{"pageNumber":"487","pageRowStart":"12150","pageSize":"25","recordCount":184569,"records":[{"id":70221704,"text":"70221704 - 2021 - Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements","interactions":[],"lastModifiedDate":"2025-05-14T13:28:26.269202","indexId":"70221704","displayToPublicDate":"2021-06-10T09:59:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements","docAbstract":"<p><span>The persistence of coastal marsh is dependent on its ability to maintain elevation relative to sea level, particularly for marshes experiencing high rates of&nbsp;shoreline&nbsp;erosion due to wave-attack, storms, and&nbsp;sea level rise. Sediments eroded at the marsh edge are either delivered onto the marsh platform or into the&nbsp;estuary, the latter resulting in a net loss of marsh sediments and&nbsp;soil carbon. Knowledge on the timing, pattern, and quantity of sediment deposition versus shoreline erosion along the marsh-estuary interface is critical for evaluating the overall health and vulnerability of coastal marshes to future scenarios of sea level rise and for estimating&nbsp;</span>sediment budgets<span>. Here we examined marsh shoreline erosion and sediment deposition for marsh sites experiencing a range of shoreline&nbsp;erosion rates&nbsp;and different levels of wind-wave exposure within the Grand Bay National Estuarine Research Reserve and Wildlife Refuge in Mississippi. We developed a method for calculating an erosion-deposition sediment budget using marsh elevation profiles, shoreline erosion rate, and sediment deposition measurements. Sediment budgets were calculated at four sites with varying shoreline erosion rates. Much of the sediment eroded at the marsh edge can be accounted for as marsh platform deposition, except at the most erosive site, suggesting a possible erosion threshold where eroded sediment mass is greater than platform deposition. Consistent with other studies of marsh creeks, sediment delivery to the marsh platform appears to be largely driven by wave climate. These data suggest that for erosive bay-estuarine shorelines, sediment delivered into the marsh is largely concentrated near the marsh shoreline, although shoreline erosion does not always result in a net loss of sediments from the marsh system in either decadal or annual assessments.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2021.107829","usgsCitation":"Smith, K., Terrano, J.F., Khan, N.S., Smith, C., and Pitchford, J.L., 2021, Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements: Geomorphology, v. 389, 107829, 16 p., https://doi.org/10.1016/j.geomorph.2021.107829.","productDescription":"107829, 16 p.","ipdsId":"IP-122214","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451930,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2021.107829","text":"Publisher Index Page"},{"id":386866,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Grand Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.76953125,\n              30.246018268082167\n            ],\n            [\n              -88.39736938476562,\n              30.246018268082167\n            ],\n            [\n              -88.39736938476562,\n              30.527962116594164\n            ],\n            [\n              -88.76953125,\n              30.527962116594164\n            ],\n            [\n              -88.76953125,\n              30.246018268082167\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"389","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terrano, Joseph F. 0000-0003-3060-7682 jterrano@usgs.gov","orcid":"https://orcid.org/0000-0003-3060-7682","contributorId":173263,"corporation":false,"usgs":true,"family":"Terrano","given":"Joseph","email":"jterrano@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818475,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Khan, Nicole S.","contributorId":213942,"corporation":false,"usgs":false,"family":"Khan","given":"Nicole","email":"","middleInitial":"S.","affiliations":[{"id":38935,"text":"Asian School of the Environment, Nanyang Technological University, 50 Nanyang Ave., Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":818476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818477,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitchford, Jonathan L 0000-0003-1168-5087","orcid":"https://orcid.org/0000-0003-1168-5087","contributorId":260687,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","email":"","middleInitial":"L","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":818478,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221587,"text":"70221587 - 2021 - The biophysical role of water and ice within permafrost nearing collapse: Insights from novel geophysical observations","interactions":[],"lastModifiedDate":"2021-06-30T19:19:52.483157","indexId":"70221587","displayToPublicDate":"2021-06-10T09:20:37","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":"The biophysical role of water and ice within permafrost nearing collapse: Insights from novel geophysical observations","docAbstract":"<p><span>The impact of permafrost thaw on hydrologic, thermal, and biotic processes remains uncertain, in part due to limitations in subsurface measurement capabilities. To better understand subsurface processes in thermokarst environments, we collocated geophysical and biogeochemical instruments along a thaw gradient between forested permafrost and collapse-scar bogs at the Alaska Peatland Experiment (APEX) site near Fairbanks, Alaska. Ambient seismic noise monitoring provided continuous high-temporal resolution measurements of water and ice saturation changes. Maps of seismic velocity change identified areas of large summertime velocity reductions nearest the youngest bog, indicating potential thaw and expansion at the bog margin. These results corresponded well with complementary borehole nuclear magnetic resonance measurements of unfrozen water content with depth, which showed permafrost soils nearest the bog edges contained the largest amount of unfrozen water along the study transect, up to 25% by volume. In situ measurements of methane within permafrost soils revealed high concentrations at these bog-edge locations, up to 30% soil gas. Supra-permafrost talik zones were observed at the bog margins, indicating talik formation and perennial liquid water may drive lateral bog expansion and enhanced permafrost carbon losses preceding thaw. Comparison of seismic monitoring with wintertime surface carbon dioxide fluxes revealed differential responses depending on time and proximity to the bogs, capturing the controlling influence of subsurface water and ice on microbial activity and surficial emissions. This study demonstrates a multidisciplinary approach for gaining new understanding of how subsurface physical properties influence greenhouse gas production, emissions, and thermokarst development.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JF006104","usgsCitation":"James, S.R., Minsley, B.J., McFarland, J., Euskirchen, E.S., Edgar, C.W., and Waldrop, M., 2021, The biophysical role of water and ice within permafrost nearing collapse: Insights from novel geophysical observations: JGR Earth Surface, v. 126, no. 6, e2021JF006104, 21 p., https://doi.org/10.1029/2021JF006104.","productDescription":"e2021JF006104, 21 p.","ipdsId":"IP-129192","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":451931,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021jf006104","text":"Publisher Index Page"},{"id":436316,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9455D1K","text":"USGS data release","linkHelpText":"Permafrost greenhouse gas and microbial data from the Alaska Peatland Experiment (APEX) 2017 to 2019"},{"id":386697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Fairbanks","otherGeospatial":"Alaska Peatland Experiment (APEX) site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149.293212890625,\n              64.35893097894458\n            ],\n            [\n              -147.667236328125,\n              64.35893097894458\n            ],\n            [\n              -147.667236328125,\n              64.88160222555004\n            ],\n            [\n              -149.293212890625,\n              64.88160222555004\n            ],\n            [\n              -149.293212890625,\n              64.35893097894458\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-25","publicationStatus":"PW","contributors":{"authors":[{"text":"James, Stephanie R. 0000-0001-5715-253X","orcid":"https://orcid.org/0000-0001-5715-253X","contributorId":260620,"corporation":false,"usgs":true,"family":"James","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":818202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":818203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McFarland, Jack 0000-0001-9672-8597","orcid":"https://orcid.org/0000-0001-9672-8597","contributorId":214819,"corporation":false,"usgs":true,"family":"McFarland","given":"Jack","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":818204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euskirchen, Eugenie S. 0000-0002-0848-4295","orcid":"https://orcid.org/0000-0002-0848-4295","contributorId":173730,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugenie","email":"","middleInitial":"S.","affiliations":[{"id":7211,"text":"University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":818205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edgar, Colin W. 0000-0002-7026-8358","orcid":"https://orcid.org/0000-0002-7026-8358","contributorId":260621,"corporation":false,"usgs":false,"family":"Edgar","given":"Colin","email":"","middleInitial":"W.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":818206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216758,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[],"preferred":true,"id":818207,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70222443,"text":"70222443 - 2021 - Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake","interactions":[],"lastModifiedDate":"2021-07-30T14:11:27.923693","indexId":"70222443","displayToPublicDate":"2021-06-10T09:08:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9121,"text":"Frontiers Earth Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">Earthquake-induced landslide inventories can be generated using field observations but doing so can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to produce landslide inventories, however, is dependent on a variety of factors, such as the extent of coverage, timing, and data quality, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover. With these challenges in mind, we use a combination of field observations and remote sensing data from multispectral, light detection and ranging (lidar), and synthetic aperture radar (SAR) sensors to produce a ground failure inventory for the urban areas affected by the 2018 magnitude (M<sub>w</sub>) 7.1 Anchorage, Alaska earthquake. The earthquake occurred during late November at high latitude (∼61°N), and the lack of sunlight, persistent cloud cover, and snow cover that occurred after the earthquake made remote mapping challenging for this event. Despite these challenges, 43 landslides were manually mapped and classified using a combination of the datasets mentioned previously. Using this manually compiled inventory, we investigate the individual performance and reliability of three remote sensing techniques in this environment not typically hospitable to remotely sensed mapping. We found that differencing pre- and post-event normalized difference vegetation index maps and lidar worked best for identifying soil slumps and rapid soil flows, but not as well for small soil slides, soil block slides and rock falls. The SAR-based methods did not work well for identifying any landslide types because of high noise levels likely related to snow. Some landslides, especially those that resulted in minor surface displacement, were identifiable only from the field observations. This work highlights the importance of the rapid collection of field observations and provides guidance for future mappers on which techniques, or combination of techniques, will be most effective at remotely mapping landslides in a subarctic and urban environment.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2021.673137","usgsCitation":"Martinez, S.N., Schaefer, L.N., Allstadt, K.E., and Thompson, E.M., 2021, Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake: Frontiers Earth Science Journal, v. 9, 673137, 13 p., https://doi.org/10.3389/feart.2021.673137.","productDescription":"673137, 13 p.","ipdsId":"IP-129070","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":451933,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.673137","text":"Publisher Index Page"},{"id":436317,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S5PVON","text":"USGS data release","linkHelpText":"Initial Observations of Landslides triggered by the 2018 Anchorage, Alaska earthquake"},{"id":387597,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -151.2158203125,\n              60.71619779357714\n            ],\n            [\n              -148.53515625,\n              60.71619779357714\n            ],\n            [\n              -148.53515625,\n              61.71070595883174\n            ],\n            [\n              -151.2158203125,\n              61.71070595883174\n            ],\n            [\n              -151.2158203125,\n              60.71619779357714\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Sabrina N. 0000-0002-1812-5990","orcid":"https://orcid.org/0000-0002-1812-5990","contributorId":237051,"corporation":false,"usgs":true,"family":"Martinez","given":"Sabrina","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820063,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70222072,"text":"70222072 - 2021 - Spatial ecology of invasive Burmese pythons in southwestern Florida","interactions":[],"lastModifiedDate":"2021-07-16T14:09:48.012348","indexId":"70222072","displayToPublicDate":"2021-06-10T09:00:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecology of invasive Burmese pythons in southwestern Florida","docAbstract":"<p><span>Understanding the spatial ecology of an invasive species is critical for designing effective control programs. Determining and quantifying home range estimates and habitat associations can streamline targeted removal efforts for wide-ranging, cryptic animals. The Burmese python (</span><i>Python bivittatus</i><span>) is a large-bodied constrictor snake with an established and expanding invasive population in southern Florida. This apex predator has severely impacted native wildlife across the Greater Everglades ecosystem. However, limited ecological information exists on this invasive species at the landscape level. Here, we present results from a study using radiotelemetry to quantify movements and habitat use patterns of 25 adult Burmese pythons in southwestern Florida, USA, for average periods of 814&nbsp;d (range: 288–1809). Our objective was to quantify home range size, movement rates, and second- and third-order habitat selection. Mean annual home range size was 7.5 km</span><sup>2</sup><span>&nbsp;± 2.9 km</span><sup>2</sup><span>&nbsp;(95% kernel density estimate), and pythons moved at a maximum mean daily rate of 0.52&nbsp;km/d. Burmese pythons selected agriculture, freshwater wetland, saline wetland, and upland land cover classes but avoided open water and urban land cover classes. Nest site selection was highest for pythons at an elevation of 1.7&nbsp;m with nesting hotspots concentrated on the borders of urban and agricultural areas or in sandy forested upland habitats. A broader understanding of the spatial utilization of Burmese pythons will enhance the utility of emerging control strategies across their invaded range.