{"pageNumber":"445","pageRowStart":"11100","pageSize":"25","recordCount":184617,"records":[{"id":70226847,"text":"70226847 - 2021 - Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland","interactions":[],"lastModifiedDate":"2021-12-15T12:40:09.70423","indexId":"70226847","displayToPublicDate":"2021-11-11T06:37:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland","docAbstract":"<p><span>The spread of flammable invasive grasses, woody plant encroachment, and enhanced aridity have interacted in many grasslands globally to increase wildfire activity and risk to valued assets. Annual variation in the abundance and distribution of fine-fuel present challenges to land managers implementing prescribed burns and mitigating wildfire, although methods to produce high-resolution fuel estimates are still under development. To further understand how prescribed fire and wildfire influence fine-fuels in a semi-arid grassland invaded by non-native perennial grasses, we combined high-resolution Sentinel-2A imagery with in situ vegetation data and machine learning to estimate yearly fine-fuel loads from 2015 to 2020. The resulting model of fine-fuel corresponded to field-based validation measurements taken in the first (R</span><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mn>2</mn></msup></semantics></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"semantics\"><span id=\"MathJax-Span-4\" class=\"msup\"><span id=\"MathJax-Span-5\" class=\"mrow\"></span><span id=\"MathJax-Span-6\" class=\"mn\">2</span></span></span></span></span></span></span><span>&nbsp;= 0.52, RMSE = 218 kg/ha) and last year (R</span><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot; display=&quot;inline&quot;><semantics><msup><mrow /><mn>2</mn></msup></semantics></math>\"><span id=\"MathJax-Span-7\" class=\"math\"><span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"semantics\"><span id=\"MathJax-Span-10\" class=\"msup\"><span id=\"MathJax-Span-11\" class=\"mrow\"></span><span id=\"MathJax-Span-12\" class=\"mn\">2</span></span></span></span></span></span></span><span>&nbsp;= 0.63, RMSE = 196 kg/ha) of this 6-year study. Serial prediction of the fine-fuel model allowed for an assessment of the effect of prescribed fire (average reduction of −80 kg/ha 1-year post fire) and wildfire (−260 kg/ha 1-year post fire) on fuel conditions. Post-fire fine-fuel loads were significantly lower than in unburned control areas sampled just outside fire perimeters from 2015 to 2020 across all fires (</span><span class=\"html-italic\">t</span><span>&nbsp;= 1.67,&nbsp;</span><span class=\"html-italic\">p</span><span>&nbsp;&lt; 0.0001); however, fine-fuel recovery occurred within 3–5 years, depending upon burn and climate conditions. When coupled with detailed fuels data from field measurements, Sentinel-2A imagery provided a means for evaluating grassland fine-fuels at yearly time steps and shows high potential for extended monitoring of dryland fuels. Our approach provides land managers with a systematic analysis of the effects of fire management treatments on fine-fuel conditions and provides an accurate, updateable, and expandable solution for mapping fine-fuels over yearly time steps across drylands throughout the world</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/fire4040084","usgsCitation":"Wells, A.G., Munson, S.M., Sesnie, S., and Villarreal, M.L., 2021, Remotely sensed fine-fuel changes from wildfire and prescribed fire in a semi-arid grassland: Fire, v. 4, no. 4, 84, 22 p., https://doi.org/10.3390/fire4040084.","productDescription":"84, 22 p.","ipdsId":"IP-134126","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450231,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4040084","text":"Publisher Index Page"},{"id":436120,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91U530P","text":"USGS data release","linkHelpText":"Remotely sensed fine-fuel data for Buenos Aires National Wildlife Refuge (BANWR) from 2015 to 2020"},{"id":436119,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9347I2H","text":"USGS data release","linkHelpText":"Remotely sensed fine fuel data for Buenos Aires National Wildlife Refuge (BANWR) from 2015 to 2020"},{"id":392940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Buenos Aires National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.61285400390625,\n              31.302021690136105\n            ],\n            [\n              -110.92071533203125,\n              31.302021690136105\n            ],\n            [\n              -110.92071533203125,\n              31.88921859876096\n            ],\n            [\n              -111.61285400390625,\n              31.88921859876096\n            ],\n            [\n              -111.61285400390625,\n              31.302021690136105\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Adam Gerhard 0000-0001-9675-4963","orcid":"https://orcid.org/0000-0001-9675-4963","contributorId":270137,"corporation":false,"usgs":true,"family":"Wells","given":"Adam","email":"","middleInitial":"Gerhard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":828474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":828475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sesnie, Steven","contributorId":239687,"corporation":false,"usgs":false,"family":"Sesnie","given":"Steven","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":true,"id":828476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":828477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225680,"text":"cir1486 - 2021 - Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050","interactions":[],"lastModifiedDate":"2026-01-26T22:36:29.876041","indexId":"cir1486","displayToPublicDate":"2021-11-10T14:05:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1486","displayTitle":"Nitrogen in the Chesapeake Bay Watershed—A Century of Change, 1950–2050","title":"Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050","docAbstract":"<h1>Foreword</h1><p>Sustaining the quality of the Nation’s water resources and the health of our diverse ecosystems depends on the availability of sound water-resources data and information to develop effective, science-based policies. Effective management of water resources also brings more certainty and efficiency to important economic sectors. Taken together, these actions lead to immediate and long-term economic, social, and environmental benefits that will make a difference to the lives of the almost 400 million people projected to live in the United States by 2050.</p><p>The Chesapeake Bay is the largest and most productive estuary in the United States and is a vital environmental and economic resource. Approximately half of the water volume of the Chesapeake Bay originates from streams and rivers that drain the 64,243 mi<sup>2</sup> Chesapeake Bay watershed. The Bay and its tributaries have been degraded by excessive nutrients, such as nitrogen, from contributing watersheds. Inputs of nitrogen to the Bay lead to increased algal growth, decreased dissolved oxygen, and declining fisheries. In 2000, the Chesapeake Bay was listed as impaired under the Clean Water Act and Total Maximum Daily Loads (TMDLs) for nutrients and sediment have been established to assist with management actions aimed at nutrient reductions. Effective nutrient management requires an understanding of past, present, and future nutrient sources, fate, and transport in the watershed.</p><p>The Chesapeake Bay community has been a pioneer in science, management, and regulation to improve water quality. Factors like climate, hydrology, source inputs, and management controls play a vital role in determining the delivery and magnitude of nitrogen inputs to the Bay. Science in the form of monitoring data, predictive tools, and interpretive reports can help inform decisions to better balance the use and control of nitrogen in coastal areas. The findings in this report can contribute to effective management of the Bay and its watershed by providing a synthesis of the understanding of how human activities and environmental change in the watershed in the past, present, and future will influence the export of nitrogen to the Bay.</p><p>We hope this publication will provide you with insights and information to meet your water resource needs and will foster increased civilian awareness and involvement in the protection and restoration of our Nation’s waters. The information in this report is intended primarily for those interested or involved in resource management and protection, conservation, regulation, and policymaking at the regional and national levels.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1486","programNote":"National Water-Quality Program","usgsCitation":"Clune, J.W., and Capel, P.D., eds., 2021, Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050 (ver. 1.2, 2024): U.S. Geological Survey Circular 1486, 168 p., https://doi.org/10.3133/cir1486.","productDescription":"vi, 168 p.","numberOfPages":"168","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-109208","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":499071,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_111889.htm","linkFileType":{"id":5,"text":"html"}},{"id":391297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1486/coverthb4.jpg"},{"id":391298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1486/cir1486.pdf","text":"Report","size":"70.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1486"},{"id":396026,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://www.usgs.gov/media/videos/nitrogen-chesapeake-bay-watershed-century-change","text":"Video","linkHelpText":"- Nitrogen in the Chesapeake Bay Watershed: A Century of 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data-mce-href=\"https://www.usgs.gov/centers/pa-water\">Pennsylvania Water Science Center</a><br>U.S. Geological Survey<br>215 Limekiln Road<br>New Cumberland, PA 17070</p>","tableOfContents":"<ul><li>Foreword</li><li>Overview of Major Findings</li><li>Environmental Setting of the Chesapeake Bay Watershed</li><li>Nitrogen Setting of the Chesapeake Bay Watershed</li><li>Historical Setting of the Chesapeake Bay Watershed</li><li>Chapter 1. Changes in Nitrogen, Water Quality, and Management</li><li>Chapter 2. Nitrogen in Streams and Groundwater</li><li>Chapter 3. Changes in Climate</li><li>Chapter 4. Changes in Hydrology</li><li>Chapter 5. Changes in Atmospheric Deposition of Nitrogen</li><li>Chapter 6. Changes in Land Use</li><li>Chapter 7. Changes in Agricultural Water-Quality Management</li><li>Chapter 8. Changes in Water-Quality Management in Developed Areas</li><li>Chapter 9. Modeling the Effect of Nitrogen Loads from Multiple Changes in the Watershed</li><li>Chapter 10. Watershed Scale Changes in Nitrogen Export: Past and Future</li><li>Excess Nitrogen Impacts on Coastal Areas Across the Nation and the World</li><li>Final Thoughts</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-11-10","revisedDate":"2024-01-09","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Clune, John W. 0000-0002-3563-1975 jclune@usgs.gov","orcid":"https://orcid.org/0000-0002-3563-1975","contributorId":173410,"corporation":false,"usgs":true,"family":"Clune","given":"John","email":"jclune@usgs.gov","middleInitial":"W.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 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During water years 2016–20, the U.S. Geological Survey, in cooperation with the Illinois Environmental Protection Agency, operated continuous monitoring stations on eight major rivers in Illinois to better quantify nutrient and sediment loadings from the State of Illinois to the Mississippi River. This report estimates nitrate, phosphorus, and suspended-sediment loadings over that period, which can provide a benchmark against which to assess future changes in loading.</p><p>In addition, this report develops a new method for incorporating the uncertainty created by gaps in continuous datasets based on Bayesian machine learning. Data gaps are a common problem in continuous monitoring, and gap filling is necessary to quantify loadings and the uncertainty in loadings, which is essential if these results are to provide a benchmark for future studies. The uncertainty estimates may also be useful in an operational context, and this report provides examples of how uncertainty can be used in monitoring-network design and potentially reducing monitoring costs.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20215092","collaboration":"Prepared in cooperation with the Illinois Environmental Protection Agency","usgsCitation":"Hodson, T.O., Terrio, P.J., Peake, C.S., and Fazio, D.J., 2021, Continuous monitoring and Bayesian estimation of nutrient and sediment loads from Illinois watersheds, for water years 2016–2020: U.S. Geological Survey Scientific Investigations Report 2021–5092, 40 p., https://doi.org/ 10.3133/ sir20215092.","productDescription":"Report: vii, 40 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-126875","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science 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 \"}}]}","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 N. Goodwin Ave.<br>Urbana, IL 61801</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>Imputation Results</li><li>Comparison Among Model Forms</li><li>Loads and Yields</li><li>Continuous Monitoring and Discrete Sampling</li><li>Network Improvements</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Station Descriptions</li></ul>","publishedDate":"2021-11-10","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"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":826484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":826486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fazio, David J. 0000-0003-0254-5162","orcid":"https://orcid.org/0000-0003-0254-5162","contributorId":268355,"corporation":false,"usgs":true,"family":"Fazio","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826487,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225748,"text":"sir20215050 - 2021 - Preliminary geohydrologic assessment of Buenos Aires National Wildlife Refuge, Altar Valley, southeastern Arizona","interactions":[],"lastModifiedDate":"2021-11-10T19:08:22.752141","indexId":"sir20215050","displayToPublicDate":"2021-11-10T09:09:24","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5050","displayTitle":"Preliminary Geohydrologic Assessment of Buenos Aires National Wildlife Refuge, Altar Valley, Southeastern Arizona","title":"Preliminary geohydrologic assessment of Buenos Aires National Wildlife Refuge, Altar Valley, southeastern Arizona","docAbstract":"<p>The Buenos Aires National Wildlife Refuge is located in the southern part of Altar Valley, southwest of Tucson in southeastern Arizona. The primary water-supply well at the Buenos Aires National Wildlife Refuge has experienced a two-decade decrease in groundwater levels in the well, as have other wells in the southern part of Altar Valley. In part to understand this trend, a study was undertaken by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, to summarize what is known about the geohydrologic system on the refuge and analyze groundwater-level trends and precipitation-groundwater correlations. In addition, available data were compiled where possible on the climate, land cover, soils, geology, and hydrology to provide a foundation for future modeling of the system.</p><p>Altar Valley is a sedimentary basin bounded by a mixture of Paleozoic to Tertiary sedimentary, volcanic, granitic, and metamorphic rocks. The valley fill is undifferentiated Tertiary to Quaternary sediments underlain by middle Miocene to Pliocene rocks that consist of moderately to strongly consolidated conglomerate and sandstone. Surface water, when present in the predominantly ephemeral streams of the valley, flows from south to north. Arivaca Creek has a cienega (or wetland) where groundwater surfaces before it flows as a short perennial reach out of Arivaca Basin. Groundwater maps compiled between 1934 and 2016 showed groundwater flowing from south to north. Before the 1980s, temporal patterns of groundwater levels in wells in Altar Valley varied substantially from one well to another. In the mid-1980s, comparatively high levels of precipitation occurred: the 1980s median value was 15.3 inches, whereas the median for the period of record was 13.2 inches. In addition, apparently corresponding groundwater level increases were seen in nearly all wells studied. After this initial increase, two different groundwater-level trends began to be observed in two spatially distinct sets of wells: in the northern part, groundwater levels were relatively steady, whereas in the southern part, groundwater levels declined from 10 to 20 feet between 1990 and 2019. Annual groundwater pumpage declined substantially in the northern part of the valley beginning in the early 1980s, but it began to increase again in the 1990s. Pumpage in the southern part has remained low and relatively steady compared to the northern part. Although the precise reasons for the declining groundwater levels in the southern part remain unclear, groundwater levels may be affected by factors such as climate cycles, long-term drought, and temperature-induced declines in recharge, resulting in increased evapotranspiration.