{"pageNumber":"1071","pageRowStart":"26750","pageSize":"25","recordCount":184743,"records":[{"id":70184965,"text":"70184965 - 2016 - Late Oligocene to present contractional structure in and around the Susitna basin, Alaska—Geophysical evidence and geological implications","interactions":[],"lastModifiedDate":"2018-06-19T19:20:30","indexId":"70184965","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Late Oligocene to present contractional structure in and around the Susitna basin, Alaska—Geophysical evidence and geological implications","docAbstract":"<p><span>The Cenozoic Susitna basin lies within an enigmatic lowland surrounded by the Central Alaska Range, Western Alaska Range (including the Tordrillo Mountains), and Talkeetna Mountains in south-central Alaska. Some previous interpretations show normal faults as the defining structures of the basin (e.g., Kirschner, 1994). However, analysis of new and existing geophysical data shows predominantly (Late Oligocene to present) thrust and reverse fault geometries in the region, as previously proposed by Hackett (1978). A key example is the Beluga Mountain fault where a 50-mGal gravity gradient, caused by the density transition from the igneous bedrock of Beluga Mountain to the &gt;4-km-thick Cenozoic sedimentary section of Susitna basin, spans a horizontal distance of ∼40 km and straddles the topographic front. The location and shape of the gravity gradient preclude a normal fault geometry; instead, it is best explained by a southwest-dipping thrust fault, with its leading edge located several kilometers to the northeast of the mountain front, concealed beneath the shallow glacial and fluvial cover deposits. Similar contractional fault relationships are observed for other basin-bounding and regional faults as well. Contractional structures are consistent with a regional shortening strain field inferred from differential offsets on the Denali and Castle Mountain right-lateral strike-slip fault systems.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01279.1","usgsCitation":"Saltus, R.W., Stanley, R.G., Haeussler, P.J., Jones, J.V., Potter, C.J., and Lewis, K.A., 2016, Late Oligocene to present contractional structure in and around the Susitna basin, Alaska—Geophysical evidence and geological implications: Geosphere, v. 12, no. 5, p. 1378-1390, https://doi.org/10.1130/GES01279.1.","productDescription":"13 p.","startPage":"1378","endPage":"1390","ipdsId":"IP-078088","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":470536,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01279.1","text":"Publisher Index Page"},{"id":337619,"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              -153,\n              61\n            ],\n            [\n              -147,\n              61\n            ],\n            [\n              -147,\n              63\n            ],\n            [\n              -153,\n              63\n            ],\n            [\n              -153,\n              61\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-11","publicationStatus":"PW","scienceBaseUri":"58ca52cee4b0849ce97c86ae","contributors":{"authors":[{"text":"Saltus, Richard W. saltus@usgs.gov","contributorId":777,"corporation":false,"usgs":true,"family":"Saltus","given":"Richard","email":"saltus@usgs.gov","middleInitial":"W.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":683725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":683726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":683727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":683728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Potter, Christopher J. 0000-0002-2300-6670 cpotter@usgs.gov","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":1026,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","email":"cpotter@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":683729,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewis, Kristen A. 0000-0003-4991-3399 klewis@usgs.gov","orcid":"https://orcid.org/0000-0003-4991-3399","contributorId":4120,"corporation":false,"usgs":true,"family":"Lewis","given":"Kristen","email":"klewis@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":683730,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70189513,"text":"70189513 - 2016 - Estimating mercury emissions resulting from wildfire in forests of the Western United States","interactions":[],"lastModifiedDate":"2018-08-07T12:28:27","indexId":"70189513","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Estimating mercury emissions resulting from wildfire in forests of the Western United States","docAbstract":"<p><span>Understanding the emissions of mercury (Hg) from wildfires is important for quantifying the global atmospheric Hg sources. Emissions of Hg from soils resulting from wildfires in the Western United States was estimated for the 2000 to 2013 period, and the potential emission of Hg from forest soils was assessed as a function of forest type and soil-heating. Wildfire released an annual average of 3100</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>1900</span><span>&nbsp;</span><span>kg-Hg</span><span>&nbsp;</span><span>y</span><sup>−&nbsp;1</sup><span><span>&nbsp;</span>for the years spanning 2000–2013 in the 11 states