{"pageNumber":"1010","pageRowStart":"25225","pageSize":"25","recordCount":184689,"records":[{"id":70191882,"text":"70191882 - 2017 - Vulnerabilities to climate change of Massachusetts animal species of greatest conservation need","interactions":[],"lastModifiedDate":"2020-07-27T19:00:31.426756","indexId":"70191882","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Vulnerabilities to climate change of Massachusetts animal species of greatest conservation need","docAbstract":"<p>Over the last decade, the Commonwealth of Massachusetts has addressed the potential and actual impacts of climate change on state flora and fauna. The state’s involvement began in 2007 when, led by the Division of Fisheries and Wildlife (DFW) and assisted by Manomet Center for Con-servation Research, it carried out one of the first habitat vulnerability assessments in North America (Manomet, 2010). The new methods and processes that resulted were later applied to vulnerability assessments in North America and elsewhere. In 2011, the state assisted the North-eastern Association of Fish and Wildlife Agencies (NEAFWA) in organizing and leading a pio-neering three-year, thirteen-state research effort to evaluate the vulnerabilities of fish and wild-life habitats to climate change in the northeast, from Maine south to West Virginia (NEAFWA, 2012).&nbsp;</p><p>This focus on climate change vulnerabilities led to three important early realizations: (1) simply categorizing and scoring vulnerabilities might not lead to better conservation outcomes. It was vital to also understand why some resources were more or less vulnerable to climate change in order to identify potential intervention points on which conservation actions and strategies could be based. (2) simply producing research results was not enough; these results had to be cast as specific conservation actions. Moreover (3), these actions needed to be communicated in a useful form to conservation “actors”, such as state agencies, land trusts, land managers, etc. These real-izations led to the next step on the Commonwealth’s journey to effective conservation in an age of climate change - the Massachusetts Wildlife Climate Action Tool (CAT).</p>","language":"English","publisher":"Massachusetts Department of Fish and Wildlife","usgsCitation":"Galbraith, H., and Morelli, T.L., 2017, Vulnerabilities to climate change of Massachusetts animal species of greatest conservation need, 19 p.","productDescription":"19 p.","ipdsId":"IP-079595","costCenters":[{"id":41705,"text":"Northeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":352202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346877,"type":{"id":15,"text":"Index Page"},"url":"https://necsc.umass.edu/biblio/vulnerabilities-climate-change-massachusetts-animal-species-greatest-conservation-need"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8c4e4b0da30c1bfc4a2","contributors":{"authors":[{"text":"Galbraith, Hector","contributorId":197459,"corporation":false,"usgs":false,"family":"Galbraith","given":"Hector","email":"","affiliations":[],"preferred":false,"id":713532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morelli, Toni L. 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":189143,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":713531,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193066,"text":"70193066 - 2017 - Extended late Holocene relative sea-level histories for North Carolina, USA","interactions":[],"lastModifiedDate":"2017-11-12T11:04:29","indexId":"70193066","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Extended late Holocene relative sea-level histories for North Carolina, USA","docAbstract":"<p>We produced ∼3000-year long relative sea-level (RSL) histories for two sites in North Carolina (USA) using foraminifera preserved in new and existing cores of dated salt-marsh sediment. At Cedar Island, RSL rose by ∼2.4&nbsp;m during the past ∼3000 years compared to ∼3.3&nbsp;m&nbsp;at Roanoke Island. This spatial difference arises primarily from differential GIA that caused late Holocene RSL rise to be 0.1–0.2&nbsp;mm/yr faster at Roanoke Island than at Cedar Island. However, a non-linear difference in RSL between the two study regions (particularly from ∼0 CE to ∼1250 CE) indicates that additional local- to regional-scale processes drove centennial-scale RSL change in North Carolina. Therefore, the Cedar Island and Roanoke Island records should be considered as independent of one another. Between-site differences on sub-millennial timescales cannot be adequately explained by non-stationary tides, sediment compaction, or local sediment dynamics. We propose that a period of accelerating RSL rise from ∼600 CE to 1100 CE that is present at Roanoke Island (and other sites north of Cape Hatteras at least as far as Connecticut), but absent at Cedar Island (and other sites south of Cape Hatteras at least as far as northeastern Florida) is a local-to regional-scale effect of dynamic ocean and/or atmospheric circulation.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2017.01.012","usgsCitation":"Kemp, A.C., Kegel, J.J., Culver, S.J., Barber, D.C., Mallinson, D.J., Leorri, E., Bernhardt, C.E., Cahill, N., Riggs, S.R., Woodson, A.L., Mulligan, R.P., and Horton, B.P., 2017, Extended late Holocene relative sea-level histories for North Carolina, USA: Quaternary Science Reviews, v. 160, p. 13-30, https://doi.org/10.1016/j.quascirev.2017.01.012.","productDescription":"18 p.","startPage":"13","endPage":"30","ipdsId":"IP-082692","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":470102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2017.01.012","text":"Publisher Index Page"},{"id":348618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cedar Island, Roanoke Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.41540527343749,\n              34.914088616906106\n            ],\n            [\n              -76.2454605102539,\n              34.914088616906106\n            ],\n            [\n              -76.2454605102539,\n              35.03449433167976\n            ],\n            [\n              -76.41540527343749,\n              35.03449433167976\n            ],\n            [\n              -76.41540527343749,\n              34.914088616906106\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.74592590332031,\n              35.801943102768846\n            ],\n            [\n              -75.59761047363281,\n              35.801943102768846\n            ],\n            [\n              -75.59761047363281,\n              35.94688293218141\n            ],\n            [\n              -75.74592590332031,\n              35.94688293218141\n            ],\n            [\n              -75.74592590332031,\n              35.801943102768846\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"160","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a096bb1e4b09af898c94147","contributors":{"authors":[{"text":"Kemp, Andrew C.","contributorId":192892,"corporation":false,"usgs":false,"family":"Kemp","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":717794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kegel, Jessica J.","contributorId":198983,"corporation":false,"usgs":false,"family":"Kegel","given":"Jessica","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Culver, Stephen J.","contributorId":198984,"corporation":false,"usgs":false,"family":"Culver","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Donald C.","contributorId":198985,"corporation":false,"usgs":false,"family":"Barber","given":"Donald","email":"","middleInitial":"C.","affiliations":[{"id":6651,"text":"Bryn Mawr College, Bryn Mawr, PA","active":true,"usgs":false}],"preferred":false,"id":717797,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mallinson, David J.","contributorId":198986,"corporation":false,"usgs":false,"family":"Mallinson","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717798,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leorri, Eduardo","contributorId":198987,"corporation":false,"usgs":false,"family":"Leorri","given":"Eduardo","email":"","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717799,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":717793,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cahill, Niamh","contributorId":150754,"corporation":false,"usgs":false,"family":"Cahill","given":"Niamh","email":"","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":717800,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Riggs, Stanley R.","contributorId":198988,"corporation":false,"usgs":false,"family":"Riggs","given":"Stanley","email":"","middleInitial":"R.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false}],"preferred":false,"id":717801,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Woodson, Anna L.","contributorId":198989,"corporation":false,"usgs":false,"family":"Woodson","given":"Anna","email":"","middleInitial":"L.","affiliations":[{"id":27911,"text":"East Carolina University Greenville, North Carolina,USA","active":true,"usgs":false},{"id":6651,"text":"Bryn Mawr College, Bryn Mawr, PA","active":true,"usgs":false}],"preferred":false,"id":717802,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":721687,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Horton, Benjamin P.","contributorId":192807,"corporation":false,"usgs":false,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false},{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":721688,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70190562,"text":"70190562 - 2017 - Mallard (Anas platyrhynchos) mortality and recovery rates vary by wing molt status at time of banding","interactions":[],"lastModifiedDate":"2017-09-07T12:30:00","indexId":"70190562","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Mallard (<i>Anas platyrhynchos</i>) mortality and recovery rates vary by wing molt status at time of banding","title":"Mallard (Anas platyrhynchos) mortality and recovery rates vary by wing molt status at time of banding","docAbstract":"<p><span>Recovery (i.e., shot, retrieved, and reported) rates and daily mortality risk of 52,330 adult Mallards (</span><i>Anas platyrhynchos</i><span>) leg-banded during pre-molt, in-molt, or post-molt during 1985–2011 were evaluated to better understand mortality during wing molt in dynamics of the Mallard population in California, USA. Recovery rates and non-hunting mortality risk varied by molt status at time of banding and California region where banded. Mallards banded during post-molt were 1.22 (95% credible interval = 1.10–1.32) times more likely to be recovered than Mallards banded pre-molt; recovery probability was similar for pre-molt and in-molt Mallards. Mallards banded post-molt had 0.43 (0.17–0.98) and in-molt 0.87 (0.51–1.49) times the daily risk of non-hunting mortality as Mallards banded pre-molt. Mallards were 0.92 (0.86–0.98) times as likely to be recovered, and daily risk of non-hunting mortality was 2.93 (1.79–4.94) times greater, if banded in Northeastern California than in California's Central Valley. Results indicate that high mortality during the molt period, especially in Northeastern California where most Mallards that breed in California molt, might be negatively affecting recovery (and potentially annual survival) of Mallards in California. Thus, conservation programs that reduce mortality during molt could help attain the desired population size for Mallards nesting in California.