{"pageNumber":"800","pageRowStart":"19975","pageSize":"25","recordCount":165485,"records":[{"id":70263652,"text":"70263652 - 2018 - The 1952 Kern County, California earthquake: A case study of issues in the analysis of historical intensity data for estimation of source parameters","interactions":[],"lastModifiedDate":"2025-02-19T14:24:12.731569","indexId":"70263652","displayToPublicDate":"2018-09-11T10:06:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3071,"text":"Physics of the Earth and Planetary Interiors","active":true,"publicationSubtype":{"id":10}},"title":"The 1952 Kern County, California earthquake: A case study of issues in the analysis of historical intensity data for estimation of source parameters","docAbstract":"<p><span>Seismic intensity data based on first-hand accounts of shaking give valuable insight into historical and early instrumental earthquakes. Comparing an observed intensity distribution to intensity-prediction models based on modern calibration events allows the magnitude to be estimated for many historic earthquakes. Magnitude estimates can also potentially be refined for earthquakes for which limited instrumental data are available. However, the complicated nature of macroseismic data and the methods used to collect and interpret the data introduce significant uncertainties. In this paper, we illustrate these challenges and possible solutions using the 1952 Kern County, California, earthquake as a case study. Published estimates of its magnitude vary from M</span><sub>W</sub><span>&nbsp;7.2–7.5, making it possibly the second largest in California during the 20th century. We considered over 1100 first-hand reports of shaking, supplemented with other data, and inferred the magnitude in several ways using intensity prediction equations, yielding a preferred intensity magnitude M</span><sub>I</sub><span>&nbsp;7.2 ± 0.2, where the uncertainty reflects our judgement. The revised intensity distribution reveals stronger shaking on the hanging wall, south of the surface expression of the White Wolf fault, than on the footwall. Characterizing the magnitude and shaking distribution of this early instrumental earthquake can help improve estimation of the seismic hazard of the region. Such reinterpreted intensities for historic earthquakes, combined with U.S. Geological Survey (USGS) Did You Feel It? data for more recent events, can be used to produce a uniform shaking dataset with which earthquake hazard map performance can be assessed.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.pepi.2018.08.007","usgsCitation":"Salditch, L., Hough, S.E., Stein, S., Spencer, B., Brooks, E., Neely, J.S., and Lucas, M.C., 2018, The 1952 Kern County, California earthquake: A case study of issues in the analysis of historical intensity data for estimation of source parameters: Physics of the Earth and Planetary Interiors, v. 283, p. 140-151, https://doi.org/10.1016/j.pepi.2018.08.007.","productDescription":"12 p.","startPage":"140","endPage":"151","ipdsId":"IP-101209","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482166,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.84752123561667,\n              35.795851992110386\n            ],\n            [\n              -119.84752123561667,\n              34.87128790332352\n            ],\n            [\n              -118.27725907195563,\n              34.87128790332352\n            ],\n            [\n              -118.27725907195563,\n              35.795851992110386\n            ],\n            [\n              -119.84752123561667,\n              35.795851992110386\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"283","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Salditch, Leah","contributorId":263445,"corporation":false,"usgs":false,"family":"Salditch","given":"Leah","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, Bruce","contributorId":350997,"corporation":false,"usgs":false,"family":"Spencer","given":"Bruce","affiliations":[],"preferred":false,"id":927671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooks, Edward","contributorId":350999,"corporation":false,"usgs":false,"family":"Brooks","given":"Edward","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927672,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927673,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lucas, Madeleine C.","contributorId":336741,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","middleInitial":"C.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":927674,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70199221,"text":"fs20183032 - 2018 - Changes in Earth’s gravity reveal changes in groundwater storage","interactions":[],"lastModifiedDate":"2018-09-12T10:07:10","indexId":"fs20183032","displayToPublicDate":"2018-09-11T10:01:46","publicationYear":"2018","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":"2018-3032","title":"Changes in Earth’s gravity reveal changes in groundwater storage","docAbstract":"<div dir=\"ltr\">Changes in the amount of water stored in underground aquifers cause small changes in Earth’s gravitational field. The U.S. Geological Survey’s Southwest Gravity Program has developed methods for measuring terrestrial gravity changes with part-per-billion precision. The measurements allow scientists to map changes in groundwater storage and to improve models that simulate groundwater flow.<br><br></div>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183032","usgsCitation":"Kennedy, J.R., 2018, Changes in Earth’s gravity reveal changes in groundwater storage: U.S. Geological Survey Fact Sheet 2018–3032, 4 p., https://doi.org/10.3133/fs20183032.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-080753","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":357229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3032/fs20183032.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3032"},{"id":357228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3032/coverthb.jpg"}],"contact":"<p><a data-mce-href=\"mailto:dc_az@usgs.gov\" href=\"mailto:dc_az@usgs.gov\" target=\"_blank\" rel=\"noopener\">Director</a>,<br><a data-mce-href=\"https://az.water.usgs.gov/\" href=\"https://az.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\">Arizona Water Science Center</a><br>U.S. Geological Survey<br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-09-11","noUsgsAuthors":false,"publicationDate":"2018-09-11","publicationStatus":"PW","scienceBaseUri":"5b98a260e4b0702d0e842e46","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744738,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70211581,"text":"70211581 - 2018 - Necropsy-based wild fish health assessment","interactions":[],"lastModifiedDate":"2020-07-31T13:38:52.250692","indexId":"70211581","displayToPublicDate":"2018-09-11T08:36:52","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"Necropsy-based wild fish health assessment","docAbstract":"<p><span>Anthropogenic influences from increased nutrients and chemical contaminants, to habitat alterations and climate change, can have significant effects on fish populations. Adverse effects monitoring, utilizing biomarkers from the organismal to the molecular level, can be used to assess the cumulative effects on fishes and other organisms. Fish health has been used worldwide as an indicator of aquatic ecosystem health. The necropsy-based fish health assessment provides data on visible abnormalities and lesions, parasites, condition and organosomatic indices. These can be compared by site, season and sex, as well as temporally, to document change over time. Severity ratings can be assigned to various observations to calculate a fish health index for more quantitative assessment. A drawback of the necropsy-based assessment is that it is based on visual observations and condition factors, which are not as sensitive as tissue and subcellular biomarkers for sublethal effects. Additionally, it is rarely possible to identify causes or risk factors associated with observed abnormalities. So, for instance a raised lesion or \"tumor\" on the fins, lips or body surface may be a neoplasm. However, it could also be a response to a parasite, chronic inflammation or hyperplasia of normal cells in response to an irritant. Conversely, neoplasms, certain parasites, other infectious agents and many tissue changes are not visible and so may be underestimated. However, during the necropsy-based assessment, blood (plasma), tissues for histopathology (microscopic pathology), genomics and other molecular analyses, and otoliths for aging can be collected. These downstream analyses, together with geospatial analyses, habitat assessments, water quality and contaminant analyses can all be important in comprehensive ecosystem evaluations.</span></p>","language":"English","publisher":"JOVE","doi":"10.3791/57946","usgsCitation":"Blazer, V., Walsh, H.L., Braham, R.P., and Smith, C.R., 2018, Necropsy-based wild fish health assessment: Journal of Visualized Experiments, v. 139, e57946, 11 p., https://doi.org/10.3791/57946.","productDescription":"e57946, 11 p.","ipdsId":"IP-094627","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468416,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6235148","text":"Publisher Index Page"},{"id":376942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","noUsgsAuthors":false,"publicationDate":"2018-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Heather L. 0000-0001-6392-4604","orcid":"https://orcid.org/0000-0001-6392-4604","contributorId":213348,"corporation":false,"usgs":false,"family":"Walsh","given":"Heather","email":"","middleInitial":"L.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":794693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Braham, Ryan P. 0000-0002-2102-0989","orcid":"https://orcid.org/0000-0002-2102-0989","contributorId":204542,"corporation":false,"usgs":true,"family":"Braham","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Cheyenne R. 0000-0002-7226-1774","orcid":"https://orcid.org/0000-0002-7226-1774","contributorId":219236,"corporation":false,"usgs":true,"family":"Smith","given":"Cheyenne","email":"","middleInitial":"R.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":794695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236833,"text":"70236833 - 2018 - The 19 September 2017 M 7.1 Puebla‐Morelos earthquake: Spectral ratios confirm Mexico City zoning","interactions":[],"lastModifiedDate":"2022-09-20T12:07:55.967914","indexId":"70236833","displayToPublicDate":"2018-09-11T07:04:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The 19 September 2017 M 7.1 Puebla‐Morelos earthquake: Spectral ratios confirm Mexico City zoning","docAbstract":"<p><span>One important element of understanding basin response to strong shaking is the analysis of spectral ratios, which may provide information about the dominant frequency of ground motion at specific locations. Spectral ratios computed from accelerations recorded by strong‐motion stations in Mexico City during the mainshock of the 19 September 2017&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mi\">M</span></span></span></span><span class=\"MJX_Assistive_MathML\">M</span></span></span><span>&nbsp;7.1 Puebla‐Morelos earthquake reveal predominate periods consistent with those mapped in the 2004 Mexican seismic design code. Furthermore, the predominant periods thus computed validate those studies using mainshock and aftershock recordings of the handful strong‐motion stations that recorded the 19 September 1985&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi></math>\"><span id=\"MathJax-Span-4\" class=\"math\"><span><span id=\"MathJax-Span-5\" class=\"mrow\"><span id=\"MathJax-Span-6\" class=\"mi\">M</span></span></span></span><span class=\"MJX_Assistive_MathML\">M</span></span></span><span>&nbsp;8.1 Michoacán earthquake. Even though the number of stations in each of the zones (zones I, II, IIIa, b, c, and d) is not the same, they still allow confirmation of site frequencies (periods) attributable to the specific zones (particularly those in zones IIIa, b, c, and d). Spectral ratios are computed with two different methods: (1)&nbsp;horizontal to horizontal (H/H) ratio of smoothed amplitude spectrum of a horizontal channel in direction X of a station with respect to the smoothed amplitude spectrum of the horizontal channel in the same X direction of a reference stiff soil (or rock) station and (2) horizontal to vertical (H/V) ratio (or also known as the Nakamura method) of both horizontal (H) and vertical (V) channels of the same station. We show a comparison of the identified frequencies (periods) derived by both methods and find they are very similar and in good agreement with those indicated in the zoning maps of Mexico City in the 2004 seismic design code.