{"pageNumber":"212","pageRowStart":"5275","pageSize":"25","recordCount":40783,"records":[{"id":70223174,"text":"sir20215048 - 2021 - Strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona","interactions":[],"lastModifiedDate":"2021-09-14T19:41:55.81256","indexId":"sir20215048","displayToPublicDate":"2021-08-18T08:08:16","publicationYear":"2021","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":"2021-5048","displayTitle":"Strandlines from Large Floods on the Colorado River in Grand Canyon National Park, Arizona","title":"Strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona","docAbstract":"<p>Strandlines of peak-stage indicators (such as driftwood logs, woody debris, and trash) provide valuable data for understanding the maximum stage and extent of inundation during floods. A series of seven strandlines have been preserved along the Colorado River in Grand Canyon National Park, Arizona, USA. A survey and analysis of these strandlines was completed from the Colorado River at Lees Ferry, Ariz., gaging station to the Colorado River near Grand Canyon, Ariz., gaging station. Owing to the longitudinally discontinuous nature of the strandlines, several lines of evidence were used to determine the year of the flood associated with each strandline segment. This evidence included strandline relative vertical position, degree of peak-stage indicator weathering, datable trash drift, and map-view location. The seven distinct strandlines identified were deposited during floods with the following peak discharges (in cubic feet per second [ft<sup>3</sup>/s]) at the Colorado River at Lees Ferry, Ariz., gaging station (year of flood in parentheses): 210,000 ft<sup>3</sup>/s (1884), 170,000 ft<sup>3</sup>/s (1921), 125,000 ft<sup>3</sup>/s (1957), 108,000 ft<sup>3</sup>/s (1958), 97,000 ft<sup>3</sup>/s (1983), 52,500 ft<sup>3</sup>/s (1986), and 45,000 ft<sup>3</sup>/s (multiple events between 1996 and 2012). Stage-discharge relations were developed in areas where all, or most of the strandlines were present, and were compared to predicted stage-discharge relations from a one-dimensional flow model. River width exerted a strong control on these relations, with much greater stage change occurring for a given discharge change in narrower bedrock-dominated reaches than in wider reaches with more extensive channel-margin alluvium. This comprehensive dataset allows for the verification of model-predicted flood stage along the Colorado River in Grand Canyon National Park.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215048","usgsCitation":"Sabol, T.A., Griffiths, R.E., Topping, D.J., Mueller, E.R., Tusso, R.B., and Hazel, J.E., Jr., 2021, Strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona: U.S. Geological Survey Scientific Investigations Report 2021-5048, 41 p., https://doi.org/10.3133/sir20215048.","productDescription":"Report: vi, 41 p.; Data Release; Version History","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-118687","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":388103,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GIQ9ZN","linkHelpText":"Surveyed peak-stage elevations, coordinates, and indicator data of strandlines from large floods on the Colorado River in Grand Canyon National Park, Arizona"},{"id":388754,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5048/versionhist.txt","size":"5 KB","linkFileType":{"id":2,"text":"txt"}},{"id":387949,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5048/covrthb.jpg"},{"id":388753,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5048/sir20215048.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.027099609375,\n              35.78662688467009\n            ],\n            [\n              -111.37390136718749,\n              35.78662688467009\n            ],\n            [\n              -111.37390136718749,\n              36.98500309285596\n            ],\n            [\n              -114.027099609375,\n              36.98500309285596\n            ],\n            [\n              -114.027099609375,\n              35.78662688467009\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<div class=\"street-block\"><div class=\"thoroughfare\"><a href=\"https://www.usgs.gov/centers/sbsc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/sbsc\">Southwest Biological Science Center</a></div><div class=\"thoroughfare\"><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a></div><div class=\"thoroughfare\">2255 N. Gemini Drive</div></div><div class=\"addressfield-container-inline locality-block country-US\"><span class=\"locality\">Flagstaff</span>,&nbsp;<span class=\"state\">AZ</span>&nbsp;<span class=\"postal-code\">86001</span></div>","tableOfContents":"<ul><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Purpose and Scope&nbsp;&nbsp;</li><li>Peak-Stage Indicators: Types and Preservation&nbsp;&nbsp;</li><li>Study Area&nbsp;&nbsp;</li><li>Expected Strandline Occurrence Based on Gaging Record&nbsp;&nbsp;</li><li>Methods&nbsp;&nbsp;</li><li>Results&nbsp;&nbsp;</li><li>Stage-Discharge Relations&nbsp;&nbsp;</li><li>Discussion&nbsp;&nbsp;</li><li>Conclusions&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Peak-Stage Indicator Data Collected Downstream from the Colorado River Near Grand Canyon, Arizona, Gaging Station&nbsp;&nbsp;</li><li>Appendix 2. Comparison of Stage-Discharge Relations Generated from the Strandlines with Those Generated by the Model of Magirl and Others (2008)</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-08-18","revisedDate":"2021-09-14","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Sabol, Thomas A. 0000-0002-4299-2285 tsabol@usgs.gov","orcid":"https://orcid.org/0000-0002-4299-2285","contributorId":3403,"corporation":false,"usgs":true,"family":"Sabol","given":"Thomas","email":"tsabol@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffiths, Ronald E. 0000-0003-3620-2926 rgriffiths@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-2926","contributorId":162,"corporation":false,"usgs":true,"family":"Griffiths","given":"Ronald","email":"rgriffiths@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821234,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":197244,"corporation":false,"usgs":true,"family":"Topping","given":"David J.","email":"dtopping@usgs.gov","affiliations":[],"preferred":true,"id":821235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Erich R. 0000-0001-8202-154X emueller@usgs.gov","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":4930,"corporation":false,"usgs":true,"family":"Mueller","given":"Erich","email":"emueller@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821236,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tusso, Robert B. 0000-0001-7541-3713 rtusso@usgs.gov","orcid":"https://orcid.org/0000-0001-7541-3713","contributorId":4079,"corporation":false,"usgs":true,"family":"Tusso","given":"Robert","email":"rtusso@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821237,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hazel, Joseph E. Jr.","contributorId":19500,"corporation":false,"usgs":true,"family":"Hazel","given":"Joseph","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":821238,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70224305,"text":"70224305 - 2021 - Urban heat island and its regional impacts using remotely sensed thermal data – A review of recent developments and methodology","interactions":[],"lastModifiedDate":"2021-09-21T12:54:25.098016","indexId":"70224305","displayToPublicDate":"2021-08-18T07:53:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2596,"text":"Land","active":true,"publicationSubtype":{"id":10}},"title":"Urban heat island and its regional impacts using remotely sensed thermal data – A review of recent developments and methodology","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Many novel research algorithms have been developed to analyze urban heat island (UHI) and UHI regional impacts (UHIRIP) with remotely sensed thermal data tables. We present a comprehensive review of some important aspects of UHI and UHIRIP studies that use remotely sensed thermal data, including concepts, datasets, methodologies, and applications. We focus on reviewing progress on multi-sensor image selection, preprocessing, computing, gap filling, image fusion, deep learning, and developing new metrics. This literature review shows that new satellite sensors and valuable methods have been developed for calculating land surface temperature (LST) and UHI intensity, and for assessing UHIRIP. Additionally, some of the limitations of using remotely sensed data to analyze the LST, UHI, and UHI intensity are discussed. Finally, we review a variety of applications in UHI and UHIRIP analyses. The assimilation of time-series remotely sensed data with the application of data fusion, gap filling models, and deep learning using the Google Cloud platform and Google Earth Engine platform also has the potential to improve the estimation accuracy of change patterns of UHI and UHIRIP over long time periods.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/land10080867","usgsCitation":"Shi, H., Xian, G.Z., Auch, R.F., Gallo, K., and Zhou, Q., 2021, Urban heat island and its regional impacts using remotely sensed thermal data – A review of recent developments and methodology: Land, v. 10, no. 8, 867, 30 p., https://doi.org/10.3390/land10080867.","productDescription":"867, 30 p.","ipdsId":"IP-119452","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":451136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land10080867","text":"Publisher Index Page"},{"id":389539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Hua 0000-0001-7013-1565","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":192768,"corporation":false,"usgs":false,"family":"Shi","given":"Hua","affiliations":[],"preferred":false,"id":823653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xian, George Z. 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":238919,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":823654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Auch, Roger F. 0000-0002-5382-5044 auch@usgs.gov","orcid":"https://orcid.org/0000-0002-5382-5044","contributorId":667,"corporation":false,"usgs":true,"family":"Auch","given":"Roger","email":"auch@usgs.gov","middleInitial":"F.","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":823655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gallo, Kevin 0000-0001-9162-5011","orcid":"https://orcid.org/0000-0001-9162-5011","contributorId":257326,"corporation":false,"usgs":false,"family":"Gallo","given":"Kevin","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":823656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhou, Qiang 0000-0002-1282-8177","orcid":"https://orcid.org/0000-0002-1282-8177","contributorId":265886,"corporation":false,"usgs":false,"family":"Zhou","given":"Qiang","affiliations":[{"id":54817,"text":"AFDS, contractor to U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":823657,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70224253,"text":"70224253 - 2021 - Adaptive two-stage inverse sampling design to estimate density, abundance, and occupancy of rare and clustered populations","interactions":[],"lastModifiedDate":"2021-09-16T12:32:41.667684","indexId":"70224253","displayToPublicDate":"2021-08-18T07:31:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive two-stage inverse sampling design to estimate density, abundance, and occupancy of rare and clustered populations","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Sampling rare and clustered populations is challenging because of the effort required to find rare units. Heuristically, a practitioner would prefer to discontinue sampling in areas where rare units of interest are apparently extremely sparse or absent. We take advantage of the characteristics of inverse sampling to adaptively inform practitioners when it is efficient to move on to sample new areas. We introduce Adaptive Two-stage Inverse Sampling (ATIS), which is designed to leave a selected area after observation of an a priori number of only non-rare units and to continue sampling in the area when rare units are observed. ATIS is efficient in many cases and yields more rare units than conventional sampling for a rare and clustered population. We derive unbiased estimators of population total and variance. We also introduce an easy-to-compute estimator, which is nearly as efficient as the unbiased estimator. A simulation study on a rare plant population of buttercups (<i>Ranunculus</i>) shows that ATIS even with the easy-to-compute estimator is more efficient than its conventional sampling counterparts and is more efficient than Two-stage Adaptive Cluster Sampling (TACS) for small and moderate final sample sizes. Additional simulations reveal that ATIS is efficient for binary data (e.g., presence or absence) whereas TACS is inefficient for binary data. The overall results indicate that ATIS is consistently efficient compared to conventional sampling and to adaptive cluster sampling in some important cases.</p></div></div>","language":"English","publisher":"PLoS One","doi":"10.1371/journal.pone.0255256","usgsCitation":"Salehi, M., and Smith, D.R., 2021, Adaptive two-stage inverse sampling design to estimate density, abundance, and occupancy of rare and clustered populations: PLoS ONE, v. 16, no. 8, e0255256, 18 p., https://doi.org/10.1371/journal.pone.0255256.","productDescription":"e0255256, 18 p.","ipdsId":"IP-131567","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0255256","text":"Publisher Index Page"},{"id":389333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Salehi, Mohammad","contributorId":265780,"corporation":false,"usgs":false,"family":"Salehi","given":"Mohammad","email":"","affiliations":[{"id":54794,"text":"Qatar University","active":true,"usgs":false}],"preferred":false,"id":823361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":823362,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226201,"text":"70226201 - 2021 - Response to “Connectivity and pore accessibility in models of soil carbon cycling”","interactions":[],"lastModifiedDate":"2021-11-16T12:35:56.788262","indexId":"70226201","displayToPublicDate":"2021-08-18T06:32:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Response to “Connectivity and pore accessibility in models of soil carbon cycling”","docAbstract":"<div class=\"article-section__content en short\"><p>Here we respond to Baveye and colleagues' recent critique of our PROMISE model, describing how this new framework significantly advances our understanding of soil spatial heterogeneity and its influence on organic matter transformations.