</span></p>","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.040.0105","usgsCitation":"Fleskes, J., Halstead, B., Kohl, J.D., and Yarris, G., 2017, Mallard (Anas platyrhynchos) mortality and recovery rates vary by wing molt status at time of banding: Waterbirds, v. 40, no. 1, p. 33-40, https://doi.org/10.1675/063.040.0105.","productDescription":"8 p.","startPage":"33","endPage":"40","ipdsId":"IP-073692","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":345547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"40","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b25b00e4b020cdf7db1fbf","contributors":{"authors":[{"text":"Fleskes, Joseph P. joe_fleskes@usgs.gov","contributorId":138999,"corporation":false,"usgs":true,"family":"Fleskes","given":"Joseph P.","email":"joe_fleskes@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":709816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kohl, Jeffrey D.","contributorId":79773,"corporation":false,"usgs":true,"family":"Kohl","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":709817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yarris, Gregory S.","contributorId":115361,"corporation":false,"usgs":true,"family":"Yarris","given":"Gregory S.","affiliations":[],"preferred":false,"id":709818,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70187613,"text":"70187613 - 2017 - Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence","interactions":[],"lastModifiedDate":"2019-12-17T09:32:50","indexId":"70187613","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence","docAbstract":"<p><span>The seismic spectrum can be constructed by assuming a Brune spectral model and estimating the parameters of seismic moment (</span><i class=\"EmphasisTypeItalic \">M</i><sub>0</sub><span>), corner frequency (</span><i class=\"EmphasisTypeItalic \">f</i><sub>c</sub><span>), and high-frequency site attenuation (</span><i class=\"EmphasisTypeItalic \">κ</i><span>). Using seismic data collected during the 2010–2011 Canterbury, New Zealand, earthquake sequence, we apply the non-linear least-squares Gauss–Newton method, a deterministic downhill optimization technique, to simultaneously determine the </span><i class=\"EmphasisTypeItalic \">M</i><sub>0</sub><span>, </span><i class=\"EmphasisTypeItalic \">f</i><sub>c</sub><span>, and </span><i class=\"EmphasisTypeItalic \">κ</i><span> for each event-station pair. We fit the Brune spectral acceleration model to Fourier-transformed S-wave records following application of path and site corrections to the data. For each event, we solve for a single </span><i class=\"EmphasisTypeItalic \">M</i><sub>0</sub><span> and </span><i class=\"EmphasisTypeItalic \">f</i><sub>c</sub><span>, while any remaining residual kappa, </span><span id=\"IEq1\" class=\"InlineEquation\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub><mi>&amp;#x03BA;</mi><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mtext>r</mtext></mrow></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msubsup\"><span><span><span id=\"MathJax-Span-4\" class=\"mi\">κ</span></span><span><span id=\"MathJax-Span-5\" class=\"texatom\"><span id=\"MathJax-Span-6\" class=\"mrow\"><span id=\"MathJax-Span-7\" class=\"mtext\">r</span></span></span></span></span></span></span></span></span></span><span class=\"MJX_Assistive_MathML\">κr</span></span></span><span>, is allowed to differ per station record to reflect varying high-frequency falloff due to path and site attenuation. We use a parametric forward modeling method, calculating initial </span><i class=\"EmphasisTypeItalic \">M</i><sub>0</sub><span> and </span><i class=\"EmphasisTypeItalic \">f</i><sub>c</sub><span> values from the local GNS New Zealand catalog </span><i class=\"EmphasisTypeItalic \">M</i><sub>w, GNS</sub><span> magnitudes and measuring an initial </span><span id=\"IEq2\" class=\"InlineEquation\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub><mi>&amp;#x03BA;</mi><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mtext>r</mtext></mrow></msub></math>\"><span id=\"MathJax-Span-8\" class=\"math\"><span><span><span id=\"MathJax-Span-9\" class=\"mrow\"><span id=\"MathJax-Span-10\" class=\"msubsup\"><span><span><span id=\"MathJax-Span-11\" class=\"mi\">κ</span></span><span><span id=\"MathJax-Span-12\" class=\"texatom\"><span id=\"MathJax-Span-13\" class=\"mrow\"><span id=\"MathJax-Span-14\" class=\"mtext\">r</span></span></span></span></span></span></span></span></span></span><span class=\"MJX_Assistive_MathML\">κr</span></span></span><span> using an automated high-frequency linear regression method. Final solutions for </span><i class=\"EmphasisTypeItalic \">M</i><sub>0</sub><span>, </span><i class=\"EmphasisTypeItalic \">f</i><sub>c</sub><span>, and </span><span id=\"IEq3\" class=\"InlineEquation\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub><mi>&amp;#x03BA;</mi><mrow class=&quot;MJX-TeXAtom-ORD&quot;><mtext>r</mtext></mrow></msub></math>\"><span id=\"MathJax-Span-15\" class=\"math\"><span><span><span id=\"MathJax-Span-16\" class=\"mrow\"><span id=\"MathJax-Span-17\" class=\"msubsup\"><span><span><span id=\"MathJax-Span-18\" class=\"mi\">κ</span></span><span><span id=\"MathJax-Span-19\" class=\"texatom\"><span id=\"MathJax-Span-20\" class=\"mrow\"><span id=\"MathJax-Span-21\" class=\"mtext\">r</span></span></span></span></span></span></span></span></span></span><span class=\"MJX_Assistive_MathML\">κr</span></span></span><span> are iteratively computed through minimization of the residual function, and the Brune model stress drop is then calculated from the final, best-fit </span><i class=\"EmphasisTypeItalic \">f</i><sub>c</sub><span>. We perform the spectral fitting routine on nested array seismic data that include the permanent GeoNet accelerometer network as well as a dense network of nearly 200 Quake Catcher Network (QCN) MEMs accelerometers, analyzing over 180 aftershocks </span><i class=\"EmphasisTypeItalic \">M</i><sub>w,GNS</sub><span>&nbsp;≥&nbsp;3.5 that occurred from 9 September 2010 to 31 July 2011. QCN stations were hosted by public volunteers and served to fill spatial gaps between existing GeoNet stations. Moment magnitudes determined using the spectral fitting procedure (</span><i class=\"EmphasisTypeItalic \">M</i><sub>w,SF</sub><span>) range from 3.5 to 5.7 and agree well with </span><i class=\"EmphasisTypeItalic \">M</i><sub>w,GNS</sub><span>, with a median difference of 0.09 and 0.17 for GeoNet and QCN records, respectively, and 0.11 when data from both networks are combined. The majority of events are calculated to have stress drops between 1.7 and 13&nbsp;MPa (20th and 80th percentile, correspondingly) for the combined networks. The overall median stress drop for the combined networks is 3.2&nbsp;MPa, which is similar to median stress drops previously reported for the Canterbury sequence. We do not observe a correlation between stress drop and depth for this region, nor a relationship between stress drop and magnitude over the catalog considered. Lateral spatial patterns in stress drop, such as a cluster of aftershocks near the eastern extent of the Greendale fault with higher stress drops and lower stress drops for aftershocks of the 2011 </span><i class=\"EmphasisTypeItalic \">M</i><sub>w,GNS</sub><span> 6.2 Christchurch mainshock, are found to be in agreement with previous reports. As stress drop is arguably a method-dependent calculation and subject to high spatial variability, our results using the parametric Gauss–Newton algorithm strengthen conclusions that the Canterbury sequence has stress drops that are more similar to those found in intraplate regions, with overall higher stress drops that are typically observed in tectonically active areas.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00024-016-1445-2","usgsCitation":"Neighbors, C., Cochran, E.S., Ryan, K., and Kaiser, A.E., 2017, Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence: Pure and Applied Geophysics, v. 174, no. 3, p. 875-893, https://doi.org/10.1007/s00024-016-1445-2.","productDescription":"19 p.","startPage":"875","endPage":"893","ipdsId":"IP-070144","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":341100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","city":"Christchurch","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              172.24365234374997,\n              -44.087585028245165\n            ],\n            [\n              173.29833984375,\n              -44.087585028245165\n            ],\n            [\n              173.29833984375,\n              -43.052833917627936\n            ],\n            [\n              172.24365234374997,\n              -43.052833917627936\n            ],\n            [\n              172.24365234374997,\n              -44.087585028245165\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"174","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-26","publicationStatus":"PW","scienceBaseUri":"59154657e4b01a342e6912df","contributors":{"authors":[{"text":"Neighbors, Corrie","contributorId":127529,"corporation":false,"usgs":false,"family":"Neighbors","given":"Corrie","affiliations":[{"id":7004,"text":"Department of Earth Sciences, University of California, Riverside","active":true,"usgs":false}],"preferred":false,"id":694761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694760,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan, Kenneth 0000-0003-3933-3163 kryan@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-3163","contributorId":191921,"corporation":false,"usgs":true,"family":"Ryan","given":"Kenneth","email":"kryan@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaiser, Anna E.","contributorId":141200,"corporation":false,"usgs":false,"family":"Kaiser","given":"Anna","email":"","middleInitial":"E.","affiliations":[{"id":6956,"text":"GNS Science/Massey University","active":true,"usgs":false}],"preferred":false,"id":694763,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195947,"text":"70195947 - 2017 - Trawl-based assessment of Lake Ontario pelagic prey fishes including Alewife and Rainbow Smelt","interactions":[],"lastModifiedDate":"2018-03-09T10:17:08","indexId":"70195947","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Trawl-based assessment of Lake Ontario pelagic prey fishes including Alewife and Rainbow Smelt","docAbstract":"<p>Managing Lake Ontario fisheries in an ecosystem-context, requires reliable data on the status and trends of prey fishes that support predator populations. We report on the community and population dynamics of Lake Ontario pelagic prey fishes, based on bottom trawl surveys. We emphasize information that supports the international Lake Ontario Committee’s Fish Community Objectives. In 2016, 142 bottom trawls were collected in U.S. waters, and for the first time 46 trawls were conducted in Canadian waters. A total of 420,386 fish from 24 species were captured. Alewife were 89% of the total fish catch and 93% of the pelagic prey fish catch. The Rainbow Smelt abundance index in U.S. waters increased slightly in 2016 relative to 2015. Interestingly, the Rainbow Smelt abundance index from tows in Canadian waters was 35% higher than the U.S. index. Abundances of Threespine Stickleback and Emerald Shiners in both U.S. and Canadian waters were low in 2016 relative to their peak abundances in the late 1990s, but Cisco abundance indices suggest a recent increase in their abundance. This year, the reported Alewife abundance time series was truncated to only include values since 1997, which were collected with the same trawl and eliminated the need to adjust values for different trawls. The 2016 adult Alewife abundance index was the second lowest abundance ever observed in the time series. This value was expected to decline from the 2015 value since the indices of juvenile Alewife were low in 2014 and the lowest ever observed in 2015. The fall condition index of adult Alewife increased in 2016 and is consistent with lower abundance and reduced competition for zooplankton resources. The 2016 Age-1 Alewife index increased relative to 2014 and 2015, and suggested lake conditions were favorable for Age-1 survival and growth during the summer of 2015 and the 2015-2016 winter. Interestingly, the catch of adult and Age1 Alewife was higher in trawls conducted in Canadian waters relative to U. S. waters. The larger trawl catches in Canadian waters suggest there may be important spatial differences in lake-wide distribution of prey fishes in April when trawling is conducted. Future surveys should to continue to sample at the whole-lake scale to understand the year to year variability in spatial distribution and the physical or biotic factors driving those distribution differences. </p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"NYSDEC Lake Ontario Annual Report 2016","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"New York State Department of Environmental Conservation","usgsCitation":"Weidel, B., Walsh, M., Connerton, M., and Holden, J.P., 2017, Trawl-based assessment of Lake Ontario pelagic prey fishes including Alewife and Rainbow Smelt, Section 12a; 13 p.","productDescription":"Section 12a; 13 p.","ipdsId":"IP-086005","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":352358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":352347,"type":{"id":11,"text":"Document"},"url":"https://www.dec.ny.gov/docs/fish_marine_pdf/lorpt16.pdf"}],"otherGeospatial":"Lake Ontario","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.0189208984375,\n              43.177141346631714\n            ],\n            [\n              -76.0528564453125,\n              43.177141346631714\n            ],\n            [\n              -76.0528564453125,\n              44.288469027276506\n            ],\n            [\n              -80.0189208984375,\n              44.288469027276506\n            ],\n            [\n              -80.0189208984375,\n              43.177141346631714\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8b9e4b0da30c1bfc492","contributors":{"authors":[{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":730645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walsh, Maureen 0000-0001-7846-5025 mwalsh@usgs.gov","orcid":"https://orcid.org/0000-0001-7846-5025","contributorId":3659,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"mwalsh@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":730646,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connerton, Michael J.","contributorId":190416,"corporation":false,"usgs":false,"family":"Connerton","given":"Michael J.","affiliations":[],"preferred":false,"id":730647,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holden, Jeremy P.","contributorId":190415,"corporation":false,"usgs":false,"family":"Holden","given":"Jeremy","email":"","middleInitial":"P.