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180100","usgsCitation":"Celebi, M., Sahakian, V.J., Melgar, D., and Quintanar, L., 2018, The 19 September 2017 M 7.1 Puebla‐Morelos earthquake: Spectral ratios confirm Mexico City zoning: Bulletin of the Seismological Society of America, v. 108, no. 6, p. 3289-3299, https://doi.org/10.1785/0120180100.","productDescription":"11 p.","startPage":"3289","endPage":"3299","ipdsId":"IP-094416","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","county":"Mexico City","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.08544921874999,\n              18.8335153964335\n            ],\n            [\n              -98.39355468749999,\n              18.8335153964335\n            ],\n            [\n              -98.39355468749999,\n              20.2209657795223\n            ],\n            [\n              -100.08544921874999,\n              20.2209657795223\n            ],\n            [\n              -100.08544921874999,\n              18.8335153964335\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"108","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-09-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":852324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sahakian, Valerie Jean 0000-0002-3278-4458","orcid":"https://orcid.org/0000-0002-3278-4458","contributorId":296738,"corporation":false,"usgs":true,"family":"Sahakian","given":"Valerie","email":"","middleInitial":"Jean","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":852381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melgar, Diego","contributorId":193030,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","email":"","affiliations":[],"preferred":false,"id":852382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quintanar, Luis","contributorId":208095,"corporation":false,"usgs":false,"family":"Quintanar","given":"Luis","email":"","affiliations":[{"id":37714,"text":"Instituto de Geofísica, Universidad Nacional Autónoma de México","active":true,"usgs":false}],"preferred":false,"id":852383,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199253,"text":"70199253 - 2018 - Internal parasites of the two subspecies of the West Indian manatee Trichechus manatus","interactions":[],"lastModifiedDate":"2018-09-13T15:55:02","indexId":"70199253","displayToPublicDate":"2018-09-10T15:54:57","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Internal parasites of the two subspecies of the West Indian manatee <i>Trichechus manatus</i>","title":"Internal parasites of the two subspecies of the West Indian manatee Trichechus manatus","docAbstract":"<p><span>The West Indian manatee&nbsp;</span><i>Trichechus manatus</i><span>&nbsp;is divided into 2 subspecies: the Antillean (</span><i>T. m. manatus</i><span>) and Florida (</span><i>T. m. latirostris</i><span>) manatees. This study reports sample prevalence of manatee parasites from populations of these 2 subspecies in different geographical locations. Although necropsy is a valuable diagnostic tool for parasite infections, the need for antemortem diagnostic techniques is important. Fecal samples collected during necropsies of Antillean manatees (n = 3) in Puerto Rico and Florida manatees (n = 10) in Crystal River, Florida, as well as from live-captured Florida manatees (n = 11) were evaluated using centrifugal flotation with sucrose and ethyl acetate sedimentation to compare parasites from each of the populations. Although both fecal examination methods provided similar results, the centrifugal flotation method required less time for diagnosis. The most common parasite eggs found in both populations included the trematodes&nbsp;</span><i>Pulmonicola cochleotrema</i><span>&nbsp;and&nbsp;</span><i>Nudacotyle undicola</i><span>, oocysts of the coccidian&nbsp;</span><i>Eimeria</i><span>&nbsp;spp., and eggs of the ascarid&nbsp;</span><i>Heterocheilus tunicatus</i><span>. Eggs of the trematode&nbsp;</span><i>Chiorchis groschafti</i><span>&nbsp;were found in both populations of manatees; however, eggs of a related species,&nbsp;</span><i>Chiorchis fabaceus,</i><span>&nbsp;were abundant in the Florida samples, but not found in Puerto Rico populations. Trematode eggs of&nbsp;</span><i>Moniligerum blairi</i><span>&nbsp;were found in both populations, but were more common in the Florida manatee (42%) than the Antillean manatee (33%). To our knowledge, this is the first report of both&nbsp;</span><i>Eimeria manatus</i><span>&nbsp;and&nbsp;</span><i>Eimeria nodulosa</i><span>&nbsp;oocysts in Antillean manatees from Puerto Rico.</span></p>","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03270","usgsCitation":"Wyrosdick, H.M., Chapman, A., Mignucci-Giannoni, A.A., Riviera-Perez, C.I., and Bonde, R.K., 2018, Internal parasites of the two subspecies of the West Indian manatee Trichechus manatus: Diseases of Aquatic Organisms, v. 130, no. 2, p. 145-152, https://doi.org/10.3354/dao03270.","productDescription":"8 p.","startPage":"145","endPage":"152","ipdsId":"IP-086853","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":357289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fa2e4b0fc368eb53937","contributors":{"authors":[{"text":"Wyrosdick, Heidi M.","contributorId":201769,"corporation":false,"usgs":false,"family":"Wyrosdick","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":744835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chapman, Alycia","contributorId":201771,"corporation":false,"usgs":false,"family":"Chapman","given":"Alycia","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":744836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mignucci-Giannoni, Antonio A.","contributorId":201773,"corporation":false,"usgs":false,"family":"Mignucci-Giannoni","given":"Antonio","email":"","middleInitial":"A.","affiliations":[{"id":36251,"text":"Interamerican University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":744837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riviera-Perez, Carla I.","contributorId":207836,"corporation":false,"usgs":false,"family":"Riviera-Perez","given":"Carla","email":"","middleInitial":"I.","affiliations":[{"id":36251,"text":"Interamerican University of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":744838,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":744834,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70199202,"text":"70199202 - 2018 - Modelling sound attenuation in heterogeneous environments for improved bioacoustic sampling of wildlife populations","interactions":[],"lastModifiedDate":"2018-09-10T13:56:12","indexId":"70199202","displayToPublicDate":"2018-09-10T13:56:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Modelling sound attenuation in heterogeneous environments for improved bioacoustic sampling of wildlife populations","docAbstract":"<ol class=\"\"><li>Acoustic sampling methods are becoming increasingly important in biological monitoring. Sound attenuation is one of the most important dynamics affecting the utility of acoustic data as it directly affects the probability of detection of individuals by acoustic sensor arrays and especially the localization of acoustic signals necessary in telemetry studies. Therefore, models of sound attenuation are necessary to make efficient use of acoustic data in ecological monitoring and assessment applications. Models of attenuation in widespread use are based on Euclidean distance between source and sensor, which is justified under spherical attenuation of sound waves in homogeneous environments.</li><li>In this paper, I develop a model of sound attenuation based on a non‐Euclidean cost‐weighted distance metric which contains attenuation coefficients that characterize the attenuation of sound due to environmental heterogeneity in the vicinity of an acoustic sensor array.</li><li>I show that parameters of the proposed attenuation model can be estimated by maximum likelihood using experimental data from an array of fixed sources, thus allowing investigators who use bioacoustic methods to devise explicit models of sound attenuation<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>and apply them to localization of sources and density estimation. In addition, drawing on analogy with spatial capture–recapture models, I argue that parameters of the non‐Euclidean model of attenuation can be estimated when source locations are<span>&nbsp;</span><i>unknown</i>. Thus, the models can be applied to real field studies which require estimation of attenuation parameters or localization of signals.</li><li>Models of heterogeneous sound attenuation allow more accurate descriptions of acoustic monitoring data, and therefore should produce more accurate estimates of ecological parameters of interest, including source locations, density, and movement trajectories. Moreover, the ability to test specific hypotheses about the effects of habitat and landscape structure on sound attenuation can improve the design of acoustic monitoring arrays and lead to more efficient deployment of acoustic sensing technology.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.13040","usgsCitation":"Royle, J.A., 2018, Modelling sound attenuation in heterogeneous environments for improved bioacoustic sampling of wildlife populations: Methods in Ecology and Evolution, v. 9, no. 9, p. 1939-1947, https://doi.org/10.1111/2041-210X.13040.","productDescription":"9 p.","startPage":"1939","endPage":"1947","ipdsId":"IP-093167","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468417,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/239079","text":"External Repository"},{"id":357206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-12","publicationStatus":"PW","scienceBaseUri":"5b98a261e4b0702d0e842e48","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":744649,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70199206,"text":"70199206 - 2018 - Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management","interactions":[],"lastModifiedDate":"2018-09-10T12:35:28","indexId":"70199206","displayToPublicDate":"2018-09-10T12:35:21","publicationYear":"2018","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":"Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management","docAbstract":"<p><span>In many parts of the world, the combined effects of habitat fragmentation and altered disturbance regimes pose a significant threat to biodiversity. This is particularly true in Mediterranean-type ecosystems (MTEs), which tend to be fire-prone, species rich, and heavily impacted by human land use. Given the spatial complexity of overlapping threats and species’ vulnerability along with limited conservation budgets, methods are needed for prioritizing areas for monitoring and management in these regions. We developed a multi-criteria Pareto ranking methodology for prioritizing spatial units for conservation and applied it to fire threat, habitat fragmentation threat, species richness, and genetic biodiversity criteria in San Diego County, California, USA. We summarized the criteria and Pareto ranking results (from west to east) within the maritime, coastal, transitional, inland climate zones within San Diego County. Fire threat increased from the maritime zone eastward to the transitional zone, then decreased in the mountainous inland climate zone. Number of fires and fire return interval departure were strongly negatively correlated. Fragmentation threats, particularly road density and development density, were highest in the maritime climate zone, declined towards the east, and were positively correlated. Species richness criteria showed distributions among climate zones similar to those of the fire threat variables. When using species richness and fire threat criteria, most lower-ranked (higher conservation priority) units occurred in the coastal and transitional zones. When considering genetic biodiversity, lower-ranked units occurred more often in the mountainous inland zone. With Pareto ranking, there is no need to select criteria weights as part of the decision-making process. However, negative correlations and larger numbers of criteria can result in more units assigned to the same rank. Pareto ranking is broadly applicable and can be used as a standalone decision analysis method or in conjunction with other methods.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0200203","usgsCitation":"Tracey, J.A., Rochester, C.J., Hathaway, S.A., Preston, K.L., Syphard, A.D., Vandergast, A.G., Diffendorfer, J., Franklin, J., MacKenzie, J.B., Oberbauer, T.A., Tremor, S., Winchell, C.S., and Fisher, R.N., 2018, Prioritizing conserved areas threatened by wildfire and fragmentation for monitoring and management: PLoS ONE, v. 13, no. 9, p. 1-23, https://doi.org/10.1371/journal.pone.0200203.","productDescription":"e0200203; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-095520","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468418,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0200203","text":"Publisher Index 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Here we examine the global relationship between peatland carbon accumulation rates during the last millennium and planetary-scale climate space. A positive relationship is found between carbon accumulation and cumulative photosynthetically active radiation during the growing season for mid- to high-latitude peatlands in both hemispheres. However, this relationship reverses at lower latitudes, suggesting that carbon accumulation is lower under the warmest climate regimes. Projections under Representative Concentration Pathway (RCP)2.6 and RCP8.5 scenarios indicate that the present-day global sink will increase slightly until around AD 2100 but decline thereafter. 