{"pageNumber":"417","pageRowStart":"10400","pageSize":"25","recordCount":184609,"records":[{"id":70227379,"text":"70227379 - 2022 - Biocrusts mediate a new mechanism for land degradation under a changing climate","interactions":[],"lastModifiedDate":"2022-01-25T17:43:08.984081","indexId":"70227379","displayToPublicDate":"2022-01-10T06:58:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Biocrusts mediate a new mechanism for land degradation under a changing climate","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Global concerns for desertification have focused on the slow recovery of extensive and expanding drylands following disturbance, which may be exacerbated by climate change. Biological soil crusts (biocrusts) are photosynthetic soil communities found in drylands worldwide, which are central to the stability and resilience of dryland ecosystems, but vulnerable to global change. Here we use multiple decade-long experiments to investigate the consequences of climate and land-use change on biocrusts and soil stability. Biocrusts recovered rapidly under ambient temperatures but warming interacted with the precipitation disturbance to halt recovery. Moreover, warming alone caused losses of mosses, lichens and soil stability. Our results present a new mechanism contributing to land degradation in drylands whereby warming drives a state shift in biocrust communities, which degrades soil stability. The synergistic effects of climate and land-use change co-occur globally and our results support projections of increased desertification and lowered dryland resilience under warming.</p></div></div>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41558-021-01249-6","usgsCitation":"Phillips, M.L., McNellis, B.E., Howell, A.J., Lauria, C.M., Belnap, J., and Reed, S., 2022, Biocrusts mediate a new mechanism for land degradation under a changing climate: Nature Climate Change, v. 12, p. 71-76, https://doi.org/10.1038/s41558-021-01249-6.","productDescription":"6 p.","startPage":"71","endPage":"76","ipdsId":"IP-133179","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":436005,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RUN1TP","text":"USGS data release","linkHelpText":"Data and software code from two long-term experiments (1996-2011 and 2005-2018) at three sites on the Colorado Plateau of North America"},{"id":394239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2022-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Phillips, Michala Lee 0000-0001-7005-8740","orcid":"https://orcid.org/0000-0001-7005-8740","contributorId":245186,"corporation":false,"usgs":true,"family":"Phillips","given":"Michala","email":"","middleInitial":"Lee","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNellis, Brandon E 0000-0001-9604-8727","orcid":"https://orcid.org/0000-0001-9604-8727","contributorId":271065,"corporation":false,"usgs":true,"family":"McNellis","given":"Brandon","email":"","middleInitial":"E","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauria, Cara Marie 0000-0001-8914-8041","orcid":"https://orcid.org/0000-0001-8914-8041","contributorId":271066,"corporation":false,"usgs":true,"family":"Lauria","given":"Cara","email":"","middleInitial":"Marie","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830675,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":830676,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70236989,"text":"70236989 - 2022 - Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale","interactions":[],"lastModifiedDate":"2022-09-27T11:54:09.921852","indexId":"70236989","displayToPublicDate":"2022-01-10T06:50:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0002\" class=\"abstract author\"><div id=\"abss0002\"><p id=\"spara010\">Predicting baseflow dynamics, protecting aquatic habitat, and managing legacy contaminants requires explicit characterization and prediction of groundwater discharge patterns throughout river networks. Using handheld thermal infrared (TIR) cameras, we surveyed 47&nbsp;km of stream length across the Farmington River watershed (1,570 km<sup>2</sup>; CT and MA, USA), mapping locations of bank and waterline groundwater discharges based on their thermal signature. Using the observed groundwater discharge locations and predicted groundwater discharge rates from 6 variations of a numerical groundwater-flow model (MODFLOW-NWT), we compared 1) predicted groundwater-discharge rates in areas with and without observed groundwater discharge, 2) spatial patterns of observed and predicted groundwater discharge locations, and 3) density of observed groundwater discharge locations with predicted discharge rates. Five of six models reasonably predicted the spatial patterns of discharge locations along the 5th order mainstem, but fewer models predicted groundwater discharge patterns in smaller streams. Our results highlight 1) the feasibility of using TIR observations to evaluate groundwater models, 2) model parameters that influence discharge prediction accuracy (riverbed sediment and bedrock hydraulic conductivity and river-aquifer connections), and 3) current strengths and future opportunities for improved modeling of groundwater-discharge patterns.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2021.104108","usgsCitation":"Barclay, J.R., Briggs, M., Moore, E., Starn, J., Hanson, A.E., and Helton, A., 2022, Where groundwater seeps: Evaluating modeled groundwater discharge patterns with thermal infrared surveys at the river-network scale: Advances in Water Resources, v. 106, 104108, 14 p., https://doi.org/10.1016/j.advwatres.2021.104108.","productDescription":"104108, 14 p.","ipdsId":"IP-130356","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":467206,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.advwatres.2021.104108","text":"Publisher Index Page"},{"id":436006,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EIV8L5","text":"USGS data release","linkHelpText":"Thermal Infrared images and field data on areas of groundwater discharge in the Farmington River watershed"},{"id":407389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts","otherGeospatial":"Farmington River Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.13323974609374,\n              41.70982942509964\n            ],\n            [\n              -72.4053955078125,\n              41.70982942509964\n            ],\n            [\n              -72.4053955078125,\n              42.27730877423709\n            ],\n            [\n              -73.13323974609374,\n              42.27730877423709\n            ],\n            [\n              -73.13323974609374,\n              41.70982942509964\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"106","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":852942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Eric","contributorId":216658,"corporation":false,"usgs":false,"family":"Moore","given":"Eric","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":852943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starn, J. Jeffrey 0000-0001-5909-0010 jjstarn@usgs.gov","orcid":"https://orcid.org/0000-0001-5909-0010","contributorId":1916,"corporation":false,"usgs":true,"family":"Starn","given":"J. Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":852944,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Ann E.H.","contributorId":296947,"corporation":false,"usgs":false,"family":"Hanson","given":"Ann","email":"","middleInitial":"E.H.","affiliations":[],"preferred":false,"id":852945,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Helton, Ashley","contributorId":219741,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":852946,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70227375,"text":"70227375 - 2022 - Species-specific responses to landscape features shaped genomic structure within Alaska galliformes","interactions":[],"lastModifiedDate":"2022-02-15T16:25:54.67058","indexId":"70227375","displayToPublicDate":"2022-01-08T07:14:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Species-specific responses to landscape features shaped genomic structure within Alaska galliformes","docAbstract":"<h3 id=\"jbi14294-sec-0001-title\" class=\"article-section__sub-title section1\">Aim</h3><p>Connectivity is vital to the resiliency of populations to environmental change and stochastic events, especially for cold-adapted species as Arctic and alpine tundra habitats retract as the climate warms. We examined the influence of past and current landscapes on genomic connectivity in cold-adapted galliformes as a critical first step to assess the vulnerability of Alaska ptarmigan and grouse to environmental change. We hypothesize that the mosaic of physical features and habitat within Alaska promoted the formation of genetic structure across species.</p><h3 id=\"jbi14294-sec-0002-title\" class=\"article-section__sub-title section1\">Location</h3><p>Alaska, United States of America.</p><h3 id=\"jbi14294-sec-0003-title\" class=\"article-section__sub-title section1\">Taxa</h3><p>Ptarmigan and Grouse (Galliformes: Tetraoninae).</p><h3 id=\"jbi14294-sec-0004-title\" class=\"article-section__sub-title section1\">Methods</h3><p>We collected double digest restriction-site-associated DNA sequence data from six ptarmigan and grouse species (<i>N</i>&nbsp;=&nbsp;13–145/species) sampled across multiple ecosystems up to ~10 degrees of latitude. Spatial genomic structure was analysed using methods that reflect different temporal scales: (1) principal components analysis to identify major trends in the distribution of genomic variation; (2) maximum likelihood clustering analyses to test for the presence of multiple genomic groupings; (3) shared co-ancestry analyses to assess contemporary relationships and (4) effective migration surfaces to identify regions that deviate from a null model of isolation by distance.</p><h3 id=\"jbi14294-sec-0005-title\" class=\"article-section__sub-title section1\">Results</h3><p>Levels of genomic structure varied across species (Φ<sub>ST</sub>&nbsp;=0.009–0.042). Three general patterns of structure emerged: (1) east-west partition located near the Yukon-Tanana uplands; (2) north-south split coinciding with the Alaska Range and (3) northern group near the Brooks Range. Species-specific patterns were observed; not all landscape features were barriers to gene flow for all ptarmigan and grouse and temporal contrasts were detected at the Brooks Range.</p><h3 id=\"jbi14294-sec-0006-title\" class=\"article-section__sub-title section1\">Main conclusions</h3><p>Within Alaska galliformes, patterns of genomic structure coincide with physiographic features and highlight the importance of physical and ecological barriers in shaping how genomic diversity is arrayed across the landscape. Lack of concordance in spatial patterns indicates that species behaviour and habitat affinities play key roles in driving the contrasting patterns of genomic structure.</p>","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14294","usgsCitation":"Sonsthagen, S.A., Wilson, R.E., and Talbot, S.L., 2022, Species-specific responses to landscape features shaped genomic structure within Alaska galliformes: Journal of Biogeography, v. 49, no. 2, p. 261-273, https://doi.org/10.1111/jbi.14294.","productDescription":"13 p.","startPage":"261","endPage":"273","ipdsId":"IP-119634","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":449226,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jbi.14294","text":"Publisher Index Page"},{"id":436007,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DDB01R","text":"USGS data release","linkHelpText":"Genomic 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Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":830649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Robert E. 0000-0003-1800-0183 rewilson@usgs.gov","orcid":"https://orcid.org/0000-0003-1800-0183","contributorId":5718,"corporation":false,"usgs":true,"family":"Wilson","given":"Robert","email":"rewilson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science 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,{"id":70227296,"text":"ofr20211030E - 2022 - System characterization report on Planet SkySat","interactions":[{"subject":{"id":70227296,"text":"ofr20211030E - 2022 - System characterization report on Planet SkySat","indexId":"ofr20211030E","publicationYear":"2022","noYear":false,"chapter":"E","displayTitle":"System Characterization Report on Planet SkySat","title":"System characterization report on Planet SkySat"},"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":"2022-01-07T16:46:40.809608","indexId":"ofr20211030E","displayToPublicDate":"2022-01-07T11:15:00","publicationYear":"2022","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":"E","displayTitle":"System Characterization Report on Planet SkySat","title":"System characterization report on Planet SkySat","docAbstract":"<p>This report addresses system characterization of Planet’s SkySat 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>SkySat is a constellation of submeter resolution Earth observation satellites providing analytics services, high-definition video, and imagery. The goal for the constellation is to capture multiple daily repeats of high-resolution imagery over any spot on the Earth. As of September 2020, 21 SkySat satellites have been launched, and the first launch occurred in November 2013. 