</p><p>Preliminary analyses of two wells, one selected from each part of the valley, using linear regression and lag correlation to investigate correlation between annual precipitation and groundwater levels, showed a maximum correlation at a lag of about 17 years in the southern part of the valley and about 25 years in the northern part, indicating that, although variable sources and traveltimes of recharged water may be needed to propagate to each location, the strongest correlation at each well is with precipitation that was recharged 17 and 25 years prior to the groundwater response in that well. Assuming a constant flow of groundwater from the southern to the northern part of the valley, a decrease in recharge is expected to lead to a decrease in aquifer storage. As to the comparatively stable groundwater levels in the northern part, pumpage is still only about one-half what it was in the early 1980s, even though pumpage has increased there since the 1990s. Water levels in most wells in the northern part were drawn down prior to the decrease in pumping in the early 1980s, possibly owing to a combination of pumping and the nearly 20-year midcentury drought that occurred between 1940 and 1960. Water levels were in the process of recovering when the increase in pumping occurred in the 1990s. Because the water levels were recovering (increasing) instead of remaining static, the increased pumping may have only limited the recovery rather than causing a decrease in water levels, as a new quasi-equilibrium state may have been reached. Additional possible causes for the stable groundwater levels include (1) upgradient aquifer transmissivity that was high enough to offset pumping, (2) a low-permeability barrier, such as bedrock or clay, at the north end of the valley that caused groundwater pooling, (3) higher lateral inflow of groundwater in the northern part of the valley, (4) a delay in the effect of storage declines propagating from the south, or (5) some combination thereof.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215050","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Owen-Joyce, S.J., Callegary, J.B., and Rosebrough, A.E., 2021, Preliminary geohydrologic assessment of Buenos Aires National Wildlife Refuge, Altar Valley, southeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2021–5050, 29 p., https://doi.org/10.3133/sir20215050.","productDescription":"Report: viii, 29 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-118417","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":391517,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5050/sir20215050.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":391518,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QST8OX","linkHelpText":"Groundwater well data and annual groundwater pumpage data (1984–2019) in Altar Valley, Arizona"},{"id":391516,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5050/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Altar Valley, Buenos Aires National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.56341552734375,\n              31.459125370764387\n            ],\n            [\n              -111.34780883789062,\n              31.459125370764387\n            ],\n            [\n              -111.34780883789062,\n              31.81864727496152\n            ],\n            [\n              -111.56341552734375,\n              31.81864727496152\n            ],\n            [\n              -111.56341552734375,\n              31.459125370764387\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/az-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/az-water\">Arizona Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Aquifer Assessment&nbsp;&nbsp;</li><li>Altar Valley Precipitation–Groundwater Level Correlation&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>Selected References&nbsp;&nbsp;</li><li>Appendix 1. Selected Well Data in the Altar Valley, Arizona, Groundwater Area&nbsp;&nbsp;</li><li>Appendix 2. Annual Groundwater Pumpage in Altar Valley, Arizona, Between 1984 and 2019</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-11-10","noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Owen-Joyce, Sandra J. 0000-0002-4400-5618 sjowen@usgs.gov","orcid":"https://orcid.org/0000-0002-4400-5618","contributorId":5215,"corporation":false,"usgs":true,"family":"Owen-Joyce","given":"Sandra","email":"sjowen@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":826481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosebrough, Amy Elizabeth","contributorId":268353,"corporation":false,"usgs":false,"family":"Rosebrough","given":"Amy","email":"","middleInitial":"Elizabeth","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":true,"id":826483,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250897,"text":"70250897 - 2021 - Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada","interactions":[],"lastModifiedDate":"2024-01-11T14:33:28.409502","indexId":"70250897","displayToPublicDate":"2021-11-10T08:31:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada","docAbstract":"<div class=\"article-section__content en main\"><p>The Great Basin in the western United States hosts various hydrothermal systems, including both active geothermal systems and ancient systems preserved as mineral deposits. New magnetotelluric and structural geologic data were collected in the Gabbs Valley area of western Nevada to demonstrate the advantage of imaging the full crustal column below known hydrothermal systems. Three-dimensional models are developed and jointly interpreted where the key findings are bottom-up and top-down controls on hydrothermal systems. Bottom-up control is dictated by weaknesses in the brittle-ductile transition that allow hydrothermal fluids to propagate into the crust; these are often collocated with Miocene volcanic structures. Top-down control is dominated by modern Walker Lane and Basin and Range tectonics that control fluid transport through the middle and upper crust. This study demonstrates that the characterization of regional mineral and geothermal resources is better informed by imaging lower crustal structures and preferential pathways to the surface.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL095009","usgsCitation":"Peacock, J., and Siler, D.L., 2021, Bottom-up and top-down control on hydrothermal resources in the Great Basin: An example from Gabbs Valley, Nevada: Geophysical Research Letters, v. 48, no. 23, e2021GL095009, 10 p., https://doi.org/10.1029/2021GL095009.","productDescription":"e2021GL095009, 10 p.","ipdsId":"IP-130794","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":489074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gl095009","text":"Publisher Index Page"},{"id":424328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"23","noUsgsAuthors":false,"publicationDate":"2021-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":891971,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70226173,"text":"70226173 - 2021 - Multilayer perceptrons (MLPs)","interactions":[],"lastModifiedDate":"2021-11-16T13:14:51.29369","indexId":"70226173","displayToPublicDate":"2021-11-10T07:14:03","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Multilayer perceptrons (MLPs)","docAbstract":"<div id=\"body\"><div class=\"content\"><p id=\"Par1\" class=\"Para\">Artificial neural networks (ANNs) are adaptable systems that can solve problems that are difficult to describe with a mathematical relationship. They seek relationships between different types of datasets with their abilities to learn either with supervision or without. ANNs recognize patterns between input and output space and generalize solutions, in a way simulating the human brain’s learning experience with many relatively simple individual processing elements, called neurons. Neurons are networked (network topology) in a number of ways depending on the problem type and complexity. One of the most widely used ANN learning techniques is supervised learning coupled with a multilayer perceptron (MLP) topology due to its flexible applicability to a wide range of modeling problems involving both general classification and regression. ANNs, due to this flexibility, have been applied to many fields since the 1990s and their theory, types (such as radial basis functions, random...</p></div></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Mathematical Geosciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-26050-7_455-1","usgsCitation":"Karacan, C.O., 2021, Multilayer perceptrons (MLPs), chap. <i>of</i> Encyclopedia of Mathematical Geosciences, 3 p., https://doi.org/10.1007/978-3-030-26050-7_455-1.","productDescription":"3 p.","ipdsId":"IP-124707","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":391746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Karacan, C. Ozgen 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":201991,"corporation":false,"usgs":true,"family":"Karacan","given":"C.","email":"","middleInitial":"Ozgen","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":826715,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70226717,"text":"70226717 - 2021 - Strong evidence for two disjunct populations of Black Scoters Melanitta americana in North America","interactions":[],"lastModifiedDate":"2021-12-07T13:05:27.13515","indexId":"70226717","displayToPublicDate":"2021-11-10T07:05:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"title":"Strong evidence for two disjunct populations of Black Scoters Melanitta americana in North America","docAbstract":"<div>Black Scoters<span>&nbsp;</span><i>Melanitta americana</i><span>&nbsp;</span>were marked with satellite transmitters on Atlantic and Pacific coasts of North America to examine continental-scale population delineation. Scoters marked on the different coasts did not overlap at any stage of the annual cycle, suggesting that birds in the two regions could be monitored and managed as separate populations: 1) an Atlantic population, which winters along the Atlantic coast and Great Lakes and breeds from northeast continental Canada westward to the Northwest Territories, and 2) a Pacific population, which winters along the Pacific coasts of Alaska, British Columbia and the Pacific northwest states, and breeds in western Alaska. Range maps for Black Scoter could reflect these distributions revealed by satellite telemetry. Our data provide new information on the distribution of Black Scoters in North America, which can be used to improve the design of future surveys.</div>","language":"English","publisher":"Wildfowl Journal","usgsCitation":"Bowman, T.D., Gilliland, S.G., Schamber, J.L., Flint, P.L., Esler, D., Boyd, W., Rosenberg, D.H., Savard, J.L., Perry, M., and Osenkowski, J.E., 2021, Strong evidence for two disjunct populations of Black Scoters Melanitta americana in North America: Wildfowl, v. 71, p. 179-192.","productDescription":"14 p.","startPage":"179","endPage":"192","ipdsId":"IP-121283","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":392567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":392559,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2759"}],"country":"Canada, United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.57812499999999,\n              48.45835188280866\n            ],\n            [\n              -58.35937499999999,\n              48.45835188280866\n            ],\n            [\n              -58.35937499999999,\n              65.94647177615738\n            ],\n            [\n              -107.57812499999999,\n              65.94647177615738\n            ],\n            [\n              -107.57812499999999,\n              48.45835188280866\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -166.2890625,\n              57.136239319177434\n            ],\n            [\n              -155.390625,\n              57.136239319177434\n            ],\n            [\n              -155.390625,\n              69.03714171275197\n            ],\n            [\n              -166.2890625,\n              69.03714171275197\n            ],\n            [\n              -166.2890625,\n              57.136239319177434\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"71","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bowman, Timothy D.","contributorId":80779,"corporation":false,"usgs":false,"family":"Bowman","given":"Timothy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":827939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilliland, Scott G.","contributorId":216936,"corporation":false,"usgs":false,"family":"Gilliland","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":827940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schamber, Jason L","contributorId":269800,"corporation":false,"usgs":false,"family":"Schamber","given":"Jason","email":"","middleInitial":"L","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":827941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":827942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Esler, Daniel 0000-0001-5501-4555 desler@usgs.gov","orcid":"https://orcid.org/0000-0001-5501-4555","contributorId":5465,"corporation":false,"usgs":true,"family":"Esler","given":"Daniel","email":"desler@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":true,"id":827943,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, W. Sean","contributorId":241002,"corporation":false,"usgs":false,"family":"Boyd","given":"W. Sean","affiliations":[{"id":48188,"text":"Environment Canada","active":true,"usgs":false}],"preferred":false,"id":827944,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberg, Daniel H.","contributorId":42774,"corporation":false,"usgs":false,"family":"Rosenberg","given":"Daniel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":827945,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Savard, Jean-Pierre L.","contributorId":101776,"corporation":false,"usgs":false,"family":"Savard","given":"Jean-Pierre","email":"","middleInitial":"L.","affiliations":[{"id":6962,"text":"Science and Technology Branch, Environment Canada","active":true,"usgs":false}],"preferred":false,"id":827946,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Perry, Matthew 0000-0001-6452-9534 mperry@usgs.gov","orcid":"https://orcid.org/0000-0001-6452-9534","contributorId":179173,"corporation":false,"usgs":true,"family":"Perry","given":"Matthew","email":"mperry@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":827947,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Osenkowski, Jason E.","contributorId":216934,"corporation":false,"usgs":false,"family":"Osenkowski","given":"Jason","email":"","middleInitial":"E.","affiliations":[{"id":39552,"text":"Rhode Island Department of Environmental Management","active":true,"usgs":false}],"preferred":false,"id":827948,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70225730,"text":"ofr20201084 - 2021 - Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species","interactions":[],"lastModifiedDate":"2021-11-10T12:31:36.129608","indexId":"ofr20201084","displayToPublicDate":"2021-11-09T15:40:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1084","displayTitle":"Decision-Support Framework for Linking Regional-Scale Management Actions to Continental-Scale Conservation of Wide-Ranging Species","title":"Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species","docAbstract":"<p><i>Anas acuta</i> (Northern pintail; hereafter pintail) was selected as a model species on which to base a decision-support framework linking regional actions to continental-scale population and harvest objectives. This framework was then used to engage stakeholders, such as Landscape Conservation Cooperatives’ (LCCs’) habitat management partners within areas of importance to pintails, while maximizing cross-taxa effects from the framework. The mathematical framework for the model had been previously developed for pintails. A key assumption incorporated into the model is that density dependence in survival occurs during the post-hunting (winter) period, where resources are hypothesized to be limiting. Because few data are available to directly inform this process, the approach used was to build a hierarchical Bayesian integrated population model (IPM) that simultaneously uses data from bird-band recoveries, breeding population counts, and harvest surveys to estimate values of parameters of an annual population projection model, including population size, survival rate, reproductive rate, and process and observation error variances, that are logically consistent with each other, given the mathematical structure imposed through the IPM.