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Stephen","contributorId":220277,"corporation":false,"usgs":false,"family":"Robinson","given":"Stephen","affiliations":[],"preferred":false,"id":774626,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Roland, Thomas P.","contributorId":220278,"corporation":false,"usgs":false,"family":"Roland","given":"Thomas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":774627,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Sanderson, Nicole K.","contributorId":220279,"corporation":false,"usgs":false,"family":"Sanderson","given":"Nicole","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":774628,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Sannel, A. B. K.","contributorId":38450,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"B. K.","affiliations":[],"preferred":false,"id":774629,"contributorType":{"id":1,"text":"Authors"},"rank":62},{"text":"Silva-Sanchez, Noemi","contributorId":220280,"corporation":false,"usgs":false,"family":"Silva-Sanchez","given":"Noemi","email":"","affiliations":[],"preferred":false,"id":774630,"contributorType":{"id":1,"text":"Authors"},"rank":63},{"text":"Steinberg, Natasha","contributorId":220281,"corporation":false,"usgs":false,"family":"Steinberg","given":"Natasha","email":"","affiliations":[],"preferred":false,"id":774631,"contributorType":{"id":1,"text":"Authors"},"rank":64},{"text":"Swindles, Graeme T.","contributorId":220282,"corporation":false,"usgs":false,"family":"Swindles","given":"Graeme","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":774632,"contributorType":{"id":1,"text":"Authors"},"rank":65},{"text":"Turner, T. Edward","contributorId":220283,"corporation":false,"usgs":false,"family":"Turner","given":"T.","email":"","middleInitial":"Edward","affiliations":[],"preferred":false,"id":774633,"contributorType":{"id":1,"text":"Authors"},"rank":66},{"text":"Uglow, Joanna","contributorId":220284,"corporation":false,"usgs":false,"family":"Uglow","given":"Joanna","email":"","affiliations":[],"preferred":false,"id":774634,"contributorType":{"id":1,"text":"Authors"},"rank":67},{"text":"Valiranta, M.","contributorId":166678,"corporation":false,"usgs":false,"family":"Valiranta","given":"M.","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":774635,"contributorType":{"id":1,"text":"Authors"},"rank":68},{"text":"van Bellen, Simon","contributorId":220285,"corporation":false,"usgs":false,"family":"van Bellen","given":"Simon","email":"","affiliations":[],"preferred":false,"id":774636,"contributorType":{"id":1,"text":"Authors"},"rank":69},{"text":"van der Linden, Marjolein","contributorId":220286,"corporation":false,"usgs":false,"family":"van der Linden","given":"Marjolein","email":"","affiliations":[],"preferred":false,"id":774637,"contributorType":{"id":1,"text":"Authors"},"rank":70},{"text":"Wang, Guoping","contributorId":220288,"corporation":false,"usgs":false,"family":"Wang","given":"Guoping","email":"","affiliations":[],"preferred":false,"id":774638,"contributorType":{"id":1,"text":"Authors"},"rank":71},{"text":"Yu, Zicheng 0000-0003-2358-2712","orcid":"https://orcid.org/0000-0003-2358-2712","contributorId":147521,"corporation":false,"usgs":false,"family":"Yu","given":"Zicheng","email":"","affiliations":[{"id":16857,"text":"Lehigh Univ.","active":true,"usgs":false}],"preferred":false,"id":774639,"contributorType":{"id":1,"text":"Authors"},"rank":72},{"text":"Zaragoza-Castells, Joana","contributorId":220289,"corporation":false,"usgs":false,"family":"Zaragoza-Castells","given":"Joana","email":"","affiliations":[],"preferred":false,"id":774640,"contributorType":{"id":1,"text":"Authors"},"rank":73},{"text":"Zhao, Yan","contributorId":220290,"corporation":false,"usgs":false,"family":"Zhao","given":"Yan","email":"","affiliations":[],"preferred":false,"id":774641,"contributorType":{"id":1,"text":"Authors"},"rank":74}]}}
,{"id":70197509,"text":"sir20185068 - 2018 - Methods used to reconstruct historical daily streamflows in northern New Jersey and southeastern New York, water years 1922–2010","interactions":[],"lastModifiedDate":"2018-09-10T16:50:30","indexId":"sir20185068","displayToPublicDate":"2018-09-10T12:00:00","publicationYear":"2018","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":"2018-5068","title":"Methods used to reconstruct historical daily streamflows in northern New Jersey and southeastern New York, water years 1922–2010","docAbstract":"<p>A study was conducted by the U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, to reconstruct streamflows for use in the RiverWare model. Methods and data used to estimate daily reconstructed streamflows at 53 sites in selected subbasins in northern New Jersey and southeastern New York are presented in the report. These subbasins contain one or more surface-water diversions that are operated or have been operated in the past by water purveyors or the New Jersey Department of Environmental Protection. Reconstructed streamflows are estimates of those streamflows that would have occurred without the effects of changes in reservoir storage or surface-water diversions by water purveyors.</p><p>Reconstructed flows at 47 sites were determined from monthly observed streamflows, changes in reservoir storage, and surface-water diversions. Monthly reconstructed streamflows were calculated directly for those months with sufficient data. Missing monthly reconstructed flows were estimated from relations between selected calculated values of monthly reconstructed flows and monthly observed flows at selected index gages. Daily reconstructed flows were determined from the disaggregation of monthly reconstructed flows on the basis of daily observed flows at selected streamgages. At six sites, reconstructed flows were determined from relations between discrete measurements of observed streamflows and daily observed streamflows at selected index gages.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185068","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Hickman, R.E., and McHugh, A.R., 2018, Methods used to reconstruct historical daily streamflows in northern New Jersey and southeastern New York, water years 1922–2010: U.S. Geological Survey Scientific Investigations Report 2018–5068, 75 p., https://doi.org/10.3133/sir20185068.","productDescription":"viii, 75 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070147","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":437761,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7J965CZ","text":"USGS data release","linkHelpText":"Data and equations used to reconstruct historical daily streamflows in northern New Jersey and southeastern New York, water years 1922-2010"},{"id":357153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5068/coverthb2.jpg"},{"id":357154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5068/sir20185068.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5068"},{"id":357155,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F7J965CZ","text":"USGS data release","description":"USGS data release","linkHelpText":"Data and equations used to reconstruct historical daily streamflows in northern New Jersey and southeastern New York, water years 1922–2010"}],"country":"United States","state":"New Jersey, New York","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.049,\n              40.402\n            ],\n            [\n              -73.906,\n              40.402\n            ],\n            [\n              -73.906,\n              41.396\n            ],\n            [\n              -75.049,\n              41.396\n            ],\n            [\n              -75.049,\n              40.402\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nj@usgs.gov\" data-mce-href=\"mailto:dc_nj@usgs.gov\">Director</a>, <a href=\"https://nj.usgs.gov/\" data-mce-href=\"https://nj.usgs.gov/\">New Jersey Water Science Center</a><br>U.S. Geological Survey <br>3450 Princeton Pike, Suite 110<br>Lawrenceville, NJ 08648</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Application of Methods to Flow-Reconstruction Sites in Each Subbasin</li><li>Limitations and Assessment of Reconstructed Flows</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Estimation of Monthly Observed Streamflows at Selected Streamgages</li><li>Appendix 2. Calculation of Monthly Observed Streamflows in Beaver Brook at the Outlet of Splitrock Reservoir from Furnished Data</li><li>Appendix 3. Estimation of Observed Daily Streamflow at Six Partial-Record Stations</li><li>Appendix 4. Estimation of Monthly Transfer Rates of the Three Pipe Diversions Used by the North Jersey District Water Supply Commission to Transfer Water to Oradell Reservoir</li><li>Appendix 5. Maintenance of Variance Extension Type 1</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2018-09-10","noUsgsAuthors":false,"publicationDate":"2018-09-10","publicationStatus":"PW","scienceBaseUri":"5b98a262e4b0702d0e842e4e","contributors":{"authors":[{"text":"Hickman, R. Edward 0000-0001-5160-3723","orcid":"https://orcid.org/0000-0001-5160-3723","contributorId":205490,"corporation":false,"usgs":true,"family":"Hickman","given":"R.","email":"","middleInitial":"Edward","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McHugh, Amy R. 0000-0002-7745-9886","orcid":"https://orcid.org/0000-0002-7745-9886","contributorId":205491,"corporation":false,"usgs":true,"family":"McHugh","given":"Amy R.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":737500,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70199203,"text":"70199203 - 2018 - Multiphase flow and underpressured shale at the Bruce nuclear site, Ontario, Canada","interactions":[],"lastModifiedDate":"2019-08-15T11:35:08","indexId":"70199203","displayToPublicDate":"2018-09-10T11:59:07","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Multiphase flow and underpressured shale at the Bruce nuclear site, Ontario, Canada","docAbstract":"<p><span>Hydraulic testing has revealed dramatic underpressures in Paleozoic shales and carbonates at the Bruce nuclear site in Ontario. Although evidence from both laboratory and field studies suggests that a small amount of gas-phase methane could be present in the shale, previous studies examining causal linkages between the gas phase and the underpressure have been inconclusive. To better elucidate processes in such a system, we used a highly simplified 1D representation of the site to test, by using iTOUGH2-EOS7C, the effects of various factors on the evolution of gas-phase methane and pressures within the system. Heterogeneity was represented by three stratigraphic regions with slightly different capillary pressure characteristics and, in one case, three thin distinct zones with very different characteristics. Underpressure occurred only when gas pressures set as an initial condition required it, and even in this case it was geologically short-lived. We conclude that the presence of multiple fluid phases is unlikely to explain the underpressure at the site; we suggest that the influence of gas-phase methane on porewater flow is minimal. This is consistent with prior conceptualizations of the underpressured section as a thick aquiclude, in which solute transport occurs extremely slowly, bounded by aquifers of significantly higher permeability.</span></p>","language":"English","publisher":"Geological Society of London","doi":"10.1144/SP482.5","usgsCitation":"Plampin, M.R., and Neuzil, C.E., 2018, Multiphase flow and underpressured shale at the Bruce nuclear site, Ontario, Canada: Geological Society, London, Special Publications, v. 482, p. 101-114, https://doi.org/10.1144/SP482.5.","productDescription":"14 p.","startPage":"101","endPage":"114","ipdsId":"IP-092568","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468421,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/sp482.5","text":"Publisher Index Page"},{"id":437762,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JQ107B","text":"USGS data release","linkHelpText":"iTOUGH2-EOS7C model used to analyze multiphase flow and underpressured shale at the Bruce Nuclear Site, Ontario, Canada"},{"id":357198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Ontario","volume":"482","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-07","publicationStatus":"PW","scienceBaseUri":"5b98a263e4b0702d0e842e50","contributors":{"authors":[{"text":"Plampin, Michelle R. 0000-0003-4068-5801 mplampin@usgs.gov","orcid":"https://orcid.org/0000-0003-4068-5801","contributorId":204983,"corporation":false,"usgs":true,"family":"Plampin","given":"Michelle","email":"mplampin@usgs.gov","middleInitial":"R.