGER), to characterize the shaking resulting from the earthquake and the impact it is likely to have on nearby populations and infrastructure. All of these products are ultimately archived in the ANSS Comprehensive Catalog (ComCat), hosted and served by the NEIC.</p><p>The NEIC also pursues an active research program to improve its ability to characterize earthquakes and understand their hazards. These efforts are all aimed at mitigating the risks of earthquakes to humankind.</p><p>To maintain its prominent position in earthquake monitoring, the NEIC must continue to evolve, concurrently improving its operations and 24/7 robustness, streamlining services and infrastructure, and keeping pace with research and innovation in the field of seismology. This document outlines how the NEIC might best achieve such goals, by describing specific avenues and opportunities for development in the next five years (2019–23).</p><p>Several key areas of operational and research focus are identified in this plan as being of the highest importance. First, NEIC must finalize improvements to its regional monitoring capabilities, including the implementation of a variety of improved earthquake detection and association algorithms. One of the most exciting avenues of recent research expansion in earthquake monitoring has involved the use of machine learning; NEIC must explore the benefits of machine learning for improved earthquake detection and source characterization. NEIC also needs to address issues related to the timeliness of earthquake information, exploring the benefits of distributing information as it becomes available, rather than when certain quality criteria are met. To that end, the incorporation of real-time Global Positioning System (GPS) data into the NEIC operational workflow will help improve the speed and accuracy of information for moderate-to-large earthquakes. Finally, NEIC should explore how to further expand and improve the quality and content of the products served during earthquake response efforts, including the generation of new earthquake sequence-specific products, adding an evolutionary component to earthquake information, and continued improvements to earthquake impact products.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/cir1457","usgsCitation":"Hayes, G.P., Earle, P.S., Benz, H.M., Wald, D.J., and Yeck, W.L., 2019, National Earthquake Information Center strategic plan, 2019–23: U.S. Geological Survey Circular 1457, 17 p., https://doi.org/10.3133/cir1457.","productDescription":"vi, 20 p.","onlineOnly":"N","ipdsId":"IP-107447","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":367395,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1457/coverthb2.jpg"},{"id":367396,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1457/circ1457.pdf","text":"Report","size":"19.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1457"}],"contact":"<p>Director,&nbsp;<a href=\"https://www.usgs.gov/centers/geohazards/\" data-mce-href=\"https://www.usgs.gov/centers/geohazards/\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS 966<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Preface</li><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Foundational List: Existing Operational Considerations that Should Continue</li><li>Aspirational List: Opportunities for Operational and Research Innovation</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-09-13","noUsgsAuthors":false,"publicationDate":"2019-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Earle, Paul S. 0000-0002-3500-017X pearle@usgs.gov","orcid":"https://orcid.org/0000-0002-3500-017X","contributorId":173551,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":770773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":767801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":767802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":767803,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70202192,"text":"sir20175037 - 2019 - Methods for estimating regional coefficient of skewness for unregulated streams in New England, based on data through water year 2011","interactions":[],"lastModifiedDate":"2026-01-23T16:05:31.669203","indexId":"sir20175037","displayToPublicDate":"2019-09-13T10:26:37","publicationYear":"2019","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":"2017-5037","displayTitle":"Methods for Estimating Regional Coefficient of Skewness for Unregulated Streams in New England, Based on Data Through Water Year 2011","title":"Methods for estimating regional coefficient of skewness for unregulated streams in New England, based on data through water year 2011","docAbstract":"<p>The magnitude of annual exceedance probability floods is greatly affected by the coefficient of skewness (skew) of the annual peak flows at a streamgage. Standard flood frequency methods recommend weighting the station skew with a regional skew to better represent regional and stable conditions. This study presents an updated analysis of a regional skew for New England developed using a robust Bayesian weighted and generalized least squares regression model. Nineteen explanatory variables for 153 streamgages were tested in the regression analysis, but none were statistically significant and, as a result, a constant model was selected to define the regional skew for New England. The constant model for the New England region has, in log units, a skew of 0.37, a model error variance of 0.13, and an average variance of prediction at a new site of 0.14. An assessment of the selected regional skew model was conducted using a Monte Carlo analysis. The Monte Carlo simulations reveal that the perceived pattern in the station skews among the 153 streamgages is an artifact of the sample variability and the covariance structure of the errors.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175037","usgsCitation":"Veilleux, A.G., Zariello, P.J., Hodgkins, G.A., Ahearn, E.A., Olson, S.A., and Cohn, T.A., 2019, Methods for estimating regional coefficient of skewness for unregulated streams in New England, based on data through water year 2011: U.S. Geological Survey Scientific Investigations Report 2017–5037, 29 p., https://doi.org/10.3133/sir20175037.","productDescription":"Report: iv, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-071009","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":367392,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MC98OM","linkHelpText":"Annual peak-flow data and PeakFQ output files for selected streamflow gaging stations operated by the U.S. Geological Survey in the New England region that were used to estimate regional skewness of annual peak flows"},{"id":367390,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5037/sir20175037.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2017–5037"},{"id":367389,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5037/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont","otherGeospatial":"New England","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.90673828125,\n              44.84808025602074\n            ],\n            [\n              -67.82958984375,\n              46.042735653846506\n            ],\n            [\n              -67.78564453125,\n              47.07012182383309\n            ],\n            [\n              -68.345947265625,\n              47.4057852900587\n            ],\n            [\n              -68.93920898437499,\n              47.2270293988673\n            ],\n            [\n              -69.027099609375,\n              47.44294999517949\n            ],\n            [\n              -69.224853515625,\n              47.45780853075031\n            ],\n            [\n              -69.98291015625,\n              46.77749276376827\n            ],\n            [\n              -70.301513671875,\n              46.210249600187225\n            ],\n            [\n              -70.400390625,\n              45.79816953017265\n            ],\n            [\n              -70.86181640625,\n              45.413876460821086\n            ],\n            [\n              -71.16943359375,\n              45.3444241045224\n            ],\n            [\n              -71.575927734375,\n              45.01141864227728\n            ],\n            [\n              -74.24560546875,\n              44.99588261816546\n            ],\n            [\n              -74.256591796875,\n              40.53050177574321\n            ],\n            [\n              -72.13623046875,\n              40.90520969727358\n            ],\n            [\n              -70.499267578125,\n              41.86956082699455\n            ],\n            [\n              -70.72998046875,\n              42.22851735620852\n            ],\n            [\n              -70.850830078125,\n              42.48830197960227\n            ],\n            [\n              -70.59814453125,\n              42.65012181368022\n            ],\n            [\n              -70.77392578125,\n              42.94838139765314\n            ],\n            [\n              -70.169677734375,\n              43.69965122967144\n            ],\n            [\n              -69.6533203125,\n              43.75522505306928\n            ],\n            [\n              -66.90673828125,\n              44.84808025602074\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,<br>Integrated Modeling and Prediction Division<br><a data-mce-href=\"https://usgs.gov/\" href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>MS 415 National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Study Area</li><li>Streamgage Data for Regional Skew Analysis</li><li>Analytical Methods To Generate Regional Skew</li><li>Data Analysis</li><li>Regression Analyses</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Assessment of New England Regional Skew Constant Model Through Monte Carlo Realizations&nbsp; &nbsp;</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-09-13","noUsgsAuthors":false,"publicationDate":"2019-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Veilleux, Andrea G. 0000-0002-8742-4660 aveilleux@usgs.gov","orcid":"https://orcid.org/0000-0002-8742-4660","contributorId":203278,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":757168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zarriello, Phillip J. 0000-0001-9598-9904 pzarriel@usgs.gov","orcid":"https://orcid.org/0000-0001-9598-9904","contributorId":1868,"corporation":false,"usgs":true,"family":"Zarriello","given":"Phillip","email":"pzarriel@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahearn, Elizabeth A. 0000-0002-5633-2640 eaahearn@usgs.gov","orcid":"https://orcid.org/0000-0002-5633-2640","contributorId":194658,"corporation":false,"usgs":true,"family":"Ahearn","given":"Elizabeth","email":"eaahearn@usgs.gov","middleInitial":"A.","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true},{"id":377,"text":"Massachusetts-Rhode Island Water Science Center","active":false,"usgs":true}],"preferred":false,"id":757171,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olson, Scott A. 0000-0002-1064-2125","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":210173,"corporation":false,"usgs":true,"family":"Olson","given":"Scott A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757172,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cohn, Timothy A. tacohn@usgs.gov","contributorId":213234,"corporation":false,"usgs":true,"family":"Cohn","given":"Timothy","email":"tacohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":757173,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70215323,"text":"70215323 - 2019 - Using a mechanistic model to develop management strategies to cool Apache Trout streams under the threat of climate change","interactions":[],"lastModifiedDate":"2020-10-16T14:15:08.962952","indexId":"70215323","displayToPublicDate":"2019-09-13T09:10:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Using a mechanistic model to develop management strategies to cool Apache Trout streams under the threat of climate change","docAbstract":"<p><span>User‐friendly stream temperature models populated with on‐site data may help in developing strategies to manage temperatures of individual stream reaches that are subject to climate change. We used the field‐tested Stream Segment Temperature model (U.S. Geological Survey) to simulate how altering discharge, groundwater input, channel wetted width, and shade prevents the temperatures of White Mountain, Arizona, stream reaches from exceeding the thermal tolerance of Apache Trout&nbsp;</span><i>Oncorhynchus apache</i><span>, both under existing conditions and under a climate change scenario. Simulations suggested increasing shade, either through streamside planting of specific numbers and species of plants or by other means, would be most effective and feasible for cooling the stream reaches we studied. Ponderosa pine&nbsp;</span><i>Pinus ponderosa</i><span>&nbsp;and Douglas fir&nbsp;</span><i>Pseudotsuga menziesii</i><span>&nbsp;provided the most shade followed in order by Engelman spruce&nbsp;</span><i>Picea engelmannii</i><span>, Bebb's willow&nbsp;</span><i>Salix bebbiana</i><span>, Arizona alder&nbsp;</span><i>Alnus oblongifolia</i><span>, and finally coyote willow&nbsp;</span><i>Salix exigua</i><span>. Vegetation survival depends on the appropriateness of site conditions at present and under climate change, and planting in buffer strips minimizes additional water removal from the watershed through evapotranspiration. Alternative shading options, including thick sedge growth, shade cloth, or felled woody vegetation, may be considered when environmental conditions do not support plantings. Increasing groundwater input can cool streams, but additional sources are scarce in the region. Decreasing the width‐to‐depth ratio would succeed best on reaches with widths greater than 2.0&nbsp;m. Increasing discharge from upstream may lower water temperature on reaches with an initial discharge greater than 0.5&nbsp;m</span><sup>3</sup><span>/s. Existing models provide suggestions to cool stream reaches. Further development of accessible software packages that incorporate evaporation, fragmentation, and other projected climate change effects into their routines will provide additional tools to help manage climate change effects.