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3564","usgsCitation":"Bartoszek, I.A., Smith, B., Reed, R., and Hart, K., 2021, Spatial ecology of invasive Burmese pythons in southwestern Florida: Ecosphere, v. 12, no. 6, e03564, 19 p., https://doi.org/10.1002/ecs2.3564.","productDescription":"e03564, 19 p.","ipdsId":"IP-120516","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":451934,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3564","text":"Publisher Index Page"},{"id":387224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Collier County","otherGeospatial":"Collier Seminole State Park, Picayune Strand State Forest, Rookery Bay National Estuarine Research Reserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.815185546875,\n              25.857987767091547\n            ],\n            [\n              -81.43272399902344,\n              25.857987767091547\n            ],\n            [\n              -81.43272399902344,\n              26.19241214758277\n            ],\n            [\n              -81.815185546875,\n              26.19241214758277\n            ],\n            [\n              -81.815185546875,\n              25.857987767091547\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Bartoszek, Ian A.","contributorId":138954,"corporation":false,"usgs":false,"family":"Bartoszek","given":"Ian","email":"","middleInitial":"A.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":819437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Brian J. 0000-0002-0531-0492","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":139672,"corporation":false,"usgs":false,"family":"Smith","given":"Brian J.","affiliations":[{"id":12876,"text":"Cherokee Nation Technology Solutions","active":true,"usgs":false}],"preferred":false,"id":819438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":819439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":819440,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70221399,"text":"70221399 - 2021 - A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya","interactions":[],"lastModifiedDate":"2021-06-14T14:00:27.974633","indexId":"70221399","displayToPublicDate":"2021-06-10T08:18:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya","docAbstract":"<div id=\"abstract-1\" class=\"section abstract\"><p id=\"p-1\">On 7 Feb 2021, a catastrophic mass flow descended the Ronti Gad, Rishiganga, and Dhauliganga valleys in Chamoli, Uttarakhand, India, causing widespread devastation and severely damaging two hydropower projects. Over 200 people were killed or are missing. Our analysis of satellite imagery, seismic records, numerical model results, and eyewitness videos reveals that ~27x10<sup>6</sup><span>&nbsp;</span>m<sup>3</sup><span>&nbsp;</span>of rock and glacier ice collapsed from the steep north face of Ronti Peak. The rock and ice avalanche rapidly transformed into an extraordinarily large and mobile debris flow that transported boulders &gt;20 m in diameter, and scoured the valley walls up to 220 m above the valley floor. The intersection of the hazard cascade with downvalley infrastructure resulted in a disaster, which highlights key questions about adequate monitoring and sustainable development in the Himalaya as well as other remote, high-mountain environments.</p></div>","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.abh4455","usgsCitation":"Shugar, D.H., Jacquemart, M., Shean, D., Bhushan, S., Upadhyay, K., Sattar, A., Schwanghart, W., McBride, S.K., Van Wyk de Vries, M., Mergili, M., Emmer, A., Deschamps-Berger, C., McDonnell, M., Bhambri, R., Allen, S., Berthier, E., Carrivick, J., Clague, J., Dokukin, M., Dunning, S., Frey, H., Gascoin, S., Haritashya, U., Huggel, C., Kaab, A., Kargel, J., Kavanaugh, J., Lacroix, P., Petley, D., Rupper, S., Azam, M., Cook, S., Dimri, A., Eriksson, M., Farinotti, D., Fiddes, J., Gnyawali, K., Harrison, S., Jha, M., Koppes, M., Kumar, S., Leiness, S., Majeed, U., Mai, S., Muhuri, A., Noetzli, J., Paul, F., Rashid, I., Sain, K., Steiner, J., Ugalde, F., Watson, C., and Westoby, M., 2021, A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya: Science, eabh4455, 15 p., https://doi.org/10.1126/science.abh4455.","productDescription":"eabh4455, 15 p.","ipdsId":"IP-127686","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":451939,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://discovery.dundee.ac.uk/en/publications/cd9567f5-1430-46d5-b8f5-81132306087a","text":"External Repository"},{"id":386471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Chamoli","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              78.8818359375,\n              30.244831915307145\n            ],\n            [\n              79.6893310546875,\n              30.244831915307145\n            ],\n            [\n              79.6893310546875,\n              30.694611546632277\n            ],\n            [\n              78.8818359375,\n              30.694611546632277\n            ],\n            [\n              78.8818359375,\n              30.244831915307145\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shugar, D. 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,{"id":70221270,"text":"sir20215046 - 2021 - Magnitude and frequency of floods in the alluvial plain of the lower Mississippi River, 2017","interactions":[],"lastModifiedDate":"2021-06-11T11:47:34.741571","indexId":"sir20215046","displayToPublicDate":"2021-06-10T08:17:31","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":"2021-5046","displayTitle":"Magnitude and Frequency of Floods in the Alluvial Plain of the Lower Mississippi River, 2017","title":"Magnitude and frequency of floods in the alluvial plain of the lower Mississippi River, 2017","docAbstract":"<p>Annual exceedance probability flows at gaged locations and regional regression equations used to estimate annual exceedance probability flows at ungaged locations were developed by the U.S. Geological Survey, in cooperation with the Mississippi Department of Transportation, to improve flood-frequency estimates at rural streams in the alluvial plain of the lower Mississippi River. These estimates were developed using current geospatial data, analytical methods, and annual peak-flow data through September 2017 at 58 streamgages in the alluvial plain of the lower Mississippi River, including 9 in Mississippi, 35 in Arkansas, 4 in Missouri, and 10 in Louisiana. Annual exceedance probability flows presented in this report incorporate streamflow data through the 2017 water year, 32 additional years of record since the previous study in 1985 of flood magnitude and frequency in the Mississippi portion of the alluvial plain of the lower Mississippi River. Ranges for standard error of prediction, average variance of prediction, and pseudo-R<sup>2</sup> are 45–61 percent, 0.035–0.059 (log cubic feet per second)<sup>2</sup>, and 90–94 percent, respectively.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215046","collaboration":"Prepared in cooperation with the Mississippi Department of Transportation","usgsCitation":"Anderson, B.T., 2021, Magnitude and frequency of floods in the alluvial plain of the lower Mississippi River, 2017: U.S. Geological Survey Scientific Investigations Report 2021–5046, 15 p., https://doi.org/10.3133/sir20215046.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"N","ipdsId":"IP-118369","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":386320,"rank":3,"type":{"id":34,"text":"Image 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href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a> <br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\">U.S. Geological Survey</a> <br>640 Grassmere Park, Suite 100 <br>Nashville, TN 37211</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Basin Characteristics and Flood-Frequency Analysis</li><li>Estimating Annual Exceedance Probability Flows</li><li>Accuracy and Limitations of Regression Equations</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-06-10","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Brandon T. 0000-0001-6698-0791","orcid":"https://orcid.org/0000-0001-6698-0791","contributorId":209976,"corporation":false,"usgs":true,"family":"Anderson","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817197,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70222475,"text":"70222475 - 2021 - A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides","interactions":[],"lastModifiedDate":"2021-11-16T15:33:34.255617","indexId":"70222475","displayToPublicDate":"2021-06-10T08:08:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Coseismic landslides are a major source of transportation disruption in mountainous areas, but few approaches exist for rapidly estimating impacts to road networks. We develop a model that links the U.S. Geological Survey (USGS) near-real-time earthquake-triggered landslide hazard model with Open Street Map (OSM) road network data to rapidly estimate segment-level obstruction risk following major earthquake activity worldwide. To train and validate the model, we process OSM data for 15 historical earthquakes and calculate the average segment-level landslide hazard from the USGS model for each event. We then fit a multivariate adaptive regression spline model for the probability of road obstruction as a function of road segment length and landslide hazard, using a training and validation dataset derived from the intersections of road networks with earthquake-triggered landslide inventories. The resulting probabilistic model is well calibrated across a range of earthquake events, with estimated obstruction probabilities matching the relative frequency of potential road obstructions. The model runs quickly and is capable of producing road segment-level obstruction estimates within minutes to hours of a major earthquake. However, in near-real-time application, the accuracy of the obstruction estimates will be dependent on the quality of the ShakeMap shaking estimates, which often improves with time as more information becomes available after the earthquake. By providing a rapid first-order translation of landslide hazard into potential infrastructure impacts, this model helps provide emergency responders with tangible information on initial areas of concern.</p></div></div>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930211020022","usgsCitation":"Wilson, B., Allstadt, K.E., and Thompson, E.M., 2021, A near-real-time model for estimating probability of road obstruction due to earthquake-triggered landslides: Earthquake Spectra, v. 37, no. 4, p. 2400-2418, https://doi.org/10.1177/87552930211020022.","productDescription":"19 p.","startPage":"2400","endPage":"2418","ipdsId":"IP-127999","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436318,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9681WYD","text":"USGS data release","linkHelpText":"gfail_lifelines"},{"id":387580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, B.H.","contributorId":221584,"corporation":false,"usgs":false,"family":"Wilson","given":"B.H.","email":"","affiliations":[],"preferred":false,"id":820169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820171,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70221414,"text":"70221414 - 2021 - Evidence for variable precipitation and discharge from Upper Cretaceous–Paleogene fluvial deposits of the Raton Basin, Colorado–New Mexico, U.S.A.","interactions":[],"lastModifiedDate":"2021-06-15T11:51:45.486509","indexId":"70221414","displayToPublicDate":"2021-06-10T06:49:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2451,"text":"Journal of Sedimentary Research","onlineIssn":"1938-3681","printIssn":"1527-1404","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for variable precipitation and discharge from Upper Cretaceous–Paleogene fluvial deposits of the Raton Basin, Colorado–New Mexico, U.S.A.","docAbstract":"<div class=\"article-section-wrapper js-article-section js-content-section  \"><p>The Raton Basin of Colorado–New Mexico, USA, is the southeasternmost basin of the Laramide intraforeland province of North America. It hosts a thick succession (4.5 km or 15,000 ft) of Upper Cretaceous to Paleogene marine and continental strata that were deposited in response to the final regression of the Western Interior Seaway and the onset of Laramide intraforeland deformation. The Upper Cretaceous–Paleogene Raton and Poison Canyon formations were previously described as meandering river and braided river deposits that represented distal and proximal members of rivers that drained the basin-bounding Sangre de Cristo–Culebra uplift. We present new observations of fluvial-channel architecture that show that both formations contain the deposits of sinuous fluvial channels. However, fluvial channels of the Raton Formation formed in ever-wet environments and were affected by steady discharge, whereas channels of the overlying Poison Canyon Formation formed in drier environments and were affected by variable discharge. The apparent transition in fluvial discharge characteristics was coeval with the progradation of fluvial fans across the Raton Basin during the Paleocene, emanating from the ancestral Sangre de Cristo–Culebra uplift. The construction of fluvial fans, coupled with the sedimentary features observed within, highlights the dual control of Laramide deformation and early Cenozoic climatic patterns on the sedimentary evolution of the Raton Basin.