within the study area. This estimate is nearly 5-fold lower than previous estimates for the study region. Lower emission estimates are attributed to an inclusion of fire severity within burn perimeters. Within reported wildfire perimeters, the average distribution of low, moderate, and high severity burns was 52, 29, and 19% of the total area, respectively. Review of literature data suggests that that low severity burning does not result in soil heating, moderate severity fire results in shallow soil heating, and high severity fire results in relatively deep soil heating (&lt;</span><span>&nbsp;</span><span>5</span><span>&nbsp;</span><span>cm). Using this approach, emission factors for high severity burns ranged from 58 to 640</span><span>&nbsp;</span><span>μg-Hg</span><span>&nbsp;</span><span>kg-fuel</span><sup>−&nbsp;1</sup><span>. In contrast, low severity burns have emission factors that are estimated to be only 18–34</span><span>&nbsp;</span><span>μg-Hg</span><span>&nbsp;</span><span>kg-fuel</span><sup>−&nbsp;1</sup><span>. In this estimate, wildfire is predicted to release 1–30</span><span>&nbsp;</span><span>g</span><span>&nbsp;</span><span>Hg</span><span>&nbsp;</span><span>ha</span><sup>−&nbsp;1</sup><span><span>&nbsp;</span>from Western United States forest soils while above ground fuels are projected to contribute an additional 0.9 to 7.8</span><span>&nbsp;</span><span>g</span><span>&nbsp;</span><span>Hg</span><span>&nbsp;</span><span>ha</span><sup>−&nbsp;1</sup><span>. Land cover types with low biomass (desert scrub) are projected to release less than 1</span><span>&nbsp;</span><span>g</span><span>&nbsp;</span><span>Hg</span><span>&nbsp;</span><span>ha</span><sup>−&nbsp;1</sup><span>. Following soil sources, fuel source contributions to total Hg emissions generally followed the order of duff</span><span>&nbsp;</span><span>&gt;</span><span>&nbsp;</span><span>wood</span><span>&nbsp;</span><span>&gt;</span><span>&nbsp;</span><span>foliage</span><span>&nbsp;</span><span>&gt;</span><span>&nbsp;</span><span>litter</span><span>&nbsp;</span><span>&gt;</span><span>&nbsp;</span><span>branches.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.01.166","usgsCitation":"Webster, J., Kane, T., Obrist, D., Ryan, J.N., and Aiken, G.R., 2016, Estimating mercury emissions resulting from wildfire in forests of the Western United States: Science of Total Environment, v. 568, p. 578-586, https://doi.org/10.1016/j.scitotenv.2016.01.166.","productDescription":"9 p.","startPage":"578","endPage":"586","ipdsId":"IP-071233","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.01.166","text":"Publisher Index Page"},{"id":343855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d82be4b0d1f9f060a188","contributors":{"authors":[{"text":"Webster, Jackson","contributorId":172157,"corporation":false,"usgs":false,"family":"Webster","given":"Jackson","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":704982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kane, Tyler J. 0000-0003-2511-7312","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":194675,"corporation":false,"usgs":false,"family":"Kane","given":"Tyler J.","affiliations":[],"preferred":false,"id":704983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obrist, Daniel","contributorId":172155,"corporation":false,"usgs":false,"family":"Obrist","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":704984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":704985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704986,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191951,"text":"70191951 - 2016 - A Lota lota consumption: Trophic dynamics of nonnative Burbot in a valuable sport fishery","interactions":[],"lastModifiedDate":"2017-10-19T11:25:32","indexId":"70191951","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"A Lota lota consumption: Trophic dynamics of nonnative Burbot in a valuable sport fishery","docAbstract":"<p><span>Unintentional and illegal introductions of species disrupt food webs and threaten the success of managed sport fisheries. Although many populations of Burbot&nbsp;</span><i>Lota lota</i><span><span>&nbsp;</span>are declining in the species’ native range, a nonnative population recently expanded into Flaming Gorge Reservoir (FGR), Wyoming–Utah, and threatens to disrupt predator–prey interactions within this popular sport fishery. To determine potential impacts on sport fishes, especially trophy Lake Trout<span>&nbsp;</span></span><i>Salvelinus namaycush</i><span>, we assessed the relative abundance of Burbot and quantified the potential trophic or food web impacts of this population by using diet, stable isotope, and bioenergetic analyses. We did not detect a significant potential for food resource competition between Burbot and Lake Trout (Schoener’s overlap index = 0.13), but overall consumption by Burbot likely affects other sport fishes, as indicated by our analyses of trophic niche space. Diet analyses suggested that crayfish were important diet items across time (89.3% of prey by weight in autumn; 49.4% in winter) and across Burbot size-classes (small: 77.5% of prey by weight; medium: 76.6%; large: 39.7%). However, overall consumption by Burbot increases as water temperatures cool, and fish consumption by Burbot in FGR was observed to increase during winter. Specifically, large Burbot consumed more salmonids, and we estimated (bioenergetically) that up to 70% of growth occurred in late autumn and winter. Further, our population-wide consumption estimates indicated that Burbot could consume up to double the biomass of Rainbow Trout<span>&nbsp;</span></span><i>Oncorhynchus mykiss</i><span><span>&nbsp;</span>stocked annually (&gt;1.3 × 10</span><sup>5</sup><span><span>&nbsp;</span>kg; &gt;1 million individuals) into FGR. Overall, we provide some of the first information regarding Burbot trophic interactions outside of the species’ native range; these findings can help to inform the management of sport fisheries if Burbot range expansion occurs elsewhere.