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":730648,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70185708,"text":"70185708 - 2017 - Divergent surface and total soil moisture projections under global warming","interactions":[],"lastModifiedDate":"2017-03-28T10:02:43","indexId":"70185708","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Divergent surface and total soil moisture projections under global warming","docAbstract":"<p><span>Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL071921","usgsCitation":"Berg, A., Sheffield, J., and Milly, P., 2017, Divergent surface and total soil moisture projections under global warming: Geophysical Research Letters, v. 44, no. 1, p. 236-244, https://doi.org/10.1002/2016GL071921.","productDescription":"9 p.","startPage":"236","endPage":"244","ipdsId":"IP-082638","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl071921","text":"Publisher Index Page"},{"id":338440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-13","publicationStatus":"PW","scienceBaseUri":"58db7631e4b0ee37af29e49e","contributors":{"authors":[{"text":"Berg, Alexis","contributorId":187496,"corporation":false,"usgs":false,"family":"Berg","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":686481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheffield, Justin","contributorId":189922,"corporation":false,"usgs":false,"family":"Sheffield","given":"Justin","email":"","affiliations":[],"preferred":false,"id":686482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milly, Paul C.D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":2119,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","email":"cmilly@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":686480,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182825,"text":"70182825 - 2017 - Sources and dispersal of land-based runoff from small Hawaiian drainages to a coral reef: Insights from geochemical signatures","interactions":[],"lastModifiedDate":"2017-03-01T15:03:24","indexId":"70182825","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Sources and dispersal of land-based runoff from small Hawaiian drainages to a coral reef: Insights from geochemical signatures","docAbstract":"Land-based sediment and contaminant runoff is a major threat to coral reefs, and runoff reduction efforts would benefit from knowledge of specific runoff sources. Geochemical signatures of small drainage basins were determined in the fine fraction of soil and sediment, then used in the nearshore region of a coral reef-fringed urban embayment on southeast Oahu, Hawaii, to describe sources and dispersal of land-based runoff. The sedimentary rare earth element ratio (La/Yb)N showed a clear distinction between the two main rock types in the overall contributing area, tholeiitic and alkalic olivine basalt. Based on this geochemical signature it was apparent that the majority of terrigenous sediment on the reef flat originated from geologically old tholeiitic drainages. Sediment from one of five tholeiitic drainages had a distinct geochemical signature, and sediment with this signature was dispersed on the reef flat 2 km west and 150 m offshore of the contributing basin. Sediment and the anthropogenic metals Cd, Pb, and Zn were entrained in runoff from the most heavily urbanized region of the watershed. Although anthropogenic Cd and Zn had localized distributions close to shore, anthropogenic Pb was found associated with fine sediment on the westernmost part of the reef flat and 400 m offshore, illustrating how trade-wind-driven sediment transport can increase the scale of runoff impacts to nearshore communities. Our findings show that sediment geochemical signatures can provide insights about the source and dispersal of land-based runoff in shallow coastal environments. The application of such knowledge to watershed management and habitat remediation efforts can aid in the protection and restoration of runoff-impacted coastal ecosystems worldwide.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2017.02.013","usgsCitation":"Takesue, R.K., and Storlazzi, C.D., 2017, Sources and dispersal of land-based runoff from small Hawaiian drainages to a coral reef: Insights from geochemical signatures: Estuarine, Coastal and Shelf Science, v. 188, p. 69-80, https://doi.org/10.1016/j.ecss.2017.02.013.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-077727","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2017.02.013","text":"Publisher Index Page"},{"id":336781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu, Maunalua Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -157.81482696533203,\n              21.25578165931365\n            ],\n            [\n              -157.8014373779297,\n              21.247942260443136\n            ],\n            [\n              -157.77568817138672,\n              21.244422394657736\n            ],\n            [\n              -157.72607803344727,\n              21.251782018135142\n            ],\n            [\n              -157.70462036132812,\n              21.259141273974\n            ],\n            [\n              -157.70444869995117,\n            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,{"id":70184974,"text":"70184974 - 2017 - Northern bobwhite breeding season ecology on a reclaimed surface mine","interactions":[],"lastModifiedDate":"2017-03-15T11:31:24","indexId":"70184974","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Northern bobwhite breeding season ecology on a reclaimed surface mine","docAbstract":"<p><span>Surface coal mining and subsequent reclamation of surface mines have converted large forest areas into early successional vegetative communities in the eastern United States. This reclamation can provide a novel opportunity to conserve northern bobwhite (</span><i>Colinus virginianus</i><span>). We evaluated the influence of habitat management activities on nest survival, nest-site selection, and brood resource selection on managed and unmanaged units of a reclaimed surface mine, Peabody Wildlife Management Area (Peabody), in west-central Kentucky, USA, from 2010 to 2013. We compared resource selection, using discrete-choice analysis, and nest survival, using the nest survival model in Program MARK, between managed and unmanaged units of Peabody at 2 spatial scales: the composition and configuration of vegetation types (i.e., macrohabitat) and vegetation characteristics at nest sites and brood locations (i.e., microhabitat). On managed sites, we also investigated resource selection relative to a number of different treatments (e.g., herbicide, disking, prescribed fire). We found no evidence that nest-site selection was influenced by macrohabitat variables, but bobwhite selected nest sites in areas with greater litter depth than was available at random sites. On managed units, bobwhite were more likely to nest where herbicide was applied to reduce sericea lespedeza (</span><i>Lespedeza cuneata</i><span>) compared with areas untreated with herbicide. Daily nest survival was not influenced by habitat characteristics or by habitat management but was influenced by nest age and the interaction of nest initiation date and nest age. Daily nest survival was greater for older nests occurring early in the breeding season (0.99, SE &lt; 0.01) but was lower for older nests occurring later in the season (0.08, SE = 0.13). Brood resource selection was not influenced by macrohabitat or microhabitat variables we measured, but broods on managed units selected areas treated with herbicide to control sericea lespedeza and were located closer to firebreaks and disked native-warm season grass stands than would be expected at random. Our results suggest the vegetation at Peabody was sufficient without manipulation to support nesting and brood-rearing northern bobwhite at a low level, but habitat management practices improved vegetation for nesting and brood-rearing resource selection. Reproductive rates (e.g., nest survival and re-nesting rates) at Peabody were lower than reported in other studies, which may be related to nutritional deficiencies caused by the abundance of sericea lespedeza. On reclaimed mine lands dominated by sericea lespedeza, we suggest continuing practices such as disking and herbicide application that are targeted at reducing sericea lespedeza to improve the vegetation for nesting and brood-rearing bobwhite. </span></p>","language":"English","publisher":"The WIldlife Society","doi":"10.1002/jwmg.21182","usgsCitation":"Brooke, J.M., Tanner, E.P., Peters, D.C., Tanner, A.M., Harper, C.A., Keyser, P.D., Clark, J.D., and Morgan, J.J., 2017, Northern bobwhite breeding season ecology on a reclaimed surface mine: Journal of Wildlife Management, v. 81, no. 1, p. 73-85, https://doi.org/10.1002/jwmg.21182.","productDescription":"13 p.","startPage":"73","endPage":"85","ipdsId":"IP-068704","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"Peabody Wildlife Management Area","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-86.8996,37.2123],[-86.8996,37.211],[-86.9065,37.2086],[-86.9021,37.1919],[-86.9038,37.1914],[-86.909,37.1909],[-86.9008,37.1842],[-86.8922,37.1875],[-86.8915,37.1829],[-86.8949,37.1775],[-86.8995,37.1761],[-86.9071,37.1796],[-86.9151,37.1795],[-86.9221,37.1803],[-86.9197,37.1758],[-86.9202,37.1699],[-86.9241,37.1653],[-86.9269,37.1576],[-86.9273,37.1521],[-86.9237,37.1449],[-86.9231,37.1427],[-86.9126,37.1356],[-86.9114,37.1319],[-86.9148,37.131],[-86.9165,37.1269],[-86.9159,37.1255],[-86.9078,37.1265],[-86.9061,37.1306],[-86.8975,37.1321],[-86.8975,37.1303],[-86.8992,37.1284],[-86.9008,37.1244],[-86.8996,37.1203],[-86.8972,37.1176],[-86.8949,37.1167],[-86.8879,37.115],[-86.8839,37.1137],[-86.8815,37.1119],[-86.8838,37.11],[-86.8861,37.1114],[-86.8907,37.1095],[-86.8942,37.1117],[-86.8971,37.1108],[-86.9023,37.1121],[-86.9016,37.1067],[-86.9039,37.1021],[-86.9021,37.0994],[-86.9009,37.0985],[-86.8974,37.0963],[-86.8979,37.0922],[-86.8944,37.0886],[-86.8972,37.0872],[-86.9047,37.0871],[-86.9082,37.0853],[-86.9248,37.0801],[-86.934,37.0782],[-86.9375,37.079],[-86.9404,37.0785],[-86.9454,37.073],[-86.9413,37.069],[-86.9766,37.0736],[-87.0531,37.0613],[-87.1185,37.0446],[-87.2504,37.0409],[-87.2512,37.0495],[-87.253,37.0504],[-87.2587,37.0498],[-87.2594,37.0539],[-87.2565,37.0562],[-87.2461,37.055],[-87.2439,37.0578],[-87.2452,37.0636],[-87.2499,37.0695],[-87.2592,37.0725],[-87.2605,37.0775],[-87.2646,37.0779],[-87.2679,37.0742],[-87.2725,37.0723],[-87.2807,37.0772],[-87.2819,37.0794],[-87.2825,37.0817],[-87.2849,37.0844],[-87.2855,37.0866],[-87.285,37.0889],[-87.284,37.0953],[-87.2854,37.1034],[-87.2843,37.108],[-87.2907,37.1101],[-87.2954,37.1128],[-87.3006,37.1132],[-87.3023,37.1118],[-87.3005,37.1082],[-87.3033,37.1063],[-87.305,37.1063],[-87.3173,37.112],[-87.3168,37.1138],[-87.3216,37.1224],[-87.324,37.1246],[-87.3288,37.135],[-87.3307,37.1395],[-87.3319,37.1408],[-87.3344,37.148],[-87.3345,37.1521],[-87.3334,37.1571],[-87.3307,37.1644],[-87.3268,37.1694],[-87.3274,37.1708],[-87.3189,37.1764],[-87.3161,37.1805],[-87.3151,37.1873],[-87.3117,37.1914],[-87.3159,37.1982],[-87.3218,37.2004],[-87.3288,37.2034],[-87.3341,37.2074],[-87.3376,37.2078],[-87.3393,37.2083],[-87.3457,37.2118],[-87.3499,37.2149],[-87.35,37.2194],[-87.3472,37.2231],[-87.349,37.2262],[-87.3578,37.2306],[-87.3561,37.2329],[-87.3591,37.2356],[-87.3656,37.2414],[-87.3714,37.2427],[-87.3714,37.244],[-87.364,37.2491],[-87.371,37.2509],[-87.3739,37.2522],[-87.3769,37.2539],[-87.3792,37.253],[-87.3855,37.2533],[-87.3885,37.2574],[-87.3886,37.2601],[-87.3865,37.2706],[-87.3861,37.2765],[-87.3844,37.2788],[-87.3816,37.2824],[-87.3829,37.2878],[-87.3841,37.2901],[-87.386,37.2955],[-87.378,37.2993],[-87.3722,37.2989],[-87.3741,37.3052],[-87.3793,37.3047],[-87.38,37.311],[-87.3738,37.3147],[-87.3709,37.3161],[-87.3663,37.318],[-87.3634,37.3158],[-87.3576,37.3145],[-87.3546,37.3105],[-87.3459,37.3097],[-87.343,37.3129],[-87.3439,37.3224],[-87.3428,37.3252],[-87.3388,37.3266],[-87.3371,37.328],[-87.3378,37.3325],[-87.3373,37.3362],[-87.3305,37.3435],[-87.3208,37.3486],[-87.322,37.3504],[-87.3124,37.3628],[-87.3005,37.3703],[-87.3011,37.3743],[-87.3075,37.3738],[-87.3093,37.3769],[-87.3059,37.382],[-87.2957,37.3916],[-87.2528,37.3864],[-87.2476,37.3865],[-87.2266,37.3836],[-87.2184,37.3805],[-87.2109,37.3811],[-87.2047,37.3857],[-87.1717,37.4134],[-87.1125,37.4114],[-87.108,37.4147],[-87.1016,37.4138],[-87.0999,37.4157],[-87.1018,37.4229],[-87.1007,37.4275],[-87.1043,37.4347],[-87.1023,37.4478],[-87.1043,37.4605],[-87.1079,37.4636],[-87.1196,37.4676],[-87.1244,37.4757],[-87.1356,37.4855],[-87.1223,37.4861],[-87.1205,37.4834],[-87.1204,37.4793],[-87.118,37.4776],[-87.1179,37.4735],[-87.115,37.4712],[-87.111,37.4731],[-87.1065,37.4809],[-87.1008,37.4841],[-87.0889,37.5002],[-87.0494,37.5519],[-87.0386,37.5611],[-87.0064,37.5801],[-87.0002,37.5865],[-86.999,37.5874],[-86.9528,37.6279],[-86.9464,37.6316],[-86.9388,37.6285],[-86.9266,37.6255],[-86.9202,37.6251],[-86.9167,37.6279],[-86.8926,37.6427],[-86.8776,37.6469],[-86.8654,37.6498],[-86.8419,37.665],[-86.8239,37.6711],[-86.8176,37.6734],[-86.8665,37.7087],[-86.8234,37.7377],[-86.6389,37.6616],[-86.6406,37.6194],[-86.6258,37.6042],[-86.6251,37.596],[-86.6198,37.5911],[-86.608,37.5771],[-86.6026,37.5695],[-86.5991,37.5672],[-86.5927,37.5646],[-86.5944,37.5609],[-86.5926,37.5591],[-86.5774,37.5538],[-86.5762,37.552],[-86.5797,37.5497],[-86.5843,37.5474],[-86.5895,37.5483],[-86.5936,37.5473],[-86.597,37.5459],[-86.5969,37.5378],[-86.6104,37.5445],[-86.6064,37.5495],[-86.6099,37.5504],[-86.6192,37.5534],[-86.6258,37.5661],[-86.6351,37.5669],[-86.6403,37.5664],[-86.6426,37.5632],[-86.6431,37.5591],[-86.6477,37.555],[-86.6646,37.5567],[-86.6685,37.548],[-86.6644,37.5449],[-86.662,37.5417],[-86.6625,37.5367],[-86.659,37.5322],[-86.6474,37.5001],[-86.6116,37.3953],[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PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-06","publicationStatus":"PW","scienceBaseUri":"58ca52cbe4b0849ce97c8696","contributors":{"authors":[{"text":"Brooke, Jarred M.","contributorId":146940,"corporation":false,"usgs":false,"family":"Brooke","given":"Jarred","email":"","middleInitial":"M.