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10337","usgsCitation":"Baker, J.P., and Bonar, S.A., 2019, Using a mechanistic model to develop management strategies to cool Apache Trout streams under the threat of climate change: North American Journal of Fisheries Management, v. 39, no. 5, p. 849-867, https://doi.org/10.1002/nafm.10337.","productDescription":"19 p.","startPage":"849","endPage":"867","ipdsId":"IP-098411","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":379466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"White Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.225830078125,\n              33.53681606773302\n            ],\n            [\n              -109.05853271484374,\n              33.53681606773302\n            ],\n            [\n              -109.05853271484374,\n              34.440893571391165\n            ],\n            [\n              -110.225830078125,\n              34.440893571391165\n            ],\n            [\n              -110.225830078125,\n              33.53681606773302\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Baker, Joy Price","contributorId":243199,"corporation":false,"usgs":false,"family":"Baker","given":"Joy","email":"","middleInitial":"Price","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":801718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":801719,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70205297,"text":"70205297 - 2019 - Photosynthetic and respiratory responses of two bog shrub species to whole ecosystem warming and elevated CO2 at the boreal-temperate ecotone","interactions":[],"lastModifiedDate":"2019-10-11T16:05:01","indexId":"70205297","displayToPublicDate":"2019-09-12T14:04:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Photosynthetic and respiratory responses of two bog shrub species to whole ecosystem warming and elevated CO<sub>2</sub> at the boreal-temperate ecotone","title":"Photosynthetic and respiratory responses of two bog shrub species to whole ecosystem warming and elevated CO2 at the boreal-temperate ecotone","docAbstract":"<p><span>Peatlands within the boreal-temperate ecotone contain the majority of terrestrial carbon in this region, and there is concern over the fate of such carbon stores in the face of global environmental changes. The Spruce and Peatland Response Under Changing Environments (SPRUCE) facility aims to advance the understanding of how such peatlands may respond to such changes, using a combination of whole ecosystem warming (WEW; +0, 2.25, 4.5, 6.75, and 9°C) and elevated CO</span><sub>2</sub><span>&nbsp;(eCO</span><sub>2</sub><span>; +500 ppm) treatments in an intact bog ecosystem. We examined photosynthetic and respiration responses in leaves of two ericaceous shrub species–leatherleaf [</span><i>Chamaedaphne calyculata</i><span>&nbsp;(L.) Moench] and bog Labrador tea [</span><i>Rhododendron groenlandicum</i><span>&nbsp;(Oeder) Kron &amp; Judd]–to the first year of combined eCO</span><sub>2</sub><span>&nbsp;and WEW treatments at SPRUCE. We surveyed the leaf N content per area (</span><i>N</i><sub><i>area</i></sub><span>), net photosynthesis (</span><i>A</i><sub><i>ST</i></sub><span>) and respiration (</span><i>R</i><sub><i>D</i>25</sub><span>) at 25°C and 400 ppm CO</span><sub>2</sub><span>&nbsp;and net photosynthesis at mean growing conditions (</span><i>A</i><sub><i>GR</i></sub><span>) of newly emerged, mature and overwintered leaves. We also measured leaf non-structural carbohydrate content (</span><i>NSC</i><span>) in mature leaves. The effects of WEW and eCO</span><sub>2</sub><span>&nbsp;varied by season and species, highlighting the need to accommodate such variability in modeling this system. In mature leaves, we did not observe a response to either treatment of&nbsp;</span><i>A</i><sub><i>ST</i></sub><span>&nbsp;or&nbsp;</span><i>R</i><sub><i>D</i>25</sub><span>&nbsp;in&nbsp;</span><i>R. groenlandicum</i><span>, but we did observe a 50% decrease in&nbsp;</span><i>A</i><sub><i>ST</i></sub><span>&nbsp;of&nbsp;</span><i>C. calyculata</i><span>&nbsp;with eCO</span><sub>2</sub><span>. In mature leaves under eCO</span><sub>2</sub><span>, neither species had increased&nbsp;</span><i>A</i><sub><i>GR</i></sub><span>&nbsp;and both had increases in&nbsp;</span><i>NSC</i><span>, indicating acclimation of photosynthesis to eCO</span><sub>2</sub><span>&nbsp;may be related to source-sink imbalances of carbohydrates. Thus, productivity gains of shrubs under eCO</span><sub>2</sub><span>&nbsp;may be lower than previously predicted for this site by models not accounting for such acclimation. In newly emerged leaves,&nbsp;</span><i>A</i><sub><i>ST</i></sub><span>&nbsp;increased with WEW in&nbsp;</span><i>R. groenlandicum</i><span>, but not&nbsp;</span><i>C. calyculata</i><span>. Overwintered leaves exhibited a decrease in&nbsp;</span><i>R</i><sub><i>D</i>25</sub><span>&nbsp;for&nbsp;</span><i>R. groenlandicum</i><span>&nbsp;and in&nbsp;</span><i>A</i><sub><i>ST</i></sub><span>&nbsp;for&nbsp;</span><i>C. calyculata</i><span>&nbsp;with increasing WEW, as well as an increase of&nbsp;</span><i>A</i><sub><i>GR</i></sub><span>&nbsp;with eCO</span><sub>2</sub><span>&nbsp;in both species. Responses in newly emerged and overwintered leaves may reflect physiological acclimation or phenological changes in response to treatments.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2019.00054","usgsCitation":"Ward, E., Warren, J.M., McLennan, D., Dusenge, M.E., Way, D.A., Wullschleger, S.D., and Hanson, P.J., 2019, Photosynthetic and respiratory responses of two bog shrub species to whole ecosystem warming and elevated CO2 at the boreal-temperate ecotone: Frontiers in Forests and Global Change, v. 2, 54, 14 p., https://doi.org/10.3389/ffgc.2019.00054.","productDescription":"54, 14 p.","ipdsId":"IP-106522","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":459841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2019.00054","text":"Publisher Index Page"},{"id":367414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Marcell Experimental Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.54206085205078,\n              47.397652013137176\n            ],\n            [\n              -93.44146728515625,\n              47.397652013137176\n            ],\n            [\n              -93.44146728515625,\n              47.46987800000272\n            ],\n            [\n              -93.54206085205078,\n              47.46987800000272\n            ],\n            [\n              -93.54206085205078,\n              47.397652013137176\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":218962,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":770778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warren, Jeffrey M .","contributorId":198318,"corporation":false,"usgs":false,"family":"Warren","given":"Jeffrey","email":"","middleInitial":"M .","affiliations":[],"preferred":false,"id":770779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLennan, David A","contributorId":218963,"corporation":false,"usgs":false,"family":"McLennan","given":"David A","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":770780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusenge, Mirindi E","contributorId":218964,"corporation":false,"usgs":false,"family":"Dusenge","given":"Mirindi","email":"","middleInitial":"E","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":770781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Way, Danielle A.","contributorId":199465,"corporation":false,"usgs":false,"family":"Way","given":"Danielle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":770782,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wullschleger, Stan D.","contributorId":167343,"corporation":false,"usgs":false,"family":"Wullschleger","given":"Stan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":770783,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanson, Paul J","contributorId":218965,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"J","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":770784,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70209084,"text":"70209084 - 2019 - Projected warming disrupts the synchrony of riparian seed dispersal and snowmelt streamflow","interactions":[],"lastModifiedDate":"2020-03-16T06:21:15","indexId":"70209084","displayToPublicDate":"2019-09-12T13:58:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Projected warming disrupts the synchrony of riparian seed dispersal and snowmelt streamflow","docAbstract":"<p>• Globally, spring phenology and abiotic processes are shifting earlier with warming. Differences in the magnitudes of these shifts may decouple the timing of plant resource requirements from resource availability. In riparian forests across the northern hemisphere, warming could decouple seed dispersal from snowmelt peak streamflow, thus reducing moisture and safe-sites for dominant tree recruitment. </p><p>• We combined field observations with climate, hydrology, and phenology models to simulate future change in synchrony of seed dispersal and snowmelt peaks in the upper South Platte River Basin, Colorado, for three Salicaceae species that dominate western USA riparian forests. </p><p>• Chilling requirements for overcoming winter endodormancy were strongest in Salix exigua, moderately supported for Populus deltoides, and indiscernible in Salix amygdaloides. Ensemble mean projected warming of 3.5ºC shifted snowmelt peaks 10-19 d earlier relative to S. exigua and P. deltoides dispersal, because decreased winter chilling combined with increased spring forcing limited change in their dispersal phenology. In contrast, warming shifted both snowmelt peaks and S. amygdaloides dispersal 21 d earlier, maintaining their synchrony. </p><p>• Decoupling of snowmelt from seed dispersal for Salicaceae with strong chilling requirements is likely to reduce resources critical for recruitment of these foundational riparian forests, although the magnitude of future decoupling remains uncertain.</p>","language":"English","publisher":"Wiley","doi":"10.1111/nph.16191","usgsCitation":"Perry, L.G., Shafroth, P.B., Hay, L., Markstrom, S.L., and Bock, A.R., 2019, Projected warming disrupts the synchrony of riparian seed dispersal and snowmelt streamflow: New Phytologist, v. 225, no. 2, p. 693-712, https://doi.org/10.1111/nph.16191.","productDescription":"20 p.","startPage":"693","endPage":"712","ipdsId":"IP-110069","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":459842,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.16191","text":"Publisher Index Page"},{"id":437340,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P994V9LI","text":"USGS data release","linkHelpText":"Riparian seed dispersal phenology and snowmelt streamflow timing in the upper South Platte River Basin, observed in 2010-2011 and simulated for 1962-2098"},{"id":373275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.16015624999999,\n              37.020098201368114\n            ],\n            [\n              -102.041015625,\n              37.020098201368114\n            ],\n            [\n              -102.041015625,\n              40.74725696280421\n            ],\n            [\n              -109.16015624999999,\n              40.74725696280421\n            ],\n            [\n              -109.16015624999999,\n              37.020098201368114\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"225","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G.","contributorId":220048,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":784861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":784860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren","contributorId":209452,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[],"preferred":true,"id":784904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":784905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":784906,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70205025,"text":"fs20193048 - 2019 - Rare earth elements in coal and coal fly ash","interactions":[],"lastModifiedDate":"2019-09-13T09:41:29","indexId":"fs20193048","displayToPublicDate":"2019-09-12T10:23:54","publicationYear":"2019","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":"2019-3048","displayTitle":"Rare Earth Elements in Coal and Coal Fly Ash","title":"Rare earth elements in coal and coal fly ash","docAbstract":"<p>The rare earth elements (REEs) are a group of 17 elements sharing similar chemical properties. They include yttrium (Y, atomic number 39), scandium (Sc, atomic number 21), and the 15 elements of the lanthanide series, atomic numbers 57 (lanthanum, La) to 71 (lutetium, Lu). Because promethium (Pm, atomic number 61) does not occur in the Earth’s crust and scandium typically has different geological occurrences from other REEs, they are not discussed further herein.</p><p>REEs are, on average, more abundant than precious metals (for example, gold, silver, and platinum), but because of their unique geochemical properties, they do not commonly form economically viable ore deposits. Nevertheless, REEs are increasingly required for a range of modern applications in defense and renewable energy technologies and in commercial products, primarily as magnets, batteries, and catalysts. The United States currently (2018) produces REEs from a single mine in California, accounting for just 9 percent of global production, whereas 70 percent of global REE production comes from China. For these reasons, REEs are considered a critical resource, and the U.S. Geological Survey (USGS) has an interest in helping to identify new sources of REEs for domestic production.</p><p>In 2017, coal use accounted for about 30 percent of the electric power generated in the United States. Fly ash, produced during the burning of coal, is a fine­-grained solid derived from noncombustible constituents of coal, such as clay minerals and quartz. When coal is burned, REEs are retained and enriched in the fly ash and, as a result, fly ash has long been considered a potential resource for REEs.</p><p>The United States has the world’s largest coal reserves and, even though gas-­fired power generation has increased significantly in the last decade, the United States continues to produce vast quantities of fly ash, about half of which is beneficially reused, primarily in construction materials. The remainder is stored, mostly in landfills and impound­ments. Thus, annual fly ash production, combined with fly ash already in stor­age, constitutes a large potential resource.</p><p>Research into how to utilize coal and coal fly ash as sources of REEs is ongo­ing. Viable recovery of REEs from coal and coal ash requires identification of coals and ashes with the highest REE concentrations and development of workable methods for REE extraction and recovery. Understanding how REEs occur within fly ash, described in this fact sheet, is one of the keys to developing possible methods for their recovery.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193048","usgsCitation":"Scott, C., and Kolker, A., 2019, Rare earth elements in coal and coal fly ash: U.S. Geological Survey Fact Sheet 2019-3048, 4 p., https://doi.org/10.3133/fs20193048.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-098987","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":367383,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3048/fs20193048.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2019-3048"},{"id":367382,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3048/coverthb.jpg"}],"contact":"<p><a href=\"https://energy.usgs.gov/GeneralInfo/ScienceCenters/Eastern.aspx\" data-mce-href=\"https://energy.usgs.gov/GeneralInfo/ScienceCenters/Eastern.aspx\">Eastern Energy Resources Science Center</a><br><a data-mce-href=\"https://usgs.gov/\" href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>12201 Sunrise Valley Drive<br>956 National Center<br>Reston, VA 20192<br><a href=\"https://energy.usgs.gov/\" data-mce-href=\"https://energy.usgs.gov/\">https://energy.usgs.gov/</a><br></p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-09-12","noUsgsAuthors":false,"publicationDate":"2019-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":769614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolker, Allan 0000-0002-5768-4533 akolker@usgs.gov","orcid":"https://orcid.org/0000-0002-5768-4533","contributorId":643,"corporation":false,"usgs":true,"family":"Kolker","given":"Allan","email":"akolker@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":769615,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70207326,"text":"70207326 - 2019 - Evaluation of maternal penning to improve calf survival in the Chisana Caribou Herd","interactions":[],"lastModifiedDate":"2019-12-17T10:13:50","indexId":"70207326","displayToPublicDate":"2019-09-12T10:02:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3773,"text":"Wildlife Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of maternal penning to improve calf survival in the Chisana Caribou Herd","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Predation is a major limiting factor for most small sedentary caribou (<i>Rangifer tarandus</i>) populations, particularly those that are threatened or endangered across the southern extent of the species’ range. Thus, reducing predation impacts is often a management goal for improving the status of small caribou populations, and lethal predator removal is the primary approach that has been applied. Given that predator control programs are often contentious, other management options that can garner broader public acceptance need to be considered.