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1227372","usgsCitation":"Klobucar, S., Saunders, W.C., and Budy, P., 2016, A Lota lota consumption: Trophic dynamics of nonnative Burbot in a valuable sport fishery: Transactions of the American Fisheries Society, v. 145, no. 6, p. 1386-1398, https://doi.org/10.1080/00028487.2016.1227372.","productDescription":"13 p.","startPage":"1386","endPage":"1398","ipdsId":"IP-074691","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah, Wyoming","otherGeospatial":"Flaming Gorge Reservoir","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.74517822265624,\n              40.875103022165824\n            ],\n            [\n              -109.35516357421874,\n              40.875103022165824\n            ],\n            [\n              -109.35516357421874,\n              41.52297326747377\n            ],\n            [\n              -109.74517822265624,\n              41.52297326747377\n            ],\n            [\n              -109.74517822265624,\n              40.875103022165824\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"145","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-14","publicationStatus":"PW","scienceBaseUri":"59e9b997e4b05fe04cd65ccf","contributors":{"authors":[{"text":"Klobucar, Stephen L.","contributorId":172291,"corporation":false,"usgs":false,"family":"Klobucar","given":"Stephen L.","affiliations":[],"preferred":false,"id":713937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saunders, W. Carl","contributorId":46883,"corporation":false,"usgs":true,"family":"Saunders","given":"W.","email":"","middleInitial":"Carl","affiliations":[],"preferred":false,"id":713938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713775,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182777,"text":"70182777 - 2016 - Inferring invasive species abundance using removal data from management actions","interactions":[],"lastModifiedDate":"2017-03-01T12:32:34","indexId":"70182777","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Inferring invasive species abundance using removal data from management actions","docAbstract":"<p><span>Evaluation of the progress of management programs for invasive species is crucial for demonstrating impacts to stakeholders and strategic planning of resource allocation. Estimates of abundance before and after management activities can serve as a useful metric of population management programs. However, many methods of estimating population size are too labor intensive and costly to implement, posing restrictive levels of burden on operational programs. Removal models are a reliable method for estimating abundance before and after management using data from the removal activities exclusively, thus requiring no work in addition to management. We developed a Bayesian hierarchical model to estimate abundance from removal data accounting for varying levels of effort, and used simulations to assess the conditions under which reliable population estimates are obtained. We applied this model to estimate site-specific abundance of an invasive species, feral swine (</span><i>Sus scrofa</i><span>), using removal data from aerial gunning in 59 site/time-frame combinations (480–19,600 acres) throughout Oklahoma and Texas, USA. Simulations showed that abundance estimates were generally accurate when effective removal rates (removal rate accounting for total effort) were above 0.40. However, when abundances were small (&lt;50) the effective removal rate needed to accurately estimates abundances was considerably higher (0.70). Based on our post-validation method, 78% of our site/time frame estimates were accurate. To use this modeling framework it is important to have multiple removals (more than three) within a time frame during which demographic changes are minimized (i.e., a closed population; ≤3&nbsp;months for feral swine). Our results show that the probability of accurately estimating abundance from this model improves with increased sampling effort (8+ flight hours across the 3-month window is best) and increased removal rate. Based on the inverse relationship between inaccurate abundances and inaccurate removal rates, we suggest auxiliary information that could be collected and included in the model as covariates (e.g., habitat effects, differences between pilots) to improve accuracy of removal rates and hence abundance estimates.