{"pageNumber":"347","pageRowStart":"8650","pageSize":"25","recordCount":165227,"records":[{"id":70255086,"text":"70255086 - 2022 - Broad Whitefish (Coregonus nasus) isotopic niches: Stable isotopes reveal diverse foraging strategies and habitat use in Arctic Alaska","interactions":[],"lastModifiedDate":"2024-06-13T11:21:41.858422","indexId":"70255086","displayToPublicDate":"2022-07-26T06:17:03","publicationYear":"2022","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":"Broad Whitefish (Coregonus nasus) isotopic niches: Stable isotopes reveal diverse foraging strategies and habitat use in Arctic Alaska","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Understanding the ecological niche of some fishes is complicated by their frequent use of a broad range of food resources and habitats across space and time. Little is known about Broad Whitefish (<i>Coregonus nasus</i>) ecological niches in Arctic landscapes even though they are an important subsistence species for Alaska’s Indigenous communities. We investigated the foraging ecology and habitat use of Broad Whitefish via stable isotope analyses of muscle and liver tissue and otoliths from mature fish migrating in the Colville River within Arctic Alaska. The range of δ<sup>13</sup>C (-31.8– -21.9‰) and δ<sup>15</sup>N (6.6–13.1‰) across tissue types and among individuals overlapped with isotope values previously observed in Arctic lakes and rivers, estuaries, and nearshore marine habitat. The large range of δ<sup>18</sup>O (4.5–10.9‰) and δD (-237.6– -158.9‰) suggests fish utilized a broad spectrum of habitats across elevational and latitudinal gradients. Cluster analysis of muscle δ<sup>13</sup>Cˈ, δ<sup>15</sup>N, δ<sup>18</sup>O, and δD indicated that Broad Whitefish occupied four different foraging niches that relied on marine and land-based (i.e., freshwater and terrestrial) food sources to varying degrees. Most individuals had isotopic signatures representative of coastal freshwater habitat (Group 3; 25%) or coastal lagoon and delta habitat (Group 1; 57%), while individuals that mainly utilized inland freshwater (Group 4; 4%) and nearshore marine habitats (Group 2; 14%) represented smaller proportions. Otolith microchemistry confirmed that individuals with more enriched muscle tissue δ<sup>13</sup>Cˈ, δD, and δ<sup>18</sup>O tended to use marine habitats, while individuals that mainly used freshwater habitats had values that were less enriched. The isotopic niches identified here represent important foraging habitats utilized by Broad Whitefish. To preserve access to these diverse habitats it will be important to limit barriers along nearshore areas and reduce impacts like roads and climate change on natural flow regimes. Maintaining these diverse connected habitats will facilitate long-term population stability, buffering populations from future environmental and anthropogenic perturbations.</p></div></div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0270474","usgsCitation":"Leppi, J., Rinella, D.J., Wipfli, M.S., and Whitman, M.S., 2022, Broad Whitefish (Coregonus nasus) isotopic niches: Stable isotopes reveal diverse foraging strategies and habitat use in Arctic Alaska: PLoS ONE, v. 17, no. 7, e0270474, 24 p., https://doi.org/10.1371/journal.pone.0270474.","productDescription":"e0270474, 24 p.","ipdsId":"IP-130263","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0270474","text":"Publisher Index Page"},{"id":430061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -164.60325251109555,\n              68.37356056205553\n            ],\n            [\n              -141.0485650110956,\n              68.37356056205553\n            ],\n            [\n              -141.0485650110956,\n              71.61406743804798\n            ],\n            [\n              -164.60325251109555,\n              71.61406743804798\n            ],\n            [\n              -164.60325251109555,\n              68.37356056205553\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Leppi, Jason C.","contributorId":338571,"corporation":false,"usgs":false,"family":"Leppi","given":"Jason C.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":903370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rinella, Daniel J.","contributorId":338572,"corporation":false,"usgs":false,"family":"Rinella","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":81169,"text":"Fish and Wildlife Field Conservation Office","active":true,"usgs":false}],"preferred":false,"id":903371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitman, Matthew S.","contributorId":338574,"corporation":false,"usgs":false,"family":"Whitman","given":"Matthew","email":"","middleInitial":"S.","affiliations":[{"id":81170,"text":"Arctic Field Office","active":true,"usgs":false}],"preferred":false,"id":903372,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70234107,"text":"70234107 - 2022 - Crustal permeability changes observed from seismic attenuation: Impacts on multi-mainshock sequences","interactions":[],"lastModifiedDate":"2022-10-17T15:45:49.488302","indexId":"70234107","displayToPublicDate":"2022-07-25T17:05:53","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Crustal permeability changes observed from seismic attenuation: Impacts on multi-mainshock sequences","docAbstract":"<p><span>We use amplitude ratios from narrowband-filtered earthquake seismograms to measure variations of seismic attenuation over time, providing unique insights into the dynamic state of stress in the Earth’s crust at depth. Our dataset from earthquakes of the 2016-2017 Central Apennines sequence allows us to obtain high-resolution time histories of seismic attenuation (frequency band: 0.5-30 Hz) characterized by strong earthquake dilatation-induced fluctuations at seismogenic depths, caused by the cumulative elastic stress drop after the sequence, as well as damage-induced ones at shallow depths caused by energetic surface waves.</span><br><span>Cumulative stress drop causes negative dilatation, reduced permeability, and seismic attenuation, whereas strong-motion surface waves produce an increase in crack density, and so in permeability and seismic attenuation. In the aftermath of the main shocks of the sequence, we show that the M ≥ 3.5 earthquake occurrence vs. time and distance is consistent with fluid diffusion: diffusion signatures are associated with changes in seismic attenuation during the first days of the Amatrice, Visso-Norcia, and Capitignano sub-sequences. We hypothesize that coseismic permeability changes create fluid diffusion pathways that are at least partly responsible for triggering multi-mainshock seismic sequences. Here we show that anelastic seismic attenuation fluctuates coherently with our hypothesis.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2022.963689","usgsCitation":"Malagnini, L., Parsons, T.E., Munafo, I., Mancini, S., Segou, M., and Geist, E.L., 2022, Crustal permeability changes observed from seismic attenuation: Impacts on multi-mainshock sequences: Frontiers in Earth Science, v. 10, 963689, 27 p., https://doi.org/10.3389/feart.2022.963689.","productDescription":"963689, 27 p.","ipdsId":"IP-131820","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2022.963689","text":"Publisher Index Page"},{"id":404620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Malagnini, Luca 0000-0001-5809-9945","orcid":"https://orcid.org/0000-0001-5809-9945","contributorId":245308,"corporation":false,"usgs":false,"family":"Malagnini","given":"Luca","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":847810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munafo, Irene","contributorId":294359,"corporation":false,"usgs":false,"family":"Munafo","given":"Irene","email":"","affiliations":[{"id":5113,"text":"INGV","active":true,"usgs":false}],"preferred":false,"id":847812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mancini, Simone 0000-0003-3415-2080","orcid":"https://orcid.org/0000-0003-3415-2080","contributorId":225525,"corporation":false,"usgs":false,"family":"Mancini","given":"Simone","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":847904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Segou, Margarita","contributorId":199044,"corporation":false,"usgs":false,"family":"Segou","given":"Margarita","affiliations":[],"preferred":false,"id":847905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847813,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70233488,"text":"sir20225062 - 2022 - Water-quality trends in surface waters of the Jemez River and Middle Rio Grande Basin from Cochiti to Albuquerque, New Mexico, 2004–19","interactions":[],"lastModifiedDate":"2022-07-26T11:02:56.544878","indexId":"sir20225062","displayToPublicDate":"2022-07-25T15:37:17","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5062","displayTitle":"Water-Quality Trends in Surface Waters of the Jemez River and Middle Rio Grande Basin from Cochiti to Albuquerque, New Mexico, 2004–19","title":"Water-quality trends in surface waters of the Jemez River and Middle Rio Grande Basin from Cochiti to Albuquerque, New Mexico, 2004–19","docAbstract":"<p>Municipal water supply for Albuquerque, New Mexico, is provided, in part, through diversion of surface water from the Rio Grande by way of the San Juan-Chama Drinking Water Project diversion structure. Changes in surface-water quality along the Rio Grande and its tributaries upstream from the San Juan-Chama Drinking Water Project diversion structure are not well characterized. This study describes the methods and results of an analysis of surface-water-quality trends for selected constituents in the Rio Grande upstream from Albuquerque. Trends were evaluated for differing time periods ranging from 2004 to 2019 by using the Seasonal Kendall Tau (SKT) test and the Weighted Regressions on Time, Discharge, and Season (WRTDS) model.</p><p>Water-quality data at three long-term sites were used for the trend analyses in this study, with the Cochiti and Alameda sites along the Rio Grande and the Jemez Canyon Dam site along the Jemez River, a tributary of the Rio Grande. The proximity of the Cochiti and Jemez Canyon Dam sites to dams is a drawback to the analysis because it is difficult to differentiate between the influence of dam management and the influence of streamflow on water-quality trends. The data used also did not fully meet desired levels of seasonal sampling density and had shorter periods of record than typically used for trend analysis, and this should be considered in the interpretation of these results.</p><p>Study results indicate that concentrations, and thereby fluxes, are influenced by changes in streamflow at the Alameda site. Most trends from the WRTDS results, obtained by using flow-normalization, were downward for constituents at the Alameda site. Most constituents that were analyzed for trends by using SKT did not have a significant trend at any of the sites included in this study, indicating either that the water quality in the Middle Rio Grande Basin has been stable during the study period or that not enough samples were collected during different seasons to characterize the range of concentration variability with streamflow. The SKT test results indicate upward trends in concentrations of the following constituents: aluminum and antimony at the Alameda site, nitrate and nitrate plus nitrite at the Cochiti site, and potassium and antimony during the spring season at Jemez Canyon Dam. The SKT test results indicate a downward trend in cobalt at the Cochiti site that is subject to bias in the cobalt concentrations. SKT test results also indicate small, downward trends in Kjeldahl nitrogen at the Alameda and Cochiti sites.</p><p>Concentrations of water-quality constituents were also compared to Federal and State water-quality standards to provide context and relevance to the results. No concentrations were above the national primary or secondary drinking water standards at the Alameda and Cochiti sites, but the Jemez Canyon Dam site did have concentrations above the U.S. Environmental Protection Agency primary drinking water standard for arsenic and above the national secondary drinking water standards for dissolved solids and aluminum. The Alameda and Cochiti sites are on reaches of the Rio Grande that are listed as impaired for gross alpha particles and the Alameda site is on a reach of the Rio Grande that is listed as impaired for <i>Escherichia coli</i>, but there were no consistent changes in concentrations of these constituents at the impaired locations.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225062","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Flickinger, A.K., and Shephard, Z.M., 2022, Water-quality trends in surface waters of the Jemez River and Middle Rio Grande Basin from Cochiti to Albuquerque, New Mexico, 2004–19: U.S. Geological Survey Scientific Investigations Report 2022–5062, 33 p., https://doi.org/10.3133/sir20225062.","productDescription":"Report: vi, 33 p.; 4 Appendixes; Dataset","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-125261","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":404243,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5062/coverthb.jpg"},{"id":404250,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062.pdf","text":"Report","size":"4.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5062"},{"id":404246,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062_appendixes.xlsx","text":"Appendixes 1–4","size":"59.7 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022–5062, appendixes 1–4"},{"id":404248,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062_appendixes.zip","text":"Appendixes 1–4","size":"17.0 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022–5062, appendixes 1–4"},{"id":404251,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5062/sir20225062.XML"},{"id":404252,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5062/images"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.24829101562499,\n              33.8430453147447\n            ],\n            [\n              -105.16113281249999,\n              33.8430453147447\n            ],\n            [\n              -105.16113281249999,\n              36.589068371399115\n            ],\n            [\n              -108.24829101562499,\n              36.589068371399115\n            ],\n            [\n              -108.24829101562499,\n              33.8430453147447\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"mailto:dc_nm@usgs.gov\" href=\"mailto:dc_nm@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/nm-water\" href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-07-25","noUsgsAuthors":false,"publicationDate":"2022-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Flickinger, Allison K. 0000-0002-8638-2569 aflickinger@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-2569","contributorId":193268,"corporation":false,"usgs":true,"family":"Flickinger","given":"Allison","email":"aflickinger@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":847227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":219039,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847228,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237659,"text":"70237659 - 2022 - Detrital zircon ages from upper Paleozoic–Triassic clastic strata on St. Lawrence Island, Alaska: An enigmatic component of the Arctic Alaska–Chukotka microplate","interactions":[],"lastModifiedDate":"2022-10-18T15:07:43.594689","indexId":"70237659","displayToPublicDate":"2022-07-25T10:00:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon ages from upper Paleozoic–Triassic clastic strata on St. Lawrence Island, Alaska: An enigmatic component of the Arctic Alaska–Chukotka microplate","docAbstract":"<p><span>New lithologic and detrital zircon (DZ) U-Pb data from Devonian–Triassic strata on St. Lawrence Island in the Bering Sea and from the western Brooks Range of Alaska suggest affinities between these two areas. The Brooks Range constitutes part of the Arctic Alaska–Chukotka microplate, but the tectonic and paleogeographic affinities of St. Lawrence Island are unknown or at best speculative. Strata on St. Lawrence Island form a Devonian–Triassic carbonate succession and a Mississippian(?)