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683783,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanner, Evan P.","contributorId":146943,"corporation":false,"usgs":false,"family":"Tanner","given":"Evan","email":"","middleInitial":"P.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683784,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peters, David C.","contributorId":146941,"corporation":false,"usgs":false,"family":"Peters","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683782,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tanner, Ashley M.","contributorId":177321,"corporation":false,"usgs":false,"family":"Tanner","given":"Ashley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":683786,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harper, Craig A.","contributorId":146944,"corporation":false,"usgs":false,"family":"Harper","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683787,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keyser, Patrick D.","contributorId":146945,"corporation":false,"usgs":false,"family":"Keyser","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":683785,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":683781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morgan, John J.","contributorId":146946,"corporation":false,"usgs":false,"family":"Morgan","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":13409,"text":"Kentucky Department of Fish & Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":684457,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70186150,"text":"70186150 - 2017 - Managing native predators: Evidence from a partial removal of raccoons (<i>Procyon lotor</i>) on the Outer Banks of North Carolina, USA","interactions":[],"lastModifiedDate":"2017-03-30T11:10:56","indexId":"70186150","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Managing native predators: Evidence from a partial removal of raccoons (<i>Procyon lotor</i>) on the Outer Banks of North Carolina, USA","docAbstract":"<p><span>Raccoons (</span><i>Procyon lotor</i><span>) are important predators of ground-nesting species in coastal systems. They have been identified as a primary cause of nest failure for the American Oystercatcher (</span><i>Haematopus palliatus</i><span>) throughout its range. Concerns over the long-term effects of raccoon predation and increased nest success following a hurricane inspired a mark-resight study of the raccoon population on a barrier island off North Carolina, USA. Approximately half of the raccoons were experimentally removed in 2008. Nests (</span><i>n =</i><span> 700) were monitored on two adjacent barrier islands during 2004–2013. Daily nest survival estimates were highest for 2004 (0.974 ± 0.005) and lowest for 2007 and 2008 (0.925 ± 0.009 and 0.925 ± 0.010, respectively). The only model in our candidate set that received any support included island and time of season, along with a diminishing effect of the hurricane and a constant, 5-year effect of the raccoon removal. For both hurricane and raccoon removal, however, the support for island-specific effects was weak (β = -0.204 ± 0.116 and 0.146 ± 0.349, respectively). We conclude that either the raccoon reduction was inadequate, or factors other than predation cause more variation in nest success than previously recognized. A multi-faceted approach to management aimed at reducing nest losses to storm overwash, predation, and human disturbance is likely to yield the largest population level benefits.</span></p>","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.040.sp103","usgsCitation":"Stocking, J.J., Simons, T.R., Parsons, A.W., and O’Connell, A.F., 2017, Managing native predators: Evidence from a partial removal of raccoons (<i>Procyon lotor</i>) on the Outer Banks of North Carolina, USA: Waterbirds, v. 40, no. sp1, p. 10-18, https://doi.org/10.1675/063.040.sp103.","productDescription":"9 p.","startPage":"10","endPage":"18","ipdsId":"IP-071197","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":338798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.7449951171875,\n              34.56764471968292\n            ],\n            [\n              -75.91552734375,\n              34.56764471968292\n            ],\n            [\n              -75.91552734375,\n              35.1356330179272\n            ],\n            [\n              -76.7449951171875,\n              35.1356330179272\n            ],\n            [\n              -76.7449951171875,\n              34.56764471968292\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"sp1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194de4b02ff32c699c91","contributors":{"authors":[{"text":"Stocking, Jessica J.","contributorId":68626,"corporation":false,"usgs":true,"family":"Stocking","given":"Jessica","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":687675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parsons, Arielle W.","contributorId":91383,"corporation":false,"usgs":true,"family":"Parsons","given":"Arielle","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":687693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":687676,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70185031,"text":"70185031 - 2017 -  Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses","interactions":[],"lastModifiedDate":"2017-03-14T12:20:25","indexId":"70185031","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":797,"text":"Annals of the Association of American Geographers","active":true,"publicationSubtype":{"id":10}},"title":" Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses","docAbstract":"<p><span>Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24694452.2016.1218267","usgsCitation":"Malanson, G.P., Zimmerman, D.L., Kinney, M., and Fagre, D.B., 2017,  Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses: Annals of the Association of American Geographers, v. 107, no. 1, p. 41-53, https://doi.org/10.1080/24694452.2016.1218267.","productDescription":"13 p.","startPage":"41","endPage":"53","ipdsId":"IP-071596","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c90123e4b0849ce97abcba","contributors":{"authors":[{"text":"Malanson, George P.","contributorId":189162,"corporation":false,"usgs":false,"family":"Malanson","given":"George","email":"","middleInitial":"P.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":684012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Dale L.","contributorId":166811,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Dale","email":"","middleInitial":"L.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":684010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Mitch","contributorId":189163,"corporation":false,"usgs":false,"family":"Kinney","given":"Mitch","email":"","affiliations":[],"preferred":false,"id":684013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":684011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70193485,"text":"70193485 - 2017 - Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment","interactions":[],"lastModifiedDate":"2017-11-10T11:05:48","indexId":"70193485","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Conservation status of the American horseshoe crab, (<i>Limulus polyphemus</i>): A regional assessment","title":"Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment","docAbstract":"<p>Horseshoe crabs have persisted for more than 200 million years, and fossil forms date to 450 million years ago. The American horseshoe crab (<i class=\"EmphasisTypeItalic \">Limulus polyphemus</i>), one of four extant horseshoe crab species, is found along the Atlantic coastline of North America ranging from Alabama to Maine, USA with another distinct population on the coasts of Campeche, Yucatán and Quintana Roo in the Yucatán Peninsula, México. Although the American horseshoe crab tolerates broad environmental conditions, exploitation and habitat loss threaten the species. We assessed the conservation status of the American horseshoe crab by comprehensively reviewing available scientific information on its range, life history, genetic structure, population trends and analyses, major threats, and conservation. We structured the status assessment by six genetically-informed regions and accounted for sub-regional differences in environmental conditions, threats, and management. The transnational regions are Gulf of Maine (USA), Mid-Atlantic (USA), Southeast (USA), Florida Atlantic (USA), Northeast Gulf of México (USA), and Yucatán Peninsula (México). Our conclusion is that the American horseshoe crab species is vulnerable to local extirpation and that the degree and extent of risk vary among and within the regions. The risk is elevated in the Gulf of Maine region due to limited and fragmented habitat. The populations of horseshoe crabs in the Mid-Atlantic region are stable in the Delaware Bay area, and regulatory controls are in place, but the risk is elevated in the New England area as evidenced by continuing declines understood to be caused by over-harvest. The populations of horseshoe crabs in the Southeast region are stable or increasing. The populations of horseshoe crabs in the Florida Atlantic region show mixed trends among areas, and continuing population reductions at the embayment level have poorly understood causes. Within the Northeast Gulf of Mexico, causes of population trends are poorly understood and currently there is no active management of horseshoe crabs. Horseshoe crabs within México have conservation protection based on limited and fragmented habitat and geographic isolation from other regions, but elevated risk applies to the horseshoe crabs in the Yucatán Peninsula region until sufficient data can confirm population stability. Future species status throughout its range will depend on the effectiveness of conservation to mitigate habitat loss and manage for sustainable harvest among and within regions.</p>","language":"English","publisher":"Springer","doi":"10.1007/s11160-016-9461-y","usgsCitation":"Smith, D.R., Brockmann, H.J., Beekey, M.A., King, T.L., Millard, M., and Zaldivar-Rae, J., 2017, Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment: Reviews in Fish Biology and Fisheries, v. 27, no. 1, p. 135-175, https://doi.org/10.1007/s11160-016-9461-y.","productDescription":"41 p.","startPage":"135","endPage":"175","ipdsId":"IP-072969","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":470094,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11160-016-9461-y","text":"Publisher Index Page"},{"id":348566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"27","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-10","publicationStatus":"PW","scienceBaseUri":"5a06c8cfe4b09af898c86135","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":721551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brockmann, H. Jane","contributorId":199472,"corporation":false,"usgs":false,"family":"Brockmann","given":"H.","email":"","middleInitial":"Jane","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":721552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beekey, Mark A.","contributorId":199471,"corporation":false,"usgs":false,"family":"Beekey","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":35545,"text":"Sacred Heart University","active":true,"usgs":false}],"preferred":false,"id":721558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":721559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Millard, Mike","contributorId":194166,"corporation":false,"usgs":false,"family":"Millard","given":"Mike","email":"","affiliations":[{"id":26874,"text":"USFWS, Lamar, PA","active":true,"usgs":false}],"preferred":false,"id":721560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zaldivar-Rae, Jaime","contributorId":199473,"corporation":false,"usgs":false,"family":"Zaldivar-Rae","given":"Jaime","email":"","affiliations":[{"id":35546,"text":"Anáhuac Mayab