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 href=\"https://www.planet.com/\" data-mce-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 SkySat has an interior geometric performance in the range of a 0.38- (0.47 pixel) to 0.75-meter (m; 0.93 pixel) root mean square error in easting and a 0.27- (0.33 pixel) to 0.55-m (0.68 pixel) root mean square error in northing, in band-to-band registration; an exterior geometric performance in the range of 0.26 (0.32 pixel) to 1.04 m (1.28 pixels) offset in comparison to ground control points; a radiometric performance in the range of 0.033 to 0.797 (linear regression); and a spatial performance in the range of 3.7 to 4.3 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.004 to 0.009.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System characterization of Earth observation sensors","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030E","usgsCitation":"Kim, M., Park, S., Sampath, A., Anderson, C., and Stensaas, G.L., 2022, System characterization report on Planet SkySat, chap. E <em>of</em> Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030E.","productDescription":"iv, 17 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126680","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":394021,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/e/coverthb.jpg"},{"id":394022,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/e/ofr20211030e.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-E"}],"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 (EROS) Center</a><br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>System Description</li><li>Standardized Procedures</li><li>Measurements and Results Summary</li><li>Analysis</li><li>Summary and Conclusions</li><li>Selected References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-01-07","noUsgsAuthors":false,"publicationDate":"2022-01-07","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":830348,"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":830349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sampath, Aparajithan 0000-0002-6922-4913 asampath@usgs.gov","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":3622,"corporation":false,"usgs":true,"family":"Sampath","given":"Aparajithan","email":"asampath@usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":830350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":830351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":830352,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70230242,"text":"70230242 - 2022 - Long-term ocean observing for international capacity development around tsunami early warning","interactions":[],"lastModifiedDate":"2022-04-05T14:43:38.626768","indexId":"70230242","displayToPublicDate":"2022-01-07T09:27:49","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Long-term ocean observing for international capacity development around tsunami early warning","docAbstract":"<p>The 2004 magnitude (M) 9.1 Sumatra-Andaman Islands earthquake in the Indian Ocean triggered the deadliest tsunami ever, killing more than 230,000 people. In response, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) established three additional Intergovernmental Coordination Groups (ICGs) for the Tsunami and Other Coastal Hazards Early Warning System: for the Caribbean and Adjacent Regions (ICG/CARIBE-EWS), for the Indian Ocean, and for the Northeastern Atlantic, Mediterranean, and Connected Seas. Along with the ICG for the Pacific Ocean, which was established in 1965, one of the goals of the new ICGs was to improve earthquake and tsunami monitoring and early warning. This need was further demonstrated by the 2011 Great East Japan (Tōhoku-oki) earthquake and tsunami, which killed more than 20,000 people, and other destructive tsunamis that occurred in the Solomon Islands, Samoa, Tonga, Chile, Indonesia, and Peru.</p><p>In response to the call to action by the UN Decade of Ocean Science for Sustainable Development (2021–2030), as well as the desired safe ocean outcome (von Hillebrandt-Andrade et al., 2021), the Intergovernmental Oceanographic Commission (IOC) of UNESCO approved the Ocean Decade Tsunami Programme in June 2021. One of its goals is to develop the capability to issue actionable alerts for tsunamis from all sources with minimum uncertainty within 10 minutes (Angove et&nbsp;al., 2019). While laudable, this goal presents complexities. Currently, warning depends on quick detection as well as the location and initial magnitude estimates of an earthquake that may generate a tsunami. Other factors that affect tsunamis, such as the faulting mechanism (how the faults slide past each other) and areal extent of the earthquake, currently take at least 20–30 minutes to forecast and are still subject to large uncertainties. Hence, agencies charged with tsunami early warning need to broadcast public alerts within minutes after an earthquake occurs but may struggle to meet this 10-minute goal without further technological advances, some of which are outlined in this article.</p><p>To reduce loss of life through adequate tsunami warning requires global ocean-based seismic, sea level, and geodetic initiatives to detect high-impact earthquakes and tsunamis, combined with sufficient communication and education so that people know how to respond when they receive alerts and warnings. The United Nations International Strategy for Disaster Reduction defines an early warning system as “a set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities, and organizations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss” (UNISDR, 2012). In short, a successful early warning system requires technology coupled with human factors (Kelman and Glantz, 2014).</p><p>In this article, we explore case studies from Japan and Canada, where scientists are leading the way in incorporating ocean observing capabilities in their early warning systems. We also explore advancements and challenges in the Caribbean, an area with a complex tectonic environment that would benefit greatly from increased global ocean observing capabilities. We also explore physical and social science interventions necessary to reduce loss of life.</p>","language":"English","publisher":"The Oceanography Society","doi":"10.5670/oceanog.2021.supplement.02-27","usgsCitation":"Sumy, D.F., McBride, S., von Hillebrandt-Andrade, C., Kohler, M.D., Orcutt, J., Kodaira, S., Moran, K., McNamara, D., Hori, T., Vanacore, E., Pirenne, B., and Collins, J., 2022, Long-term ocean observing for international capacity development around tsunami early warning: Oceanography, v. 34, no. 4, p. 70-77, https://doi.org/10.5670/oceanog.2021.supplement.02-27.","productDescription":"8 p.","startPage":"70","endPage":"77","ipdsId":"IP-135818","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":449228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2021.supplement.02-27","text":"Publisher Index 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jcollins@whoi.edu","contributorId":177449,"corporation":false,"usgs":false,"family":"Collins","given":"John A.","email":"jcollins@whoi.edu","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":839640,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70227471,"text":"70227471 - 2022 - Analytical assessments in support of the U.S. Fish and Wildlife Service 3-bat species status assessment","interactions":[],"lastModifiedDate":"2022-01-19T13:28:43.787648","indexId":"70227471","displayToPublicDate":"2022-01-07T07:25:46","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Analytical assessments in support of the U.S. Fish and Wildlife Service 3-bat species status assessment","docAbstract":"<p><span>Beginning in February of 2020, researchers and staff of the United States Geological Survey (USGS), Bat Conservation International (BCI), Virginia Polytechnic Institute and State University, and Montana State University associated with the North American Bat Monitoring Program (NABat) collaborated with the United States Fish and Wildlife Service (USFWS) to provide technical assistance in support of the USFWS Three Bat Species Status Assessments (SSA) including the little brown bat (MYLU, Myotis lucifugus), northern long-eared bat (MYSE, Myotis septentrionalis), and tricolored bat (PESU, Perimyotis subflavus). Analytical support for the SSA was not intended to provide interpretive results, which should therefore be considered beyond the scope of this report. Technical assistance for the SSA included facilitating the USFWS data call by educating and working directly with data contributors to manage, submit, and archive a variety of bat monitoring data in the online NABat database1 using standardized data submission templates accessible through the upload features on the NABat website. Most data collected through the USFWS data call for the SSA were submitted and stored in the NABat database. These represent the efforts of hundreds of partnering organizations across more than 200 individual NABat Partner Portal Projects. A few organizations contributed data for use in these analyses that were not submitted to the NABat database. Records submitted in response to the USFWS data call included bat capture, stationary and mobile acoustic, and internal roost count data (winter and summer). Data collated in the NABat database and used for the analyses described herein are documented (NABat 2020a, NABat 2020b, NABat 2021) and available through the NABat third party request feature.</span><br></p>","language":"English","publisher":"U.S. Fish and Wildlife","doi":"10.7944/P9B4RWEU","usgsCitation":"2022, Analytical assessments in support of the U.S. Fish and Wildlife Service 3-bat species status assessment, iv, 272 p., https://doi.org/10.7944/P9B4RWEU.","productDescription":"iv, 272 p.","ipdsId":"IP-135871","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":436011,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YG45TG","text":"USGS data release","linkHelpText":"In Support of the U.S. Fish and Wildlife Service 3-Bat Species Status Assessment: Winter Colony Count Analysis"},{"id":436010,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W9OZU0","text":"USGS data release","linkHelpText":"In Support of the U.S. Fish and Wildlife Service 3-Bat Species Status Assessment: Summer Mobile Acoustic Transect Analysis"},{"id":436009,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97XVX22","text":"USGS data release","linkHelpText":"In Support of the U.S. Fish and Wildlife Service 3-Bat Species Status Assessment: Predicted Wind Take Allocated To Hibernacula Each Year Under Current and Future Scenarios"},{"id":436008,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V5H833","text":"USGS data release","linkHelpText":"In Support of the U.S. Fish and Wildlife Service 3-Bat Species Status Assessment: Wind Energy Influence"},{"id":394511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Straw, Bethany R. 0000-0001-9086-4600","orcid":"https://orcid.org/0000-0001-9086-4600","contributorId":271020,"corporation":false,"usgs":true,"family":"Straw","given":"Bethany","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":831064,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Martin, Jaclyn 0000-0001-7156-6448","orcid":"https://orcid.org/0000-0001-7156-6448","contributorId":271172,"corporation":false,"usgs":true,"family":"Martin","given":"Jaclyn","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":831147,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Reichard, Jonathan D.","contributorId":138946,"corporation":false,"usgs":false,"family":"Reichard","given":"Jonathan D.","affiliations":[{"id":6678,"text":"U.S. Fish and Wildlife Service, Alaska Maritime National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":831074,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":204260,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":831148,"contributorType":{"id":2,"text":"Editors"},"rank":4}]}}
,{"id":70227484,"text":"70227484 - 2022 - Dynamic Rupture TAG – The 2021 Ingredients Workshop – Stress Conditions (SCEC Project 21127)","interactions":[],"lastModifiedDate":"2022-01-19T13:23:36.273283","indexId":"70227484","displayToPublicDate":"2022-01-07T07:22:51","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Dynamic Rupture TAG – The 2021 Ingredients Workshop – Stress Conditions (SCEC Project 21127)","docAbstract":"<p>No abstract available.&nbsp;</p>","language":"English","publisher":"SCEC","usgsCitation":"Harris, R.A., and Barall, M., 2022, Dynamic Rupture TAG – The 2021 Ingredients Workshop – Stress Conditions (SCEC Project 21127), 11 p.","productDescription":"11 p.","ipdsId":"IP-136605","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":394510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":394499,"type":{"id":15,"text":"Index Page"},"url":"https://files.scec.org/s3fs-public/reports/2021/21127_report.pdf?d3yII_9DzEeYKFu.q0KWviwaTJ70Ait0"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":831145,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563 mbarall@usgs.gov","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":271197,"corporation":false,"usgs":true,"family":"Barall","given":"Michael","email":"mbarall@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":831146,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227460,"text":"70227460 - 2022 - gTOOLS, an open-source MATLAB program for processing high precision, relative gravity data for time-lapse gravity monitoring","interactions":[],"lastModifiedDate":"2022-01-18T13:22:54.043797","indexId":"70227460","displayToPublicDate":"2022-01-07T07:18:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"gTOOLS, an open-source MATLAB program for processing high precision, relative gravity data for time-lapse gravity monitoring","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>gTOOLS is an open-source software for the processing of relative gravity data. gTOOLS is available in MATLAB and as a compiled executable to be run under the free MATLAB Runtime Compiler. The software has been designed for time-lapse (temporal) gravity monitoring. Although programmed to read the Scintrex CG-5 and CG-6&nbsp;gravimeters&nbsp;output data files, it can be easily modified to read data files from other gravimeters. The software binds together single-task processing modules within a very simple&nbsp;</span>user interface<span>&nbsp;</span>that is based on one text file. Gravity processing involves three modules: (a) gravimeter calibration; (b) automatic processing of gravity data to find adjusted gravity differences; and (c) post processing of results. Each module is optional and runs independently from the others. Data processing includes (a) averaging out the measurements noise, and correction for solid Earth tides, and ocean loading, and residual instrumental drift, and (b) calculate the residual instrumental drift and gravity differences between the base station and monitoring sites, and their uncertainties, by a weighted least square analysis of the gravity data. The software allows the automatic processing of a gravity campaign spanning multiple days in a single run. The software is tested on gravity data from 2015 eruption at Cotopaxi volcano, Ecuador.