</p><p>The main accomplishments of this study are (1) development of an IPM for pintail to guide harvest and habitat management, (2) development of a Prairie Parkland Region breeding submodel to predict pintail productivity, (3) development of statistical methodology to estimate pintail productivity (as measured by the ratio of juvenile to adults in hunter-collected wing samples) and winter survival and to relate these estimates to covariates, and (4) illustration of how to use a model and estimated parameter values to predict pintail population size and sustainable harvest as a function of habitat.</p><p>Estimation of pintail survival from bird-banding data shows that there has been relatively little variation in survival over the period 1960–2013. A productivity model showed strong effects of breeding ground conditions, wintering-ground precipitation, and density dependence on pintail productivity. Thus, most temporal variation in pintail demographic rates has been due to effects on reproduction and not survival, including effects of breeding or wintering-ground habitat. These results indicate that habitat conservation efforts may be most effective if they focus on maintaining or increasing breeding and wintering-ground habitat to increase pintail productivity rather than pintail survival. Environmental perturbations in excess of historical experience, such as what could occur under climate change, might have meaningful effects on survival but cannot be estimated with current data. Direct effects of climate, land use, or management are likely to be greater on productivity than survival, but substantial uncertainty remains about predictions of equilibrium population size and sustainable yield.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201084","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Osnas, E.E., Boomer, G.S., Devries, J.H., and Runge, M.C., 2021, Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species: U.S. Geological Survey Open-File Report 2020–1084, 31 p., https://doi.org/10.3133/ofr20201084.","productDescription":"Report: vi, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-083951","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":391433,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93YTR3X","text":"USGS data release","linkHelpText":"Data release—Decision-support framework for linking regional-scale management actions to continental-scale conservation of wide-ranging species"},{"id":391431,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1084/coverthb.jpg"},{"id":391432,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1084/ofr20201084.pdf","text":"Report","size":"6.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1084"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eesc\" data-mce-href=\"https://www.usgs.gov/centers/eesc\">Eastern Ecological Science Center</a><br>U.S. Geological Survey<br>12100 Beech Forest Road<br>Laurel, MD 20708</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>Objectives</li><li>Methods</li><li>Decision-Support Framework Results</li><li>Discussion</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2021-11-09","noUsgsAuthors":false,"publicationDate":"2021-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Osnas, Erik E. 0000-0001-9528-0866 eosnas@usgs.gov","orcid":"https://orcid.org/0000-0001-9528-0866","contributorId":5586,"corporation":false,"usgs":true,"family":"Osnas","given":"Erik","email":"eosnas@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boomer, G. Scott 0000-0001-5854-3604","orcid":"https://orcid.org/0000-0001-5854-3604","contributorId":261408,"corporation":false,"usgs":false,"family":"Boomer","given":"G.","email":"","middleInitial":"Scott","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":true,"id":826433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Devries, James H.","contributorId":268336,"corporation":false,"usgs":false,"family":"Devries","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":7182,"text":"Ducks Unlimited Canada","active":true,"usgs":false}],"preferred":true,"id":826434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826435,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70225545,"text":"ofr20211091 - 2021 - Digital Shoreline Analysis System (DSAS) version 5.1 user guide","interactions":[],"lastModifiedDate":"2024-05-16T14:04:20.434812","indexId":"ofr20211091","displayToPublicDate":"2021-11-09T12:45:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1091","displayTitle":"Digital Shoreline Analysis System (DSAS) Version 5.1 User Guide","title":"Digital Shoreline Analysis System (DSAS) version 5.1 user guide","docAbstract":"<p>The Digital Shoreline Analysis System version 5 software is an add-in to Esri ArcGIS Desktop version 10.4–10.7 that enables a user to calculate rate-of-change statistics from a time series of vector shoreline positions. The Digital Shoreline Analysis System provides an automated method for establishing measurement locations, performs rate calculations, provides the statistical data necessary to assess the reliability of the rates, and includes a beta model for forecasting shoreline position. The Digital Shoreline Analysis System version 5.1 includes updates to the interface and the application of proxy-datum bias. This in-depth user guide provides comprehensive instruction on the installation and use of the program, including how to create a reference baseline for measurements, steps needed to generate measurement transects and metadata, guidelines on how to manually add or edit existing transects, and an explanation of the visualization options to display calculated rates of shoreline change.</p><p><strong>Note:</strong> As of May 2024, the current version of the Digital Shoreline Analysis System (DSAS), version 6.0, is a standalone desktop application for calculating shoreline or boundary change over time. The user guide for DSAS version 5.1 is applicable to many aspects of version 6.0. The user guide provides relevant information on the DSAS workflow, including how to define a reference baseline for measurements, attribute requirements for baselines and shorelines, and supporting information on rate calculations and statistics.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211091","usgsCitation":"Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S., 2021, Digital Shoreline Analysis System (DSAS) version 5.1 user guide: U.S. Geological Survey Open-File Report 2021–1091, 104 p., https://doi.org/10.3133/ofr20211091.","productDescription":"Report: xi, 104 p.; Software Release","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123671","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":390774,"rank":4,"type":{"id":18,"text":"Project Site"},"url":"https://www.usgs.gov/centers/whcmsc/science/digital-shoreline-analysis-system-dsas","text":"Digital Shoreline Analysis System (DSAS)"},{"id":390775,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P13WIZ8M","text":"Digital Shoreline Analysis System version 6.0"},{"id":390767,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1091/ofr20211091.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1091"},{"id":390766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1091/coverthb.jpg"}],"contact":"<p><a href=\"mailto:WHSC_science_director@usgs.gov\" data-mce-href=\"mailto:WHSC_science_director@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/whcmsc\" data-mce-href=\"https://www.usgs.gov/centers/whcmsc\">Woods Hole Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>384 Woods Hole Road<br>Quissett Campus<br>Woods Hole, MA 02543–1598</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>1. Introduction</li><li>2. Installation Steps</li><li>3. Sample Data</li><li>4. DSAS Toolbar</li><li>5. Required Inputs</li><li>6. DSAS Workflow</li><li>7. Statistics</li><li>8. Beta Shoreline Forecasting</li><li>9. Summary Report</li><li>10. Metadata</li><li>11. References Cited</li><li>12. Appendix 1. Troubleshooting</li><li>13.Appendix 2. Calculating and Applying the Proxy-Datum Bias Between High-Water Line and Mean High Water Shorelines</li><li>14. Appendix 3. Summary Report Text</li><li>15. Appendix 4. Sample Data Workflows</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-11-09","noUsgsAuthors":false,"publicationDate":"2021-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Himmelstoss, Emily A. 0000-0002-1760-5474 ehimmelstoss@usgs.gov","orcid":"https://orcid.org/0000-0002-1760-5474","contributorId":194838,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily","email":"ehimmelstoss@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":825525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henderson, Rachel E. 0000-0001-5810-7941 rehenderson@contractor.usgs.gov","orcid":"https://orcid.org/0000-0001-5810-7941","contributorId":196870,"corporation":false,"usgs":true,"family":"Henderson","given":"Rachel","email":"rehenderson@contractor.usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":825526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kratzmann, Meredith G. 0000-0002-2513-2144 mkratzmann@usgs.gov","orcid":"https://orcid.org/0000-0002-2513-2144","contributorId":4950,"corporation":false,"usgs":true,"family":"Kratzmann","given":"Meredith","email":"mkratzmann@usgs.gov","middleInitial":"G.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":825527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":825528,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70229675,"text":"70229675 - 2021 - Morphometric sex identification of nestling and free-flying Tasmanian Wedge-tailed Eagles (Aquila audax fleayi)","interactions":[],"lastModifiedDate":"2022-03-14T12:26:28.215938","indexId":"70229675","displayToPublicDate":"2021-11-09T06:44:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Morphometric sex identification of nestling and free-flying Tasmanian Wedge-tailed Eagles (Aquila audax fleayi)","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">The endangered Tasmanian Wedge-tailed Eagle (<i>Aquila audax fleayi</i>) is the focus of continued research and conservation efforts. A tool for accurate and efficient identification of the sex of individuals would be a valuable aid to research and management. However, plumages are monomorphic between the sexes, making sex identification difficult without molecular analyses. Our aim was to assess whether Tasmanian Wedge-tailed Eagles of different age classes could be sexed accurately using morphological measurements. We took measurements of 25 live late-stage eagle nestlings and 108 carcasses of free-flying birds found opportunistically throughout Tasmania. Sex of all individuals was confirmed via genetic analyses. Free-flying birds were larger than nestlings; thus, we used age-specific statistical tools to distinguish the sexes. For both nestlings and free-flying birds, females were significantly larger than males, but overlap between the sexes prevented accurate sex identification using any single measurement. We used stepwise linear discriminant function analyses to select morphometric measurements necessary for accurate sex identification. Free-flying birds could be sexed with 97.6% accuracy using a combination of measurements of the forearm length, tarsus width (i.e., lateromedial width), and hallux length. Late-stage nestlings (9–10 wk old) could be sexed with 95.4% accuracy using measurements of the hallux width (i.e., lateromedial width), hallux breadth (i.e., anteroposterior width of hallux), and tarsus breadth (i.e., anteroposterior width of the tarsometatarsus at the narrowest point). The discriminate functions we present also allow the identification of sex in cases where morphological sex identification may be in doubt and molecular analyses should be prioritized. These equations provide a valuable research tool for studies of sexual differences in behavior and causes of mortality of this endangered subspecies.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.3356/JRR-20-115","usgsCitation":"Pay, J.M., Katzner, T., Wiersma, J.M., Brown, W.E., Hawkins, C.E., Proft, K.M., and Cameron, E.Z., 2021, Morphometric sex identification of nestling and free-flying Tasmanian Wedge-tailed Eagles (Aquila audax fleayi): Journal of Raptor Research, v. 55, no. 4, p. 539-551, https://doi.org/10.3356/JRR-20-115.","productDescription":"13 p.","startPage":"539","endPage":"551","ipdsId":"IP-113722","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":502434,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Morphometric_sex_identification_of_nestling_and_free-flying_Tasmanian_wedge-tailed_eagles_Aquila_Audax_Fleayi_/23012030","text":"External Repository"},{"id":397053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","otherGeospatial":"Tasmania","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              143.701171875,\n              -43.707593504052944\n            ],\n            [\n              149.326171875,\n              -43.707593504052944\n            ],\n            [\n              149.326171875,\n              -39.77476948529546\n            ],\n            [\n              143.701171875,\n              -39.77476948529546\n            ],\n            [\n              143.701171875,\n              -43.707593504052944\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"55","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pay, James M.","contributorId":245078,"corporation":false,"usgs":false,"family":"Pay","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":837883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":837884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiersma, Jason M","contributorId":288430,"corporation":false,"usgs":false,"family":"Wiersma","given":"Jason","email":"","middleInitial":"M","affiliations":[{"id":61754,"text":"Forest Practices Authority","active":true,"usgs":false}],"preferred":false,"id":837885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, William E. 0000-0003-1595-9655","orcid":"https://orcid.org/0000-0003-1595-9655","contributorId":245082,"corporation":false,"usgs":false,"family":"Brown","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837886,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawkins, Clare E.","contributorId":245079,"corporation":false,"usgs":false,"family":"Hawkins","given":"Clare","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":837887,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Proft, Kirstin M","contributorId":288431,"corporation":false,"usgs":false,"family":"Proft","given":"Kirstin","email":"","middleInitial":"M","affiliations":[{"id":16141,"text":"University of Tasmania","active":true,"usgs":false}],"preferred":false,"id":837888,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cameron, Elissa Z.","contributorId":245084,"corporation":false,"usgs":false,"family":"Cameron","given":"Elissa","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":837889,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70228954,"text":"70228954 - 2021 - Food habits of American Kestrels in the Southern High Plains of Texas","interactions":[],"lastModifiedDate":"2022-02-25T12:33:54.81349","indexId":"70228954","displayToPublicDate":"2021-11-09T06:31:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Food habits of American Kestrels in the Southern High Plains of Texas","docAbstract":"<div class=\"div0\"><div class=\"row ArticleContentRow\"><p id=\"ID0EF\" class=\"first\">The American Kestrel (<i>Falco sparverius</i>) is in general decline across its North American distribution. In contrast to widespread patterns of decline, kestrel populations appear stable in the southern Great Plains region. Historically, this region had a very low occurrence of kestrels, and their current abundance is highly likely due to vegetation and structures associated with settlement by people of European descent. To determine prey use by breeding kestrels, we placed motion-activated video cameras at preexisting kestrel nest boxes located in the Southern High Plains in 2017. We recorded over 4200 prey deliveries during 1748 hr of observation at five nests over the 4-wk brood-rearing period. On basis of frequency, these deliveries were dominated by reptiles (74.8%), with invertebrates (18.2%), mammals (4.4%), birds (2.9%), and unidentified (1.2%) prey used to lesser extents. Prey delivery rates were high relative to other studies; across the brood-rearing period we recorded an average of 2.3 deliveries/hr, equating to an average of 0.49 deliveries and 3.85 g of prey/nestling/hr. Because invertebrates dominate the diet reported in most kestrel food habit studies, the volume of reptiles captured as prey was unexpected. Even more unanticipated was the number of large prey captured, including juvenile eastern cottontails (<i>Sylvilagus floridanus</i>) and ground squirrels (<i>Ictidomys tridecemlineatus</i>,<span>&nbsp;</span><i>Xerospermophilus spilosoma</i>). We suspect the proportion of vertebrate prey captured during the nesting season may explain the local high rates of nesting success and number of young fledged.