University","active":true,"usgs":false}],"preferred":false,"id":721561,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191823,"text":"70191823 - 2017 - Nitrogen additions affect litter quality and soil biochemical properties in a peatland of Northeast China","interactions":[],"lastModifiedDate":"2017-10-18T10:22:13","indexId":"70191823","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen additions affect litter quality and soil biochemical properties in a peatland of Northeast China","docAbstract":"<p><span>Nitrogen (N) is a limiting nutrient in many peatland ecosystems. Enhanced N deposition, a major component of global climate change, affects ecosystem carbon (C) balance and alters soil C storage by changing plant and soil properties. However, the effects of enhanced N deposition on peatland ecosystems are poorly understood. We conducted a two-year N additions field experiment in a peatland dominated by&nbsp;</span><i>Eriophorum vaginatum</i><span><span>&nbsp;</span>in the Da Xing’an Mountains, Northeast China. Four levels of N treatments were applied: (1) CK (no N added), (2) N1 (6</span><span>&nbsp;</span><span>g</span><span>&nbsp;</span><span>N</span><span>&nbsp;</span><span>m</span><sup>−2</sup><span>&nbsp;</span><span>yr</span><sup>−1</sup><span>), (3) N2 (12</span><span>&nbsp;</span><span>g</span><span>&nbsp;</span><span>N</span><span>&nbsp;</span><span>m</span><sup>−2</sup><span>&nbsp;</span><span>yr</span><sup>−1</sup><span>), and (4) N3 (24</span><span>&nbsp;</span><span>g</span><span>&nbsp;</span><span>N</span><span>&nbsp;</span><span>m</span><sup>−2</sup><span><span>&nbsp;</span></span><span>&nbsp;</span><span>yr</span><sup>−1</sup><span>). Plant and soil material was harvested at the end of the second growing season. N additions increased litter N and phosphorus (P) content, as well as β-glucosidase, invertase, and acid-phosphatase activity, but decreased litter C:N and C:P ratios. Litter carbon content remained unchanged. N additions increased available NH</span><sub>4</sub><sup>+</sup><span>–N and NO</span><sub>3</sub><sup>−</sup><span>–N as well as total Gram-positive (Gram+), Gram-negative (Gram−), and total bacterial phospholipid fatty acids (PLFA) in shallow soil (0–15</span><span>&nbsp;</span><span>cm depth). An increase in these PLFAs was accompanied by a decrease in soil labile organic C (microbial biomass carbon and dissolved organic carbon), and appeared to accelerate decomposition and reduce the stability of the soil C pool. Invertase and urease activity in shallow soils and acid-phosphatase activity in deep soils (15–30</span><span>&nbsp;</span><span>cm depth) was inhibited by N additions. Together, these findings suggest that an increase in N deposition in peatlands could accelerate litter decomposition and the loss of labile C, as well as alter microbial biomass and function.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2016.12.025","usgsCitation":"Song, Y., Song, C., Meng, H., Swarzenski, C.M., Wang, X., and Tan, W., 2017, Nitrogen additions affect litter quality and soil biochemical properties in a peatland of Northeast China: Ecological Engineering, v. 100, p. 175-185, https://doi.org/10.1016/j.ecoleng.2016.12.025.","productDescription":"11 p.","startPage":"175","endPage":"185","ipdsId":"IP-071131","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":346828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              121.5087890625,\n              53.028000167735165\n            ],\n            [\n              123.035888671875,\n              53.028000167735165\n            ],\n            [\n              123.035888671875,\n              53.51418452077113\n            ],\n            [\n              121.5087890625,\n              53.51418452077113\n            ],\n            [\n              121.5087890625,\n              53.028000167735165\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"100","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e86837e4b05fe04cd4d206","contributors":{"authors":[{"text":"Song, Yanyu","contributorId":197346,"corporation":false,"usgs":false,"family":"Song","given":"Yanyu","email":"","affiliations":[],"preferred":false,"id":713256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Song, Changchun","contributorId":177141,"corporation":false,"usgs":false,"family":"Song","given":"Changchun","email":"","affiliations":[],"preferred":false,"id":713257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meng, Henan","contributorId":197347,"corporation":false,"usgs":false,"family":"Meng","given":"Henan","email":"","affiliations":[],"preferred":false,"id":713258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swarzenski, Christopher M. 0000-0001-9843-1471 cswarzen@usgs.gov","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":656,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Christopher","email":"cswarzen@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713234,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Xianwei","contributorId":197348,"corporation":false,"usgs":false,"family":"Wang","given":"Xianwei","email":"","affiliations":[],"preferred":false,"id":713259,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tan, Wenwen","contributorId":197349,"corporation":false,"usgs":false,"family":"Tan","given":"Wenwen","email":"","affiliations":[],"preferred":false,"id":713260,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191921,"text":"70191921 - 2017 - San Francisco Bay living shorelines: Restoring Eelgrass and Olympia Oysters for habitat and shore protection","interactions":[],"lastModifiedDate":"2020-08-21T13:20:58.481643","indexId":"70191921","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"17","title":"San Francisco Bay living shorelines: Restoring Eelgrass and Olympia Oysters for habitat and shore protection","docAbstract":"<p><span>Living shorelines projects utilize a suite of sediment stabilization and habitat restoration techniques to maintain or build the shoreline, while creating habitat for a variety of species, including invertebrates, fish, and birds (see National Oceanic and Atmospheric Administration [NOAA] 2015 for an overview). The term “living shorelines” denotes provision of living space and support for estuarine and coastal organisms through the strategic placement of native vegetation and natural materials. This green coastal infrastructure can serve as an alternative to bulkheads and other engineering solutions that provide little to no habitat in comparison (Arkema et al. 2013; Gittman et al. 2014; Scyphers et al. 2011). In the United States, the living shorelines approach has been implemented primarily on the East and Gulf Coasts, where it has been shown to enhance habitat values and increase connectivity between wetlands, mudflats, and subtidal lands, while reducing shoreline erosion during storms and even hurricanes (Currin et al. 2015; Gittman et al. 2014, 2015).</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Living shorelines: The science and management of nature-based coastal protection","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CRC Press","isbn":"9781498740029","usgsCitation":"Boyer, K.E., Zabin, C., De La Cruz, S., Grosholz, E., Orr, M., Lowe, J., Latta, M., Miller, J., Kiriakopolos, S., Pinnell, C., Kunz, D., Moderan, J., Stockmann, K., Ayala, G., Abbott, R., and Obernolte, R., 2017, San Francisco Bay living shorelines: Restoring Eelgrass and Olympia Oysters for habitat and shore protection, chap. 17 <i>of</i> Living shorelines: The science and management of nature-based coastal protection, p. 333-362.","productDescription":"30 p.","startPage":"333","endPage":"362","ipdsId":"IP-080822","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":351822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346922,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Living-Shorelines-The-Science-and-Management-of-Nature-Based-Coastal-Protection/Bilkovic-Mitchell-Peyre-Toft/p/book/9781498740029"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.3544921875,\n              37.046408899699564\n 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Chela","contributorId":197536,"corporation":false,"usgs":false,"family":"Zabin","given":"Chela","email":"","affiliations":[],"preferred":false,"id":713696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De La Cruz, Susan sdelacruz@usgs.gov","contributorId":131159,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"sdelacruz@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":713694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grosholz, Edwin D.","contributorId":171563,"corporation":false,"usgs":false,"family":"Grosholz","given":"Edwin D.","affiliations":[],"preferred":false,"id":713697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, 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Kevin","contributorId":197544,"corporation":false,"usgs":false,"family":"Stockmann","given":"Kevin","affiliations":[],"preferred":false,"id":713706,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ayala, Geana","contributorId":197545,"corporation":false,"usgs":false,"family":"Ayala","given":"Geana","email":"","affiliations":[],"preferred":false,"id":713707,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Abbott, Robert","contributorId":197546,"corporation":false,"usgs":false,"family":"Abbott","given":"Robert","email":"","affiliations":[],"preferred":false,"id":713708,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Obernolte, Rena","contributorId":197547,"corporation":false,"usgs":false,"family":"Obernolte","given":"Rena","email":"","affiliations":[],"preferred":false,"id":713709,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70192616,"text":"70192616 - 2017 - The basis function approach for modeling autocorrelation in ecological data","interactions":[],"lastModifiedDate":"2017-11-10T11:17:00","indexId":"70192616","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The basis function approach for modeling autocorrelation in ecological data","docAbstract":"<p><span>Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1674","usgsCitation":"Hefley, T.J., Broms, K.M., Brost, B.M., Buderman, F.E., Kay, S.L., Scharf, H., Tipton, J., Williams, P.J., and Hooten, M., 2017, The basis function approach for modeling autocorrelation in ecological data: Ecology, v. 98, no. 3, p. 632-646, https://doi.org/10.1002/ecy.1674.","productDescription":"15 p.","startPage":"632","endPage":"646","ipdsId":"IP-070118","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470033,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1606.05658","text":"External Repository"},{"id":348572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8cfe4b09af898c86138","contributors":{"authors":[{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":721574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Broms, Kristin M.","contributorId":171524,"corporation":false,"usgs":false,"family":"Broms","given":"Kristin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":721577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kay, Shannon L.","contributorId":193049,"corporation":false,"usgs":false,"family":"Kay","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scharf, Henry","contributorId":200238,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","affiliations":[],"preferred":false,"id":721579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":721580,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721581,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716562,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70193644,"text":"70193644 - 2017 - Who knew? First Myotis sodalis (Indiana Bat) maternity colony in the coastal plain of Virginia","interactions":[],"lastModifiedDate":"2017-11-05T22:00:33","indexId":"70193644","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Who knew? First <i>Myotis sodalis</i> (Indiana Bat) maternity colony in the coastal plain of Virginia","title":"Who knew? First Myotis sodalis (Indiana Bat) maternity colony in the coastal plain of Virginia","docAbstract":"<p>We report the first confirmed <i>Myotis sodalis</i> (Indiana Bat) maternity colony in Virginia, discovered at Fort A.P. Hill Military Reservation in Caroline County along the Piedmont-Coastal Plain Fall Line. Acoustic surveys conducted in 2014 indicated likely presence of Indiana Bats on the installation. Subsequent focal mist-netting during May–June 2015 resulted in capture of 4 lactating females that we subsequently radio tracked to a maternity colony site containing at least 20 individuals. The core roosting-area was comprised of <i>Pinus taeda</i> (Loblolly Pine) snags with abundant exfoliating bark and high solar exposure. This forest patch was adjacent to a large emergentshrub wetland and within a larger matrix of mature, mid-Atlantic hardwood forests. The site where we found the colony location is 140 km east of the nearest known hibernaculum and is outside of the previously documented extent of this species' occurrence.