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2021.105028","usgsCitation":"Battaglia, M., Calahorrano-Di Patre, A., and Flinders, A.F., 2022, gTOOLS, an open-source MATLAB program for processing high precision, relative gravity data for time-lapse gravity monitoring: Computers & Geosciences, v. 160, 105028, 11 p., https://doi.org/10.1016/j.cageo.2021.105028.","productDescription":"105028, 11 p.","ipdsId":"IP-128961","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449232,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cageo.2021.105028","text":"Publisher Index Page"},{"id":394450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"160","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":831029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calahorrano-Di Patre, Antonina","contributorId":224661,"corporation":false,"usgs":false,"family":"Calahorrano-Di Patre","given":"Antonina","email":"","affiliations":[{"id":40906,"text":"Simon Fraser University, BC, Canada","active":true,"usgs":false}],"preferred":false,"id":831035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flinders, Ashton F. 0000-0003-2483-4635","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":271052,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":831036,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227323,"text":"70227323 - 2022 - Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley","interactions":[],"lastModifiedDate":"2022-03-15T16:48:45.543671","indexId":"70227323","displayToPublicDate":"2022-01-07T07:12:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Concept</h3><p>California’s Central Valley provides critical habitat for migratory waterbirds, yet only 10% of naturally occurring wetlands remain. Competition for limited water supplies and climate change will impact the long-term viability of these intensively managed habitats.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>Forecast the distribution, abundance, and connectivity of surface water and managed wetland habitats, using 5 spatially explicit (270 m<sup>2</sup>) climate/land use/water prioritization scenarios. Mapping potential future dynamic flooded habitat used by waterbirds and other wetland-dependent wildlife to inform management decisions.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We integrated a climate-driven hydrologic water use model with a spatially explicit land change model, to examine stakeholder-driven scenarios of future land change, climate, and water use and their impacts on future habitat availability.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Declining water availability is the dominant driver of habitat loss across scenarios. The hot/dry scenarios showed the greatest declines in January flooded area by 2101—an important month for overwintering waterbirds. In contrast, higher water supplies in wet climates drive perennial cropland conversion and loss of potential habitat. Potential flooded cropland declined (25 and 33%) under warmer/wetter climate conditions due to this conversion to perennial crops, exposing habitat vulnerability.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusion</h3><p>Climate-driven loss of water availability had a greater impact on flooded habitat availability than land-use change. When combined, climate change and the conversion of potentially flooded cropland to perennial cropland will threaten future waterbird habitat particularly in January, the peak of the migratory bird season, even when habitat restoration goals are met. Stakeholder-informed scenario analysis can identify target areas for potential habitat change, vulnerability, and conservation.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-021-01398-1","usgsCitation":"Wilson, T., Matchett, E., Byrd, K.B., Conlisk, E., Reiter, M.E., Wallace, C., Flint, L.E., Flint, A.L., and Moritsch, M.M., 2022, Climate and land change impacts on future managed wetland habitat: A case study from California’s Central Valley: Landscape Ecology, v. 37, p. 861-881, https://doi.org/10.1007/s10980-021-01398-1.","productDescription":"21 p.","startPage":"861","endPage":"881","ipdsId":"IP-127595","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":394093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.29980468749999,\n              40.111688665595956\n            ],\n            [\n              -122.78320312499999,\n              39.9434364619742\n            ],\n            [\n              -122.607421875,\n              39.13006024213511\n            ],\n            [\n              -122.34374999999999,\n              38.20365531807149\n            ],\n            [\n              -121.59667968749999,\n              37.125286284966805\n            ],\n            [\n              -120.41015624999999,\n              35.92464453144099\n            ],\n            [\n              -118.95996093749999,\n              34.92197103616377\n            ],\n  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tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":830456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conlisk, Erin","contributorId":270185,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":830458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reiter, Matthew E. 0000-0002-0587-786X","orcid":"https://orcid.org/0000-0002-0587-786X","contributorId":271031,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":56258,"text":"Point Blue","active":true,"usgs":false}],"preferred":false,"id":830459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wallace, Cynthia 0000-0003-0001-8828 cwallace@usgs.gov","orcid":"https://orcid.org/0000-0003-0001-8828","contributorId":149179,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia","email":"cwallace@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830460,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830461,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830462,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moritsch, Monica Mei Jeen 0000-0002-3890-1264","orcid":"https://orcid.org/0000-0002-3890-1264","contributorId":225210,"corporation":false,"usgs":true,"family":"Moritsch","given":"Monica","email":"","middleInitial":"Mei Jeen","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":830463,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70227381,"text":"70227381 - 2022 - Stoneflies in the genus Lednia (Plecoptera: Nemouridae): Sentinels of climate change impacts on mountain stream biodiversity","interactions":[],"lastModifiedDate":"2022-04-26T12:00:22.972891","indexId":"70227381","displayToPublicDate":"2022-01-07T06:39:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Stoneflies in the genus Lednia (Plecoptera: Nemouridae): Sentinels of climate change impacts on mountain stream biodiversity","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Rapid recession of glaciers and snowfields is threatening the habitats of cold-water biodiversity worldwide. In many ice-sourced headwaters of western North America, stoneflies in the genus<span>&nbsp;</span><i>Lednia</i><span>&nbsp;</span>(Plecoptera: Nemouridae) are a prominent member of the invertebrate community. With a broad distribution in mountain streams and close ties to declining glacier cover,<span>&nbsp;</span><i>Lednia</i><span>&nbsp;</span>has emerged as a sentinel of climate change threats to high-elevation aquatic biodiversity.<span>&nbsp;</span><i>Lednia tumana</i>, which is endemic to Glacier National Park, USA and the surrounding mountains, is the most well-studied species in the genus and in 2019 became federally protected under the U.S. Endangered Species Act (ESA) due to climate-induced loss of meltwater habitats. Three other<span>&nbsp;</span><i>Lednia</i><span>&nbsp;</span>species have also been described, and like<span>&nbsp;</span><i>L. tumana</i>, each is endemic to a mountain region of western North America:<span>&nbsp;</span><i>Lednia sierra</i><span>&nbsp;</span>in the Sierra Nevada,<span>&nbsp;</span><i>Lednia borealis</i><span>&nbsp;</span>in the Cascade Range, and<span>&nbsp;</span><i>Lednia tetonica</i><span>&nbsp;</span>in the Teton Range. In this review, we provide a comprehensive overview of<span>&nbsp;</span><i>Lednia</i><span>&nbsp;</span>ecology, genetics, and physiology, with an emphasis on the conservation outlook for the group and species with similar headwater distributions. We highlight substantial progress made in the last decade to better understand the ecology and evolution of<span>&nbsp;</span><i>Lednia</i>, including the identification of 140<span>&nbsp;</span><i>Lednia-</i>containing streams (an increase from 12 streams in 2010), and a more complete understanding of the degree to which warming streams may imperil species in the genus. In light of the ESA listing of<span>&nbsp;</span><i>L. tumana</i>, we show that similar conservation threats likely face all extant<span>&nbsp;</span><i>Lednia</i><span>&nbsp;</span>species. However, substantial gaps in our knowledge remain, primarily centering around their distributions (and the potential for as yet undescribed species), life history, ecophysiology, and trophic ecology. We conclude by describing pressing questions for<span>&nbsp;</span><i>Lednia</i><span>&nbsp;</span>that when addressed will expand knowledge of the genus and its conservation as well as broader understanding of climate risks to mountain stream biodiversity worldwide.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10531-021-02344-y","usgsCitation":"Green, M.D., Tronstad, L., Giersch, J.J., Shah, A.A., Fallon, C.E., Blevins, E., Kai, T., Muhlfeld, C.C., Finn, D.S., and Hotaling, S., 2022, Stoneflies in the genus Lednia (Plecoptera: Nemouridae): Sentinels of climate change impacts on mountain stream biodiversity: Biodiversity and Conservation, v. 31, p. 353-377, https://doi.org/10.1007/s10531-021-02344-y.","productDescription":"25 p.","startPage":"353","endPage":"377","ipdsId":"IP-130086","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science 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Joseph 0000-0001-7818-3941 jgiersch@usgs.gov","orcid":"https://orcid.org/0000-0001-7818-3941","contributorId":198074,"corporation":false,"usgs":true,"family":"Giersch","given":"J.","email":"jgiersch@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":830690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shah, Alisha A. 0000-0002-8454-7905","orcid":"https://orcid.org/0000-0002-8454-7905","contributorId":271069,"corporation":false,"usgs":false,"family":"Shah","given":"Alisha","email":"","middleInitial":"A.","affiliations":[{"id":56265,"text":"Division of Biological Sciences, University of Montana, Missoula, MT, USA","active":true,"usgs":false}],"preferred":false,"id":830691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fallon, Candace E. 0000-0002-6100-6436","orcid":"https://orcid.org/0000-0002-6100-6436","contributorId":271070,"corporation":false,"usgs":false,"family":"Fallon","given":"Candace","email":"","middleInitial":"E.","affiliations":[{"id":56266,"text":"The Xerces Society for Invertebrate Conservation, Portland, OR, USA","active":true,"usgs":false}],"preferred":false,"id":830692,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blevins, Emilie","contributorId":211792,"corporation":false,"usgs":false,"family":"Blevins","given":"Emilie","email":"","affiliations":[{"id":38320,"text":"Xerxes Society, OR","active":true,"usgs":false}],"preferred":false,"id":830693,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kai, Taylor","contributorId":271071,"corporation":false,"usgs":false,"family":"Kai","given":"Taylor","email":"","affiliations":[{"id":56267,"text":"College of Medicine, University of Kentucky, Lexington, KY, USA","active":true,"usgs":false}],"preferred":false,"id":830694,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":830695,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Finn, Debra S.","contributorId":198312,"corporation":false,"usgs":false,"family":"Finn","given":"Debra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":830696,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hotaling, Scott 0000-0002-5965-0986","orcid":"https://orcid.org/0000-0002-5965-0986","contributorId":176860,"corporation":false,"usgs":false,"family":"Hotaling","given":"Scott","email":"","affiliations":[],"preferred":false,"id":830697,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70228524,"text":"70228524 - 2022 - Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2022-07-07T16:38:12.50761","indexId":"70228524","displayToPublicDate":"2022-01-07T06:37:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem","docAbstract":"<ol class=\"\"><li>Predators may create healthier prey populations by selectively removing diseased individuals. Predators typically prefer some ages of prey over others, which may, or may not, align with those prey ages that are most likely to be diseased.