</p></div></div>","language":"English","publisher":"BioOne","doi":"10.3356/JRR-20-75","usgsCitation":"Boal, C.W., Thornely, M., and Mullican, S., 2021, Food habits of American Kestrels in the Southern High Plains of Texas: Journal of Raptor Research, v. 55, no. 4, p. 574-583, https://doi.org/10.3356/JRR-20-75.","productDescription":"10 p.","startPage":"574","endPage":"583","ipdsId":"IP-119424","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Southern High Plains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.4033203125,\n              32.69486597787505\n            ],\n            [\n              -99.1845703125,\n              32.69486597787505\n            ],\n            [\n              -99.1845703125,\n              36.98500309285596\n            ],\n            [\n              -103.4033203125,\n              36.98500309285596\n            ],\n            [\n              -103.4033203125,\n              32.69486597787505\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"55","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":836023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thornely, M.A.","contributorId":280096,"corporation":false,"usgs":false,"family":"Thornely","given":"M.A.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":836024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullican, S.D.","contributorId":280097,"corporation":false,"usgs":false,"family":"Mullican","given":"S.D.","email":"","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":836025,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225612,"text":"cir1485 - 2021 - U.S. Geological Survey invasive species research—Improving detection, awareness, decision support, and control","interactions":[],"lastModifiedDate":"2022-05-31T14:43:28.639583","indexId":"cir1485","displayToPublicDate":"2021-11-08T08:50:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1485","displayTitle":"U.S. Geological Survey Invasive Species Research—Improving Detection, Awareness, Decision Support, and Control","title":"U.S. Geological Survey invasive species research—Improving detection, awareness, decision support, and control","docAbstract":"<p>More than 6,500 nonindigenous species are now established in the United States, posing risks to human and wildlife health, native plants and animals, and our valued ecosystems. The annual environmental, economic, and health-related costs of invasive species are substantial. Invasive species can drive native species onto the endangered species list, resulting in associated regulatory costs; exacerbate the threat of wildland fire, which destroys property and threatens lives; increase the cost of delivering water and power; damage infrastructure; and degrade recreation opportunities and discourage tourism. The U.S. Geological Survey (USGS) works with sister agencies in the U.S. Department of the Interior (DOI) and other Federal, State, and territorial agencies, Tribes, and other stakeholders to provide information and tools needed to help solve problems posed by invasive species across the country. Key components of USGS invasive species science include developing novel prevention, forecasting, early detection, decision support, and control tools.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1485","isbn":"978-1-4113-4459-4","usgsCitation":"Tam, C.K., Daniel, W.M., Campbell, E., English, J.J., and Soileau, S.C., 2021, U.S. Geological Survey invasive species research—Improving detection, awareness, decision support, and control (ver. 1.1, May 2022): U.S. Geological Survey Circular 1485, 28 p., https://doi.org/10.3133/cir1485.","productDescription":"iv, 28 p.","numberOfPages":"28","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-122383","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":391017,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1485/cir1485.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1485"},{"id":391165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1485/coverthb2.jpg"},{"id":401312,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1485/versionHist.txt","size":"3.03 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: November 3, 2021; Version 1.1: May 31, 2022","contact":"<p>Associate Director, <a href=\"https://www.usgs.gov/mission-areas/ecosystems\" data-mce-href=\"https://www.usgs.gov/mission-areas/ecosystems\">Ecosystems Mission Area</a><br>U.S. Geological Survey<br>Mail Stop 300<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Biosurveillance Network for Invasive Species and Wildlife Disease</li><li>Early Detection and Rapid Response Tool Development</li><li>Molecular Detection</li><li>Aquatic Invasive Species</li><li>Invasive Grasses and Vegetation</li><li>Invasive Aquatic Plants</li><li>Invasive Reptiles</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2021-11-03","revisedDate":"2022-05-31","noUsgsAuthors":false,"publicationDate":"2021-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Tam, Cindy Kolar 0000-0001-6634-2343","orcid":"https://orcid.org/0000-0001-6634-2343","contributorId":214652,"corporation":false,"usgs":true,"family":"Tam","given":"Cindy Kolar","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":825913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Wesley M. 0000-0002-7656-8474 wdaniel@usgs.gov","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":194723,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","email":"wdaniel@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":825914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Earl 0000-0002-4073-1276","orcid":"https://orcid.org/0000-0002-4073-1276","contributorId":210698,"corporation":false,"usgs":false,"family":"Campbell","given":"Earl","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":true,"id":825915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"English, James J. 0000-0002-2412-2518 jjenglish@usgs.gov","orcid":"https://orcid.org/0000-0002-2412-2518","contributorId":268146,"corporation":false,"usgs":true,"family":"English","given":"James","email":"jjenglish@usgs.gov","middleInitial":"J.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":825917,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soileau, Suzanna C. 0000-0002-4331-0098 ssoileau@usgs.gov","orcid":"https://orcid.org/0000-0002-4331-0098","contributorId":198208,"corporation":false,"usgs":true,"family":"Soileau","given":"Suzanna","email":"ssoileau@usgs.gov","middleInitial":"C.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":825916,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226445,"text":"70226445 - 2021 - Setting and tracking suppression targets for sea lampreys in the Great Lakes","interactions":[],"lastModifiedDate":"2022-01-07T16:02:24.796186","indexId":"70226445","displayToPublicDate":"2021-11-08T07:10:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Setting and tracking suppression targets for sea lampreys in the Great Lakes","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab005\" class=\"abstract author\" lang=\"en\"><div id=\"as005\"><p id=\"sp0005\">In response to invasive species, the course of action taken by management agencies often evolves over a range of options from a do-nothing approach to suppression to complete eradication. As a case study of suppression targets, we explore the history of approaches used by the Great Lakes Fishery Commission in response to the invasion of the Laurentian Great Lakes by sea lampreys (<i>Petromyzon marinus</i>). With the early realization that eradication was not possible using available techniques, focus shifted to suppression of sea lampreys to support fish community objectives for the lakes. As a surrogate for damage to the fishery, a suppression target was defined for the maximum acceptable marking rate, indicated by the average number of sea lamprey wounds observed on every 100 large lake trout (<i>Salvelinus namaycush</i>) surveyed. Historic marking rates were used to delineate time periods of acceptable sea lamprey predation levels as an approximate measure of sea lamprey-induced mortality. A second target, independent of lake trout population status, was based on the average sea lamprey abundance estimated during the specified time periods. These intuitive targets have served as suppression benchmarks for the Sea Lamprey Control Program in the Great Lakes, allowing decision makers to gauge progress towards targets, refine control strategies and prioritize geographic areas for increased control effort. Here we document the development and subsequent changes to targets, summarize the methods used to implement these changes, and provide considerations for the future.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.10.007","usgsCitation":"Treska, T., Ebener, M.P., Christie, G., Adams, J.V., and Siefkes, M.J., 2021, Setting and tracking suppression targets for sea lampreys in the Great Lakes: Journal of Great Lakes Research, v. 47, no. Suppl 1, p. 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Service","active":true,"usgs":false}],"preferred":false,"id":826930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebener, Mark P.","contributorId":25099,"corporation":false,"usgs":false,"family":"Ebener","given":"Mark","email":"","middleInitial":"P.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":826931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christie, Gavin","contributorId":269347,"corporation":false,"usgs":false,"family":"Christie","given":"Gavin","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":826932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":826933,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siefkes, Michael J","contributorId":150989,"corporation":false,"usgs":false,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":826934,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231399,"text":"70231399 - 2021 - Hydrogeomorphic recovery and temporal changes in rainfall thresholds for debris flows following wildfire","interactions":[],"lastModifiedDate":"2022-05-10T11:46:01.87279","indexId":"70231399","displayToPublicDate":"2021-11-08T06:42:47","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeomorphic recovery and temporal changes in rainfall thresholds for debris flows following wildfire","docAbstract":"<div class=\"article-section__content en main\"><p>Wildfire-induced changes to soil and vegetation promote runoff-generated debris flows in steep watersheds. Postfire debris flows are most commonly observed in steep watersheds during the first wet season following a wildfire, but it is unclear how long the elevated threat of debris flow persists and why debris-flow potential changes in recovering burned areas. This work quantifies how rainfall intensity-duration (ID) thresholds for debris-flow initiation change with time since burning and provides a mechanistic explanation for these changes. We constrained a hydrologic model using field and remotely sensed measurements of soil-infiltration capacity, vegetation cover, runoff, and debris-flow activity. We applied this model to estimate rainfall ID thresholds for debris-flow initiation within three burned areas in the southwestern United States over a postfire recovery period of three to four years. Modeling suggests ID thresholds are lowest immediately following the fire (below a one-year recurrence interval [RI] storm) and increase with time, such that a 10- to 25-year RI storm would be required to generate a debris flow after three years of recovery. Modeled changes in rainfall ID thresholds result from increases in soil infiltration capacity, canopy interception, hydraulic roughness, and median grain size of sediment entrained in an incipient debris flow. The relative importance of each of these factors varied among our three sites. Results improve our ability to assess temporal changes in postfire debris-flow potential, highlight how site-specific factors may alter the persistence of postfire debris-flow hazards, and provide additional constraints on the timescale of recovery following wildfire.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JF006374","usgsCitation":"Hoch, O.J., McGuire, L.A., Youberg, A.M., and Rengers, F.K., 2021, Hydrogeomorphic recovery and temporal changes in rainfall thresholds for debris flows following wildfire: JGR Earth Surface, v. 126, no. 12, e2021JF006374, 26 p., https://doi.org/10.1029/2021JF006374.","productDescription":"e2021JF006374, 26 p.","ipdsId":"IP-133449","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":487544,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021jf006374","text":"Publisher Index Page"},{"id":400378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, New Mexico","otherGeospatial":"Buzzard Fire, Fish Fire, Pinal Fire","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.8525390625,\n              33.54139466898275\n            ],\n            [\n              -107.75390625,\n              33.54139466898275\n            ],\n            [\n              -107.75390625,\n              34.397844946449865\n            ],\n            [\n              -108.8525390625,\n              34.397844946449865\n            ],\n            [\n              -108.8525390625,\n              33.54139466898275\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.30078124999997,\n              33.8521697014074\n            ],\n            [\n              -117.44384765624997,\n              33.8521697014074\n            ],\n            [\n              -117.44384765624997,\n              34.59704151614417\n            ],\n            [\n              -118.30078124999997,\n              34.59704151614417\n            ],\n            [\n              -118.30078124999997,\n              33.8521697014074\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.03857421874997,\n              33.10074540514422\n            ],\n            [\n              -111.09374999999999,\n              33.10074540514422\n            ],\n            [\n              -111.09374999999999,\n              33.779147331286474\n            ],\n            [\n              -112.03857421874997,\n              33.779147331286474\n            ],\n            [\n              -112.03857421874997,\n              33.10074540514422\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Hoch, Olivia J.","contributorId":291569,"corporation":false,"usgs":false,"family":"Hoch","given":"Olivia","email":"","middleInitial":"J.","affiliations":[{"id":52636,"text":"Department of Geosciences, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":842507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, Luke A. 0000-0001-8178-7922 lmcguire@usgs.gov","orcid":"https://orcid.org/0000-0001-8178-7922","contributorId":203420,"corporation":false,"usgs":false,"family":"McGuire","given":"Luke","email":"lmcguire@usgs.gov","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":842508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Youberg, Ann M. 0000-0002-2005-3674","orcid":"https://orcid.org/0000-0002-2005-3674","contributorId":172609,"corporation":false,"usgs":false,"family":"Youberg","given":"Ann","email":"","middleInitial":"M.