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":744650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neuzil, Christopher E. 0000-0003-2022-4055 ceneuzil@usgs.gov","orcid":"https://orcid.org/0000-0003-2022-4055","contributorId":2322,"corporation":false,"usgs":true,"family":"Neuzil","given":"Christopher","email":"ceneuzil@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":744651,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70198845,"text":"cir1446 - 2018 - U.S. Geological Survey sage-grouse and sagebrush ecosystem research annual report for 2018","interactions":[],"lastModifiedDate":"2018-12-12T09:32:55","indexId":"cir1446","displayToPublicDate":"2018-09-10T11:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1446","displayTitle":"U.S. Geological Survey Sage-Grouse and Sagebrush Ecosystem Research Annual Report for 2018","title":"U.S. Geological Survey sage-grouse and sagebrush ecosystem research annual report for 2018","docAbstract":"<p>The sagebrush (<i>Artemisia</i> spp.) ecosystem extends across a large portion of the Western United States, and the greater sage-grouse (<i>Centrocercus urophasianus</i>) is one of the iconic species of this ecosystem. Greater sage-grouse populations occur in 11 States and are dependent on relatively large expanses of sagebrush-dominated habitat. Sage-grouse populations have been experiencing long-term declines owing to multiple stressors, including interactions among fire, exotic plant invasions, and human land uses, which have resulted in significant loss, fragmentation, and degradation of landscapes once dominated by sagebrush. In addition to the sage-grouse, over 350 species of plants and animals are dependent on the sagebrush ecosystem.</p><p>Increasing knowledge about how these species and the sagebrush ecosystem respond to these stressors and to management actions can inform and improve strategies to maintain existing areas of intact sagebrush and restore degraded landscapes. The U.S. Geological Survey (USGS) has a broad research program focused on providing the science needed to inform these strategies and to help land and resource managers at the Federal, State, Tribal, and local levels as they work towards sustainable sage-grouse populations and restored landscapes for the broad range of uses critical to stakeholders in the Western United States.</p><p>USGS science has provided a foundation for major land and resource management decisions including those that precluded the need to list the greater sage-grouse under the Endangered Species Act. The USGS is continuing to build on that foundation to inform science-based decisions to help support local economies and the continued conservation, management, and restoration of the sagebrush ecosystem.</p><p>This report contains descriptions of USGS sage-grouse and sagebrush ecosystem research projects that are ongoing or were active during 2018 and is organized into five thematic areas: Fire, Invasive Species, Restoration, Sagebrush, Sage-Grouse, and Other Sagebrush-Associated Species; and Climate and Weather.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1446","isbn":"978-1-4113-4526-9","usgsCitation":"Hanser, S.E., ed., 2018, U.S. Geological Survey sage-grouse and sagebrush ecosystem research annual report for 2018: U.S. Geological Survey Circular 1446, 67 p., https://doi.org/10.3133/cir1446.","productDescription":"iv, 67 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-098865","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":356725,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1446/coverthb.jpg"},{"id":356726,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1446/cir1446.pdf","text":"Report","size":"15.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIRC 1446"}],"contact":"<p><a href=\"https://www.usgs.gov/ecosystems/sage-grouse-sagebrush-ecosystem\" data-mce-href=\"https://www.usgs.gov/ecosystems/sage-grouse-sagebrush-ecosystem\">Sage-Grouse and Sagebrush Ecosystem Program</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Mail Stop 301<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Research To Support the Management of Sage-Grouse and the Sagebrush Ecosystem</li><li>Structure of the U.S. Geological Survey Sage-Grouse and Sage Ecosystem Research Program</li><li>List of Projects</li><li>Project Descriptions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-09-10","noUsgsAuthors":false,"publicationDate":"2018-09-10","publicationStatus":"PW","scienceBaseUri":"5b98a263e4b0702d0e842e54","contributors":{"editors":[{"text":"Hanser, Steven E. 0000-0002-4430-2073 shanser@usgs.gov","orcid":"https://orcid.org/0000-0002-4430-2073","contributorId":127554,"corporation":false,"usgs":true,"family":"Hanser","given":"Steven","email":"shanser@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":743826,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}}
,{"id":70198854,"text":"cir1447 - 2018 - U.S. Geological Survey energy and wildlife research annual report for 2018","interactions":[],"lastModifiedDate":"2018-12-12T09:35:36","indexId":"cir1447","displayToPublicDate":"2018-09-10T11:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1447","displayTitle":"U.S. Geological Survey Energy and Wildlife Research Annual Report for 2018","title":"U.S. Geological Survey energy and wildlife research annual report for 2018","docAbstract":"<p>USGS scientists provide scientific information and options that land and resource managers and private industries can use to make decisions regarding the development of energy resources while protecting the health of ecosystems. Studies focus on delivering information to avoid, minimize, or mitigate the impacts of energy infrastructure on fish and wildlife. USGS scientists are currently developing mapping tools and models that identify areas of biological strengths and weaknesses or high- and low-quality habitat and can identify opportunities for conservation—areas of high-quality habitat where energy-generating potential is low—and areas of potential risk—areas of high-quality habitat where energy-generating potential is high. These tools can assist resource managers and the industry concerning siting of energy development and selection of off-site mitigation areas. Scientific efforts, such as these, further the understanding of impacts related to energy development and create workable solutions. The three goals guiding USGS activities related to the interactions between wildlife and energy development are to understand risks by identifying when, where, and how fish and wildlife share space with energy facilities, measure direct and indirect impacts to species, and inform feasible and cost-effective solutions to minimize impacts through technological fixes, management, and mitigation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1447","isbn":"978-1-4113-4257-6","collaboration":" ","usgsCitation":"Khalil, Mona, ed., 2018, U.S. Geological Survey energy and wildlife research annual report for 2018 (ver. 1.1,  October 2018): U.S. Geological Survey Circular 1447, 102 p., https://doi.org/10.3133/cir1447.","productDescription":"v, 101 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-099243","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":357117,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1447/cir1447.pdf","text":"Report","size":"20.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIRC 1447"},{"id":357956,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1447/versionHist.txt","size":"1.32 KB","linkFileType":{"id":2,"text":"txt"}},{"id":357116,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1447/coverthb4.jpg"}],"edition":"Version 1.1: October 2018; Version 1.0: September 2018","contact":"<p><a href=\"https://www2.usgs.gov/ecosystems/energy_wildlife/ \" data-mce-href=\"https://www2.usgs.gov/ecosystems/energy_wildlife/\">Energy and Wildlife Program</a> <br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Science to Understand Risks, Measure Impacts, and Inform Solutions</li><li>Partners</li><li>USGS Mission</li><li>Energy and Wildlife Science Strategy</li><li>Updates to the Annual Report</li><li>List of Projects</li><li>Energy Icons</li><li>Study Locations</li><li>Project Descriptions</li><li>References Cited</li><li>List of Species</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-09-10","revisedDate":"2018-10-02","noUsgsAuthors":false,"publicationDate":"2018-09-10","publicationStatus":"PW","scienceBaseUri":"5b98a263e4b0702d0e842e52","contributors":{"editors":[{"text":"Khalil, Mona 0000-0002-6046-1293 mkhalil@usgs.gov","orcid":"https://orcid.org/0000-0002-6046-1293","contributorId":174228,"corporation":false,"usgs":true,"family":"Khalil","given":"Mona","email":"mkhalil@usgs.gov","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":744485,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}}
,{"id":70222923,"text":"70222923 - 2018 - A comparison of the chemical sensitivities between in vitro and in vivo propagated juvenile freshwater mussels: Implications for standard toxicity testing","interactions":[],"lastModifiedDate":"2021-08-10T15:17:20.512097","indexId":"70222923","displayToPublicDate":"2018-09-10T10:11:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of the chemical sensitivities between in vitro and in vivo propagated juvenile freshwater mussels: Implications for standard toxicity testing","docAbstract":"<p><span>Unionid mussels are ecologically important and are globally imperiled. Toxicants contribute to mussel declines, and toxicity tests using juvenile mussels—a sensitive life stage—are valuable in determining thresholds used to set water quality criteria. In vitro culture methods provide an efficient way to propagate juveniles for toxicity testing, but their relative chemical sensitivity compared with in vivo propagated juveniles is unknown. Current testing guidelines caution against using in vitro cultured juveniles until this sensitivity is described. Our objective was to evaluate the relative sensitivity of juvenile mussels produced from both in vitro and in vivo propagation methods to selected chemicals. We conducted 96-h acute toxicity tests according to ASTM International guidelines with 3 mussel species and 6 toxicants: chloride, nickel, ammonia, and 3 copper-based compounds. Statistically significant differences between in vitro and in vivo juvenile 96-h median effect concentrations were observed in 8 of 17 tests, and in vitro juveniles were more sensitive in 6 of the 8 significant differences. At 96 h, 4 of the 8 statistically different tests for a given chemical were within a factor of 2, which is the intralaboratory variation demonstrated in a recent evaluation of mussel toxicity tests. We found that although differences in chemical sensitivity exist between in vitro and in vivo propagated juvenile mussels, they are within normal toxicity test variation. Therefore, in vitro propagated juvenile mussels may be appropriate for use in ASTM International-based toxicity testing.</span></p>","language":"English","publisher":"Society of Environmental Toxicology and Cehmistry","doi":"10.1002/etc.4270","usgsCitation":"Popp, A., Cope, W., McGregor, M., Kwak, T.J., Augspurger, T., Levine, J.F., and Koch, L., 2018, A comparison of the chemical sensitivities between in vitro and in vivo propagated juvenile freshwater mussels: Implications for standard toxicity testing: Environmental Toxicology and Chemistry, v. 37, no. 12, p. 3077-3085, https://doi.org/10.1002/etc.4270.","productDescription":"9 p.","startPage":"3077","endPage":"3085","ipdsId":"IP-100193","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":387816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"12","noUsgsAuthors":false,"publicationDate":"2018-09-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Popp, A.","contributorId":263409,"corporation":false,"usgs":false,"family":"Popp","given":"A.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":820812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cope, W. G.","contributorId":263410,"corporation":false,"usgs":false,"family":"Cope","given":"W. G.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":820813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGregor, M.A.","contributorId":263412,"corporation":false,"usgs":false,"family":"McGregor","given":"M.A.","email":"","affiliations":[{"id":53972,"text":"Kentucky Department of Fish and Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":820814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":820815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Augspurger, T.","contributorId":81844,"corporation":false,"usgs":false,"family":"Augspurger","given":"T.","email":"","affiliations":[],"preferred":false,"id":820816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Levine, Jay F.","contributorId":80902,"corporation":false,"usgs":false,"family":"Levine","given":"Jay","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":820817,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Koch, L.","contributorId":263415,"corporation":false,"usgs":false,"family":"Koch","given":"L.