</p></div>","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.2110/jsr.2020.081","usgsCitation":"Schwartz, T.M., Dechesne, M., and Zellman, K.L., 2021, Evidence for variable precipitation and discharge from Upper Cretaceous–Paleogene fluvial deposits of the Raton Basin, Colorado–New Mexico, U.S.A.: Journal of Sedimentary Research, v. 91, no. 6, p. 571-594, https://doi.org/10.2110/jsr.2020.081.","productDescription":"24 p.","startPage":"571","endPage":"594","ipdsId":"IP-116144","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":436319,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X7Z5VM","text":"USGS data release","linkHelpText":"Measured sections and paleocurrent data from fluvial deposits of the Upper Cretaceous-Paleogene Raton and Poison Canyon Formations, Raton Basin, Colorado-New Mexico, USA"},{"id":386488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico","otherGeospatial":"Raton Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.58984375,\n              36.24427318493909\n            ],\n            [\n              -103.3154296875,\n              36.24427318493909\n            ],\n            [\n              -103.3154296875,\n              37.37015718405753\n            ],\n            [\n              -104.58984375,\n              37.37015718405753\n            ],\n            [\n              -104.58984375,\n              36.24427318493909\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"91","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Schwartz, Theresa Maude 0000-0001-6606-4072","orcid":"https://orcid.org/0000-0001-6606-4072","contributorId":245180,"corporation":false,"usgs":true,"family":"Schwartz","given":"Theresa","email":"","middleInitial":"Maude","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":817626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":213936,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":817627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zellman, Kristine L. 0000-0002-7088-429X kzellman@usgs.gov","orcid":"https://orcid.org/0000-0002-7088-429X","contributorId":4849,"corporation":false,"usgs":true,"family":"Zellman","given":"Kristine","email":"kzellman@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":817628,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70228458,"text":"70228458 - 2021 - Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data","interactions":[],"lastModifiedDate":"2022-02-11T20:17:25.428531","indexId":"70228458","displayToPublicDate":"2021-06-09T14:13:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data","docAbstract":"Understanding the influence of individual attributes on demographic processes is a key objective of wildlife population studies. Capture-recapture and age data are commonly collected to investigate hypotheses about survival, reproduction, and viability. We present a novel age-structured Jolly-Seber model that incorporates age and capture-recapture data to provide comprehensive information on population dynamics, including abundance, age-dependent survival, recruitment, age structure, and population growth rates. We applied our model to a multi-year capture-recapture study of polar bears (Ursus maritimus) in western Hudson Bay, Canada (20122018), where management and conservation require a detailed understanding of how polar bears respond to climate change and other factors. In simulation studies, the age-structured Jolly-Seber model improved precision of survival, recruitment, and annual abundance estimates relative to standard Jolly-Seber models that omit age information. Furthermore, incorporating age information improved precision of population growth rates, increased power to detect trends in abundance, and allowed direct estimation of age-dependent survival and changes in annual age structure. Our case study provided detailed evidence for senescence in polar bear survival. Median survival estimates were lower (<0.95) for individuals aged <5 years, remained high (>0.95) for individuals aged 722 years, and subsequently declined to near zero for individuals >30 years. We also detected cascading effects of large recruitment classes on population age structure, which created major shifts in age structure when these classes entered the population and then again when they reached prime breeding ages (1015 years old). Overall, age-structured Jolly-Seber models provide a flexible means to investigate ecological and evolutionary processes that shape populations (e.g., via senescence, life expectancy, and lifetime reproductive success) while improving our ability to investigate population dynamics and forecast population changes from capture-recapture data.","language":"English","publisher":"Plos","doi":"10.1371/journal.pone.0252748","usgsCitation":"Hostetter, N., Lunn, N.J., Richardson, E.S., Regehr, E.V., and Converse, S.J., 2021, Age-structured Jolly-Seber model expands inference and improves parameter estimation from capture-recapture data: PLoS ONE, .0252748, 19 p., https://doi.org/10.1371/journal.pone.0252748.","productDescription":".0252748, 19 p.","ipdsId":"IP-116069","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":451942,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0252748","text":"Publisher Index Page"},{"id":395865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hostetter, Nathan J.","contributorId":275833,"corporation":false,"usgs":false,"family":"Hostetter","given":"Nathan J.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":834349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lunn, Nicholas J.","contributorId":275835,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":56899,"text":"canada","active":true,"usgs":false}],"preferred":false,"id":834350,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Evan S.","contributorId":275836,"corporation":false,"usgs":false,"family":"Richardson","given":"Evan","email":"","middleInitial":"S.","affiliations":[{"id":56899,"text":"canada","active":true,"usgs":false}],"preferred":false,"id":834351,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Regehr, Eric V.","contributorId":275837,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":834352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":834348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221848,"text":"70221848 - 2021 - Confirmed cases of Ophidiomycosis in museum specimens from the USA as early as 1945, United States","interactions":[],"lastModifiedDate":"2023-06-28T16:42:23.531182","indexId":"70221848","displayToPublicDate":"2021-06-09T12:54:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1493,"text":"Emerging Infectious Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Confirmed cases of Ophidiomycosis in museum specimens from the USA as early as 1945, United States","docAbstract":"<p><span>Ophidiomycosis represents a conservation threat to wild snake populations. The disease was reported in North America early in the 21st century, but the history of ophidiomycosis has not been investigated. We examined museum specimens and confirmed cases of ophidiomycosis &gt;50 years before the disease’s reported emergence.</span></p>","language":"English","publisher":"Centers for Disease Control and Prevention","doi":"10.3201/eid2707.204864","usgsCitation":"Lorch, J.M., Price, S.J., Lankton, J.S., and Drayer, A.N., 2021, Confirmed cases of Ophidiomycosis in museum specimens from the USA as early as 1945, United States: Emerging Infectious Diseases, v. 27, no. 7, p. 1986-1989, https://doi.org/10.3201/eid2707.204864.","productDescription":"4 p.: Data Release","startPage":"1986","endPage":"1989","ipdsId":"IP-125352","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":451944,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid2707.204864","text":"Publisher Index Page"},{"id":387139,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418595,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FLC1XK"}],"volume":"27","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":818976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Steven J. 0000-0002-2388-0579","orcid":"https://orcid.org/0000-0002-2388-0579","contributorId":57738,"corporation":false,"usgs":false,"family":"Price","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":818977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":818978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drayer, Andrea N.","contributorId":212843,"corporation":false,"usgs":false,"family":"Drayer","given":"Andrea","email":"","middleInitial":"N.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":818979,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70229175,"text":"70229175 - 2021 - Trophic niches of native and nonnative fishes along a river-reservoir continuum","interactions":[],"lastModifiedDate":"2022-03-02T17:42:26.092574","indexId":"70229175","displayToPublicDate":"2021-06-09T11:33:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Trophic niches of native and nonnative fishes along a river-reservoir continuum","docAbstract":"<p>Instream barriers can constrain dispersal of nonnative fishes, creating opportunities to test their impact on native communities above and below these barriers. Deposition of sediments in a river inflow to Lake Powell, USA resulted in creation of a large waterfall prohibiting upstream movement of fishes from the reservoir allowing us to evaluate the trophic niche of fishes above and below this barrier. We expected niche overlap among native and nonnative species would increase in local assemblages downstream of the barrier where nonnative fish diversity and abundance were higher. Fishes upstream of the barrier had more distinct isotopic niches and species exhibited a wider range in δ<sup>15</sup>N relative to downstream. In the reservoir, species were more constrained in δ<sup>15</sup>N and differed more in δ<sup>13</sup>C, representing a shorter, wider food web. Differences in energetic pathways and resource availability among habitats likely contributed to differences in isotopic niches. Endangered Razorback Sucker (<i>Xyrauchen texanus</i>) aggregate at some reservoir inflows in the Colorado River basin, and this is where we found the highest niche overlap among species. Whether isotopic niche overlap among adult native and nonnative species has negative consequences is unclear, because data on resource availability and use are lacking; however, these observations do indicate the potential for competition. Still, the impacts of diet overlap among trophic generalists, such as Razorback Sucker, are likely low, particularly in habitats with diverse and abundant food bases such as river-reservoir inflows.</p>","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-021-91730-1","usgsCitation":"Pennock, C., Ahrens, Z.T., McKinstry, M., Budy, P., and Gido, K., 2021, Trophic niches of native and nonnative fishes along a river-reservoir continuum: Scientific Reports, v. 11, p. 1-12, https://doi.org/10.1038/s41598-021-91730-1.","productDescription":"12140, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-123081","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":451948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-91730-1","text":"Publisher Index Page"},{"id":396658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Lake Powell, San Juan River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.72021484375,\n              37.131855694734625\n            ],\n            [\n              -109.77951049804688,\n              37.131855694734625\n            ],\n            [\n              -109.77951049804688,\n              37.34395908944491\n            ],\n            [\n              -110.72021484375,\n              37.34395908944491\n            ],\n            [\n              -110.72021484375,\n              37.131855694734625\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Pennock, Casey A.","contributorId":287044,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":836859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahrens, Zachary T.","contributorId":287536,"corporation":false,"usgs":false,"family":"Ahrens","given":"Zachary","email":"","middleInitial":"T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":836860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKinstry, Mark","contributorId":271257,"corporation":false,"usgs":false,"family":"McKinstry","given":"Mark","affiliations":[{"id":12646,"text":"BOR","active":true,"usgs":false}],"preferred":false,"id":836861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gido, Keith B.","contributorId":17465,"corporation":false,"usgs":true,"family":"Gido","given":"Keith B.","affiliations":[],"preferred":false,"id":836862,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221590,"text":"70221590 - 2021 - Hydropeaking intensity and dam proximity limit aquatic invertebrate diversity in the Colorado River Basin","interactions":[],"lastModifiedDate":"2021-06-24T14:18:28.947841","indexId":"70221590","displayToPublicDate":"2021-06-09T09:03:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Hydropeaking intensity and dam proximity limit aquatic invertebrate diversity in the Colorado River Basin","docAbstract":"<p><span>River biodiversity is threatened globally by hydropower dams, and there is a need to understand how dam management favors certain species while filtering out others. We examined aquatic invertebrate communities within the tailwaters 0–24&nbsp;km downstream of seven large hydropower dams in the Colorado River Basin of the western United States. We quantified aquatic invertebrate dominance, richness, abundance, and biomass at multiple locations within individual tailwaters and across the basin and identified biological community responses associated with dam operations and distance from dam. We found that each tailwater was dominated by 3–7 invertebrate taxa, accounting for 95% of total abundance. Half of these dominant taxa were non-insect, non-flying species and thus were unavailable to terrestrial consumers. Consistent with previous studies, aquatic insects and sensitive taxa were negatively associated with hydropeaking intensity (magnitude of daily flow fluctuations associated with hydropower generation), which limits the composition and potentially the quality of the invertebrate food base. While total invertebrate abundance and biomass did not change with increasing distance downstream from dams, insect and sensitive taxa richness, abundance, and biomass all increased, suggesting that impacts of hydropeaking are most acute immediately downstream of dams. Our results demonstrate that tailwaters experiencing hydropeaking support high abundances of aquatic invertebrate, but the diversity of these communities is low.