</p>","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/045.024.0110","usgsCitation":"St. Germain, M.J., Kniowski, A.B., Silvis, A., and Ford, W.M., 2017, Who knew? First Myotis sodalis (Indiana Bat) maternity colony in the coastal plain of Virginia: Northeastern Naturalist, v. 24, no. 1, p. N5-N10, https://doi.org/10.1656/045.024.0110.","productDescription":"6 p.","startPage":"N5","endPage":"N10","ipdsId":"IP-076231","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","volume":"24","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a003150e4b0531197b5a74a","contributors":{"authors":[{"text":"St. Germain, Michael J.","contributorId":25959,"corporation":false,"usgs":false,"family":"St. Germain","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":719732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kniowski, Andrew B.","contributorId":191558,"corporation":false,"usgs":false,"family":"Kniowski","given":"Andrew","email":"","middleInitial":"B.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":720413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":720414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":720415,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70186330,"text":"70186330 - 2017 - Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes","interactions":[],"lastModifiedDate":"2018-01-13T15:10:14","indexId":"70186330","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3032,"text":"Permafrost and Periglacial Processes","active":true,"publicationSubtype":{"id":10}},"title":"Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes","docAbstract":"<p><span>The distribution of shallow frozen ground is paramount to research in cold regions, and is subject to temporal and spatial changes influenced by climate, landscape disturbance and ecosystem succession. Remote sensing from airborne and satellite platforms is increasing our understanding of landscape-scale permafrost distribution, but typically lacks the resolution to characterise finer-scale processes and phenomena, which are better captured by integrated surface geophysical methods. Here, we demonstrate the use of electrical resistivity imaging (ERI), electromagnetic induction (EMI), ground penetrating radar (GPR) and infrared imaging over multiple summer field seasons around the highly dynamic Twelvemile Lake, Yukon Flats, central Alaska, USA. Twelvemile Lake has generally receded in the past 30 yr, allowing permafrost aggradation in the receded margins, resulting in a mosaic of transient frozen ground adjacent to thick, older permafrost outside the original lakebed. ERI and EMI best evaluated the thickness of shallow, thin permafrost aggradation, which was not clear from frost probing or GPR surveys. GPR most precisely estimated the depth of the active layer, which forward electrical resistivity modelling indicated to be a difficult target for electrical methods, but could be more tractable in time-lapse mode. Infrared imaging of freshly dug soil pit walls captured active-layer thermal gradients at unprecedented resolution, which may be useful in calibrating emerging numerical models. GPR and EMI were able to cover landscape scales (several kilometres) efficiently, and new analysis software showcased here yields calibrated EMI data that reveal the complicated distribution of shallow permafrost in a transitional landscape.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ppp.1893","usgsCitation":"Briggs, M.A., Campbell, S., Nolan, J., Walvoord, M.A., Ntarlagiannis, D., Day-Lewis, F.D., and Lane, J.W., 2017, Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes: Permafrost and Periglacial Processes, v. 28, no. 1, p. 52-65, https://doi.org/10.1002/ppp.1893.","productDescription":"14 p.","startPage":"52","endPage":"65","ipdsId":"IP-069599","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":438431,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UST855","text":"USGS data release","linkHelpText":"Surface geophysical data for characterizing shallow, discontinuous frozen ground near Fort Yukon, Alaska"},{"id":339120,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -145.5,\n              66.45\n            ],\n            [\n              -145.25,\n              66.45\n            ],\n            [\n              -145.25,\n              66.6\n            ],\n            [\n              -145.5,\n              66.6\n            ],\n            [\n              -145.5,\n              66.45\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-24","publicationStatus":"PW","scienceBaseUri":"58e4b0b1e4b09da67999777a","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":688344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Seth","contributorId":190402,"corporation":false,"usgs":false,"family":"Campbell","given":"Seth","affiliations":[],"preferred":false,"id":688345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nolan, Jay","contributorId":190403,"corporation":false,"usgs":false,"family":"Nolan","given":"Jay","email":"","affiliations":[],"preferred":false,"id":688346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":688347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ntarlagiannis, Dimitrios","contributorId":150729,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":688348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":688349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":688350,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70188344,"text":"70188344 - 2017 - Toppling analysis of the Echo Cliffs precariously balanced rock","interactions":[],"lastModifiedDate":"2022-11-02T14:00:48.646049","indexId":"70188344","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","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":"Toppling analysis of the Echo Cliffs precariously balanced rock","docAbstract":"<p><span>Toppling analysis of a precariously balanced rock (PBR) can provide insight into the nature of ground motion that has not occurred at that location in the past and, by extension, can constrain peak ground motions for use in engineering design. Earlier approaches have targeted 2D models of the rock or modeled the rock–pedestal contact using spring‐damper assemblies that require recalibration for each rock. Here, a method to model PBRs in 3D is presented through a case study of the Echo Cliffs PBR. The 3D model is created from a point cloud of the rock, the pedestal, and their interface, obtained using terrestrial laser scanning. The dynamic response of the model under earthquake excitation is simulated using a rigid‐body dynamics algorithm. The veracity of this approach is demonstrated through comparisons against data from shake‐table experiments. Fragility maps for toppling probability of the Echo Cliffs PBR as a function of various ground‐motion parameters, rock–pedestal interface friction coefficient, and excitation direction are presented. These fragility maps indicate that the toppling probability of this rock is low (less than 0.2) for peak ground acceleration (PGA) and peak ground velocity (PGV) lower than 3  m/s</span><sup>2</sup><span> and 0.75  m/s, respectively, suggesting that the ground‐motion intensities at this location from earthquakes on nearby faults have most probably not exceeded the above‐mentioned PGA and PGV during the age of the PBR. Additionally, the fragility maps generated from this methodology can also be directly coupled with existing probabilistic frameworks to obtain direct constraints on unexceeded ground motion at a PBR’s location.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160169","usgsCitation":"Veeraraghavan, S., Hudnut, K.W., and Krishnan, S., 2017, Toppling analysis of the Echo Cliffs precariously balanced rock: Bulletin of the Seismological Society of America, v. 107, no. 1, p. 72-84, https://doi.org/10.1785/0120160169.","productDescription":"13 p.","startPage":"72","endPage":"84","ipdsId":"IP-078915","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470046,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20161213-141035303","text":"External Repository"},{"id":342189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Echo Cliffs precariously balanced rock","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.92706014090601,\n              34.12673669928829\n            ],\n            [\n              -118.92706014090601,\n              34.12580082827124\n            ],\n            [\n              -118.92597045637072,\n              34.12580082827124\n            ],\n            [\n              -118.92597045637072,\n              34.12673669928829\n            ],\n            [\n              -118.92706014090601,\n              34.12673669928829\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-13","publicationStatus":"PW","scienceBaseUri":"5937bf2de4b0f6c2d0d9c75b","contributors":{"authors":[{"text":"Veeraraghavan, Swetha","contributorId":192670,"corporation":false,"usgs":false,"family":"Veeraraghavan","given":"Swetha","email":"","affiliations":[],"preferred":false,"id":697334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudnut, Kenneth W. 0000-0002-3168-4797 hudnut@usgs.gov","orcid":"https://orcid.org/0000-0002-3168-4797","contributorId":2550,"corporation":false,"usgs":true,"family":"Hudnut","given":"Kenneth","email":"hudnut@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krishnan, Swaminathan","contributorId":192671,"corporation":false,"usgs":false,"family":"Krishnan","given":"Swaminathan","email":"","affiliations":[],"preferred":false,"id":697335,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70184180,"text":"70184180 - 2017 - Nocturnal insect availability in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley","interactions":[],"lastModifiedDate":"2017-03-01T14:16:54","indexId":"70184180","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Nocturnal insect availability in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley","docAbstract":"Silviculture used to alter forest structure and thereby enhance wildlife habitat has been advocated for bottomland hardwood forest management on public conservation lands in the Mississippi Alluvial Valley. Although some songbirds respond positively to these management actions to attain desired forest conditions for wildlife, the response of other species, is largely unknown. Nocturnal insects are a primary prey base for bats, thereby influencing trophic interactions within hardwood forests. To better understand how silviculture influences insect availability for bats, we conducted vegetation surveys and sampled insect biomass within silviculturally treated bottomland hardwood forest stands. We used passive blacklight traps to capture nocturnal flying insects in 64 treated and 64 untreated reference stands, located on 15 public conservation areas in Arkansas, Louisiana, and Mississippi. Dead wood and silvicultural treatments were positively associated with greater biomass of macro-Lepidoptera, macro-Coleoptera, and all insect taxa combined. Biomass of micro-Lepidoptera was negatively associated with silvicultural treatment but comprised only a small proportion of total biomass. Understanding the response of nocturnal insects to wildlife-forestry silviculture provides insight for prescribed silvicultural management affecting bat species.","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2017.02.009","usgsCitation":"Ketzler, L.P., Christopher Comer, and Twedt, D.J., 2017, Nocturnal insect availability in bottomland hardwood forests managed for wildlife in the Mississippi Alluvial Valley: Forest Ecology and Management, v. 391, p. 127-134, https://doi.org/10.1016/j.foreco.2017.02.009.","productDescription":"8 p.","startPage":"127","endPage":"134","ipdsId":"IP-077314","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470050,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2017.02.009","text":"Publisher Index Page"},{"id":336772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Louisiana, Mississippi","otherGeospatial":"Mississippi alluvial valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.69238281249999,\n              35.585851593232356\n            ],\n            [\n              -88.857421875,\n              37.055177106660814\n            ],\n            [\n              -89.736328125,\n              37.26530995561875\n            ],\n            [\n              -90.52734374999999,\n              36.87962060502676\n            ],\n            [\n              -90.791015625,\n              36.43896124085945\n            ],\n            [\n              -91.60400390625,\n              35.69299463209881\n            ],\n            [\n              -92.30712890625,\n              34.379712580462204\n            ],\n            [\n              -91.8017578125,\n              33.76088200086917\n            ],\n            [\n              -91.73583984374999,\n              33.15594830078649\n            ],\n            [\n              -92.1533203125,\n              32.76880048488168\n            ],\n            [\n              -92.2412109375,\n              32.08257455954592\n            ],\n            [\n              -92.39501953125,\n              31.147006308556566\n            ],\n            [\n              -92.900390625,\n              