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.1383","usgsCitation":"Davis, A.J., Hooten, M., Miller, R.S., Farnsworth, M.L., Lewis, J., Moxcey, M., and Pepin, K., 2016, Inferring invasive species abundance using removal data from management actions: Ecological Applications, v. 26, no. 7, p. 2339-2346, https://doi.org/10.1002/eap.1383.","productDescription":"8 p.","startPage":"2339","endPage":"2346","ipdsId":"IP-067270","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":336748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500bb01","contributors":{"authors":[{"text":"Davis, Amy J.","contributorId":149854,"corporation":false,"usgs":false,"family":"Davis","given":"Amy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":680416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":673716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":680417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farnsworth, Matthew L.","contributorId":56473,"corporation":false,"usgs":false,"family":"Farnsworth","given":"Matthew","email":"","middleInitial":"L.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":680418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lewis, Jesse S.","contributorId":147540,"corporation":false,"usgs":false,"family":"Lewis","given":"Jesse S.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":680419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moxcey, Michael","contributorId":187442,"corporation":false,"usgs":false,"family":"Moxcey","given":"Michael","email":"","affiliations":[],"preferred":false,"id":680420,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pepin, Kim M. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":187441,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim M.","affiliations":[],"preferred":false,"id":680421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70193668,"text":"70193668 - 2016 - Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments","interactions":[],"lastModifiedDate":"2017-11-13T14:18:21","indexId":"70193668","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments","docAbstract":"<p><span>Conservation organizations worldwide are investing in climate change vulnerability assessments. Most vulnerability assessment methods focus on either landscape features or species traits that can affect a species vulnerability to climate change. However, landscape features and species traits likely interact to affect vulnerability. We compare a landscape-based assessment, a trait-based assessment, and an assessment that combines landscape variables and species traits for 113 species of birds, herpetofauna</span><span>, and mammals in the northeastern United States. Our aim is to better understand which species traits and landscape variables have the largest influence on assessment results and which types of vulnerability assessments are most useful for different objectives. Species traits were most important for determining which species will be most vulnerable to climate change. The sensitivity of species to dispersal barriers and the species average natal dispersal distance were the most important traits. Landscape features were most important for determining where species will be most vulnerable because species were most vulnerable in areas where multiple landscape features combined to increase vulnerability, regardless of species traits. The interaction between landscape variables and species traits was important when determining how to reduce climate change vulnerability. For example, an assessment that combines information on landscape connectivity, climate change velocity, and natal dispersal distance suggests that increasing landscape connectivity may not reduce the vulnerability of many species. Assessments that include landscape features and species traits will likely be most useful in guiding conservation under climate change.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2016.07.030","usgsCitation":"Nadeau, C.P., and Fuller, A.K., 2016, Combining landscape variables and species traits can improve the utility of climate change vulnerability assessments: Biological Conservation, v. 202, p. 30-38, https://doi.org/10.1016/j.biocon.2016.07.030.","productDescription":"9 p.","startPage":"30","endPage":"38","ipdsId":"IP-060118","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.70556640625,\n              37.996162679728116\n            ],\n            [\n              -66.70898437499999,\n              37.996162679728116\n            ],\n            [\n              -66.70898437499999,\n              47.68018294648414\n            ],\n            [\n              -80.70556640625,\n              47.68018294648414\n            ],\n            [\n              -80.70556640625,\n              37.996162679728116\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"202","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fcb7e4b06e28e9c24166","contributors":{"authors":[{"text":"Nadeau, Christopher P.","contributorId":105956,"corporation":false,"usgs":true,"family":"Nadeau","given":"Christopher","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":721844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719842,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178310,"text":"70178310 - 2016 - Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction","interactions":[],"lastModifiedDate":"2019-09-06T11:17:58","indexId":"70178310","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction","docAbstract":"Land subsidence includes both gentle downwarping and sudden sinking of\nsegments of the land surface. Major anthropogenic causes of land subsidence\nare extraction of fluids including water, oil, and gas. Measurement and detec-\ntion of land subsidence include both ground-based and remotely sensed air-\nborne and space-based methods. Methods for measurement of subsidence at\npoints include differential leveling, global positioning system surveys, and\nextensometers. Satellite-borne differential interferometric synthetic aperture\nradar and airborne LiDAR techniques can detect land-surface movement over\nwide areas of interest. Aquifer-system compaction and subsidence owing to\ngroundwater extraction typically occurs in areas of unconsolidated alluvial or\nbasin-fill aquifer systems comprising aquifers and aquitards. Approaches to\nanalyzing and modeling deformation of aquifer systems follow from the basic\nrelations  between  head,  stress,  compressibility,  and  groundwater  flow.\nAnalysis and simulation of aquifer-system compaction have been addressed\nprimarily using either an approach based on conventional groundwater flow\ntheory or an approach based on linear poroelasticity theory. Both approaches\nrely on the principle of effective stress outlined by Karl Terzaghi in 1925. In\nthe approach based on conventional groundwater flow theory, an aquitard\ndrainage model explains the compaction of fine grained material using the\nprinciple of effective stress and theory of hydrodynamic lag. Packages for the\nwidely-used MODFLOW groundwater model are available to simulate aqui-\nfer-system  compaction  and  land  subsidence  using  the  aquitard-drainage\napproach. Poroelasticity theory describes the more fully coupled processes of\ngroundwater flow and three-dimensional deformation of aquifer systems.\nThe general theory accounts for compressible fluid, porous matrix and solid\ngrains. Simulation codes using the poroelastic theory include some commer-\ncial software products and a few research codes.","largerWorkTitle":"Handbook of applied hydrology","language":"English","publisher":"McGraw-Hill Education","isbn":"9780071835091","usgsCitation":"Galloway, D.L., and Leake, S.A., 2016, Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction, chap. <i>of</i> Handbook of applied hydrology, p. 56.1-56.11.","productDescription":"11 p.","startPage":"56.1","endPage":"56.11","ipdsId":"IP-066741","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":337768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58cba41ae4b0849ce97dc744","contributors":{"editors":[{"text":"Singh, Vijay P.","contributorId":176741,"corporation":false,"usgs":false,"family":"Singh","given":"Vijay","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":684832,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":653592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leake, Stanley A. 0000-0003-3568-2542 saleake@usgs.gov","orcid":"https://orcid.org/0000-0003-3568-2542","contributorId":1846,"corporation":false,"usgs":true,"family":"Leake","given":"Stanley","email":"saleake@usgs.gov","middleInitial":"A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653593,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70182773,"text":"70182773 - 2016 - The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption","interactions":[],"lastModifiedDate":"2017-03-01T14:43:11","indexId":"70182773","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption","docAbstract":"The June 6, 1912 eruption of more than 13 km3 of dense rock equivalent (DRE) magma at Novarupta vent, Alaska was the largest of the 20th century. It ejected >7 km3 of rhyolite, ~1.3 km3 of andesite and ~4.6 km3 of dacite. Early ideas about the origin of pyroclastic flows and magmatic differentiation (e.g., compositional zonation of reservoirs) were shaped by this eruption. Despite being well studied, the timing of events that led to the chemically and mineralogically zoned magma reservoir remain poorly known. Here we provide new insights using the textures and chemical compositions of plagioclase and orthopyroxene crystals and by reevaluating previous U-Th isotope data. Compositional zoning of the magma reservoir likely developed a few thousand years before the eruption by several additions of mafic magma below an extant silicic reservoir. Melt compositions calculated from Sr contents in plagioclase fill the compositional gap between 68 and 76% SiO2 in whole pumice clasts, consistent with uninterrupted crystal growth from a continuum of liquids. Thus, our findings support a general model in which large volumes of crystal-poor rhyolite are related to intermediate magmas through gradual separation of melt from crystal-rich mush. The rhyolite is incubated by, but not mixed with, episodic recharge pulses of mafic magma that interact thermochemically with the mush and intermediate magmas. Hot, Mg-, Ca-, and Al-rich mafic magma intruded into, and mixed with, deeper parts of the reservoir (andesite and dacite) multiple times. Modeling the relaxation of the Fe-Mg concentrations in orthopyroxene and Mg in plagioclase rims indicates that the final recharge event occurred just weeks prior to the eruption. Rapid addition of mass, volatiles, and heat from the recharge magma, perhaps aided by partial melting of cumulate mush below the andesite and dacite, pressurized the reservoir and likely propelled a ~10 km lateral dike that allowed the overlying rhyolite to reach the surface.