–Triassic clastic succession that are subdivided according to three distinctive DZ age distributions. The Devonian–Triassic carbonate succession has Mississippian-age quartz arenite beds with Silurian, Cambrian, Neoproterozoic, and Mesoproterozoic DZ age modes, and it exhibits similar age distributions and lithologic and biostratigraphic characteristics as Mississippian-age Utukok Formation strata in the Kelly River allochthon of the western Brooks Range. Consistent late Neoproterozoic, Cambrian, and Silurian ages in each of the Mississippian-age units suggest efficient mixing of the DZ prior to deposition, and derivation from strata exposed by the pre-Mississippian unconformity and/or Endicott Group strata that postdate the unconformity. The Mississippian(?)–Triassic clastic succession is subdivided into feldspathic and graywacke subunits. The feldspathic subunit has a unimodal DZ age mode at 2.06 Ga, identical to Nuka Formation strata in the Nuka Ridge allochthon of the western Brooks Range, and it records a distinctive depositional episode related to late Paleozoic juxtaposition of a Paleoproterozoic terrane along the most distal parts of the Arctic Alaska–Chukotka microplate. The graywacke subunit has Triassic maximum depositional ages and abundant late Paleozoic grains, likely sourced from fringing arcs and/or continent-scale paleorivers draining Eurasia, and it has similar age distributions to Triassic strata from the Lisburne Peninsula (northwestern Alaska), Chukotka and Wrangel Island (eastern Russia), and the northern Sverdrup Basin (Canadian Arctic), but, unlike the Devonian–Triassic carbonate succession and feldspathic subunit of the Mississippian(?)–Triassic clastic succession, it has no obvious analogue in the western Brooks Range allochthon stack. These correlations establish St. Lawrence Island as conclusively belonging to the Arctic Alaska–Chukotka microplate, thus enhancing our understanding of the circum-Arctic region in late Paleozoic–Triassic time.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02490.1","usgsCitation":"Amato, J.M., Dumoulin, J.A., Gottlieb, E.S., and Moore, T.E., 2022, Detrital zircon ages from upper Paleozoic–Triassic clastic strata on St. Lawrence Island, Alaska: An enigmatic component of the Arctic Alaska–Chukotka microplate: Geosphere, v. 18, no. 5, p. 1492-1523, https://doi.org/10.1130/GES02490.1.","productDescription":"32 p.","startPage":"1492","endPage":"1523","ipdsId":"IP-134575","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":447026,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02490.1","text":"Publisher Index Page"},{"id":435756,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99PILIK","text":"USGS data release","linkHelpText":"Location Data for Petrographic Samples and Isotopic and Age Data from Detrital Zircon Grains from Selected Rock Samples from St. Lawrence Island and the Western Brooks Range, Alaska"},{"id":408489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"St. Lawrence Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -171.968994140625,\n              62.88520467163244\n            ],\n            [\n              -168.50830078125,\n              62.88520467163244\n            ],\n            [\n              -168.50830078125,\n              63.86487567533106\n            ],\n            [\n              -171.968994140625,\n              63.86487567533106\n            ],\n            [\n              -171.968994140625,\n              62.88520467163244\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"18","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Amato, Jeffrey M.","contributorId":247883,"corporation":false,"usgs":false,"family":"Amato","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":49682,"text":"Dept of Geolgical Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":854897,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":854898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gottlieb, Eric S. 0000-0002-4904-9492","orcid":"https://orcid.org/0000-0002-4904-9492","contributorId":291239,"corporation":false,"usgs":false,"family":"Gottlieb","given":"Eric","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":854899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Thomas E. 0000-0002-0878-0457 tmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-0878-0457","contributorId":127538,"corporation":false,"usgs":true,"family":"Moore","given":"Thomas","email":"tmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":854900,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70233917,"text":"70233917 - 2022 - Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world","interactions":[],"lastModifiedDate":"2022-08-15T13:59:24.968029","indexId":"70233917","displayToPublicDate":"2022-07-25T07:27:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5263,"text":"Nature Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Responses of terrestrial ecosystems to climate change have been explored in many regions worldwide. While continued drying and warming may alter process rates and deteriorate the state and performance of ecosystems, it could also lead to more fundamental changes in the mechanisms governing ecosystem functioning. Here we argue that climate change will induce unprecedented shifts in these mechanisms in historically wetter climatic zones, towards mechanisms currently prevalent in dry regions, which we refer to as ‘dryland mechanisms’. We discuss 12 dryland mechanisms affecting multiple processes of ecosystem functioning, including vegetation development, water flow, energy budget, carbon and nutrient cycling, plant production and organic matter decomposition. We then examine mostly rare examples of the operation of these mechanisms in non-dryland regions where they have been considered irrelevant at present. Current and future climate trends could force microclimatic conditions across thresholds and lead to the emergence of dryland mechanisms and their increasing control over ecosystem functioning in many biomes on Earth.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41559-022-01779-y","usgsCitation":"Grunzweig, J.M., De Boeck, H.J., Rey, A., Santos, M., Adam, O., Bahn, M., Belnap, J., Deckmyn, G., Dekker, S.C., Flores, O., Gliksman, D., Helman, D., Hultine, K.R., Liu, L., Meron, E., Michael, Y., Sheffer, E., Throop, H.L., Tzuk, O., and Yakir, D., 2022, Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world: Nature Ecology & Evolution, v. 6, p. 1064-1076, https://doi.org/10.1038/s41559-022-01779-y.","productDescription":"13 p.","startPage":"1064","endPage":"1076","ipdsId":"IP-139122","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467173,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://dspace.library.uu.nl/handle/1874/422177","text":"External Repository"},{"id":404534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2022-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Grunzweig, Jose M","contributorId":293846,"corporation":false,"usgs":false,"family":"Grunzweig","given":"Jose","email":"","middleInitial":"M","affiliations":[{"id":63529,"text":"Institute of Plant Sciences and Genetics in Agriculture, the Robert H. Smith Faculty of Agriculture, Food and Environment, the Hebrew University of Jerusalem, Rehovot, Israel","active":true,"usgs":false}],"preferred":false,"id":847637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Boeck, Hans J.","contributorId":288839,"corporation":false,"usgs":false,"family":"De Boeck","given":"Hans","email":"","middleInitial":"J.","affiliations":[{"id":61845,"text":"Plants and Ecosystems, Department of Biology, University of Antwerp, Antwerp, Belgium","active":true,"usgs":false}],"preferred":false,"id":847638,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rey, Ana","contributorId":293847,"corporation":false,"usgs":false,"family":"Rey","given":"Ana","email":"","affiliations":[{"id":63530,"text":"Department of Biogeography and Global Change, National Museum of Natural History, Spanish Scientific Council (CSIC), C/Serrano 115bis, 28006 Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":847639,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Santos, Maria J.","contributorId":293848,"corporation":false,"usgs":false,"family":"Santos","given":"Maria J.","affiliations":[{"id":63531,"text":"Department of Geography, University of Zurich, Zurich Switzerland","active":true,"usgs":false}],"preferred":false,"id":847640,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adam, Ori","contributorId":293849,"corporation":false,"usgs":false,"family":"Adam","given":"Ori","email":"","affiliations":[{"id":63532,"text":"The Fredy and Nadine Herrmann Institute of Earth Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel","active":true,"usgs":false}],"preferred":false,"id":847641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bahn, Michael","contributorId":210470,"corporation":false,"usgs":false,"family":"Bahn","given":"Michael","email":"","affiliations":[],"preferred":false,"id":847642,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":847643,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Deckmyn, Gaby","contributorId":293850,"corporation":false,"usgs":false,"family":"Deckmyn","given":"Gaby","email":"","affiliations":[{"id":63534,"text":"Plants and Ecosystems, Department of Biology, Universiteit Antwerpen, Wilrijk, Belgium","active":true,"usgs":false}],"preferred":false,"id":847644,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dekker, Stefan C","contributorId":293851,"corporation":false,"usgs":false,"family":"Dekker","given":"Stefan","email":"","middleInitial":"C","affiliations":[{"id":63535,"text":"Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":847645,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Flores, Omar","contributorId":293852,"corporation":false,"usgs":false,"family":"Flores","given":"Omar","email":"","affiliations":[{"id":63537,"text":"Plants and Ecosystems, Department of Biology, Universiteit Antwerpen, Wilrijk, Belgium; Department of Biogeography and Global Change, National Museum of Natural History, Spanish Scientific Council (CSIC), C/Serrano 115bis, 28006 Madrid, Spain","active":true,"usgs":false}],"preferred":false,"id":847646,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gliksman, Daniel","contributorId":293853,"corporation":false,"usgs":false,"family":"Gliksman","given":"Daniel","email":"","affiliations":[{"id":63538,"text":"Faculty of Environmental Sciences, Institute for Hydrology and Meteorology, Technische Universität Dresden, 01735 Tharandt, Germany; Institute of Geography, Technische Universität Dresden, Helmholtzstr. 10, 01069, Dresden, Germany","active":true,"usgs":false}],"preferred":false,"id":847647,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Helman, David","contributorId":293854,"corporation":false,"usgs":false,"family":"Helman","given":"David","email":"","affiliations":[{"id":63539,"text":"Institute of Environmental Sciences, the Robert H. Smith Faculty of Agriculture, Food and Environment, and Advanced School for Environmental Studies, the Hebrew University of Jerusalem, Rehovot, Israel","active":true,"usgs":false}],"preferred":false,"id":847648,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hultine, Kevin R.","contributorId":181976,"corporation":false,"usgs":false,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":847649,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Liu, Lingling","contributorId":243596,"corporation":false,"usgs":false,"family":"Liu","given":"Lingling","email":"","affiliations":[{"id":48746,"text":"Natural Capital Project, Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA","active":true,"usgs":false}],"preferred":false,"id":847650,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Meron, Ehud","contributorId":293855,"corporation":false,"usgs":false,"family":"Meron","given":"Ehud","email":"","affiliations":[{"id":63540,"text":"Dept of Physics, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel; Dept of Solar Energy and Environmental Physics, Blaustein Institutes for Desert Research, 35 Ben-Gurion Univ of the Negev, Sede Boqer Campus 84990, Israel","active":true,"usgs":false}],"preferred":false,"id":847651,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Michael, Yaron","contributorId":293856,"corporation":false,"usgs":false,"family":"Michael","given":"Yaron","email":"","affiliations":[{"id":63539,"text":"Institute of Environmental Sciences, the Robert H. Smith Faculty of Agriculture, Food and Environment, and Advanced School for Environmental Studies, the Hebrew University of Jerusalem, Rehovot, Israel","active":true,"usgs":false}],"preferred":false,"id":847652,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sheffer, Efrat","contributorId":293857,"corporation":false,"usgs":false,"family":"Sheffer","given":"Efrat","email":"","affiliations":[{"id":63529,"text":"Institute of Plant Sciences and Genetics in Agriculture, the Robert H. Smith Faculty of Agriculture, Food and Environment, the Hebrew University of Jerusalem, Rehovot, Israel","active":true,"usgs":false}],"preferred":false,"id":847653,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Throop, Heather L. 0000-0002-7963-4342","orcid":"https://orcid.org/0000-0002-7963-4342","contributorId":139051,"corporation":false,"usgs":false,"family":"Throop","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12633,"text":"Biology Department, New Mexico State University, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":847654,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tzuk, Omer","contributorId":293858,"corporation":false,"usgs":false,"family":"Tzuk","given":"Omer","email":"","affiliations":[{"id":63541,"text":"Department of Physics, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel; Present address: Department of Industrial Engineering, Faculty of Engineering, Tel-Aviv University, Tel Aviv-Yafo, Israel","active":true,"usgs":false}],"preferred":false,"id":847655,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Yakir, Dan","contributorId":293859,"corporation":false,"usgs":false,"family":"Yakir","given":"Dan","email":"","affiliations":[{"id":63542,"text":"Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel","active":true,"usgs":false}],"preferred":false,"id":847656,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}}