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address:  TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":true,"id":842509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":842510,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70226154,"text":"70226154 - 2021 - Carbon and ecohydrological priorities in managing woody encroachment: UAV perspective 63 years after a control treatment","interactions":[],"lastModifiedDate":"2021-12-10T17:42:20.47679","indexId":"70226154","displayToPublicDate":"2021-11-08T06:17:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Carbon and ecohydrological priorities in managing woody encroachment: UAV perspective 63 years after a control treatment","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Woody encroachment, including both woody species expansion and density increase, is a globally observed phenomenon that deteriorates arid and semi-arid rangeland health, biodiversity, and ecosystem services. Mechanical and chemical control treatments are commonly performed to reduce woody cover and restore ecohydrologic function. While the immediate impacts of woody control treatments are well documented in short-term studies, treatment impacts at decadal scales are not commonly studied. Using a controlled herbicide treatment from 1954 in the Sierra Ancha Experimental Forest in central Arizona, USA, we quantify woody encroachment and associated aboveground carbon accumulation in treated and untreated watersheds. Woody encroachment and aboveground carbon are estimated using high resolution multispectral images and photogrammetric data from a fixed-wing unmanned aerial vehicle (UAV). We then combine the contemporary UAV image-derived estimates with historical records from immediately before and after the treatment to consider long-term trends in woody vegetation cover, aboveground carbon, water yield, and sedimentation. Our results indicate that the treatment has had a lasting impact. More than six decades later, woody cover in two treated watersheds are still significantly lower compared to two control watersheds, even though woody cover increased in all four drainages. Aboveground woody carbon in the treated watersheds is approximately one half that accumulated in the control watersheds. The historical records indicate that herbicide treatment also increased water yield and reduced annual sedimentation. Given the sustained reduction in woody cover and aboveground woody biomass in treated watersheds, we infer that the herbicide treatment has had similarly long lasting impacts on ecohydrological function. Land managers can consider legacy impacts from control treatments to better balance carbon and ecohydrological consequences of woody encroachment and treatment activities.</p></div>","language":"English","publisher":"IOPScience","doi":"10.1088/1748-9326/ac3796","usgsCitation":"Sankey, T.T., Leonard, J., Moore, M., Sankey, J., and Belmonte, A., 2021, Carbon and ecohydrological priorities in managing woody encroachment: UAV perspective 63 years after a control treatment: Environmental Research Letters, 124053, 14 p., https://doi.org/10.1088/1748-9326/ac3796.","productDescription":"124053, 14 p.","ipdsId":"IP-129603","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":450259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac3796","text":"Publisher Index Page"},{"id":391674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-12-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":826670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Jackson","contributorId":268790,"corporation":false,"usgs":false,"family":"Leonard","given":"Jackson","email":"","affiliations":[{"id":55664,"text":"USDA Forest Service RMRS","active":true,"usgs":false}],"preferred":false,"id":826671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Margaret","contributorId":268791,"corporation":false,"usgs":false,"family":"Moore","given":"Margaret","email":"","affiliations":[{"id":52178,"text":"Northern Arizona University, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":826672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":826673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belmonte, Adam","contributorId":222546,"corporation":false,"usgs":false,"family":"Belmonte","given":"Adam","email":"","affiliations":[{"id":40559,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":826674,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70228744,"text":"70228744 - 2021 - Effects of stocking density on stress response and susceptibility to infectious hematopoietic necrosis virus in rainbow trout","interactions":[],"lastModifiedDate":"2022-02-17T13:11:48.571116","indexId":"70228744","displayToPublicDate":"2021-11-06T07:07:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8604,"text":"Journal of the American Association for Laboratory Animal Science","active":true,"publicationSubtype":{"id":10}},"title":"Effects of stocking density on stress response and susceptibility to infectious hematopoietic necrosis virus in rainbow trout","docAbstract":"<div class=\"tab-content\"><div id=\"Abst\" class=\"tab-pane active\">The goals of this study were to examine the effect of stocking density on the stress response and disease susceptibility in juvenile rainbow trout (<i>Oncorhynchus mykiss</i>). Fish were sorted into one of 2 stocking densities (high density \"HD\", 20-40 kg/m<sup>3</sup>) or (low density, \"LD\", 4-8 kg/m<sup>3</sup>) and 3 stress indices (cortisol levels in serum and water, and neutrophil: lymphocyte (N:L) ratios from blood smears) were measured at multiple time points over 21 d. Serum cortisol was significantly increased at 1 h in LD samples and at 14 d in HD samples. Water cortisol concentrations were significantly higher in LD tanks as compared with HD tanks on day 14. N:L ratios were significantly higher in HD tanks on day 14 as compared with LD tanks and with baseline. The effect of stocking density on mortality after exposure to infectious hematopoietic necrosis virus (IHNV) was compared between fish held in HD or LD conditions, with or without prior acclimation to the different density conditions. No significant differences in survival were found between HD and LD treatments or between acclimated and nonacclimated treatments. Cumulative results indicate that 1) 1 to 4 gram rainbow trout did not generally demonstrate significant differences in stress indices at the density conditions tested over a 21-d period, 2) independent differences were found in 3 stress indices at day 14 after sorting into LD and HD holding conditions; and 3) LD and HD stocking densities did not have a significant effect on mortality due to IHNV.</div></div>","language":"English","publisher":"American Association for Laboratory Animal Science","doi":"10.30802/aalas-jaalas-21-000003","usgsCitation":"Klug, J.J., Treuting, P.M., Sanders, G.E., Winton, J., and Kurath, G., 2021, Effects of stocking density on stress response and susceptibility to infectious hematopoietic necrosis virus in rainbow trout: Journal of the American Association for Laboratory Animal Science, v. 60, no. 6, p. 637-645, https://doi.org/10.30802/aalas-jaalas-21-000003.","productDescription":"9 p.","startPage":"637","endPage":"645","ipdsId":"IP-127868","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":450262,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8628528","text":"External Repository"},{"id":396092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Klug, Jenna J","contributorId":279646,"corporation":false,"usgs":false,"family":"Klug","given":"Jenna","email":"","middleInitial":"J","affiliations":[{"id":57325,"text":"Department of Comparative Medicine, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":835256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Treuting, Piper M","contributorId":279647,"corporation":false,"usgs":false,"family":"Treuting","given":"Piper","email":"","middleInitial":"M","affiliations":[{"id":57325,"text":"Department of Comparative Medicine, University of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":835257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanders, George E.","contributorId":147207,"corporation":false,"usgs":false,"family":"Sanders","given":"George","email":"","middleInitial":"E.","affiliations":[{"id":16803,"text":"University of Washington, School of Medicine, Dept. of Comparative Medicine, T-160 Health Sciences Center, Seattle, WA  98195","active":true,"usgs":false}],"preferred":false,"id":835258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winton, James 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":179330,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":835259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":835260,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70225704,"text":"ofr20211100 - 2021 - Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York","interactions":[],"lastModifiedDate":"2022-04-14T16:03:17.800312","indexId":"ofr20211100","displayToPublicDate":"2021-11-05T13:15:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1100","displayTitle":"Shoreface and Holocene Sediment Thickness Offshore of Rockaway Peninsula, New York","title":"Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York","docAbstract":"<p>During September and October 2019, the U.S. Geological Survey mapped the shoreface and inner continental shelf offshore of the Rockaway Peninsula in New York using high-resolution chirp seismic reflection and single-beam bathymetry geophysical techniques. The results from this study are important for assessing the Quaternary evolution of the Rockaway Peninsula and determining coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles and maps of shoreface and Holocene sediment thickness from the shoreline to about 2 kilometers offshore. The results indicate that shoreface and Holocene sediment thickness demonstrates zonal variability because of underlying geology and sediment availability. Based on geomorphic features and underlying stratigraphy, the study area is separated into west, west-central, east-central, and east zones. Holocene sediment, which includes the shoreface and seafloor features with positive morphology (for example, nearshore bars, ebb-tide deltas, and sorted bedforms), thickens to the west and may be related to accommodation and westward dip of the regional unconformity. Shoreface units, which are thought to represent the active volume of littoral sediment, are thickest in the west-central peninsula where the geologic base of the shoreface is deeper. Shoreface units with moderate thickness are in the western and eastern peninsula where there are positive morphological features (for example, deposits accumulating updrift from the jetty, ebb-tide deltas, and so on). The thinnest shorefaces are in the east-central Rockaway Peninsula because of less accommodation caused by the shoaling regional unconformity.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211100","collaboration":"Prepared in cooperation with the National Fish and Wildlife Foundation","usgsCitation":"Wei, E.A., Miselis, J.L., and Forde, A.S., 2021, Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York: U.S. Geological Survey Open-File Report 2021–1100, 14 p., https://doi.org/10.3133/ofr20211100.","productDescription":"Report: iv, 14 p.; 2 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125818","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":391426,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211100/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391345,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1100/images/"},{"id":391343,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZO8QKJ","linkHelpText":"Archive of chirp subbottom profile data collected in 2019 from Rockaway Peninsula, New York"},{"id":391346,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.XML"},{"id":391344,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WNJSFN","linkHelpText":"Coastal bathymetry and backscatter data collected in September and October 2019 from Rockaway Peninsula, New York"},{"id":391342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.pdf","text":"Report","size":"11.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1100"},{"id":391341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1100/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Rockaway Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.76152038574219,\n              40.57067539946112\n            ],\n            [\n              -73.74229431152344,\n              40.593620934177494\n            ],\n            [\n              -73.76083374023438,\n              40.59414233212419\n            ],\n            [\n              -73.82469177246094,\n              40.58527801407785\n            ],\n            [\n              -73.8885498046875,\n              40.563372896916164\n            ],\n            [\n              -73.92974853515625,\n              40.549287249082035\n            ],\n            [\n              -73.94622802734375,\n              40.53937335015618\n            ],\n            [\n              -73.9441680908203,\n              40.529979881843865\n            ],\n            [\n              -73.92974853515625,\n              40.526326510744006\n            ],\n            [\n              -73.883056640625,\n              40.53311118427234\n            ],\n            [\n              -73.83018493652344,\n              40.54772199417569\n            ],\n            [\n              -73.77388000488281,\n              40.56389453066509\n            ],\n            [\n              -73.76152038574219,\n              40.57067539946112\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/spcmsc\" data-mce-href=\"https://www.usgs.gov/centers/spcmsc\">St. Petersburg Coastal and Marine Science Center</a><br>U.S. Geological Survey<br>600 4th Street South<br>St. Petersburg, FL 33701</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Regional Geologic Setting</li><li>Data Collection and Processing</li><li>Seismic Stratigraphy</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-11-05","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wei, Emily A. 0000-0003-4008-0933","orcid":"https://orcid.org/0000-0003-4008-0933","contributorId":223488,"corporation":false,"usgs":true,"family":"Wei","given":"Emily","email":"","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826344,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225753,"text":"70225753 - 2021 - Exposure of predatory and scavenging birds to anticoagulant rodenticides in France: Exploration of data from French surveillance programs","interactions":[],"lastModifiedDate":"2022-01-25T17:12:08.987756","indexId":"70225753","displayToPublicDate":"2021-11-05T07:24:58","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Exposure of predatory and scavenging birds to anticoagulant rodenticides in France: Exploration of data from French surveillance programs","docAbstract":"<div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0060\">Wild raptors are widely used to assess exposure to different environmental contaminants, including anticoagulant rodenticides (ARs). ARs are used on a global scale for rodent control, and act by disruption of the vitamin K cycle that results in haemorrhage usually accompanied by death within days. Some ARs are highly persistent and bioaccumulative, which can cause significant exposure of non-target species. We characterized AR exposure in a heterogeneous sample of dead raptors collected over 12 years (2008–2019) in south-eastern France. Residue analysis of 156 liver samples through LC-MS/MS revealed that 50% (78/156) were positive for ARs, with 13.5% (21/156) having summed second-generation AR (SGAR) concentrations &gt;100 ng/g ww. While SGARs were commonly detected (97.4% of positive samples), first-generation ARs were rarely found (7.7% of positive samples). ARs were more frequently detected and at greater concentration in predators (prevalence: 82.5%) than in scavengers (38.8%). Exposure to multiple ARs was common (64.1% of positive samples). While chlorophacinone exposure decreased over time, an increasing exposure trend was observed for the SGAR brodifacoum, suggesting that public policies may not be efficient at mitigating risk of exposure for non-target species. Haemorrhage was observed in 88 birds, but AR toxicosis was suspected in only 2 of these individuals, and no difference in frequency of haemorrhage was apparent in birds displaying summed SGAR levels above or below 100 ng/g ww. As for other contaminants, 17.2% of liver samples (11/64) exhibited Pb levels compatible with sub-clinical poisoning (&gt;6 μg/g dw), with 6.3% (4/64) above the threshold for severe/lethal poisoning (&gt;30 μg/g dw). Nine individuals with Pb levels &gt;6 μg/g dw also had AR residues, demonstrating exposure to multiple contaminants. Broad toxicological screening for other contaminants was positive for 18 of 126 individuals, with carbofuran and mevinphos exposure being the suspected cause of death of 17 birds. Our findings demonstrate lower but still substantial AR exposure of scavenging birds compared to predatory birds, and also illustrate the complexity of diagnosing AR toxicosis through forensic investigations.