</p></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15850","usgsCitation":"Waring, B.G., Sulman, B.N., Reed, S., Smith, A.P., Averill, C., Creamer, C., Cusack, D.F., Hall, S.J., Jastrow, J.D., Jilling, A., Kemner, K.M., Kleber, M., Liu, X.A., Pett-Ridge, J., and Schulz, M.S., 2021, Response to “Connectivity and pore accessibility in models of soil carbon cycling”: Global Change Biology, v. 27, no. 21, p. e15-e16, https://doi.org/10.1111/gcb.15850.","productDescription":"2 p.","startPage":"e15","endPage":"e16","ipdsId":"IP-132355","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":451147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15850","text":"Publisher Index Page"},{"id":391730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"21","noUsgsAuthors":false,"publicationDate":"2021-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Waring, Bonnie G. 0000-0002-8457-5164","orcid":"https://orcid.org/0000-0002-8457-5164","contributorId":245284,"corporation":false,"usgs":false,"family":"Waring","given":"Bonnie","email":"","middleInitial":"G.","affiliations":[{"id":49130,"text":"Utah State University, Department of Biology and Ecology Center, Logan UT 84322","active":true,"usgs":false}],"preferred":false,"id":826846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":826847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":826848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, A. Peyton","contributorId":245298,"corporation":false,"usgs":false,"family":"Smith","given":"A.","email":"","middleInitial":"Peyton","affiliations":[],"preferred":false,"id":826849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Averill, Colin","contributorId":245299,"corporation":false,"usgs":false,"family":"Averill","given":"Colin","email":"","affiliations":[],"preferred":false,"id":826850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creamer, Courtney Ann","contributorId":268877,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney Ann","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":826851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cusack, Daniela F. 0000-0003-4681-7449","orcid":"https://orcid.org/0000-0003-4681-7449","contributorId":245300,"corporation":false,"usgs":false,"family":"Cusack","given":"Daniela","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":826852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, Steven J. 0000-0002-7841-2019","orcid":"https://orcid.org/0000-0002-7841-2019","contributorId":244336,"corporation":false,"usgs":false,"family":"Hall","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":826853,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jastrow, Julie D.","contributorId":254970,"corporation":false,"usgs":false,"family":"Jastrow","given":"Julie","email":"","middleInitial":"D.","affiliations":[{"id":51371,"text":"Environmental Science Division, Argonne National Laboratory, Lemont IL 60439","active":true,"usgs":false}],"preferred":false,"id":826854,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jilling, Andrea","contributorId":254971,"corporation":false,"usgs":false,"family":"Jilling","given":"Andrea","email":"","affiliations":[{"id":51372,"text":"Department of Plant and Soil Sciences, Oklahoma State University, Stillwater OK 74078","active":true,"usgs":false}],"preferred":false,"id":826855,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kemner, Kenneth M.","contributorId":245301,"corporation":false,"usgs":false,"family":"Kemner","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":826856,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kleber, Markus","contributorId":254972,"corporation":false,"usgs":false,"family":"Kleber","given":"Markus","affiliations":[{"id":51374,"text":"Department of Crop and Soil Science, Oregon State University, Corvallis OR 97331","active":true,"usgs":false}],"preferred":false,"id":826857,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Liu, Xiao-Jun Allen","contributorId":245302,"corporation":false,"usgs":false,"family":"Liu","given":"Xiao-Jun","email":"","middleInitial":"Allen","affiliations":[],"preferred":false,"id":826858,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pett-Ridge, Jennifer","contributorId":254974,"corporation":false,"usgs":false,"family":"Pett-Ridge","given":"Jennifer","affiliations":[{"id":51376,"text":"Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore CA 94551","active":true,"usgs":false}],"preferred":false,"id":826859,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":268879,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie","email":"mschulz@usgs.gov","middleInitial":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":826860,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70223173,"text":"ofr20211076 - 2021 - An integrated population model for southern sea otters","interactions":[],"lastModifiedDate":"2021-08-17T12:12:45.270165","indexId":"ofr20211076","displayToPublicDate":"2021-08-16T13:30:04","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1076","displayTitle":"An Integrated Population Model for Southern Sea Otters","title":"An integrated population model for southern sea otters","docAbstract":"<p>Southern sea otters (<i>Enhydra lutris nereis</i>) have recovered slowly from their near extinction a century ago, and their continued recovery has been challenged by multiple natural and anthropogenic factors. Development of an integrated population model (IPM) for southern sea otters has been identified as a management priority, to help in evaluating the relative impacts of known threats and guide best management options for species recovery. An IPM represents an analytical modeling framework where various types of data relevant to animal health, population trends, and survival can be evaluated collectively to project future population dynamics under different resource management scenarios. Here, we describe the development of a spatially explicit IPM for southern sea otters that is fit by using Bayesian methods to multiple datasets including a time series of range-wide survey counts, estimated survival rates of tagged animals from telemetry-based population studies, and cause-of-death data from comprehensive necropsies of beach-cast carcasses. The core of the model is a stage-structured matrix, in which survival rates for a given life history stage, year, and location are computed as the outcome of multiple ‘competing risks,’ or hazards, allowing for spatiotemporal variation in each hazard, density-dependence, and stochasticity. The parameterized IPM was used to (1) examine how age and sex-specific hazards vary over space and time, (2) gain insights into density-dependent variation in specific hazards, (3) assess population-level effects of known mortality hazards in the past and in future projections, and (4) evaluate the relative benefits of various potential management actions to address these hazards.</p><p>Our results indicated that different types of hazards have variable impacts at different life history stages of sea otters; for example, shark-bite mortality had a strong impact on mortality of subadult females but relatively low impacts on aged adult female survival, whereas End Lactation Syndrome showed just the opposite age-based pattern. There also was spatial and temporal variation in exposure to different hazards; for example, shark-bite mortality generally was highest at the north and south ends of the sea otter range, End Lactation Syndrome and cardiac disease were highest in the center part of the range, and harmful algal bloom intoxication and protozoal infection mortalities were highest around Morro Bay. The relative impacts of hazards depended on population density; for example, shark-bite mortality had the greatest effect on male survival when population abundance was low, but as densities increased the impacts of cardiac disease (for aged adults) and acanthocephalan peritonitis (for subadults) exceeded the effects of shark-bite mortality. Sensitivity analyses showed that modifying certain hazard rates can have substantial impacts on future population growth; for example, if the shark-bite hazard rate were to decrease by 20 percent, projected abundance after 50 years is predicted to be 18-percent higher, on average, than under baseline conditions. We used the IPM to evaluate the possible impacts of a potential management action: the reintroduction of sea otters to currently unoccupied parts of their historical range. We found that there were large increases in expected growth potential associated with reintroduction programs to various locations to the north and south of the currently occupied range, although a reintroduction to San Francisco Bay was projected to have the greatest potential impacts on future population growth.</p><p>The IPM for southern sea otters presented here provides resource managers with a useful tool for evaluating the impacts of specific hazards, forecasting future population dynamics and range expansion, and evaluating alternative management scenarios.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211076","programNote":"Wildlife Program","usgsCitation":"Tinker, M.T., Carswell, L.P., Tomoleoni, J.A., Hatfield, B.B., Harris, M.D., Miller, M.A., Moriarty, M.E., Johnson, C.K., Young, C., Henkel, L.A., Staedler, M.M., Miles, A.K., and Yee, J.L., 2021, An integrated population model for southern sea otters: U.S. Geological Survey Open-File Report 2021–1076, 50 p., https://doi.org/10.3133/ofr20211076.","productDescription":"vii, 50 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-126237","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":387937,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1076/images"},{"id":387936,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1076/ofr20211076.xml"},{"id":387935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1076/ofr20211076.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1076/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.23388671874999,\n              37.125286284966805\n            ],\n            [\n              -121.59667968749999,\n              37.37015718405753\n            ],\n            [\n              -121.55273437499999,\n              37.666429212090605\n            ],\n            [\n              -122.1240234375,\n              38.61687046392973\n            ],\n            [\n              -122.84912109375,\n              39.30029918615029\n            ],\n            [\n              -123.37646484374999,\n              40.329795743702064\n            ],\n            [\n              -123.37646484374999,\n              40.84706035607122\n            ],\n            [\n              -123.3544921875,\n              41.705728515237524\n            ],\n            [\n              -123.22265625000001,\n              42.00032514831621\n            ],\n            [\n              -124.49707031249999,\n              42.01665183556825\n            ],\n            [\n              -124.98046874999999,\n              40.94671366508002\n            ],\n            [\n              -124.67285156250001,\n              39.90973623453719\n            ],\n            [\n              -124.18945312500001,\n              38.92522904714054\n            ],\n            [\n              -123.3544921875,\n              37.579412513438385\n            ],\n            [\n              -122.9150390625,\n              37.23032838760387\n            ],\n            [\n              -122.23388671874999,\n              37.125286284966805\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,<br><a href=\"https://www.usgs.gov/%20centers/%20werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/ centers/ werc\">Western Ecological Research Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>References Cited</li><li>Appendix 1. Supplementary Tables and Figures</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-08-16","noUsgsAuthors":false,"publicationDate":"2021-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carswell, Lilian P.","contributorId":221789,"corporation":false,"usgs":false,"family":"Carswell","given":"Lilian P.","affiliations":[{"id":40429,"text":"USFWS - Ventura FWO","active":true,"usgs":false}],"preferred":false,"id":821220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomoleoni, Joseph A. 0000-0001-6980-251X jtomoleoni@usgs.gov","orcid":"https://orcid.org/0000-0001-6980-251X","contributorId":167551,"corporation":false,"usgs":true,"family":"Tomoleoni","given":"Joseph","email":"jtomoleoni@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatfield, Brian B. 0000-0003-1432-2660 brian_hatfield@usgs.gov","orcid":"https://orcid.org/0000-0003-1432-2660","contributorId":127457,"corporation":false,"usgs":true,"family":"Hatfield","given":"Brian","email":"brian_hatfield@usgs.gov","middleInitial":"B.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":821222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, Michael D.","contributorId":127460,"corporation":false,"usgs":false,"family":"Harris","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":821223,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Melissa A.","contributorId":57701,"corporation":false,"usgs":false,"family":"Miller","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":39007,"text":"CA Dept of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":821224,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moriarty, Megan E.","contributorId":247708,"corporation":false,"usgs":true,"family":"Moriarty","given":"Megan","email":"","middleInitial":"E.","affiliations":[{"id":49627,"text":"Karen C. Drayer Wildlife Health Center and EpiCenter for Disease Dynamics, One Health Institute, University of California Davis School of Veterinary Medicine, 1089 Veterinary Medicine Dr. VM3B, Davis, CA, United States","active":true,"usgs":false}],"preferred":true,"id":821225,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Christine K.","contributorId":23771,"corporation":false,"usgs":false,"family":"Johnson","given":"Christine K.","affiliations":[],"preferred":false,"id":821226,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Young, Colleen","contributorId":179103,"corporation":false,"usgs":true,"family":"Young","given":"Colleen","email":"","affiliations":[],"preferred":true,"id":821227,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Henkel, Laird A.","contributorId":207274,"corporation":false,"usgs":false,"family":"Henkel","given":"Laird","email":"","middleInitial":"A.","affiliations":[{"id":37508,"text":"California Department of Fish and Wildlife, Santa Cruz, CA","active":true,"usgs":false}],"preferred":false,"id":821228,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Staedler, Michelle M. 0000-0002-1101-6580","orcid":"https://orcid.org/0000-0002-1101-6580","contributorId":222317,"corporation":false,"usgs":true,"family":"Staedler","given":"Michelle","email":"","middleInitial":"M.","affiliations":[{"id":6953,"text":"Monterey Bay Aquarium","active":true,"usgs":false}],"preferred":true,"id":821229,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Miles, A. Keith 0000-0002-3108-808X keith_miles@usgs.gov","orcid":"https://orcid.org/0000-0002-3108-808X","contributorId":196,"corporation":false,"usgs":true,"family":"Miles","given":"A.","email":"keith_miles@usgs.gov","middleInitial":"Keith","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821230,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821231,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70224933,"text":"70224933 - 2021 - Multiple coping strategies maintain stability of a small mammal population in a resource-restricted environment","interactions":[],"lastModifiedDate":"2021-10-06T12:31:28.063054","indexId":"70224933","displayToPublicDate":"2021-08-16T07:26:08","publicationYear":"2021","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":"Multiple coping strategies maintain stability of a small mammal population in a resource-restricted environment","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>In semi-arid environments, aperiodic rainfall pulses determine plant production and resource availability for higher trophic levels, creating strong bottom-up regulation. The influence of climatic factors on population vital rates often shapes the dynamics of small mammal populations in such resource-restricted environments. Using a 21-year biannual capture–recapture dataset (1993 to 2014), we examined the impacts of climatic factors on the population dynamics of the brush mouse (<i>Peromyscus boylii</i>) in semi-arid oak woodland of coastal-central California. We applied Pradel's temporal symmetry model to estimate capture probability (<i>p</i>), apparent survival (<i>φ</i>), recruitment (<i>f</i>), and realized population growth rate (<i>λ</i>) of the brush mouse and examined the effects of temperature, rainfall, and El Niño on these demographic parameters. The population was stable during the study period with a monthly realized population growth rate of 0.993 ±<span>&nbsp;</span><i>SE</i><span>&nbsp;</span>0.032, but growth varied over time from 0.680&nbsp;±&nbsp;0.054 to 1.450&nbsp;±&nbsp;0.083. Monthly survival estimates averaged 0.789&nbsp;±&nbsp;0.005 and monthly recruitment estimates averaged 0.175&nbsp;±&nbsp;0.038. Survival probability and realized population growth rate were positively correlated with rainfall and negatively correlated with temperature. In contrast, recruitment was negatively correlated with rainfall and positively correlated with temperature. Brush mice maintained their population through multiple coping strategies, with high recruitment during warmer and drier periods and higher survival during cooler and wetter conditions. Although climatic change in coastal-central California will likely favor recruitment over survival, varying strategies may serve as a mechanism by which brush mice maintain resilience in the face of climate change. Our results indicate that rainfall and temperature are both important drivers of brush mouse population dynamics and will play a significant role in predicting the future viability of brush mice under a changing climate.