</li><li>The interaction of age-specific infection and predation has not been previously explored and likely has sizable effects on disease dynamics. We hypothesize that predator cleansing effects will be greater when the disease and predation occur in the same prey age groups.</li><li>We examine the predator cleansing effect using a model where both vulnerability to predators and pathogen prevalence vary with age. We tailor this model to chronic wasting disease (CWD) in mule deer and elk populations in the Greater Yellowstone Ecosystem, with empirical data from Yellowstone grey wolves and cougars.</li><li>Model results suggest that under moderate, yet realistic, predation pressure from cougars and wolves independently, predators may decrease CWD outbreak size substantially and delay the accumulation of symptomatic deer and elk. The magnitude of this effect is driven by the ability of predators to selectively remove late-stage CWD infections that are likely the most responsible for transmission, but this may not be the age class they typically select. Thus, predators that select for infected young adults over uninfected juveniles have a stronger cleansing effect, and these effects are strengthened when transmission rates increase with increasing prey morbidity. There are also trade-offs from a management perspective—that is, increasing predator kill rates can result in opposing forces on prey abundance and CWD prevalence.</li><li>Our modelling exploration shows that predators have the potential to reduce prevalence in prey populations when prey age and disease severity are considered, yet the strength of this effect is influenced by predators' selection for demography or body condition. Current CWD management focuses on increasing cervid hunting as the primary management tool, and our results suggest predators may also be a useful tool under certain conditions, but not necessarily without additional impacts on host abundance and demography. Protected areas with predator populations will play a large role in informing the debate over predator impacts on disease.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.13661","usgsCitation":"Brandell, E.E., Cross, P., Smith, D., Rogers, W.J., Galloway, N.L., MacNulty, D., Stahler, D.R., Treanor, J.J., and Hudson, P., 2022, Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem: Journal of Animal Ecology, v. 91, no. 7, p. 1373-1384, https://doi.org/10.1111/1365-2656.13661.","productDescription":"12 p.","startPage":"1373","endPage":"1384","ipdsId":"IP-127787","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":449236,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.13661","text":"Publisher Index Page"},{"id":436012,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93XICBO","text":"USGS data release","linkHelpText":"CWDsims version v0.2.2"},{"id":395837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.29150390625,\n              42.56926437219384\n            ],\n            [\n              -107.75390625,\n              42.56926437219384\n            ],\n            [\n              -107.75390625,\n              45.120052841530544\n            ],\n            [\n              -111.29150390625,\n              45.120052841530544\n            ],\n            [\n              -111.29150390625,\n              42.56926437219384\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"91","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Brandell, Ellen E.","contributorId":253140,"corporation":false,"usgs":false,"family":"Brandell","given":"Ellen","email":"","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":834503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":834504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Douglas W.","contributorId":179181,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas W.","affiliations":[],"preferred":false,"id":834505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, William J.","contributorId":173588,"corporation":false,"usgs":false,"family":"Rogers","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":834506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galloway, Nathan L.","contributorId":276042,"corporation":false,"usgs":false,"family":"Galloway","given":"Nathan","email":"","middleInitial":"L.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":834507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"MacNulty, Daniel R.","contributorId":179179,"corporation":false,"usgs":false,"family":"MacNulty","given":"Daniel R.","affiliations":[],"preferred":false,"id":834508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stahler, Daniel R.","contributorId":179180,"corporation":false,"usgs":false,"family":"Stahler","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":834509,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Treanor, John J.","contributorId":169528,"corporation":false,"usgs":false,"family":"Treanor","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":834510,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hudson, Peter J.","contributorId":253146,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":834511,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70227273,"text":"tm2A18 - 2022 - Protocol for installing and monitoring a RestoreNet restoration field trial network site","interactions":[],"lastModifiedDate":"2022-01-10T15:34:14.059259","indexId":"tm2A18","displayToPublicDate":"2022-01-06T12:21:49","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-A18","displayTitle":"Protocol for Installing and Monitoring a RestoreNet Restoration Field Trial Network Site","title":"Protocol for installing and monitoring a RestoreNet restoration field trial network site","docAbstract":"<p>RestoreNet is an ecological restoration experiment that is networked across multiple sites, spanning dryland ecosystems in the southwestern United States. The experiment is organized and led by the U.S. Geological Survey’s Restoration Assessment and Monitoring Program for the Southwest (RAMPS). This protocol functions to provide guidance to additional partners on how to set up a RestoreNet site and expand the network to new locations. This protocol contains information for site selection, materials acquisition, experiment installation, data collection and monitoring, and data curation. Information includes protocols for the RestoreNet seeded experiment and an additional optional experiment using installed container seedlings initially propagated in a greenhouse. Participation in RestoreNet contributes to a growing body of knowledge on cutting edge ecological restoration methods for use in the southwestern United States to benefit land managers, landowners, and restoration practitioners.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm2A18","collaboration":"Prepared in cooperation with Northern Arizona University","usgsCitation":"Laushman, K.M., McCormick, M.L., Munson, S.M., Balazs, K.R., and Butterfield, B.J., 2021, Protocol for installing and monitoring a RestoreNet restoration field trial network site: U.S. Geological Survey Techniques and Methods, book 2, chap. A18, 34 p., https://doi.org/10.3133/tm2A18.","productDescription":"vii, 34 p.","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-124290","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":393961,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/02/a18/covrthb.jpg"},{"id":393962,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/02/a18/tm2a18.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Texas, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.83984375,\n              32.84267363195431\n            ],\n            [\n              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      ]\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>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Site Design&nbsp;&nbsp;</li><li>Monitoring Protocol&nbsp;&nbsp;</li><li>Data Curation&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>Selected References&nbsp;&nbsp;</li><li>Appendix 1&nbsp;&nbsp;</li><li>Appendix 2&nbsp;&nbsp;</li><li>Appendix 3&nbsp;&nbsp;</li><li>Appendix 4&nbsp;&nbsp;</li><li>Appendix 5&nbsp;&nbsp;</li><li>Appendix 6&nbsp;&nbsp;</li><li>Appendix 7&nbsp;&nbsp;</li><li>Appendix 8&nbsp;&nbsp;</li><li>Appendix 9&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2022-01-06","noUsgsAuthors":false,"publicationDate":"2022-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Laushman, Katherine M. 0000-0002-4333-6386","orcid":"https://orcid.org/0000-0002-4333-6386","contributorId":229512,"corporation":false,"usgs":true,"family":"Laushman","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Molly L. 0000-0002-4361-7567 mmccormick@usgs.gov","orcid":"https://orcid.org/0000-0002-4361-7567","contributorId":196257,"corporation":false,"usgs":true,"family":"McCormick","given":"Molly","email":"mmccormick@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":830242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":830243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balazs, Kathleen R.","contributorId":223214,"corporation":false,"usgs":false,"family":"Balazs","given":"Kathleen","email":"","middleInitial":"R.","affiliations":[{"id":24810,"text":"Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":830244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butterfield, Bradley J.","contributorId":18096,"corporation":false,"usgs":true,"family":"Butterfield","given":"Bradley J.","affiliations":[],"preferred":false,"id":830245,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228939,"text":"70228939 - 2022 - The relative importance of mercury methylation and demethylation in rice paddy soil varies depending on the presence of rice plants","interactions":[],"lastModifiedDate":"2022-02-24T16:12:06.534218","indexId":"70228939","displayToPublicDate":"2022-01-06T10:04:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1480,"text":"Ecotoxicology and Environmental Safety","active":true,"publicationSubtype":{"id":10}},"title":"The relative importance of mercury methylation and demethylation in rice paddy soil varies depending on the presence of rice plants","docAbstract":"<p><span>Neurotoxic methylmercury (MeHg) accumulates in rice grain from paddy soil, where its concentration is controlled by microbial mercury methylation and demethylation. Both up- and down-regulation of methylation is known to occur in the presence of rice plants in comparison to non-vegetated paddy soils; the influence of rice plant presence/absence on demethylation is unknown. To assess the concurrent influence of rice plant presence/absence on methylation and demethylation, and to determine which process was more dominant in controlling soil MeHg concentrations, we maintained six rhizoboxes of paddy soil with and without rice plants. At the peak of plant growth, we simultaneously measured ambient MeHg, ambient inorganic mercury (IHg), and potential rate constants of methylation and demethylation (K</span><sub>meth</sub><span>&nbsp;and K</span><sub>demeth</sub><span>) in soil using stable isotope tracers and ID-GC-ICPMS. We also measured organic matter content, elemental S, and water-extractable sulfate. We found MeHg concentrations were differentially controlled by MeHg production and degradation processes, depending on whether plants were present. In non-vegetated boxes, MeHg concentration was controlled by K</span><sub>meth</sub><span>, as evidenced by a strong and positive correlation, while K</span><sub>demeth</sub><span>&nbsp;had no relation to MeHg concentration. These results indicate methylation was the dominant driver of MeHg concentration in non-vegetated soil. In vegetated boxes, K</span><sub>demeth</sub><span>&nbsp;strongly and negatively predicted MeHg concentration, indicating that demethylation was the dominant control in soil with plants. MeHg concentration, K</span><sub>meth</sub><span>, and % MeHg all had significantly less variance in vegetated than in non-vegetated soils due to a consistent elimination of greater values. This pattern suggests that reduced MeHg production capacity was a secondary control on MeHg concentrations in vegetated soils. We observed no difference in the magnitude or variance of K</span><sub>demeth</sub><span>&nbsp;between treatments, suggesting that demethylation was robust to soil chemical conditions influenced by the plant, perhaps because of a wider taxonomic diversity of demethylators. Our results suggest that methylation and demethylation processes could both be leveraged to alter MeHg concentrations in rice paddy soil.