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.3559","usgsCitation":"Abernathy, E., Muehlbauer, J., Kennedy, T., Tonkin, J.D., Van Driesche, R., and Lytle, D.A., 2021, Hydropeaking intensity and dam proximity limit aquatic invertebrate diversity in the Colorado River Basin: Ecosphere, v. 12, no. 6, e03559, 12 p., https://doi.org/10.1002/ecs2.3559.","productDescription":"e03559, 12 p.","ipdsId":"IP-121386","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":451952,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3559","text":"Publisher Index Page"},{"id":436321,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DM0X8U","text":"USGS data release","linkHelpText":"Benthic macroinvertebrate tailwater data in the Colorado River Basin, 2013 &amp;amp; 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,{"id":70229105,"text":"70229105 - 2021 - Disease or drought: Environmental fluctuations release zebra from a potential pathogen-triggered ecological trap","interactions":[],"lastModifiedDate":"2022-03-02T12:16:15.358591","indexId":"70229105","displayToPublicDate":"2021-06-09T08:47:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Disease or drought: Environmental fluctuations release zebra from a potential pathogen-triggered ecological trap","docAbstract":"<p><span>When a transmission hotspot for an environmentally persistent pathogen establishes in otherwise high-quality habitat, the disease may exert a strong impact on a host population. However, fluctuating environmental conditions lead to heterogeneity in habitat quality and animal habitat preference, which may interrupt the overlap between selected and risky habitats. We evaluated spatio-temporal patterns in anthrax mortalities in a plains zebra (</span><i>Equus quagga</i><span>) population in Etosha National Park, Namibia, incorporating remote-sensing and host telemetry data. A higher proportion of anthrax mortalities of herbivores was detected in open habitats than in other habitat types. Resource selection functions showed that the zebra population shifted habitat selection in response to changes in rainfall and vegetation productivity. Average to high rainfall years supported larger anthrax outbreaks, with animals congregating in preferred open habitats, while a severe drought forced animals into otherwise less preferred habitats, leading to few anthrax mortalities. Thus, the timing of anthrax outbreaks was congruent with preference for open plains habitats and a corresponding increase in pathogen exposure. Given shifts in habitat preference, the overlap in high-quality habitat and high-risk habitat is intermittent, reducing the adverse consequences for the population.</span></p>","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2021.0582","usgsCitation":"Huang, Y., Joel, H., Küsters, M., Barandongo, Z., Cloete, C.C., Hartmann, A., Kamath, P., Kilian, J.W., Mfune, J.K., Shatumbu, G., Zidon, R., Getz, W., and Turner, W.C., 2021, Disease or drought: Environmental fluctuations release zebra from a potential pathogen-triggered ecological trap: Proceedings of the Royal Society B: Biological Sciences, v. 288, no. 1952, 20210582, 10 p., https://doi.org/10.1098/rspb.2021.0582.","productDescription":"20210582, 10 p.","ipdsId":"IP-122317","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451956,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/5cj8c68f","text":"Publisher Index Page"},{"id":396601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Namibia","otherGeospatial":"Etosha National Park","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[16.34498,-28.57671],[15.60182,-27.82125],[15.21047,-27.09096],[14.98971,-26.11737],[14.74321,-25.39292],[14.40814,-23.85301],[14.38572,-22.65665],[14.25771,-22.11121],[13.86864,-21.69904],[13.3525,-20.87283],[12.82685,-19.67317],[12.60856,-19.04535],[11.79492,-18.06913],[11.7342,-17.30189],[12.21546,-17.11167],[12.81408,-16.94134],[13.46236,-16.97121],[14.0585,-17.42338],[14.20971,-17.3531],[18.26331,-17.30995],[18.95619,-17.78909],[21.37718,-17.93064],[23.21505,-17.52312],[24.03386,-17.29584],[24.68235,-17.35341],[25.07695,-17.57882],[25.08444,-17.66182],[24.52071,-17.88712],[24.21736,-17.88935],[23.57901,-18.28126],[23.19686,-17.86904],[21.65504,-18.21915],[20.91064,-18.25222],[20.88113,-21.81433],[19.89546,-21.84916],[19.89577,-24.76779],[19.89473,-28.4611],[19.00213,-28.97244],[18.4649,-29.04546],[17.83615,-28.85638],[17.3875,-28.78351],[17.21893,-28.35594],[16.82402,-28.08216],[16.34498,-28.57671]]]},\"properties\":{\"name\":\"Namibia\"}}]}","volume":"288","issue":"1952","noUsgsAuthors":false,"publicationDate":"2021-06-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Huang, Yen-Hua","contributorId":287150,"corporation":false,"usgs":false,"family":"Huang","given":"Yen-Hua","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":836527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Joel, Hendrina","contributorId":287154,"corporation":false,"usgs":false,"family":"Joel","given":"Hendrina","affiliations":[{"id":39588,"text":"University of Namibia","active":true,"usgs":false}],"preferred":false,"id":836531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Küsters, Martina","contributorId":287157,"corporation":false,"usgs":false,"family":"Küsters","given":"Martina","affiliations":[{"id":61496,"text":"Etosha Ecological Institute","active":true,"usgs":false}],"preferred":false,"id":836534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barandongo, Zoe R.","contributorId":287489,"corporation":false,"usgs":false,"family":"Barandongo","given":"Zoe R.","affiliations":[],"preferred":false,"id":836806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cloete, Claudine C.","contributorId":287151,"corporation":false,"usgs":false,"family":"Cloete","given":"Claudine","email":"","middleInitial":"C.","affiliations":[{"id":61496,"text":"Etosha Ecological Institute","active":true,"usgs":false}],"preferred":false,"id":836528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartmann, Axel","contributorId":287153,"corporation":false,"usgs":false,"family":"Hartmann","given":"Axel","email":"","affiliations":[{"id":61496,"text":"Etosha Ecological Institute","active":true,"usgs":false}],"preferred":false,"id":836530,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kamath, Pauline L.","contributorId":287155,"corporation":false,"usgs":false,"family":"Kamath","given":"Pauline L.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":836532,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kilian, J. 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,{"id":70223842,"text":"70223842 - 2021 - Migration patterns and wintering distribution of common loons breeding in the Upper Midwest","interactions":[],"lastModifiedDate":"2021-09-10T12:27:12.260118","indexId":"70223842","displayToPublicDate":"2021-06-09T07:23:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Migration patterns and wintering distribution of common loons breeding in the Upper Midwest","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Identification of geographic linkages among breeding, migratory and wintering common loon<span>&nbsp;</span><i>Gavia immer</i><span>&nbsp;</span>populations is needed to inform regional and national conservation planning efforts and compensation of loons lost during marine oil spill events. Satellite telemetry and archival geolocator tags were used to determine the migration patterns and wintering locations of breeding adult and young of the year juvenile common loons captured and marked on lakes in Minnesota, Wisconsin and Michigan. Adult loons typically traveled from breeding lakes, often via larger staging lakes, to the Great Lakes (primarily Lake Michigan) and then on to wintering areas. Most radiomarked juvenile common loons utilized natal lakes or local lakes through mid-November. Subsequently, the first fall migration of juvenile loons was generally initiated later, and more direct and quicker to wintering areas relative to adults. Among adult (n = 103) and juvenile (n = 23) loons that completed fall migration, most wintered in the Gulf of Mexico (GOM), with smaller proportions wintering off the southern Atlantic Coast or impoundments in the southeastern United States. Spring migration of adults to breeding lakes was less prolonged than fall migration, with adult male loons tending to depart wintering areas earlier than adult females. Juvenile common loons migrated during their first spring from wintering sites in the GOM to summer in the Gulf of St Lawrence/Nova Scotia Coastal region. Juvenile mortality was largely linked to parasitic infection and emaciation; spring appeared to be a survival bottleneck among juvenile loons monitored in our study. Our results identify several areas where common loon conservation efforts could be directed to protect key habitats and minimize stressors during the non-breeding period.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/jav.02609","usgsCitation":"Kenow, K.P., Fara, L., Houdek, S.C., Gray, B.R., Heard, D.J., Meyer, M.W., Fox, T.J., Kratt, R., Ford, S.L., Gendron-Fitzpatrick, A., and Henderson, C.L., 2021, Migration patterns and wintering distribution of common loons breeding in the Upper Midwest: Journal of Avian Biology, v. 52, no. 8, e02609, 18 p., https://doi.org/10.1111/jav.02609.","productDescription":"e02609, 18 p.","ipdsId":"IP-118791","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":490076,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jav.02609","text":"Publisher Index Page"},{"id":436322,"rank":0,"type":{"id":30,"text":"Data 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tfox@usgs.gov","orcid":"https://orcid.org/0000-0002-6167-3001","contributorId":1701,"corporation":false,"usgs":true,"family":"Fox","given":"Timothy","email":"tfox@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":822900,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kratt, Robert 0000-0003-3314-7669 rkratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3314-7669","contributorId":3012,"corporation":false,"usgs":true,"family":"Kratt","given":"Robert","email":"rkratt@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":822901,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ford, Scott L.","contributorId":265536,"corporation":false,"usgs":false,"family":"Ford","given":"Scott","email":"","middleInitial":"L.","affiliations":[{"id":35864,"text":"Avian Specialty Veterinary Services","active":true,"usgs":false}],"preferred":false,"id":822902,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gendron-Fitzpatrick, Anette 0000-0001-5286-7069","orcid":"https://orcid.org/0000-0001-5286-7069","contributorId":265537,"corporation":false,"usgs":false,"family":"Gendron-Fitzpatrick","given":"Anette","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":822903,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Henderson, Carrol L.","contributorId":213967,"corporation":false,"usgs":false,"family":"Henderson","given":"Carrol","email":"","middleInitial":"L.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":822904,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70223155,"text":"70223155 - 2021 - Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands","interactions":[],"lastModifiedDate":"2021-09-14T16:50:28.22241","indexId":"70223155","displayToPublicDate":"2021-06-09T07:19:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands","docAbstract":"<ul class=\"unordered-list\"><li>Dryland net primary productivity (NPP) is sensitive to temporal variation in precipitation (PPT), but the magnitude of this ‘temporal sensitivity’ varies spatially. Hypotheses for spatial variation in temporal sensitivity have often emphasized abiotic factors, such as moisture limitation, while overlooking biotic factors, such as vegetation structure.</li><li>We tested these hypotheses using spatiotemporal models fit to remote-sensing data sets to assess how vegetation structure and climate influence temporal sensitivity across five dryland ecoregions of the western USA.</li><li>Temporal sensitivity was higher in locations and ecoregions dominated by herbaceous vegetation. By contrast, much less spatial variation in temporal sensitivity was explained by mean annual PPT. In fact, ecoregion-specific models showed inconsistent associations of sensitivity and PPT; whereas sensitivity decreased with increasing mean annual PPT in most ecoregions, it increased with mean annual PPT in the most arid ecoregion, the hot deserts.</li><li>The strong, positive influence of herbaceous vegetation on temporal sensitivity indicates that herbaceous-dominated drylands will be particularly sensitive to future increases in precipitation variability and that dramatic changes in cover type caused by invasions or shrub encroachment will lead to changes in dryland NPP dynamics, perhaps independent of changes in precipitation.