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":820818,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70199175,"text":"70199175 - 2018 - Approaches for improving field soil identification","interactions":[],"lastModifiedDate":"2018-09-09T20:22:08","indexId":"70199175","displayToPublicDate":"2018-09-09T20:22:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Approaches for improving field soil identification","docAbstract":"<p>Use of soil survey information by non-soil-scientists is often limited by their inability to select the correct soil map unit component (COMP). Here, we developed two approaches that can be deployed to smartphones for non-soil-scientists to identify COMP from the location alone or location together with easily observed field data (i.e., slope, depth to the restrictive layer, and soil texture by depth). In addition, we also compared the two newly developed approaches with a traditional approach identifying COMP based on the dominant COMP (DC-based approach). All three approaches were tested with the Rapid Assessment of US Soil Carbon database and the combined USDA- NRCS Soil Survey Geographic database and the USDA-NRCS State Soil Geographic Database. The results indicated that the observation-based approach performed significantly better than the other two approaches, suggesting that a small set of easy-to-measure site-specific observations could significantly improve COMP identification. The location- and DC-based approaches had similar low performance overall. However, the location-based approach slightly improved identifications over the DC-based approach for cases where (i) there were multiple possible components within the soil map unit and (ii) the components were located in close proximity to a boundary of a different soil map unit polygon. The benefit of using the location-based approach may be greater in specific soil survey areas where topography was the major factor leading to the creation of the map unit legend.</p>","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2017.09.0337","usgsCitation":"Fan, Z., Wills, S.A., Herrick, J.E., Nauman, T.W., Brungard, C.W., Beaudette, D.E., Levi, M.R., and O’Geen, A.T., 2018, Approaches for improving field soil identification: Soil Science Society of America Journal, v. 82, no. 4, p. 871-877, https://doi.org/10.2136/sssaj2017.09.0337.","productDescription":"7 p.","startPage":"871","endPage":"877","ipdsId":"IP-091477","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":357148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","scienceBaseUri":"5b98a263e4b0702d0e842e56","contributors":{"authors":[{"text":"Fan, Zhaosheng","contributorId":199104,"corporation":false,"usgs":false,"family":"Fan","given":"Zhaosheng","email":"","affiliations":[],"preferred":false,"id":744538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wills, Skye A.","contributorId":207736,"corporation":false,"usgs":false,"family":"Wills","given":"Skye","email":"","middleInitial":"A.","affiliations":[{"id":37616,"text":"USDA-NRCS National Soil Survey Center","active":true,"usgs":false}],"preferred":false,"id":744539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":744540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brungard, Colby W.","contributorId":207737,"corporation":false,"usgs":false,"family":"Brungard","given":"Colby","email":"","middleInitial":"W.","affiliations":[{"id":37617,"text":"Department of Plant and Environmental Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":744541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beaudette, Dylan E.","contributorId":207738,"corporation":false,"usgs":false,"family":"Beaudette","given":"Dylan","email":"","middleInitial":"E.","affiliations":[{"id":37618,"text":"USDA-NRCS Soil Survey Division, Sonora, CA","active":true,"usgs":false}],"preferred":false,"id":744542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Levi, Matthew R.","contributorId":207739,"corporation":false,"usgs":false,"family":"Levi","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":37619,"text":"USDA- ARS Research Unit","active":true,"usgs":false}],"preferred":false,"id":744543,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O’Geen, Anthony T.","contributorId":207740,"corporation":false,"usgs":false,"family":"O’Geen","given":"Anthony","email":"","middleInitial":"T.","affiliations":[{"id":37041,"text":"Department of Land, Air, and Water Resources, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":744544,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70199176,"text":"70199176 - 2018 - Soil property and class maps of the conterminous United States at 100-meter spatial resolution","interactions":[],"lastModifiedDate":"2018-09-09T20:20:06","indexId":"70199176","displayToPublicDate":"2018-09-09T20:16:58","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Soil property and class maps of the conterminous United States at 100-meter spatial resolution","docAbstract":"<p>With growing concern for the depletion of soil resources, conventional soil maps need to be updated and provided at finer and finer resolutions to be able to support spatially explicit human–landscape models. Three US soil point datasets—the National Cooperative Soil Survey Characterization Database, the National Soil Information System, and the Rapid Carbon Assessment dataset—were combined with a stack of over 200 environmental datasets and gSSURGO polygon maps to generate complete coverage gridded predictions at 100-m spatial resolution of six soil properties (percentage of organic C, total N, bulk density, pH, and percentage of sand and clay) and two US soil taxonomic classes (291 great groups [GGs] and 78 modified particle size classes [mPSCs]) for the conterminous United States. Models were built using parallelized random forest and gradient boosting algorithms as implemented in the ranger and xgboost packages for R. Soil property predictions were generated at seven standard soil depths (0, 5, 15, 30, 60, 100, and 200 cm). Prediction probability maps for US soil taxonomic classifications were also generated. Cross validation results indicated an out-of-bag classification accuracy of 60% for GGs and 66% for mPSCs; for soil properties, RMSE for leave-location-out cross-validation was 0.74 (<i>R</i><sup>2</sup> = 0.68), 17.8 wt% (<i>R</i><sup>2</sup> = 0.57), 12 wt% (<i>R</i><sup>2</sup> = 0.46), 3.63 wt% (<i>R</i><sup>2</sup> = 0.41), 0.2 g cm<sup>−3</sup> (<i>R</i><sup>2</sup> = 0.42), and 0.27 wt% (<i>R</i><sup>2</sup> = 0.39) for pH, percent sand and clay, weight percentage of organic C, bulk density, and weight percentage of total N, respectively. Nine independent validation datasets were used to assess prediction accuracies for soil class models, and results ranged between 24 and 58% and between 24 and 93% for GG and mPSC prediction accuracies, respectively. Although mapping accuracies were variable and likely lower than gSSURGO in some areas, this modeling approach can enable easier integration of soil information with spatially explicit models compared with multicomponent map units.</p>","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2017.04.0122","usgsCitation":"Ramcharan, A., Hengl, T., Nauman, T.W., Brungard, C.W., Waltman, S., Wills, S.A., and Thompson, J., 2018, Soil property and class maps of the conterminous United States at 100-meter spatial resolution: Soil Science Society of America Journal, v. 82, no. 1, p. 186-201, https://doi.org/10.2136/sssaj2017.04.0122.","productDescription":"16 p.","startPage":"186","endPage":"201","ipdsId":"IP-086724","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468422,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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University Park, PA 16802","active":true,"usgs":false}],"preferred":false,"id":744546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hengl, Tomislav","contributorId":207742,"corporation":false,"usgs":false,"family":"Hengl","given":"Tomislav","email":"","affiliations":[{"id":37621,"text":"ISRIC—World Soil Information Wageningen, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":744547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brungard, Colby W.","contributorId":207737,"corporation":false,"usgs":false,"family":"Brungard","given":"Colby","email":"","middleInitial":"W.","affiliations":[{"id":37617,"text":"Department of Plant and Environmental Sciences, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":744548,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waltman, Sharon","contributorId":192099,"corporation":false,"usgs":false,"family":"Waltman","given":"Sharon","email":"","affiliations":[],"preferred":false,"id":744549,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wills, Skye A.","contributorId":207736,"corporation":false,"usgs":false,"family":"Wills","given":"Skye","email":"","middleInitial":"A.","affiliations":[{"id":37616,"text":"USDA-NRCS National Soil Survey Center","active":true,"usgs":false}],"preferred":false,"id":744550,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thompson, James","contributorId":83806,"corporation":false,"usgs":false,"family":"Thompson","given":"James","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":744551,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70199177,"text":"70199177 - 2018 - Reductions in tree performance during hotter droughts are mitigated by shifts in nitrogen cycling","interactions":[],"lastModifiedDate":"2018-10-23T16:53:07","indexId":"70199177","displayToPublicDate":"2018-09-09T20:08:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3090,"text":"Plant, Cell & Environment","onlineIssn":"1365-3040","active":true,"publicationSubtype":{"id":10}},"title":"Reductions in tree performance during hotter droughts are mitigated by shifts in nitrogen cycling","docAbstract":"<p>Climate warming should result in hotter droughts of unprecedented severity in this century. Such droughts have been linked with massive tree mortality, and data suggest that warming interacts with drought to aggravate plant performance. Yet how forests will respond to hotter droughts remains unclear, as does the suite of mechanisms trees use to deal with hot droughts. We used an ecosystem‐scale manipulation of precipitation and temperature on piñon pine (<i>Pinus edulis</i>) and juniper (<i>Juniperus monosperma</i>) trees to investigate nitrogen (N) cycling‐induced mitigation processes related to hotter droughts. We found that while negative impacts on plant carbon and water balance are manifest after prolonged drought, performance reductions were not amplified by warmer temperatures. Rather, increased temperatures for 5&nbsp;years stimulated soil N cycling under piñon trees and modified tree N allocation for both species, resulting in mitigation of hotter drought impacts on tree water and carbon functions. These findings suggest that adjustments in N cycling are likely after multi‐year warming conditions and that such changes may buffer reductions in tree performance during hotter droughts. The results highlight our incomplete understanding of trees' ability to acclimate to climate change, raising fundamental questions about the resistance potential of forests to long‐term, compound climatic stresses. </p>","language":"English","publisher":"Wiley","doi":"10.1111/pce.13389","usgsCitation":"Grossiord, C., Gessler, A., Reed, S.C., Borrego, I., Collins, A.D., Dickman, L.T., Ryan, M., Schonbeck, L., Sevanto, S., Vilagroso, A., and McDowell, N.G., 2018, Reductions in tree performance during hotter droughts are mitigated by shifts in nitrogen cycling: Plant, Cell & Environment, v. 41, no. 11, p. 2627-2637, https://doi.org/10.1111/pce.13389.","productDescription":"11 p.","startPage":"2627","endPage":"2637","ipdsId":"IP-092543","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/pce.13389","text":"Publisher Index Page"},{"id":357146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-16","publicationStatus":"PW","scienceBaseUri":"5b98a264e4b0702d0e842e5a","contributors":{"authors":[{"text":"Grossiord, Charlotte","contributorId":207749,"corporation":false,"usgs":false,"family":"Grossiord","given":"Charlotte","email":"","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":744562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gessler, Arthur","contributorId":199448,"corporation":false,"usgs":false,"family":"Gessler","given":"Arthur","email":"","affiliations":[],"preferred":false,"id":744561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borrego, Isaac","contributorId":207748,"corporation":false,"usgs":false,"family":"Borrego","given":"Isaac","email":"","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":744560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collins, Adam D.","contributorId":199440,"corporation":false,"usgs":false,"family":"Collins","given":"Adam","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":744559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dickman, Lee