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoenv.2021.113143","usgsCitation":"Strickman, R.J., Larson, S.M., Huang, H., Kakouros, E., Marvin-DiPasquale, M.C., Mitchell, C.P., and Neumann, R.B., 2022, The relative importance of mercury methylation and demethylation in rice paddy soil varies depending on the presence of rice plants: Ecotoxicology and Environmental Safety, v. 230, 113143, 10 p., https://doi.org/10.1016/j.ecoenv.2021.113143.","productDescription":"113143, 10 p.","ipdsId":"IP-130664","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":449239,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoenv.2021.113143","text":"Publisher Index Page"},{"id":396427,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"230","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Strickman, R. J.","contributorId":280064,"corporation":false,"usgs":false,"family":"Strickman","given":"R.","email":"","middleInitial":"J.","affiliations":[{"id":27967,"text":"University of Washington, Seattle WA","active":true,"usgs":false}],"preferred":false,"id":835974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, S. M.","contributorId":36309,"corporation":false,"usgs":false,"family":"Larson","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":835975,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, H.","contributorId":280065,"corporation":false,"usgs":false,"family":"Huang","given":"H.","affiliations":[{"id":57416,"text":"University of Toronto Scarborough, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":835976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kakouros, Evangelos 0000-0002-4778-4039 kakouros@usgs.gov","orcid":"https://orcid.org/0000-0002-4778-4039","contributorId":2587,"corporation":false,"usgs":true,"family":"Kakouros","given":"Evangelos","email":"kakouros@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":835977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":835978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mitchell, C. P. J.","contributorId":280066,"corporation":false,"usgs":false,"family":"Mitchell","given":"C.","email":"","middleInitial":"P. J.","affiliations":[{"id":57416,"text":"University of Toronto Scarborough, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":835979,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neumann, R. B.","contributorId":280067,"corporation":false,"usgs":false,"family":"Neumann","given":"R.","email":"","middleInitial":"B.","affiliations":[{"id":27967,"text":"University of Washington, Seattle WA","active":true,"usgs":false}],"preferred":false,"id":835980,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70227283,"text":"70227283 - 2022 - Complete genome sequence of Rhodococcus opacus strain MoAcy1 (DSM 44186), an aerobic acetylenotroph isolated from soil","interactions":[],"lastModifiedDate":"2022-01-07T17:04:43.905159","indexId":"70227283","displayToPublicDate":"2022-01-06T08:27:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5813,"text":"Microbiology Resource Announcements","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Complete genome sequence of <i>Rhodococcus opacus</i> strain MoAcy1 (DSM 44186), an aerobic acetylenotroph isolated from soil","title":"Complete genome sequence of Rhodococcus opacus strain MoAcy1 (DSM 44186), an aerobic acetylenotroph isolated from soil","docAbstract":"<p><span>We report the genome of&nbsp;</span><span class=\"named-content\" data-type=\"genus-species\">Rhodococcus opacus</span><span>&nbsp;strain MoAcy1 (</span>DSM 44186<span>), an aerobic soil isolate capable of using acetylene as its primary carbon and energy source (acetylenotrophy). The genome is composed of a single circular chromosome of ∼8 Mbp and two closed plasmids, with a G+C content of 67.3%.</span></p>","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/MRA.00814-21","usgsCitation":"Sutton, J.M., Bushman, T., Akob, D., and Fierst, J.L., 2022, Complete genome sequence of Rhodococcus opacus strain MoAcy1 (DSM 44186), an aerobic acetylenotroph isolated from soil: Microbiology Resource Announcements, v. 11, no. 1, E00814-21, 2 p., https://doi.org/10.1128/MRA.00814-21.","productDescription":"E00814-21, 2 p.","ipdsId":"IP-132416","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":449242,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/mra.00814-21","text":"Publisher Index Page"},{"id":394016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sutton, John M.","contributorId":179294,"corporation":false,"usgs":false,"family":"Sutton","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":830266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bushman, Timothy J.","contributorId":270976,"corporation":false,"usgs":false,"family":"Bushman","given":"Timothy J.","affiliations":[{"id":56236,"text":"Department of Biological Sciences, The University of Alabama","active":true,"usgs":false}],"preferred":false,"id":830267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Akob, Denise M. 0000-0003-1534-3025","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":204701,"corporation":false,"usgs":true,"family":"Akob","given":"Denise M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":830268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fierst, Janna L.","contributorId":179295,"corporation":false,"usgs":false,"family":"Fierst","given":"Janna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":830269,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70238964,"text":"70238964 - 2022 - Introduction: Climate change in the mountains of Maine and the Northeast","interactions":[],"lastModifiedDate":"2022-12-19T13:26:10.36789","indexId":"70238964","displayToPublicDate":"2022-01-06T07:18:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Introduction: Climate change in the mountains of Maine and the Northeast","docAbstract":"<p id=\"ID0E2AAC\">No abstract available.&nbsp;</p>","language":"English","publisher":"BioOne","doi":"10.1656/045.028.s1111","usgsCitation":"Nelson, S., McDonough MacKenzie, C., Morelli, T.L., Wason, J., Wentzell, B., Hovel, R.A., Hodgkins, G.A., Miller-Rushing, A.J., Miller, D., Tatko, S., Cross, A., and Pounch, M., 2022, Introduction: Climate change in the mountains of Maine and the Northeast: Northeastern Naturalist, v. 28, no. 11, p. ii-ix, https://doi.org/10.1656/045.028.s1111.","productDescription":"10 p.","startPage":"ii","endPage":"ix","ipdsId":"IP-130303","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":410695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.4848699643923,\n              47.607085121892226\n            ],\n            [\n              -78.4848699643923,\n              41.01705361593531\n            ],\n            [\n              -66.53681906604862,\n              41.01705361593531\n           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Maine","active":true,"usgs":false}],"preferred":false,"id":859427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":859428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wason, Jay","contributorId":300108,"corporation":false,"usgs":false,"family":"Wason","given":"Jay","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":859429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wentzell, Bryan","contributorId":300109,"corporation":false,"usgs":false,"family":"Wentzell","given":"Bryan","email":"","affiliations":[{"id":65019,"text":"Maine Mountain Collaborative","active":true,"usgs":false}],"preferred":false,"id":859430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hovel, Rachel A.","contributorId":171740,"corporation":false,"usgs":false,"family":"Hovel","given":"Rachel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":859431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science 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,{"id":70227289,"text":"70227289 - 2022 - Mesilla / Conejos-Médanos Basin: U.S.-Mexico transboundary water resources and research needs","interactions":[],"lastModifiedDate":"2022-01-25T17:42:14.142072","indexId":"70227289","displayToPublicDate":"2022-01-06T07:16:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Mesilla / Conejos-Médanos Basin: U.S.-Mexico transboundary water resources and research needs","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Synthesizing binational data to characterize shared water resources is critical to informing binational management. This work uses binational hydrogeology and water resource data in the Mesilla/Conejos-Médanos Basin (Basin) to describe the hydrologic conceptual model and identify potential research that could help inform sustainable management. The Basin aquifer is primarily composed of continuous basin-fill Santa Fe Group sediments, allowing for transboundary throughflow. Groundwater flow, however, may be partially or fully restricted by intrabasin uplifts and limited recharge. The shallow groundwater in the Rio Grande alluvium receives recharge from the Rio Grande and responds to changes in water supply and demand. About 11% of Rio Grande alluvial groundwater volume is recharged annually, an amount that is less than recent withdrawals. Potentially recoverable fresh to slightly brackish groundwater was estimated at 82,600 cubic hectometers in the U.S. portion of the Basin and 69,100 cubic hectometers in the Mexican portion. Alluvial groundwater geochemistry is governed by the evaporative concentration of the Rio Grande and agricultural diversions, whereas deeper groundwater geochemistry is governed by mixing and geochemical processes. Continued refinements to storage estimates, the water budget, and deep groundwater extent and geochemistry can improve estimates of sustainable use and inform alternative water sources.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/w14020134","usgsCitation":"Robertson, A.J., Matherne, A., Pepin, J.D., Ritchie, A., Sweetkind, D., Teeple, A., Granados Olivas, A., Garcia Vasquez, A.C., Carroll, K.C., Fuchs, E.H., and Galanter, A.E., 2022, Mesilla / Conejos-Médanos Basin: U.S.-Mexico transboundary water resources and research needs: Water, v. 14, no. 2, p. 134-170, https://doi.org/10.3390/w14020134.","productDescription":"37 p.","startPage":"134","endPage":"170","ipdsId":"IP-132917","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science 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]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Andrew J. 0000-0003-2130-0347 ajrobert@usgs.gov","orcid":"https://orcid.org/0000-0003-2130-0347","contributorId":4129,"corporation":false,"usgs":true,"family":"Robertson","given":"Andrew","email":"ajrobert@usgs.gov","middleInitial":"J.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matherne, Anne-Marie 0000-0002-5873-2226","orcid":"https://orcid.org/0000-0002-5873-2226","contributorId":32279,"corporation":false,"usgs":true,"family":"Matherne","given":"Anne-Marie","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pepin, Jeff D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeff","email":"","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ritchie, Andre B. 0000-0003-1289-653X","orcid":"https://orcid.org/0000-0003-1289-653X","contributorId":205392,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andre B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":210808,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":830308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Teeple, Andrew 0000-0003-1781-8354 apteeple@usgs.gov","orcid":"https://orcid.org/0000-0003-1781-8354","contributorId":193061,"corporation":false,"usgs":true,"family":"Teeple","given":"Andrew","email":"apteeple@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830309,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Granados Olivas, Alfredo 0000-0002-8989-4420","orcid":"https://orcid.org/0000-0002-8989-4420","contributorId":270987,"corporation":false,"usgs":false,"family":"Granados Olivas","given":"Alfredo","email":"","affiliations":[{"id":56243,"text":"Universidad Autónoma de Ciudad Juárez","active":true,"usgs":false}],"preferred":false,"id":830310,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garcia Vasquez, Ana Cristina 0000-0003-4360-8545","orcid":"https://orcid.org/0000-0003-4360-8545","contributorId":270988,"corporation":false,"usgs":false,"family":"Garcia Vasquez","given":"Ana","email":"","middleInitial":"Cristina","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":830311,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carroll, Kenneth C. 0000-0003-2097-9589","orcid":"https://orcid.org/0000-0003-2097-9589","contributorId":247827,"corporation":false,"usgs":false,"family":"Carroll","given":"Kenneth","email":"","middleInitial":"C.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":830312,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fuchs, Erek H. 0000-0001-9170-9469","orcid":"https://orcid.org/0000-0001-9170-9469","contributorId":270989,"corporation":false,"usgs":false,"family":"Fuchs","given":"Erek","email":"","middleInitial":"H.","affiliations":[{"id":56244,"text":"Elephant Butte Irrigation District","active":true,"usgs":false}],"preferred":false,"id":830313,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830314,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70233604,"text":"70233604 - 2022 - Tectonostratigraphy and major structures of the Georgian Greater Caucasus: Implications for structural architecture, along-strike continuity, and orogen evolution","interactions":[],"lastModifiedDate":"2022-07-27T12:11:19.232869","indexId":"70233604","displayToPublicDate":"2022-01-06T07:08:51","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Tectonostratigraphy and major structures of the Georgian Greater Caucasus: Implications for structural architecture, along-strike continuity, and orogen evolution","docAbstract":"<div id=\"132358730\" class=\"article-section-wrapper js-article-section js-content-section  \"><p>Although the Greater Caucasus Mountains have played a central role in absorbing late Cenozoic convergence between the Arabian and Eurasian plates, the orogenic architecture and the ways in which it accommodates modern shortening remain debated. Here, we addressed this problem using geologic mapping along two transects across the southern half of the western Greater Caucasus to reveal a suite of regionally coherent stratigraphic packages that are juxtaposed across a series of thrust faults, which we call the North Georgia fault system. From south to north within this system, stratigraphically repeated ~5–10-km-thick thrust sheets show systematically increasing bedding dip angles (&lt;30° in the south to subvertical in the core of the range). Likewise, exhumation depth increases toward the core of the range, based on low-temperature thermochronologic data and metamorphic grade of exposed rocks. In contrast, active shortening in the modern system is accommodated, at least in part, by thrust faults along the southern margin of the orogen. Facilitated by the North Georgia fault system, the western Greater Caucasus Mountains broadly behave as an in-sequence, southward-propagating imbricate thrust fan, with older faults within the range progressively abandoned and new structures forming to accommodate shortening as the thrust propagates southward. We suggest that the single-fault-centric “Main Caucasus thrust” paradigm is no longer appropriate, as it is a system of faults, the North Georgia fault system, that dominates the architecture of the western Greater Caucasus Mountains.