,{"id":70235715,"text":"70235715 - 2022 - Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace-of-life","interactions":[],"lastModifiedDate":"2022-08-16T11:42:49.081347","indexId":"70235715","displayToPublicDate":"2022-07-25T06:41:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace-of-life","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Pathogen transmission depends on host density, mobility and contact. These components emerge from host and pathogen movements that themselves arise through interactions with the surrounding environment. The environment, the emergent host and pathogen movements, and the subsequent patterns of density, mobility and contact form an ‘epidemiological landscape’ connecting the environment to specific locations where transmissions occur. Conventionally, the epidemiological landscape has been described in terms of the geographical coordinates where hosts or pathogens are located. We advocate for an alternative approach that relates those locations to attributes of the local environment. Environmental descriptions can strengthen epidemiological forecasts by allowing for predictions even when local geographical data are not available. Environmental predictions are more accessible than ever thanks to new tools from movement ecology, and we introduce a ‘movement-pathogen pace of life’ heuristic to help identify aspects of movement that have the most influence on spatial epidemiology. By linking pathogen transmission directly to the environment, the epidemiological landscape offers an efficient path for using environmental information to inform models describing when and where transmission will occur.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/ele.14032","usgsCitation":"Manlove, K.R., Wilber, M.Q., White, L., Bastille-Rousseau, G., Yang, A., Gilbertson, M.L., Craft, M.E., Cross, P., Wittemyer, G., and Pepin, K.M., 2022, Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace-of-life: Ecology Letters, v. 25, no. 8, p. 1760-1782, https://doi.org/10.1111/ele.14032.","productDescription":"23 p.","startPage":"1760","endPage":"1782","ipdsId":"IP-134496","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":405178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-07-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Manlove, Kezia R.","contributorId":198305,"corporation":false,"usgs":false,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":849062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilber, Mark Q.","contributorId":127720,"corporation":false,"usgs":false,"family":"Wilber","given":"Mark","email":"","middleInitial":"Q.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":849063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Lauren","contributorId":295300,"corporation":false,"usgs":false,"family":"White","given":"Lauren","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":849064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bastille-Rousseau, Guillaume 0000-0001-6799-639X","orcid":"https://orcid.org/0000-0001-6799-639X","contributorId":190877,"corporation":false,"usgs":false,"family":"Bastille-Rousseau","given":"Guillaume","email":"","affiliations":[{"id":40724,"text":"Cooperative Wildlife Research Laboratory and Department of Forestry, Southern Illinois University, 251 Life Science II, Mail Code 6504, Carbondale, Illinois 62901 USA","active":true,"usgs":false}],"preferred":false,"id":849065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, Alan","contributorId":206553,"corporation":false,"usgs":false,"family":"Yang","given":"Alan","email":"","affiliations":[{"id":37339,"text":"Scripps/UCSD","active":true,"usgs":false}],"preferred":false,"id":849066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gilbertson, Marie L. J.","contributorId":212116,"corporation":false,"usgs":false,"family":"Gilbertson","given":"Marie","email":"","middleInitial":"L. J.","affiliations":[{"id":38415,"text":"Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA","active":true,"usgs":false}],"preferred":false,"id":849067,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Craft, Meggan E.","contributorId":168372,"corporation":false,"usgs":false,"family":"Craft","given":"Meggan","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":849068,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":849069,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wittemyer, George","contributorId":198621,"corporation":false,"usgs":false,"family":"Wittemyer","given":"George","email":"","affiliations":[],"preferred":false,"id":849070,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pepin, K. M","contributorId":295301,"corporation":false,"usgs":false,"family":"Pepin","given":"K.","email":"","middleInitial":"M","affiliations":[{"id":63834,"text":"United States Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":849071,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70236768,"text":"70236768 - 2022 - Shedding kinetics of Infectious Hematopoietic Necrosis Virus (IHNV) in juvenile spring- and fall-run Chinook salmon of the Columbia River Basin","interactions":[],"lastModifiedDate":"2022-09-20T11:06:54.557843","indexId":"70236768","displayToPublicDate":"2022-07-24T08:11:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5762,"text":"Animals","active":true,"publicationSubtype":{"id":10}},"title":"Shedding kinetics of Infectious Hematopoietic Necrosis Virus (IHNV) in juvenile spring- and fall-run Chinook salmon of the Columbia River Basin","docAbstract":"<p><span>This investigation sought to characterize the shedding of infectious hematopoietic necrosis virus (IHNV) in two populations of Columbia River Basin (CRB) Chinook salmon (</span><i><span class=\"html-italic\">Oncorhynchus tshawytscha</span></i><span>). Juvenile spring- and fall-run Chinook salmon were exposed by immersion to each of three IHN virus strains from the UC, MD, and L subgroups, and then monitored for viral shedding from individual fish for 30 days. Detectable quantities of UC, MD and L IHN virus were shed by a subset of fish from each host population (1–9 out of 10 fish total in each treatment group). Viral shedding kinetics were consistent, with a rapid onset of shedding, peak shedding by 2–3 days, and then a rapid decline to below detectable levels by 7 days’ post-exposure to IHNV. Intraspecies variation was observed as spring Chinook salmon shed more UC virus than fall fish: spring Chinook salmon shed UC virus in greater numbers of fish, with 22-fold higher mean peak shedding magnitude, 33-fold higher mean total virus shed per fish, and 900-fold higher total virus shed per treatment group. The L and MD viruses had comparable shedding at intermediate levels in each host population. All viral shedding occurred well before host mortality began, and shedding magnitude did not correlate with virulence differences. Overall, the greater shedding of UC virus from spring Chinook salmon, combined with low virulence, indicates a uniquely high transmission potential that may explain the predominance of UC viruses in CRB Chinook salmon. This also suggests that spring-run fish may contribute more to the ecology of IHNV in the CRB than fall-run Chinook salmon.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/ani12151887","usgsCitation":"Hernandez, D.G., and Kurath, G., 2022, Shedding kinetics of Infectious Hematopoietic Necrosis Virus (IHNV) in juvenile spring- and fall-run Chinook salmon of the Columbia River Basin: Animals, v. 12, no. 15, 1887, 18 p., https://doi.org/10.3390/ani12151887.","productDescription":"1887, 18 p.","ipdsId":"IP-141291","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":447030,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/ani12151887","text":"Publisher Index Page"},{"id":435757,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97QNE6M","text":"USGS data release","linkHelpText":"Shed viral load and survival of spring-run and fall-run Columbia River Basin Chinook salmon exposed to 3 genogroups of infectious hematopoietic necrosis virus (IHNV)"},{"id":406948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.288330078125,\n              45.251688256117646\n            ],\n            [\n              -118.267822265625,\n              45.251688256117646\n            ],\n            [\n              -118.267822265625,\n              46.7248003746672\n            ],\n            [\n              -124.288330078125,\n              46.7248003746672\n            ],\n            [\n              -124.288330078125,\n              45.251688256117646\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"15","noUsgsAuthors":false,"publicationDate":"2022-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hernandez, Daniel G.","contributorId":257868,"corporation":false,"usgs":false,"family":"Hernandez","given":"Daniel","email":"","middleInitial":"G.","affiliations":[{"id":52147,"text":"University of Washington, School of Aquatic and Fishery Sciences, Seattle, WA, 98195, USA","active":true,"usgs":false}],"preferred":false,"id":852127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurath, Gael 0000-0003-3294-560X","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":220175,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70243774,"text":"70243774 - 2022 - Test of a screw-style fish lift for introducing migratory fish into a selective fish passage device","interactions":[],"lastModifiedDate":"2023-05-19T11:51:22.060717","indexId":"70243774","displayToPublicDate":"2022-07-24T06:44:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Test of a screw-style fish lift for introducing migratory fish into a selective fish passage device","docAbstract":"Barriers are an effective mechanism for managing invasive species like sea lamprey in the Lau-rentian Great Lakes, but are detrimental because they limit the migration of desirable, native species. Fish passage technologies that selectively pass desirable species while blocking unde-sirable species are needed. Optical sorting tools combined with newly developed computer learning algorithms could be used to identify invasive species from high resolution imagery and potentially isolate them from an assortment of Great Lakes fishes. Many existing barriers lack fishways and optical sorting may require fish to be dewatered for image capture. The Archimedes screw, a device originating from 234 BC, offers the potential to continuously lift fish and water over low-head barriers or into an optical sorting device. To test the efficacy of an Archimedes screw fish lift to capture and pass Great Lakes fishes, we built a field-scale prototype and installed it at the Cheboygan Dam, Michigan USA in 2021. The fish lift safely transported 704 fish (688 of which were suckers) in 11 days. Passage of suckers through the fish lift increased with water temperature and attraction flow. There were no observed injuries in transported fish or mortalities in a subset of suckers held post-transport.","language":"English","publisher":"MDPI","doi":"10.3390/w14152298","usgsCitation":"Zielinski, D., Miehls, S.M., and Lewandoski, S.A., 2022, Test of a screw-style fish lift for introducing migratory fish into a selective fish passage device: Water, v. 14, no. 15, 2298, 11 p., https://doi.org/10.3390/w14152298.","productDescription":"2298, 11 p.","ipdsId":"IP-141796","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":447032,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w14152298","text":"Publisher Index Page"},{"id":417235,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Cheboygan Lock and Dam, Cheboygan River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.48246352255947,\n              45.63422833640519\n            ],\n            [\n              -84.48249493956641,\n              45.63381094446876\n            ],\n            [\n              -84.48118589759555,\n              45.63370110396923\n            ],\n            [\n              -84.48059944679251,\n              45.63413314202643\n            ],\n            [\n              -84.48246352255947,\n              45.63422833640519\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"15","noUsgsAuthors":false,"publicationDate":"2022-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Zielinski, Daniel","contributorId":245798,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":873214,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":873215,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lewandoski, Sean A.","contributorId":221007,"corporation":false,"usgs":false,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"A.