T.","contributorId":207747,"corporation":false,"usgs":false,"family":"Dickman","given":"Lee","email":"","middleInitial":"T.","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":744558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ryan, Max","contributorId":207746,"corporation":false,"usgs":false,"family":"Ryan","given":"Max","email":"","affiliations":[{"id":37625,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":744557,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schonbeck, Leonie","contributorId":207745,"corporation":false,"usgs":false,"family":"Schonbeck","given":"Leonie","email":"","affiliations":[{"id":37624,"text":"Swiss Federal Research Institute WSL","active":true,"usgs":false}],"preferred":false,"id":744556,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sevanto, Sanna","contributorId":150845,"corporation":false,"usgs":false,"family":"Sevanto","given":"Sanna","email":"","affiliations":[],"preferred":false,"id":744555,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vilagroso, Alberto","contributorId":207744,"corporation":false,"usgs":false,"family":"Vilagroso","given":"Alberto","email":"","affiliations":[{"id":37623,"text":"Fundación CEAM, Joint Research Unit University of Alicante – CEAM","active":true,"usgs":false}],"preferred":false,"id":744554,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McDowell, Nate G.","contributorId":207743,"corporation":false,"usgs":false,"family":"McDowell","given":"Nate","email":"","middleInitial":"G.","affiliations":[{"id":37622,"text":"Earth Systems Science Division, Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":744553,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70199178,"text":"70199178 - 2018 - Biocrusts enhance soil fertility and Bromus tectorum growth, and interact with warming to influence germination","interactions":[],"lastModifiedDate":"2018-09-10T10:05:49","indexId":"70199178","displayToPublicDate":"2018-09-09T20:04:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3089,"text":"Plant and Soil","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Biocrusts enhance soil fertility and <i>Bromus tectorum</i> growth, and interact with warming to influence germination","title":"Biocrusts enhance soil fertility and Bromus tectorum growth, and interact with warming to influence germination","docAbstract":"<p><strong>Background and aims</strong></p><p>Biocrusts are communities of cyanobacteria, mosses, and/or lichens found in drylands worldwide. Biocrusts are proposed to enhance soil fertility and productivity, but simultaneously act as a barrier to the invasive grass, <i>Bromus tectorum</i>, in western North America. Both biocrusts and <i>B. tectorum</i> are sensitive to climate change drivers, yet how their responses might interact to affect dryland ecosystems is unclear.</p><p><strong>Methods</strong></p><p>Using mesocosms with bare soil versus biocrust cover, we germinated <i>B. tectorum</i> seeds collected from warmed, warmed + watered, and ambient temperature plots within a long-term climate change experiment on the Colorado Plateau, USA. We characterized biocrust influences on soil fertility and grass germination, morphology, and chemistry.</p><p><strong>Results</strong></p><p>Biocrusts increased soil fertility and <i>B. tectorum</i> biomass, specific leaf area (SLA), and root:shoot ratios. Germination rates were unaffected by mesocosm cover-type. Biocrusts delayed germination timing while also interacting with the warmed treatment to advance, and with the warmed + watered treatment to delay germination.</p><p><strong>Conclusions</strong></p><p>Biocrusts promoted <i>B. tectorum</i> growth, likely through positive influence on soil fertility which was elevated in biocrust mesocosms, and interacted with seed treatment-provenance to affect germination. Understanding how anticipated losses of biocrusts will affect invasion dynamics will require further investigation of how plant plasticity/adaptation to specific climate drivers interact with soil and biocrust properties.</p>","language":"English","publisher":"Springer","doi":"10.1007/s11104-017-3525-1","usgsCitation":"Ferrenberg, S., Faist, A.M., Howell, A.J., and Reed, S.C., 2018, Biocrusts enhance soil fertility and Bromus tectorum growth, and interact with warming to influence germination: Plant and Soil, v. 429, no. 1-2, p. 77-90, https://doi.org/10.1007/s11104-017-3525-1.","productDescription":"14 p.","startPage":"77","endPage":"90","ipdsId":"IP-092574","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":357145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","volume":"429","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-15","publicationStatus":"PW","scienceBaseUri":"5b98a264e4b0702d0e842e5c","contributors":{"authors":[{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faist, Akasha M.","contributorId":193038,"corporation":false,"usgs":false,"family":"Faist","given":"Akasha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":744565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744563,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199179,"text":"70199179 - 2018 - Long-term evolution of sand transport through a river network: Relative influences of a dam versus natural changes in grain size from sand waves","interactions":[],"lastModifiedDate":"2018-09-20T16:17:27","indexId":"70199179","displayToPublicDate":"2018-09-09T19:59:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5739,"text":"Journal of Geophysical Research: Earth Surface","onlineIssn":"2169-9011","active":true,"publicationSubtype":{"id":10}},"title":"Long-term evolution of sand transport through a river network: Relative influences of a dam versus natural changes in grain size from sand waves","docAbstract":"<p>Temporal and spatial nonuniformity in supplies of water and sand in a river network leads to sand transport that is in local disequilibrium with the upstream sand supply. In such river networks, sand is transported downstream as elongating waves in which coupled changes in grain size and transport occur. Depending on the magnitude of each sand‐supplying event and the interval between such events, changes in bed‐sand grain size associated with sand‐wave passage may more strongly regulate sand transport than do changes in water discharge. When sand transport is controlled more by episodic resupply of sand than by discharge, upstream dam construction may exacerbate or mitigate sand‐transport disequilibria, thus leading to complicated and difficult‐to‐predict patterns of deposition and erosion. We analyzed all historical sediment‐transport data and embarked on a 4‐year program of continuous sediment‐transport measurements to describe disequilibrium sand transport in a river network. Results indicate that sand transport in long river segments can evolve over ≥50‐year timescales following rare large sand‐supplying events. These natural changes in sand transport in distal downstream river segments can be larger than those caused by an upstream dam. Because there is no way to know <i>a priori</i> whether sand transport in a river has changed in response to changes in the upstream sand supply, contemporary continuous measurements of sand transport are required for accurate sand loads and budgeting. Analysis of only historical sediment‐transport measurements, as is common in the literature, may lead to incorrect conclusions with respect to current or future sediment‐transport conditions. </p>","language":"English","publisher":"Americal Geophysical Union","doi":"10.1029/2017JF004534","usgsCitation":"Topping, D.J., Mueller, E., Schmidt, J.C., Griffiths, R.E., Dean, D.J., and Grams, P.E., 2018, Long-term evolution of sand transport through a river network: Relative influences of a dam versus natural changes in grain size from sand waves: Journal of Geophysical Research: Earth Surface, v. 123, no. 8, p. 1879-1909, https://doi.org/10.1029/2017JF004534.","productDescription":"31 p.","startPage":"1879","endPage":"1909","ipdsId":"IP-085261","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468424,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jf004534","text":"Publisher Index Page"},{"id":357144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-20","publicationStatus":"PW","scienceBaseUri":"5b98a264e4b0702d0e842e5e","contributors":{"authors":[{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":140985,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mueller, Erich R. 0000-0001-8202-154X","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":207750,"corporation":false,"usgs":false,"family":"Mueller","given":"Erich R.","affiliations":[{"id":37626,"text":"Department of Geography, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":744568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, John C.","contributorId":207751,"corporation":false,"usgs":false,"family":"Schmidt","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":37627,"text":"Department of Watershed Sciences, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":744569,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffiths, Ronald E. 0000-0003-3620-2926 rgriffiths@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-2926","contributorId":162,"corporation":false,"usgs":true,"family":"Griffiths","given":"Ronald","email":"rgriffiths@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dean, David J. 0000-0003-0203-088X djdean@usgs.gov","orcid":"https://orcid.org/0000-0003-0203-088X","contributorId":131047,"corporation":false,"usgs":true,"family":"Dean","given":"David","email":"djdean@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744573,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70199150,"text":"70199150 - 2018 - KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 1: measurements, pressure dependence and pore-fluid effects","interactions":[],"lastModifiedDate":"2018-09-07T16:06:00","indexId":"70199150","displayToPublicDate":"2018-09-07T16:05:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 1: measurements, pressure dependence and pore-fluid effects","docAbstract":"<p><span>Measuring the permeability of tight rocks remains a challenging task. In addition to the traditional sources of errors that affect more permeable formations (e.g. sample selection, non-representative specimens, disturbance introduced during sample acquisition and preparation), tight rocks can be particularly prone to solid–fluid interactions and thus more sensitive to the methods, procedures and techniques used to measure permeability. To address this problem, it is desirable to collect, for a single material, measurements obtained by different methods and pore-fluids. For that purpose a collaborative benchmarking exercise involving 24 laboratories was organized for measuring the permeability of a single low permeability material, the Grimsel granodiorite, at a common effective confining pressure (5&nbsp;MPa). The objectives of the benchmark were: (i) to compare the results for a given method, (ii) to compare the results between different methods, (iii) to analyze the accuracy of each method, (iv) to study the influence of experimental conditions (especially the nature of pore fluid), (v) to discuss the relevance of indirect methods and models and finally (vi) to suggest good practice for low permeability measurements. In total 39 measurements were collected that allowed us to discuss the influence of (i) pore-fluid, (ii) measurement method, (iii) sample size and (iv) pressure sensitivity. Discarding some outliers from the bulk data set (4 out of 39) an average permeability of 1.11&nbsp;×&nbsp;10</span><sup>−18</sup><span>&nbsp;m² with a standard deviation of 0.57&nbsp;×&nbsp;10</span><sup>−18</sup><span>&nbsp;m² was obtained. The most striking result was the large difference in permeability for gas measurements compared to liquid measurements. Regardless of the method used, gas permeability was higher than liquid permeability by a factor approximately 2 (</span><i>k</i><sub>gas&nbsp;</sub><span>=&nbsp;1.28&nbsp;×&nbsp;10</span><sup>−18</sup><span>&nbsp;m² compared to&nbsp;</span><i>k</i><sub>liquid&nbsp;</sub><span>=&nbsp;0.65&nbsp;×&nbsp;10</span><sup>−18</sup><span>&nbsp;m²). Possible explanations are that (i) liquid permeability was underestimated due to fluid-rock interactions (ii) gas permeability was overestimated due to insufficient correction for gas slippage and/or (iii) gases and liquids do not probe exactly the same porous networks. The analysis of Knudsen numbers shows that the gas permeability measurements were performed in conditions for which the Klinkenberg correction is sufficient. Smaller samples had a larger scatter of permeability values, suggesting that their volume were below the Representative Elementary Volume. The pressure dependence of permeability was studied by some of the participating teams in the range 1–30&nbsp;MPa and could be fitted to an exponential law&nbsp;</span><i>k&nbsp;</i><span>=&nbsp;</span><i>k<sub>o</sub></i><span>.exp(–</span><i>γP</i><sub>eff</sub><span>) with&nbsp;</span><i>γ</i><span>&nbsp;=&nbsp;0.093 MPa</span><sup>−1</sup><span>. Good practice rules for measuring permeability in tight materials are also provided.