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.07.015","usgsCitation":"Singer, B.S., Costa, F., Herrin, J.S., Hildreth, W., and Fierstein, J., 2016, The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption: Earth and Planetary Science Letters, v. 451, p. 125-137, https://doi.org/10.1016/j.epsl.2016.07.015.","productDescription":"13 p. ","startPage":"125","endPage":"137","ipdsId":"IP-078234","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.07.015","text":"Publisher Index Page"},{"id":336778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"451","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500bb03","contributors":{"authors":[{"text":"Singer, Brad S.","contributorId":184168,"corporation":false,"usgs":false,"family":"Singer","given":"Brad","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":673704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrin, Jason S.","contributorId":184170,"corporation":false,"usgs":false,"family":"Herrin","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":680460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":673707,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70188153,"text":"70188153 - 2016 - Lateral and subsurface flows impact arctic coastal plain lake water budgets","interactions":[],"lastModifiedDate":"2018-10-25T16:43:24","indexId":"70188153","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Lateral and subsurface flows impact arctic coastal plain lake water budgets","docAbstract":"<p><span>Arctic thaw lakes are an important source of water for aquatic ecosystems, wildlife, and humans. Many recent studies have observed changes in Arctic surface waters related to climate warming and permafrost thaw; however, explaining the trends and predicting future responses to warming is difficult without a stronger fundamental understanding of Arctic lake water budgets. By measuring and simulating surface and subsurface hydrologic fluxes, this work quantified the water budgets of three lakes with varying levels of seasonal drainage, and tested the hypothesis that lateral and subsurface flows are a major component of the post-snowmelt water budgets. A water budget focused only on post-snowmelt surface water fluxes (stream discharge, precipitation, and evaporation) could not close the budget for two of three lakes, even when uncertainty in input parameters was rigorously considered using a Monte Carlo approach. The water budgets indicated large, positive residuals, consistent with up to 70% of mid-summer inflows entering lakes from lateral fluxes. Lateral inflows and outflows were simulated based on three processes; supra-permafrost subsurface inflows from basin-edge polygonal ground, and exchange between seasonally drained lakes and their drained margins through runoff and evapotranspiration. Measurements and simulations indicate that rapid subsurface flow through highly conductive flowpaths in the polygonal ground can explain the majority of the inflow. Drained lakes were hydrologically connected to marshy areas on the lake margins, receiving water from runoff following precipitation and losing up to 38% of lake efflux to drained margin evapotranspiration. Lateral fluxes can be a major part of Arctic thaw lake water budgets and a major control on summertime lake water levels. Incorporating these dynamics into models will improve our ability to predict lake volume changes, solute fluxes, and habitat availability in the changing Arctic.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.10917","usgsCitation":"Koch, J.C., 2016, Lateral and subsurface flows impact arctic coastal plain lake water budgets: Hydrological Processes, v. 30, no. 21, p. 3918-3931, https://doi.org/10.1002/hyp.10917.","productDescription":"14 p.","startPage":"3918","endPage":"3931","ipdsId":"IP-064008","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":342033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"30","issue":"21","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-21","publicationStatus":"PW","scienceBaseUri":"59327926e4b0e9bd0eab5513","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":696929,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70189238,"text":"70189238 - 2016 - Inter-comparison of three-dimensional models of volcanic plumes","interactions":[],"lastModifiedDate":"2017-07-06T13:11:53","indexId":"70189238","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Inter-comparison of three-dimensional models of volcanic plumes","docAbstract":"<p><span>We performed an inter-comparison study of three-dimensional models of volcanic plumes. A set of common volcanological input parameters and meteorological conditions were provided for two kinds of eruptions, representing a weak and a strong eruption column. From the different models, we compared the maximum plume height, neutral buoyancy level (where plume density equals that of the atmosphere), and level of