30.486550842588485\n            ],\n            [\n              -93.27392578125,\n              29.783449456820605\n            ],\n            [\n              -90.4833984375,\n              29.152161283318915\n            ],\n            [\n              -89.62646484375,\n              29.935895213372444\n            ],\n            [\n              -91.20849609375,\n              30.278044377800153\n            ],\n            [\n              -91.51611328125,\n              30.92107637538488\n            ],\n            [\n              -91.3623046875,\n              31.50362930577303\n            ],\n            [\n              -90.791015625,\n              32.287132632616384\n            ],\n            [\n              -90.32958984375,\n              32.76880048488168\n            ],\n            [\n              -90.06591796875,\n              33.37641235124676\n            ],\n            [\n              -90,\n              34.397844946449865\n            ],\n            [\n              -90.2197265625,\n              34.84987503195418\n            ],\n            [\n              -89.69238281249999,\n              35.585851593232356\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"391","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eb9fe4b01ccd5500bacf","contributors":{"authors":[{"text":"Ketzler, Loraine P.","contributorId":187409,"corporation":false,"usgs":false,"family":"Ketzler","given":"Loraine","email":"","middleInitial":"P.","affiliations":[{"id":32360,"text":"Stephen F. Austin State University, Nacogdoches, TX","active":true,"usgs":false}],"preferred":false,"id":680366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christopher Comer","contributorId":187410,"corporation":false,"usgs":false,"family":"Christopher Comer","affiliations":[],"preferred":false,"id":680367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":680365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70191671,"text":"70191671 - 2017 - New insights into nitrate dynamics in a karst groundwater system gained from in situ high-frequency optical sensor measurements","interactions":[],"lastModifiedDate":"2017-10-24T14:04:19","indexId":"70191671","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"New insights into nitrate dynamics in a karst groundwater system gained from in situ high-frequency optical sensor measurements","docAbstract":"<p><span>Understanding nitrate dynamics in groundwater systems as a function of climatic conditions, especially during contrasting patterns of drought and wet cycles, is limited by a lack of temporal and spatial data. Nitrate sensors have the capability for making accurate, high-frequency measurements of nitrate in situ, but have not yet been evaluated for long-term use in groundwater wells. We measured in situ nitrate continuously in two groundwater monitoring wells —one rural and one urban—located in the recharge zone of a productive karst aquifer in central Texas in order to resolve changes that occur over both short-term (hourly to daily) and long-term (monthly to yearly) periods. Nitrate concentrations, measured as nitrate-nitrogen in milligrams per liter (mg/L), during drought conditions showed little or no temporal change as groundwater levels declined. During aquifer recharge, extremely rapid changes in concentration occurred at both wells as documented by hourly data. At both sites, nitrate concentrations were affected by recharging surface water as evidenced by nitrate concentrations in groundwater recharge (0.8–1.3</span><span>&nbsp;</span><span>mg/L) that were similar to previously reported values for regional recharging streams. Groundwater nitrate concentrations responded differently at urban and rural sites during groundwater recharge. Concentrations at the rural well (approximately 1.0</span><span>&nbsp;</span><span>mg/L) increased as a result of higher nitrate concentrations in groundwater recharge relative to ambient nitrate concentrations in groundwater, whereas concentrations at the urban well (approximately 2.7</span><span>&nbsp;</span><span>mg/L) decreased as a result of the dilution of higher ambient nitrate concentrations relative to those in groundwater recharge. Notably, nitrate concentrations decreased to as low as 0.8</span><span>&nbsp;</span><span>mg/L at the urban site during recharge but postrecharge concentrations exceeded 3.0</span><span>&nbsp;</span><span>mg/L. A return to higher nitrate concentrations postrecharge indicates mobilization of a localized source of elevated nitrate within the urbanized area of the aquifer. Changes in specific conductance were observed at both sites during groundwater recharge, and a significant correlation between specific conductance and nitrate (correlation coefficient [R]</span><span>&nbsp;</span><span>=</span><span>&nbsp;</span><span>0.455) was evident at the urban site where large (3-fold) changes in nitrate occurred. Nitrate concentrations and specific conductance measured during a depth profile indicated that the water column was generally homogeneous as expected for this karst environment, but changes were observed in the most productive zone of the aquifer that might indicate some heterogeneity within the complex network of flow paths. Resolving the timing and magnitude of changes and characterizing fine-scale vertical differences would not be possible using conventional sampling techniques. The patterns observed in situ provided new insight into the dynamic nature of nitrate in a karst groundwater system.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.12.038","usgsCitation":"Opsahl, S.P., Musgrove, M., and Slattery, R.N., 2017, New insights into nitrate dynamics in a karst groundwater system gained from in situ high-frequency optical sensor measurements: Journal of Hydrology, v. 546, p. 179-188, https://doi.org/10.1016/j.jhydrol.2016.12.038.","productDescription":"10 p.","startPage":"179","endPage":"188","ipdsId":"IP-067710","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":347247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.469970703125,\n              29.11857441491087\n            ],\n            [\n              -97.55584716796875,\n              29.11857441491087\n            ],\n            [\n              -97.55584716796875,\n              30.458144351018078\n            ],\n            [\n              -100.469970703125,\n              30.458144351018078\n            ],\n            [\n              -100.469970703125,\n              29.11857441491087\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"546","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f05123e4b0220bbd9a1d9f","contributors":{"authors":[{"text":"Opsahl, Stephen P. 0000-0002-4774-0415 sopsahl@usgs.gov","orcid":"https://orcid.org/0000-0002-4774-0415","contributorId":4713,"corporation":false,"usgs":true,"family":"Opsahl","given":"Stephen","email":"sopsahl@usgs.gov","middleInitial":"P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":713012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slattery, Richard N. 0000-0002-9141-9776 rnslatte@usgs.gov","orcid":"https://orcid.org/0000-0002-9141-9776","contributorId":2471,"corporation":false,"usgs":true,"family":"Slattery","given":"Richard","email":"rnslatte@usgs.gov","middleInitial":"N.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193265,"text":"70193265 - 2017 - Integrating multiple data sources in species distribution modeling: A framework for data fusion","interactions":[],"lastModifiedDate":"2018-12-20T12:52:54","indexId":"70193265","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating multiple data sources in species distribution modeling: A framework for data fusion","docAbstract":"<p>The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (“Shared,” “Correlation,” “Covariates”) for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source (“Single”). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.</p>","language":"English","publisher":"Wiley","doi":"10.1002/ecy.1710","usgsCitation":"Pacifici, K., Reich, B.J., Miller, D.A., Gardner, B., Stauffer, G.E., Singh, S., McKerrow, A., and Collazo, J., 2017, Integrating multiple data sources in species distribution modeling: A framework for data fusion: Ecology, v. 98, no. 3, p. 840-850, https://doi.org/10.1002/ecy.1710.","productDescription":"11 p.","startPage":"840","endPage":"850","ipdsId":"IP-073421","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":470049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.1710","text":"Publisher Index Page"},{"id":348018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd24e4b0531197b13cad","contributors":{"authors":[{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reich, Brian J.","contributorId":150871,"corporation":false,"usgs":false,"family":"Reich","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":719050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":719051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stauffer, Glenn E.","contributorId":171536,"corporation":false,"usgs":false,"family":"Stauffer","given":"Glenn","email":"","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":719052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Singh, Susheela","contributorId":11646,"corporation":false,"usgs":false,"family":"Singh","given":"Susheela","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719061,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":719062,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":719063,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70184186,"text":"70184186 - 2017 - Mercury exposure may influence fluctuating asymmetry in waterbirds","interactions":[],"lastModifiedDate":"2017-11-22T17:04:33","indexId":"70184186","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","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":"Mercury exposure may influence fluctuating asymmetry in waterbirds","docAbstract":"<p><span>Variation in avian bilateral symmetry can be an indicator of developmental instability in response to a variety of stressors, including environmental contaminants. The authors used composite measures of fluctuating asymmetry to examine the influence of mercury concentrations in 2 tissues on fluctuating asymmetry within 4 waterbird species. Fluctuating asymmetry increased with mercury concentrations in whole blood and breast feathers of Forster's terns (</span><i>Sterna forsteri</i><span>), a species with elevated mercury concentrations. Specifically, fluctuating asymmetry in rectrix feather 1 was the most strongly correlated structural variable of those tested (wing chord, tarsus, primary feather 10, rectrix feather 6) with mercury concentrations in Forster's terns. However, for American avocets (</span><i>Recurvirostra americana</i><span>), black-necked stilts (</span><i>Himantopus mexicanus</i><span>), and Caspian terns (</span><i>Hydroprogne caspia</i><span>), the authors found no relationship between fluctuating asymmetry and either whole-blood or breast feather mercury concentrations, even though these species had moderate to elevated mercury exposure. The results indicate that mercury contamination may act as an environmental stressor during development and feather growth and contribute to fluctuating asymmetry of some species of highly contaminated waterbirds. </span></p>","language":"English","publisher":"Wiley","doi":"10.1002/etc.3688","usgsCitation":"Herring, G., Eagles-Smith, C.A., and Ackerman, J., 2017, Mercury exposure may influence fluctuating asymmetry in waterbirds: Environmental Toxicology and Chemistry, v. 36, no. 6, p. 1599-1605, https://doi.org/10.1002/etc.3688.","productDescription":"7 p.","startPage":"1599","endPage":"1605","ipdsId":"IP-067136","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":438432,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KW5D5Z","text":"USGS data release","linkHelpText":"Fluctuating asymmetry in waterbirds in relation to mercury exposure"},{"id":336770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58b7eb9ee4b01ccd5500bacd","contributors":{"authors":[{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":680424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":680425,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192856,"text":"70192856 - 2017 - LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response","interactions":[],"lastModifiedDate":"2017-10-30T15:08:59","indexId":"70192856","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1440,"text":"Earthzine","active":true,"publicationSubtype":{"id":10}},"title":"LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response","docAbstract":"<p><span>The LANDFIRE Program</span><span><span>&nbsp;</span>produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as well as many other<span> applications</span></span><span>. The initial LANDFIRE<span> National</span></span><span><span>&nbsp;</span>Existing Vegetation Type (EVT</span><span>) and vegetation structure layers, including vegetation percent cover and height, were mapped circa 2001 and released in 2009 [5]. Each EVT is representative of the dominant plant community within a given area. The EVT layer has since been updated by identifying areas of<span> landscape change</span></span><span><span>&nbsp;</span>and modifying the vegetation types utilizing a series of rules that consider the disturbance type, severity of disturbance, and time since disturbance [6, 7]. Non-disturbed areas were adjusted for vegetation growth and succession. LANDFIRE vegetation structure layers also have been updated by using data modeling techniques [see 6 for a full description]. The subsequent updated<span> versions</span></span><span><span>&nbsp;</span>of LANDFIRE include LANDFIRE<span> 2008, 2010, 2012</span></span><span>, and LANDFIRE<span> 2014</span></span><span><span>&nbsp;</span>is being incrementally released, with all data being released in early 2017. Additionally, a comprehensive remap of the baseline data,<span> LANDFIRE 2015 Remap</span></span><span>, is being prototyped, and production is tentatively<span> planned</span></span><span><span>&nbsp;</span>to begin in early 2017 to provide a more current baseline for future updates.