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7997","usgsCitation":"Polyakov, A., Tietje, W., Srivathsa, A., Rolland, V., Hines, J.E., and Oli, M.K., 2021, Multiple coping strategies maintain stability of a small mammal population in a resource-restricted environment: Ecology and Evolution, v. 11, no. 18, p. 12529-12541, https://doi.org/10.1002/ece3.7997.","productDescription":"13 p.","startPage":"12529","endPage":"12541","ipdsId":"IP-115578","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451160,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7997","text":"External Repository"},{"id":390247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Camp Roberts","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.87570190429688,\n              35.70358951560828\n            ],\n            [\n              -120.66902160644531,\n              35.71083783530009\n            ],\n            [\n              -120.69786071777344,\n              35.8389682993045\n            ],\n            [\n              -120.904541015625,\n              35.83451505415075\n            ],\n            [\n              -120.87570190429688,\n              35.70358951560828\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"18","noUsgsAuthors":false,"publicationDate":"2021-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Polyakov, Anne Y","contributorId":267223,"corporation":false,"usgs":false,"family":"Polyakov","given":"Anne Y","affiliations":[{"id":55449,"text":"University of California, Department of Environmental Science, Policy, and Management, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":824718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tietje, William D","contributorId":267224,"corporation":false,"usgs":false,"family":"Tietje","given":"William D","affiliations":[{"id":55449,"text":"University of California, Department of Environmental Science, Policy, and Management, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":824719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Srivathsa, Arjun","contributorId":267225,"corporation":false,"usgs":false,"family":"Srivathsa","given":"Arjun","email":"","affiliations":[{"id":55450,"text":"4Department of Wildlife Ecology and Conservation, Univ. of FL","active":true,"usgs":false}],"preferred":false,"id":824720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rolland, Virginie","contributorId":267226,"corporation":false,"usgs":false,"family":"Rolland","given":"Virginie","email":"","affiliations":[{"id":55451,"text":"2Department of Biology, Arkansas State University","active":true,"usgs":false}],"preferred":false,"id":824721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oli, Madan K. 0000-0001-6944-0061","orcid":"https://orcid.org/0000-0001-6944-0061","contributorId":201302,"corporation":false,"usgs":false,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":824723,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70225600,"text":"70225600 - 2021 - Climate change effects on North American fish and fisheries to inform adaptation strategies","interactions":[],"lastModifiedDate":"2021-10-27T12:25:27.099518","indexId":"70225600","displayToPublicDate":"2021-08-16T07:22:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5686,"text":"Fisheries Magazine","active":true,"publicationSubtype":{"id":10}},"title":"Climate change effects on North American fish and fisheries to inform adaptation strategies","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Climate change is a global persistent threat to fish and fish habitats throughout North America. Climate-induced modification of environmental regimes, including changes in streamflow, water temperature, salinity, storm surges, and habitat connectivity can change fish physiology, disrupt spawning cues, cause fish extinctions and invasions, and alter fish community structure. Reducing greenhouse emissions remains the primary mechanism to slow the pace of climate change, but local and regional management agencies and stakeholders have developed an arsenal of adaptation strategies to help partially mitigate the effects of climate change on fish. We summarize common stressors posed by climate change in North America, including (1) increased water temperature, (2) changes in precipitation, (3) sea level rise, and (4) ocean acidification, and present potential adaptation strategies that fishery professionals may apply to help vulnerable fish and fisheries cope with a changing climate. 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These strategies provide opportunities for managers to mitigate the effects of climate change on fish and fish habitat while needed global policies to reduce greenhouse gas emissions emerge, which may offer more lasting solutions.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/fsh.10668","usgsCitation":"Paukert, C.P., Olden, J., Lynch, A., Brashears, D., Chambers, R.C., Chu, C., Daly, M., Dibble, K.L., Falke, J.A., Issak, D., Jacobson, P.C., Jensen, O.P., and Munroe, D., 2021, Climate change effects on North American fish and fisheries to inform adaptation strategies: Fisheries Magazine, v. 9, no. 46, p. 449-464, https://doi.org/10.1002/fsh.10668.","productDescription":"16 p.","startPage":"449","endPage":"464","ipdsId":"IP-125386","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":451161,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/fsh.10668","text":"External Repository"},{"id":391006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.1015625,\n              7.36246686553575\n            ],\n            [\n              -81.9140625,\n              17.97873309555617\n            ],\n            [\n              -78.3984375,\n              24.5271348225978\n            ],\n            [\n              -56.6015625,\n              45.089035564831036\n            ],\n            [\n              -54.140625,\n              53.9560855309879\n            ],\n            [\n              -62.57812500000001,\n              64.01449619484472\n            ],\n            [\n              -94.21875,\n              71.30079291637452\n            ],\n            [\n              -135,\n              73.52839948765174\n            ],\n            [\n              -163.4765625,\n              70.72897946208789\n            ],\n            [\n              -168.046875,\n              65.5129625532949\n            ],\n            [\n              -163.4765625,\n              58.07787626787517\n            ],\n            [\n              -157.1484375,\n              54.77534585936447\n            ],\n            [\n              -138.1640625,\n              51.39920565355378\n            ],\n            [\n              -128.32031249999997,\n              41.244772343082076\n            ],\n            [\n              -114.60937499999999,\n              23.241346102386135\n            ],\n            [\n              -95.97656249999999,\n              11.178401873711785\n            ],\n            [\n              -82.96875,\n              5.61598581915534\n            ],\n            [\n              -79.1015625,\n              7.36246686553575\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"46","noUsgsAuthors":false,"publicationDate":"2021-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":825786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":825787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lynch, Abigail 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":216203,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":825788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brashears, Dave","contributorId":268062,"corporation":false,"usgs":false,"family":"Brashears","given":"Dave","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":825789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chambers, R. Christopher","contributorId":268063,"corporation":false,"usgs":false,"family":"Chambers","given":"R.","email":"","middleInitial":"Christopher","affiliations":[{"id":38698,"text":"NOAA Fisheries","active":true,"usgs":false}],"preferred":false,"id":825790,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chu, Cindy","contributorId":176496,"corporation":false,"usgs":false,"family":"Chu","given":"Cindy","email":"","affiliations":[],"preferred":false,"id":825791,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daly, Margaret","contributorId":268065,"corporation":false,"usgs":false,"family":"Daly","given":"Margaret","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":825792,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":825793,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":825794,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Issak, Dan","contributorId":268067,"corporation":false,"usgs":false,"family":"Issak","given":"Dan","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":825795,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jacobson, Peter C.","contributorId":177331,"corporation":false,"usgs":false,"family":"Jacobson","given":"Peter","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":825796,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jensen, Olaf P.","contributorId":92159,"corporation":false,"usgs":false,"family":"Jensen","given":"Olaf","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":825797,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Munroe, Daphne","contributorId":268069,"corporation":false,"usgs":false,"family":"Munroe","given":"Daphne","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":825798,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70224336,"text":"70224336 - 2021 - PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data","interactions":[],"lastModifiedDate":"2021-09-23T12:19:33.804007","indexId":"70224336","displayToPublicDate":"2021-08-16T07:16:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0035\">Phenology<span>&nbsp;is the study of recurring plant and animal life-cycle stages which can be observed across spatial and temporal scales that span orders of magnitude (e.g., organisms to landscapes). The variety of scales at which phenological processes operate is reflected in the range of methods for collecting phenologically relevant data, and the programs focused on these collections. Consideration of the scale at which phenological observations are made, and the platform used for observation, is critical for the interpretation of phenological data and the application of these data to both research questions and land management objectives. However, there is currently little capacity to facilitate access, integration and analysis of cross-scale, multi-platform phenological data. This paper reports on a new suite of software and analysis tools – the “Pheno-Synthesis Software Suite,” or PS3 – to facilitate integration and analysis of phenological and ancillary data, enabling investigation and interpretation of phenological processes at scales ranging from organisms to landscapes and from days to decades. We use PS3 to investigate phenological processes in a semi-aride, mixed shrub-grass ecosystem, and find that the apparent importance of seasonal precipitation to vegetation activity (i.e., “greenness”) is affected by the scale and platform of observation. We end by describing potential applications of PS3 to phenological modeling and forecasting, understanding patterns and drivers of phenological activity in real-world ecosystems, and supporting agricultural and&nbsp;natural resource management&nbsp;and decision-making.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2021.101400","usgsCitation":"Morisette, J., Duffy, K.A., Weltzin, J., Browning, D.M., Marsh, L.R., Friesz, A., Zachmann, L.J., Enns, K., Landau, V.A., Gerst, K.L., Crimmins, T.M., Jones, K.D., Chang, T., Miller, B.W., Maiersperger, T., and Richardson, A.D., 2021, PS3: The Pheno-Synthesis software suite for integration and analysis of multi-scale, multi-platform phenological data: Ecological Informatics, v. 65, 101400, 11 p., https://doi.org/10.1016/j.ecoinf.2021.101400.","productDescription":"101400, 11 p.","ipdsId":"IP-129986","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2021.101400","text":"Publisher Index Page"},{"id":389635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Morisette, Jeffrey 0000-0002-0483-0082","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":212187,"corporation":false,"usgs":false,"family":"Morisette","given":"Jeffrey","affiliations":[{"id":38451,"text":"U.S. Department of the Interior, National Invasive Species Council Secretariat","active":true,"usgs":false}],"preferred":false,"id":823798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffy, Katharyn A 0000-0001-6108-7718","orcid":"https://orcid.org/0000-0001-6108-7718","contributorId":265935,"corporation":false,"usgs":false,"family":"Duffy","given":"Katharyn","email":"","middleInitial":"A","affiliations":[{"id":54828,"text":"School of Informatics, Computing, and Cyber Systems Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":823799,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weltzin, Jake 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":196323,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake","email":"jweltzin@usgs.gov","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":433,"text":"National Phenology Network","active":true,"usgs":true}],"preferred":true,"id":823800,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Browning, Dawn M 0000-0002-1252-6013","orcid":"https://orcid.org/0000-0002-1252-6013","contributorId":265936,"corporation":false,"usgs":false,"family":"Browning","given":"Dawn","email":"","middleInitial":"M","affiliations":[{"id":54829,"text":"U.S. Department of Agriculture – Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":823801,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marsh, Lee R 0000-0003-4411-7123","orcid":"https://orcid.org/0000-0003-4411-7123","contributorId":265937,"corporation":false,"usgs":false,"family":"Marsh","given":"Lee","email":"","middleInitial":"R","affiliations":[{"id":54830,"text":"USA National Phenology Network, School of Natural Resources and Environment, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":823802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Friesz, Aaron 0000-0003-4096-3824","orcid":"https://orcid.org/0000-0003-4096-3824","contributorId":176645,"corporation":false,"usgs":false,"family":"Friesz","given":"Aaron","affiliations":[],"preferred":false,"id":823803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zachmann, Luke J 0000-0003-2313-1460","orcid":"https://orcid.org/0000-0003-2313-1460","contributorId":265938,"corporation":false,"usgs":false,"family":"Zachmann","given":"Luke","email":"","middleInitial":"J","affiliations":[{"id":54831,"text":"Conservation Science Partners, Inc","active":true,"usgs":false}],"preferred":false,"id":823804,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Enns, Kyle 0000-0001-7675-697X","orcid":"https://orcid.org/0000-0001-7675-697X","contributorId":205857,"corporation":false,"usgs":true,"family":"Enns","given":"Kyle","email":"","affiliations":[{"id":291,"text":"Fort Collins Science 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M.","contributorId":178236,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":823808,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jones, Katherine D.","contributorId":169802,"corporation":false,"usgs":false,"family":"Jones","given":"Katherine","email":"","middleInitial":"D.