maximum radial spreading of the umbrella cloud. We also compared the vertical profiles of eruption column properties, integrated across cross-sections of the plume (integral variables). Although the models use different numerical procedures and treatments of subgrid turbulence and particle dynamics, the inter-comparison shows qualitatively consistent results. In the weak plume case (mass eruption rate 1.5</span><span>&nbsp;</span><span>×</span><span>&nbsp;</span><span>10</span><sup>6</sup><span>&nbsp;</span><span>kg</span><span>&nbsp;</span><span>s</span><sup>−&nbsp;1</sup><span>), the vertical profiles of plume properties (e.g., vertical velocity, temperature) are similar among models, especially in the buoyant plume region. Variability among the simulated maximum heights is ~</span><span>&nbsp;</span><span>20%, whereas neutral buoyancy level and level of maximum radial spreading vary by ~</span><span>&nbsp;</span><span>10%. Time-averaging of the three-dimensional (3D) flow fields indicates an effective entrainment coefficient around 0.1 in the buoyant plume region, with much lower values in the jet region, which is consistent with findings of small-scale laboratory experiments. On the other hand, the strong plume case (mass eruption rate 1.5</span><span>&nbsp;</span><span>×</span><span>&nbsp;</span><span>10</span><sup>9</sup><span>&nbsp;</span><span>kg</span><span>&nbsp;</span><span>s</span><sup>−&nbsp;1</sup><span>) shows greater variability in the vertical plume profiles predicted by the different models. Our analysis suggests that the unstable flow dynamics in the strong plume enhances differences in the formulation and numerical solution of the models. This is especially evident in the overshooting top of the plume, which extends a significant portion (~</span><span>&nbsp;</span><span>1/8) of the maximum plume height. Nonetheless, overall variability in the spreading level and neutral buoyancy level is ~</span><span>&nbsp;</span><span>20%, whereas that of maximum height is ~</span><span>&nbsp;</span><span>10%. This inter-comparison study has highlighted the different capabilities of 3D volcanic plume models, and identified key features of weak and strong plumes, including the roles of jet stability, entrainment efficiency, and particle non-equilibrium, which deserve future investigation in field, laboratory, and numerical studies.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.06.011","usgsCitation":"Suzuki, Y., Costa, A., Cerminara, M., Esposti Ongaro, T., Herzog, M., Van Eaton, A.R., and Denby, L., 2016, Inter-comparison of three-dimensional models of volcanic plumes: Journal of Volcanology and Geothermal Research, v. 326, p. 26-42, https://doi.org/10.1016/j.jvolgeores.2016.06.011.","productDescription":"17 p.","startPage":"26","endPage":"42","ipdsId":"IP-071593","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470540,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17863/cam.1638","text":"External Repository"},{"id":343414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"326","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595f4c3ee4b0d1f9f057e345","contributors":{"authors":[{"text":"Suzuki, Yujiro","contributorId":194289,"corporation":false,"usgs":false,"family":"Suzuki","given":"Yujiro","email":"","affiliations":[],"preferred":false,"id":703662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Antonio","contributorId":194290,"corporation":false,"usgs":false,"family":"Costa","given":"Antonio","email":"","affiliations":[{"id":27088,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV)","active":true,"usgs":false}],"preferred":false,"id":703663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cerminara, Matteo","contributorId":194291,"corporation":false,"usgs":false,"family":"Cerminara","given":"Matteo","email":"","affiliations":[],"preferred":false,"id":703664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esposti Ongaro, Tomaso","contributorId":194292,"corporation":false,"usgs":false,"family":"Esposti Ongaro","given":"Tomaso","email":"","affiliations":[],"preferred":false,"id":703665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herzog, Michael","contributorId":194293,"corporation":false,"usgs":false,"family":"Herzog","given":"Michael","email":"","affiliations":[],"preferred":false,"id":703666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":703661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Denby, Leif","contributorId":194294,"corporation":false,"usgs":false,"family":"Denby","given":"Leif","email":"","affiliations":[],"preferred":false,"id":703667,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70178430,"text":"70178430 - 2016 - Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","interactions":[],"lastModifiedDate":"2017-04-19T11:49:02","indexId":"70178430","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","docAbstract":"The east-central Great Basin near the Utah-Nevada border contains two great \ngroundwater flow systems.  The first, the White River regional groundwater \nflow system, consists of a string of hydraulically connected hydrographic basins \nin Nevada spanning about 270 miles from north to south.  The northernmost \nbasin is Long Valley and the southernmost basin is the Black Mountain area, a \nvalley bordering the Colorado River.  