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.151291","usgsCitation":"Moriceau, M., Lefebvre, S., Fourel, I., Benoit, E., Buronfosse, F., Orabi, P., Rattner, B.A., and Lattard, V., 2021, Exposure of predatory and scavenging birds to anticoagulant rodenticides in France: Exploration of data from French surveillance programs: Science of the Total Environment, v. 810, 151291, 13 p., https://doi.org/10.1016/j.scitotenv.2021.151291.","productDescription":"151291, 13 p.","ipdsId":"IP-130715","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450265,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hal.science/hal-03419591","text":"Publisher Index Page"},{"id":391567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"France","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -5.9765625,\n              42.13082130188811\n            ],\n            [\n              8.26171875,\n              42.13082130188811\n            ],\n            [\n              8.26171875,\n              51.39920565355378\n            ],\n            [\n              -5.9765625,\n              51.39920565355378\n            ],\n            [\n              -5.9765625,\n              42.13082130188811\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"810","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moriceau, Meg-Anne","contributorId":268361,"corporation":false,"usgs":false,"family":"Moriceau","given":"Meg-Anne","email":"","affiliations":[{"id":55634,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, F69 280 Marcy-l’Étoile, FR","active":true,"usgs":false}],"preferred":false,"id":826500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lefebvre, Sebastien","contributorId":228855,"corporation":false,"usgs":false,"family":"Lefebvre","given":"Sebastien","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":826528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fourel, Isabelle","contributorId":228856,"corporation":false,"usgs":false,"family":"Fourel","given":"Isabelle","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":826529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Benoit, Etienne","contributorId":228857,"corporation":false,"usgs":false,"family":"Benoit","given":"Etienne","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":826530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buronfosse, Florence","contributorId":268365,"corporation":false,"usgs":false,"family":"Buronfosse","given":"Florence","email":"","affiliations":[{"id":55636,"text":"CNITV, VetAgro Sup, 1 avenue Bourgelat, 69 280 Marcy-l’Étoile, FR","active":true,"usgs":false}],"preferred":false,"id":826531,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orabi, Pascal","contributorId":268366,"corporation":false,"usgs":false,"family":"Orabi","given":"Pascal","email":"","affiliations":[{"id":55638,"text":"French Bird Protection League (LPO France)","active":true,"usgs":false}],"preferred":false,"id":826532,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826533,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lattard, Virginie","contributorId":228858,"corporation":false,"usgs":false,"family":"Lattard","given":"Virginie","email":"","affiliations":[{"id":41519,"text":"USC1233 RS2GP, INRA, VetAgro Sup, Univ Lyon, France","active":true,"usgs":false}],"preferred":false,"id":826534,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70226816,"text":"70226816 - 2021 - Viral-like particles are associated with endosymbiont pathology in Florida corals affected by stony coral tissue loss disease","interactions":[],"lastModifiedDate":"2021-12-14T13:02:14.825455","indexId":"70226816","displayToPublicDate":"2021-11-05T06:59:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Viral-like particles are associated with endosymbiont pathology in Florida corals affected by stony coral tissue loss disease","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb0\">Stony coral tissue loss disease (SCTLD) was first documented in 2014 near the Port of Miami, Florida, and has since spread north and south along Florida’s Coral Reef, killing large numbers of more than 20 species of coral and leading to the functional extinction of at least one species,<span>&nbsp;</span><i>Dendrogyra cylindrus</i>. SCTLD is assumed to be caused by bacteria based on presence of different molecular assemblages of bacteria in lesioned compared to apparently healthy tissues, its apparent spread among colonies, and cessation of spread of lesions in individual colonies treated with antibiotics. However, light microscopic examination of tissues of corals affected with SCTLD has not shown bacteria associated with tissue death. Rather, microscopy shows dead and dying coral cells and symbiotic dinoflagellates (endosymbionts) indicating a breakdown of host cell and endosymbiont symbiosis. It is unclear whether host cells die first leading to death of endosymbionts or vice versa. Based on microscopy, hypotheses as to possible causes of SCTLD include infectious agents not visible at the light microscopy level or toxicosis, perhaps originating from endosymbionts. To clarify this, we examined corals affected with SCTLD and apparently healthy corals using transmission electron microscopy. Endosymbionts in SCTLD-affected and apparently healthy corals consistently had varying degrees of pathology associated with elongated particles compatible in morphology with filamentous positive single-stranded RNA viruses of plants termed anisometric viral-like particles (AVLP). There was apparent progression from early to late replication of AVLP in the cytoplasm of endosymbionts adjacent to or at times within chloroplasts, with morphologic changes in chloroplasts consistent with those seen in plant cells infected by viruses. Coral host cell pathology appeared limited to massive proliferation and lysis of mucus cells. Based on these findings, we hypothesize that SCTLD is a viral disease of endosymbionts leading to coral host death. Efforts to confirm the presence of a virus associated with SCTLD through other means would be appropriate. These include showing the presence of a virus through molecular assays such as deep sequencing, attempts to grow this virus in the laboratory through culture of endosymbionts, localization of virus in tissue sections using immunohistochemistry or<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>hybridization, and experimental infection of known-virus-negative corals to replicate disease at the gross and microscopic level.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2021.750658","usgsCitation":"Work, T.M., Weatherby, T.M., Landsberg, J.H., Kiryu, Y., Cook, S.M., and Peters, E.C., 2021, Viral-like particles are associated with endosymbiont pathology in Florida corals affected by stony coral tissue loss disease: Frontiers in Marine Science, v. 8, 750658, 18 p., https://doi.org/10.3389/fmars.2021.750658.","productDescription":"750658, 18 p.","ipdsId":"IP-133106","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":450267,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.750658","text":"Publisher Index Page"},{"id":436122,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B6M72R","text":"USGS data release","linkHelpText":"Viral-like particles are associated with endosymbiont pathology in Florida corals affected by stony coral tissue loss disease"},{"id":392848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.11035156249999,\n              24.327076540018634\n            ],\n            [\n              -75.89355468749999,\n              24.327076540018634\n            ],\n            [\n              -75.89355468749999,\n              31.541089879585808\n            ],\n            [\n              -88.11035156249999,\n              31.541089879585808\n            ],\n            [\n              -88.11035156249999,\n              24.327076540018634\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":828376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weatherby, Tina M.","contributorId":245384,"corporation":false,"usgs":false,"family":"Weatherby","given":"Tina","email":"","middleInitial":"M.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":828377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landsberg, Jan H.","contributorId":207918,"corporation":false,"usgs":false,"family":"Landsberg","given":"Jan","email":"","middleInitial":"H.","affiliations":[{"id":37664,"text":"Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, St. Petersburg, FL, USA","active":true,"usgs":false}],"preferred":false,"id":828378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiryu, Yasunaru","contributorId":270081,"corporation":false,"usgs":false,"family":"Kiryu","given":"Yasunaru","email":"","affiliations":[{"id":56072,"text":"Florida Fish & Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":828379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, Samantha M.","contributorId":270082,"corporation":false,"usgs":false,"family":"Cook","given":"Samantha","email":"","middleInitial":"M.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":828380,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peters, Esther C.","contributorId":209975,"corporation":false,"usgs":false,"family":"Peters","given":"Esther","email":"","middleInitial":"C.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":828381,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70226820,"text":"70226820 - 2021 - Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc","interactions":[],"lastModifiedDate":"2021-12-14T12:55:19.654772","indexId":"70226820","displayToPublicDate":"2021-11-05T06:53:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc","docAbstract":"<p>The Mojave Desert region is in a critical position for assessing models of Laramide orogenesis, which is hypothesized to have initiated as one or more seamounts subducted beneath the Cretaceous continental margin. Geochronological and geochemical characteristics of Late Cretaceous magmatic products provide the opportunity to test the validity of Laramide orogenic models. Laramide-aged plutons are exposed along a transect across the Cordilleran Mesozoic magmatic system from Joshua Tree National Park in the Eastern Transverse Ranges eastward into the central Mojave Desert. A transect at latitude ∼33.5°N to 34.5°N includes: (1) the large upper-crustal Late Cretaceous Cadiz Valley batholith, (2) a thick section of Proterozoic to Jurassic host rocks, (3) Late Cretaceous stock to pluton-sized bodies at mesozonal depths, and (4) a Jurassic to Late Cretaceous midcrustal sheeted complex emplaced at ∼20 km depth that transitions into a migmatite complex truncated along the San Andreas fault. This magmatic section is structurally correlative with the Big Bear Lake intrusive suite in the San Bernardino Mountains and similar sheeted rocks recovered in the Cajon Pass Deep Scientific Drillhole.</p><p>Zircon U-Pb geochronology of 12 samples via secondary ionization mass spectrometry (SIMS) (six from the Cadiz Valley batholith and six from the Cajon Pass Deep Scientific Drillhole) indicates that all Cretaceous igneous units investigated were intruded between 83 and 74 Ma, and Cajon Pass samples include a Jurassic age component. A compilation of new and published SIMS geochronological data demonstrates that voluminous magmatism in the Eastern Transverse Ranges and central Mojave Desert was continuous throughout the period suggested for the intersection and flat-slab subduction of the Shatsky Rise conjugate deep into the interior of western North America.</p><p>Whole-rock major-element, trace-element, and isotope geochemistry data from samples from a suite of 106 igneous rocks represent the breadth of Late Cretaceous units in the transect. Geochemistry indicates an origin in a subduction environment and intrusion into a crust thick enough to generate residual garnet. The lack of significant deflections of compositional characteristics and isotopic ratios in igneous products through space and time argues against a delamination event prior to 74 Ma.</p><p>We argue that Late Cretaceous plutonism from the Eastern Transverse Ranges to the central Mojave Desert represents subduction zone arc magmatism that persisted until ca. 74 Ma. This interpretation is inconsistent with the proposed timing of the docking of the Shatsky Rise conjugate with the margin of western North America, particularly models in which the leading edge of the Shatsky Rise was beneath Wyoming at 74 Ma. Alternatively, the timing of cessation of plutonism precedes the timing of the passage of the Hess Rise conjugate beneath western North America at ca. 70–65 Ma. The presence, geochemical composition, and age of arc products in the Eastern Transverse Ranges and central Mojave Desert region must be accounted for in any tectonic model of the transition from Sevier to Laramide orogenesis.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02225.1","usgsCitation":"Economos, R., Barth, A.P., Wooden, J., Paterson, S.R., Friesenhahn, B., Weigand, B., Anderson, J., Roell, J., Palmer, E., Ianno, A., and Howard, K.A., 2021, Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc: Geosphere, v. 17, no. 6, p. 2042-2061, https://doi.org/10.1130/GES02225.1.","productDescription":"20 p.","startPage":"2042","endPage":"2061","ipdsId":"IP-114848","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02225.1","text":"Publisher Index Page"},{"id":392846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.597412109375,\n              32.98102014898148\n            ],\n            [\n              -114.5599365234375,\n              32.98102014898148\n            ],\n            [\n              -114.5599365234375,\n              35.074964853989556\n            ],\n            [\n              -118.597412109375,\n              35.074964853989556\n            ],\n            [\n              -118.597412109375,\n              32.98102014898148\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"17","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Economos, R.C","contributorId":270083,"corporation":false,"usgs":false,"family":"Economos","given":"R.C","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Andrew P.","contributorId":214136,"corporation":false,"usgs":false,"family":"Barth","given":"Andrew","email":"","middleInitial":"P.","affiliations":[{"id":38983,"text":"Indiana University - Purdue University","active":true,"usgs":false}],"preferred":false,"id":828385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wooden, J.L.","contributorId":192664,"corporation":false,"usgs":false,"family":"Wooden","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":828386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paterson, S. R","contributorId":270084,"corporation":false,"usgs":false,"family":"Paterson","given":"S.","email":"","middleInitial":"R","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":828387,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Friesenhahn, Brody","contributorId":270085,"corporation":false,"usgs":false,"family":"Friesenhahn","given":"Brody","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828388,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weigand, B.A","contributorId":270086,"corporation":false,"usgs":false,"family":"Weigand","given":"B.A","email":"","affiliations":[{"id":56075,"text":"University of Göttingen","active":true,"usgs":false}],"preferred":false,"id":828389,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, J.L.","contributorId":270087,"corporation":false,"usgs":false,"family":"Anderson","given":"J.L.","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":828390,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roell, J.L.","contributorId":270088,"corporation":false,"usgs":false,"family":"Roell","given":"J.L.","email":"","affiliations":[{"id":56076,"text":"Indiana/Purdue University","active":true,"usgs":false}],"preferred":false,"id":828391,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Palmer, E.F.","contributorId":270089,"corporation":false,"usgs":false,"family":"Palmer","given":"E.F.","email":"","affiliations":[{"id":56076,"text":"Indiana/Purdue University","active":true,"usgs":false}],"preferred":false,"id":828392,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ianno, A.J.","contributorId":270090,"corporation":false,"usgs":false,"family":"Ianno","given":"A.J.","affiliations":[{"id":39566,"text":"Juniata College","active":true,"usgs":false}],"preferred":false,"id":828393,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828394,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70231396,"text":"70231396 - 2021 - The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","interactions":[],"lastModifiedDate":"2022-05-10T11:50:54.064361","indexId":"70231396","displayToPublicDate":"2021-11-05T06:47:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","docAbstract":"<p>Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (&gt;10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (&lt;0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12  × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).