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":823809,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chang, Tony","contributorId":191992,"corporation":false,"usgs":false,"family":"Chang","given":"Tony","email":"","affiliations":[],"preferred":false,"id":823810,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":823811,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Maiersperger, Tom 0000-0003-3132-6997 tmaiersperger@usgs.gov","orcid":"https://orcid.org/0000-0003-3132-6997","contributorId":3693,"corporation":false,"usgs":true,"family":"Maiersperger","given":"Tom","email":"tmaiersperger@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":823812,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Richardson, Andrew D.","contributorId":178336,"corporation":false,"usgs":false,"family":"Richardson","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":823813,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70238866,"text":"70238866 - 2021 - Invasive Lake Trout reproduction in Yellowstone Lake under an active suppression program","interactions":[],"lastModifiedDate":"2022-12-14T14:34:17.139695","indexId":"70238866","displayToPublicDate":"2021-08-15T08:10:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Invasive Lake Trout reproduction in Yellowstone Lake under an active suppression program","docAbstract":"<p><span>In Yellowstone Lake, predation by invasive Lake Trout&nbsp;</span><i>Salvelinus namaycush</i><span>&nbsp;has caused significant abundance declines in native Yellowstone Cutthroat Trout&nbsp;</span><i>Oncorhynchus clarkii bouvieri</i><span>. Lake Trout suppression has been ongoing since 1995; assessment and simulation modeling are used to measure suppression effectiveness and guide efforts. Lake Trout reproduction demographics are linked to these modeling efforts via quantification of the population stock–recruitment relationship. To improve estimation of this relationship for Lake Trout in Yellowstone Lake, we assessed reproduction demographics by quantifying spawning periodicity, size at maturity, and female fecundity. Histological assessment suggested that females with a gonadosomatic index (GSI) &gt;3.0 and males with a GSI &gt;1.0 were capable of spawning. Approximately 65% of mature females appeared to have spawned on an annual cycle. In 2015, the mean absolute and relative fecundities were 4,612 eggs and 1,535 eggs/kg, respectively; temporal differences in relative fecundity (1996, 2006, 2007, and 2015) were not statistically significant. Lake Trout population fecundity has declined from a peak in 2010 due to reduction in abundance of spawners. The estimated population fecundity of approximately 4.7 million eggs in 2020 represents an 81% decline from the mean estimate of previous samples and an 87% reduction from peak population fecundity. Despite declines in population fecundity, age-2 recruitment has increased in recent years; our results suggest these increases are not related to changes in reproductive demographics, but rather are related to increased prerecruitment survival. Our results provide information for understanding temporal variation in spawning stock biomass of Lake Trout in Yellowstone Lake and the capacity of the population to respond to suppression. When responding to an invasive species, fishery managers should recognize that population characteristics (e.g., reproduction demographics, population dynamics) in invaded systems may differ from those in the species’ native range; such differences can influence the effectiveness of management actions and policies.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10320","usgsCitation":"Heredia, N.A., Gresswell, R.E., Webb, M.A., Brenden, T., and Sandstrom, P., 2021, Invasive Lake Trout reproduction in Yellowstone Lake under an active suppression program: Transactions of the American Fisheries Society, v. 150, p. 637-650, https://doi.org/10.1002/tafs.10320.","productDescription":"14 p.","startPage":"637","endPage":"650","ipdsId":"IP-101302","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451168,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.montana.edu/xmlui/handle/1/17172","text":"External Repository"},{"id":410470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -110.17221715497779,\n              44.31593705993478\n            ],\n            [\n              -110.2779915024647,\n              44.432370639062185\n            ],\n            [\n              -110.26952955466584,\n              44.542541941218076\n            ],\n            [\n              -110.35626451960522,\n              44.56515410795788\n            ],\n            [\n              -110.44088399759472,\n              44.54404969234673\n            ],\n   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bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":152031,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":858988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Molly A.H.","contributorId":299904,"corporation":false,"usgs":false,"family":"Webb","given":"Molly","email":"","middleInitial":"A.H.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":858989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brenden, Travis O.","contributorId":276046,"corporation":false,"usgs":false,"family":"Brenden","given":"Travis O.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":859012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Philip T.","contributorId":299906,"corporation":false,"usgs":false,"family":"Sandstrom","given":"Philip T.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":858992,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226964,"text":"70226964 - 2021 - Invaders from islands: Thermal matching, potential or flexibility?","interactions":[],"lastModifiedDate":"2021-12-22T12:38:26.19629","indexId":"70226964","displayToPublicDate":"2021-08-14T06:35:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9963,"text":"Biological Journal of the Linnaean Society","active":true,"publicationSubtype":{"id":10}},"title":"Invaders from islands: Thermal matching, potential or flexibility?","docAbstract":"<p class=\"chapter-para\">Native-range thermal constraints may not reflect the geographical distributions of species introduced from native island ranges in part due to rapid physiological adaptation in species introduced to new environments. Correlative ecological niche models may thus underestimate potential invasive distributions of species from islands. The northern curly-tailed lizard (<i>Leiocephalus carinatus</i>) is established in Florida, including populations north of its native range. Competing hypotheses may explain this distribution: Thermal Matching (distribution reflects thermal conditions of the native range), Thermal Potential (species tolerates thermal extremes absent in the native range) and/or Thermal Flexibility (thermal tolerance reflects local thermal extremes). We rejected the Thermal Matching hypothesis by comparing ecological niche models developed from native vs. native plus invasive distributions;<span>&nbsp;</span><i>L. carinatus</i><span>&nbsp;</span>exists in areas of low suitability in Florida as predicted by the native-distribution model. We then compared critical thermal limits of<span>&nbsp;</span><i>L. carinatus</i><span>&nbsp;</span>from two non-native populations to evaluate the Thermal Potential and Flexibility hypotheses: one matching native range latitudes, and another 160 km north of the native range that experiences more frequent cold weather events. Critical thermal minima in the northern population were lower than in the south, supporting the Thermal Flexibility hypothesis, whereas critical thermal maxima did not differ.</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/biolinnean/blab103","usgsCitation":"Claunch, N.M., Goodman, C., Reed, R., Guralnick, R.P., Romagosa, C.M., and Taylor, E., 2021, Invaders from islands: Thermal matching, potential or flexibility?: Biological Journal of the Linnaean Society, v. 134, no. 3, p. 587-603, https://doi.org/10.1093/biolinnean/blab103.","productDescription":"17 p.","startPage":"587","endPage":"603","ipdsId":"IP-126295","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":451178,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biolinnean/blab103","text":"Publisher Index Page"},{"id":436241,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XGK1GG","text":"USGS data release","linkHelpText":"Florida invasive Leiocephalus carinatus ecological niche model, thermal environment, and thermal tolerance, 1991-2020"},{"id":393290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bahamas, Cuba, United 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Florida","active":true,"usgs":false}],"preferred":false,"id":828961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":828962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guralnick, Robert P.","contributorId":146671,"corporation":false,"usgs":false,"family":"Guralnick","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":828963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":828964,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, Emily N.","contributorId":270300,"corporation":false,"usgs":false,"family":"Taylor","given":"Emily N.","affiliations":[{"id":56144,"text":"Cal Poly State U.","active":true,"usgs":false}],"preferred":false,"id":828965,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70227641,"text":"70227641 - 2021 - Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data","interactions":[],"lastModifiedDate":"2022-01-24T15:02:28.871949","indexId":"70227641","displayToPublicDate":"2021-08-13T08:59:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data","docAbstract":"<p><span>Kansas is one of the most productive agricultural states in the United States, where&nbsp;agricultural irrigation&nbsp;is a primary user of underground and surface water. Because of low precipitation and declining groundwater levels in western and central Kansas, sustainable management of irrigation water resources is a critical issue in the agricultural productivity of the state. The objective of this study is to analyze and characterize the water use and water balance in the croplands of Kansas using satellite observations,&nbsp;meteorological data, and&nbsp;</span><i>in situ</i><span>&nbsp;irrigation water use records. We used actual&nbsp;evapotranspiration&nbsp;(</span><i>ETa</i><span>), precipitation, soil moisture, and irrigation water use to calculate water balance for Kansas in 2015 at scales of counties, climatic divisions, and&nbsp;groundwater management&nbsp;districts (GMD). The Operational Simplified&nbsp;Surface Energy&nbsp;Balance model was implemented to estimate 30-m resolution&nbsp;</span><i>ETa</i><span>. Results showed that the seasonal (May – September) precipitation,&nbsp;soil water storage&nbsp;change, and&nbsp;</span><i>ETa</i><span>&nbsp;are 528&nbsp;mm, 80&nbsp;mm, and 555&nbsp;mm, respectively, on average of all croplands in the state. The annual net irrigation water consumption was 293&nbsp;mm for irrigated croplands, indicating that irrigation water constitutes an substantial portion of the water supply in the state. The total volumetric irrigation water use was 3.24&nbsp;km</span><sup>3</sup><span>&nbsp;for all croplands within five GMDs in western and south-central Kansas, while only 0.38&nbsp;km</span><sup>3</sup><span>&nbsp;was outside of GMDs. The multiple regression models of&nbsp;</span><i>ETa</i><span>&nbsp;against precipitation and irrigation water use were statistically significant with&nbsp;</span><i>R</i><sup>2</sup><span>&nbsp;values of 0.71 and 0.87, respectively, at county and climate division scales. Regression models also indicated a higher rate of&nbsp;</span><i>ETa</i><span>&nbsp;response to irrigation water use than that to precipitation. Our study demonstrated the spatial patterns of crop water use and water balance in Kansas, which could provide useful information for management of irrigation agriculture and water resources for the state.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2021.107106","usgsCitation":"Ji, L., Senay, G.B., Friedrichs, M., Schauer, M., and Boiko, O., 2021, Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data: Agricultural Water Management, v. 256, 107106, 16 p., https://doi.org/10.1016/j.agwat.2021.107106.","productDescription":"107106, 16 p.","ipdsId":"IP-126709","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":451184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2021.107106","text":"Publisher Index Page"},{"id":394759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-99.541116,36.999573],[-99.648652,36.999604],[-99.657658,37.000197],[-99.875409,37.001659],[-99.995201,37.001631],[-100.115722,37.002206],[-100.193754,37.002133],[-100.552683,37.000735],[-100.734517,36.999059],[-100.756894,36.999357],[-100.855634,36.998626],[-100.904274,36.998745],[-100.945469,36.998153],[-101.012641,36.998176],[-101.359674,36.996232],[-102.04224,36.993083],[-102.041749,37.034397],[-102.041809,37.111973],[-102.042092,37.125021],[-102.041963,37.258164],[-102.041664,37.29765],[-102.042089,37.352819],[-102.041524,37.375018],[-102.042016,37.535261],[-102.041574,37.680436],[-102.042158,37.760164],[-102.042953,37.803535],[-102.044644,38.045532],[-102.044255,38.113011],[-102.044589,38.125013],[-102.044251,38.141778],[-102.044944,38.384419],[-102.044442,38.415802],[-102.044936,38.41968],[-102.045324,38.453647],[-102.045074,38.669617],[-102.045334,38.799463],[-102.046571,39.047038],[-102.04937,39.41821],[-102.049554,39.538932],[-102.050422,39.646048],[-102.050099,39.653812],[-102.050594,39.675594],[-102.051569,39.849805],[-102.051744,40.003078],[-101.904176,40.003162],[-101.841025,40.002784],[-101.409953,40.002354],[-101.324036,40.002696],[-100.937427,40.002145],[-100.75883,40.002302],[-100.66023,40.002162],[-100.645445,40.001883],[-100.196959,40.001494],[-99.990926,40.001503],[-99.948167,40.001813],[-99.930433,40.001516],[-99.813401,40.0014],[-99.772121,40.001804],[-99.756835,40.001342],[-99.746628,40.00182],[-99.49766,40.001912],[-99.423565,40.00227],[-99.412645,40.001868],[-99.282967,40.001879],[-99.018701,40.002333],[-98.710404,40.00218],[-98.690287,40.002548],[-98.652494,40.002245],[-98.64071,40.002493],[-98.560578,40.002274],[-98.274017,40.002516],[-98.250008,40.002307],[-98.193483,40.002614],[-98.099659,40.002227],[-97.838379,40.00191],[-97.777155,40.002167],[-97.510264,40.001835],[-97.369199,40.00206],[-97.20231,40.001442],[-97.142448,40.001495],[-97.137866,40.001814],[-97.049663,40.001323],[-96.916093,40.001506],[-96.622401,40.001158],[-96.610349,40.000881],[-96.467536,40.001035],[-96.125937,40.000432],[-96.02409,40.000719],[-95.30829,39.999998],[-95.308404,39.993758],[-95.30778,39.990618],[-95.307111,39.989114],[-95.302507,39.984357],[-95.289715,39.977706],[-95.274757,39.972115],[-95.269886,39.969396],[-95.261854,39.960618],[-95.257652,39.954886],[-95.250254,39.948644],[-95.241383,39.944949],[-95.236761,39.943931],[-95.231114,39.943784],[-95.220212,39.944433],[-95.21644,39.943953],[-95.213737,39.943206],[-95.204428,39.938949],[-95.201277,39.934194],[-95.20069,39.928155],[-95.20201,39.922438],[-95.205745,39.915169],[-95.206326,39.912121],[-95.206196,39.909557],[-95.205733,39.908275],[-95.201935,39.904053],[-95.199347,39.902709],[-95.193816,39.90069],[-95.189565,39.899959],[-95.179453,39.900062],[-95.172296,39.902026],[-95.159834,39.906984],[-95.156024,39.907243],[-95.149657,39.905948],[-95.146055,39.904183],[-95.143802,39.901918],[-95.142563,39.897992],[-95.142445,39.89542],[-95.143403,39.889356],[-95.142718,39.885889],[-95.140601,39.881688],[-95.137092,39.878351],[-95.134747,39.876852],[-95.128166,39.874165],[-95.105912,39.869164],[-95.090158,39.86314],[-95.085003,39.861883],[-95.081534,39.861718],[-95.052535,39.864374],[-95.042142,39.864805],[-95.037767,39.865542],[-95.032053,39.868337],[-95.027931,39.871522],[-95.025422,39.876711],[-95.025119,39.878833],[-95.025947,39.886747],[-95.02524,39.8897],[-95.024389,39.891202],[-95.018743,39.897372],[-95.013152,39.899953],[-95.00844,39.900596],[-95.003819,39.900401],[-94.990284,39.89701],[-94.986975,39.89667],[-94.977749,39.897472],[-94.963345,39.901136],[-94.959276,39.901671],[-94.95154,39.900533],[-94.943867,39.89813],[-94.934493,39.893366],[-94.929574,39.888754],[-94.927897,39.886112],[-94.927359,39.883966],[-94.927252,39.880258],[-94.928466,39.876344],[-94.931463,39.872602],[-94.938791,39.866954],[-94.940743,39.86441],[-94.942407,39.861066],[-94.942567,39.856602],[-94.939767,39.85193],[-94.937655,39.849786],[-94.92615,39.841322],[-94.916918,39.836138],[-94.909942,39.834426],[-94.903157,39.83385],[-94.892677,39.834378],[-94.889493,39.834026],[-94.886933,39.833098],[-94.881013,39.828922],[-94.878677,39.826522],[-94.877044,39.823754],[-94.876544,39.820594],[-94.875944,39.813294],[-94.876344,39.806894],[-94.880932,39.797338],[-94.884084,39.794234],[-94.890292,39.791626],[-94.892965,39.791098],[-94.925605,39.789754],[-94.929654,39.788282],[-94.932726,39.786282],[-94.935206,39.78313],[-94.935782,39.778906],[-94.935302,39.77561],[-94.934262,39.773642],[-94.929653,39.769098],[-94.926229,39.76649],[-94.916789,39.760938],[-94.912293,39.759338],[-94.906244,39.759418],[-94.899156,39.761258],[-94.895268,39.76321],[-94.883924,39.770186],[-94.88146,39.771258],[-94.871144,39.772994],[-94.869644,39.772894],[-94.867143,39.771694],[-94.865243,39.770094],[-94.863143,39.767294],[-94.860743,39.76309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 \"}}]}","volume":"256","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":272078,"corporation":false,"usgs":false,"family":"Ji","given":"Lei","affiliations":[{"id":56342,"text":"ASRC Federal Data Solutions, Contractor to USGS Earth Resources Observation and Science Center","active":true,"usgs":false}],"preferred":false,"id":831480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":831481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":199093,"corporation":false,"usgs":false,"family":"Friedrichs","given":"MacKenzie","affiliations":[],"preferred":false,"id":831482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":181608,"corporation":false,"usgs":false,"family":"Schauer","given":"Matthew","affiliations":[],"preferred":false,"id":831483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boiko, Olena 0000-0002-2007-7852","orcid":"https://orcid.org/0000-0002-2007-7852","contributorId":272079,"corporation":false,"usgs":false,"family":"Boiko","given":"Olena","email":"","affiliations":[{"id":56343,"text":"KBR, Contractor to USGS Earth Resources Observation and Science Center","active":true,"usgs":false}],"preferred":false,"id":831484,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70227097,"text":"70227097 - 2021 - Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records","interactions":[],"lastModifiedDate":"2021-12-29T14:33:21.49436","indexId":"70227097","displayToPublicDate":"2021-08-13T08:29:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p>The geographic distribution of a species is a fundamental component in understanding its ecology and is necessary for forming effective conservation plans. For rare and elusive species of conservation concern, accurate maps of predicted occurrence are particularly problematic and often highly subjective.<span>&nbsp;</span><i>Spilogale putorius</i><span>&nbsp;</span>(Eastern Spotted Skunk) populations have experienced large declines since the 1940s. Their elusive behavior and perceived rarity result in low detection probability when using conventional methods for sampling small mammals. Low detection probability often causes uncertainty as to where Eastern Spotted Skunks could be a management concern. We modeled the distribution of predicted occurrence of Eastern Spotted Skunks using verifiable occurrence and non-detection records obtained throughout Virginia from 2010 to 2020. Occurrence data consisted of trapping records reported to the Virginia Department of Wildlife Resources, incidental photo-verified reports of sightings and road-killed animals, and remote-camera detections. Non-detections were presumed at baited remote-camera locations following intense survey efforts. We fit predicted occurrence models using generalized linear modeling in an information-theoretic framework using the package ‘stats’ in Program R. Our results incidated a greater probability of presence from the Blue Ridge westward, increasing with slope steepness along northeastern- to southeastern-facing slopes and decreasing with slope steepness along southeastern- to southwestern-facing slopes. Emergent rock outcrops prominent along northeastern slopes offer ample protective rocky cover, whereas mixed<span>&nbsp;</span><i>Quercus</i><span>&nbsp;</span>spp. (oak),<span>&nbsp;</span><i>Kalmia latifolia</i><span>&nbsp;</span>(Mountain Laurel), and<span>&nbsp;</span><i>Rhododendron maximum</i><span>&nbsp;</span>(Rosebay Rhododendron) forest communities along southern-facing slopes provide suitable areas of cover, both of which are critical for spotted skunk survival and reproductive success. Our analysis provides insight into the relationships between landscape features and Eastern Spotted Skunk distributions across Virginia. Understanding these relationships is critical for the effective management and conservation of this vulnerable species.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.1656/058.020.0sp1105","usgsCitation":"Thorne, E.D., and Ford, W., 2021, Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records: Southeastern Naturalist, v. 20, no. 11, p. 39-51, https://doi.org/10.1656/058.020.0sp1105.","productDescription":"13 p.","startPage":"39","endPage":"51","ipdsId":"IP-123161","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451186,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/111969","text":"External Repository"},{"id":393575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.13330078125,\n              36.31512514748051\n            ],\n            [\n              -74.20166015624999,\n              36.31512514748051\n            ],\n            [\n              -74.20166015624999,\n              40.027614437486655\n            ],\n            [\n              -84.13330078125,\n              40.027614437486655\n            ],\n            [\n              -84.13330078125,\n              36.31512514748051\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thorne, Emily D.","contributorId":270628,"corporation":false,"usgs":false,"family":"Thorne","given":"Emily","email":"","middleInitial":"D.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":829626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829625,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70228894,"text":"70228894 - 2021 - Wetland selection by female Ring-Necked Ducks (Aythya collaris) in the Southern Atlantic Flyway","interactions":[],"lastModifiedDate":"2022-02-23T13:28:46.986794","indexId":"70228894","displayToPublicDate":"2021-08-13T07:21:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Wetland selection by female Ring-Necked Ducks (Aythya collaris) in the Southern Atlantic Flyway","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>On the wintering grounds, wetland selection by waterfowl is influenced by spatiotemporal resource distribution. The ring-necked duck (<i>Aythya collaris</i>) winters in the southeastern United States where a disproportionate amount of Atlantic Flyway ring-necked duck harvest occurs. We quantified female ring-necked duck selection for wetland characteristics during and after the 2017–2018 and 2018–2019 waterfowl hunting seasons using discrete choice modeling under a Bayesian framework. Relative probability of selection was primarily influenced by characteristics at the local wetland scale. Relative probability of selection was higher for flooded agriculture and vegetated wetlands than open water and was positively influenced by wetland area during the winter. After the hunting season, the relative probability of selection decreased for flooded agriculture but increased for vegetated wetlands, and the effect of wetland area decreased in magnitude. We attribute changes in selection during and after the hunting season to dietary shifts related to migratory preparation, resource depletion, and reproductive pairing. Understanding the wetland characteristics that wintering waterfowl select, and the spatial scale at which selection occurs, is important for informing effective wetland management and waterfowl harvest practices.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s13157-021-01485-8","usgsCitation":"Mezebish, T.D., Chandler, R., Olsen, G.H., Goodman, M., Rohwer, F., Meng, N.J., and McConnell, M.D., 2021, Wetland selection by female Ring-Necked Ducks (Aythya collaris) in the Southern Atlantic Flyway: Wetlands, v. 41, 84, 13 p., https://doi.org/10.1007/s13157-021-01485-8.","productDescription":"84, 13 p.","ipdsId":"IP-130253","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":396335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.73754882812499,\n              29.99300228455108\n            ],\n            [\n              -81.59545898437499,\n              29.99300228455108\n            ],\n            [\n              -81.59545898437499,\n              31.062345409804433\n            ],\n            [\n              -84.73754882812499,\n              31.062345409804433\n            ],\n            [\n              -84.73754882812499,\n              29.99300228455108\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2021-08-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Mezebish, Tori D.","contributorId":239496,"corporation":false,"usgs":false,"family":"Mezebish","given":"Tori","email":"","middleInitial":"D.","affiliations":[{"id":27618,"text":"University of Georgia, Warnell School of Forestry and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":835802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard rchandler@usgs.gov","contributorId":2511,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":835838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Glenn H. 0000-0002-7188-6203","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":238130,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goodman, Michele","contributorId":239497,"corporation":false,"usgs":false,"family":"Goodman","given":"Michele","email":"","affiliations":[{"id":47893,"text":"Elmwood Park Zoo, Norristown, Pennyslvania","active":true,"usgs":false}],"preferred":false,"id":835804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohwer, Frank C.","contributorId":239498,"corporation":false,"usgs":false,"family":"Rohwer","given":"Frank C.","affiliations":[{"id":47894,"text":"Delta Waterfowl, Bismark North Dakota","active":true,"usgs":false}],"preferred":false,"id":835805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meng, Nicholas J.","contributorId":264806,"corporation":false,"usgs":false,"family":"Meng","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":54559,"text":"Warnell School of Forestry and Natural Resources, University of Georgia,","active":true,"usgs":false}],"preferred":false,"id":835839,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McConnell, Mark D.","contributorId":239499,"corporation":false,"usgs":false,"family":"McConnell","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":47895,"text":"College of Forest Resources, Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":835806,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223230,"text":"70223230 - 2021 - Merging empirical and mechanistic approaches to modeling aquatic visual foraging using a generalizable visual reaction distance model","interactions":[],"lastModifiedDate":"2021-08-18T12:22:11.267846","indexId":"70223230","displayToPublicDate":"2021-08-13T07:19:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Merging empirical and mechanistic approaches to modeling aquatic visual foraging using a generalizable visual reaction distance model","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0002\" class=\"abstract author\"><div id=\"abss0002\"><p id=\"spara011\">Visual encounter distance models are important tools for predicting how light and water clarity mediate visual predator-prey interactions that affect the structure and function of aquatic ecosystems at multiple spatial, temporal, and organizational scales. The two main varieties of visual encounter distance models, mechanistic and empirical, are used for similar purposes but take fundamentally different approaches to model development and have different strengths and weaknesses in terms of predictive accuracy, physical and biological interpretability of parameters, ability to incorporate outside information, and utility for knowledge transfer. To overcome weaknesses of existing mechanistic and empirical models and bridge the gap between approaches, we developed a generalized visual reaction distance model that relaxes assumptions of a widely-used mechanistic model that are violated in real predator-prey interactions. We compared the performance of the generalized visual reaction distance model to a widely used mechanistic model and an empirical visual encounter distance model by fitting models to data from four predator-prey experiments. The generalized visual reaction distance model substantially outperformed the other models in all cases based on fit to reaction distance data and presents an attractive alternative to prior models based on comparatively high predictive accuracy, use of interpretable parameters, and ability to incorporate outside information—characteristics that facilitate knowledge transfer.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2021.109688","usgsCitation":"Rohan, S.K., Beauchamp, D., Essington, T.E., and Hansen, A.G., 2021, Merging empirical and mechanistic approaches to modeling aquatic visual foraging using a generalizable visual reaction distance model: Ecological Modelling, v. 457, 109688, 13 p., https://doi.org/10.1016/j.ecolmodel.2021.109688.","productDescription":"109688, 13 p.","ipdsId":"IP-118285","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":451195,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2021.109688","text":"Publisher Index Page"},{"id":388085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"457","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rohan, Sean K.","contributorId":260255,"corporation":false,"usgs":false,"family":"Rohan","given":"Sean","email":"","middleInitial":"K.","affiliations":[{"id":52548,"text":"National Marine Fisheries Service, Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115, USA","active":true,"usgs":false}],"preferred":false,"id":821471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":821472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essington, Timothy E.","contributorId":95826,"corporation":false,"usgs":false,"family":"Essington","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":821473,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, Adam G.","contributorId":197415,"corporation":false,"usgs":false,"family":"Hansen","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":34919,"text":"Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, Colorado 80526, USA","active":true,"usgs":false}],"preferred":false,"id":821474,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","interactions":[{"subject":{"id":70202002,"text":"70202002 - 2021 - Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA","indexId":"70202002","publicationYear":"2021","noYear":false,"chapter":"10","title":"Perspectives on the paleolimnology of the late Eocene Florissant lake from diatom and sedimentary evidence at Clare’s Quarry, Teller County, Colorado, USA"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":1},{"subject":{"id":70204951,"text":"70204951 - 2021 - Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California","indexId":"70204951","publicationYear":"2021","noYear":false,"chapter":"8","title":"Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":2},{"subject":{"id":70214977,"text":"70214977 - 2019 - Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California","indexId":"70214977","publicationYear":"2019","noYear":false,"chapter":"19","title":"Holocene sedimentary architecture and paleoclimate variability at Mono Lake, California"},"predicate":"IS_PART_OF","object":{"id":70225733,"text":"70225733 - 2021 - From saline to freshwater: The diversity of western lakes in space and time","indexId":"70225733","publicationYear":"2021","noYear":false,"title":"From saline to freshwater: The diversity of western lakes in space and time"},"id":3}],"lastModifiedDate":"2021-11-08T15:31:24.702283","indexId":"70225733","displayToPublicDate":"2021-08-12T08:42:20","publicationYear":"2021","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"From saline to freshwater: The diversity of western lakes in space and time","docAbstract":"<p><span>Beginning with the nineteenth-century territorial surveys, the lakes and lacustrine deposits in what is now the western United States were recognized for their economic value to the expanding nation. In the latter half of the twentieth century, these systems have been acknowledged as outstanding examples of depositional systems serving as models for energy exploration and environmental analysis, many with global applications in the twenty-first century. The localities presented in this volume extend from exposures of the Eocene Green River Formation in Utah and Florissant Formation in Colorado, through the Pleistocene and Holocene lakes of the Great Basin to lakes along the California and Oregon coast. The chapters explore environmental variability, sedimentary processes, fire history, the impact of lakes on crustal flexure, and abrupt climate events in arid regions, often through the application of new tools and proxies.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/SPE536","usgsCitation":"2021, From saline to freshwater: The diversity of western lakes in space and time, v. 536, xii, 506 p., https://doi.org/10.1130/SPE536.","productDescription":"xii, 506 p.","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":391468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"536","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":826440,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826441,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}}