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":873216,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70262467,"text":"70262467 - 2022 - A framework for integrating inferred movement behavior into disease risk models","interactions":[],"lastModifiedDate":"2025-01-21T15:12:25.147614","indexId":"70262467","displayToPublicDate":"2022-07-24T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A framework for integrating inferred movement behavior into disease risk models","docAbstract":"<p><span>Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely&nbsp;</span><i>Bacillus anthracis</i><span>&nbsp;(the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra (</span><i>Equus quagga</i><span>) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40462-022-00331-8","usgsCitation":"Dougherty, E., Seidel, D., Blackburn, J., Turner, W.C., and Getz, W., 2022, A framework for integrating inferred movement behavior into disease risk models: Movement Ecology, v. 10, 31, 15 p., https://doi.org/10.1186/s40462-022-00331-8.","productDescription":"31, 15 p.","ipdsId":"IP-138565","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481077,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-022-00331-8","text":"Publisher Index Page"},{"id":480820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Namibia","otherGeospatial":"Etosha National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              15.655851549884602,\n              -18.75382547428198\n            ],\n            [\n              15.655851549884602,\n              -19.249215511439346\n            ],\n            [\n              16.38844485420617,\n              -19.249215511439346\n            ],\n            [\n              16.38844485420617,\n              -18.75382547428198\n            ],\n            [\n              15.655851549884602,\n              -18.75382547428198\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-07-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dougherty, Eric R.","contributorId":349723,"corporation":false,"usgs":false,"family":"Dougherty","given":"Eric R.","affiliations":[],"preferred":false,"id":924662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seidel, Dana P.","contributorId":349724,"corporation":false,"usgs":false,"family":"Seidel","given":"Dana P.","affiliations":[],"preferred":false,"id":924663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blackburn, Jason K.","contributorId":349725,"corporation":false,"usgs":false,"family":"Blackburn","given":"Jason K.","affiliations":[],"preferred":false,"id":924664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turner, Wendy Christine 0000-0002-0302-1646","orcid":"https://orcid.org/0000-0002-0302-1646","contributorId":287053,"corporation":false,"usgs":true,"family":"Turner","given":"Wendy","email":"","middleInitial":"Christine","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Getz, Wayne M.","contributorId":287152,"corporation":false,"usgs":false,"family":"Getz","given":"Wayne M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":924665,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70234143,"text":"70234143 - 2022 - Barium enrichment in the non-spinose planktic foraminifer, Globorotalia truncatulinoides","interactions":[],"lastModifiedDate":"2022-08-02T11:46:22.195509","indexId":"70234143","displayToPublicDate":"2022-07-23T06:42:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Barium enrichment in the non-spinose planktic foraminifer, Globorotalia truncatulinoides","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab005\" class=\"abstract author\"><div id=\"as005\"><p id=\"sp0005\">Observations of elevated barium-to-calcium ratios (Ba/Ca) in<span>&nbsp;</span><i>Globorotalia truncatulinoides</i><span>&nbsp;</span>have been attributed to contaminant phases, deep calcification depth and diagenetic processes. Here we investigate intra- and inter-test Ba/Ca variability in the non-spinose planktic foraminifer,<span>&nbsp;</span><i>G. truncatulinoides</i><span>, from a&nbsp;sediment trap&nbsp;time series in the northern&nbsp;Gulf of Mexico&nbsp;to gain insights into the environmental influences on barium enrichment in this and other non-spinose species. We use&nbsp;laser ablation inductively coupled plasma mass spectrometry&nbsp;(LA-ICP-MS) to differentiate between the elemental composition of the crust and lamellar&nbsp;calcite&nbsp;in non-encrusted (&lt;150&nbsp;m calcification depth) and encrusted (&gt;150&nbsp;m calcification depth) specimens of&nbsp;</span><i>G. truncatulinoides</i>. We find that the Ba/Ca ratio in lamellar calcite is between two and three orders of magnitude higher (10–280&nbsp;μmol/mol) than that of the crust (0–3&nbsp;μmol/mol). We include seasonal water column profiles of the Ba/Ca ratio in the northern Gulf of Mexico and determine that the vertical gradient in seawater barium concentration cannot account for the intra-test Ba/Ca variations in<span>&nbsp;</span><i>G. truncatulinoides</i>. We find the Ba/Ca ratio of the crust to be within the range observed in co-occurring spinose species of foraminifera (pink and white chromotypes of<span>&nbsp;</span><i>Globigerinoides ruber</i>, and<span>&nbsp;</span><i>Orbulina universa</i>) while the range of Ba/Ca in lamellar calcite is consistent with co-occurring non-spinose foraminifera (<i>Pulleniatina obliquiloculata</i>,<span>&nbsp;</span><i>Globorotalia menardii</i>,<span>&nbsp;</span><i>G. tumida</i>, and<span>&nbsp;</span><i>Neogloboquadrina dutertrei</i>). Our data are consistent with the hypothesis that<span>&nbsp;</span><i>G. truncatulinoides</i><span>&nbsp;</span>calcifies in a marine snow aggregate microenvironment that is enriched in barium relative to ambient seawater. We suggest that<span>&nbsp;</span><i>G. truncatulinoides</i><span>&nbsp;</span>crust is formed after the rhizopodia retract and the foraminifer detaches from its marine snow substrate.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2022.07.006","usgsCitation":"Richey, J.N., Fehrenbacher, J., Reynolds, C., Davis, C.Z., and Spero, H.J., 2022, Barium enrichment in the non-spinose planktic foraminifer, Globorotalia truncatulinoides: Geochimica et Cosmochimica Acta, v. 333, no. 15, p. 184-199, https://doi.org/10.1016/j.gca.2022.07.006.","productDescription":"16 p.","startPage":"184","endPage":"199","ipdsId":"IP-137553","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":487005,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2022.07.006","text":"Publisher Index Page"},{"id":435758,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YQMIH5","text":"USGS data release","linkHelpText":"Globorotalia truncatulinoides Trace Element Geochemistry (Barium, Magnesium, Strontium, Manganese, and Calcium) From the Gulf of Mexico Sediment Trap"},{"id":404642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"333","issue":"15","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fehrenbacher, Jennifer S.","contributorId":294386,"corporation":false,"usgs":false,"family":"Fehrenbacher","given":"Jennifer S.","affiliations":[{"id":63562,"text":"Oregon State University, College of Earth, Ocean, and Atmospheric Sciences","active":true,"usgs":false}],"preferred":false,"id":847955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Caitlin E. 0000-0002-1724-3055","orcid":"https://orcid.org/0000-0002-1724-3055","contributorId":204634,"corporation":false,"usgs":true,"family":"Reynolds","given":"Caitlin E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":847956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Catherine Z. 0000-0003-4279-5369","orcid":"https://orcid.org/0000-0003-4279-5369","contributorId":294387,"corporation":false,"usgs":false,"family":"Davis","given":"Catherine","email":"","middleInitial":"Z.","affiliations":[{"id":63563,"text":"North Carolina State University, Department of Marine, Earth, and Atmospheric Sciences","active":true,"usgs":false}],"preferred":false,"id":847957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spero, Howard J. 0000-0001-5465-8607","orcid":"https://orcid.org/0000-0001-5465-8607","contributorId":294388,"corporation":false,"usgs":false,"family":"Spero","given":"Howard","email":"","middleInitial":"J.","affiliations":[{"id":63564,"text":"University of California Davis, Department of Earth and Planetary Sciences","active":true,"usgs":false}],"preferred":false,"id":847958,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70233531,"text":"fs20223035 - 2022 - Groundwater quality in the Surficial Aquifer System, Southeastern United States:","interactions":[],"lastModifiedDate":"2026-03-24T21:21:47.685347","indexId":"fs20223035","displayToPublicDate":"2022-07-22T14:28:48","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3035","displayTitle":"Groundwater Quality in the Surficial Aquifer System, Southeastern United States","title":"Groundwater quality in the Surficial Aquifer System, Southeastern United States:","docAbstract":"<p>Groundwater provides nearly 50 percent of the Nation’s drinking water. To help protect this vital resource, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Project assesses groundwater quality in aquifers that are important sources of drinking water (Burow and Belitz, 2014). The surficial aquifer system constitutes one of the important aquifer systems being evaluated.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223035","collaboration":"National Water-Quality Assessment Project","programNote":"National Water Quality Program","usgsCitation":"Kingsbury, J.A., 2022, Groundwater quality in the Surficial Aquifer System, Southeastern United States: U.S. Geological Survey Fact Sheet 2022-3035, 4 p., https://doi.org/10.3133/fs20223035.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-135417","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":404355,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3035/covrthb.jpg"},{"id":404356,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3035/fs20223035.pdf","text":"Report","size":"3.3 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 \"}}]}","contact":"<p><a data-mce-href=\"mailto:email=wausp-info@usgs.gov\" href=\"mailto:email=wausp-info@usgs.gov\" target=\"_blank\" rel=\"noopener\">NAWQA Chief Scientist</a><br><a href=\"https://www.usgs.gov/mission-areas/water-resources\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources\">National Water-Quality Program</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a>&nbsp;<br>12201 Sunrise Valley Drive, MS 413&nbsp;<br>Reston, VA 20192-0002</p>","tableOfContents":"<ul><li>Background&nbsp;&nbsp;</li><li>Overview of Water Quality&nbsp;&nbsp;</li><li>Results: Groundwater Quality at the Depth Zone Used for Public Supply in the Surficial Aquifer System&nbsp;&nbsp;</li><li>Inorganic Constituents&nbsp;&nbsp;</li><li>Organic Constituents&nbsp;&nbsp;</li><li>Benchmarks for Evaluating Groundwater Quality&nbsp;&nbsp;</li><li>References Cited&nbsp;</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-07-22","noUsgsAuthors":false,"publicationDate":"2022-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847353,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70233533,"text":"sir20225060 - 2022 - Trends in groundwater levels, and orthophosphate and nitrate concentrations in the Middle Snake River Region, south-central Idaho","interactions":[],"lastModifiedDate":"2022-09-27T13:37:37.610574","indexId":"sir20225060","displayToPublicDate":"2022-07-22T09:58:04","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5060","displayTitle":"Trends in Groundwater Levels, and Orthophosphate and Nitrate Concentrations in the Middle Snake River Region, South-Central Idaho","title":"Trends in groundwater levels, and orthophosphate and nitrate concentrations in the Middle Snake River Region, south-central Idaho","docAbstract":"<p class=\"p1\">The U.S. Geological Survey (USGS) evaluated nitrate and orthophosphate concentrations in groundwater for temporal trends (monotonic and step trends) for the middle Snake River region (Cassia, Gooding, Jerome, Lincoln, Minidoka, and Twin Falls Counties) in south-central Idaho using the Regional Kendall test (monotonic trends) and the Wilcoxon signed rank test (step trends). The study evaluated two trend periods: 2000–09 and 2010–19/20. The study area was divided into six hydrogeologic zones (HZs) that had similar geologic and hydrologic characteristics and that correlated with county boundaries where possible. Two well networks sampled by the USGS National Water Quality Program within the HZs were also evaluated.</p><p class=\"p1\">The northern Gooding County HZ had statistically significant increasing nitrate concentration trends for both the monotonic and step trends in the early trend period, while the Cassia and Jerome/Southern Gooding County HZs only had one of the statistical tests with statistically significant increasing nitrate concentrations. The Minidoka County HZ had conflicting results between the two statistical tests for the early time period with a statistically significant increasing monotonic trend in nitrate concentration and a statistically significant decreasing step trend. The differing results between these two statistical tests indicates the significance of concentration data during the middle of the time period. Both the Lincoln and Twin Falls County HZs did not have statistically significant trends for either test during either time period as well as the Northern Gooding County HZ for the latter time period. The Minidoka County HZ had statistically significant nitrate trends for both tests in the latter time period along with one of the trend tests for the Cassia and Jerome/Southern Gooding County HZ. Most of the nitrate concentration trend rates are low from 0.01 to 0.12 milligram per liter per year (mg/L/year) with the northern Gooding County HZ having the highest trend rate during the early time period of 0.28 mg/L/year for the step trend and 0.55 mg/L/year for the monotonic trend.</p><p class=\"p1\">All the HZs and both well networks had statistically significant increasing orthophosphate-concentrations trends in groundwater for the early time period except for the Lincoln County HZ and the step-trend for the Minidoka County HZ. Orthophosphate concentration trend rates for the early period were low, ranging from 0.001 to 0.015 mg/L/year. Only two HZs and the well networks had enough orthophosphate concentration data available in the latter time period to do statistical analysis. The two HZs (Minidoka and Southern Gooding/Jerome County) both have decreasing orthophosphate concentration trends, with only the monotonic trend for the Southern Gooding/Jerome County HZ being statistically significant at 90 percent with a rate of −0.001 mg/L/year.</p><p class=\"p2\">Groundwater levels in two well networks in the eastern Snake River Plain aquifer were also evaluated for trends (monotonic and step), with both networks having statistically significant declining groundwater levels for the 1993–2009 trend period. The latter trend period (2010–20) had statistically significant declining groundwater levels for the A&amp;B well network and statistically significant increasing groundwater levels for the Jerome/Gooding well network, which is downgradient from an aquifer recharge area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225060","collaboration":"Prepared in cooperation with the Idaho Department of Environmental Quality and the Middle Snake Regional Water Resource Commission","usgsCitation":"Skinner, K.D., 2022, Trends in groundwater levels, and orthophosphate and nitrate concentrations in the Middle Snake River Region, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2022–5060, 18 p., https://doi.org/10.3133/sir20225060.","productDescription":"vii, 18 p.","onlineOnly":"Y","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":404369,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225060/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5060"},{"id":404371,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5060/sir20225060.XML"},{"id":404370,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5060/images"},{"id":404368,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5060/sir20225060.