</p><p>Substantial calf losses to predation in the few weeks following birth are common for these small caribou populations. Therefore, we employed a novel experimental approach of maternal penning with the goal of reducing early calf mortality in the Chisana Caribou Herd, a declining population in southwest Yukon and adjacent Alaska thought to number around 300 individuals. Maternal penning entailed temporarily holding pregnant females on their native range in a large pen secure from predators from late March through the initial weeks of calf rearing to mid‐June. During 2003–2006, we conducted 4 annual penning trials with 17–50 pregnant females each year (<i>n</i> = 146 total), assessed survival of calves born in the pens, and evaluated survival and nutritional effects of penning for females that were held. We also investigated the herd's population dynamics during 2003–2008 to determine effects of maternal penning on calf recruitment and population growth. In addition to information gained during maternal penning, we determined natality and survival patterns via radiotelemetry, conducted autumn age‐sex composition surveys each year, and censused the population in mid‐October 2003, 2005, and 2007. Based on our penning trials and demographic investigations, we used simulation models to evaluate the effects of maternal penning relative to a population's inherent growth rate (finite rate of increase [λ] without maternal penning) and penning effort (proportion of calves born in penning) to provide perspective on utility of this approach for improving the status of small imperiled caribou populations.</p><p>Pregnant females held in maternal penning tolerated captivity well in that they exhibited positive nutritional responses to<span>&nbsp;</span><i>ad libitum</i><span>&nbsp;</span>feed we provided and higher survival than free‐ranging females (0.993 and 0.951 for penned and free‐ranging females, respectively). Survival of pen calves from birth to mid‐June was substantially higher than that of free‐ranging calves (<img class=\"section_image\" src=\"https://wildlife.onlinelibrary.wiley.com/cms/attachment/0e6ef12e-eaa7-4d2f-ab08-ea5b2bd86630/wmon1044-math-0001.png\" alt=\"urn:x-wiley:00840173:media:wmon1044:wmon1044-math-0001\" data-mce-src=\"https://wildlife.onlinelibrary.wiley.com/cms/attachment/0e6ef12e-eaa7-4d2f-ab08-ea5b2bd86630/wmon1044-math-0001.png\"> = 0.950 and 0.376, respectively). This initial period accounted for 76% of the annual calf mortality in the free‐ranging population. Pen‐born calves maintained their survival advantage over wild‐born calves to the end of their first year (<img class=\"section_image\" src=\"https://wildlife.onlinelibrary.wiley.com/cms/attachment/dbad290f-0978-47cf-a834-0ee7ab365628/wmon1044-math-0002.png\" alt=\"urn:x-wiley:00840173:media:wmon1044:wmon1044-math-0002\" data-mce-src=\"https://wildlife.onlinelibrary.wiley.com/cms/attachment/dbad290f-0978-47cf-a834-0ee7ab365628/wmon1044-math-0002.png\"> = 0.575 and 0.192, respectively) during years penning occurred.</p><p>Females in the Chisana Herd were highly productive with 57% producing their first offspring at 2 years of age, and annual natality rates averaging 0.842 calves/female ≥2 years old. Age‐specific natality rates exceeded 0.900 for 4–9‐year‐olds, then exhibited senescent decline to 0.467 by 19 years old. Annual survival of free‐ranging adult females and calves averaged 0.892 and 0.184, respectively, over all study years; both were reduced during 2004 because of poor winter survival. We noted reduced nutritional condition of caribou late that winter in that females we captured were lighter than in other years and produced lighter calves. We suspect that the reduced survival during winter 2004 and the observed nutritional characteristics resulted from adverse snow conditions in combination with effects of the extreme drought experienced the previous summer. Age‐specific survival of adult females was ≥0.900 through 10 years of age, then declined with age.</p><p>The Chisana Herd numbered 720 caribou in mid‐October 2003, or more than twice that estimated prior to initiating maternal penning, and increased to 766 caribou by mid‐October 2007. We calculated that penning added 54.2 yearling recruits, or 40% of calves released from penning. Based on the maternal penning results and the population's vital rates, we determined that the herd would have been stable during 2003–2007 at about 713 caribou without maternal penning; thus, the increase in herd size we observed resulted from maternal penning and was equivalent to the estimate of additional yearling recruits. The improvement in the population trend invoked by maternal penning was limited by the larger than expected population size and resulting low penning effort (<img class=\"section_image\" src=\"https://wildlife.onlinelibrary.wiley.com/cms/attachment/13da9eca-7696-4e7d-9e85-88b51c02dabb/wmon1044-math-0003.png\" alt=\"urn:x-wiley:00840173:media:wmon1044:wmon1044-math-0003\" data-mce-src=\"https://wildlife.onlinelibrary.wiley.com/cms/attachment/13da9eca-7696-4e7d-9e85-88b51c02dabb/wmon1044-math-0003.png\"> = 11% of calves born in pen).</p><p>Our simulations corroborated that maternal penning increased population size by the number of additional recruits provided, even at low penning effort, for inherently stable populations. As the inherent rate of increase dropped below λ = 1.000, more of the additional recruits from penning were needed to offset the downward population inertia, thus requiring increased penning effort to reach stability. For populations declining at λ &lt; 0.890, stability could not be achieved with 100% penning effort given the vital rates in our models.</p><p>Maternal penning in its limited application to date has proven to be broadly popular as a nonlethal management action aimed at reducing initial calf mortality from predation in small caribou populations. However, based on the Chisana program and 3 subsequent efforts elsewhere, improvement in population trends have been modest at best and come at a high financial cost. Given the necessity of maximizing penning effort, maternal penning may have a role in addressing conservation challenges for some small caribou populations that are stable or slowly declining, but its application should be primarily driven by objective assessment of the likelihood of improving population trends rather than popularity relative to other management options.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/wmon.1044","usgsCitation":"Adams, L., Farnell, R.G., Oakley, M.P., Jung, T., Larocque, L., Lortie, G., McLelland, J., Reid, M., Roffler, G.H., and Russell, D., 2019, Evaluation of maternal penning to improve calf survival in the Chisana Caribou Herd: Wildlife Monographs, v. 204, no. 1, p. 5-46, https://doi.org/10.1002/wmon.1044.","productDescription":"42 p.","startPage":"5","endPage":"46","ipdsId":"IP-079916","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":459845,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wmon.1044","text":"Publisher Index Page"},{"id":370338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Wrangell‐St. Elias National Park and Preserve, Kluane Wildlife Sanctuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -144.05273437499997,\n              60.48970392643919\n            ],\n            [\n              -137.21923828125,\n              60.48970392643919\n            ],\n            [\n              -137.21923828125,\n              63.38167869302983\n            ],\n            [\n              -144.05273437499997,\n              63.38167869302983\n            ],\n            [\n              -144.05273437499997,\n              60.48970392643919\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"204","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-09-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":777714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farnell, Richard G.","contributorId":56870,"corporation":false,"usgs":false,"family":"Farnell","given":"Richard","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":777715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oakley, Michelle P.","contributorId":221305,"corporation":false,"usgs":false,"family":"Oakley","given":"Michelle","email":"","middleInitial":"P.","affiliations":[{"id":33063,"text":"Yukon Department of Environment","active":true,"usgs":false}],"preferred":false,"id":777716,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jung, Thomas","contributorId":221306,"corporation":false,"usgs":false,"family":"Jung","given":"Thomas","affiliations":[{"id":33063,"text":"Yukon Department of Environment","active":true,"usgs":false}],"preferred":false,"id":777717,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larocque, Lorne","contributorId":221307,"corporation":false,"usgs":false,"family":"Larocque","given":"Lorne","email":"","affiliations":[{"id":33063,"text":"Yukon Department of Environment","active":true,"usgs":false}],"preferred":false,"id":777718,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lortie, Grant","contributorId":221308,"corporation":false,"usgs":false,"family":"Lortie","given":"Grant","email":"","affiliations":[],"preferred":false,"id":777719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McLelland, Jamie","contributorId":221309,"corporation":false,"usgs":false,"family":"McLelland","given":"Jamie","email":"","affiliations":[{"id":33063,"text":"Yukon Department of Environment","active":true,"usgs":false}],"preferred":false,"id":777720,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reid, Mason","contributorId":51639,"corporation":false,"usgs":true,"family":"Reid","given":"Mason","affiliations":[],"preferred":false,"id":777721,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":777722,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Russell, Don","contributorId":200378,"corporation":false,"usgs":false,"family":"Russell","given":"Don","email":"","affiliations":[],"preferred":false,"id":777723,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70206677,"text":"70206677 - 2019 - Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors","interactions":[],"lastModifiedDate":"2019-11-15T16:03:38","indexId":"70206677","displayToPublicDate":"2019-09-11T15:46:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors","docAbstract":"<p><span>Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8&nbsp;years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat (</span><i>Myotis lucifugus</i><span>) and the hoary bat (</span><i>Lasiurus cinereus</i><span>). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat (</span><img class=\"section_image\" src=\"https://onlinelibrary.wiley.com/cms/attachment/da39f929-a37b-4ef9-9420-c6f4bfe40083/ece35612-math-0001.png\" alt=\"urn:x-wiley:20457758:media:ece35612:ece35612-math-0001\" data-mce-src=\"https://onlinelibrary.wiley.com/cms/attachment/da39f929-a37b-4ef9-9420-c6f4bfe40083/ece35612-math-0001.png\"><span>&nbsp;=&nbsp;0.86&nbsp;±&nbsp;0.10) since 2010, but no evidence of decline for the little brown bat (</span><img class=\"section_image\" src=\"https://onlinelibrary.wiley.com/cms/attachment/3af7a05c-e0f3-4ccc-a03b-47cbf6affca2/ece35612-math-0002.png\" alt=\"urn:x-wiley:20457758:media:ece35612:ece35612-math-0002\" data-mce-src=\"https://onlinelibrary.wiley.com/cms/attachment/3af7a05c-e0f3-4ccc-a03b-47cbf6affca2/ece35612-math-0002.png\"><span>&nbsp;=&nbsp;1.1&nbsp;±&nbsp;0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5612","usgsCitation":"Rodhouse, T.J., Rodriguez, R.M., Banner, K.M., Ormsbee, P.C., Barnett, J., and Irvine, K., 2019, Evidence of region‐wide bat population decline from long‐term monitoring and Bayesian occupancy models with empirically informed priors: Ecology and Evolution, v. 9, no. 19, p. 11078-11088, https://doi.org/10.1002/ece3.5612.","productDescription":"11 p.","startPage":"11078","endPage":"11088","ipdsId":"IP-107039","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":459850,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5612","text":"Publisher Index Page"},{"id":369257,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.8486328125,\n              41.75492216766298\n            ],\n            [\n              -116.806640625,\n              41.75492216766298\n            ],\n            [\n              -116.806640625,\n              49.081062364320736\n            ],\n            [\n              -124.8486328125,\n              49.081062364320736\n            ],\n            [\n              -124.8486328125,\n              41.75492216766298\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"19","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Rodhouse, Thomas J.","contributorId":173361,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":775348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodriguez, Rogelio M.","contributorId":220628,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Rogelio","email":"","middleInitial":"M.","affiliations":[{"id":40195,"text":"Oregon State University-Cascades Campus","active":true,"usgs":false}],"preferred":false,"id":775349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banner, Katharine M.","contributorId":220630,"corporation":false,"usgs":false,"family":"Banner","given":"Katharine","email":"","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":775350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ormsbee, Patricia C.","contributorId":173426,"corporation":false,"usgs":false,"family":"Ormsbee","given":"Patricia","email":"","middleInitial":"C.","affiliations":[{"id":27227,"text":"U.S. Forest Service, Willamette National Forest","active":true,"usgs":false}],"preferred":false,"id":775351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnett, Jenny","contributorId":220629,"corporation":false,"usgs":false,"family":"Barnett","given":"Jenny","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":775352,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Irvine, Kathryn 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":220632,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":775347,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70203470,"text":"pp1837B - 2019 - Evaluation of chemical and hydrologic processes in the eastern Snake River Plain Aquifer based on results from geochemical modeling, Idaho National Laboratory, eastern Idaho","interactions":[],"lastModifiedDate":"2023-04-14T16:58:11.822101","indexId":"pp1837B","displayToPublicDate":"2019-09-11T15:03:14","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837-B","displayTitle":"Evaluation of Chemical and Hydrologic Processes in the Eastern Snake River Plain Aquifer Based on Results from Geochemical Modeling, Idaho National Laboratory, Eastern Idaho","title":"Evaluation of chemical and hydrologic processes in the eastern Snake River Plain Aquifer based on results from geochemical modeling, Idaho National Laboratory, eastern Idaho","docAbstract":"<p>Nuclear research activities at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) produced liquid and solid chemical and radiochemical wastes that were disposed to the subsurface resulting in detectable concentrations of some waste constituents in the eastern Snake River Plain (ESRP) aquifer. These waste constituents may affect the water quality of the aquifer and may pose risks to the eventual users of the aquifer water. To understand these risks to water quality the U.S. Geological Survey, in cooperation with the DOE, conducted geochemical mass-balance modeling of the ESRP aquifer to improve the understanding of chemical reactions, sources of recharge, mixing of water, and groundwater flow directions in the shallow (upper 250 feet) aquifer at the INL.</p><p>Modeling was conducted using the water chemistry of 127 water samples collected from sites at and near the INL. Water samples were collected between 1952 and 2017 with most of the samples collected during the mid-1990s. Geochemistry and isotopic data used in geochemical modeling consisted of dissolved oxygen, carbon dioxide, major ions, silica, aluminum, iron, and the stable isotope ratios of hydrogen, oxygen, and carbon.</p><p>Geochemical modeling results indicated that the primary chemical reactions in the aquifer were precipitation of calcite and dissolution of plagioclase (An<sub>60</sub>) and basalt volcanic glass. Secondary minerals other than calcite included calcium montmorillonite and goethite. Reverse cation exchange, consisting of sodium exchanging for calcium on clay minerals, occurred near site facilities where large amounts of sodium were released to the ESRP aquifer in wastewater discharge. Reverse cation exchange acted to retard the movement of wastewater-derived sodium in the aquifer.