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggy304","usgsCitation":"David, C., Wasserman, J., Amann, F., Lockner, D.A., Rutter, E., Vanorio, T., Amann Hildenbrand, A., Billiotte, J., Reuschle, T., Lasseux, D., Fortin, J., Lenormand, R., Selvadurai, A., Meredith, P., Browning, J., Mitchell, T., Loggia, D., Nono, F., Sarout, J., Esteban, L., Davy, C., Louis, L., Boitnott, G., Madonna, C., Jahns, E., M., F., Berthe, G., Delage, P., Braun, P., Gregoire, D., Perrier, L., Polito, P., Jannot, Y., Sommier, A., Krooss, B., Fink, R., Hu, Q., Klaver, J., and Clark, A., 2018, KG²B, a collaborative benchmarking exercise for estimating the permeability of the Grimsel granodiorite - Part 1: measurements, pressure dependence and pore-fluid effects: Geophysical Journal International, v. 215, no. 2, p. 799-824, https://doi.org/10.1093/gji/ggy304.","productDescription":"26 p.","startPage":"799","endPage":"824","ipdsId":"IP-093306","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468425,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1093/gji/ggy304","text":"External Repository"},{"id":357133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"215","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-25","publicationStatus":"PW","scienceBaseUri":"5b98a265e4b0702d0e842e62","contributors":{"authors":[{"text":"David, Christian","contributorId":207604,"corporation":false,"usgs":false,"family":"David","given":"Christian","email":"","affiliations":[{"id":37570,"text":"Université de Cergy-Pontoise, Laboratoire GEC, Cergy-Pontoise, 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,{"id":70199260,"text":"70199260 - 2018 - Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions","interactions":[],"lastModifiedDate":"2022-04-22T16:59:01.163613","indexId":"70199260","displayToPublicDate":"2018-09-07T16:03:54","publicationYear":"2018","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":"Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions","docAbstract":"<p><span>Long-term, interdisciplinary studies of relations between climate and ecological conditions on wetland-upland landscapes have been lacking, especially studies integrated across scales meaningful for adaptive resource management. We collected data&nbsp;</span><i>in situ</i><span>&nbsp;at individual wetlands, and via satellite for surrounding 4-km</span><sup>2</sup><span>&nbsp;landscape blocks, to assess relations between annual weather dynamics, snow duration, phenology, wetland surface-water availability, amphibian presence and calling activity, greenness, and evapotranspiration in four U.S. conservation areas from 2008 to 2012. Amid recent decades of relatively warm growing seasons, 2012 and 2010 were the first and second warmest seasons, respectively, dating back to 1895. Accordingly, we observed the earliest starts of springtime biological activity during those two years. In all years, early-season amphibians first called soon after daily mean air temperatures were ≥ 0°C and snow had mostly melted. Similarly, satellite-based indicators suggested seasonal leaf-out happened soon after snowmelt and temperature thresholds for plant growth had occurred. Daily fluctuations in weather and water levels were related to amphibian calling activity, including decoupling the timing of the onset of calling at the start of season from the onset of calling events later in the season. Within-season variation in temperature and precipitation also was related to vegetation greenness and evapotranspiration, but more at monthly and seasonal scales. Wetland water levels were moderately to strongly associated with precipitation and early or intermittent wetland drying likely reduced amphibian reproduction success in some years, even though&nbsp;</span><i>Pseudacris crucifer</i><span>&nbsp;occupied sites at consistently high levels. Notably, satellite-based indicators of landscape water availability did not suggest such consequential, intra-seasonal variability in wetland surface-water availability. Our cross-disciplinary data show how temperature and precipitation interacted to affect key ecological relations and outcomes on our study landscapes. These results demonstrate the value of multi-year studies and the importance of scale for understanding actual climate-related effects in these areas.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0201951","usgsCitation":"Sadinski, W., Gallant, A.L., Roth, M., Brown, J.F., Senay, G., Brininger, W.L., Jones, P.M., and Stoker, J.M., 2018, Multi-year data from satellite- and ground-based sensors show details and scale matter in assessing climate’s effects on wetland surface water, amphibians, and landscape conditions: PLoS ONE, v. 13, no. 9, e0201951, 50 p., https://doi.org/10.1371/journal.pone.0201951.","productDescription":"e0201951, 50 p.","ipdsId":"IP-089216","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468426,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70199169,"text":"70199169 - 2018 - Spring temperature, migration chronology, and nutrient allocation to eggs in three species of arctic‐nesting geese: Implications for resilience to climate warming","interactions":[],"lastModifiedDate":"2018-10-23T16:53:49","indexId":"70199169","displayToPublicDate":"2018-09-07T15:51:54","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Spring temperature, migration chronology, and nutrient allocation to eggs in three species of arctic‐nesting geese: Implications for resilience to climate warming","docAbstract":"<p><span>The macronutrients that Arctic herbivores invest in their offspring are derived from endogenous reserves of fat and protein (capital) that females build prior to the period of investment or from foods they consume concurrently with investment (income). The relative contribution from each source can be influenced by temporal and environmental constraints on a female's ability to forage on Arctic breeding areas. Warming temperatures and advancing Arctic phenology may alter those constraints. From 2011–2014, we examined relationships among spring temperature, timing of migration and reproduction, and the sources of nutrients females deposited in eggs for three sympatric species of geese that nested in northern Alaska. Compared to lesser snow geese (</span><i>Anser caerulescens caerulescens</i><span>) and greater white‐fronted geese (</span><i>Anser albifrons frontalis</i><span>), black brant (</span><i>Branta bernicla nigricans</i><span>) were more likely to initiate follicle development during migration, resulting in fewer days between their arrival in the Arctic and the onset of incubation, and requiring a relatively greater capital investment in eggs. Delaying follicle development until after their arrival in the Arctic provided snow geese and white‐fronted geese an opportunity to forage near their nesting area and to deposit exogenous nutrients in eggs. With warmer spring temperatures brant invested more capital in eggs but snow geese invested less capital. Brant likely used capital to meet costs associated with earlier onset of follicle development when phenology was advanced, whereas snow geese used capital to compensate for poor foraging conditions during colder Arctic springs. Global warming is likely to reduce the quality of lower‐latitude marine habitats where brant acquire endogenous reserves, and advancing Arctic phenology may increase their reliance on those reserves during reproduction. Near‐term warming in northern Alaska may improve foraging conditions and favor the reproductive strategies of some herbivores such as snow geese and white‐fronted geese that mainly invest Arctic nutrients in their offspring.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14418","usgsCitation":"Hupp, J.W., Ward, D.H., Soto, D.X., and Hobson, K.A., 2018, Spring temperature, migration chronology, and nutrient allocation to eggs in three species of arctic‐nesting geese: Implications for resilience to climate warming: Global Change Biology, v. 24, no. 11, p. 5056-5071, https://doi.org/10.1111/gcb.14418.","productDescription":"16 p.","startPage":"5056","endPage":"5071","ipdsId":"IP-093873","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437764,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76M3643","text":"USGS data release","linkHelpText":"Goose Migration and Egg Nutrient Allocation, Colville River Delta, Alaska, 2011-2015"},{"id":357130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-23","publicationStatus":"PW","scienceBaseUri":"5b98a265e4b0702d0e842e64","contributors":{"authors":[{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":744505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":744506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soto, David X.","contributorId":207729,"corporation":false,"usgs":false,"family":"Soto","given":"David","email":"","middleInitial":"X.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":744507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hobson, Keith A.","contributorId":207730,"corporation":false,"usgs":false,"family":"Hobson","given":"Keith","email":"","middleInitial":"A.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":744508,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199170,"text":"70199170 - 2018 - Genetic evidence supports sporadic and independent introductions of subtype H5 low pathogenic avian influenza A viruses from wild birds to domestic poultry in North America","interactions":[],"lastModifiedDate":"2019-03-26T16:20:45","indexId":"70199170","displayToPublicDate":"2018-09-07T15:49:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2497,"text":"Journal of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Genetic evidence supports sporadic and independent introductions of subtype H5 low pathogenic avian influenza A viruses from wild birds to domestic poultry in North America","docAbstract":"<p><span>Wild bird–origin influenza A viruses (IAVs or avian influenza) have led to sporadic outbreaks among domestic poultry in the United States (US) and Canada, resulting in economic losses through the implementation of costly containment practices and destruction of birds. We used evolutionary analyses of virus sequence data to determine that 78 H5 low pathogenic avian influenza viruses (LPAIVs) isolated from domestic poultry in the US and Canada during 2001–2017 resulted from 18 independent virus introductions from wild birds. Within the wild bird reservoir, the hemagglutinin gene segments of H5 LPAIVs exist primarily as two co-circulating genetic sublineages, and our findings suggest the H5 gene segments flow within each migratory bird flyway and among adjacent flyways, with limited exchange between the non-adjacent Atlantic and Pacific Flyways. Phylogeographic analyses provided evidence that IAVs from dabbling ducks and swans/geese contributed to emergence of viruses among domestic poultry. H5 LPAIVs isolated from commercial farm poultry (i.e. turkey) were descended from a single introduction typically remain a single genotype, whereas those from live bird markets sometimes led to multiple genotypes, reflecting the potential for reassortment with other IAVs circulating within live bird markets. H5 LPAIV introduced from wild birds to domestic poultry represent economic threats to the U.S. poultry industry, and our data suggest that such introductions have been sporadic, controlled effectively through production monitoring and a stamping-out policy, and are, therefore, unlikely to result in sustained detections in commercial poultry operations.</span></p>","language":"English","publisher":"American Society of Microbiology","doi":"10.1128/JVI.00913-18","usgsCitation":"Li, L., Bowman, A.S., DeLiberto, T., Killian, M.L., Krauss, S., Nolting, J.M., Torchetti, M.K., Ramey, A.M., Reeves, A.B., Stallknecht, D.E., Webby, R.J., and Wan, X., 2018, Genetic evidence supports sporadic and independent introductions of subtype H5 low pathogenic avian influenza A viruses from wild birds to domestic poultry in North America: Journal of Virology, v. 92, no. 19, p. 1-16, https://doi.org/10.1128/JVI.00913-18.","productDescription":"e00913-18; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-096036","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468427,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/jvi.00913-18","text":"Publisher Index Page"},{"id":357129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"19","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a265e4b0702d0e842e66","contributors":{"authors":[{"text":"Li, Lei","contributorId":207731,"corporation":false,"usgs":false,"family":"Li","given":"Lei","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":744511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowman, Andrew S.","contributorId":190853,"corporation":false,"usgs":false,"family":"Bowman","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":744512,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLiberto, Thomas J.","contributorId":139362,"corporation":false,"usgs":false,"family":"DeLiberto","given":"Thomas J.","affiliations":[{"id":12749,"text":"USDA APHIS National Wildlife Research Center, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":744513,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Killian, Mary L.","contributorId":29685,"corporation":false,"usgs":false,"family":"Killian","given":"Mary","email":"","middleInitial":"L.