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5060"},{"id":404367,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5060/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Middle Snake River region","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-113.2165,42.6319],[-113.2115,42.6323],[-113.2046,42.6345],[-113.1978,42.6339],[-113.186,42.6311],[-113.1767,42.6283],[-113.1769,42.6187],[-113.1762,42.5896],[-113.0261,42.5889],[-113.0068,42.5892],[-113.0062,42.5601],[-113.0056,42.531],[-113.0053,42.5164],[-113.0043,42.5014],[-113.004,42.4864],[-113.0019,42.4146],[-113.0031,42.3283],[-113.0031,42.2701],[-113.0034,42.2551],[-113.0031,42.242],[-113.0028,42.1992],[-113.0034,42.1697],[-113.0031,42.1256],[-113.0022,42.1111],[-113.0025,42.097],[-113.0022,42.082],[-113.0025,42.0689],[-113.0028,41.9985],[-113.0608,41.9977],[-113.08,41.9975],[-113.1516,41.9966],[-113.1549,41.9968],[-113.159,41.9968],[-113.1782,41.9967],[-113.4253,41.9953],[-113.4499,41.995],[-113.4636,41.9949],[-113.4685,41.9948],[-113.5092,41.9945],[-113.566,41.9939],[-113.5976,41.994],[-113.608,41.9937],[-113.6198,41.9936],[-113.6569,41.993],[-113.7019,41.9924],[-113.7229,41.9921],[-113.734,41.9921],[-113.7432,41.992],[-113.7636,41.9915],[-113.8322,41.9904],[-113.8519,41.9899],[-113.8526,41.9898],[-113.8705,41.9904],[-113.8735,41.9905],[-113.91,41.9911],[-113.9285,41.9914],[-113.9483,41.9916],[-113.952,41.9916],[-113.9717,41.9921],[-113.9902,41.9924],[-114.0138,41.9929],[-114.0404,41.9934],[-114.0412,41.9934],[-114.0489,41.9935],[-114.1592,41.9941],[-114.2259,41.9944],[-114.2457,41.9945],[-114.2817,41.9947],[-114.2852,41.9947],[-114.3414,41.9944],[-114.3816,41.9944],[-114.4014,41.9944],[-114.5379,41.9949],[-114.5972,41.9953],[-114.5984,41.9953],[-114.6163,41.9958],[-114.6361,41.9963],[-114.6533,41.997],[-114.6749,41.9974],[-114.712,41.9981],[-114.7565,41.999],[-114.8126,41.9998],[-114.833,42],[-114.8546,42.0003],[-114.8578,42.0002],[-114.8725,41.9998],[-114.8904,41.9993],[-114.893,41.9992],[-114.9115,41.9985],[-114.9288,41.9981],[-114.9683,41.9968],[-114.9857,41.9966],[-115.0387,41.996],[-115.0388,42.0137],[-115.0383,42.0287],[-115.0378,42.0428],[-115.0375,42.0869],[-115.0365,42.1159],[-115.0366,42.1305],[-115.0361,42.145],[-115.036,42.2032],[-115.0361,42.2172],[-115.0363,42.2463],[-115.037,42.2613],[-115.0359,42.2754],[-115.0381,42.5666],[-115.0382,42.5807],[-115.0391,42.6089],[-115.038,42.6239],[-115.0391,42.7698],[-115.0386,42.7816],[-115.0377,42.8257],[-115.0379,42.8526],[-115.0392,42.868],[-115.0396,42.9116],[-115.039,42.9139],[-115.0478,42.918],[-115.0628,42.9138],[-115.0665,42.9143],[-115.069,42.9147],[-115.0872,42.921],[-115.0874,42.9392],[-115.0869,42.9528],[-115.0872,42.996],[-115.0875,43.0265],[-115.087,43.041],[-115.0863,43.112],[-115.0871,43.1275],[-115.0864,43.1984],[-115.067,43.1985],[-115.0129,43.1987],[-114.9903,43.1988],[-114.9702,43.1989],[-114.9539,43.199],[-114.9401,43.199],[-114.8741,43.1992],[-114.8546,43.1988],[-114.756,43.1995],[-114.7352,43.1995],[-114.7139,43.1996],[-114.695,43.1996],[-114.6372,43.2001],[-114.6159,43.1997],[-114.5907,43.1997],[-114.5179,43.1997],[-114.499,43.1997],[-114.3991,43.2001],[-114.3865,43.2001],[-114.3777,43.1997],[-114.3338,43.2001],[-114.1591,43.2006],[-114.1384,43.2001],[-114.041,43.1998],[-114.0209,43.1998],[-113.9957,43.1992],[-113.9204,43.198],[-113.8971,43.1979],[-113.7991,43.1974],[-113.7802,43.1978],[-113.7771,43.1977],[-113.7187,43.1974],[-113.713,43.1974],[-113.6753,43.1976],[-113.6559,43.1979],[-113.5698,43.1978],[-113.5622,43.1982],[-113.5553,43.1982],[-113.5358,43.198],[-113.5145,43.1978],[-113.4133,43.198],[-113.4116,42.951],[-113.4118,42.9355],[-113.4117,42.8637],[-113.4113,42.8487],[-113.4325,42.8493],[-113.4707,42.8491],[-113.4707,42.8055],[-113.4709,42.791],[-113.4707,42.7209],[-113.4712,42.6914],[-113.4732,42.6769],[-113.4734,42.6673],[-113.459,42.6713],[-113.4334,42.6734],[-113.4128,42.6727],[-113.3978,42.6781],[-113.384,42.6807],[-113.3722,42.6801],[-113.3647,42.6773],[-113.3512,42.6672],[-113.3408,42.6571],[-113.3346,42.6511],[-113.3285,42.6465],[-113.3229,42.6415],[-113.3162,42.636],[-113.3076,42.6291],[-113.2975,42.6317],[-113.2907,42.6307],[-113.2864,42.6289],[-113.2814,42.6266],[-113.2714,42.6278],[-113.2652,42.6287],[-113.2609,42.6259],[-113.2561,42.6163],[-113.2498,42.6181],[-113.2441,42.6217],[-113.2366,42.6257],[-113.2322,42.6265],[-113.2228,42.6283],[-113.2165,42.6319]]]},\"properties\":{\"name\":\"Cassia\",\"state\":\"ID\"}}]}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br>U.S. Geological Survey<br>230 Collins Rd<br>Boise, Idaho 83702-4520</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2022-07-22","noUsgsAuthors":false,"publicationDate":"2022-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Skinner, Kenneth D. 0000-0003-1774-6565 kskinner@usgs.gov","orcid":"https://orcid.org/0000-0003-1774-6565","contributorId":138820,"corporation":false,"usgs":true,"family":"Skinner","given":"Kenneth","email":"kskinner@usgs.gov","middleInitial":"D.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":847355,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70235770,"text":"70235770 - 2022 - Cathodoluminescence response of barite at room and liquid nitrogen temperatures","interactions":[],"lastModifiedDate":"2022-08-18T15:08:46.507218","indexId":"70235770","displayToPublicDate":"2022-07-22T09:52:55","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Cathodoluminescence response of barite at room and liquid nitrogen temperatures","docAbstract":"<p>Rare earth element (REE) enrichment in the Elk Creek carbonatite, Nebraska USA, is comparable to ore grade enrichment in carbonatite-hosted REE deposits[1]. Petrographic examination of textures documents a complex history of crystallization, brecciation, recrystallization, oxidation, and near surface alteration. Barite (BaSO<sub>4</sub>) is present in most units, including REE-enriched zones, such that it may provide important constraints on processes that lead to ore-grade enrichment of carbonatites. Samples containing barite from different temperature regimes within the deposit were chosen to study the cathodoluminescence (CL) response at room and liquid nitrogen (LN) temperatures to help determine the processes by which REEs were enriched within the deposit and possible contributions of REE to the CL response.</p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S1431927622003178","usgsCitation":"Lowers, H.A., MacRae, C., Wilson, N., and Verplanck, P., 2022, Cathodoluminescence response of barite at room and liquid nitrogen temperatures, v. 28, no. S1, p. 668-670, https://doi.org/10.1017/S1431927622003178.","productDescription":"3 p.","startPage":"668","endPage":"670","ipdsId":"IP-138351","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":405309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"S1","noUsgsAuthors":false,"publicationDate":"2022-08-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lowers, Heather A. 0000-0001-5360-9264 hlowers@usgs.gov","orcid":"https://orcid.org/0000-0001-5360-9264","contributorId":191307,"corporation":false,"usgs":true,"family":"Lowers","given":"Heather","email":"hlowers@usgs.gov","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":849229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacRae, Colin","contributorId":295342,"corporation":false,"usgs":false,"family":"MacRae","given":"Colin","email":"","affiliations":[{"id":63849,"text":"CSIRO Minerals","active":true,"usgs":false}],"preferred":false,"id":849230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Nick","contributorId":295343,"corporation":false,"usgs":false,"family":"Wilson","given":"Nick","email":"","affiliations":[{"id":63849,"text":"CSIRO Minerals","active":true,"usgs":false}],"preferred":false,"id":849231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verplanck, Philip L. 0000-0002-3653-6419","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":212813,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":849232,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70235784,"text":"70235784 - 2022 - A review of asteroid biology in the context of sea star wasting: Possible causes and consequences","interactions":[],"lastModifiedDate":"2022-09-27T16:57:37.17445","indexId":"70235784","displayToPublicDate":"2022-07-22T07:08:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1014,"text":"Biological Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"A review of asteroid biology in the context of sea star wasting: Possible causes and consequences","docAbstract":"<div class=\"col-lg-9 article__content\"><div class=\"article__body show-references \"><div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Sea star wasting—marked in a variety of sea star species as varying degrees of skin lesions followed by disintegration—recently caused one of the largest marine die-offs ever recorded on the west coast of North America, killing billions of sea stars. Despite the important ramifications this mortality had for coastal benthic ecosystems, such as increased abundance of prey, little is known about the causes of the disease or the mechanisms of its progression. Although there have been studies indicating a range of causal mechanisms, including viruses and environmental effects, the broad spatial and depth range of affected populations leaves many questions remaining about either infectious or non-infectious mechanisms. Wasting appears to start with degradation of mutable connective tissue in the body wall, leading to disintegration of the epidermis. Here, we briefly review basic sea star biology in the context of sea star wasting and present our current knowledge and hypotheses related to the symptoms, the microbiome, the viruses, and the associated environmental stressors. We also highlight throughout the article knowledge gaps and the data needed to better understand sea star wasting mechanistically, its causes, and potential management.</p></div></div></div></div>","language":"English","publisher":"University of Chicago Press","doi":"10.1086/719928","usgsCitation":"Oulhen, N., Byrne, M., Duffin, P., Gomez-Chiarri, M., Hewson, I., Hodin, J., Konar, B., Lipp, E., Miner, B.G., Newton, A., Schiebelhut, L.M., Smolowitz, R., Wahltinez, S.J., Wessel, G.M., Work, T.M., Zaki, H.A., and Wares, J.P., 2022, A review of asteroid biology in the context of sea star wasting: Possible causes and consequences: Biological Bulletin, v. 234, no. 1, p. 50-75, https://doi.org/10.1086/719928.","productDescription":"26 p.","startPage":"50","endPage":"75","ipdsId":"IP-131688","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":447038,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10642522","text":"External Repository"},{"id":405334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"234","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oulhen, Nathalie","contributorId":295354,"corporation":false,"usgs":false,"family":"Oulhen","given":"Nathalie","email":"","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":849267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrne, Maria","contributorId":295355,"corporation":false,"usgs":false,"family":"Byrne","given":"Maria","email":"","affiliations":[{"id":16826,"text":"University of Sydney","active":true,"usgs":false}],"preferred":false,"id":849268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duffin, Paige","contributorId":295356,"corporation":false,"usgs":false,"family":"Duffin","given":"Paige","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":849269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gomez-Chiarri, Marta","contributorId":295357,"corporation":false,"usgs":false,"family":"Gomez-Chiarri","given":"Marta","email":"","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":849270,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hewson, Ian","contributorId":295358,"corporation":false,"usgs":false,"family":"Hewson","given":"Ian","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":849271,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hodin, Jason","contributorId":295360,"corporation":false,"usgs":false,"family":"Hodin","given":"Jason","email":"","affiliations":[{"id":63853,"text":"Friday Harbor Labs","active":true,"usgs":false}],"preferred":false,"id":849272,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Konar, Brenda","contributorId":295362,"corporation":false,"usgs":false,"family":"Konar","given":"Brenda","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":849273,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lipp, Erin K","contributorId":295364,"corporation":false,"usgs":false,"family":"Lipp","given":"Erin K","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":849274,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miner, Benjamin G","contributorId":295366,"corporation":false,"usgs":false,"family":"Miner","given":"Benjamin","email":"","middleInitial":"G","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":849275,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Newton, Alisa L","contributorId":295368,"corporation":false,"usgs":false,"family":"Newton","given":"Alisa L","affiliations":[{"id":63854,"text":"Disney's Animals Science and Environment","active":true,"usgs":false}],"preferred":false,"id":849276,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schiebelhut, Lauren M","contributorId":295369,"corporation":false,"usgs":false,"family":"Schiebelhut","given":"Lauren","email":"","middleInitial":"M","affiliations":[{"id":54780,"text":"UC Merced","active":true,"usgs":false}],"preferred":false,"id":849277,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smolowitz, Roxanna","contributorId":295370,"corporation":false,"usgs":false,"family":"Smolowitz","given":"Roxanna","email":"","affiliations":[{"id":39003,"text":"Roger Williams University","active":true,"usgs":false}],"preferred":false,"id":849278,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wahltinez, Sarah J","contributorId":295371,"corporation":false,"usgs":false,"family":"Wahltinez","given":"Sarah","email":"","middleInitial":"J","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":849279,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wessel, Gary M","contributorId":295372,"corporation":false,"usgs":false,"family":"Wessel","given":"Gary","email":"","middleInitial":"M","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":849280,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":849281,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zaki, Hossam A","contributorId":295373,"corporation":false,"usgs":false,"family":"Zaki","given":"Hossam","email":"","middleInitial":"A","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":849282,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Wares, John P","contributorId":295374,"corporation":false,"usgs":false,"family":"Wares","given":"John","email":"","middleInitial":"P","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":849283,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70235705,"text":"70235705 - 2022 - Early treatment of white-nose syndrome is necessary to stop population decline","interactions":[],"lastModifiedDate":"2022-10-17T15:49:29.799347","indexId":"70235705","displayToPublicDate":"2022-07-22T07:02:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Early treatment of white-nose syndrome is necessary to stop population decline","docAbstract":"<ol class=\"\"><li>Since its introduction to North America, white-nose syndrome has been associated with declines greater than 90% in several bat species, prompting the development of treatments to reduce disease-related mortality. As treatment application is scaled up, predicting responses at the population level will help in the development of management plans.</li><li>We develop a model allowing for the implementation of multiple treatment scenarios in bat populations at risk of severe mortality from white-nose syndrome. Our model allows for variation in over 10 parameters, including effectiveness of treatment, treatment-related disturbance, number of individuals treated, number of hibernacula treated, herd immunity and movement among hibernacula. Additionally, the model allows treatments to be applied to individuals, the hibernaculum or a combination of the two. We simulated treatments for populations of 1000, 10,000 and 100,000 individuals, with the distribution of individuals within hibernacula based on field surveys of<span>&nbsp;</span><i>Myotis lucifugus</i>.