</p><p>Regional groundwater inflow was the primary source of recharge to the aquifer underlying the Northeast and Southeast INL Areas. Birch Creek (BC), the Big Lost River (BLR), and groundwater from BC valley provided recharge to the North INL Area, and the BLR and groundwater from BC and Little Lost River (LLR) valleys provided recharge to the Central INL Area. The BLR, groundwater from the BLR and LLR valleys and the Lost River Range, and precipitation provided recharge to the Northwest and Southwest INL Areas. The primary source of recharge west and southwest of the INL was groundwater inflow from BLR valley. Upwelling geothermal water was a small source of recharge at two wells. Aquifer recharge from surface water in the northern, central, and western parts of the INL indicated that the aquifer in these areas was a dynamic, open system, whereas the aquifer in the eastern part of the INL, which receives little recharge from surface water, was a relatively static and closed system.</p><p>Sources of recharge identified from isotope ratios and&nbsp;geochemical modeling (major ion concentrations) were nearly&nbsp;identical for the North, Northeast, Southeast, and Central INL&nbsp;Areas, which indicated that both methods probably accurately&nbsp;identified the sources of recharge in these areas. Conversely,&nbsp;isotope ratios indicated that the BLR and groundwater&nbsp;from the LLR valley provided most recharge to the western&nbsp;parts of the Northwest and Southwest INL Areas, whereas&nbsp;geochemical modeling results indicated a smaller area of&nbsp;recharge from the BLR and groundwater from the LLR valley,&nbsp;a larger area of recharge from the Lost River Range, and&nbsp;recharge of groundwater from the BLR valley that extended&nbsp;to the west INL boundary. The results from geochemical&nbsp;modeling probably were more accurate because major ion&nbsp;concentrations, but not isotope ratios, were available to&nbsp;characterize groundwater from the BLR valley and the Lost&nbsp;River Range.&nbsp;</p><p>Sources of recharge identified with a groundwater flow&nbsp;model (using particle tracking) and geochemical modeling&nbsp;were similar for the Northeast and Southeast INL Areas.&nbsp;However, differences between the models were that the&nbsp;geochemical model represented (1) recharge of groundwater&nbsp;from the Lost River Range in the western part of the INL,&nbsp;whereas the flow model did not, (2) recharge of groundwater&nbsp;from the BC and BLR valleys extending farther south and&nbsp;east, respectively, than the flow model, and (3) more recharge&nbsp;from the BLR in the Southwest INL Area than the flow model.<br></p><p>Mixing of aquifer water beneath the INL included (1)&nbsp;mixing of regional groundwater and water from the BC valley&nbsp;in the Northeast and Southeast INL Areas and (2) mixing of&nbsp;surface water (primarily from the BLR) and groundwater&nbsp;across much of the North, Central, Northwest, and Southwest&nbsp;INL Areas. Localized recharge from precipitation mixed with&nbsp;groundwater in the Northwest and Southwest INL Areas, and&nbsp;localized upwelling geothermal water mixed with groundwater&nbsp;in the Central and Northeast INL Areas. Flow directions of&nbsp;regional groundwater were south in the eastern part of the INL&nbsp;and south-southwest at downgradient locations. Groundwater&nbsp;from the BC and LLR valleys initially flowed southeast&nbsp;before changing to south-southwest flow directions that&nbsp;paralleled regional groundwater, and groundwater from the&nbsp;BLR valley initially flowed south before changing to a southsouthwest direction.<br></p><p>Wastewater-contaminated groundwater flowed south&nbsp;from the Idaho Nuclear Technology and Engineering Center&nbsp;(INTEC) infiltration ponds in a narrow plume, with the&nbsp;percentage of wastewater in groundwater decreasing due to&nbsp;dilution, dispersion, and (or) degradation from about 60‒80&nbsp;percent wastewater 0.7‒0.8 mile (mi) south of the INTEC&nbsp;infiltration ponds to about 1.4 percent wastewater about&nbsp;15.5 mi south of the INTEC infiltration ponds. Wastewater contaminated groundwater flowed southeast and then&nbsp;southwest from the Naval Reactors Facility industrial waste&nbsp;ditch, with the percentage of wastewater in groundwater&nbsp;decreasing from about 100 percent wastewater adjacent to the&nbsp;waste ditch to about 2 percent wastewater about 0.6 mi south&nbsp;of the waste ditch.<br></p><p><br data-mce-bogus=\"1\"></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1837B","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Rattray, G.W., 2019, Evaluation of chemical and hydrologic processes in the eastern Snake River Plain aquifer based on results from geochemical modeling, Idaho National Laboratory, eastern Idaho: U.S. Geological Survey Professional Paper 1837-B (DOE/ID-22248), 85 p., https://doi.org/10.3133/pp1837B.","productDescription":"viii, 85 p.","ipdsId":"IP-098993","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":415799,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837D","text":"PP 1837 Chapter D","description":"PP 1837 Chapter D"},{"id":415798,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837C","text":"PP 1837 Chapter C","description":"PP 1837 Chapter C"},{"id":415797,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837A","text":"PP 1837 Chapter A","description":"PP 1837 Chapter A"},{"id":367371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1837/b/pp1837b.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1837B"},{"id":367370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1837/b/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.16629028320312,\n              43.402054267905655\n            ],\n            [\n              -111.87515258789062,\n              43.402054267905655\n            ],\n            [\n              -111.87515258789062,\n              43.68872888432795\n            ],\n            [\n              -112.16629028320312,\n              43.68872888432795\n            ],\n            [\n              -112.16629028320312,\n              43.402054267905655\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","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\" rel=\"noopener\" 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</li><li>Introduction</li><li>Geochemistry Data</li><li>Sources of Solutes</li><li>Geochemical Modeling</li><li>Hydrologic Interpretation of Model Results</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li><li>Glossary</li><li>Appendixes 1–2</li></ul>","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2019-09-11","noUsgsAuthors":false,"publicationDate":"2019-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762788,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70205261,"text":"70205261 - 2019 - Drought-mediated extinction of an arid-land amphibian: Insights from a spatially explicit dynamic occupancy model","interactions":[],"lastModifiedDate":"2019-09-13T09:52:19","indexId":"70205261","displayToPublicDate":"2019-09-11T11:49:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Drought-mediated extinction of an arid-land amphibian: Insights from a spatially explicit dynamic occupancy model","docAbstract":"Understanding how natural and anthropogenic processes affect population dynamics of species with patchy distributions is critical to predicting their responses to environmental changes. Despite considerable evidence that demographic rates and dispersal patterns vary temporally in response to an array of biotic and abiotic processes, few applications of metapopulation theory have sought to explore factors that explain spatio-temporal variation in extinction or colonization rates. To facilitate exploring these factors, we extended a spatially explicit model of metapopulation dynamics to create a framework that requires only binary presence-absence data, makes few assumptions about the dispersal process, and accounts for imperfect detection. We apply this framework to 22 years of biannual survey data for lowland leopard frogs, Lithobates yavapaiensis, an amphibian that inhabits arid stream systems in the southwestern U.S. and northern Mexico. Our results highlight the importance of accounting for factors that govern temporal variation in transition probabilities, as both extinction and colonization rates varied with hydrologic conditions. Specifically, local extinctions were more frequent during drought periods, particularly at sites without reliable surface water. Colonization rates increased when larval and dispersal periods were wetter than normal, which increased the probability that potential emigrants metamorphosed and reached neighboring sites. Extirpation of frogs from one watershed during a period of severe drought demonstrated the influence of site-level features, as frogs persisted only in areas where most sites held water consistently and where the amount of sediment deposited from high-elevation wildfires was low. Application of our model provided novel insights into how climate-related processes affected the distribution and population dynamics of an arid-land amphibian. The approach we describe has application to a wide array of species that inhabit patchy environments, can improve our understanding of factors that govern metapopulation dynamics, and can inform strategies for conservation of imperiled species.","language":"English","publisher":"Wiley","doi":"10.1002/eap.1859","usgsCitation":"Zylstra, E.R., Swann, D.E., Hossack, B.R., and Steidl, R., 2019, Drought-mediated extinction of an arid-land amphibian: Insights from a spatially explicit dynamic occupancy model: Ecological Applications, v. 29, no. 3, e01859, 15 p., https://doi.org/10.1002/eap.1859.","productDescription":"e01859, 15 p.","onlineOnly":"Y","ipdsId":"IP-095315","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":459858,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/632180","text":"External Repository"},{"id":367345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Rincon Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.70648193359375,\n              32.66018807572586\n            ],\n            [\n              -110.93170166015625,\n              32.465743313283596\n            ],\n            [\n              -110.9564208984375,\n              32.35676318267808\n            ],\n            [\n              -110.66253662109375,\n              32.2546200600072\n            ],\n            [\n              -110.753173828125,\n              32.22674287041067\n            ],\n            [\n              -110.73944091796875,\n              32.15933769278929\n            ],\n            [\n              -110.60211181640624,\n              32.05464469054932\n            ],\n            [\n              -110.3961181640625,\n              32.056972505418514\n            ],\n            [\n              -110.390625,\n              32.15236189465577\n            ],\n            [\n              -110.43731689453125,\n              32.25926542645933\n            ],\n            [\n              -110.58013916015625,\n              32.400834826722196\n            ],\n            [\n              -110.68450927734375,\n              32.491230287947594\n            ],\n            [\n              -110.70648193359375,\n              32.66018807572586\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"29","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"editors":[{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":770597,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Zylstra, Erin R 0000-0002-2536-0403","orcid":"https://orcid.org/0000-0002-2536-0403","contributorId":218873,"corporation":false,"usgs":false,"family":"Zylstra","given":"Erin","email":"","middleInitial":"R","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":770594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swann, Don E.","contributorId":218874,"corporation":false,"usgs":false,"family":"Swann","given":"Don","email":"","middleInitial":"E.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":770595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":770593,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steidl, Robert J","contributorId":218875,"corporation":false,"usgs":false,"family":"Steidl","given":"Robert J","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":770596,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70205273,"text":"70205273 - 2019 - Using social-context matching to improve spatial function-transfer performance for cultural ecosystem service models","interactions":[],"lastModifiedDate":"2019-09-11T11:41:28","indexId":"70205273","displayToPublicDate":"2019-09-11T11:32:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Using social-context matching to improve spatial function-transfer performance for cultural ecosystem service models","docAbstract":"Recreational and aesthetic enjoyment of public lands is increasing across a wide range of activities, highlighting the need to assess and adapt management to accommodate these uses. Despite a growing number of studies on mapping cultural ecosystem services, most are local-scale assessments that rely on costly and time-consuming primary data collection. As a result, the availability of spatial information on non-market values associated with cultural ecosystem services (social values) remains limited. Spatial function transfer, if it could be justified for social-value models, would expedite the development of social-value information and promote its more regular inclusion in ecosystem service assessments. We used survey data from six national forests in Colorado and Wyoming to explore the potential for transferring cultural ecosystem service models between forests and specifically to test the hypothesis that transfer performance increases with social-context similarity between transferring and receiving areas. Results confirm this relationship but fall just short of being able to predict with certainty when transferred models will meet the minimum performance criterion needed for defensible use by managers. Social values are highly variable and can be difficult to predict, but our results suggest that with the right combination of indicators spatial function transfer can become a defensible means of generating social-value information when primary data collection is not feasible.