</p></div>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02385.1","usgsCitation":"Trexler, C.C., Cowgill, E., Niemi, N., Vasey, D.A., and Godoladze, T., 2022, Tectonostratigraphy and major structures of the Georgian Greater Caucasus: Implications for structural architecture, along-strike continuity, and orogen evolution: Geosphere, v. 18, no. 1, p. 211-240, https://doi.org/10.1130/GES02385.1.","productDescription":"30 p.","startPage":"211","endPage":"240","ipdsId":"IP-122971","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":449249,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02385.1","text":"Publisher Index Page"},{"id":404484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Georgia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              37.9248046875,\n              38.8225909761771\n            ],\n            [\n              48.8232421875,\n              38.8225909761771\n            ],\n            [\n              48.8232421875,\n              44.74673324024678\n            ],\n            [\n              37.9248046875,\n              44.74673324024678\n            ],\n            [\n              37.9248046875,\n              38.8225909761771\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Trexler, Charles Cashman 0000-0001-5046-9729","orcid":"https://orcid.org/0000-0001-5046-9729","contributorId":257823,"corporation":false,"usgs":true,"family":"Trexler","given":"Charles","email":"","middleInitial":"Cashman","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":847529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowgill, Eric","contributorId":192850,"corporation":false,"usgs":false,"family":"Cowgill","given":"Eric","affiliations":[],"preferred":false,"id":847530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niemi, Nathan A","contributorId":203251,"corporation":false,"usgs":false,"family":"Niemi","given":"Nathan A","affiliations":[{"id":36590,"text":"Dept. of Earth and Environmental Sciences, University of Michigan, Ann Arbor","active":true,"usgs":false}],"preferred":false,"id":847531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vasey, Dylan A 0000-0002-2182-4733","orcid":"https://orcid.org/0000-0002-2182-4733","contributorId":293645,"corporation":false,"usgs":false,"family":"Vasey","given":"Dylan","email":"","middleInitial":"A","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":847532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Godoladze, Tea","contributorId":293646,"corporation":false,"usgs":false,"family":"Godoladze","given":"Tea","email":"","affiliations":[{"id":63351,"text":"Ilia State University","active":true,"usgs":false}],"preferred":false,"id":847533,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70232130,"text":"70232130 - 2022 - Coastal paleogeography of the Pacific Northwest, USA, for the last 12,000 years accounting for three-dimensional earth structure","interactions":[],"lastModifiedDate":"2022-10-31T14:26:48.507141","indexId":"70232130","displayToPublicDate":"2022-01-06T06:43:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"Coastal paleogeography of the Pacific Northwest, USA, for the last 12,000 years accounting for three-dimensional earth structure","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Predictive modeling&nbsp;of submerged&nbsp;archaeological sites&nbsp;requires accurate sea-level predictions in order to reconstruct coastal&nbsp;paleogeography&nbsp;and associated geographic features that may have influenced the locations of occupation sites such as rivers and embayments. Earlier reconstructions of the paleogeography of parts of the western&nbsp;U.S.&nbsp;coast used an assumption of eustatic sea level, but this neglects the large spatial variations in relative sea level (RSL) associated with glacial isostatic adjustment (GIA) and tectonics. Subsequent work using a one-dimensional (1-D) solid Earth model showed that reconstructions that accounted for GIA result in significant differences from those based on eustatic sea level. However, these analyses neglected the complex three-dimensional (3-D) solid Earth structure associated with the Cascadia&nbsp;</span>subduction zone<span>&nbsp;that has also strongly influenced RSL along the Oregon-Washington (OR-WA) coast, requiring that the paleogeographic reconstructions must also account for this effect. Here we use RSL predictions from a 3-D solid Earth model that have been validated by RSL data to update previous paleogeographic reconstructions of the OR-WA coast for the last 12 kyr based on a 1-D solid Earth model. The large differences in the spatial variations in RSL on the OR-WA&nbsp;continental shelves&nbsp;predicted by the 3-D model relative to eustatic and 1-D models demonstrate that accurate reconstructions of coastal paleogeography for predictive modeling of submerged archaeological sites need to account for 3-D viscoelastic Earth structure in areas of complex tectonics.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2022.01.003","usgsCitation":"Clark, J., Alder, J.R., Borreggine, M., Mitrovica, J.X., and Latychev, K., 2022, Coastal paleogeography of the Pacific Northwest, USA, for the last 12,000 years accounting for three-dimensional earth structure: Quaternary International, v. 638-639, p. 197-204, https://doi.org/10.1016/j.quaint.2022.01.003.","productDescription":"8 p.","startPage":"197","endPage":"204","ipdsId":"IP-135421","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science 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,{"id":70227173,"text":"sir20215126 - 2022 - Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16","interactions":[],"lastModifiedDate":"2026-04-02T20:03:05.696911","indexId":"sir20215126","displayToPublicDate":"2022-01-05T16:40:00","publicationYear":"2022","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":"2021-5126","displayTitle":"Hydrology and Water Quality in 15 Watersheds in DeKalb County, Georgia, 2012–16","title":"Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16","docAbstract":"<p>The U.S. Geological Survey, in cooperation with DeKalb County Department of Watershed Management, established a long-term water-quantity and water-quality monitoring program in 2012 to monitor and analyze the hydrologic and water-quality conditions of 15 watersheds in DeKalb County, Georgia—an urban and suburban area located in north-central Georgia that includes the easternmost part of the City of Atlanta. This report synthesizes the watershed characteristics and monitoring data collected for the first 5 years of the program, 2012 through 2016. The study area was predominantly medium-density residential (43.9 percent), commercial/industrial/institutional (21.4 percent), forest/park/agriculture (13.6 percent), and high-density residential (11.5 percent) land uses. Land-surface slope averaged 8.7 percent, imperviousness averaged 25.3 percent, and population density averaged 2,936 people per square mile. Watershed imperviousness ranged from 8.7 to 36.6 percent.</p><p>In the study area for 2014 to 2016 (when streamflow data were available for all watersheds), runoff represented 40.9 percent of precipitation. Hydrograph separations indicated that 43 percent of runoff occurred as base flow, whereas the remainder occurred as stormflow. Higher watershed imperviousness was significantly related to higher amounts of runoff (Pearson product-moment correlation coefficient [<i>r</i>] = 0.517), higher runoff ratios (<i>r</i> = 0.646), and lower amounts (<i>r</i> = −0.637) and proportions (<i>r</i> = −0.898) of base-flow runoff. Stormwater best management practices have been implemented in the study watersheds; however, these practices do not appear to fully mitigate the effects of urban development and land use on stream hydrology.</p><p>Total copper, lead, and zinc concentrations in base-flow and stormflow samples exceeded the national recommended aquatic life criteria for chronic and acute conditions, respectively, to varying degrees. <i>Escherichia coli</i> density predictive regression models indicated that the U.S. Environmental Protection Agency’s Beach Action Value was exceeded at individual watersheds between 44.6 and 100 percent of the time. Exceedance of the Beach Action Value indicates possible unsafe conditions for primary contact recreation and could be used for timely notification of the potential health risks. Annual loads and yields were estimated for 15 constituents. Loads were typically higher for years with higher runoff while variations among watershed yields appear associated with watershed and land use characteristics. The lowest yields for almost all constituents occurred in the Stone Mountain Creek watershed—likely the result of the retention of sediment and reduction of nutrients in Stone Mountain Lake and two smaller downstream reservoirs within the watershed. The Little Stone Mountain Creek watershed also had some of the lowest yields for most constituents, likely due to the lack of many pollutant sources associated with its predominantly medium-density residential land use (95.5 percent), but had the highest total nitrate plus nitrite yields. The Intrenchment Creek watershed consistently had some of the highest yields across all constituents except for total nitrate plus nitrite. The high yields may be related to its high percentage of impervious area (36.0 percent) and high amount of heavily developed land use (high-density residential, 29.9 percent and commercial/industrial/institutional, 26.0 percent). Mean watershed constituent yields in this study were significantly higher than those from a similar analysis of 13 suburban to urban watersheds in adjacent Gwinnett County for 6 of the 10 constituents compared.</p><p>This study provides a thorough assessment of watershed characteristics, hydrology, and water-quality conditions of the 15 study watersheds and can be used to identify possible factors that affect runoff and water quality. Watershed managers can use these data and analyses to inform management decisions regarding the designated uses of streams, minimization of flooding, protection of aquatic habitats, and optimization of the effectiveness of best management practices.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215126","collaboration":"Prepared in cooperation with DeKalb County Department of Watershed Management","usgsCitation":"Aulenbach, B.T., Kolb, K., Joiner, J.K., and Knaak, A.E., 2022, Hydrology and water quality in 15 watersheds in DeKalb County, Georgia, 2012–16: U.S. Geological Survey Scientific Investigations Report 2021–5126, 105 p., https://doi.org/10.3133/sir20215126.","productDescription":"Report: xii, 105 p.; Data Release; Database","numberOfPages":"105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-117184","costCenters":[{"id":316,"text":"Georgia Water Science 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<a href=\"https://www.usgs.gov/centers/sa-water\" data-mce-href=\"https://www.usgs.gov/centers/sa-water\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br>1770 Corporate Drive, Suite 500<br>Norcross, GA 30093</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Design and Methods</li><li>Watershed Characteristics</li><li>Water Budget</li><li>Surface-Water Quality</li><li>Discussion</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Water-Quality Assurance and Control Summary</li><li>Appendix 2. Regression-Model Load Estimation Methodology Changes</li><li>Appendix 3. LOADEST Load Model Evaluation</li><li>Appendix 4. Assessment of Effects of Time-Step Load Methodology on Load Estimates</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-01-05","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829912,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolb, Katharine 0000-0002-1663-1662 kkolb@usgs.gov","orcid":"https://orcid.org/0000-0002-1663-1662","contributorId":5537,"corporation":false,"usgs":true,"family":"Kolb","given":"Katharine","email":"kkolb@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":829913,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joiner, John K. 0000-0001-9702-4911 jkjoiner@usgs.gov","orcid":"https://orcid.org/0000-0001-9702-4911","contributorId":3056,"corporation":false,"usgs":true,"family":"Joiner","given":"John","email":"jkjoiner@usgs.gov","middleInitial":"K.