</li><li>When treatments are applied to individuals, we found that treatment success was most influenced by the number of bats effectively treated, the magnitude of disturbance and the year of first treatment relative to initial mortality. For treatments applied to hibernacula, we found year of first treatment relative to initial mortality, magnitude of disturbance and effectiveness of treatment to be the best predictors of success.</li><li>Treatments have the potential to mitigate white-nose syndrome-related mortality, but application of treatments after initial mass mortality seems to be of limited benefit. Unknowns surrounding influential treatment parameters, such as disturbance to hibernating bats, created substantial variation across outcomes and highlight the importance of obtaining field estimates of parameters associated with treatments.</li><li><i>Synthesis and applications</i>: While treatment applications can increase survival from white-nose syndrome, their potential is strongly diminished when not applied before or during the early epidemic stages. Once the disease is established, increasing survival and reproduction through methods other than disease treatments could be a better option. In the United States, most areas yet to reach the late epidemic or established stage are in the west where bats do not aggregate in large colonies and treating a substantial number of individuals will be difficult.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.14254","usgsCitation":"Grider, J.F., Thogmartin, W.E., Campbell Grant, E.H., Bernard, R.F., and Russell, R., 2022, Early treatment of white-nose syndrome is necessary to stop population decline: Journal of Applied Ecology, v. 59, no. 10, p. 2531-2541, https://doi.org/10.1111/1365-2664.14254.","productDescription":"11 p.","startPage":"2531","endPage":"2541","ipdsId":"IP-132875","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":447039,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.14254","text":"Publisher Index Page"},{"id":435759,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95GDPZM","text":"USGS data release","linkHelpText":"Applying Simulated Treatments to Bat Populations Experiencing Severe White-nose Syndrome Mortality"},{"id":405181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Grider, John Forrest 0000-0002-8245-190X","orcid":"https://orcid.org/0000-0002-8245-190X","contributorId":295255,"corporation":false,"usgs":true,"family":"Grider","given":"John","email":"","middleInitial":"Forrest","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":848982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":848983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":848984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernard, Riley F.","contributorId":295256,"corporation":false,"usgs":false,"family":"Bernard","given":"Riley","email":"","middleInitial":"F.","affiliations":[{"id":63808,"text":"Department of Zoology and Physiology, University of Wyoming, 1000 E. University Ave., Laramie, WY 82071 USA","active":true,"usgs":false}],"preferred":false,"id":848985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Robin E. 0000-0001-8726-7303","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":219536,"corporation":false,"usgs":true,"family":"Russell","given":"Robin E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":848986,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70233543,"text":"70233543 - 2022 - Graphite as an electrically conductive indicator of ancient crustal-scale fluid flow within mineral systems","interactions":[],"lastModifiedDate":"2022-07-25T11:58:25.374822","indexId":"70233543","displayToPublicDate":"2022-07-22T06:56:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Graphite as an electrically conductive indicator of ancient crustal-scale fluid flow within mineral systems","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0010\" class=\"abstract author\"><div id=\"as0010\"><p id=\"sp0010\">Magnetotelluric (MT) imaging results from mineral provinces in Australia and in the United States show an apparent spatial relationship between crustal-scale electrical conductivity anomalies and major magmatic-hydrothermal iron oxide-apatite/iron oxide-copper-gold (IOA-IOCG) deposits. Although these observations have driven substantial interest in the use of MT data to image ancient fluid pathways, the exact cause of these anomalies has been unclear. Here, we interpret the conductors to be the result of graphite precipitation from CO<sub>2</sub><span>-rich magmatic fluids during cooling. These fluids would have exsolved from mafic&nbsp;magmas&nbsp;at mid- to lower-crustal depths; saline magmatic fluids that could drive&nbsp;mineralization&nbsp;were likely derived from related, more evolved intrusions at shallower crustal levels. In our model, the conductivity anomalies then mark zones that once were the deep roots of ancient magmatic-hydrothermal mineral systems.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2022.117700","usgsCitation":"Murphy, B.S., Huizenga, J.M., and Bedrosian, P.A., 2022, Graphite as an electrically conductive indicator of ancient crustal-scale fluid flow within mineral systems: Earth and Planetary Science Letters, v. 594, 117700, 9 p., https://doi.org/10.1016/j.epsl.2022.117700.","productDescription":"117700, 9 p.","ipdsId":"IP-135267","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":447040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2022.117700","text":"Publisher Index Page"},{"id":404413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"594","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":847373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huizenga, Jan Marten","contributorId":293595,"corporation":false,"usgs":false,"family":"Huizenga","given":"Jan","email":"","middleInitial":"Marten","affiliations":[{"id":63330,"text":"Norwegian University of Life Sciences; , James Cook University, Townsville, Queensland, Australia; , University of Johannesburg, Auckland Park, South Africa","active":true,"usgs":false}],"preferred":false,"id":847374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":847375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70239794,"text":"70239794 - 2022 - Modeled interactions of mountain pine beetle and wildland fire under future climate and management scenarios for three western US landscapes","interactions":[],"lastModifiedDate":"2023-01-20T12:59:55.100827","indexId":"70239794","displayToPublicDate":"2022-07-22T06:56:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeled interactions of mountain pine beetle and wildland fire under future climate and management scenarios for three western US landscapes","docAbstract":"<p>Mountain pine beetle (MPB) is a native disturbance agent across most pine forests in the western US. Climate changes will directly and indirectly impact frequencies and severities of MPB outbreaks, which can then alter fuel characteristics and wildland fire dynamics via changes in stand structure and composition. To investigate the importance of MPB to past and future landscape dynamics, we used the mechanistic, spatially explicit ecosystem process model FireBGCv2 to quantify interactions among climate, MPB, wildfire, fire suppression, and fuel management under historical and projected future climates for three western US landscapes. We compared simulated FireBGCv2 output from three MPB modules (none, simple empirical, and complex mechanistic) using three focus variables and six exploratory variables to evaluate the importance of MPB to landscape dynamics.</p>","language":"English","publisher":"Springer","doi":"10.1186/s42408-022-00137-4","usgsCitation":"Keane, R., Bentz, B., Holsinger, L.M., Saab, V., and Loehman, R.A., 2022, Modeled interactions of mountain pine beetle and wildland fire under future climate and management scenarios for three western US landscapes: Fire Ecology, v. 18, 12, 18 p., https://doi.org/10.1186/s42408-022-00137-4.","productDescription":"12, 18 p.","ipdsId":"IP-139683","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":447042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-022-00137-4","text":"Publisher Index Page"},{"id":412113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.98363968463241,\n              49.37174471222207\n            ],\n            [\n              -124.98363968463241,\n              41.36819847856913\n            ],\n            [\n              -109.9167960885596,\n              41.36819847856913\n            ],\n            [\n              -109.9167960885596,\n              49.37174471222207\n            ],\n            [\n              -124.98363968463241,\n              49.37174471222207\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2022-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Keane, Robert","contributorId":187606,"corporation":false,"usgs":false,"family":"Keane","given":"Robert","affiliations":[],"preferred":false,"id":861970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bentz, Barbara","contributorId":146954,"corporation":false,"usgs":false,"family":"Bentz","given":"Barbara","affiliations":[],"preferred":false,"id":861971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holsinger, Lisa M.","contributorId":187607,"corporation":false,"usgs":false,"family":"Holsinger","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":6679,"text":"US Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":861972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saab, Victoria","contributorId":301089,"corporation":false,"usgs":false,"family":"Saab","given":"Victoria","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":861973,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":false,"id":861974,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70248760,"text":"70248760 - 2022 - A menu of climate change adaptation actions for terrestrial wildlife management","interactions":[],"lastModifiedDate":"2023-09-20T11:59:10.547283","indexId":"70248760","displayToPublicDate":"2022-07-22T06:52:47","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"A menu of climate change adaptation actions for terrestrial wildlife management","docAbstract":"<div class=\"abstract-group \"><div class=\"article-section__content en main\"><p>The real-world application of climate change adaptation practices in terrestrial wildlife conservation has been slowed by a lack of practical guidance for wildlife managers. Although there is a rapidly growing body of literature on the topic of climate change adaptation and wildlife management, the literature is weighted towards a narrow range of adaptation actions and administrative or policy recommendations that are typically beyond the decision space and influence of wildlife professionals. We developed a menu of tiered adaptation actions for terrestrial wildlife management to translate broad concepts into actionable approaches to help managers respond to climate change risks and meet desired management goals. The menu includes actions related to managing wildlife populations as well as managing wildlife habitat. We designed this resource to be used with the Adaptation Workbook, a structured decision-support tool for climate adaptation. We describe real-world examples in which managers have used the Wildlife Adaptation Menu to integrate climate adaptation considerations into wildlife management and conservation projects. Our examples illustrate how a comprehensive and structured menu of adaptation approaches can help managers brainstorm specific actions and more easily and clearly communicate the intent of their climate adaptation efforts.</p></div></div>","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.1331","usgsCitation":"Handler, S., LeDee, O.E., Hoving, C.L., Zuckerberg, B., and Swanston, C., 2022, A menu of climate change adaptation actions for terrestrial wildlife management: Wildlife Society Bulletin, v. 46, no. 4, e1331, 22 p., https://doi.org/10.1002/wsb.1331.","productDescription":"e1331, 22 p.","ipdsId":"IP-129214","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":447044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1331","text":"Publisher Index Page"},{"id":420971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Handler, Stephen D.","contributorId":329859,"corporation":false,"usgs":false,"family":"Handler","given":"Stephen D.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":883477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LeDee, Olivia E. 0000-0002-7791-5829 oledee@usgs.gov","orcid":"https://orcid.org/0000-0002-7791-5829","contributorId":242820,"corporation":false,"usgs":true,"family":"LeDee","given":"Olivia","email":"oledee@usgs.gov","middleInitial":"E.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":883478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoving, Christopher L.","contributorId":329860,"corporation":false,"usgs":false,"family":"Hoving","given":"Christopher","email":"","middleInitial":"L.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":883479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zuckerberg, Benjamin","contributorId":329861,"corporation":false,"usgs":false,"family":"Zuckerberg","given":"Benjamin","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":883480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swanston, Christopher W.","contributorId":329862,"corporation":false,"usgs":false,"family":"Swanston","given":"Christopher W.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":883481,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70233424,"text":"fs20223022 - 2022 - WHISPers—Providing situational awareness of wildlife  disease threats to the Nation—A fact sheet for the  biosurveillance community","interactions":[],"lastModifiedDate":"2022-09-16T15:59:48.77998","indexId":"fs20223022","displayToPublicDate":"2022-07-21T14:15:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3022","displayTitle":"WHISPers—Providing Situational Awareness of Wildlife Disease Threats to the Nation—A Fact Sheet for the Biosurveillance Community","title":"WHISPers—Providing situational awareness of wildlife  disease threats to the Nation—A fact sheet for the  biosurveillance community","docAbstract":"<p>Solutions for emerging infectious disease and bioterror threats can be improved by incorporating integrated biodefense strategies, including improved surveillance for animal and zoonotic diseases, strong national leadership, and effective management tools. Active biosurveillance for disease events is key to early detection, warning, and overall situational awareness and enables better communication, coordination, decision making, and data-driven responses. The national biosurveillance infrastructure has well-established channels for human and domestic animal health data through the Centers for Disease Control and Prevention and U.S. Department of Agriculture, and State, county, and local authorities. Wildlife disease information, however, has been more challenging to acquire and access, in part, due to the comparatively small infrastructure and resources dedicated to wildlife health and also because regulatory authority for wildlife and wildlife health is split among Federal, State, Tribal, and indigenous natural resource authorities. To address these issues, the Wildlife Health Information Sharing Partnership-event reporting system (WHISPers; <a href=\"https://whispers.usgs.gov\" data-mce-href=\"https://whispers.usgs.gov\">https://whispers.usgs.gov</a>) was developed by the U.S. Geological Survey National Wildlife Health Center to promote collaboration and sharing of wildlife health information and to provide situational awareness and timely information about wildlife disease threats. WHISPers is a free science gateway and data portal that provides interactive query, display, reporting, and export capabilities for wildlife health event summary information.