</li></ul>","language":"English","publisher":"Wiley","doi":"10.1111/nph.17543","usgsCitation":"Felton, A., Shriver, R.K., Bradford, J., Suding, K.N., Allred, B.W., and Adler, P.B., 2021, Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands: New Phytologist, v. 231, no. 6, p. 2150-2161, https://doi.org/10.1111/nph.17543.","productDescription":"12 p.","startPage":"2150","endPage":"2161","ipdsId":"IP-130381","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":451960,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.17543","text":"Publisher Index Page"},{"id":387892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"231","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-07-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Felton, Andrew J","contributorId":264213,"corporation":false,"usgs":false,"family":"Felton","given":"Andrew J","affiliations":[{"id":54404,"text":"Department of Wildland Resources and The Ecology Center, Utah State University, Logan, Utah","active":true,"usgs":false}],"preferred":false,"id":821118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shriver, Robert K 0000-0002-4590-4834","orcid":"https://orcid.org/0000-0002-4590-4834","contributorId":222834,"corporation":false,"usgs":false,"family":"Shriver","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":821119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":821120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suding, Katharine N. 0000-0002-5357-0176","orcid":"https://orcid.org/0000-0002-5357-0176","contributorId":168385,"corporation":false,"usgs":false,"family":"Suding","given":"Katharine","email":"","middleInitial":"N.","affiliations":[{"id":6709,"text":"University of Colorado, Denver","active":true,"usgs":false}],"preferred":false,"id":821121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allred, Brady W","contributorId":216378,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","email":"","middleInitial":"W","affiliations":[{"id":39397,"text":"W.A. Franke College of Forestry and Conservation University of Montana, Missoula","active":true,"usgs":false}],"preferred":false,"id":821122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":821123,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70221565,"text":"70221565 - 2021 - Persistent multidecadal variability since the 15th century in the southern Barents Sea derived from annually resolved shell-based records","interactions":[],"lastModifiedDate":"2021-06-23T12:26:54.254945","indexId":"70221565","displayToPublicDate":"2021-06-09T07:18:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2321,"text":"Journal of Geophysical Research: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Persistent multidecadal variability since the 15th century in the southern Barents Sea derived from annually resolved shell-based records","docAbstract":"<p><span>In the North Atlantic Ocean, multidecadal variability in sea surface temperatures (SSTs) over the past several centuries has largely been inferred through terrestrial proxies and decadally resolved marine proxies. Annually resolved proxy records from marine archives provide valuable insight into this variability, but are especially rare from high latitude environments, particularly for centennial timescales. We constructed continuous, absolutely dated records of shell growth (1449–2014 CE; 564&nbsp;years) and oxygen isotope ratios (δ</span><sup>18</sup><span>O</span><sub>shell</sub><span>; 1539–2014 CE; 476&nbsp;years) from shells of the bivalve&nbsp;</span><i>Arctica islandica</i><span>&nbsp;from coastal northern Norway, a location sensitive to large-scale North Atlantic Ocean dynamics. An annual (January–December) SST reconstruction derived from δ</span><sup>18</sup><span>O</span><sub>shell</sub><span>&nbsp;for the past five centuries suggests an increase of at least 2°C from the mid-18th century to 2014. The SST reconstruction correlates significantly with instrumental records and with other proxy reconstructions in the southern Barents Sea region. Spectral analysis of the shell growth and isotope records supports evidence for Atlantic multidecadal variability (65–80&nbsp;year periodicity) extending into polar and subpolar latitudes for the past five centuries. These results provide additional evidence that multidecadal variability in SSTs are a persistent feature of the North Atlantic marine system.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JC017074","usgsCitation":"Mette, M., Wanamaker, A.D., Retelle, M.J., Carroll, M.L., Andersson, C., and Ambrose, W.G., 2021, Persistent multidecadal variability since the 15th century in the southern Barents Sea derived from annually resolved shell-based records: Journal of Geophysical Research: Oceans, v. 126, no. 6, e2020JC017074, 22 p., https://doi.org/10.1029/2020JC017074.","productDescription":"e2020JC017074, 22 p.","ipdsId":"IP-124748","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Norway, Iceland, Greenland","otherGeospatial":"Greenland Sea, Iceland Sea, Norwegian Sea, Barents Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              5.2734375,\n              58.26328705248601\n            ],\n            [\n              6.6796875,\n              61.60639637138628\n            ],\n            [\n              15.99609375,\n              67.40748724648756\n            ],\n            [\n              27.24609375,\n              70.78690984117928\n            ],\n            [\n              61.69921875,\n              77.19617635994676\n            ],\n            [\n              15.99609375,\n              76.63922560965885\n            ],\n            [\n              4.04296875,\n              79.74993207509453\n            ],\n            [\n              -18.45703125,\n              79.20430943611333\n            ],\n            [\n              -24.609375,\n              73.3782147793946\n            ],\n            [\n              -36.73828124999999,\n              65.94647177615738\n            ],\n            [\n              -42.01171875,\n              62.67414334669093\n            ],\n            [\n              -29.003906249999996,\n              52.482780222078226\n            ],\n            [\n              -11.42578125,\n              57.040729838360875\n            ],\n            [\n              -0.87890625,\n              61.52269494598361\n            ],\n            [\n              5.2734375,\n              58.26328705248601\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Mette, Madelyn Jean 0000-0002-4504-8847","orcid":"https://orcid.org/0000-0002-4504-8847","contributorId":260511,"corporation":false,"usgs":true,"family":"Mette","given":"Madelyn Jean","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wanamaker, Alan D. Jr.","contributorId":260512,"corporation":false,"usgs":false,"family":"Wanamaker","given":"Alan","suffix":"Jr.","email":"","middleInitial":"D.","affiliations":[{"id":52605,"text":"Iowa State University, USA","active":true,"usgs":false}],"preferred":false,"id":818063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Retelle, Michael J. 0000-0002-5341-0711","orcid":"https://orcid.org/0000-0002-5341-0711","contributorId":260513,"corporation":false,"usgs":false,"family":"Retelle","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":52606,"text":"Bates College, USA; University Centre in Svalbard, Norway","active":true,"usgs":false}],"preferred":false,"id":818064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carroll, Michael L. 0000-0002-1530-6016","orcid":"https://orcid.org/0000-0002-1530-6016","contributorId":260514,"corporation":false,"usgs":false,"family":"Carroll","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":52607,"text":"Akvaplan-niva, FRAM - High North Research Centre for Climate and the Environment, Norway","active":true,"usgs":false}],"preferred":false,"id":818065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andersson, Carin 0000-0002-7113-6066","orcid":"https://orcid.org/0000-0002-7113-6066","contributorId":260515,"corporation":false,"usgs":false,"family":"Andersson","given":"Carin","email":"","affiliations":[{"id":52608,"text":"NORCE Norwegian Research Centre, Norway; Bjerknes Centre for Climate Research, Norway","active":true,"usgs":false}],"preferred":false,"id":818066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ambrose, William G. Jr. 0000-0002-0709-7779","orcid":"https://orcid.org/0000-0002-0709-7779","contributorId":260516,"corporation":false,"usgs":false,"family":"Ambrose","given":"William","suffix":"Jr.","email":"","middleInitial":"G.","affiliations":[{"id":52609,"text":"Coastal Carolina University, USA","active":true,"usgs":false}],"preferred":false,"id":818067,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70221349,"text":"70221349 - 2021 - Beyond streamflow: Call for a national data repository of streamflow presence for streams and rivers in the United States","interactions":[],"lastModifiedDate":"2021-06-14T11:44:55.108744","indexId":"70221349","displayToPublicDate":"2021-06-09T07:10:54","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Beyond streamflow: Call for a national data repository of streamflow presence for streams and rivers in the United States","docAbstract":"<p><span>Observations of the presence or absence of surface water in streams are useful for characterizing streamflow permanence, which includes the frequency, duration, and spatial extent of surface flow in streams and rivers. Such data are particularly valuable for headwater streams, which comprise the vast majority of channel length in stream networks, are often non-perennial, and are frequently the most data deficient. Datasets of surface water presence exist across multiple data collection groups in the United States but are not well aligned for easy integration. Given the value of these data, a unified approach for organizing information on surface water presence and absence collected by diverse surveys would facilitate more effective and broad application of these data and address the gap in streamflow data in headwaters. In this paper, we highlight the numerous existing datasets on surface water presence in headwater streams, including recently developed crowdsourcing approaches. We identify the challenges of integrating multiple surface water presence/absence datasets that include differences in the definitions and categories of streamflow status, data collection method, spatial and temporal resolution, and accuracy of geographic location. Finally, we provide a list of critical and useful components that could be used to integrate different streamflow permanence datasets.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w13121627","usgsCitation":"Jaeger, K.L., Hafen, K., Dunham, J.B., Fritz, K.M., Kampf, S.K., Barnhart, T., Kaiser, K.E., Sando, R., Johnson, S.L., McShane, R., and Dunn, S.B., 2021, Beyond streamflow: Call for a national data repository of streamflow presence for streams and rivers in the United States: Water, v. 12, no. 13, 20 p., https://doi.org/10.3390/w13121627.","productDescription":"20 p.","ipdsId":"IP-126559","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":451965,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13121627","text":"Publisher Index Page"},{"id":386412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                48.27\n              ],\n              [\n          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         -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"12","issue":"13","noUsgsAuthors":false,"publicationDate":"2021-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hafen, Konrad 0000-0002-1451-362X","orcid":"https://orcid.org/0000-0002-1451-362X","contributorId":215959,"corporation":false,"usgs":true,"family":"Hafen","given":"Konrad","email":"","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":817399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritz, Ken M. 0000-0002-3831-2531","orcid":"https://orcid.org/0000-0002-3831-2531","contributorId":203959,"corporation":false,"usgs":false,"family":"Fritz","given":"Ken","email":"","middleInitial":"M.","affiliations":[{"id":36773,"text":"USEPA NERL","active":true,"usgs":false}],"preferred":false,"id":817400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kampf, Stephanie K. 0000-0001-8991-2679","orcid":"https://orcid.org/0000-0001-8991-2679","contributorId":225146,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","email":"","middleInitial":"K.","affiliations":[{"id":41048,"text":"Associate Professor, Department of Ecosystem Science and Sustainability, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":817401,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":202558,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817402,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kaiser, Kendra E. 0000-0003-1773-6236","orcid":"https://orcid.org/0000-0003-1773-6236","contributorId":211475,"corporation":false,"usgs":false,"family":"Kaiser","given":"Kendra","email":"","middleInitial":"E.","affiliations":[{"id":38255,"text":"Boise State Unviersity","active":true,"usgs":false}],"preferred":false,"id":817403,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":817404,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Sherri L 0000-0002-4223-3465","orcid":"https://orcid.org/0000-0002-4223-3465","contributorId":192210,"corporation":false,"usgs":false,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":817405,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McShane, Ryan R. 0000-0002-3128-0039","orcid":"https://orcid.org/0000-0002-3128-0039","contributorId":219009,"corporation":false,"usgs":true,"family":"McShane","given":"Ryan R.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817406,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dunn, Sarah Beth 0000-0003-4463-0074","orcid":"https://orcid.org/0000-0003-4463-0074","contributorId":260169,"corporation":false,"usgs":true,"family":"Dunn","given":"Sarah","email":"","middleInitial":"Beth","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817407,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70228896,"text":"70228896 - 2021 - Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff","interactions":[],"lastModifiedDate":"2022-02-23T12:55:03.615285","indexId":"70228896","displayToPublicDate":"2021-06-09T06:47:57","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff","docAbstract":"<div class=\"article-section__content en main\"><p>Applying models to developed agricultural regions remains a difficult problem because there are no existing modeling codes that represent both the complex physics of the hydrology and anthropogenic manipulations to water distribution and consumption. We apply an integrated groundwater – surface water and hydrologic river operations model to an irrigated river valley in northwestern Nevada/northern California, United States to evaluate the impacts of climate change on snow-fed agricultural systems that use surface water and groundwater conjunctively. We explicitly represent individual surface water rights within the hydrologic model and allow the integrated code to change river diversions in response to earlier snowmelt runoff and water availability. Historically under-used supplemental groundwater rights are dynamically activated within the model to offset diminished surface water deliveries. The model accounts for feedbacks between the natural hydrology and anthropogenic stresses, which is a first-of-its-kind assessment of the impacts of climate change on individual water rights, and more broadly on river basin operations. Earlier snowmelt decreases annual surface water deliveries to all water rights, not just the junior water rights, owing to a lack of surface water storage in the upper river basin capable of capturing earlier runoff. Conversely, downstream irrigators with access to reservoir storage benefit from earlier runoff flowing past upstream points of diversion prior to the start of the irrigation season. Despite regional shifts toward greater reliance on groundwater for irrigation, crop consumption (a common surrogate for crop yield) decreases due to spatiotemporal changes in water supply that preferentially impact a subset of growers in the region.