,{"id":70223202,"text":"70223202 - 2021 - Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2021-09-14T16:54:11.190706","indexId":"70223202","displayToPublicDate":"2021-08-12T08:03:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico","docAbstract":"<div class=\"article-section__content en main\"><p>Flows into and out of the Gulf of Mexico (GoM) are integral to North Atlantic ocean circulation, and help facilitate poleward heat transport in the Western Hemisphere. The GoM also serves as a key source of moisture for much of North America. Modern patterns of sea-surface temperature (SST) and salinity in the GoM are influenced by the Loop Current, its eddy-shedding dynamics, and the ensuing interplay with coastal processes. Here we present sub-centennial-scale records of SST and stable oxygen isotope composition of seawater (<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/0ab33ba3-5adf-434f-bd1c-b48fc204fd2b/palo21077-math-0001.png\" alt=\"urn:x-wiley:25724517:media:palo21077:palo21077-math-0001\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/0ab33ba3-5adf-434f-bd1c-b48fc204fd2b/palo21077-math-0001.png\"><sup>18</sup>O<sub>sw</sub>; a proxy for salinity) over the past 11,700 years using planktic foraminiferal geochemistry in sediments from the Garrison Basin, northwestern GoM. We measured<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/f7f0b0d0-0435-42ca-8977-41ff3778eba6/palo21077-math-0002.png\" alt=\"urn:x-wiley:25724517:media:palo21077:palo21077-math-0002\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/f7f0b0d0-0435-42ca-8977-41ff3778eba6/palo21077-math-0002.png\">O and magnesium-to-calcium ratios in tests of<span>&nbsp;</span><i>Globigerinoides ruber</i><span>&nbsp;</span>(white) to generate quantitative estimates of past sea-surface conditions. Our results replicate and extend late Holocene reconstructions from the Garrison Basin, using which we then create composites of SST and<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/71b1f56d-78fd-4002-8f9a-10fcc73e9851/palo21077-math-0003.png\" alt=\"urn:x-wiley:25724517:media:palo21077:palo21077-math-0003\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/71b1f56d-78fd-4002-8f9a-10fcc73e9851/palo21077-math-0003.png\"><sup>18</sup>O<sub>sw</sub>. We find considerable centennial and millennial-scale variability in both SST and<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/e7dcb00a-0535-47ac-aaed-9d00b1e485ca/palo21077-math-0004.png\" alt=\"urn:x-wiley:25724517:media:palo21077:palo21077-math-0004\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/e7dcb00a-0535-47ac-aaed-9d00b1e485ca/palo21077-math-0004.png\"><sup>18</sup>O<sub>sw</sub>, although their evolution over the Holocene is distinct. Whereas mean-annual SSTs display pronounced millennial-scale variability,<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/763c0798-9404-4d3b-84b1-5d98dbed926b/palo21077-math-0005.png\" alt=\"urn:x-wiley:25724517:media:palo21077:palo21077-math-0005\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/763c0798-9404-4d3b-84b1-5d98dbed926b/palo21077-math-0005.png\"><sup>18</sup>O<sub>sw</sub><span>&nbsp;</span>exhibits a secular trend spanning multiple millennia and points to increasing northwestern GoM surface salinity since the early Holocene. We then synthesize available Holocene records from across the GoM, and alongside the Garrison Basin composite, uncover substantial, yet regionally consistent, spatiotemporal variability. Finally, we discuss the role of the Loop Current and coastal influx of freshwater in imposing these heterogeneities. We conclude that dynamic surface-ocean changes occurred across the GoM over the Holocene.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021PA004221","usgsCitation":"Thiumalai, K., Richey, J.N., and Quinn, T.M., 2021, Holocene evolution of sea-surface temperature and salinity in the Gulf of Mexico: Paleoceanography and Paleoclimatology, v. 36, no. 8, e2021PA004221, 16 p., https://doi.org/10.1029/2021PA004221.","productDescription":"e2021PA004221, 16 p.","ipdsId":"IP-120738","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":436244,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q5L9VU","text":"USGS data release","linkHelpText":"Radiocarbon Dates and Foraminiferal Geochemistry Data for Sediment Core Collected from Garrison Basin, Gulf of Mexico"},{"id":388097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.07861328125,\n              27.00040800352175\n            ],\n            [\n              -83.60595703125,\n              29.611670115197377\n            ],\n            [\n              -86.37451171875,\n              29.859701442126756\n            ],\n            [\n              -88.9453125,\n              29.76437737516313\n            ],\n            [\n              -88.92333984375,\n              28.671310915880834\n            ],\n            [\n              -91.91162109375,\n              29.286398892934763\n            ],\n            [\n              -95.07568359375,\n              29.017748018496047\n            ],\n            [\n              -97.09716796875,\n              27.11781284232125\n            ],\n            [\n              -96.94335937499999,\n              24.647017162630366\n            ],\n            [\n              -97.18505859374999,\n              21.922663209325922\n            ],\n            [\n              -95.3173828125,\n              20.838277806058933\n            ],\n            [\n              -81.54052734375,\n              24.307053283225915\n            ],\n            [\n              -83.07861328125,\n              27.00040800352175\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Thiumalai, Kaustubh 0000-0002-7875-4182","orcid":"https://orcid.org/0000-0002-7875-4182","contributorId":264344,"corporation":false,"usgs":false,"family":"Thiumalai","given":"Kaustubh","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":821389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quinn, Terrence M.","contributorId":82949,"corporation":false,"usgs":false,"family":"Quinn","given":"Terrence","email":"","middleInitial":"M.","affiliations":[{"id":6732,"text":"Geological Sciences, University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":821391,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70224645,"text":"70224645 - 2021 - Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes","interactions":[],"lastModifiedDate":"2021-10-01T12:32:21.081687","indexId":"70224645","displayToPublicDate":"2021-08-12T07:30:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Regeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush (<i>Artemisia tridentata</i>) after disturbances including fire-invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long-lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range-wide big sagebrush regeneration responses in natural vegetation (process-based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model). The process-based model suggested substantial geographic variation in long-term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression-based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long-term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re-creating conditions of uninvaded, unburned natural big sagebrush vegetation for post-fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire-invasive annual grass cycle.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3695","usgsCitation":"Schlaepfer, D.R., Bradford, J., Lauenroth, W.K., and Shriver, R.K., 2021, Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes: Ecosphere, v. 12, no. 8, e03695, 26 p., https://doi.org/10.1002/ecs2.3695.","productDescription":"e03695, 26 p.","ipdsId":"IP-126859","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":451203,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3695","text":"Publisher Index Page"},{"id":436245,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MB2QB8","text":"USGS data release","linkHelpText":"Simulated rangewide big sagebrush regeneration estimates and relationships with abiotic variables as function of soils under historical and future climate projections"},{"id":390101,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -125.68359374999999,\n              28.536274512989916\n            ],\n            [\n              -100.546875,\n              28.536274512989916\n            ],\n            [\n              -100.546875,\n              49.724479188712984\n            ],\n            [\n              -125.68359374999999,\n              49.724479188712984\n            ],\n            [\n              -125.68359374999999,\n              28.536274512989916\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":824525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":824526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":824527,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70230438,"text":"70230438 - 2021 - Paleoclimate record for Lake Coyote, California, and the Last Glacial Maximum and deglacial paleohydrology (25 to 14 cal ka) of the Mojave River","interactions":[],"lastModifiedDate":"2022-04-13T12:17:55.623098","indexId":"70230438","displayToPublicDate":"2021-08-12T07:14:28","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Paleoclimate record for Lake Coyote, California, and the Last Glacial Maximum and deglacial paleohydrology (25 to 14 cal ka) of the Mojave River","docAbstract":"<p>Lake Coyote, California, which formed in one of five basins along the Mojave River, acted both as a part of the Lake Manix basin and, after the formation of Afton Canyon and draining of Lake Manix ca. 24.5 calibrated (cal) ka, a side basin that was filled episodically for the next 10,000 yr. As such, its record of lake level is an important counterpart to the record of the other terminal basin, Lake Mojave, following the draining of Lake Manix. We studied lake and fluvial deposits and their geomorphology and identified five principal periods of recurring lakes in the Coyote basin by dating mollusks. Several of these periods in detail consist of multiple lake-rise pulses, for which we identified specific fluvial deposits that represent the Mojave River entering the basin. The pulsed record of rapid lake rise and decline is interpreted as switching of the Mojave River between Lake Coyote and Lake Mojave. A composite lake record for both basins shows nearly continuous lake maintenance by the Mojave River from 24.5 cal ka to ca. 14 cal ka. One potential gap in the lake record, ca. 22.7–21.8 cal ka, may indicate either temporary river routing to yet another basin or a dry climatic period. The Mojave River discharge was sufficient to maintain at least one terminal lake throughout most of the Last Glacial Maximum and deglacial periods, indicating that paleoclimate was moist and/or cool well into the Bølling-Allerød and that the lake records may not be sensitive to variations from moderate to high discharge. Nuances of lake-level changes in both the Coyote and Mojave basins are difficult to interpret as paleoclimatic events because the current chronologic control on lake levels from nearshore deposits does not provide the necessary precision.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From Saline to Freshwater: The Diversity of Western Lakes in Space and Time","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2536(12)","usgsCitation":"Miller, D., Dudash, S.L., and McGeehin, J., 2021, Paleoclimate record for Lake Coyote, California, and the Last Glacial Maximum and deglacial paleohydrology (25 to 14 cal ka) of the Mojave River, chap. <i>of</i> From Saline to Freshwater: The Diversity of Western Lakes in Space and Time, v. 536, p. 201-220, https://doi.org/10.1130/2018.2536(12).","productDescription":"20 p.","startPage":"201","endPage":"220","ipdsId":"IP-087116","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":398633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Lake Coyote","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.10302734374999,\n              34.08906131584994\n            ],\n            [\n              -114.76318359375,\n              34.08906131584994\n            ],\n            [\n              -114.76318359375,\n              36.19109202182454\n            ],\n            [\n              -118.10302734374999,\n              36.19109202182454\n            ],\n            [\n              -118.10302734374999,\n              34.08906131584994\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"536","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":840431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudash, Stephanie L. 0000-0001-8728-5915 sdudash@usgs.gov","orcid":"https://orcid.org/0000-0001-8728-5915","contributorId":5911,"corporation":false,"usgs":true,"family":"Dudash","given":"Stephanie","email":"sdudash@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":840432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGeehin, John P.","contributorId":290192,"corporation":false,"usgs":false,"family":"McGeehin","given":"John P.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":840433,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70229486,"text":"70229486 - 2021 - Tolerance of northern Gulf of Mexico eastern oysters to chronic warming at extreme salinities","interactions":[],"lastModifiedDate":"2022-03-09T13:10:17.276921","indexId":"70229486","displayToPublicDate":"2021-08-12T07:06:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"Tolerance of northern Gulf of Mexico eastern oysters to chronic warming at extreme salinities","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>The&nbsp;eastern oyster,&nbsp;</span><i>Crassostrea virginica</i><span>, provides critical ecosystem services and supports valuable fishery and&nbsp;aquaculture industries&nbsp;in northern&nbsp;Gulf of Mexico&nbsp;(nGoM) subtropical&nbsp;estuaries&nbsp;where it is grown subtidally. Its upper critical thermal limit is not well defined, especially when combined with extreme&nbsp;salinities. The cumulative mortalities of the&nbsp;progenies&nbsp;of wild&nbsp;</span><i>C. virginica</i><span>&nbsp;</span>from four nGoM estuaries differing in mean annual salinity, acclimated to low (4.0), moderate (20.0), and high (36.0) salinities at 28.9&nbsp;°C (84&nbsp;°F) and exposed to increasing target temperatures of 33.3&nbsp;°C (92&nbsp;°F), 35.6&nbsp;°C (96&nbsp;°F) or 37.8&nbsp;°C (100&nbsp;°F), were measured over a three-week period. Oysters of all stocks were the most sensitive to increasing temperatures at low salinity, dying quicker (i.e., lower median lethal time, LT<sub>50</sub>) than at the moderate and high salinities and resulting in high cumulative mortalities at all target temperatures. Oysters of all stocks at moderate salinity died the slowest with high cumulative mortalities only at the two highest temperatures. The F1 oysters from the more southern and hypersaline Upper Laguna Madre estuary were generally more tolerant to prolonged higher temperatures (higher LT<sub>50</sub>) than stocks originating from lower salinity estuaries, most notably at the highest salinity. Using the measured temperatures oysters were exposed to, 3-day median lethal Celsius degrees (LD<sub>50</sub>) were estimated for each stock at each salinity. The lowest 3-day LD<sub>50</sub><span>&nbsp;</span>(35.1–36.0&nbsp;°C) for all stocks was calculated at a salinity of 4.0, while the highest 3-day LD<sub>50</sub><span>&nbsp;</span>(40.1–44.0&nbsp;°C) was calculated at a salinity of 20.0.