<a href=\"mailto: whispers@usgs.gov\" data-mce-href=\"mailto: whispers@usgs.gov\"></a></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223022","usgsCitation":"Richards, B.J., Kimberli, J.M., and White, C. LeAnn, 2022, WHISPers—Providing situational awareness of wildlife disease threats to the Nation—A fact sheet for the biosurveillance community: U.S. Geological Survey Fact Sheet 2022–3022, 4 p., https://doi.org/10.3133/fs20223022.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-131585","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":404118,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3022/fs20223022.pdf","text":"Report","size":"414 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3022"},{"id":404117,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3022/coverthb2.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n           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           ],\n              [\n                -119.43884,\n                34.34848\n              ],\n              [\n                -120.36778,\n                34.44711\n              ],\n              [\n                -120.62286,\n                34.60855\n              ],\n              [\n                -120.74433,\n                35.15686\n              ],\n              [\n                -121.71457,\n                36.16153\n              ],\n              [\n                -122.54747,\n                37.55176\n              ],\n              [\n                -122.51201,\n                37.78339\n              ],\n              [\n                -122.95319,\n                38.11371\n              ],\n              [\n                -123.7272,\n                38.95166\n              ],\n              [\n                -123.86517,\n                39.76699\n              ],\n              [\n                -124.39807,\n                40.3132\n              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[\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -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}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/nwhc\" data-mce-href=\"https://www.usgs.gov/centers/nwhc\">National Wildlife Health Center</a><br>U.S. Geological Survey<br>6006 Schroeder Road<br>Madison, WI 53711-6223</p>","tableOfContents":"<ul><li>Biosurveillance and Wildlife Disease Event Data</li><li>Partners in Biosurveillance</li><li>Beyond Wildlife Disease</li><li>References Cited</li></ul>","publishedDate":"2022-07-21","noUsgsAuthors":false,"publicationDate":"2022-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":219535,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":847066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Kimberli J.G. 0000-0002-7947-0894","orcid":"https://orcid.org/0000-0002-7947-0894","contributorId":81447,"corporation":false,"usgs":true,"family":"Miller","given":"Kimberli","email":"","middleInitial":"J.G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":847067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":847068,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70233493,"text":"sir20225056 - 2022 - Light attenuation and erosion characteristics of fine sediments in a highly turbid, shallow, Great Basin Lake—Malheur Lake, Oregon, 2017–18","interactions":[],"lastModifiedDate":"2022-09-28T14:04:55.75131","indexId":"sir20225056","displayToPublicDate":"2022-07-21T13:47:09","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5056","displayTitle":"Light Attenuation and Erosion Characteristics of Fine Sediments in a Highly Turbid, Shallow, Great Basin Lake—Malheur Lake, Oregon, 2017–18","title":"Light attenuation and erosion characteristics of fine sediments in a highly turbid, shallow, Great Basin Lake—Malheur Lake, Oregon, 2017–18","docAbstract":"<p class=\"p1\">Malheur Lake is a large, shallow, turbid lake in southeastern Oregon that fluctuates widely in surface area in response to yearly precipitation and climatic cycles. High suspended-sediment concentrations (SSCs) likely are negatively affecting the survival of aquatic plants by reducing the intensity of solar radiation reaching the plants, thus inhibiting photosynthesis. This study was designed to determine the types of suspended material, the erodibility of the lakebed, the attenuation of photosynthetically active radiation (PAR) through the water column, and the effects of wind and precipitation on SSC.</p><p class=\"p1\">Two sites in the lake were monitored for approximately 5 months during the summer growing season each year (2017–19). At these sites, turbidity, chlorophyll <i>a</i> fluorescence (a surrogate for concentration), and underwater PAR measurements were collected continuously, and discrete samples were collected every 2 weeks and analyzed for SSC, loss on ignition, and chlorophyll <i>a</i> concentration. Underwater PAR profile measurements were collected during site visits, and a nearby meteorological station recorded terrestrial PAR and wind speeds.</p><p class=\"p1\">About 18 percent of suspended material in the water was organic and mostly detrital. Nearly 100 percent of all suspended material was fine material (less than 63 micrometers), and more than 90 percent of the surficial lakebed material was fine material. The high concentrations of fine material in the water column can be expected to strongly attenuate light.</p><p class=\"p1\">SSC was significantly higher at both sites in 2018 compared to 2017 and 2019; the interannual differences were mostly due to the lower amount of precipitation in 2018, which resulted in shallower lake depths. Three years of SSC values multiplied by water depth showed a seasonal pattern: concentrations were often highest in early spring, lowest in summer, and intermediate in autumn.</p><p class=\"p1\">Episodic wind events with speeds of 5–10 meters per second caused rapid increases in turbidity above background that lasted for a few days. However, a baseline SSC value multiplied by water depth (estimated to be 0.11 kilograms per square meter) was present between wind events and even under ice, suggesting a persistent suspension of very fine, highly erodible material. Terrestrial and underwater PAR measurements were used to develop a relation between PAR attenuation and turbidity that can be used in modeling restoration scenarios. Calculated bottom shear stress caused by wind-generated waves ranged from 0 to 0.4 pascals (Pa). Erosion experiments indicated variability in the bottom sediments from the two lake sites, but much of the lakebed is highly erodible at a threshold of 0.05 to 0.1 Pa.</p><p class=\"p1\">Restoration actions may target the persistent turbidity (for example, the use of flocculation) or transient turbidity (for example, construction of wave-reduction barriers), with a goal of attaining approximately 36 micromoles photons per square meter per second of PAR at the lakebed to promote emergence of sago pondweed and other desirable plants. Currently, that threshold often is reached from 4 to 34 centimeters (cm) below the water surface in 1 meter water depth, depending on wind conditions, but halving persistent turbidity would increase the upper end of the range to 55 cm. Additional studies regarding the effects of (1) sediment drying on resuspension and (2) nutrient inputs and internal cycling on phytoplankton populations would help determine the most appropriate restoration strategies.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225056","usgsCitation":"Wood, T.M., and Smith, C.D., 2022, Light attenuation and erosion characteristics of fine sediments in a highly turbid, shallow, Great Basin Lake—Malheur Lake, Oregon, 2017–18: U.S. Geological Survey Scientific Investigations Report 2022–5056, 51 p., https://doi.org/10.3133/sir20225056.","productDescription":"Report: x, 51 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-123319","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":404300,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95FMN8F","text":"USGS data release","description":"USGS data release","linkHelpText":"Photosynthetically active radiation measurements collected at Malheur Lake, Oregon, 2017-18"},{"id":404299,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92ZBWJ5","text":"USGS data release","description":"USGS data release","linkHelpText":"Phytoplankton data for Malheur Lake, Oregon, 2018-20"},{"id":404302,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5056/sir20225056.XML"},{"id":404301,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5056/images"},{"id":404297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5056/sir20225056.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5056"},{"id":404296,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5056/coverthb.jpg"},{"id":404298,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225056/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5056"}],"country":"United States","state":"Oregon","otherGeospatial":"Malheur Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.08218383789062,\n              43.113014204188914\n            ],\n            [\n              -118.42300415039062,\n              43.113014204188914\n            ],\n            [\n              -118.42300415039062,\n              43.49178653083377\n            ],\n            [\n              -119.08218383789062,\n              43.49178653083377\n            ],\n            [\n              -119.08218383789062,\n              43.113014204188914\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/or-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 92701</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Interannual and Seasonal Patterns in Optically Active Particles, 2017–19</li><li>Relation Between Optically Active Particles and Wind, 2017–19</li><li>Light Attenuation as a Function of Optically Active Particles</li><li>Measurement of Critical Shear Stress</li><li>Light Attenuation by Persistent and Transient Turbidity</li><li>Summary</li><li>References Cited</li><li>Appendixes 1–4</li></ul>","publishedDate":"2022-07-21","noUsgsAuthors":false,"publicationDate":"2022-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Cassandra D. 0000-0003-1088-1772 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-1088-1772","contributorId":205220,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":847242,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70233492,"text":"fs20223029 - 2022 - Occurrence and transport of aerially applied herbicides to control invasive buffelgrass in Rincon Mountain District, Saguaro National Park, Arizona","interactions":[],"lastModifiedDate":"2026-03-24T21:16:44.180885","indexId":"fs20223029","displayToPublicDate":"2022-07-21T11:01:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3029","displayTitle":"Occurrence and Transport of Aerially Applied Herbicides to Control Invasive Buffelgrass in Rincon Mountain District, Saguaro National Park, Arizona","title":"Occurrence and transport of aerially applied herbicides to control invasive buffelgrass in Rincon Mountain District, Saguaro National Park, Arizona","docAbstract":"<p>Resource managers of the Saguaro National Park are concerned about the spread of the invasive species <i>Cenchrus ciliaris </i>L. (buffelgrass) and the threat it poses to desert ecosystems. Glyphosate-based herbicide treatments seem to be one of a few viable options to control the spread of buffelgrass in the mountainous terrain of the National Park. The U.S. Geological Survey completed a 4-year study with the National Park Service that investigated the potential for glyphosate and associated byproducts to remain in soil and transport with stormwater runoff to ecologically important surface waters after aerial application of glyphosate-based herbicides. The results of this study are helping managers and park administrators better understand the long-term effects of treating buffelgrass with glyphosate-based herbicides.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223029","collaboration":"Prepared in cooperation with the National Park Service and Saguaro National Park","usgsCitation":"Paretti, N.V., and Gungle, B., 2022, Occurrence and transport of aerially applied herbicides to control invasive buffelgrass in Rincon Mountain District, Saguaro National Park, Arizona: U.S. Geological Survey Fact Sheet 2022-3029, 6 p., https://doi.org/10.3133/fs20223029.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-112584","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":404264,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3029/covrthb.jpg"},{"id":404265,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3029/fs20223029.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3029"},{"id":404266,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215039","text":"Scientific Investigations Report 2021–5039","description":"Paretti, N.V., Beisner, K.R., Gungle, B., Meyer, M.T., Kunz, B.K.,Hermosillo, E., Cederberg, J.R., and Mayo, J.P., 2021, Occurrence, fate, and transport of aerially applied herbicides to control invasive buffelgrass within Saguaro National Park Rincon Mountain District, Arizona, 2015–18: U.S. Geological Survey Scientific Investigations Report 2021–5039, 65 p., https://doi.org/10.3133/sir20215039.","linkHelpText":"- Occurrence, Fate, and Transport of Aerially Applied Herbicides to Control Invasive Buffelgrass within Saguaro National Park Rincon Mountain District, Arizona, 2015–18"},{"id":501489,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113309.