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":744514,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Scott","contributorId":190854,"corporation":false,"usgs":false,"family":"Krauss","given":"Scott","email":"","affiliations":[],"preferred":false,"id":744515,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nolting, Jacqueline M.","contributorId":190855,"corporation":false,"usgs":false,"family":"Nolting","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":744516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Torchetti, Mia Kim","contributorId":190856,"corporation":false,"usgs":false,"family":"Torchetti","given":"Mia","email":"","middleInitial":"Kim","affiliations":[],"preferred":false,"id":744517,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":744509,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":744510,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stallknecht, David E.","contributorId":14323,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":744518,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Webby, Richard J.","contributorId":190857,"corporation":false,"usgs":false,"family":"Webby","given":"Richard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":744519,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wan, Xiu-Feng","contributorId":173959,"corporation":false,"usgs":false,"family":"Wan","given":"Xiu-Feng","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":744520,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70199171,"text":"70199171 - 2018 - Introduction of Eurasian-origin H8N4 influenza A virus into North America via migratory birds","interactions":[],"lastModifiedDate":"2018-09-20T16:19:13","indexId":"70199171","displayToPublicDate":"2018-09-07T15:45:23","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1493,"text":"Emerging Infectious Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Introduction of Eurasian-origin H8N4 influenza A virus into North America via migratory birds","docAbstract":"<p><span>We identified a Eurasian-origin influenza A(H8N4) virus in North America by sampling wild birds in western Alaska, USA. Evidence for repeated introductions of influenza A viruses into North America by migratory birds suggests that intercontinental dispersal might not be exceedingly rare and that our understanding of viral establishment is incomplete.</span></p>","language":"English","publisher":"CDC","doi":"10.3201/eid2410.180447","usgsCitation":"Ramey, A.M., Reeves, A.B., Donnelly, T.F., Poulson, R., and Stallknecht, D.E., 2018, Introduction of Eurasian-origin H8N4 influenza A virus into North America via migratory birds: Emerging Infectious Diseases, v. 24, no. 10, p. 1950-1953, https://doi.org/10.3201/eid2410.180447.","productDescription":"4 p.","startPage":"1950","endPage":"1953","ipdsId":"IP-096179","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":468428,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid2410.180447","text":"Publisher Index Page"},{"id":357128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a266e4b0702d0e842e68","contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":744521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":744522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donnelly, Tyrone F. tfdonnelly@usgs.gov","contributorId":4369,"corporation":false,"usgs":true,"family":"Donnelly","given":"Tyrone","email":"tfdonnelly@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":744523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":744524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stallknecht, David E.","contributorId":14323,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":744525,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70201103,"text":"70201103 - 2018 - Impacts of tidal road-stream crossings on aquatic organism passage","interactions":[],"lastModifiedDate":"2018-11-29T15:11:27","indexId":"70201103","displayToPublicDate":"2018-09-07T15:11:21","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"131-2018","title":"Impacts of tidal road-stream crossings on aquatic organism passage","docAbstract":"<p><span>ivers and streams are highly vulnerable to fragmentation from roads due to their prevalence in the landscape. Road-stream crossings are far more numerous than other anthropogenic barriers such as dams; these crossing structures (culverts, bridges, fords, and tide gates) have been demonstrated to impede the passage of aquatic organisms. However, road-stream crossings vary widely in the extent to which they serve as a barrier. It is important to identify barrier severity to facilitate prioritization of restoration activities, since proactively addressing all structures is not feasible. In 2015 the North Atlantic Landscape Conservation Collaborative (LCC) funded a project managed by the North Atlantic Aquatic Connectivity Cooperative (NAACC) to develop a unified protocol for assessing aquatic road-stream crossings focusing on aquatic connectivity. The NAACC relied on rapid field-based assessments, which have been shown to be a useful tool for gathering information necessary for prioritization. However, the rapid assessment protocol developed from the NAACC initiative is not applicable to tidal crossings as it does not address two-directional flow, daily water depth fluctuations, or many of the species likely present in coastal habitats.</span></p><p><span>The goal of this report is to provide the background necessary to create guidelines and rapid assessment tools for assessing risk posed to aquatic organism passage at tidal crossings. To accomplish these goals, this report identifies species present in tidally influenced coastal wetlands, the unique traits they may display that puts them at risk for detrimental impact from impeded passage, and passage threats unique to tidal crossings that are not addressed by protocols designed for non-tidal systems. Species lists were compiled through literature reviews and discussions with regional researchers and managers familiar with coastal ecosystems or fish passage concerns. Life history traits, environmental sensitivities, and movement patterns for each species were compiled to build a database that can be queried to identify species that are highly vulnerable to impeded passage at tidal crossings (Available at: <a rel=\"noopener\" href=\"https://umass.box.com/s/w5mhokxjxshyxmr7si2v0gzcypcitu9d\" target=\"_blank\" data-metrics-event-name=\"event\" data-metrics-merge-pagedefaults=\"true\" data-metrics-event-category=\"metadata\" data-metrics-event-action=\"click\" data-metrics-event-label=\"link:https://umass.box.com/s/w5mhokxjxshyxmr7si2v0gzcypcitu9d\" data-mce-href=\"https://umass.box.com/s/w5mhokxjxshyxmr7si2v0gzcypcitu9d\">https://umass.box.com/s/w5mhokxjxshyxmr7si2v0gzcypcitu9d</a>). These risk factors for species, combined with passage threats associated with specific crossing characteristics are discussed in this report. The species list is thorough enough to provide a baseline summary of the types of threats experienced by aquatic organisms at tidal road-stream crossings, but it is not exhaustive. Unique ecosystems, species assemblages, management goals, and prioritization models may require different approaches and solutions. Thus, care must be taken to ensure that assessment tools are appropriate to a project’s target species, habitats, and scale.</span></p>","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Becker, S., Jackson, S., Jordaan, A., and Roy, A.H., 2018, Impacts of tidal road-stream crossings on aquatic organism passage: Cooperator Science Series 131-2018, ii, 57 p.","productDescription":"ii, 57 p.","ipdsId":"IP-090405","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":359809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":359808,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/digital/collection/document/id/2238/"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c0108d5e4b0815414cc2dfd","contributors":{"authors":[{"text":"Becker, Sarah","contributorId":210890,"corporation":false,"usgs":false,"family":"Becker","given":"Sarah","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":752685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, Scott","contributorId":210891,"corporation":false,"usgs":false,"family":"Jackson","given":"Scott","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":752686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jordaan, Adrian","contributorId":210892,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":752687,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":752684,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70199160,"text":"70199160 - 2018 - Spatially explicit patterns in a dryland's soil respiration and relationships with climate, whole plant photosynthesis and soil fertility","interactions":[],"lastModifiedDate":"2018-09-07T13:53:51","indexId":"70199160","displayToPublicDate":"2018-09-07T13:53:47","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit patterns in a dryland's soil respiration and relationships with climate, whole plant photosynthesis and soil fertility","docAbstract":"<p><span>Arid and semiarid ecosystems play a significant role in regulating global carbon cycling, yet our understanding of the controls over the dominant pathways of dryland CO</span><sub>2</sub><span>exchange remains poor. Substantial amounts of dryland soil are not covered by vascular plants and this patchiness in cover has important implications for spatial patterns and controls of carbon cycling. Spatial variation in soil respiration has been attributed to variation in soil moisture, temperature, nutrients and rhizodeposition, while seasonal patterns have been attributed to changes in moisture, temperature and photosynthetic inputs belowground. To characterize how controls over respiration vary spatially and temporally in a dryland ecosystem and to concurrently explore multiple potential controls, we estimated whole plant net photosynthesis (A</span><sub>net</sub><span>) and soil respiration at four distances from the plant base, as well as corresponding fine root biomass and soil carbon and nitrogen pools, four times during a growing season. To determine if the controls vary between different plant functional types for Colorado Plateau species, measurements were made on the C</span><sub>4</sub><span>&nbsp;shrub,&nbsp;</span><i>Atriplex confertifolia</i><span>, and C</span><sub>3</sub><span>&nbsp;grass,&nbsp;</span><i>Achnatherum hymenoides</i><span>. Soil respiration declined throughout the growing season and diminished with distance from the plant base, though variations in both were much smaller than expected. The strongest relationship was between soil respiration and soil moisture. Soil respiration was correlated with whole plant A</span><sub>net</sub><span>, although the relationship varied between species and distance from plant base. In the especially dry year of this study we did not observe any consistent correlations between soil respiration and soil carbon or nitrogen pools. Our findings suggest that abiotic factors, especially soil moisture, strongly regulate the response of soil respiration to biotic factors and soil carbon and nitrogen pools in dryland communities and, at least in dry years, may override expected spatial and seasonal patterns.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/oik.04935","usgsCitation":"Wertin, T.M., Young, K.E., and Reed, S.C., 2018, Spatially explicit patterns in a dryland's soil respiration and relationships with climate, whole plant photosynthesis and soil fertility: Oikos, v. 127, no. 9, p. 1280-1290, https://doi.org/10.1111/oik.04935.","productDescription":"11 p.","startPage":"1280","endPage":"1290","ipdsId":"IP-096157","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":357119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-17","publicationStatus":"PW","scienceBaseUri":"5b98a266e4b0702d0e842e6a","contributors":{"authors":[{"text":"Wertin, Timothy M.","contributorId":207719,"corporation":false,"usgs":false,"family":"Wertin","given":"Timothy","email":"","middleInitial":"M.","affiliations":[{"id":37615,"text":"Carl R. Woese Institute for Genomic Biology, University of Illinois","active":true,"usgs":false}],"preferred":false,"id":744483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Kristina E. kyoung@usgs.gov","contributorId":5842,"corporation":false,"usgs":true,"family":"Young","given":"Kristina","email":"kyoung@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":744484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":744482,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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