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2021.103072","usgsCitation":"Marshall, D., Coxe, N., La Peyre, M., Walton, W., Rikard, F.S., Beseres Pollack, J., Kelly, M., and La Peyre, J., 2021, Tolerance of northern Gulf of Mexico eastern oysters to chronic warming at extreme salinities: Journal of Thermal Biology, v. 100, 103072, 7 p., https://doi.org/10.1016/j.jtherbio.2021.103072.","productDescription":"103072, 7 p.","ipdsId":"IP-126113","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451207,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.lsu.edu/biosci_pubs/3821","text":"Publisher Index Page"},{"id":396900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Texas","otherGeospatial":"Northern Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.91015624999999,\n              26.03704188651584\n            ],\n            [\n              -90.52734374999999,\n              26.03704188651584\n            ],\n            [\n              -90.52734374999999,\n              30.826780904779774\n            ],\n            [\n              -97.91015624999999,\n              30.826780904779774\n            ],\n            [\n              -97.91015624999999,\n              26.03704188651584\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"100","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, D.A.","contributorId":287622,"corporation":false,"usgs":false,"family":"Marshall","given":"D.A.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coxe, N.C.","contributorId":288255,"corporation":false,"usgs":false,"family":"Coxe","given":"N.C.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":837592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walton, W.C.","contributorId":287624,"corporation":false,"usgs":false,"family":"Walton","given":"W.C.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":837593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rikard, F. Scott","contributorId":288303,"corporation":false,"usgs":false,"family":"Rikard","given":"F.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":837656,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beseres Pollack, J.","contributorId":288257,"corporation":false,"usgs":false,"family":"Beseres Pollack","given":"J.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":837594,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, M.A.","contributorId":221161,"corporation":false,"usgs":false,"family":"Kelly","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":837595,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"La Peyre, J.F.","contributorId":274908,"corporation":false,"usgs":false,"family":"La Peyre","given":"J.F.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":837596,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70222521,"text":"sir20215052 - 2021 - American and Sacramento Rivers, California, erodibility measurements and model","interactions":[],"lastModifiedDate":"2021-08-11T17:57:23.670031","indexId":"sir20215052","displayToPublicDate":"2021-08-11T08:55:06","publicationYear":"2021","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":"2021-5052","displayTitle":"American and Sacramento Rivers, California, Erodibility Measurements and Model","title":"American and Sacramento Rivers, California, erodibility measurements and model","docAbstract":"<h1>Executive Summary&nbsp; </h1><p>A previous report by the authors described sediment sampling and drilling by the U.S. Geological Survey (USGS) beside the American and Sacramento Rivers near Sacramento, California, in support of a U.S. Army Corps of Engineers project focused on regional flood control. The drilling was performed to define lithology, extract samples for laboratory testing, and perform borehole erosion tests (BETs). The U.S. Department of Agriculture (USDA) performed jet erodibility tests (JETs) near each drilling site, and a team from Texas A&amp;M University performed laboratory tests with an erosion function apparatus (EFA). Collectively, the effort was intended to reveal spatial variations in sediment erodibility and provide data for use in a model to simulate morphological response to a major flood. The data collected by the USGS are available in a public data release.</p><p>This report, developed in cooperation with the U.S. Army Corps of Engineers, provides comparisons of the three types of measurements of the erodibility of riverbed sediments. The BET is performed in the field and reveals erodibility of sediments below the bed surface. The JET is likewise performed in the field but reveals only erodibility of exposed sediments. The EFA test is done in the laboratory and was performed on soils extracted from different depths beneath the bed surface, in many cases reconstituted for laboratory testing. Tests were performed at nominally similar locations but differed by meters to tens of meters in horizontal locations.</p><p>The comparison was undertaken to investigate differences among results obtained by the individual measurement approaches and to elucidate pros and cons of each method. The critical shear stress to initiate erosion and the rate of change of erosion rate per unit increase of excess shear stress, sometimes referred to as the erosion coefficient, served as the primary basis for comparison. The three test methods in some cases resulted in order of magnitude differences in estimates of these parameters. Some differences could be attributed to variances in site location or result from testing surface sediment versus a deeper layer, but systematic differences are also evident in the results. The tests performed in the laboratory using the EFA resulted in much lower values of critical shear stress and much higher values of the erosion coefficient compared to the JET tests performed by the USDA team on surface sediments. Critical shear stress was poorly resolved in the BET results because of the limited number of results per site, but the erosion coefficients derived from BET results were systematically lower than those obtained using the EFA.</p><p>A new, simplified approach is also proposed to estimate the increase in channel cross-sectional area during a large flood, given data describing the initial river cross section, riverbed erodibility parameters, and peak flood discharge and duration. The model runs until the cross section erodes to an equilibrium condition or the flood ends. Output describes the area of the cross section at the end of the simulation and the time required to reach equilibrium if it was reached within the simulated period. The model assumes unique, constant values for both the critical shear stress and the erosion coefficient and represents the fluid mechanics in a simplified way, making it of limited value for quantitative predictions. It does, however, provide an indication of which cross sections are most likely to undergo the greatest change in the design event and can be used to investigate sensitivity of erosion predictions to variability in sediment erodibility measurements.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215052","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","programNote":"Cooperative Research Units","usgsCitation":"Work, P., and Livsey, D., 2021, American and Sacramento Rivers, California, erodibility measurements and model: U.S. Geological Survey Scientific Investigations Report 2021–5052, 30 p., https://doi.org/10.3133/sir20215052.","productDescription":"Report: vii, 30 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-122004","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":387634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5052/covrthb.jpg"},{"id":387637,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5052/images"},{"id":387635,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5052/sir20215052.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":387636,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5052/sir20215052.xml"},{"id":387638,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96MCT2Q","linkHelpText":"Borehole Erosion Test data, Lower American and Sacramento Rivers, California, 2019 (ver. 4.0, July 2021)"}],"country":"United States","state":"California","otherGeospatial":"American River, Sacramento River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.58981323242188,\n              38.41378642476067\n            ],\n            [\n              -121.34124755859375,\n              38.41378642476067\n            ],\n            [\n              -121.34124755859375,\n              38.60292007223949\n            ],\n            [\n              -121.58981323242188,\n              38.60292007223949\n            ],\n            [\n              -121.58981323242188,\n              38.41378642476067\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Executive Summary&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Comparison of the Three Methods for Quantifying Erodibility&nbsp;&nbsp;</li><li>Comparison of Test Results&nbsp;&nbsp;</li><li>Equilibrium Model for Cross-Section Erosion&nbsp;&nbsp;</li><li>Summary and Conclusions&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Plots Relating Erosion and Shear Stress Data Derived from Borehole Erosion Tests for the American and Sacramento Rivers</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-08-11","noUsgsAuthors":false,"publicationDate":"2021-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Paul A. 0000-0002-2815-8040 pwork@usgs.gov","orcid":"https://orcid.org/0000-0002-2815-8040","contributorId":168561,"corporation":false,"usgs":true,"family":"Work","given":"Paul","email":"pwork@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Livsey, Daniel N. 0000-0002-2028-6128 dlivsey@usgs.gov","orcid":"https://orcid.org/0000-0002-2028-6128","contributorId":181870,"corporation":false,"usgs":true,"family":"Livsey","given":"Daniel","email":"dlivsey@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":820455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227258,"text":"70227258 - 2021 - The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate","interactions":[],"lastModifiedDate":"2022-01-05T13:12:29.380875","indexId":"70227258","displayToPublicDate":"2021-08-11T07:09:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0045\" style=\"\"><span>Modeling studies project that in the future surface waters in the northeast US will continue to recover from&nbsp;acidification&nbsp;over decades following reductions in atmospheric&nbsp;sulfur dioxide&nbsp;and&nbsp;nitrogen oxides&nbsp;emissions. However, these studies generally assume stationary climatic conditions over the simulation period and ignore the linkages between soil and surface&nbsp;water recovery&nbsp;from acid deposition and changing climate, despite fundamental impacts to&nbsp;watershed processes&nbsp;and comparable time scales for both phenomena. In this study, the integrated biogeochemical model PnET-BGC was applied to two montane forest watersheds in the Adirondack region of New York, USA to evaluate the recovery of surface waters from historical acidification in response to possible future changes in climate and atmospheric sulfur and nitrogen deposition. Statistically downscaled climate scenarios on average project warmer temperatures and greater precipitation for the Adirondack by the end of the century. Model simulations suggest under constant climate, acid-sensitive Buck Creek would gain 12.8 μeq L</span><sup>−1</sup><span>&nbsp;</span>of acid neutralizing capacity (ANC) by 2100 from large reductions in deposition, whereas acid insensitive Archer Creek is projected to gain 7.9 μeq L<sup>−1</sup><span>&nbsp;</span>of ANC. However, climate change could limit those improvements in acid-base status. Under climate change, a negative offset relative to the ANC increases with no climate change are projected for both streams by 2100. In acid-insensitive Archer Creek the negative offset (−8.5 μeq L<sup>−1</sup>) was large enough that ANC is projected to decrease by −0.6 μeq L<sup>−1</sup>, whereas in acid-sensitive Buck Creek, the negative offset (−0.4 μeq L<sup>−1</sup>) resulted in a slight decline of the projected future ANC increase to 12.4 μeq L<sup>−1</sup>. Calculated target loads for 2150 for both sites decreased when future climate change was considered in model simulations, which suggests further reductions in acid deposition may be necessary to restore ecosystem structure and function under a changing climate.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.149626","usgsCitation":"Shao, S., Burns, D., Shen, H., Chen, Y., Russell, A.G., and Driscoll, C., 2021, The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate: Science of the Total Environment, v. 800, 149626, 13 p., https://doi.org/10.1016/j.scitotenv.2021.149626.","productDescription":"149626, 13 p.","ipdsId":"IP-128626","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":393906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.443115234375,\n              42.76314586689494\n            ],\n            [\n              -73.201904296875,\n              42.76314586689494\n            ],\n            [\n              -73.201904296875,\n              45.081278612418764\n            ],\n            [\n              -75.443115234375,\n              45.081278612418764\n            ],\n            [\n              -75.443115234375,\n              42.76314586689494\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"800","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shao, Shuai","contributorId":222597,"corporation":false,"usgs":false,"family":"Shao","given":"Shuai","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":830149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":830150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shen, Huizhong 0000-0003-1335-8477","orcid":"https://orcid.org/0000-0003-1335-8477","contributorId":270927,"corporation":false,"usgs":false,"family":"Shen","given":"Huizhong","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Yilin 0000-0001-5532-4115","orcid":"https://orcid.org/0000-0001-5532-4115","contributorId":270928,"corporation":false,"usgs":false,"family":"Chen","given":"Yilin","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830152,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Armistead G 0000-0003-2027-8870","orcid":"https://orcid.org/0000-0003-2027-8870","contributorId":270929,"corporation":false,"usgs":false,"family":"Russell","given":"Armistead","email":"","middleInitial":"G","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":830153,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Driscoll, Charles T.","contributorId":240874,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":830154,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226570,"text":"70226570 - 2021 - Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream","interactions":[],"lastModifiedDate":"2021-11-29T12:54:51.469752","indexId":"70226570","displayToPublicDate":"2021-08-10T06:53:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream","docAbstract":"<div id=\"abs0002\" class=\"abstract author\"><div id=\"abss0002\"><p id=\"spara005\">Evolving complex mixtures of pharmaceuticals and transformation products in effluent-dominated streams pose potential impacts to aquatic species; thus, understanding the attenuation dynamics in the field and characterizing the prominent attenuation mechanisms of pharmaceuticals and their transformation products (TPs) is critical for hazard assessments. Herein, we determined the attenuation dynamics and the associated prominent mechanisms of pharmaceuticals and their corresponding TPs via a combined long-term field study and controlled laboratory experiments. For the field study, we quantified spatiotemporal exposure concentrations of five pharmaceuticals and six associated TPs in a small, temperate-region effluent-dominated stream during baseflow conditions where the wastewater plant was the main source of pharmaceuticals. We selected four sites (upstream, at, and two progressively downstream from effluent discharge) and collected water samples at 16 time points (64 samples in total, approximately twice monthly, depending on flows) for 1 year. Concurrently, we conducted photolysis, sorption, and biodegradation batch tests under controlled conditions to determine the major attenuation mechanisms. We observed 10-fold greater attenuation rates in the field compared to batch tests, demonstrating that connecting laboratory batch tests with field measurements to enhance predictive power is a critical need. Batch systems alone, often used for assessment, are useful for determining fate processes but poorly approximate in-stream attenuation kinetics. Sorption was the dominant attenuation process (t<sub>1/2</sub>&lt;7.7 d) for 5 of 11 compounds in the batch tests, while the other compounds (<i>n</i>&nbsp;=&nbsp;6) persisted in the batch tests and along the 5.1&nbsp;km stream reach. In-stream parent-to-product transformation was minimal. Differential attenuation contributed to the evolving pharmaceutical mixture and created changing exposure conditions with concomitant implications for aquatic and terrestrial biota. Tandem field and laboratory characterization can better inform modeling efforts for transport and risk assessments.