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR027924","usgsCitation":"Kitlasten, W., Morway, E.D., Niswonger, R.G., Gardner, M., White, J.T., Triana, E., and Selkowitz, D.J., 2021, Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff: Water Resources Research, v. 57, no. 6, e2020WR027924, 30 p., https://doi.org/10.1029/2020WR027924.","productDescription":"e2020WR027924, 30 p.","ipdsId":"IP-117751","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":451969,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020wr027924","text":"Publisher Index Page"},{"id":436323,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MDWZM4","text":"USGS data release","linkHelpText":"GSFLOW and MODSIM-GSFLOW model used to evaluate the potential effects of increased temperature on the Carson Valley watershed and agricultural system in eastern California and western Nevada"},{"id":396333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Carson Valley system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.9921875,\n              37.96152331396614\n            ],\n            [\n              -119.0478515625,\n              37.96152331396614\n            ],\n            [\n              -119.0478515625,\n              39.53793974517628\n            ],\n            [\n              -121.9921875,\n              39.53793974517628\n            ],\n            [\n              -121.9921875,\n              37.96152331396614\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"57","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kitlasten, Wesley 0000-0002-2049-9107","orcid":"https://orcid.org/0000-0002-2049-9107","contributorId":279994,"corporation":false,"usgs":false,"family":"Kitlasten","given":"Wesley","affiliations":[],"preferred":false,"id":835821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":835822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":835823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, Murphy 0000-0002-3951-6667","orcid":"https://orcid.org/0000-0002-3951-6667","contributorId":279996,"corporation":false,"usgs":false,"family":"Gardner","given":"Murphy","affiliations":[],"preferred":false,"id":835824,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":835825,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Triana, Enrique","contributorId":169532,"corporation":false,"usgs":false,"family":"Triana","given":"Enrique","email":"","affiliations":[{"id":25556,"text":"MWH Global, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":835826,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":835827,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70221226,"text":"ofr20211021 - 2021 - Cape Romain partnership for coastal protection","interactions":[],"lastModifiedDate":"2021-06-09T15:41:26.952716","indexId":"ofr20211021","displayToPublicDate":"2021-06-08T16:20:09","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":"2021-1021","displayTitle":"Cape Romain Partnership for Coastal Protection","title":"Cape Romain partnership for coastal protection","docAbstract":"<p>This final report summarizes activities, outcomes, and lessons learned from a 3-year project titled “Climate Change Adaptation for Coastal National Wildlife Refuges” with the Cape Romain National Wildlife Refuge (NWR) and local partners in the surrounding South Carolina Lowcountry. The Lowcountry is classified as the 10-county area encompassing the coastal plain of South Carolina (this report specifically focuses on Berkeley, Charleston, and Georgetown Counties). The goals of this work, sponsored by the U.S. Geological Survey’s Southeast Climate Adaptation Science Center (SECASC), were to foster active engagement with stakeholders; to develop a comprehensive definition of adaptation problems faced by agencies, organizations, and individuals near the Cape Romain NWR that accounts for global change, local values, knowledge and perceptions; and to encourage social learning and building of effective networks and trust across South Carolina Lowcountry organizations and individuals. Although project scoping began at the scale of the Atlantic seaboard, by engaging with NWRs from Massachusetts to Florida, participating refuge personnel eventually selected the Cape Romain NWR to serve as a case study for testing our goals. The Cape Romain Partnership for Coastal Conservation was established to address global change impacts at a regional level and includes representation from Federal and State resource agencies, local conservation nongovernmental organizations, and organizations representing underserved community interests. Research topics, originating from discussions with Cape Romain Partnership for Coastal Conservation members, focused on quantifying key drivers of change including localized sea-level rise (SLR) predictions, estimates of coastal hurricane inundation as amplified by SLR, and urban growth trends and forecasts. These key drivers provided a foundation to engage stakeholders in planning exercises to begin a process of collective understanding and collaborative decision making. The goal of this process was to develop collective strategies of adaptation to enhance community and ecosystem resilience in the South Carolina Lowcountry.</p><p>South Carolina’s Lowcountry is experiencing rapid environmental and social transformation because of SLR rates approaching twice the global average, chronic tidal flooding and catastrophic storm surges, erosion and loss of habitats that provide essential services to wildlife and humans, and increasing social polarization fueled by aggressive low-density urban growth and other forms of land conversion. To support characterizations of plausible future scenarios, we used available or, in some cases, developed new models to project future conditions of key environmental and social-economic drivers. Because of the imprecision of mean global SLR projections, the SECASC commissioned a climatological study to account for local conditions and multiple representative concentration pathways to project a tailored distribution of future sea levels. These projections were matched to SLR scenarios provided by existing models to anticipate the range of future coastal habitat changes in the South Carolina Lowcountry. SLR scenarios were also incorporated into existing storm-surge models, which do not account for alternate baseline sea levels, to project the local effects of future hurricanes. To evaluate the extent and effects of population growth and urban expansion, we relied on an existing urban-growth model to map the spatial distribution of land-conversion probabilities, the total area of which is predicted to increase twofold to threefold over the next 60 years. In addition to this simplified model, an econometric model is in development to account for nonlinear feedback dynamics in land value, land use, and ecosystem service production. Although not yet completed, the goals of this model are to produce more-detailed projections of growth dynamics and to allow predictions of development patterns resulting from alternate land-use planning policies and incentives.</p><p>Collaborative planning for an uncertain future requires more than providing decision makers with information on future physical and ecological conditions; developing effective and consensual strategies must also integrate sociological values, multiple cultural perspectives, and an understanding of human behavior. To support broad stakeholder engagement in integrative approaches to adaptation planning, emphasis was placed on the importance of considering differences in how individuals perceive their environment and create meaning. Because cultural frameworks form the basis for perceptions and, ultimately, the behaviors of individuals and institutions, we describe a model of human behavior and how it can be used to understand the effect of cultural complexity and variation in perception on choices, behavioral change, and long-term maintenance of behaviors. We consider a model commonly used in the field of behavioral health that accommodates variation in human perception when describing stages of behavior and the dynamics of behavioral change. Tailoring communication and engagement activities to targeted stakeholders is likely to benefit from increased understanding of behavioral change processes.</p><p>The complex nature of this problem limited the usefulness of a traditional decision-analytic approach, we explored alternative methods for engagement, collaborative learning and decision making. Recognizing that project partners and Lowcountry stakeholders may be at different stages of preparedness and interest level for modifying behavior as a function of global change, we facilitated a scenario-planning exercise to familiarize partners with this well-established approach for communicating the opportunities and threats arising under alternative, plausible futures. We developed narratives for four alternative South Carolina Lowcountry scenarios to be used in later strategic planning that focus on quantitative trends for three primary drivers with high impact and high uncertainty: manifestations of climate change, social-political shifts at a global level, and forces of local value and power structures. This scenario-planning exercise underscored the complex relation between the temporospatial scale of the production of ecological goods and services and the institutional scale at which they are managed. We then guided the partners through an assessment of the relevant strengths and weaknesses of the Cape Romain Partnership for Coastal Protection, using the threats and opportunities characterized by each scenario to understand how the partnership might respond when attempting to meet conservation and societal objectives. The partnership identified key strengths including partnership experience, outreach and technical capacities, a substantial conservation land base, and high social cohesion in the South Carolina Lowcountry. Limited communication expertise, institutional inertia, and insufficient staffing and funding were recognized as important weaknesses across the partnership. By examining and scoring combinations of internal strengths and weaknesses and external threats and opportunities, the partnership developed sets of prioritized strategies to consider in the context of a given scenario. Although we had insufficient time to examine all scenarios in detail, the intent was to identify a portfolio of strategic actions to address threats and opportunities represented in multiple plausible futures. Top-ranking strategies encompassed a range of actions that focused on strengthening the conservation community and communicating the benefits of nature (that is, ecosystem services) to leveraging partnerships to expand land protection.</p><p>This report also details the methods and preliminary results of several models developed or applied in support of this project. Two parcel-selection algorithms were used to evaluate anticipated habitat changes and patterns of urban growth to guide decisions on optimal conservation reserve design to protect habitat communities. One approach used a widely available planning software (MARXAN) to maximize conservation benefits near the Cape Romain NWR, whereas the other approach was a novel application of economic theory to account for uncertainty in future conditions and for the risks of unanticipated habitat loss. This latter model applies modern portfolio theory to estimate the risk of investing in any portfolio of land parcels (that is, candidate “reserves”) under climate-change uncertainty by quantifying the variation and spatial correlation of conservation benefits derived from each portfolio. We expanded the range of actions beyond simply whether or not to invest in a set of land parcels, an approach commonly used in spatial conservation planning, to also include consideration of divestment from currently protected lands. Such refinements allow for better accounting of system dynamics and can evaluate the benefits of flexible conservation tools such as rolling easements. Model results were conditional on a decision maker’s risk tolerance but highlighted general strategies of land conservation to increase future habitat representation beyond what is expected under the current protected land base. We built models that may help inform coastal planning by estimating salinity dynamics and the performance of oyster reef restoration efforts to predict the combined effects of global change and management of freshwater flows on coastal habitats and the processes that contribute to their resilience. These models can support restoration decisions by evaluating the expected benefits of site locations for shoreline protection and fisheries production. Lastly, we developed a spatially explicit economic model that predicts feedback dynamics among land value, land-use change, and effects on ecosystem service provision to explore zoning policies and incentives on urban growth and ecosystem services.</p><p>We summarize these efforts with insights and considerations for the Cape Romain Partnership for Coastal Protection to continue to engage stakeholders in effective adaptation planning. First, notions of place attachment (referred to as sense of place), and the role of culture in social discourse are increasingly being used to understand the complex interactions between society and the environment and how societies respond and adapt to climate change. Sense of place was a unifying theme whenever the future of the South Carolina Lowcountry was discussed. The contribution of the South Carolina Lowcountry’s environmental wealth, rich cultural heritage, and quality of life to sense of place has important implications for how adaptation planning might best be pursued. More community-based governance of the commons (in other words, natural and cultural resources held in common), in which broad stakeholder participation and power sharing are key elements, is considered important. This devolution of governance is characterized by polycentric institutions and self-organizing social networks that promote a local culture of knowledge sharing, problem solving, and learning. These so-called bridging organizations (or individuals) often provide the leadership necessary to bring together potentially disparate Government agencies and institutions, private organizations, and individuals in a collective process of problem solving. Our observations also suggest that the conservation community in the South Carolina Lowcountry views its activities as integral to the broader governance of social-ecological systems, in which responses to the forces of global change are mediated through culture, economics, and politics. Rather than directly competing with other interests, the South Carolina Lowcountry conservation community seems to embrace an interpretation of conservation in which the fundamental objective is the quality of human life rather than environmental protection.