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2019.100945","usgsCitation":"Semmens, D.J., Sherrouse, B.C., and Ancona, Z.H., 2019, Using social-context matching to improve spatial function-transfer performance for cultural ecosystem service models: Ecosystem Services, v. 38, https://doi.org/10.1016/j.ecoser.2019.100945.","onlineOnly":"Y","ipdsId":"IP-091558","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467325,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2019.100945","text":"Publisher Index Page"},{"id":437343,"rank":0,"type":{"id":30,"text":"Data 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,{"id":70205274,"text":"70205274 - 2019 - Monarch habitat as a component of multifunctional landscape restoration using continuous riparian buffers","interactions":[],"lastModifiedDate":"2019-09-11T11:31:44","indexId":"70205274","displayToPublicDate":"2019-09-11T11:31:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Monarch habitat as a component of multifunctional landscape restoration using continuous riparian buffers","docAbstract":"Stabilizing the eastern, migratory population of monarch butterflies (Danaus plexippus) is expected to require substantial habitat restoration on agricultural land in the core breeding area of the Upper Midwestern U.S. Previous research has considered the potential to utilize marginal land for this purpose because of its low productivity, erodible soils, and high nutrient input requirements. This strategy has strong potential for restoring milkweed (Asclepias spp.), but may be limited in terms of its ability to generate additional biophysical and socioeconomic benefits for local communities. Here we explore the possibility of restoring milkweed via the creation of continuous riparian buffer strips around rivers and streams throughout the region. We use a GIS-based analysis to consider the potential of several different buffer-width scenarios to meet milkweed restoration targets. We further estimate the ability of these habitat areas to provide additional functionality in the form of crop pollination and water quality regulation across the entire region. Finally, we estimate the conservative economic value of these ecosystem services and compare it with the lost value of crops associated with each scenario. Results suggest that riparian buffers could be used to meet 10-43% of the total milkweed restoration target of 1.3 billion new stems with moderate management. The value of water quality and pollination benefits provided by buffers is estimated to exceed costs only for our smallest buffer-width scenario, with a cost-benefit ratio of 1:2. Larger buffer widths provide more milkweed, but costs to farmers exceed the benefits we were able to quantify. The large-scale restoration of multifunctional riparian corridors thus has the potential to be a win-win scenario, adding milkweed stems while also providing a variety of other valuable benefits. This suggests the potential to leverage monarch habitat restoration efforts for the benefit of a wider variety of species and broader coalition of beneficiaries.","language":"English","publisher":"Ecological Society of America","doi":"10.3389/fenvs.2019.00126","usgsCitation":"Semmens, D.J., and Ancona, Z.H., 2019, Monarch habitat as a component of multifunctional landscape restoration using continuous riparian buffers: Frontiers in Environmental Science, v. 7, 126 p., https://doi.org/10.3389/fenvs.2019.00126.","productDescription":"126 p.","numberOfPages":"126","onlineOnly":"Y","ipdsId":"IP-106057","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467326,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2019.00126","text":"Publisher Index Page"},{"id":437345,"rank":0,"type":{"id":30,"text":"Data 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,{"id":70215104,"text":"70215104 - 2019 - Detection of rock bridges by infrared thermal imaging and modeling","interactions":[],"lastModifiedDate":"2020-10-07T15:48:15.017733","indexId":"70215104","displayToPublicDate":"2019-09-11T10:39:37","publicationYear":"2019","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":"Detection of rock bridges by infrared thermal imaging and modeling","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Characterization of rock discontinuities and rock bridges is required to define stability conditions of fractured rock masses in both natural and engineered environments. Although remote sensing methods for mapping discontinuities have improved in recent years, remote detection of intact rock bridges on cliff faces remains challenging, with their existence typically confirmed only after failure. In steep exfoliating cliffs, such as El Capitan in Yosemite Valley (California, USA), rockfalls mainly occur along cliff-parallel exfoliation joints, with rock bridges playing a key role in the stability of partially detached exfoliation sheets. We employed infrared thermal imaging (i.e., thermography) as a new means of detecting intact rock bridges prior to failure. An infrared thermal panorama of El Capitan revealed cold thermal signatures for the surfaces of two granitic exfoliation sheets, consistent with the expectation that air circulation cools the back of the partially detached sheets. However, we also noted small areas of warm thermal anomalies on these same sheets, even during periods of nocturnal rock cooling. Rock attachment via rock bridges is the likely cause for the warm anomalies in the thermal data. 2-D model simulations of the thermal behavior of one of &nbsp;the monitored sheets reproduce the observed anomalies and explain the temperature differences detected in the rock bridge area. Based on combined thermal and ground-based lidar imaging, and using geometric and rock fracture mechanics analysis, we are able to quantify the stability of both sheets. Our analysis demonstrates that thermography can remotely detect intact rock bridges and thereby greatly improve rockfall hazard assessment.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-49336-1","usgsCitation":"Guerin, A., Jaboyefoff, M., Collins, B.D., Derron, M., Stock, G.M., Matasci, B., Boesiger, M., Lefeuvre, C., and Podladchikov, Y.Y., 2019, Detection of rock bridges by infrared thermal imaging and modeling: Scientific Reports, v. 9, 13138, 19 p., https://doi.org/10.1038/s41598-019-49336-1.","productDescription":"13138, 19 p.","ipdsId":"IP-102814","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":459866,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-49336-1","text":"Publisher Index Page"},{"id":379177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.981689453125,\n              37.13404537126446\n            ],\n            [\n              -118.83911132812499,\n              37.13404537126446\n            ],\n            [\n              -118.83911132812499,\n              38.14319750166766\n            ],\n            [\n              -119.981689453125,\n              38.14319750166766\n            ],\n            [\n              -119.981689453125,\n              37.13404537126446\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2019-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Guerin, Antoine","contributorId":236904,"corporation":false,"usgs":false,"family":"Guerin","given":"Antoine","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaboyefoff, Michel","contributorId":242812,"corporation":false,"usgs":false,"family":"Jaboyefoff","given":"Michel","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":800885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Derron, Marc-Henri","contributorId":236906,"corporation":false,"usgs":false,"family":"Derron","given":"Marc-Henri","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stock, Greg M.","contributorId":202873,"corporation":false,"usgs":false,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":800887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matasci, Battista","contributorId":204938,"corporation":false,"usgs":false,"family":"Matasci","given":"Battista","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boesiger, Martin","contributorId":242813,"corporation":false,"usgs":false,"family":"Boesiger","given":"Martin","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800889,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lefeuvre, Caroline","contributorId":242814,"corporation":false,"usgs":false,"family":"Lefeuvre","given":"Caroline","email":"","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800890,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Podladchikov, Yury Y.","contributorId":242815,"corporation":false,"usgs":false,"family":"Podladchikov","given":"Yury","email":"","middleInitial":"Y.","affiliations":[{"id":37010,"text":"University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":800891,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70228039,"text":"70228039 - 2019 - How characteristic is the species characteristic selection scale?","interactions":[],"lastModifiedDate":"2022-02-03T16:15:10.817312","indexId":"70228039","displayToPublicDate":"2019-09-11T10:12:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"How characteristic is the species characteristic selection scale?","docAbstract":"<h3 id=\"geb12998-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>The importance of framing investigations of organism–environment relationships to interpret patterns at relevant spatial scales is increasingly recognized. However, most research related to environmental relationships is single-scaled, implicitly or explicitly assuming that a “species characteristic selection scale” exists. We tested the premise that a single characteristic scale exists to understand species–environment relationships within species by asking (a) what are the characteristic scales of species’ relationships with environmental predictors, and (b) is within-species, cross-predictor consistency in characteristic scales a general phenomenon.</p><h3 id=\"geb12998-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Nebraska, USA.</p><h3 id=\"geb12998-sec-0003-title\" class=\"article-section__sub-title section1\">Time period</h3><p>2016.</p><h3 id=\"geb12998-sec-0004-title\" class=\"article-section__sub-title section1\">Major taxa studied</h3><p>Birds.</p><h3 id=\"geb12998-sec-0005-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We used data from 86 species at &gt;&nbsp;500 locations to build hierarchical N-mixture models relating species abundance to land cover variables. By incorporating Bayesian latent indicator scale selection, we identified the spatial scales that best explain species–environment relationships with each land cover predictor. We quantified the extent of cross-predictor consistency in characteristic scales, and contrasted this to the expectation given a single species’ characteristic scale.</p><h3 id=\"geb12998-sec-0006-title\" class=\"article-section__sub-title section1\">Results</h3><p>We found no evidence for a characteristic spatial scale explaining all abundance–environment relationships within species, rather we found substantial variation in scale-dependence across multiple environmental attributes. Furthermore, 33% of species displayed evidence of multiple important spatial scales within environmental attributes.</p><h3 id=\"geb12998-sec-0007-title\" class=\"article-section__sub-title section1\">Major conclusions</h3><p>Within species there is little evidence for a single characteristic scale of environmental relationships and considerable variation in species’ scale dependencies. Because species may respond to multiple environmental attributes at different spatial scales, or single environmental attributes at multiple scales, we caution against any unoptimized single-scale studies. Our results demonstrate that until a framework is developed to predict the scales at which species respond to environmental characteristics, multi-scale investigations must be performed to identify and account for multi-scale dependencies. Natural selection acting on species’ response to distinct environmental attributes, rather than natural selection acting on species’ perception of spatial scales per se, may have shaped patterns of scale dependency and is an area ripe for investigation.</p>","language":"English","publisher":"Wiley","doi":"10.1111/geb.12998","usgsCitation":"Stuber, E.F., and Fontaine, J.J., 2019, How characteristic is the species characteristic selection scale?: Global Ecology and Biogeography, v. 28, no. 12, p. 1839-1854, https://doi.org/10.1111/geb.12998.","productDescription":"16 p.","startPage":"1839","endPage":"1854","ipdsId":"IP-096833","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.053249,41.001406],[-104.053127,43.000585],[-101.849982,42.999329],[-101.625424,42.996238],[-100.472742,42.999288],[-98.49855,42.99856],[-98.490483,42.977948],[-98.467356,42.947556],[-98.448309,42.936428],[-98.444145,42.929242],[-98.437285,42.928393],[-98.430934,42.931504],[-98.42074,42.931924],[-98.34623,42.902747],[-98.325864,42.8865],[-98.280007,42.874996],[-98.25181,42.872824],[-98.219826,42.853157],[-98.189765,42.841628],[-98.167523,42.836925],[-98.14806,42.840013],[-98.137912,42.832728],[-98.127489,42.820127],[-98.107688,42.810633],[-98.094574,42.799309],[-98.067388,42.784759],[-98.062913,42.781119],[-98.059838,42.772772],[-98.056625,42.770781],[-98.035034,42.764205],[-98.013046,42.762299],[-98.005739,42.764167],[-98.000348,42.763256],[-97.977588,42.769923],[-97.950147,42.769619],[-97.936716,42.775754],[-97.921434,42.788352],[-97.908983,42.794909],[-97.888562,42.817251],[-97.879878,42.835395],[-97.878976,42.843673],[-97.875849,42.847725],[-97.877003,42.854394],[-97.875345,42.858724],[-97.84527,42.867734],[-97.828496,42.868797],[-97.817075,42.861781],[-97.774456,42.849774],[-97.72045,42.847439],[-97.686506,42.842435],[-97.657846,42.844626],[-97.611811,42.858367],[-97.603762,42.858329],[-97.591916,42.853837],[-97.561928,42.847552],[-97.531867,42.850105],[-97.504847,42.858477],[-97.49149,42.851625],[-97.470529,42.850455],[-97.452177,42.846048],[-97.442279,42.846224],[-97.431951,42.851542],[-97.417066,42.865918],[-97.408315,42.868334],[-97.393966,42.86425],[-97.376695,42.865195],[-97.368643,42.858419],[-97.359569,42.854816],[-97.336156,42.856802],[-97.306677,42.867604],[-97.289859,42.855499],[-97.267946,42.852583],[-97.248556,42.855386],[-97.218825,42.845848],[-97.217411,42.843519],[-97.218269,42.829561],[-97.213957,42.820143],[-97.213084,42.813007],[-97.210126,42.809296],[-97.200431,42.805485],[-97.166978,42.802087],[-97.150763,42.795566],[-97.138216,42.783428],[-97.134461,42.774494],[-97.131331,42.771929],[-97.096128,42.76934],[-97.065592,42.772189],[-97.033229,42.765904],[-97.02485,42.76243],[-96.99282,42.759481],[-96.97912,42.76009],[-96.96888,42.754278],[-96.96123,42.740623],[-96.965833,42.727096],[-96.964776,42.722455],[-96.961576,42.719841],[-96.948902,42.719465],[-96.924156,42.730327],[-96.906797,42.7338],[-96.886845,42.725222],[-96.860436,42.720797],[-96.843419,42.712024],[-96.806223,42.704154],[-96.801652,42.698774],[-96.800485,42.692466],[-96.802178,42.672237],[-96.800986,42.669758],[-96.793238,42.666024],[-96.76406,42.661985],[-96.746949,42.666223],[-96.728024,42.666882],[-96.691269,42.6562],[-96.687669,42.653126],[-96.687788,42.645992],[-96.709485,42.621932],[-96.711546,42.614758],[-96.7093,42.603753],[-96.681369,42.574486],[-96.658754,42.566426],[-96.643589,42.557604],[-96.63533,42.54764],[-96.632882,42.528987],[-96.628179,42.516963],[-96.625958,42.513576],[-96.611489,42.506088],[-96.603468,42.50446],[-96.591121,42.50541],[-96.567896,42.517877],[-96.548791,42.520547],[-96.538036,42.518131],[-96.528753,42.513273],[-96.520683,42.504761],[-96.515891,42.49427],[-96.508587,42.486691],[-96.501321,42.482749],[-96.478792,42.479635],[-96.443408,42.489495],[-96.423892,42.48898],[-96.396107,42.484095],[-96.386007,42.474495],[-96.381307,42.461694],[-96.380707,42.446394],[-96.387608,42.432494],[-96.413609,42.407894],[-96.41498,42.393442],[-96.408436,42.376092],[-96.417093,42.361443],[-96.417786,42.351449],[-96.413895,42.343393],[-96.407998,42.337408],[-96.384169,42.325874],[-96.375307,42.318339],[-96.369212,42.308344],[-96.368454,42.291848],[-96.365792,42.285875],[-96.356406,42.276493],[-96.336003,42.264806],[-96.328905,42.254734],[-96.327706,42.249992],[-96.330004,42.240224],[-96.322868,42.233637],[-96.323723,42.229887],[-96.336323,42.218922],[-96.356591,42.215182],[-96.35987,42.210545],[-96.348066,42.194747],[-96.347243,42.186721],[-96.350323,42.17744],[-96.347752,42.166806],[-96.33798,42.157197],[-96.319528,42.146647],[-96.310085,42.132523],[-96.301023,42.128042],[-96.279203,42.12348],[-96.2689,42.11359],[-96.266594,42.103262],[-96.267636,42.096177],[-96.276758,42.081416],[-96.279079,42.074026],[-96.278445,42.060399],[-96.275548,42.051976],[-96.271427,42.044988],[-96.263886,42.039858],[-96.256087,42.03808],[-96.246832,42.041616],[-96.238392,42.041088],[-96.225656,42.035217],[-96.221901,42.029558],[-96.223611,42.022652],[-96.238859,42.012315],[-96.241932,42.006965],[-96.240713,41.999351],[-96.236487,41.996428],[-96.225463,41.994734],[-96.215225,42.006701],[-96.206083,42.009267],[-96.194556,42.008662],[-96.188067,42.006323],[-96.183568,41.999987],[-96.192141,41.984461],[-96.186265,41.977417],[-96.177203,41.976325],[-96.156538,41.980137],[-96.141228,41.978063],[-96.129505,41.971673],[-96.129186,41.965136],[-96.133318,41.955732],[-96.144583,41.941544],[-96.136613,41.927167],[-96.136743,41.920826],[-96.142265,41.915379],[-96.159098,41.