</p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-13-5127-2021","usgsCitation":"Olefeldt, D., Hovemyr, M., Kuhn, M., Bastviken, D., Bohn, T., Connolly, J., Crill, P., Euskirchen, E., Finkelstein, S., Genet, H., Grosse, G., Harris, L., Heffernan, L., Helbig, M., Hugelium, G., Hutchins, R., Juutinen, S., Lara, M., Malhotra, A., Manies, K.L., McGuire, A., Natali, S., O’Donnell, J.A., Parmentier, F., Rasanen, A., Schaedel, C., Sonnentag, O., Strack, M., Tank, S., Treat, C., Varner, R., Virtanen, T., Watts, J., and Warren, R., 2021, The Boreal-Arctic Wetland and Lake Dataset (BAWLD): Earth System Science Data, v. 13, p. 5127-5149, https://doi.org/10.5194/essd-13-5127-2021.","productDescription":"23 p.","startPage":"5127","endPage":"5149","ipdsId":"IP-129170","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450274,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5194/essd-13-5127-2021","text":"External Repository"},{"id":400379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":842473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hovemyr, Mikael","contributorId":291509,"corporation":false,"usgs":false,"family":"Hovemyr","given":"Mikael","email":"","affiliations":[],"preferred":false,"id":842474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuhn, M.A.","contributorId":291510,"corporation":false,"usgs":false,"family":"Kuhn","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":842475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bastviken, D","contributorId":264953,"corporation":false,"usgs":false,"family":"Bastviken","given":"D","affiliations":[{"id":54595,"text":"Department of Thematic Studies - Environmental Change, Linköping University, Linköping, Sweden","active":true,"usgs":false}],"preferred":false,"id":842476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bohn, T.J.","contributorId":291513,"corporation":false,"usgs":false,"family":"Bohn","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":842477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connolly, J.","contributorId":291515,"corporation":false,"usgs":false,"family":"Connolly","given":"J.","email":"","affiliations":[],"preferred":false,"id":842478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Crill, P.M.","contributorId":248742,"corporation":false,"usgs":false,"family":"Crill","given":"P.M.","affiliations":[{"id":49996,"text":"Stockholm University, Department of Geological Sciences and Bolin Centre for Climate Research, Stockholm, Sweden","active":true,"usgs":false}],"preferred":false,"id":842479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Euskirchen, E.S.","contributorId":216778,"corporation":false,"usgs":false,"family":"Euskirchen","given":"E.S.","email":"","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":842480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Finkelstein, S.A.","contributorId":257296,"corporation":false,"usgs":false,"family":"Finkelstein","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":842481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Genet, H.","contributorId":291521,"corporation":false,"usgs":false,"family":"Genet","given":"H.","affiliations":[],"preferred":false,"id":842482,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Grosse, G.","contributorId":192805,"corporation":false,"usgs":false,"family":"Grosse","given":"G.","email":"","affiliations":[],"preferred":false,"id":842483,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Harris, L.I.","contributorId":291522,"corporation":false,"usgs":false,"family":"Harris","given":"L.I.","email":"","affiliations":[],"preferred":false,"id":842484,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Heffernan, L.","contributorId":291524,"corporation":false,"usgs":false,"family":"Heffernan","given":"L.","email":"","affiliations":[],"preferred":false,"id":842485,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Helbig, M.","contributorId":169378,"corporation":false,"usgs":false,"family":"Helbig","given":"M.","email":"","affiliations":[{"id":25485,"text":"Université de Montréal, Canada","active":true,"usgs":false}],"preferred":false,"id":842486,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hugelium, G.","contributorId":291527,"corporation":false,"usgs":false,"family":"Hugelium","given":"G.","email":"","affiliations":[],"preferred":false,"id":842487,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hutchins, R.","contributorId":291530,"corporation":false,"usgs":false,"family":"Hutchins","given":"R.","email":"","affiliations":[],"preferred":false,"id":842488,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Juutinen, S.","contributorId":257303,"corporation":false,"usgs":false,"family":"Juutinen","given":"S.","affiliations":[],"preferred":false,"id":842489,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lara, M.J.","contributorId":291534,"corporation":false,"usgs":false,"family":"Lara","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":842490,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Malhotra, A.","contributorId":291536,"corporation":false,"usgs":false,"family":"Malhotra","given":"A.","affiliations":[],"preferred":false,"id":842491,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":842492,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"McGuire, A.D.","contributorId":199633,"corporation":false,"usgs":false,"family":"McGuire","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":842493,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Natali, S.M.","contributorId":291541,"corporation":false,"usgs":false,"family":"Natali","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":842494,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"O’Donnell, J. A.","contributorId":195376,"corporation":false,"usgs":false,"family":"O’Donnell","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":842495,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Parmentier, F-J.W.","contributorId":291544,"corporation":false,"usgs":false,"family":"Parmentier","given":"F-J.W.","affiliations":[],"preferred":false,"id":842496,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Rasanen, A.","contributorId":291546,"corporation":false,"usgs":false,"family":"Rasanen","given":"A.","email":"","affiliations":[],"preferred":false,"id":842497,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Schaedel, C.","contributorId":291547,"corporation":false,"usgs":false,"family":"Schaedel","given":"C.","email":"","affiliations":[],"preferred":false,"id":842498,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Sonnentag, O.","contributorId":257322,"corporation":false,"usgs":false,"family":"Sonnentag","given":"O.","affiliations":[],"preferred":false,"id":842499,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Strack, M.","contributorId":291552,"corporation":false,"usgs":false,"family":"Strack","given":"M.","email":"","affiliations":[],"preferred":false,"id":842500,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Tank, S.E.","contributorId":169370,"corporation":false,"usgs":false,"family":"Tank","given":"S.E.","email":"","affiliations":[{"id":12799,"text":"University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":842501,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Treat, C. C.","contributorId":257236,"corporation":false,"usgs":false,"family":"Treat","given":"C. C.","affiliations":[{"id":51984,"text":"University of Finland","active":true,"usgs":false}],"preferred":false,"id":842502,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Varner, R.K.","contributorId":291557,"corporation":false,"usgs":false,"family":"Varner","given":"R.K.","affiliations":[],"preferred":false,"id":842503,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Virtanen, T.","contributorId":291558,"corporation":false,"usgs":false,"family":"Virtanen","given":"T.","email":"","affiliations":[],"preferred":false,"id":842504,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Watts, J.D.","contributorId":291559,"corporation":false,"usgs":false,"family":"Watts","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":842505,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Warren, R.K.","contributorId":291562,"corporation":false,"usgs":false,"family":"Warren","given":"R.K.","email":"","affiliations":[],"preferred":false,"id":842506,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}}
,{"id":70225637,"text":"sir20215099 - 2021 - Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","interactions":[],"lastModifiedDate":"2021-11-05T11:03:38.802132","indexId":"sir20215099","displayToPublicDate":"2021-11-04T16:15:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5099","displayTitle":"Regression Models for Estimating Sediment, Nutrient Concentrations and Loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","title":"Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","docAbstract":"<p>Sediment and nutrient transport in the School Branch watershed (in central Indiana west of Indianapolis) is considered to be heavily affected by agricultural land use throughout the watershed. In 2015, the U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, deployed continuous water-quality monitors and began collecting discrete water-quality samples at the streamflow-gaging station School Branch at CR750N at Brownsburg, Indiana (U.S. Geological Survey station 03353420). Regression models that estimate concentrations of suspended sediment, total nitrogen, and total phosphorus were developed by relating streamflow and continuously monitored water-quality data to concentrations measured in discrete water-quality samples collected from June 2015 through February 2019. Regression model diagnostics indicated that streamflow and sensor-measured turbidity concentrations explained about 95 percent of the variation in suspended-sediment concentration and 73 percent of the variation in total phosphorus concentration. Similarly, streamflow and sensor-measured nitrate plus nitrite concentrations explained about 97 percent of the variation in total nitrogen concentrations.</p><p>Daily loads of suspended sediment, total nitrogen, and total phosphorus were computed from regression model concentrations and instantaneous streamflow. The estimated mean daily suspended-sediment discharge (June 2015 through February 2019) was 1.184 tons per day; the estimated median suspended-sediment discharge was 0.053 tons per day. The estimated mean daily total nitrogen discharge (June 2015 through February 2019) was 127.50 pounds per day; the estimated median total nitrogen discharge was 28.49 pounds per day. The estimated mean daily total phosphorus discharge (June 2015 through February 2019) was 12.08 pounds per day; the estimated median total-phosphorus discharge was 1.208 pounds per day.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215099","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Downhour, M.S., Bunch, A.R., and Lathrop, T.R., 2021, Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019: U.S. Geological Survey Scientific Investigations Report 2021–5099, 15 p., https://doi.org/10.3133/sir20215099.","productDescription":"Report: v, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-119874","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":391136,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":391135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YWNBAQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data and regression model for suspended sediment for School Branch at CR750N at Brownsburg, Indiana June 23, 2015, to February 6, 2019"},{"id":391133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5099/coverthb.jpg"},{"id":391134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5099/sir20215099.pdf","text":"Report","size":"1.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5099"}],"country":"United States","state":"Indiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.44866943359375,\n              39.81170080625297\n            ],\n            [\n              -86.23306274414062,\n              39.81170080625297\n            ],\n            [\n              -86.23306274414062,\n              40.01604611654875\n            ],\n            [\n              -86.44866943359375,\n              40.01604611654875\n            ],\n            [\n              -86.44866943359375,\n              39.81170080625297\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/co-water\" href=\"https://www.usgs.gov/centers/co-water\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS–415<br>Denver, CO 80225–0046<br></p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Study Area</li><li>Approach and Methods</li><li>Results of Data Collection: Discrete and Continuous Water-Quality Data</li><li>Quality Control/Quality Assurance</li><li>Regression Models</li><li>Constituent Load Computation</li><li>Limitations</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2021-11-04","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Downhour, Myles S. 0000-0001-6677-412X","orcid":"https://orcid.org/0000-0001-6677-412X","contributorId":218220,"corporation":false,"usgs":true,"family":"Downhour","given":"Myles","email":"","middleInitial":"S.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunch, Aubrey R. 0000-0002-2453-3624 aurbunch@usgs.gov","orcid":"https://orcid.org/0000-0002-2453-3624","contributorId":4351,"corporation":false,"usgs":true,"family":"Bunch","given":"Aubrey","email":"aurbunch@usgs.gov","middleInitial":"R.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lathrop, Timothy R. 0000-0002-3568-1286 trlathro@usgs.gov","orcid":"https://orcid.org/0000-0002-3568-1286","contributorId":213061,"corporation":false,"usgs":true,"family":"Lathrop","given":"Timothy","email":"trlathro@usgs.gov","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826027,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225636,"text":"sir20215038 - 2021 - Groundwater/surface-water interactions in the Partridge River Basin and evaluation of hypothetical future mine pits, Minnesota","interactions":[],"lastModifiedDate":"2022-03-23T13:15:47.763523","indexId":"sir20215038","displayToPublicDate":"2021-11-04T10:55:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5038","displayTitle":"Groundwater/Surface-Water Interactions in the Partridge River Basin and Evaluation of Hypothetical Future Mine Pits, Minnesota","title":"Groundwater/surface-water interactions in the Partridge River Basin and evaluation of hypothetical future mine pits, Minnesota","docAbstract":"<p>The Partridge River Basin (PRB) covers 156 square miles in northeastern Minnesota with headwaters in the Mesabi Iron Range. The basin is characterized by extensive wetlands, lakes, and streams in poorly drained and often thin glacial material overlying Proterozoic bedrock. To better understand the interaction between these extensive surface water features and the groundwater system, a three-dimensional, steady-state, groundwater-flow model of the PRB was developed by the U.S. Geological Survey in cooperation with the Great Lakes Indian Fish &amp; Wildlife Commission using the finite-difference computer code MODFLOW-NWT. The model simulates steady-state base flow in streams and groundwater interactions using the streamflow routing (SFR2) package. Existing mining features including tailings basins, stockpiles, pumped mine pits, and flooded mine pits were simulated using either high hydraulic conductivity zones or the drain (DRN) package. The unsaturated zone flow (UZF) package was used to better represent the groundwater system in areas with a high water table and for wetlands often associated with such areas. UZF typically is used to represent unsaturated zone processes but also can simulate the rejection of recharge and groundwater discharge to the land surface when the water table is near land surface. The steady-state model used data from the 2011 to 2013 period when 2011 high-resolution land surface (light detecting and ranging [lidar]) data were available that reflected land-surface and water elevations from mining activity in the basin. The parameter-estimation software suite PEST_HP was used to obtain a best fit of the modeled to measured groundwater levels, streamflow, pit inflow rates, and mapped peat deposits. The PEST calibration used the target residuals from two models with the same model parameters and targets from two separate periods: (1) a 1995–2015 calibration model, which provided a larger number of calibration targets, and (2) a 2011–2013 mining conditions model, which included calibration targets that reflected conditions consistent with the modeled mine-workings topography.