</p><p>Fundamental to the types of governance reforms described above is the notion of coproduction, in which experts and users collaborate to develop a shared body of knowledge. In this approach, scientists work with stakeholders to help frame questions, design research, and collect and analyze data. Such sustained collaborations are increasingly believed to be an effective way to produce useable (or actionable) science. The emphasis on social learning, leveraging strong social networks, coordinating and deliberating among diverse stakeholders, and applying principles of adaptive management is an essential contribution to adaptive capacity. The diverse and robust set of scientific approaches, methods to help stakeholders collaborate in effective and goal-driven planning processes, and decision tools resulting from this project hopefully will assist Cape Romain NWR and its partners prepare for climatic, ecological, and social changes over the coming decades.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211021","usgsCitation":"Eaton, M.J., Johnson, F.A., Mikels-Carrasco, J., Case, D.J., Martin, J., Stith, B., Yurek, S., Udell, B., Villegas, L., Taylor, L., Haider, Z., Charkhgard, H., and Kwon, C., 2021, Cape Romain Partnership for Coastal Protection: U.S. Geological Survey Open-File Report 2021–1021, 158 p., https://doi.org/10.3133/ofr20211021.","productDescription":"xii, 158 p.","numberOfPages":"174","onlineOnly":"Y","ipdsId":"IP-100705","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":386276,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1021/coverthb.jpg"},{"id":386277,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1021/ofr20211021.pdf","text":"Report","size":"33.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1021"}],"country":"United States","state":"South Carolina","otherGeospatial":"Cape Romain 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              -79.8431396484375,\n              32.78842902722552\n            ],\n            [\n              -79.815673828125,\n              32.765336175015776\n            ],\n            [\n              -79.63577270507811,\n              32.85421076375021\n            ],\n            [\n              -79.55886840820312,\n              32.92455477363828\n            ],\n            [\n              -79.47784423828125,\n              33.00981511270531\n            ],\n            [\n              -79.3487548828125,\n              33.0063602132054\n            ],\n            [\n              -79.27047729492188,\n              33.12490094278685\n            ],\n            [\n              -79.34600830078125,\n              33.16169660598766\n            ],\n            [\n              -79.50393676757812,\n              33.060471419708115\n            ],\n            [\n              -79.60968017578125,\n              32.99599470276581\n            ],\n            [\n              -79.6673583984375,\n              32.93838636388491\n            ],\n            [\n              -79.68658447265625,\n              32.91533251206152\n            ],\n            [\n              -79.8431396484375,\n              32.78842902722552\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/ecosystems/climate-adaptation-science-centers/southeast-casc\" href=\"https://www.usgs.gov/ecosystems/climate-adaptation-science-centers/southeast-casc\">Southeast Climate Adaptation Science Center</a><br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>127 David Clark Labs<br>Raleigh, NC 27695</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Chapter A. Introduction</li><li>Chapter B. Drivers of Change in South Carolina’s Lowcountry</li><li>Chapter C. Stakeholder Engagement</li><li>Chapter D. Scenario Planning—Possible Futures in the South Carolina Lowcountry</li><li>Chapter E. Strategic Planning Using a Strengths, Weaknesses, Opportunities, and Threats Analysis</li><li>Chapter F. Decision Support Tools to Assist with Adaptation to Sea-Level Rise and Urbanization</li><li>Chapter G. Cape Romain Partnership for Coastal Protection—Parting Thoughts</li><li>Glossary</li><li>Appendix 1. Tracks of Tropical Storms Affecting the Lowcountry, 1910–2009</li><li>Appendix 2. Coastal Salinity and Water Temperature Model</li><li>Appendix 3. Predicting Long-Term Performance and Risk of Oyster Reef Restorations Under Deep Uncertainty in Climate and Management Policy</li><li>Appendix 4. Integrating Econometric Land-Use Models with Ecological Modeling of Ecosystem Services to Guide Coastal Management and Planning—Methods and Provisional Results</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-06-08","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":216712,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":817128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Fred A. 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":213877,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":817129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mikels-Carrasco, Jessica","contributorId":245520,"corporation":false,"usgs":false,"family":"Mikels-Carrasco","given":"Jessica","email":"","affiliations":[{"id":49215,"text":"D.J. Case & Assoc.","active":true,"usgs":false}],"preferred":false,"id":817130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Case, David J.","contributorId":140653,"corporation":false,"usgs":false,"family":"Case","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13543,"text":"DJ Case & Associates","active":true,"usgs":false}],"preferred":false,"id":817131,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":216722,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":817132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stith, Bradley bstith@usgs.gov","contributorId":3596,"corporation":false,"usgs":true,"family":"Stith","given":"Bradley","email":"bstith@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":817133,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216729,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":817134,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Udell, Bradley","contributorId":216709,"corporation":false,"usgs":false,"family":"Udell","given":"Bradley","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":817135,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Villegas, Laura","contributorId":238524,"corporation":false,"usgs":false,"family":"Villegas","given":"Laura","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":817136,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Taylor, Laura","contributorId":169433,"corporation":false,"usgs":false,"family":"Taylor","given":"Laura","email":"","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":817137,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haider, Zulquarnain","contributorId":216706,"corporation":false,"usgs":false,"family":"Haider","given":"Zulquarnain","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":817138,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Charkhgard, Hadi","contributorId":216710,"corporation":false,"usgs":false,"family":"Charkhgard","given":"Hadi","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":817139,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kwon, Changhyun","contributorId":216711,"corporation":false,"usgs":false,"family":"Kwon","given":"Changhyun","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":817140,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
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2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":22}],"lastModifiedDate":"2021-06-14T19:24:16.123976","indexId":"ofr20211030","displayToPublicDate":"2021-06-08T15:32:44","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","displayTitle":"System Characterization of Earth Observation Sensors","title":"System characterization of Earth observation sensors","docAbstract":"<p>This U.S. Geological Survey Open-File Report provides information from assessments of Earth observation sensors completed by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports are provided as independent measures of basic system performance by the Earth Resources Observation and Science Cal/Val Center of Excellence team by completing the geometric, radiometric, and spatial characterization. The results of these assessments are a snapshot in time.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030","usgsCitation":"Ramaseri Chandra, S.N., comp., 2021, System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, [variously paged], https://doi.org/10.3133/ofr20211030.","productDescription":"iii, 2 p.","numberOfPages":"10","onlineOnly":"Y","ipdsId":"IP-129352","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":386313,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/ofr20211030.pdf","text":"Report","size":"21.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030"},{"id":386312,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/coverthb.jpg"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a> <br><a href=\"https://www.usgs.gov/\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>47914 252nd Street <br>Sioux Falls, SD 57198</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Introduction</li><li>System Characterization</li><li>Report Limitations</li><li>Disclaimer</li><li>Reference Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-06-08","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"compilers":[{"text":"Ramaseri Chandra, Shankar N. 0000-0002-4434-4468","orcid":"https://orcid.org/0000-0002-4434-4468","contributorId":216043,"corporation":false,"usgs":true,"family":"Ramaseri Chandra","given":"Shankar","email":"","middleInitial":"N.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":817190,"contributorType":{"id":3,"text":"Compilers"},"rank":1}]}}
,{"id":70222052,"text":"70222052 - 2021 - A review of osmoregulation in lamprey","interactions":[],"lastModifiedDate":"2022-01-06T17:51:29.334548","indexId":"70222052","displayToPublicDate":"2021-06-08T15:29:26","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":"A review of osmoregulation in lamprey","docAbstract":"<p><span>Lamprey are living representatives of the basal vertebrate agnathan lineage. Many lamprey species are anadromous with a complex life cycle that includes metamorphosis from a freshwater (FW) benthic filter-feeding larva into a parasitic juvenile which migrates to seawater (SW) or (in landlocked populations) large bodies of FW. After a juvenile/adult trophic period that can last up to two years, adults return to rivers and migrate upstream to spawn in FW. Therefore, the osmoregulatory challenges anadromous lamprey face during migrations are similar to those of derived diadromous jawed fishes because lamprey osmoregulate to maintain plasma osmolality at approximately one third SW as well. While in FW, lamprey gills actively take up ions and their kidneys excrete excess water to compensate for passive ion loss and water gain. When in SW, lamprey drink SW and their gills actively secrete excess ions (to compensate for salt loading and dehydration). Nevertheless, lampreys diverged from the rest of the vertebrate lineage more than 500 million years ago, which is reflected in similarities and differences in ionocyte (ion transport cell)&nbsp;<a class=\"topic-link\" title=\"Learn more about ultrastructure from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/ultrastructure\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/ultrastructure\">ultrastructure</a>&nbsp;and distribution as well as tight junctions in epithelia. The current review discusses recent advances in our understanding of ion transport mechanisms of lamprey with a focus on sea lamprey (</span><i>Petromyzon marinus</i><span>) due to the large literature on this species. We emphasize key molecular and cellular mechanisms in osmoregulatory organs (i.e., gill, kidney and gut) and provide insight relative to what is known in other fishes and identify areas where more research is needed.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.05.003","usgsCitation":"Ferreira-Martins, D., Wilson, J.M., Kelly, S.P., Kolosov, D., and McCormick, S.D., 2021, A review of osmoregulation in lamprey: Journal of Great Lakes Research, v. 47, no. Suppl 1, p. S59-S71, https://doi.org/10.1016/j.jglr.2021.05.003.","productDescription":"13 p.","startPage":"S59","endPage":"S71","ipdsId":"IP-120788","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451972,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2021.05.003","text":"Publisher Index Page"},{"id":387197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"Suppl 1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ferreira-Martins, Diogo","contributorId":228920,"corporation":false,"usgs":false,"family":"Ferreira-Martins","given":"Diogo","email":"","affiliations":[{"id":37062,"text":"UMASS","active":true,"usgs":false}],"preferred":false,"id":819314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Jonathan M","contributorId":261133,"corporation":false,"usgs":false,"family":"Wilson","given":"Jonathan","email":"","middleInitial":"M","affiliations":[{"id":41188,"text":"Wilfrid Laurier University","active":true,"usgs":false}],"preferred":false,"id":819315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Scott P","contributorId":261134,"corporation":false,"usgs":false,"family":"Kelly","given":"Scott","email":"","middleInitial":"P","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":819316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolosov, Dennis","contributorId":261136,"corporation":false,"usgs":false,"family":"Kolosov","given":"Dennis","email":"","affiliations":[{"id":16184,"text":"York University","active":true,"usgs":false}],"preferred":false,"id":819317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":819318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70221219,"text":"ofr20211052 - 2021 - Fluvial Egg Drift Simulator (FluEgg) user’s manual","interactions":[],"lastModifiedDate":"2021-06-09T15:26:43.415516","indexId":"ofr20211052","displayToPublicDate":"2021-06-08T11:02:47","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":"2021-1052","displayTitle":"Fluvial Egg Drift Simulator (FluEgg) User’s Manual","title":"Fluvial Egg Drift Simulator (FluEgg) user’s manual","docAbstract":"<p>The Fluvial Egg Drift Simulator (FluEgg) was developed to simulate the transport and dispersion of invasive carp eggs and larvae in a river. FluEgg currently (2020) supports modeling of bighead carp (<i>Hypophthalmichthys nobilis</i>), silver carp (<i>H. molitrix</i>), and grass carp (<i>Ctenopharyngodon idella</i>), with the planned addition of black carp (<i>Mylopharyngodon piceus</i>) once developmental data are available. FluEgg integrates the biological development of invasive carp eggs and larvae with a particle transport model that simulates the advection and dispersion of the eggs and larvae based on user-supplied one-dimensional hydraulic conditions. FluEgg can be used to evaluate the hydrodynamic suitability of a river for invasive carp spawning, to inform sampling and monitoring efforts, and to identify the most likely spawning areas of captured eggs or larvae.