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,{"id":70208561,"text":"70208561 - 2019 - Soil and stand structure explain shrub mortality patterns following global change–type drought and extreme precipitation","interactions":[],"lastModifiedDate":"2020-02-18T06:17:13","indexId":"70208561","displayToPublicDate":"2019-09-11T06:46:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Soil and stand structure explain shrub mortality patterns following global change–type drought and extreme precipitation","docAbstract":"(Bradford) The probability of extreme weather events is increasing, with the potential for widespread impacts to plants, plant communities, and ecosystems. Reports of drought-related tree mortality are becoming more frequent along with increasing evidence that drought accompanied by high temperatures is especially detrimental. Simultaneously, extreme large precipitation events have become more frequent over the past century. Water-limited ecosystems may be more vulnerable to these extreme events than other ecosystems, especially when pushed outside of their historical range of variability. However, drought-related mortality of shrubs—an important component of dryland vegetation—remains understudied relative to tree mortality. In 2014, a landscape-scale die-off of the widespread shrub, big sagebrush (Artemisia tridentata Nutt.), was reported in southwest Wyoming, following extreme hot and dry conditions in 2012 and extremely high precipitation in September of 2013. Here, we examined how severe drought, extreme precipitation, soil texture and salinity, and potential competition contributed to this die-off event. At 98 plots within and around the die-off we quantified big sagebrush mortality, characterized soil texture and salinity, and simulated soil water conditions from 1916-2016 using an ecosystem water balance model. We found that the extreme weather conditions alone did not explain patterns of big sagebrush mortality and did not result in extreme (historically unprecedented) soil water conditions during the drought. Instead, plots with chronically dry soil conditions experienced greatest mortality following the global-change type (hot) drought in 2012. Furthermore, mortality was greater in locations with high potential run-on and low potential run-off where saturated soil conditions were simulated in September 2013, suggesting that extreme precipitation also played an important role in the die-off in these locations. In locations where drought alone contributed to mortality, competition negatively impacted big sagebrush. In locations that may have been affected by both drought and saturation, however, mortality was greatest where competition was lowest, suggesting that these locations may have already been less favorable to big sagebrush. Paradoxically, vulnerability to both extreme events (drought and saturation) was associated with finer-textured soils, and our results highlight the importance of soils in determining local variation the vulnerability of dryland plants to extreme events.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2889","usgsCitation":"Renne, R.R., Schlaepfer, D., Palmquist, K.A., Bradford, J.B., Burke, I.C., and Lauenroth, W.K., 2019, Soil and stand structure explain shrub mortality patterns following global change–type drought and extreme precipitation: Ecology, v. 100, no. 12, e02889, 17 p., https://doi.org/10.1002/ecy.2889.","productDescription":"e02889, 17 p.","ipdsId":"IP-107245","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":372376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.67626953125,\n              41.29431726315258\n            ],\n            [\n              -108.67675781249999,\n              41.29431726315258\n            ],\n            [\n              -108.67675781249999,\n              42.74701217318067\n            ],\n            [\n              -110.67626953125,\n              42.74701217318067\n            ],\n            [\n              -110.67626953125,\n              41.29431726315258\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"100","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-10-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Renne, Rachel R.","contributorId":213935,"corporation":false,"usgs":false,"family":"Renne","given":"Rachel","email":"","middleInitial":"R.","affiliations":[{"id":38934,"text":"School of Forestry and Environmental Studies, Yale University, New Haven, CT 06511, USA","active":true,"usgs":false}],"preferred":false,"id":782495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":782498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burke, Ingrid C.","contributorId":127653,"corporation":false,"usgs":false,"family":"Burke","given":"Ingrid","email":"","middleInitial":"C.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782499,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":782500,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70206135,"text":"70206135 - 2019 - Multivariate models and analyses","interactions":[],"lastModifiedDate":"2020-09-01T20:05:54.143483","indexId":"70206135","displayToPublicDate":"2019-09-10T12:46:42","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"3","title":"Multivariate models and analyses","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Quantitative analyses in wildlife science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","usgsCitation":"Stuber, E., Chizinski, C., Lusk, J., and Fontaine, J.J., 2019, Multivariate models and analyses, chap. 3 <i>of</i> Quantitative analyses in wildlife science, p. 32-62.","productDescription":"31 p.","startPage":"32","endPage":"62","ipdsId":"IP-086961","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":368670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368669,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/title/quantitative-analyses-wildlife-science"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stuber, Erica","contributorId":198588,"corporation":false,"usgs":false,"family":"Stuber","given":"Erica","affiliations":[],"preferred":false,"id":773692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chizinski, Christopher","contributorId":219974,"corporation":false,"usgs":false,"family":"Chizinski","given":"Christopher","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":773693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lusk, Jeffrey","contributorId":219975,"corporation":false,"usgs":false,"family":"Lusk","given":"Jeffrey","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":773694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","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":773691,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70206136,"text":"70206136 - 2019 - Comparing ecological models","interactions":[],"lastModifiedDate":"2020-02-19T13:37:17","indexId":"70206136","displayToPublicDate":"2019-09-10T12:42:08","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Comparing ecological models","docAbstract":"<p>No abstract available.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Quantitative Analyses in Wildlife Science","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","isbn":"9781421431086","usgsCitation":"Hooten, M., and Cooch, E.G., 2019, Comparing ecological models, chap. 4 <i>of</i> Quantitative Analyses in Wildlife Science, p. 63-76.","productDescription":"14 p.","startPage":"63","endPage":"76","ipdsId":"IP-086981","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":368668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368667,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://jhupbooks.press.jhu.edu/title/quantitative-analyses-wildlife-science"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":773695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":773991,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70205905,"text":"70205905 - 2019 - κ0 and broadband site spectra in Southern California from source model-constrained inversion","interactions":[],"lastModifiedDate":"2019-10-09T12:39:08","indexId":"70205905","displayToPublicDate":"2019-09-10T12:35:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"κ0 and broadband site spectra in Southern California from source model-constrained inversion","docAbstract":"Ground-motion modeling requires accurate representation of the earthquake source, path, and site. Site amplification is often modeled by VS30, the time-averaged shear-wave velocity of the top 30 meters of the Earth’s surface, though recent studies find that its ability to accurately predict site effects varies. Another measure of the site is κ0, the attenuation of high frequency energy near the site (Anderson & Hough, 1984). We develop a novel application of the Andrews (1986) method to simultaneously invert the spectra of 3,357 earthquakes in Southern California into source and site components. These earthquakes have magnitudes 2.5 to 5.72 and were recorded on 16 stations for a total of 52,297 records. We constrain the inversion with an individual earthquake demonstrating the most Brune-like shape to preserve the site spectra. We then solve for κ0 site amplification at each station in three frequency bands: 1-6 Hz, 6-14 Hz, and 14-35 Hz. The resulting values of κ0 range from 0.017 seconds at ANZA station PFO to 0.059 seconds at ANZA station SND. We compare our results with values of site κ0 from other studies as well as site residuals from GMPEs. We find good agreement between our site κ0 and previous studies in the region. We find that κ0 and high frequency site amplification (14-35 Hz band) correlates well with independent site residuals, making it a good first-order approximation for the effects of site attenuation or amplification on ground motion.","language":"English","publisher":"GeoScienceWorld","doi":"10.1785/0120190037","usgsCitation":"Klimasewski, A., Sahakian, V., Baltay Sundstrom, A.S., Boatwright, J., Fletcher, J.P., and Baker, L., 2019, κ0 and broadband site spectra in Southern California from source model-constrained inversion: Bulletin of the Seismological Society of America, v. 109, no. 5, p. 1878-1889, https://doi.org/10.1785/0120190037.","productDescription":"12 p.","startPage":"1878","endPage":"1889","ipdsId":"IP-102984","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":368167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368166,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1785/0120190037"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.5849609375,\n              32.76880048488168\n            ],\n            [\n              -113.4228515625,\n              32.76880048488168\n            ],\n            [\n              -113.4228515625,\n              38.61687046392973\n            ],\n            [\n              -124.5849609375,\n              38.61687046392973\n            ],\n            [\n              -124.5849609375,\n              32.76880048488168\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"109","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Klimasewski, Alexis","contributorId":219664,"corporation":false,"usgs":false,"family":"Klimasewski","given":"Alexis","email":"","affiliations":[{"id":40043,"text":"U. Oregon","active":true,"usgs":false}],"preferred":false,"id":772822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":772823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":772821,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boatwright, John","contributorId":219666,"corporation":false,"usgs":false,"family":"Boatwright","given":"John","affiliations":[{"id":40044,"text":"USGS, deceased","active":true,"usgs":false}],"preferred":false,"id":772826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fletcher, Jon Peter 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":219665,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":772824,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Lawrence 0000-0001-8563-2362","orcid":"https://orcid.org/0000-0001-8563-2362","contributorId":206522,"corporation":false,"usgs":true,"family":"Baker","given":"Lawrence","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":772825,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70205246,"text":"70205246 - 2019 - Factors affecting post-release survival of coded-wire tagged Lake Trout Salvelinus namaycush in Lake Michigan at four historical spawning locations","interactions":[],"lastModifiedDate":"2019-10-28T10:20:26","indexId":"70205246","displayToPublicDate":"2019-09-10T09:51:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Factors affecting post-release survival of coded-wire tagged Lake Trout Salvelinus namaycush in Lake Michigan at four historical spawning locations","docAbstract":"Since the 1950s, fishery agencies on Lake Michigan have pursued Lake Trout Salvelinus namaycush rehabilitation through Sea Lamprey Petromyzon marinus control, harvest regulations, and by stocking millions of fish annually.  Stocking was prioritized at four historically important spawning locations beginning in 1985, and coded wire tags (CWTs) were used to help evaluate performance.  We used data from CWT fish captured in fishery-independent surveys from 1998 – 2014 to evaluate relative post-release survival of Lake Trout, estimated by catch-per-unit-effort and corrected for the number of fish stocked (CPUE), across 173 CWT tag lots of the 1994 – 2003 year classes stocked at these four locations. Boosted regression tree (BRT) models were used to assess the relative influence of four variables on Lake Trout CPUE in two age groups (age 4-5 years and 6-10 years) and paired with analyses of variance to test for statistical significance. Genetic strain (29.1%), stocking location (27.8%), mortality at release (23.1%) and predator density (19.9%) had similar influence on the relative survival of younger fish, whereas relative survival of older fish was heavily influenced by stocking location (79.8%).  Survival of both age groups was lowest for fish stocked in the Northern Refuge, where the age structure was truncated due to fishery harvest and Sea Lamprey predation. Survival of stocked fish was higher at the Southern Refuge, Clay Banks, and Julian’s Reef, where mortality from sea lamprey and harvest was lower, and where increases in wild Lake Trout have been observed in recent years.  Stocked Lake Michigan remnant genetic strains also appeared to survive better than strains from other lakes at these three locations, but strain effects could not be fully disentangled from effects of stocking location, and continued stocking of multiple genetic strains may provide resiliency toward future selection pressures. Continued progress toward rehabilitation will require reducing fishing and lamprey-induced mortality in northern Lake Michigan to build parental stocks of advanced ages as well as balancing efforts among competing management goals.","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10338","usgsCitation":"Kornis, M.S., Bronte, C.R., Holey, M.E., Hanson, S.D., Treska, T.J., Jonas, J.L., Madenjian, C.P., Claramunt, R.M., Robillard, S.R., Breidert, B., Donner, K.C., Lenart, S.J., Martell, A.W., McKee, P.C., and Olson, E., 2019, Factors affecting post-release survival of coded-wire tagged Lake Trout Salvelinus namaycush in Lake Michigan at four historical spawning locations: North American Journal of Fisheries Management, v. 39, no. 5, p. 868-895, https://doi.org/10.1002/nafm.10338.","productDescription":"28 p.","startPage":"868","endPage":"895","ipdsId":"IP-104527","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":367309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.88037109375,\n              46.10370875598026\n            ],\n            [\n              -86.3525390625,\n              46.164614496897094\n            ],\n            [\n              -87.51708984375,\n              45.90529985724799\n            ],\n            [\n              -88.2861328125,\n              44.55916341529182\n            ],\n            [\n              -88.04443359375,\n              43.88205730390537\n            ],\n            [\n              -88.06640625,\n              42.84375132629021\n            ],\n            [\n              -88.06640625,\n              41.86956082699455\n            ],\n            [\n              -87.29736328125,\n              41.541477666790286\n            ],\n            [\n              -86.66015624999999,\n              41.5579215778042\n            ],\n            [\n              -86.0009765625,\n              42.24478535602799\n            ],\n            [\n              -85.869140625,\n              42.87596410238256\n            ],\n            [\n              -86.02294921875,\n              44.166444664458595\n            ],\n            [\n              -85.84716796875,\n              44.449467536006935\n            ],\n            [\n              -85.18798828125,\n              44.762336674810996\n            ],\n            [\n              -84.7705078125,\n              45.166547157856016\n            ],\n            [\n              -84.88037109375,\n              46.10370875598026\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"39","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Kornis, Matthew S.","contributorId":201252,"corporation":false,"usgs":false,"family":"Kornis","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":770502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bronte, Charles R.","contributorId":190727,"corporation":false,"usgs":false,"family":"Bronte","given":"Charles","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":770503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holey, Mark E.","contributorId":212699,"corporation":false,"usgs":false,"family":"Holey","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":770504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, S. Dale","contributorId":218843,"corporation":false,"usgs":false,"family":"Hanson","given":"S.","email":"","middleInitial":"Dale","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":770505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Treska, Theodore J.","contributorId":218844,"corporation":false,"usgs":false,"family":"Treska","given":"Theodore","email":"","middleInitial":"J.