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117537","usgsCitation":"Zhi, H., Mianecki, A.L., Kolpin, D., Klaper, R.D., Iwanowicz, L., and LeFevre, G.H., 2021, Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream: Water Research, v. 203, 117537, 10 p., https://doi.org/10.1016/j.watres.2021.117537.","productDescription":"117537, 10 p.","ipdsId":"IP-124512","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":451233,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12424012/","text":"Publisher Index Page"},{"id":392181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"203","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zhi, Hui","contributorId":225502,"corporation":false,"usgs":false,"family":"Zhi","given":"Hui","email":"","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":827369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mianecki, Alyssa L","contributorId":269532,"corporation":false,"usgs":false,"family":"Mianecki","given":"Alyssa","email":"","middleInitial":"L","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":827370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":827371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klaper, Rebecca D.","contributorId":218114,"corporation":false,"usgs":false,"family":"Klaper","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":827372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":827373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":827374,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70222679,"text":"ofr20211030D - 2021 - System characterization report on Planet’s Dove-R","interactions":[{"subject":{"id":70222679,"text":"ofr20211030D - 2021 - System characterization report on Planet’s Dove-R","indexId":"ofr20211030D","publicationYear":"2021","noYear":false,"chapter":"D","displayTitle":"System Characterization Report on Planet’s Dove-R","title":"System characterization report on Planet’s Dove-R"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2021-08-25T20:34:50.342041","indexId":"ofr20211030D","displayToPublicDate":"2021-08-09T14:39:33","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"D","displayTitle":"System Characterization Report on Planet’s Dove-R","title":"System characterization report on Planet’s Dove-R","docAbstract":"<h1>Executive Summary</h1><p>This report addresses system characterization of Planet’s Dove-R and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.</p><p>Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 4-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at <a data-mce-href=\"https://www.planet.com/\" href=\"https://www.planet.com/\">https://www.planet.com/</a>.</p><p>The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Dove-R has an interior geometric performance in the range of −0.306 (−0.102 pixel) to 0.286 m (0.095 pixel) in easting and 0.090 (0.030 pixel) to 1.084 m (0.361 pixel) in northing in band-to-band registration, an exterior geometric performance of −5.10 m (−0.51 pixel) in easting and 3.30 m (0.33 pixel) in northing offset in comparison to Sentinel-2, a radiometric performance in the range of −0.023 to −0.008 in offset and 0.948 to 1.077 in slope, and a spatial performance in the range of 2.96 to 3.15 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.001 to 0.003.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030D","usgsCitation":"Kim, M., Park, S., Anderson, C., and Stensaas, G.L., 2021, System characterization report on Planet’s Dove-R, chap. D <i>of</i>  Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 34 p., https://doi.org/10.3133/ofr20211030D.","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-126678","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":387784,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/d/ofr20211030d.pdf","text":"Report","size":"3.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030D"},{"id":387783,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/d/coverthb.jpg"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a> <br>U.S. Geological Survey<br>47914 252nd Street <br>Sioux Falls, SD 57198</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>System Description</li><li>Procedures</li><li>Measurements</li><li>Analysis</li><li>Summary and Conclusions</li><li>Selected References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-08-09","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":820804,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":820805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":820806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":820807,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70223380,"text":"70223380 - 2021 - Integrating telemetry data at several scales with spatial capture–recapture to improve density estimates","interactions":[],"lastModifiedDate":"2021-08-25T13:01:10.970191","indexId":"70223380","displayToPublicDate":"2021-08-09T07:59:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Integrating telemetry data at several scales with spatial capture–recapture to improve density estimates","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Accurate population estimates are essential for monitoring and managing wildlife populations. Mark–recapture sampling methods have regularly been used to estimate population parameters for rare and cryptic species, including the federally listed Mojave desert tortoise (<i>Gopherus agassizii</i>); however, the methods employed are often plagued by violations of statistical assumptions, which have the potential to bias density estimates. By incorporating spatial information into conventional density estimation models, spatial capture–recapture (SCR) models can account for common assumption violations such as spatially heterogeneous detection probabilities and temporary emigration when animals leave plots during a survey. We conducted mark–recapture surveys at 10 1-km<sup>2</sup><span>&nbsp;</span>plots in and adjacent to the Ivanpah Valley of California and Nevada from 2015 to 2019. Locality data were collected concurrently using radio-telemetry and GPS data loggers. GPS data demonstrated that desert tortoises frequently exhibited temporary emigration outside a plot during the survey periods, thereby complicating standard approaches for closed-model density estimation. We integrated mark–recapture survey data for subadults and adults at each plot with corresponding spatial capture locations and supplementary spatial data using a modified SCR model fitted in a Bayesian framework. We compared density estimates modeled with conventional non-spatial methods, as well as three SCR models based on symmetrical usage areas described by various levels and types of supplementary spatial data. The conventional model consistently resulted in inflated estimates of density while the SCR models allowed us to generate spatially corrected estimates for a species where detectability and densities are low. However, we found that if not properly specified, the temporal scale of supplementary data may result in an unintended source of bias in parameter estimates. Integrating spatial data over a larger temporal scale than mark–recapture surveys were conducted resulted in higher detection probabilities and lower density estimates, due to an overestimation of space use. Our results not only demonstrate the importance of accounting for spatial information but also the value of understanding the potential for bias when integrating multiple data sets at different temporal resolutions. The methods presented can be used to enhance monitoring efforts for the Mojave desert tortoise and other species where mark–recapture methods are used.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3689","usgsCitation":"Mitchell, C.I., Shoemaker, K.T., Esque, T., Vandergast, A.G., Hromada, S.J., Dutcher, K.E., Heaton, J.S., and Nussear, K.E., 2021, Integrating telemetry data at several scales with spatial capture–recapture to improve density estimates: Ecosphere, v. 12, no. 8, e03689, 23 p., https://doi.org/10.1002/ecs2.3689.","productDescription":"e03689, 23 p.","ipdsId":"IP-127713","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451246,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3689","text":"Publisher Index Page"},{"id":388475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.587158203125,\n              35.092945313732635\n            ],\n            [\n              -114.730224609375,\n              35.092945313732635\n            ],\n            [\n              -114.730224609375,\n              35.782170703266075\n            ],\n            [\n              -115.587158203125,\n              35.782170703266075\n            ],\n            [\n              -115.587158203125,\n              35.092945313732635\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Corey I","contributorId":245149,"corporation":false,"usgs":false,"family":"Mitchell","given":"Corey","email":"","middleInitial":"I","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shoemaker, Kevin T. 0000-0002-3789-3856","orcid":"https://orcid.org/0000-0002-3789-3856","contributorId":255290,"corporation":false,"usgs":false,"family":"Shoemaker","given":"Kevin","email":"","middleInitial":"T.","affiliations":[{"id":51513,"text":"Department of Natural Resources and Environmental Science, University of Nevada, Reno. 1664 N Virginia St, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":821892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":821894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821895,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dutcher, Kirsten E.","contributorId":221063,"corporation":false,"usgs":false,"family":"Dutcher","given":"Kirsten","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821896,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heaton, Jill S.","contributorId":175155,"corporation":false,"usgs":false,"family":"Heaton","given":"Jill","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":821897,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Kenneth E.","contributorId":117361,"corporation":false,"usgs":false,"family":"Nussear","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":821898,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70223216,"text":"70223216 - 2021 - Holocene hydroclimatic reorganizations in northwest Canada inferred from lacustrine carbonate oxygen isotopes","interactions":[],"lastModifiedDate":"2021-08-18T12:54:03.5729","indexId":"70223216","displayToPublicDate":"2021-08-09T07:50:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Holocene hydroclimatic reorganizations in northwest Canada inferred from lacustrine carbonate oxygen isotopes","docAbstract":"<div class=\"article-section__content en main\"><p>Sub-centennial oxygen (<i>δ</i><sup>18</sup>O) isotopes of ostracod and authigenic calcite from Squanga Lake provides evidence of hydroclimatic extremes and a series of post-glacial climate system reorganizations for the interior region of northwest Canada. Authigenic calcite<span>&nbsp;</span><i>δ</i><sup>18</sup>O values range from −16‰ to −21‰ and are presently similar to modern lake water and annual precipitation values. Ostracod<span>&nbsp;</span><i>δ</i><sup>18</sup>O record near identical trends with calcite, offset by +1.7&nbsp;±&nbsp;0.6‰. At 11&nbsp;ka BP (kaBP&nbsp;=&nbsp;thousands of years before 1950), higher<span>&nbsp;</span><i>δ</i><sup>18</sup>O values reflect decreased precipitation−evaporation (P−E) balance from residual ice sheet influences on moisture availability. A trend to lower<span>&nbsp;</span><i>δ</i><sup>18</sup>O values until ∼8&nbsp;ka BP reflects a shift to wetter conditions, and reorganization of atmospheric circulation. The last millennium and modern era are relatively dry, though not as dry as the early Holocene extreme. North Pacific climate dynamics remained an important driver of P−E balance in northwest Canada throughout the Holocene.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL092948","usgsCitation":"Lasher, G.E., Abbott, M.B., Anderson, L., Yasarer, L., Rosenheimer, M., and Finney, B., 2021, Holocene hydroclimatic reorganizations in northwest Canada inferred from lacustrine carbonate oxygen isotopes: Geophysical Research Letters, v. 48, no. 16, e2021GL092948, 9 p., https://doi.org/10.1029/2021GL092948.","productDescription":"e2021GL092948, 9 p.","ipdsId":"IP-126880","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":499920,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/63019564c9524c3bb5db5f48dbd19357","text":"External Repository"},{"id":388093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Yukon Territory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -140.80078125,\n              60.37042901631508\n            ],\n            [\n              -139.482421875,\n              60.108670463036\n            ],\n            [\n              -123.662109375,\n              59.84481485969105\n            ],\n            [\n              -124.71679687499999,\n              61.01572481397616\n            ],\n            [\n              -126.65039062499999,\n              60.88770004207789\n            ],\n            [\n              -126.91406249999999,\n              61.48075950007598\n            ],\n            [\n              -129.111328125,\n              62.2679226294176\n            ],\n            [\n              -129.990234375,\n              63.78248603116502\n            ],\n            [\n              -132.099609375,\n              64.84893726357947\n            ],\n            [\n              -132.1875,\n              65.5129625532949\n            ],\n            [\n              -132.890625,\n              66.01801815922045\n            ],\n            [\n              -133.505859375,\n              66.12496236487968\n            ],\n            [\n              -133.9453125,\n              66.99884379185184\n            ],\n            [\n              -135.35156249999997,\n              67.06743335108298\n            ],\n            [\n              -136.93359375,\n              68.84766505841037\n            ],\n            [\n              -140.44921875,\n              69.65708627301174\n            ],\n            [\n              -141.240234375,\n              69.68761843185617\n            ],\n            [\n              -140.80078125,\n              60.37042901631508\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"48","issue":"16","noUsgsAuthors":false,"publicationDate":"2021-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Lasher, G. 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