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829914,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knaak, Andrew E. 0000-0003-1813-8959 aknaak@usgs.gov","orcid":"https://orcid.org/0000-0003-1813-8959","contributorId":3123,"corporation":false,"usgs":true,"family":"Knaak","given":"Andrew","email":"aknaak@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829915,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227265,"text":"sir20215102 - 2022 - Main-stem seepage and base-flow recession time constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18","interactions":[],"lastModifiedDate":"2026-04-02T19:42:13.334029","indexId":"sir20215102","displayToPublicDate":"2022-01-05T16:35:00","publicationYear":"2022","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":"2021-5102","displayTitle":"Main-Stem Seepage and Base-Flow Recession Time Constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18","title":"Main-stem seepage and base-flow recession time constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18","docAbstract":"<p>The Niobrara River of northern Nebraska is a valuable water resource that sustains irrigated agriculture and recreation, as well as a diverse ecosystem. Large-quantity withdrawals from the source aquifer system have the potential to reduce the flow into the river and to adversely affect the free-flowing condition of the Niobrara National Scenic River (NSR). Therefore, to understand the magnitude and characteristics of those flows, the U.S. Geological Survey (USGS), in cooperation with the National Park Service, began a study to quantify seepage gains/losses along the eastern half of the Niobrara NSR and to create a map characterizing the base-flow recession time constant (tau) in the Niobrara NSR study area.</p><p>In 2016, a seepage study was completed to quantify seepage gains/losses along the eastern half of the Niobrara NSR. The seepage study results indicated that the main-stem streamflow on the Niobrara River increases 375 cubic feet per second (ft<sup>3</sup>/s) in the 39.9-mile study reach (river mile 119.3 to river mile 79.4). Although most of the streamflow increases are attributed to tributary inflows (297 ft<sup>3</sup>/s, 79 percent), 78 ft<sup>3</sup>/s are attributed to seepage gains within the reach. Seepage rates in the study reach ranged from 1.41 cubic feet per second per mile ([ft<sup>3</sup>/s]/mi) to 2.56 (ft<sup>3</sup>/s)/mi, with a mean seepage rate of 2 (ft<sup>3</sup>/s)/mi.</p><p>Tau values were calculated at 10 sites in the Niobrara NSR study area, and kriging geostatistical techniques were used to develop a contour map to estimate tau values at locations where streamflow was not measured. The minimum tau value was 12.1 days at Willow Creek at Atwood Road near Carns, Nebraska (USGS station 06463670), and the maximum value was 45.5 days at Tyler Falls at Fort Niobrara National Wildlife Refuge near Valentine, Nebr. (USGS station 06461150).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215102","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Strauch, K.R., and Soenksen, P.J., 2022, Main-stem seepage and base-flow recession time constants in the Niobrara National Scenic River Basin, Nebraska, 2016–18: U.S. Geological Survey Scientific Investigations Report 2021–5102, 17 p., https://doi.org/10.3133/sir20215102.","productDescription":"Report: vi, 17 p.; Data Release; Dataset","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125025","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":393921,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PDP1BI","text":"USGS data release","linkHelpText":"Datasets used to map the base-flow recession time constants in the Niobrara National Scenic River in Nebraska, 2016–18"},{"id":502117,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112068.htm","linkFileType":{"id":5,"text":"html"}},{"id":393922,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":393920,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5102/sir20215102.pdf","text":"Report","size":"2.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5102"},{"id":393919,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5102/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Niobrara National Scenic River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.974609375,\n              41.64007838467894\n            ],\n            [\n              -100.08544921874999,\n              41.64007838467894\n            ],\n            [\n              -100.08544921874999,\n              42.956422511073335\n            ],\n            [\n              -103.974609375,\n              42.956422511073335\n            ],\n            [\n              -103.974609375,\n              41.64007838467894\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/nebraska-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/nebraska-water-science-center\">Nebraska Water Science Center</a><br>U.S. Geological Survey<br>5231 South 19th Street<br>Lincoln, NE 68512</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Main-Stem Seepage</li><li>Base-Flow Recession Time Constants</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-01-05","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Strauch, Kellan R. 0000-0002-7218-2099 kstrauch@usgs.gov","orcid":"https://orcid.org/0000-0002-7218-2099","contributorId":1006,"corporation":false,"usgs":true,"family":"Strauch","given":"Kellan","email":"kstrauch@usgs.gov","middleInitial":"R.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soenksen, Philip J. pjsoenks@usgs.gov","contributorId":3983,"corporation":false,"usgs":true,"family":"Soenksen","given":"Philip","email":"pjsoenks@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":830199,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227264,"text":"ofr20211110 - 2022 - A steady-state groundwater flow model for the Des Moines River alluvial aquifer near Prospect Park, Des Moines, Iowa","interactions":[],"lastModifiedDate":"2026-03-25T17:47:27.104632","indexId":"ofr20211110","displayToPublicDate":"2022-01-05T16:35:00","publicationYear":"2022","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":"2021-1110","displayTitle":"A Steady-State Groundwater Flow Model for the Des Moines River Alluvial Aquifer near Prospect Park, Des Moines, Iowa","title":"A steady-state groundwater flow model for the Des Moines River alluvial aquifer near Prospect Park, Des Moines, Iowa","docAbstract":"<p>The Des Moines River alluvial aquifer is an important source of water for Des Moines Water Works, the municipal water utility that provides residential and commercial water resources to the residents of Des Moines, Iowa, and surrounding municipalities. As an initial step in developing a better understanding of the groundwater resources of the Des Moines River alluvial aquifer, the U.S. Geological Survey constructed a steady-state numerical groundwater flow model in cooperation with Des Moines Water Works to simulate water-table elevations in the Des Moines River alluvial aquifer near Prospect Park in Des Moines under winter low-flow conditions.</p><p>A simple conceptual model consisting of a hydrogeologic framework, water budget, and inferred water-table elevation map was developed for the model area. The inferred water-table elevation map was constructed based on general knowledge of hydrogeology within the model area and was used to set calibration targets for numerical model calibration. A steady-state numerical model was constructed based on the conceptual model using MODFLOW-NWT to simulate an area of about 15 square kilometers near Prospect Park in Des Moines. Parameter ESTimation software was used for model calibration to assess and optimize performance of the horizontal hydraulic conductivity and recharge parameters. The numerical groundwater flow model and supporting data are available in the USGS data release associated with this report, which contains the model archive.</p><p>Performance of the calibrated steady-state model was assessed by comparing observed and simulated water-table elevations, as well as estimated and simulated contributions to streamflow within the model area. The difference between observed water-table elevations and simulated water-table elevations was −0.1 meter at the majority of calibration targets, with the negative value indicating an overestimation of the simulated water-table elevation value compared to the observed water-table elevation value, and the root mean square error was 0.13 meter, which represents about 20 percent of the difference in observed water-table elevations. The simulated value of contributions to streamflow within the model area was considered similar to the estimated value, increasing confidence in the ability of the model to accurately represent the groundwater flow system in the Des Moines River alluvial aquifer in the model area during winter low-flow conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211110","collaboration":"Prepared in cooperation with Des Moines Water Works","usgsCitation":"FitzGerald, K.M., Ha, W.S., Haj, A.E., Gruhn, L.R., Bristow, E.L., and Weber, J.R., 2022, A steady-state groundwater flow model for the Des Moines River alluvial aquifer near Prospect Park, Des Moines, Iowa: U.S. Geological Survey Open-File Report 2021–1110, 20 p., https://doi.org/10.3133/ofr20211110.","productDescription":"Report: vii, 20 p.; Data Release; Dataset","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130288","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501532,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112070.htm","linkFileType":{"id":5,"text":"html"}},{"id":393916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1110/ofr20211110.pdf","text":"Report","size":"2.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1110"},{"id":393915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1110/coverthb.jpg"},{"id":393917,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":393918,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"}],"country":"United States","state":"Iowa","city":"Des Moines","otherGeospatial":"Prospect Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.65175247192383,\n              41.611463744813506\n            ],\n            [\n              -93.61836433410645,\n              41.611463744813506\n            ],\n            [\n              -93.61836433410645,\n              41.63019942878951\n            ],\n            [\n              -93.65175247192383,\n              41.63019942878951\n            ],\n            [\n              -93.65175247192383,\n              41.611463744813506\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269<br>Iowa City, IA 52240</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Conceptual Model of Groundwater Flow</li><li>Numerical Model of Groundwater Flow</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-01-05","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Goldstein, Kendall M.F. 0000-0002-0732-4345","orcid":"https://orcid.org/0000-0002-0732-4345","contributorId":270949,"corporation":false,"usgs":true,"family":"Goldstein","given":"Kendall","middleInitial":"M.F.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ha, Wonsook S. 0000-0002-7252-698X","orcid":"https://orcid.org/0000-0002-7252-698X","contributorId":266139,"corporation":false,"usgs":true,"family":"Ha","given":"Wonsook","email":"","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haj, Adel E. 0000-0002-3377-7161 ahaj@usgs.gov","orcid":"https://orcid.org/0000-0002-3377-7161","contributorId":147631,"corporation":false,"usgs":true,"family":"Haj","given":"Adel","email":"ahaj@usgs.gov","middleInitial":"E.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bristow, Emilia L. 0000-0002-7939-166X ebristow@usgs.gov","orcid":"https://orcid.org/0000-0002-7939-166X","contributorId":214538,"corporation":false,"usgs":true,"family":"Bristow","given":"Emilia L.","email":"ebristow@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830196,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weber, Jared R. 0000-0003-0505-2865","orcid":"https://orcid.org/0000-0003-0505-2865","contributorId":150534,"corporation":false,"usgs":true,"family":"Weber","given":"Jared","email":"","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":830197,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70256764,"text":"70256764 - 2022 - Structural and functional landscape connectivity for lesser prairie-chickens in the Sand Shinnery Oak Prairie Ecoregion","interactions":[],"lastModifiedDate":"2024-09-04T16:54:59.120656","indexId":"70256764","displayToPublicDate":"2022-01-05T11:49:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Structural and functional landscape connectivity for lesser prairie-chickens in the Sand Shinnery Oak Prairie Ecoregion","docAbstract":"<p><span>The lesser prairie-chicken (</span><i>Tympanuchus pallidicinctus</i><span>) is a species of conservation concern on the Southern High Plains of Texas and New Mexico, USA. Because fragmentation and isolation have increased since pre-settlement, dispersal through this heterogeneous landscape may be constrained, with serious implications for conservation and management of this species. Our objectives were to quantify landscape connectivity for lesser prairie-chickens within a patch network of potentially isolated leks (breeding display grounds), and examine effects of land use change on modeled lesser prairie-chicken movements through the landscape. We used graph theory to quantify structural landscape connectivity and circuit theory to quantify functional landscape connectivity for lesser prairie-chickens in the Sand Shinnery Oak Prairie Ecoregion of the Southern High Plains. There was a high degree of clustering among leks (</span><i>n</i><span> = 1,023 leks), with a 41.9-km coalescence distance of the network. We identified 3 leks as cutpoints within the network, meaning if the habitat patches containing these leks were fragmented, the remaining leks would become isolated from each other. We also identified several leks that were important for maintaining overall population connectivity for lesser prairie-chickens on the Southern High Plains. Conservation Reserve Program land was important for maintaining connectivity among leks to the north and west of the main lek core area located in New Mexico, but wind energy development constrained pathways to the north and south of this main lek core area. Our results suggest that landscape connectivity was reduced by row-crop agriculture and energy production and facilitated by the Conservation Reserve Program within the Sand Shinnery Oak Prairie Ecoregion.