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":770506,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jonas, Jory L.","contributorId":215449,"corporation":false,"usgs":false,"family":"Jonas","given":"Jory","email":"","middleInitial":"L.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":770507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":770501,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Claramunt, Randall M.","contributorId":190497,"corporation":false,"usgs":false,"family":"Claramunt","given":"Randall","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":770508,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Robillard, Steven R.","contributorId":218845,"corporation":false,"usgs":false,"family":"Robillard","given":"Steven","email":"","middleInitial":"R.","affiliations":[{"id":33955,"text":"Illinois Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":770509,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Breidert, Brian","contributorId":195539,"corporation":false,"usgs":false,"family":"Breidert","given":"Brian","email":"","affiliations":[{"id":34295,"text":"Indiana DNR","active":true,"usgs":false}],"preferred":false,"id":770510,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Donner, Kevin C.","contributorId":218846,"corporation":false,"usgs":false,"family":"Donner","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":39923,"text":"Little Traverse Bay Band of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":770511,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lenart, Stephen J.","contributorId":218847,"corporation":false,"usgs":false,"family":"Lenart","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":770512,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Martell, Archie W.","contributorId":218848,"corporation":false,"usgs":false,"family":"Martell","given":"Archie","email":"","middleInitial":"W.","affiliations":[{"id":34298,"text":"Little River Band of Ottawa Indians","active":true,"usgs":false}],"preferred":false,"id":770513,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McKee, Patrick C.","contributorId":218849,"corporation":false,"usgs":false,"family":"McKee","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":770514,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Olson, Erik J.","contributorId":218850,"corporation":false,"usgs":false,"family":"Olson","given":"Erik J.","affiliations":[{"id":34297,"text":"Grand Traverse Band of Ottawa and Chippewa Indians","active":true,"usgs":false}],"preferred":false,"id":770515,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70210078,"text":"70210078 - 2019 - Hydrothermal fluid migration due to interaction with shallow magma: Insights from gravity changes before and after the 2015 eruption of Cotopaxi volcano, Ecuador","interactions":[],"lastModifiedDate":"2020-05-13T13:51:46.81254","indexId":"70210078","displayToPublicDate":"2019-09-10T08:45:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal fluid migration due to interaction with shallow magma: Insights from gravity changes before and after the 2015 eruption of Cotopaxi volcano, Ecuador","docAbstract":"On August 14, 2015 Cotopaxi Volcano (Ecuador) erupted with several phreatomagmatic explosions after nearly 135 years of quiescence. Unrest began in April 2015 with an increase in the number of daily seismic events and inflation of the  flanks of the volcano. Time-lapse gravity measurements started at Cotopaxi volcano in June 2015. Although minor gravity changes were detected prior to eruptive activity, however, the largest gravity variations at Cotopaxi were measured between October 2015 and March 2016, when other geophysical parameters had reached background levels. Inverse modelling of GPS data suggests a deep intrusion prior to the eruptive activity, while inverse modelling of post-eruptive gravity changes suggests variations in the volcano hydrothermal system. Deformation, seismicity, and gravity changes are consistent with the intrusion of a deep magmatic source between April and August 2015. Part of the magma rose from depth and interacted with the hydrothermal system, causing the phreatomagmatic activity and pushing hydrothermal  fluids from a deep aquifer into a shallow perched aquifer.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2019.106667","collaboration":"","usgsCitation":"Calahorrano-Di Patre, A., William-Jones, G., Battaglia, M., Mothes, P., Gaunt, E., Zurek, J., Ruiz, M., and Witter, J., 2019, Hydrothermal fluid migration due to interaction with shallow magma: Insights from gravity changes before and after the 2015 eruption of Cotopaxi volcano, Ecuador: Journal of Volcanology and Geothermal Research, v. 387, 106667, 19 p., https://doi.org/10.1016/j.jvolgeores.2019.106667.","productDescription":"106667, 19 p.","ipdsId":"IP-108094","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":374747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-80.30256,-3.40486],[-79.77029,-2.65751],[-79.98656,-2.22079],[-80.36878,-2.68516],[-80.96777,-2.24694],[-80.76481,-1.96505],[-80.93366,-1.05745],[-80.58337,-0.90666],[-80.39932,-0.2837],[-80.0209,0.36034],[-80.09061,0.76843],[-79.54276,0.98294],[-78.85526,1.38092],[-77.85506,0.80993],[-77.66861,0.82589],[-77.42498,0.39569],[-76.57638,0.25694],[-76.29231,0.41605],[-75.80147,0.0848],[-75.37322,-0.15203],[-75.23372,-0.91142],[-75.545,-1.56161],[-76.63539,-2.60868],[-77.8379,-3.00302],[-78.45068,-3.8731],[-78.6399,-4.54778],[-79.20529,-4.95913],[-79.62498,-4.4542],[-80.02891,-4.34609],[-80.44224,-4.42572],[-80.46929,-4.05929],[-80.18401,-3.82116],[-80.30256,-3.40486]]]},\"properties\":{\"name\":\"Ecuador\"}}]}","volume":"387","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Mothes, Patricia","contributorId":178532,"corporation":false,"usgs":false,"family":"Mothes","given":"Patricia","affiliations":[],"preferred":false,"id":789013,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Gaunt, Elizabeth","contributorId":224663,"corporation":false,"usgs":false,"family":"Gaunt","given":"Elizabeth","email":"","affiliations":[{"id":28071,"text":"Instituto Geofisico, Escuela Politecnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789014,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Zurek, Jeffrey","contributorId":191169,"corporation":false,"usgs":false,"family":"Zurek","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":789015,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Ruiz, Mario","contributorId":224427,"corporation":false,"usgs":false,"family":"Ruiz","given":"Mario","affiliations":[{"id":40882,"text":"Instituto Geofísico at the Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789016,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Witter, Jeffery","contributorId":224664,"corporation":false,"usgs":false,"family":"Witter","given":"Jeffery","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789017,"contributorType":{"id":2,"text":"Editors"},"rank":8}],"authors":[{"text":"Calahorrano-Di Patre, Antonina","contributorId":224661,"corporation":false,"usgs":false,"family":"Calahorrano-Di Patre","given":"Antonina","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"William-Jones, Glyn","contributorId":224662,"corporation":false,"usgs":false,"family":"William-Jones","given":"Glyn","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":789012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mothes, Patricia","contributorId":178532,"corporation":false,"usgs":false,"family":"Mothes","given":"Patricia","affiliations":[],"preferred":false,"id":789034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaunt, Elizabeth","contributorId":224663,"corporation":false,"usgs":false,"family":"Gaunt","given":"Elizabeth","email":"","affiliations":[{"id":28071,"text":"Instituto Geofisico, Escuela Politecnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zurek, Jeffrey","contributorId":191169,"corporation":false,"usgs":false,"family":"Zurek","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":789036,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruiz, Mario","contributorId":224427,"corporation":false,"usgs":false,"family":"Ruiz","given":"Mario","affiliations":[{"id":40882,"text":"Instituto Geofísico at the Escuela Politécnica Nacional, Quito, Ecuador","active":true,"usgs":false}],"preferred":false,"id":789037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Witter, Jeffery","contributorId":224664,"corporation":false,"usgs":false,"family":"Witter","given":"Jeffery","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":789038,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70203786,"text":"sir20195058 - 2019 - Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18","interactions":[],"lastModifiedDate":"2019-09-10T08:04:36","indexId":"sir20195058","displayToPublicDate":"2019-09-09T15:55:00","publicationYear":"2019","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":"2019-5058","displayTitle":"Controls on Spatial and Temporal Variations of Brine Discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18","title":"Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18","docAbstract":"<p>The Paradox Valley in southwestern Colorado is a collapsed anticline formed by movement of the salt-rich Paradox Formation at the core of the anticline. The salinity of the Dolores River, a tributary of the Colorado River, increases substantially as it crosses the valley because of discharge of brine-rich groundwater derived from the underlying salts. Although the brine is naturally occurring, it increases the salinity of the Colorado River, which is a major concern to downstream agricultural, municipal, and industrial water users. The U.S. Geological Survey in cooperation with the Bureau of Reclamation conducted a study to improve the characterization of processes controlling spatial and temporal variations in brine discharge to the Dolores River. For the study, three geophysical surveys were conducted in March, May, and September 2017, and water levels were monitored in selected ponds and groundwater wells from November 2016 to May 2018. The study also utilized streamflow and specific conductance data from two U.S. Geological Survey streamflow-gaging stations on the Dolores River to estimate salt load to the river.</p><p>River-based continuous resistivity profiling and frequency domain electromagnetic induction surveys made during low-flow conditions indicated a zone of brine-rich groundwater close to the riverbed along an approximately 4-kilometer reach of the river. Under high-flow conditions, the brine was depressed as much as 2 meters below the riverbed, and brine discharge to the river was reduced to a minimum. Direct current electrical resistivity surveys show that the freshwater lens overlying the brine is much thicker (up to 10 meters) on the west bank than on the east bank (less than 5 meters). A large low-conductivity anomaly at river distance 6,800 meters was observed in all surveys and may represent a freshwater discharge zone or a losing reach of the river.</p><p>Filling and draining of the wildlife ponds on the west side of the river had a negligible effect on salt loads in the river during the study period. Groundwater monitoring showed there was active exchange of water between the river and the adjacent alluvial aquifer. When river stage was low, groundwater flowed towards the river, and brine discharge to the river increased. When the river stage was high, the gradient was reversed, and fresh surface water recharged the alluvial aquifer&nbsp;minimizing brine discharge. Most of the salt load to the river occurred during the winter and appeared to be enhanced by diurnal stage fluctuations.</p><p>A conceptual model of brine discharge to the river is presented at three scales. Groundwater at the regional scale drives dissolution of salt in the Paradox Formation and flow of brine into the base of the alluvial aquifer. Surface water–groundwater interactions&nbsp;at the scale of the alluvial aquifer control brine discharge to the river seasonally and interannually. At the finest scale, diurnal fluctuations in river stage drive exchange of freshwater with saltier&nbsp;pore water in the hyporheic zone, which appears to increase brine&nbsp;discharge to the river during winter.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195058","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Mast, M.A., and Terry, N., 2019, Controls on spatial and temporal variations of brine discharge to the Dolores River in the Paradox Valley, Colorado, 2016–18: U.S. Geological Survey Scientific Investigations Report 2019–5058, 25 p., https://doi.org/10.3133/sir20195058.\n","productDescription":"vi, 25 p.","onlineOnly":"Y","ipdsId":"IP-103865","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437347,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77080NB","text":"USGS data release","linkHelpText":"Raw Data from Continuous Resistivity Profiles and Electromagnetic Surveys Collected in and adjacent to the Dolores River in the Paradox Valley, Colorado (2017)"},{"id":367271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5058/sir20195058.