</span></p>","language":"English","publisher":"IEEE","usgsCitation":"Picotte, J.J., Long, J., Peterson, B., and Nelson, K., 2017, LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response: Earthzine, v. March 2017, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-078297","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347605,"type":{"id":15,"text":"Index Page"},"url":"https://earthzine.org/2017/03/20/landfire-2015-remap-utilization-of-remotely-sensed-data-to-classify-existing-vegetation-type-and-structure-to-support-strategic-planning-and-tactical-response/"}],"volume":"March 2017","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a38e4b063d5d30980ec","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717222,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195841,"text":"70195841 - 2017 - Antarctic ice-core water (USGS49) – A new isotopic reference material for δ2H and δ18O measurements of water","interactions":[],"lastModifiedDate":"2018-03-06T11:04:55","indexId":"70195841","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Antarctic ice-core water (USGS49) – A new isotopic reference material for δ<i>2</i>H and δ<i>18</i>O measurements of water","title":"Antarctic ice-core water (USGS49) – A new isotopic reference material for δ2H and δ18O measurements of water","docAbstract":"<p><span>As a result of the scarcity of isotopic reference waters for daily use, a new secondary isotopic reference material for international distribution has been prepared from ice-core water from the Amundsen–Scott South Pole Station. This isotopic reference material, designated as USGS49, was filtered, homogenised, loaded into glass ampoules, sealed with a torch, autoclaved to eliminate biological activity and measured by dual-inlet isotope-ratio mass spectrometry. The δ</span><sup>2</sup><span>H and δ</span><sup>18</sup><span>O values of USGS49 are −394.7&nbsp;±&nbsp;0.4 and −50.55&nbsp;±&nbsp;0.04&nbsp;mUr (where mUr&nbsp;=&nbsp;0.001&nbsp;=&nbsp;‰), respectively, relative to VSMOW, on scales normalised such that the δ</span><sup>2</sup><span>H and δ</span><sup>18</sup><span>O values of SLAP reference water are, respectively, −428 and −55.5&nbsp;mUr. Each uncertainty is an estimated expanded uncertainty (</span><i>U&nbsp;</i><span>=</span><i>&nbsp;</i><span>2</span><i>u</i><sub>c</sub><span>) about the reference value that provides an interval that has about a 95% probability of encompassing the true value. This isotopic reference material is intended as one of two isotopic reference waters for daily normalisation of stable hydrogen and oxygen isotopic analysis of water with an isotope-ratio mass spectrometer or a laser absorption spectrometer. It is available by the case of 144 glass ampoules or as a set of sixteen glass ampoules containing 5&nbsp;ml of water in each ampoule.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ggr.12135","usgsCitation":"Lorenz, J.M., Qi, H., and Coplen, T.B., 2017, Antarctic ice-core water (USGS49) – A new isotopic reference material for δ2H and δ18O measurements of water: Geostandards and Geoanalytical Research, v. 41, no. 1, p. 63-68, https://doi.org/10.1111/ggr.12135.","productDescription":"6 p.","startPage":"63","endPage":"68","ipdsId":"IP-077712","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352252,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"5afee8b9e4b0da30c1bfc494","contributors":{"authors":[{"text":"Lorenz, Jennifer M. 0000-0002-5826-7264 jlorenz@usgs.gov","orcid":"https://orcid.org/0000-0002-5826-7264","contributorId":3558,"corporation":false,"usgs":true,"family":"Lorenz","given":"Jennifer","email":"jlorenz@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":730257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":730258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":730259,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192069,"text":"70192069 - 2017 - When perception reflects reality: Non-native grass invasion alters small mammal risk landscapes and survival","interactions":[],"lastModifiedDate":"2017-10-19T13:52:07","indexId":"70192069","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"When perception reflects reality: Non-native grass invasion alters small mammal risk landscapes and survival","docAbstract":"<p><span>Modification of habitat structure due to invasive plants can alter the risk landscape for wildlife by, for example, changing the quality or availability of refuge habitat. Whether perceived risk corresponds with actual fitness outcomes, however, remains an important open question. We simultaneously measured how habitat changes due to a common invasive grass (cheatgrass,&nbsp;</span><i>Bromus tectorum</i><span>) affected the perceived risk, habitat selection, and apparent survival of a small mammal, enabling us to assess how well perceived risk influenced important behaviors and reflected actual risk. We measured perceived risk by nocturnal rodents using a giving-up density foraging experiment with paired shrub (safe) and open (risky) foraging trays in cheatgrass and native habitats. We also evaluated microhabitat selection across a cheatgrass gradient as an additional assay of perceived risk and behavioral responses for deer mice (</span><i>Peromyscus maniculatus</i><span>) at two spatial scales of habitat availability. Finally, we used mark-recapture analysis to quantify deer mouse apparent survival across a cheatgrass gradient while accounting for detection probability and other habitat features. In the foraging experiment, shrubs were more important as protective cover in cheatgrass-dominated habitats, suggesting that cheatgrass increased perceived predation risk. Additionally, deer mice avoided cheatgrass and selected shrubs, and marginally avoided native grass, at two spatial scales. Deer mouse apparent survival varied with a cheatgrass–shrub interaction, corresponding with our foraging experiment results, and providing a rare example of a native plant mediating the effects of an invasive plant on wildlife. By synthesizing the results of three individual lines of evidence (foraging behavior, habitat selection, and apparent survival), we provide a rare example of linkage between behavioral responses of animals indicative of perceived predation risk and actual fitness outcomes. Moreover, our results suggest that exotic grass invasions can influence wildlife populations by altering risk landscapes and survival.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2785","usgsCitation":"Ceradnini, J.P., and Chalfoun, A.D., 2017, When perception reflects reality: Non-native grass invasion alters small mammal risk landscapes and survival: Ecology and Evolution, v. 7, no. 6, p. 1823-1835, https://doi.org/10.1002/ece3.2785.","productDescription":"13 p.","startPage":"1823","endPage":"1835","ipdsId":"IP-073821","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2785","text":"Publisher Index Page"},{"id":346981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Thunder Basin National Grassland","volume":"7","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"59e9b996e4b05fe04cd65ca7","contributors":{"authors":[{"text":"Ceradnini, Joseph P.","contributorId":197675,"corporation":false,"usgs":false,"family":"Ceradnini","given":"Joseph","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":714060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714059,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70190053,"text":"70190053 - 2017 - Unusual geologic evidence of coeval seismic shaking and tsunamis shows variability in earthquake size and recurrence in the area of the giant 1960 Chile earthquake","interactions":[],"lastModifiedDate":"2017-08-08T10:52:14","indexId":"70190053","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Unusual geologic evidence of coeval seismic shaking and tsunamis shows variability in earthquake size and recurrence in the area of the giant 1960 Chile earthquake","docAbstract":"<p>An uncommon coastal sedimentary record combines evidence for seismic shaking and coincident tsunami inundation since AD 1000 in the region of the largest earthquake recorded instrumentally: the giant 1960 southern Chile earthquake (Mw 9.5). The record reveals significant variability in the size and recurrence of megathrust earthquakes and ensuing tsunamis along this part of the Nazca-South American plate boundary. A 500-m long coastal outcrop on Isla Chiloé, midway along the 1960 rupture, provides continuous exposure of soil horizons buried locally by debris-flow diamicts and extensively by tsunami sand sheets. The diamicts flattened plants that yield geologically precise ages to correlate with well-dated evidence elsewhere. The 1960 event was preceded by three earthquakes that probably resembled it in their effects, in AD 898 - 1128, 1300 - 1398 and 1575, and by five relatively smaller intervening earthquakes. Earthquakes and tsunamis recurred exceptionally often between AD 1300 and 1575. Their average recurrence interval of 85 years only slightly exceeds the time already elapsed since 1960. This inference is of serious concern because no earthquake has been anticipated in the region so soon after the 1960 event, and current plate locking suggests that some segments of the boundary are already capable of producing large earthquakes. This long-term earthquake and tsunami history of one of the world's most seismically active subduction zones provides an example of variable rupture mode, in which earthquake size and recurrence interval vary from one earthquake to the next.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.12.007","usgsCitation":"Cisternas, M., Garrett, E., Wesson, R.L., Dura, T., and Ely, L.L., 2017, Unusual geologic evidence of coeval seismic shaking and tsunamis shows variability in earthquake size and recurrence in the area of the giant 1960 Chile earthquake: Marine Geology, v. 385, no. 1 March 2017, p. 101-113, https://doi.org/10.1016/j.margeo.2016.12.007.","productDescription":"13 p.","startPage":"101","endPage":"113","ipdsId":"IP-083320","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470047,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/file/1364141/1/Accepted%20Journal%20Article","text":"External Repository"},{"id":344645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://ars.els-cdn.com/content/image/1-s2.0-S0025322716X00138-cov150h.gif"}],"geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.619140625,\n              -43.46089378008257\n            ],\n            [\n              -73.19091796875,\n              -43.46089378008257\n            ],\n            [\n              -73.19091796875,\n              -41.73033005046652\n            ],\n            [\n              -74.619140625,\n              -41.73033005046652\n            ],\n            [\n              -74.619140625,\n              -43.46089378008257\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"385","issue":"1 March 2017","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"598acddce4b09fa1cb0e13db","contributors":{"authors":[{"text":"Cisternas, M.","contributorId":193403,"corporation":false,"usgs":false,"family":"Cisternas","given":"M.","email":"","affiliations":[],"preferred":false,"id":707338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garrett, E","contributorId":195524,"corporation":false,"usgs":false,"family":"Garrett","given":"E","email":"","affiliations":[],"preferred":false,"id":707339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wesson, Robert L. 0000-0003-2702-0012 rwesson@usgs.gov","orcid":"https://orcid.org/0000-0003-2702-0012","contributorId":850,"corporation":false,"usgs":true,"family":"Wesson","given":"Robert","email":"rwesson@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":707340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dura, T.","contributorId":193399,"corporation":false,"usgs":false,"family":"Dura","given":"T.","affiliations":[],"preferred":false,"id":707341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ely, L. 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