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211052","usgsCitation":"Domanski, M.M., LeRoy, J.Z., Berutti, M., and Jackson, P.R., 2021, Fluvial Egg Drift Simulator (FluEgg) user’s manual: U.S. Geological Survey Open-File Report 2021–1052, 30 p., https://doi.org/10.3133/ofr20211052.","productDescription":"Report: vii, 30 p.; Software Release","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-120778","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":386269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1052/coverthb.jpg"},{"id":386270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1052/ofr20211052.pdf","text":"Report","size":"2.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1052"},{"id":386273,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://doi.org/10.5066/P93UCQR2","text":"USGS software release","linkHelpText":"— FluEgg"}],"contact":"<p><a data-mce-href=\"mailto:%20dc_il@usgs.gov\" href=\"mailto:%20dc_il@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/cm-water\" href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br><a data-mce-href=\"https://www.usgs.gov/\" href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>405 North Goodwin <br>Urbana, IL 61801</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Installation</li><li>Graphical User Interface for the Fluvial Egg Drift Simulator (FluEgg)</li><li>Reverse Modeling</li><li>Plotting and Post-Processing Results</li><li>Example Applications</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-06-08","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LeRoy, Jessica Z. 0000-0003-4035-6872 jzinger@usgs.gov","orcid":"https://orcid.org/0000-0003-4035-6872","contributorId":174534,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica","email":"jzinger@usgs.gov","middleInitial":"Z.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berutti, Michael","contributorId":259314,"corporation":false,"usgs":false,"family":"Berutti","given":"Michael","email":"","affiliations":[],"preferred":false,"id":817104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":817105,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70242081,"text":"70242081 - 2021 - Navigating the science-policy interface","interactions":[],"lastModifiedDate":"2023-04-06T15:12:51.569789","indexId":"70242081","displayToPublicDate":"2021-06-08T10:01:50","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Navigating the science-policy interface","docAbstract":"As a wildlife population ecologist who wants to conduct useful science, I find the Endangered Species Act (ESA), like other federal wildlife statutes,  an intriguing read. The topic is in my wheelhouse—fish, wildlife, and plants, with a focus at the population and species levels. There is an emphasis on science, in fact, the “best scientific and commercial data available.”  And there are intriguing questions: what threats does a species face? What habitat would be critical for its survival? Could any federal actions put the species or critical habitat in greater peril? I am not alone in this attraction. Hundreds of scientists continue to consider the types of scientific analysis suggested by the ESA.  The enthusiasm is palpable.\n\nIf the first cursory read of the ESA is intriguing to me as a scientist, the second close read is tantalizing—I realize that something very attractive is just out of reach. I know how to estimate the probability of extinction, but I do not know what “in danger of extinction” means.  I know how to evaluate the incremental change in status that might arise from some level of proposed take, but I do not know what “is not likely to jeopardize the continued existence” of a species means.  The standards expressed in the statute are not stated in purely scientific terms. Thus, ESA decisions cannot be based solely on science, and require additional policy interpretation.  Clarity about these policy interpretations—even awareness that they are needed—can be hard to find, leaving a gap between what I can provide as a scientist and what an ESA decision maker needs.\n\nThis awareness of the interaction between science and policy is also occurring in the larger field of conservation science, where there has been an increasing recognition of a research-implementation gap,  the need for actionable science,  and the promise of translational ecology.  All of these terms emphasize that science alone does not result in action; instead, action arises out of decisions that are informed both by science and by values. At the interface of science and policy, a scientist can deliver relevant knowledge, and a decision maker can explain the policy context in which that science is needed. As a scientist wanting to conduct useful science, I crave this two-way conversation. But how can this conversation be structured in a meaningful and appropriate way?\n\nIn this chapter, I explore how decision analysis can be used to navigate the science-policy interface for ESA decisions. Decision analysis is a large, well-established field that studies how decisions are made and how they could be made, with explicit attention given to clarifying and separating the values-based and science-based elements of a decision; identifying the impediments that make a decision difficult; and providing tools to overcome those impediments. There have been concerted efforts to apply formal decision analysis to ESA decisions,  but the practice is not yet widespread across both the U.S. Fish and Wildlife Service and the National Marine Fisheries Service (the Services).\n\nThe chapter begins with an introduction to decision analysis and how it seeks to bridge the science-policy interface. In subsequent sections, I explore how a decision analyst might frame listing and reclassification decisions, recovery planning, section 7 consultation, budget allocations, and a few other ESA decisions, with an emphasis on two questions: for each type of decision, what policy clarifications does the decision maker need to make; and knowing the policy context, what type of scientific assessment is needed. In the final discussion, I identify common themes among the types of decisions, and offer thoughts on how decision analysis could be more widely used to integrate science into ESA decisions.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Endangered species act: Law, policy, and perspectives","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Bar Association","usgsCitation":"Runge, M.C., 2021, Navigating the science-policy interface, chap. <i>of</i> Endangered species act: Law, policy, and perspectives, p. 391-416.","productDescription":"26 p.","startPage":"391","endPage":"416","ipdsId":"IP-101704","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":415322,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.americanbar.org/products/inv/book/413429989/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Baur, Donald","contributorId":304009,"corporation":false,"usgs":false,"family":"Baur","given":"Donald","email":"","affiliations":[],"preferred":false,"id":868880,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Li, Ya-Wei","contributorId":304010,"corporation":false,"usgs":false,"family":"Li","given":"Ya-Wei","email":"","affiliations":[],"preferred":false,"id":868881,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"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":868780,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70230786,"text":"70230786 - 2021 - Evidence for latent crustal fluid injection transients in southern California from long-duration earthquake swarms","interactions":[],"lastModifiedDate":"2022-04-26T15:05:29.120521","indexId":"70230786","displayToPublicDate":"2021-06-08T10:00:27","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":"Evidence for latent crustal fluid injection transients in southern California from long-duration earthquake swarms","docAbstract":"<p><span>Earthquake swarms are manifestations of aseismic driving processes deep in the crust. We examine the spatiotemporal distribution of aseismic processes in Southern California using a 12-years catalog of swarms derived with deep learning algorithms. In a core portion of the plate boundary region, which is not associated with elevated heat flow, we identify 92 long-duration swarms ranging from 6&nbsp;months to 7&nbsp;years that constitute 26.4% of the total seismicity. We find that 53% of the swarms exhibit ultra-slow diffusive patterns with propagating backfronts, consistent with expectations for natural fluid injection processes. The chronology of the swarms indicates that the aseismic driving processes were active at all times during 2008–2020. The observations challenge common views about the nature of swarms, which would characterize any one of these sequences as anomalous. The regional prevalence of these sequences suggests that transient fluid injection processes play a key role in crustal fluid transport.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GL092465","usgsCitation":"Ross, Z.E., and Cochran, E.S., 2021, Evidence for latent crustal fluid injection transients in southern California from long-duration earthquake swarms: Geophysical Research Letters, v. 48, no. 12, e2021GL092465, 12 p., https://doi.org/10.1029/2021GL092465.","productDescription":"e2021GL092465, 12 p.","ipdsId":"IP-128760","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":451975,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021gl092465","text":"External Repository"},{"id":399670,"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              -117,\n              33\n            ],\n            [\n              -115.75,\n              33\n            ],\n            [\n              -115.75,\n              33.75\n            ],\n            [\n              -117,\n              33.75\n            ],\n            [\n              -117,\n              33\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"48","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Ross, Zachary E.","contributorId":196001,"corporation":false,"usgs":false,"family":"Ross","given":"Zachary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":841359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":841360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70228415,"text":"70228415 - 2021 - Long-term population fluctuations of a Burrowing Owl population on Kirtland Air Force Base, New Mexico, USA","interactions":[],"lastModifiedDate":"2022-02-10T16:06:53.252014","indexId":"70228415","displayToPublicDate":"2021-06-08T10:00:25","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":"Long-term population fluctuations of a Burrowing Owl population on Kirtland Air Force Base, New Mexico, USA","docAbstract":"<p><span>Western Burrowing Owls (</span><i>Athene cunicularia hypugaea</i><span>; hereafter, Burrowing Owls) were once widespread residents of grasslands throughout western North America, but their range has contracted, and abundance has declined in some regions. The causes of declines and geographic variation in population trends of Burrowing Owls are unclear but may be linked to changing land use and urbanization. Burrowing Owls are often found in association with airfields and airports, and their presence at such facilities is sometimes considered to be in conflict with those operations. Documenting the long-term persistence of Burrowing Owls at active airfields can help airfield managers who face decisions regarding compatibility of owls and airfield operations. We report the results of a long-term effort to monitor Burrowing Owls on Kirtland Air Force Base in New Mexico, USA, including the rapid recovery of Burrowing Owl numbers from near-extirpation and the relationships between abundance and other demographic traits. The number of breeding pairs of Burrowing Owls increased from one pair in 2013 to 28 pairs in 2019 and 2020, and the number of fledglings produced increased from one in 2013 to 84 in 2019 and 61 in 2020. The recovery was not uniform across all areas of Kirtland Air Force Base, and some formerly occupied areas remained unoccupied. We documented dispersal outside the Air Force base boundary and that the number of breeding pairs was more strongly influenced by the number of offspring produced in the prior year than the number of owls returning from prior years, which indicated that the population is part of a larger meta-population. Our results demonstrate that the maintenance of Burrowing Owl populations is not necessarily at odds with safe airfield operations, that Burrowing Owls exhibit complex population dynamics, and can rapidly recolonize previously occupied areas if habitat and nest sites remain suitable.</span></p>","language":"English","publisher":"Raptor Research Foundation","doi":"10.3356/0892-1016-55.2.241","usgsCitation":"Lundblad, C., Conway, C.J., Cruz-McDonnell, K., Doublet, D., Desmond, M.J., Navis, C., and Ongman, K., 2021, Long-term population fluctuations of a Burrowing Owl population on Kirtland Air Force Base, New Mexico, USA: Journal of Raptor Research, v. 55, no. 2, p. 241-254, https://doi.org/10.3356/0892-1016-55.2.241.","productDescription":"14 p.","startPage":"241","endPage":"254","ipdsId":"IP-115742","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Kirtland Air Force Base","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.61407470703125,\n              34.9501163530137\n            ],\n            [\n              -106.35314941406249,\n              34.9501163530137\n            ],\n            [\n              -106.35314941406249,\n              35.08\n            ],\n            [\n              -106.61407470703125,\n              35.08\n            ],\n            [\n              -106.61407470703125,\n              34.9501163530137\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lundblad, Carl G.","contributorId":265812,"corporation":false,"usgs":false,"family":"Lundblad","given":"Carl G.","affiliations":[{"id":27205,"text":"U. 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