</p><p>Calibration of the PRB model resulted in ranges of glacial horizontal hydraulic conductivity parameters that generally agreed with literature values and other models of the region. Horizontal hydraulic conductivity of the bedrock was higher in the upper bedrock layers where numerous and continuous fractures have been observed and lower in the deeper bedrock layers. Average basin-wide calibrated infiltration was 5.3 inches per year. An average of 4.6 inches per year of infiltration crosses the water table and becomes recharge and 0.7 inch per year is rejected by UZF due to saturated conditions at the land surface. Simulated groundwater runoff (the sum of rejected recharge and groundwater seepage to the land surface) can either be routed to streams or removed from the model as evapotranspiration. The calibrated model indicates relatively shallow groundwater-flow paths dominating and approximately 50 percent of the stream base flow coming from groundwater runoff.</p><p>The 2011–2013 mining conditions model was then used to develop five model scenarios simulating the response of the groundwater and surface-water system to potential hydrologic stress. The purpose of these mine pit scenarios is to present a possible workflow to quantify a model’s uncertainty for a given model forecast and serve as a possible guide for initial data collection that may improve a future model’s ability to make such a forecast. The scenarios included one scenario with the currently existing Peter Mitchell pit at final buildout and flooded to an elevation of 1,500 feet, and four scenarios with a hypothetical, new mine pit plus the flooded Peter Mitchell at final buildout. The five model scenarios were used to forecast streamflow at six locations in the PRB, pit inflow rates for the new mine pits and the flooded Peter Mitchell pit, and the average depth to water in 12 wetlands. A linear uncertainty analysis was performed using information from the PEST calibration and tools in the PyEMU python package to assess model uncertainty propagation to the model forecasts. Streamflows generally were reduced with future mining and the greatest streamflow reductions occurred from the flooded Peter Mitchell Pit, probably due to its large size. Average depth to groundwater in wetlands was most affected the closer the wetland was to a new mine pit.</p><p>Linear uncertainty methods were also used to evaluate data worth, which is the ability for potential new groundwater elevation observations to reduce the uncertainty in scenario forecasts. Data worth was performed for a grid of new hydraulic head observations. Overall, areas with nonnegligible data worth generally corresponded to wetland areas with no groundwater seepage to land surface from UZF. These model behaviors indicated that the land-surface boundary condition simulated by the UZF package was pinning the groundwater elevations to the land surface in areas with groundwater seepage (33 percent of the 2011–2013 base conditions model) such that the sensitivity to new observations in these areas was minimal. Therefore, representing wetlands as boundary conditions minimized the usefulness of data worth calculations because wetland areas were present over a large part of the model domain.</p><p>Probabilistic capture zones were estimated for each of the mines in the model scenarios. A capture zone represents the area contributing recharge to a model feature, like a well or a mine pit, and can be calculated by forward tracking particles from the water table. By using Monte Carlo techniques, it is possible to generate estimated capture zones that include the probability of recharge capture given the uncertainty present in the model. Monte Carlo techniques use randomly generated model parameter sets sampled from a plausible parameter range to create many possible realizations. The resulting capture zone arrays were calculated by tallying the total number of realizations in which a particle from a model cell was captured by the feature. Probabilities from the Monte Carlo runs ranged from 1 (captured in 100 percent of the runs) near the pits to 0 (captured in 0 percent of the runs) at the edges of the capture zone. Capture zones were not always spatially continuous; for example, the capture zone for the proposed mine pits south of the flooded Peter Mitchell pit was discontinuous with capture surrounding the proposed mine pit and north of the flooded Peter Mitchell pit. This northern section represents deeper groundwater flow paths that originate in the topographic high, move under the flooded pit, and discharge into the proposed pit. This pattern of capture indicates the possibility of some deeper flow through the upper fractured bedrock when the shallow groundwater flow system is modified. These results underscore that future site-specific applications of the base condition model require the input of site-specific data and recalibration to focus on the site of interest.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215038","collaboration":"Prepared in cooperation with the Great Lakes Indian Fish & Wildlife Commission","usgsCitation":"Haserodt, M.J., Hunt, R.J., Fienen, M.N., and Feinstein, D.T., 2021, Groundwater/surface-water interactions in the Partridge River Basin and evaluation of hypothetical future mine pits, Minnesota: U.S. Geological Survey Scientific Investigations Report 2021–5038, 94 p., https://doi.org/10.3133/sir20215038.","productDescription":"Report: ix, 87 p.; Data Release; Dataset","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-123210","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391131,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5038/sir20215038.xml","text":"Report xml","size":"277 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5038 xml"},{"id":391130,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":391132,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5038/images"},{"id":391129,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VODOU8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT and MODPATH models, capture zones and uncertainty data analysis for the Partridge River Basin, Minnesota"},{"id":391127,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5038/coverthb.jpg"},{"id":391128,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5038/sir20215038.pdf","text":"Report","size":"69.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5038"}],"country":"United States","state":"Minnesota","otherGeospatial":"Partridge River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -92.25,\n              47.4\n            ],\n            [\n              -91.75,\n              47.4\n            ],\n            [\n              -91.75,\n              47.8\n            ],\n            [\n              -92.25,\n              47.8\n            ],\n            [\n              -92.25,\n              47.4\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/umid-water\" data-mce-href=\"https://www.usgs.gov/centers/umid-water\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive,<br>Madison, WI 53726</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>Geologic Setting</li><li>Hydrogeologic Setting and Conceptual Model of the Flow System</li><li>Water Use</li><li>Groundwater Flow Model Construction</li><li>Model Calibration</li><li>Calibration Results and Discussion</li><li>Model Results and Discussion</li><li>Hypothetical Mine Pit Scenarios and Model Forecasts</li><li>Model Forecast Results and Associated Uncertainty</li><li>Probabilistic Capture Zones</li><li>Data Worth</li><li>Assumptions and Limitations</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Additional Data Processing Steps to Build the MODFLOW-NWT Packages</li><li>Appendix 2. Estimation of Dipping Bedrock Units</li><li>Appendix 3. Streamflow Target Processing</li><li>Appendix 4. MODPATH and Monte Carlo Setup for Capture Zone Analysis</li><li>Appendix 5. Data Worth Setup</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2021-11-04","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Haserodt, Megan J. 0000-0002-8304-090X mhaserodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-090X","contributorId":174791,"corporation":false,"usgs":true,"family":"Haserodt","given":"Megan","email":"mhaserodt@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":203888,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel T.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826024,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70227100,"text":"70227100 - 2021 - Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development","interactions":[],"lastModifiedDate":"2021-12-29T14:27:45.567844","indexId":"70227100","displayToPublicDate":"2021-11-04T08:17:26","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">In eastern North America, “tree bats” (Genera:<span>&nbsp;</span><span class=\"html-italic\">Lasiurus</span><span>&nbsp;</span>and<span>&nbsp;</span><span class=\"html-italic\">Lasionycteris</span>) are highly susceptible to collisions with wind energy turbines and are known to fly offshore during migration. This raises concern about ongoing expansion of offshore wind-energy development off the Atlantic Coast. Season, atmospheric conditions, and site-level characteristics such as local habitat (e.g., forest coverage) have been shown to influence wind turbine collision rates by bats onshore, and therefore may be related to risk offshore. Therefore, to assess the factors affecting coastal presence of bats, we continuously gathered tree bat occurrence data using stationary acoustic recorders on five structures (four lighthouses on barrier islands and one light tower offshore) off the coast of Virginia, USA, across all seasons, 2012–2019. We used generalized additive models to describe tree bat occurrence on a nightly basis. We found that sites either indicated maternity or migratory seasonal occurrence patterns associated with local roosting resources, i.e., presence of trees. Across all sites, nightly occurrence was negatively related to wind speed and positively related to temperature and visibility. Using predictive performance metrics, we concluded that our model was highly predictive for the Virginia coast. Our findings were consistent with other studies—tree bat occurrence probability and presumed mortality risk to offshore wind-energy collisions is highest on low wind speed nights, high temperature and visibility nights, and during spring and fall. The high predictive model performance we observed provides a basis for which managers, using a similar monitoring and modeling regime, could develop an effective curtailment-based mitigation strategy.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/ani11113146","usgsCitation":"True, M., Reynolds, R., and Ford, W., 2021, Monitoring and modeling tree bat (Genera: Lasiurus, Lasionycteris) occurrence using acoustics on structures off the mid-Atlantic coast—Implications for offshore wind development: Animals, v. 11, no. 11, 3146, 18 p., https://doi.org/10.3390/ani11113146.","productDescription":"3146, 18 p.","ipdsId":"IP-133484","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":450276,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani11113146","text":"Publisher Index Page"},{"id":393573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.10504150390625,\n              37.05736900011469\n            ],\n            [\n              -75.22613525390625,\n              37.05736900011469\n            ],\n            [\n              -75.22613525390625,\n              38.02213147353745\n            ],\n            [\n              -76.10504150390625,\n              38.02213147353745\n            ],\n            [\n              -76.10504150390625,\n              37.05736900011469\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"True, Michael C.","contributorId":270631,"corporation":false,"usgs":false,"family":"True","given":"Michael C.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":829630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Richard J.","contributorId":270633,"corporation":false,"usgs":false,"family":"Reynolds","given":"Richard J.","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":829631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":829629,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70230362,"text":"70230362 - 2021 - Olfactory lures in predator control do not increase predation risk to birds in areas of conservation concern","interactions":[],"lastModifiedDate":"2022-04-08T11:44:31.171653","indexId":"70230362","displayToPublicDate":"2021-11-04T06:40:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Olfactory lures in predator control do not increase predation risk to birds in areas of conservation concern","docAbstract":"<p><strong>Context:<span>&nbsp;</span></strong>Lethal control of predators is often undertaken to protect species of conservation concern. Traps are frequently baited to increase capture efficacy, but baited traps can potentially increase predation risk by attracting predators to protected areas. This is especially important if targeted predators can escape capture due to low trap success. Snake traps using live mouse lures may be beneficial if traps effectively remove snakes in the presence of birds and do not attract additional snakes to the area.</p><p><strong>Aims:<span>&nbsp;</span></strong>The present study evaluated whether mouse-lure traps in areas occupied by birds (simulated by deploying bird-lure traps) could influence predation risk from an invasive snake on Guam.</p><p><strong>Methods:<span>&nbsp;</span></strong>Snake traps were used, with Japanese quail (<i>Coturnix japonica</i>) as a proxy for predation risk, to assess if an adjacent trap with a mouse (<i>Mus musculus</i>) would attract brown treesnakes (<i>Boiga irregularis</i>) to a focal area and increase contact between an invasive snake and avian prey. Catch per unit effort (CPUE) at stations containing either a bird-lure trap, mouse-lure trap or pair of traps (i.e. one bird-lure and one mouse-lure trap) was evaluated.</p><p><strong>Key results:<span>&nbsp;</span></strong>Bird-lure traps paired with mouse-lure traps did not differ in CPUE from isolated bird-lure traps. At paired stations, CPUE of snakes in mouse-lure traps was 2.3× higher than bird-lure traps, suggesting mouse lures were capable of drawing snakes away from avian prey. Bird-lure traps at paired stations experienced a decay in captures over time, whereas CPUE for isolated bird-lure traps increased after 9 weeks and exceeded mouse-lure traps after 7 weeks.</p><p><strong>Conclusions:<span>&nbsp;</span></strong>Mouse lures did not increase the risk of snakes being captured in bird-lure traps. Instead, mouse-lure traps may have locally suppressed snakes, whereas stations without mouse-lure traps still had snakes in the focal area, putting avian prey at greater risk. However, snakes caught with bird lures tended to be larger and in better body condition, suggesting preference for avian prey over mammalian prey in larger snakes.</p><p><strong>Implications:<span>&nbsp;</span></strong>Strategic placement of olfactory traps within areas of conservation concern may be beneficial for protecting birds of conservation concern from an invasive snake predator.</p>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WR21022","usgsCitation":"Klug, P.E., Yackel Adams, A.A., and Reed, R., 2021, Olfactory lures in predator control do not increase predation risk to birds in areas of conservation concern: Wildlife Research, v. 49, no. 2, p. 183-192, https://doi.org/10.1071/WR21022.","productDescription":"10 p.","startPage":"183","endPage":"192","ipdsId":"IP-124833","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450278,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr21022","text":"Publisher Index Page"},{"id":398376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Klug, Page E.","contributorId":210065,"corporation":false,"usgs":false,"family":"Klug","given":"Page","email":"","middleInitial":"E.","affiliations":[{"id":38064,"text":"USDA WS NWRC","active":true,"usgs":false}],"preferred":false,"id":840081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":840082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":840083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}