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona","otherGeospatial":"Saguaro National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.79025268554686,\n              31.99643007718664\n            ],\n            [\n              -110.31372070312499,\n              31.99643007718664\n            ],\n            [\n              -110.31372070312499,\n              32.310348764525806\n            ],\n            [\n              -110.79025268554686,\n              32.310348764525806\n            ],\n            [\n              -110.79025268554686,\n              31.99643007718664\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/az-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/az-water\">Arizona Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","tableOfContents":"<ul><li>Introduction&nbsp;&nbsp;</li><li>Approach: Measuring glyphosate in Saguaro National Park&nbsp;&nbsp;</li><li>Results&nbsp;&nbsp;</li><li>Broader Context and Ecological Implications</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2022-07-21","noUsgsAuthors":false,"publicationDate":"2022-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Paretti, Nicholas V. 0000-0003-2178-4820 nparetti@usgs.gov","orcid":"https://orcid.org/0000-0003-2178-4820","contributorId":173412,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas","email":"nparetti@usgs.gov","middleInitial":"V.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gungle, Bruce 0000-0001-6406-1206 bgungle@usgs.gov","orcid":"https://orcid.org/0000-0001-6406-1206","contributorId":2237,"corporation":false,"usgs":true,"family":"Gungle","given":"Bruce","email":"bgungle@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":847238,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70233291,"text":"sir20225045 - 2022 - Update and recalibration of the Rio Grande Transboundary Integrated Hydrologic Model, New Mexico and Texas, United States, and northern Chihuahua, Mexico","interactions":[],"lastModifiedDate":"2022-07-21T14:47:24.69486","indexId":"sir20225045","displayToPublicDate":"2022-07-21T09:50:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5045","displayTitle":"Update and Recalibration of the Rio Grande Transboundary Integrated Hydrologic Model, New Mexico and Texas, United States, and Northern Chihuahua, Mexico","title":"Update and recalibration of the Rio Grande Transboundary Integrated Hydrologic Model, New Mexico and Texas, United States, and northern Chihuahua, Mexico","docAbstract":"<p>The Rio Grande Transboundary Integrated Hydrologic Model (RGTIHM) was developed through an interagency effort between the U.S. Geological Survey and the Bureau of Reclamation to provide a tool for analyzing the hydrologic system response to the historical evolution of water use and potential changes in water supplies and demands in the Hatch Valley (also known as Rincon Valley in the study area) and Mesilla Basin, New Mexico and Texas, United States, and northern Chihuahua, Mexico. Reclamation operates the Rio Grande Project (RGP) to store and deliver surface water for irrigation and municipal use within the study area and in the El Paso Valley south of the El Paso Narrows.</p><p>Biases in the RGTIHM’s simulation of streamflow and aquifer storage depletion and the availability of new estimates of historical agricultural consumptive use in the study area initiated an update and recalibration of the RGTIHM. In addition to the new estimates of historical agricultural consumptive use, updates were made to more accurately represent the natural system and included adjustments to the initial groundwater levels; streamflow rating tables; Rio Grande, canal, and drain streambed elevations; tributary streambed elevations; surface-water inflows and diversions; RGP surface-water deliveries and canal waste; on-farm efficiency; the routing of surface-water runoff within the MODFLOW Farm Process; and general head boundaries used to simulate interbasin groundwater flow. Model settings, including the assignment of hydraulic conductivity and storage properties to model layers and the MODFLOW solver package, were adjusted to improve numerical stability, and the model was recalibrated to better simulate the natural system. The updated and recalibrated RGTIHM demonstrates a robust ability to simulate the spatially and temporally variable measurements, estimates, or reports of hydraulic head, surface-water flows, agricultural pumping, RGP surface-water deliveries and canal waste, and decadal aquifer storage changes, with improvements over the previous version of the model.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225045","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Ritchie, A.B., Galanter, A.E., Flickinger, A.K., Shephard, Z.M., and Ferguson, I.M., 2022, Update and recalibration of the Rio Grande Transboundary Integrated Hydrologic Model, New Mexico and Texas, United States, and northern Chihuahua, Mexico: U.S. Geological Survey Scientific Investigations Report 2022–5045, 28 p., https://doi.org/10.3133/sir20225045.","productDescription":"Report: vi, 28 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-132740","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":404020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5045/coverthb.jpg"},{"id":404021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5045/sir20225045.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5045"},{"id":404023,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5045/images"},{"id":404024,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5045/sir20225045.xml"},{"id":404022,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99PLDXV","text":"USGS data release","linkHelpText":"MODFLOW One-Water Hydrologic Flow Model (MF-OWHM) used to simulate conjunctive use in the Hatch Valley and Mesilla Basin,   New Mexico and Texas, United States, and northern Chihuahua, Mexico"}],"country":"Mexico, United States","state":"Chihuahua, New Mexico, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108,\n              31.5\n            ],\n            [\n              -106,\n              31.5\n            ],\n            [\n              -106,\n              33.25\n            ],\n            [\n              -108,\n              33.25\n            ],\n            [\n              -108,\n              31.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/new-mexico-water-science-center/\" data-mce-href=\"http://www.usgs.gov/centers/new-mexico-water-science-center/\"> New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Model Updates</li><li>Model Recalibration</li><li>Calibration Results and Model Outputs</li><li>Model Performance, Limitations, and Suggestions for Future Work</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2022-07-21","noUsgsAuthors":false,"publicationDate":"2022-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritchie, Andre B. 0000-0003-1289-653X","orcid":"https://orcid.org/0000-0003-1289-653X","contributorId":205392,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andre B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846921,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846922,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flickinger, Allison K. 0000-0002-8638-2569","orcid":"https://orcid.org/0000-0002-8638-2569","contributorId":223702,"corporation":false,"usgs":true,"family":"Flickinger","given":"Allison","email":"","middleInitial":"K.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferguson, Ian M. iferguson@usbr.gov","contributorId":293311,"corporation":false,"usgs":false,"family":"Ferguson","given":"Ian","email":"iferguson@usbr.gov","middleInitial":"M.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":846925,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70233464,"text":"70233464 - 2022 - Herbivory changes biomass allocation but does not induce resistance among clones of an invasive plant","interactions":[],"lastModifiedDate":"2022-08-02T15:10:10.758258","indexId":"70233464","displayToPublicDate":"2022-07-21T09:21:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5819,"text":"Arthropod-Plant Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Herbivory changes biomass allocation but does not induce resistance among clones of an invasive plant","docAbstract":"<p>Inducible responses to herbivores can be either localized or spread systemically throughout a plant. The ways in which clonal plants integrate their response to herbivores among clonal ramets is not well understood. Yet, this is important to understand the impacts that herbivores may have on clonal plants. We conducted a factorial split-plot greenhouse experiment to determine whether resistance is induced among ramets and how biomass allocation changes among ramets following herbivore damage to one of them. We manipulated the presence of two herbivores,<span>&nbsp;</span><i>Pieris rapae</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Trichoplusia ni,</i><span>&nbsp;</span>and the root connection of ramets of the clonal invasive weed,<span>&nbsp;</span><i>Lepidium draba</i>. We found local inducible resistance on the ramet where an herbivore fed, but not in neighboring ramets. Biomass allocation shifted in response to herbivores. Feeding by the generalist caterpillar<span>&nbsp;</span><i>T. ni</i><span>&nbsp;</span>resulted in a greater belowground biomass relative to shoot biomass in the local plant, but only when the clonal connection was intact. In contrast, herbivores had little impact on the root mass fraction of neighboring ramets. Herbivory to the local ramet increased the regrowth of neighboring ramets that lacked clonal connection, a trend that was driven by the specialist herbivore<span>&nbsp;</span><i>P. rapae</i>. Herbivores did not induce systemic resistance among ramets of<span>&nbsp;</span><i>L. draba</i>, but herbivores, especially the specialist, did alter how neighboring ramets regrow after grazing or mowing. Our observations suggest that individual ramets have fairly autonomous responses to herbivores, and that coordination among ramets, when present, may happen via signals that do not depend on root connections.</p>","language":"English","publisher":"Springer","doi":"10.1007/s11829-022-09897-x","usgsCitation":"Becker, Z., Ode, P.J., West, N., and Pearse, I.S., 2022, Herbivory changes biomass allocation but does not induce resistance among clones of an invasive plant: Arthropod-Plant Interactions, v. 16, p. 297-307, https://doi.org/10.1007/s11829-022-09897-x.","productDescription":"11 p.","startPage":"297","endPage":"307","ipdsId":"IP-122252","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435760,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99MSTOE","text":"USGS data release","linkHelpText":"Data on how Lepidium draba responds to damage of clones"},{"id":404219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Becker, Zoe","contributorId":248271,"corporation":false,"usgs":false,"family":"Becker","given":"Zoe","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":847161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ode, Paul J.","contributorId":197314,"corporation":false,"usgs":false,"family":"Ode","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":847162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"West, Natalie","contributorId":293501,"corporation":false,"usgs":false,"family":"West","given":"Natalie","email":"","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":847163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":847164,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70233453,"text":"70233453 - 2022 - Geomorphic controls on floodplain connectivity, ecosystem services, and sensitivity to climate change: An example from the lower Missouri River","interactions":[],"lastModifiedDate":"2022-07-21T14:02:14.824922","indexId":"70233453","displayToPublicDate":"2022-07-21T08:53:00","publicationYear":"2022","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":"Geomorphic controls on floodplain connectivity, ecosystem services, and sensitivity to climate change: An example from the lower Missouri River","docAbstract":"Floodplains of large rivers are exploited for agricultural production, industrial and municipal development, and transportation infrastructure. Recently, increased frequency of costly floods has prompted consideration of whether offsetting benefits might accrue from management of floodplains for ecosystem services. We employed a simple inundation model for 800 km of the Lower Missouri River, USA, to evaluate spatial and temporal distributions of ecological floodplain inundation metrics and how those distributions might vary with levee removal and climatic change. The model evaluates inundation at 30 × 30 m resolution on a daily basis over 82 years of record. We quantified provisioning of waterfowl habitat and potential denitrification. Spatial variability is affected by ongoing geomorphic adjustments that affect floodplain connectivity. Statistical models indicate that available floodplain area and recent aggradation are predictive of most inundation metrics. Connectivity is sensitive to climate-change scenarios that predict increased floodplain inundation during spring waterfowl migrations; the greatest sensitivity to future climate exists where channel-floodplain geomorphology presently enhances floodplain connectivity. Evaluation of floodplain denitrification indicates that on average, the nonleveed part of the floodplain could denitrify 0.05%–1.7% of the mean annual nitrogen load of the river. Levee removal could increase this rate to only 3.6% of the nitrogen load. The capacity of floodplain connectivity to influence certain ecosystem services is highly variable in space along the Lower Missouri River and may be appreciably influenced by climate change. Hence, decisions to optimize management of large-river floodplains are likely to be highly location dependent.","language":"English","publisher":"John Wiley & Sons","doi":"10.1029/2021WR031204","usgsCitation":"Jacobson, R., Bouska, K.L., Bulliner, E., Lindner, G., and Paukert, C., 2022, Geomorphic controls on floodplain connectivity, ecosystem services, and sensitivity to climate change: An example from the lower Missouri River: Water Resources Research, v. 58, no. 6, e2021WR031204, 26 p., https://doi.org/10.1029/2021WR031204.","productDescription":"e2021WR031204, 26 p.","ipdsId":"IP-133183","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":447047,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr031204","text":"Publisher Index Page"},{"id":435761,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SP3E3M","text":"USGS data release","linkHelpText":"Inundation metrics by 10-km bend, Lower Missouri River Floodplain"},{"id":404213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Kansas, Missouri, Nebraska, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.7838134765625,\n              42.8115217450979\n            ],\n            [\n              -97.2894287109375,\n              42.79943131987838\n            ],\n            [\n              -97.1356201171875,\n              42.69858589169842\n            ],\n           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This study investigated the long-term (1980s to 2010s) effects of increasing urbanization on key stormflow characteristics using observed 15 min streamflow data across six broad hydroclimate representative urban watersheds in the conterminous United States. The results indicate upward trends in peak stormflow and downward trends in time-to-peak stormflow at four out of six watersheds. The watershed in the Great Plains region had the largest annual increasing (decreasing) percent change in peak stormflow (time-to-peak stormflow). 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