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22146","usgsCitation":"Schilder, L., Heintzman, L., Mcintyre, N., Harryman, S., Hagen, C., Martin, R.E., Boal, C.W., and Grisham, B., 2022, Structural and functional landscape connectivity for lesser prairie-chickens in the Sand Shinnery Oak Prairie Ecoregion: Journal of Wildlife Management, v. 86, no. 1, e22146, 17 p., https://doi.org/10.1002/jwmg.22146.","productDescription":"e22146, 17 p.","ipdsId":"IP-123187","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433460,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Sand Shinnery Oak Prairie ecoregion","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.08205634648147,\n              35.20735590338778\n            ],\n            [\n              -105.08205634648147,\n              32.04246611821024\n            ],\n            [\n              -101.86163388662169,\n              32.04246611821024\n            ],\n            [\n              -101.86163388662169,\n              35.20735590338778\n            ],\n            [\n              -105.08205634648147,\n              35.20735590338778\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"86","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Schilder, L.J.","contributorId":341785,"corporation":false,"usgs":false,"family":"Schilder","given":"L.J.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heintzman, L.J.","contributorId":341786,"corporation":false,"usgs":false,"family":"Heintzman","given":"L.J.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mcintyre, N.E.","contributorId":215186,"corporation":false,"usgs":false,"family":"Mcintyre","given":"N.E.","email":"","affiliations":[{"id":39194,"text":"Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409-3131 USA","active":true,"usgs":false}],"preferred":false,"id":908895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harryman, S.","contributorId":341788,"corporation":false,"usgs":false,"family":"Harryman","given":"S.","email":"","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":908896,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagen, C.A.","contributorId":276129,"corporation":false,"usgs":false,"family":"Hagen","given":"C.A.","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":908897,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, R. E.","contributorId":138911,"corporation":false,"usgs":false,"family":"Martin","given":"R.","email":"","middleInitial":"E.","affiliations":[{"id":12575,"text":"Ecological Associates, Inc, Jensen Beach, Florida","active":true,"usgs":false}],"preferred":false,"id":908898,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908899,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grisham, Blake A.","contributorId":341793,"corporation":false,"usgs":false,"family":"Grisham","given":"Blake A.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":908900,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70227175,"text":"sir20215125 - 2022 - Continuous monitoring of nutrient and sediment loads from the Des Plaines River at Route 53 at Joliet, Illinois, water years 2018–20","interactions":[],"lastModifiedDate":"2026-04-02T20:01:25.048208","indexId":"sir20215125","displayToPublicDate":"2022-01-05T10:55:00","publicationYear":"2022","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":"2021-5125","displayTitle":"Continuous Monitoring of Nutrient and Sediment Loads from the Des Plaines River at Route 53 at Joliet, Illinois, Water Years 2018–20","title":"Continuous monitoring of nutrient and sediment loads from the Des Plaines River at Route 53 at Joliet, Illinois, water years 2018–20","docAbstract":"<p>The Des Plaines River in southern Wisconsin and northern Illinois is the principal conduit for the discharge of wastewater effluent and stormwater runoff from the greater Chicago metropolitan area. In November 2017, the U.S. Geological Survey, in cooperation with the Metropolitan Water Reclamation District of Greater Chicago, installed a continuous monitoring station to measure water quality and streamflow in the Des Plaines River at Joliet, Illinois. Surrogate models encompassing continuous data and discrete water-quality samples were used to estimate loads of nitrate, total phosphorus, and suspended sediment. Comparisons to other major rivers in Illinois show that the Des Plaines River is a substantial contributor to statewide loading estimates for nitrate and total phosphorus but only a minor contributor to suspended sediment. Future loading estimates of total phosphorus could include more research into the effects of combined sewage overflows because these effects likely increased model uncertainty. The results in this report document current loadings and provide a baseline from which to assess future water-quality management decisions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215125","collaboration":"Prepared in cooperation with Metropolitan Water Reclamation District of Greater Chicago","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., and Hodson, T.O., 2022, Continuous monitoring of nutrient and sediment loads from the Des Plaines River at Route 53 at Joliet, Illinois, water years 2018–20 (ver. 1.1, February 2022): U.S. Geological Survey Scientific Investigations Report 2021–5125, 15 p., https://doi.org/10.3133/sir20215125.","productDescription":"Report: vii, 15 p.; Data Release; Database","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-129874","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":393780,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9M4BH1C","text":"USGS data release","linkHelpText":"Modeled nutrient and sediment concentrations from the Des Plaines River at Route 53 at Joliet, Illinois, based on continuous monitoring from October 1, 2017, through September 30, 2020"},{"id":396575,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5125/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":393783,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5125/images/"},{"id":393782,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5125/sir20215125.XML"},{"id":393781,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":393779,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5125/sir20215125.pdf","text":"Report","size":"2.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5125"},{"id":393778,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5125/coverthb2.jpg"},{"id":502126,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112067.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","city":"Joliet","otherGeospatial":"Des Plaines River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.25,\n              41.5\n            ],\n            [\n              -87.5,\n              41.5\n            ],\n            [\n              -87.5,\n              42.25\n            ],\n            [\n              -88.25,\n              42.25\n            ],\n            [\n              -88.25,\n              41.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: January 5, 2022; Version 1.1: February 28, 2022","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 North Goodwin<br>Urbana, IL 61801</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Methods</li><li>Data Coverage</li><li>Streamflow and Discrete Water-Quality Data</li><li>Loads and Yields</li><li>Uncertainty and Future Improvements</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-01-05","revisedDate":"2022-02-28","noUsgsAuthors":false,"publicationDate":"2022-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Peake, Colin S. 0000-0001-9712-1623","orcid":"https://orcid.org/0000-0001-9712-1623","contributorId":268354,"corporation":false,"usgs":true,"family":"Peake","given":"Colin","email":"","middleInitial":"S.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodson, Timothy O. 0000-0003-0962-5130","orcid":"https://orcid.org/0000-0003-0962-5130","contributorId":78634,"corporation":false,"usgs":true,"family":"Hodson","given":"Timothy","email":"","middleInitial":"O.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829920,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227287,"text":"70227287 - 2022 - Contributing areas to domestic wells in dipping sedimentary rocks under extreme recharge events","interactions":[],"lastModifiedDate":"2022-08-01T16:50:20.804308","indexId":"70227287","displayToPublicDate":"2022-01-05T08:12:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Contributing areas to domestic wells in dipping sedimentary rocks under extreme recharge events","docAbstract":"<p><span>We use particle tracking to determine contributing areas (CAs) to wells for transient flow models that simulate cyclic domestic pumping and extreme recharge events in a small synthetic watershed underlain by dipping sedimentary rocks. The CAs consist of strike-oriented bands at locations where the water table intersects high-hydraulic conductivity beds, and from which groundwater flows to the pumping well. Factors that affect the size and location of the CAs include topographic flow directions, rock dip direction, cross-bed fracture density, and position of the well relative to streams. For an effective fracture porosity (n</span><sub>e</sub><span>) of 10</span><sup>-4</sup><span>, the fastest advective travel times from CAs to wells are only a few hours. These results indicate that wells in this type of geologic setting can be highly vulnerable to contaminants or pathogens flushed into the subsurface during extreme recharge events. Increasing n</span><sub>e</sub><span>&nbsp;to 10</span><sup>-3</sup><span>&nbsp;results in modestly smaller CAs and delayed well vulnerability due to slower travel times. CAs determined for steady-state models of the same setting, but with long-term average recharge and pumping rates, are smaller than CAs in the models with extreme recharge. Also, the earliest-arriving particles arrive at the wells later in the steady-state models than in the extreme-recharge models. The results highlight the importance of characterizing geologic structure, simulating plausible effective porosities, and simulating pumping and recharge transience when determining CAs in fractured rock aquifers to assess well vulnerability under extreme precipitation events.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gwat.13169","usgsCitation":"Tiedeman, C.R., and Shapiro, A.M., 2022, Contributing areas to domestic wells in dipping sedimentary rocks under extreme recharge events: Groundwater, v. 60, no. 4, p. 460-476, https://doi.org/10.1111/gwat.13169.","productDescription":"17 p.","startPage":"460","endPage":"476","ipdsId":"IP-128281","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":449254,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13169","text":"Publisher Index Page"},{"id":436015,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93DZ84P","text":"USGS data release","linkHelpText":"MODFLOW-NWT and MODPATH6 models used to simulate contributing areas in hypothetical sedimentary rock aquifers under extreme recharge events"},{"id":394014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":830286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":830287,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70227317,"text":"70227317 - 2022 - Disease and secondary sexual traits: Effects of pneumonia on horn size of bighorn sheep","interactions":[],"lastModifiedDate":"2022-02-15T16:23:37.652149","indexId":"70227317","displayToPublicDate":"2022-01-05T07:39:28","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Disease and secondary sexual traits: Effects of pneumonia on horn size of bighorn sheep","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Secondary sexual traits (e.g., horns and antlers) have ecological and evolutionary importance and are of management interest for game species. Yet, how these traits respond to emerging threats like infectious disease remains underexplored. Infectious pneumonia threatens bighorn sheep (<i>Ovis canadensis</i>) populations across North America and we hypothesized it may also reduce horn growth in male sheep. We assess the effect of pneumonia on horn size in male bighorn sheep using 12 herd datasets from across the western United States that had horn growth and disease data. Disease resulted in 12–35% reduction in increment (yearly) length and 3–13% reduction in total horn length in exposed individuals. The disease effect was prolonged when pathogens continued to circulate in sheep populations. Further, disease likely delays the age at which horns reach ¾-curl and prevents achievement of full-curl. This is further evidenced with 6 of the 12 herds experiencing an increase in average age at harvest following die-off events.</p></div></div>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22154","usgsCitation":"Martin, A., Hogg, J.T., Manlove, K.R., LaSharr, T.N., Shannon, J.M., McWhirter, D.E., Miyasaki, H., Monteith, K., and Cross, P., 2022, Disease and secondary sexual traits: Effects of pneumonia on horn size of bighorn sheep: Journal of Wildlife Management, v. 86, no. 1, e22154, 19 p., https://doi.org/10.1002/jwmg.22154.","productDescription":"e22154, 19 p.","ipdsId":"IP-126452","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":449256,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22154","text":"Publisher Index 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