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5058"},{"id":367270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5058/coverthb.jpg"}],"country":"United States","state":"Colorado","county":"Montrose County","otherGeospatial":"Paradox Valley","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-108.3772,38.6678],[-108.1472,38.6675],[-107.965,38.6664],[-107.9279,38.6661],[-107.9084,38.6664],[-107.8589,38.6663],[-107.8206,38.6664],[-107.7782,38.6661],[-107.7658,38.6663],[-107.741,38.6662],[-107.5011,38.6657],[-107.4992,38.6304],[-107.4989,38.6172],[-107.4992,38.5737],[-107.499,38.5356],[-107.4989,38.4717],[-107.4991,38.4531],[-107.4991,38.4504],[-107.4989,38.4445],[-107.4995,38.4404],[-107.4991,38.4246],[-107.4994,38.4096],[-107.4993,38.4033],[-107.4997,38.3656],[-107.4995,38.3248],[-107.4995,38.3008],[-107.5213,38.301],[-107.6333,38.3005],[-107.6358,38.3095],[-107.633,38.3172],[-107.6314,38.3223],[-107.6292,38.3286],[-107.6339,38.3286],[-107.6867,38.3288],[-107.7049,38.329],[-107.7236,38.3287],[-107.7964,38.329],[-107.8146,38.3292],[-107.8522,38.3291],[-107.8715,38.3293],[-107.9079,38.3292],[-107.9449,38.3295],[-107.9631,38.3296],[-108.0007,38.3304],[-108.0206,38.3305],[-108.1127,38.3312],[-108.1274,38.331],[-108.1276,38.3183],[-108.1165,38.3185],[-108.1163,38.3121],[-108.0987,38.312],[-108.0985,38.283],[-108.0815,38.2828],[-108.0807,38.2547],[-108.0085,38.2537],[-108.0084,38.2482],[-107.9814,38.2477],[-107.981,38.2328],[-107.9628,38.2326],[-107.9627,38.2263],[-107.9468,38.2265],[-107.9466,38.2184],[-107.9367,38.2185],[-107.9367,38.1732],[-107.946,38.1731],[-107.946,38.1517],[-107.9654,38.1519],[-108.0549,38.1522],[-108.2235,38.152],[-108.2411,38.1522],[-108.2587,38.1523],[-108.3336,38.1523],[-108.3506,38.1519],[-108.4641,38.1524],[-108.4841,38.1525],[-108.5397,38.1527],[-108.6304,38.153],[-108.6492,38.1531],[-109.041,38.1531],[-109.0409,38.1603],[-109.0607,38.2768],[-109.0608,38.3304],[-109.0608,38.3521],[-109.0607,38.378],[-109.0607,38.4052],[-109.0606,38.4197],[-109.0604,38.4555],[-109.0604,38.4637],[-109.0602,38.4981],[-109.0602,38.4991],[-108.6635,38.4992],[-108.3791,38.4999],[-108.3771,38.6116],[-108.3772,38.6678]]]},\"properties\":{\"name\":\"Montrose\",\"state\":\"CO\"}}]}","contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/co-water/\" data-mce-href=\"http://www.usgs.gov/centers/co-water/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-415<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Geophysical Surveys and Hydrologic Measurements</li><li>Controls on Brine Discharge to the Dolores River</li><li>Conceptual Model of Brine Discharge to the Dolores River</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-09-09","noUsgsAuthors":false,"publicationDate":"2019-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764129,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terry, Neil C. 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","middleInitial":"C.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","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":764130,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70215387,"text":"70215387 - 2019 - Monitoring drought impact on annual forage production in semi-arid grasslands: A case study of Nebraska sandhills","interactions":[],"lastModifiedDate":"2020-10-18T14:02:49.47461","indexId":"70215387","displayToPublicDate":"2019-09-09T08:58:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring drought impact on annual forage production in semi-arid grasslands: A case study of Nebraska sandhills","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Land management practices and disturbances (e.g. overgrazing, fire) have substantial effects on grassland forage production. When using satellite remote sensing to monitor climate impacts, such as drought stress on annual forage production, minimizing land management practices and disturbance effects sends a clear climate signal to the productivity data. This study investigates the effect of this climate signal by: (1) providing spatial estimates of expected biomass under specific climate conditions, (2) determining which drought indices explain the majority of interannual variability in this biomass, and (3) developing a predictive model that estimates the annual biomass early in the growing season. To address objective 1, this study uses an established methodology to determine Expected Ecosystem Performance (EEP) in the Nebraska Sandhills, US, representing annual forage levels after accounting for non-climatic influences. Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) data were used to approximate actual ecosystem performance. Seventeen years (2000–2016) of annual EEP was calculated using piecewise regression tree models of site potential and climate data. Expected biomass (EB), EEP converted to biomass in kg*ha<sup>−1</sup>*yr<sup>−1</sup>, was then used to examine the predictive capacity of several drought indices and the onset date of the growing season. Subsets of these indices were used to monitor and predict annual expected grassland biomass. Independent field-based biomass production data available from two Sandhills locations were used for validation of the EEP model. The EB was related to field-based biomass production (R<sup>2</sup><span>&nbsp;</span>= 0.66 and 0.57) and regional rangeland productivity statistics of the Soil Survey Geographic Database (SSURGO) dataset. The Evaporative Stress Index (ESI), the 3- and 6-month Standardized Precipitation Index (SPI), and the U.S. Drought Monitor (USDM), which represented moisture conditions during May, June and July, explained the majority of the interannual biomass variability in this grassland system (three-month ESI explained roughly 72% of the interannual biomass variability). A new model was developed to use drought indices from early in the growing season to predict the total EB for the whole growing season. This unique approach considers only climate-related drought signal on productivity. The capability to estimate annual EB by the end of May will potentially enable land managers to make informed decisions about stocking rates, hay purchase needs, and other management issues early in the season, minimizing their potential drought losses.<span>&nbsp;</span><a onclick=\"if (!window.__cfRLUnblockHandlers) return false; ga('send', 'pageview', $(this).attr('href'));\" href=\"https://www.mdpi.com/2072-4292/11/18/2106/htm\" data-mce-href=\"https://www.mdpi.com/2072-4292/11/18/2106/htm\">View Full-Text</a></div>","language":"English","publisher":"MDPI","doi":"10.3390/rs11182106","usgsCitation":"Podebradska, M., Wylie, B., Hayes, M.J., Wardlow, B.D., Bathke, D.J., Bliss, N.B., and Dahal, D., 2019, Monitoring drought impact on annual forage production in semi-arid grasslands: A case study of Nebraska sandhills: Remote Sensing, v. 11, no. 18, 25 p., https://doi.org/10.3390/rs11182106.","productDescription":"25 p.","ipdsId":"IP-110482","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":459881,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11182106","text":"Publisher Index Page"},{"id":437348,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BOIO3D","text":"USGS data release","linkHelpText":"Time Series of expected Nebraska Sandhills livestock forage (2000 - 2016)"},{"id":379492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.216552734375,\n              40.60561205826018\n            ],\n            [\n              -97.525634765625,\n              40.60561205826018\n            ],\n            [\n              -97.525634765625,\n              42.98053954751642\n            ],\n            [\n              -103.216552734375,\n              42.98053954751642\n            ],\n            [\n              -103.216552734375,\n              40.60561205826018\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"18","noUsgsAuthors":false,"publicationDate":"2019-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Podebradska, Marketa 0000-0002-3121-4904","orcid":"https://orcid.org/0000-0002-3121-4904","contributorId":218698,"corporation":false,"usgs":false,"family":"Podebradska","given":"Marketa","email":"","affiliations":[{"id":33286,"text":"School of Natural Resources, University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":801946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":201929,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":801947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Michael J. 0000-0001-5006-166X","orcid":"https://orcid.org/0000-0001-5006-166X","contributorId":243284,"corporation":false,"usgs":false,"family":"Hayes","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":48673,"text":"School of Natural Resources, University of Nebraska-Lincoln, 811 Hardin Hall, 3310 Holdrege Street, Lincoln, Nebraska 68583-0988","active":true,"usgs":false}],"preferred":false,"id":801948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wardlow, Brian D. 0000-0002-4767-581X","orcid":"https://orcid.org/0000-0002-4767-581X","contributorId":191403,"corporation":false,"usgs":false,"family":"Wardlow","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":801949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bathke, Deborah J.","contributorId":197224,"corporation":false,"usgs":false,"family":"Bathke","given":"Deborah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":801950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bliss, Norman B. 0000-0003-2409-5211 bliss@usgs.gov","orcid":"https://orcid.org/0000-0003-2409-5211","contributorId":1921,"corporation":false,"usgs":true,"family":"Bliss","given":"Norman","email":"bliss@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":801951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":801952,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70207005,"text":"70207005 - 2019 - Influence of dissolved organic carbon on the acute toxicity of copper and zinc to White Sturgeon (Acipenser transmontanus) and a Cladoceran (Ceriodaphnia dubia)","interactions":[],"lastModifiedDate":"2019-12-03T08:14:52","indexId":"70207005","displayToPublicDate":"2019-09-09T08:13:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Influence of dissolved organic carbon on the acute toxicity of copper and zinc to White Sturgeon (Acipenser transmontanus) and a Cladoceran (Ceriodaphnia dubia)","docAbstract":"We conducted acute lethality tests with white sturgeon (Acipenser transmontanus) and Ceriodaphnia dubia exposed to copper and zinc at dissolved organic carbon concentrations ranging from 0.5 to 5.5 mg/L. Dissolved organic carbon had minimal effects on zinc toxicity but did have a protective effect on acute copper toxicity, which was equal to that predicted by the copper biotic ligand model (BLM). The BLM‐adjusted copper median effect concentrations for A. transmontanus ranged from 2.4 to 8.2 mg/L.","language":"English","publisher":"Wiley","doi":"10.1002/etc.4592","usgsCitation":"Ivey, C.D., Besser, J.M., Steevens, J.A., Walther, M., and Melton, V., 2019, Influence of dissolved organic carbon on the acute toxicity of copper and zinc to White Sturgeon (Acipenser transmontanus) and a Cladoceran (Ceriodaphnia dubia): Environmental Toxicology and Chemistry, v. 38, no. 12, p. 2682-2687, https://doi.org/10.1002/etc.4592.","productDescription":"6 p.","startPage":"2682","endPage":"2687","ipdsId":"IP-107987","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437349,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92U3R7G","text":"USGS data release","linkHelpText":"Influence of dissolved organic carbon on the acute toxicity of copper and zinc to white sturgeon (Acipenser transmontanus) and the cladoceran (Ceriodaphnia dubia)"},{"id":369850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"12","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":776506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":776507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":776508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walther, Michael 0000-0002-6506-561X mwalther@usgs.gov","orcid":"https://orcid.org/0000-0002-6506-561X","contributorId":220992,"corporation":false,"usgs":true,"family":"Walther","given":"Michael","email":"mwalther@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":776509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Melton, Vanessa","contributorId":220993,"corporation":false,"usgs":true,"family":"Melton","given":"Vanessa","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":776510,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70216116,"text":"70216116 - 2019 - Isolation by a hydroelectric dam induces minimal impacts on genetic diversity and population structure in six fish species","interactions":[],"lastModifiedDate":"2020-11-06T14:08:27.769553","indexId":"70216116","displayToPublicDate":"2019-09-09T08:01:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Isolation by a hydroelectric dam induces minimal impacts on genetic diversity and population structure in six fish species","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Reduced connectivity created by artificial barriers can influence the genetic integrity of isolated subpopulations by reducing local population sizes and altering patterns of gene flow. We investigated the genetic impacts of one such barrier, the Prairie du Sac dam, Wisconsin, USA, using microsatellite data from six fish species with varying life history traits sampled above and below the dam. Contrary to many past studies in other systems, we did not detect any significant differences in genetic diversity between populations found above and below the Prairie du Sac dam. Our results also revealed low genetic differentiation (<i>F</i><sub><i>ST</i></sub> = 0–0.008) between populations above and below the dam for all species. In fact, we found that more genetic variation was partitioned among sampling years than between above and below dam populations for all but one of the species. Results from coalescent simulations designed to model our study system indicated that the genetic impacts of the dam will likely be detectable approximately 40–60 generations after the dam was constructed, and that it is possible to largely mitigate these impacts with a fish passage strategy that facilitates a migration rate of ≥ 1% between above and below dam populations. In summary, our findings suggest the genetic impacts of dams can be relatively minimal on short time scales, and that fish passage strategies can significantly reduce genetic impacts if designed appropriately.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10592-019-01220-1","usgsCitation":"Ruzich, J., Turnquist, K., Nye, N., Rowe, D., and Larson, W., 2019, Isolation by a hydroelectric dam induces minimal impacts on genetic diversity and population structure in six fish species: Conservation Genetics, v. 20, p. 1421-1436, https://doi.org/10.1007/s10592-019-01220-1.","productDescription":"16 p.","startPage":"1421","endPage":"1436","ipdsId":"IP-100522","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":380254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Wisconsin River","geographicExtents":"{\n  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,{"id":70205625,"text":"70205625 - 2019 - The landscape of soil carbon data: Emerging questions, synergies and databases","interactions":[],"lastModifiedDate":"2019-10-09T10:15:22","indexId":"70205625","displayToPublicDate":"2019-09-08T10:59:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5866,"text":"Progress in Physical Geography: Earth and Environment","active":true,"publicationSubtype":{"id":10}},"title":"The landscape of soil carbon data: Emerging questions, synergies and databases","docAbstract":"<p><span>Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.</span></p>","language":"English","publisher":"Sage","doi":"10.1177/0309133319873309","usgsCitation":"Avni Malhotra, Katherine Todd-Brown, Luke Nave, Batjes, N., Holmquist, J., Alison Hoyt, Colleen Iversen, Jackson, R.B., Lathja, K., Lawrence, C.R., Olga Vinduśková, Wieder, W., Williams, M., Gustaf Hugelias, and Harden, J., 2019, The landscape of soil carbon data: Emerging questions, synergies and databases: Progress in Physical Geography: Earth and Environment, v. 43, no. 5, p. 707-719, https://doi.org/10.1177/0309133319873309.","productDescription":"13 p.","startPage":"707","endPage":"719","ipdsId":"IP-106672","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":459890,"rank":0,"type":{"id":41,"text":"Open Access 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Nave","contributorId":219294,"corporation":false,"usgs":false,"family":"Luke Nave","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":771922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batjes, Niels","contributorId":219295,"corporation":false,"usgs":false,"family":"Batjes","given":"Niels","email":"","affiliations":[{"id":39988,"text":"ISRIC World Soil Information","active":true,"usgs":false}],"preferred":false,"id":771923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holmquist, James","contributorId":217021,"corporation":false,"usgs":false,"family":"Holmquist","given":"James","email":"","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":771924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alison Hoyt","contributorId":219296,"corporation":false,"usgs":false,"family":"Alison 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