The general regional groundwater flow \ndirection is north to south. The second flow system, the Great Salt Lake Desert \nregional groundwater flow system, consists of hydrographic basins that straddle\nthe Utah-Nevada border, with a length of about 150 miles from north to south.  \nThe general regional groundwater flow direction is from south to north towards \nthe Great Salt Lake Desert.\n\nFor 15 years with support from the Southern Nevada Water Authority (SNWA), \nhydrologists, geologists, and geophysicists studied the basin connections and \nthe groundwater resources in these and adjacent flow systems over an area of \nabout 25,000 square miles. A major first part of the SNWA study was \nconstructing a 3-dimensional digital hydrogeologic framework based on \ngeologic maps and cross sections at 1:250,000 scale. This framework \ndocuments the presence of three major aquifers: (1) Paleozoic carbonate \nrocks, (2) Eocene to Miocene volcanic rocks, and (3) Miocene to Holocene \nbasin-fill sediments, as well as confining units that constrain flow. We \ninterpret that movement of most groundwater through and across basins is by \nfracture-dominated flow along faults/fractures, yet in most places flow is \nprevented or retarded across faults, so mapping structures gives a first \napproximation to conduits and barriers to flow.\n\nThe most important structures by far are high-angle normal faults of the \nbasin-range episode of east-west extensional deformation. This event \nbegan at about 20 Ma, although most deformation and the formation of the \npresent topography took place between 10 Ma and present.  This topography \nconsists of north-trending basins (mostly grabens) that alternate with north-\ntrending ranges (mostly horsts); erosion of the ranges filled the basins with \nclastic alluvial basin-fill deposits.\n\nGeophysics provides data on the third dimension (cross sections) of the \nhydrogeologic framework.  Audiomagnetotelluric profiles and gravity \ninversion located faults and enabled us to estimate thicknesses of basin-fill \ndeposits. To this framework, hydrologic studies addressed precipitation, \nsurface water, and springs, as well as groundwater levels, volumes, \ngeochemistry, water budgets, and monitoring. At nearly the same time as \nour study, the Utah Geological Survey (UGS) and U.S. Geological Survey \n(USGS) addressed the same issues in many of the same areas, and publication \nof the efforts by all three agencies reveals a surprising similarity of conclusions, \nwith some critical exceptions, which therefore demonstrates the great value of \nmany scientists independently studying the same complex scientific problem. \nThe differences in conclusions include directions and volumes of some ground-\nwater flow paths, such as one proposed by the USGS of unlikely groundwater \nflow from Steptoe Valley to southern Snake Valley, and another proposed by the \nUGS of unlikely significant groundwater recharge flow from the Snake Range to \nthe Fish Springs complex.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Resources and Geo- logy of Utah's West Desert","language":"English","publisher":"Utah Geologic Association","usgsCitation":"Rowley, P.D., Dixon, G.L., Watrus, J.M., Burns, A.G., Mankinen, E.A., McKee, E.H., Pari, K.T., Ekren, E.B., and Patrick, W.G., 2016, Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada, chap. <i>of</i> Resources and Geo- logy of Utah's West Desert, v. 45, p. 167-200.","productDescription":"34 p. ","startPage":"167","endPage":"200","ipdsId":"IP-073283","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":339955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339954,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.mapstore.utah.gov/uga45.html"}],"country":"United States","state":"Utah","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.046551,41.251716],[-111.046723,40.997959],[-110.750727,40.996847],[-110.715026,40.996347],[-110.539819,40.996346],[-110.500718,40.994746],[-110.375714,40.994947],[-110.250709,40.996089],[-110.237848,40.995427],[-110.125709,40.99655],[-110.121639,40.997101],[-110.048476,40.997555],[-110.006495,40.997815],[-110.000708,40.997352],[-109.999838,40.99733],[-109.97553,40.997912],[-109.855299,40.997614],[-109.854302,40.997661],[-109.715409,40.998191],[-109.713877,40.998266],[-109.676421,40.998395],[-109.534926,40.998143],[-109.500694,40.999127],[-109.250735,41.001009],[-109.231985,41.002059],[-109.173682,41.000859],[-109.050076,41.000659],[-109.048455,40.826081],[-109.049088,40.714562],[-109.048373,40.662602],[-109.048249,40.653601],[-109.048044,40.619231],[-109.050074,40.540358],[-109.049955,40.539901],[-109.050698,40.499963],[-109.050314,40.495092],[-109.050946,40.444368],[-109.050969,40.222662],[-109.050973,40.180849],[-109.050944,40.180712],[-109.050813,40.059579],[-109.050873,40.058915],[-109.050615,39.87497],[-109.05104,39.660472],[-109.051363,39.497674],[-109.050765,39.366677],[-109.051512,39.126095],[-109.052436,38.999985],[-109.053292,38.942878],[-109.053233,38.942467],[-109.053797,38.905284],[-109.053943,38.904414],[-109.054189,38.874984],[-109.057388,38.795456],[-109.059541,38.719888],[-109.060253,38.599328],[-109.059962,38.499987],[-109.060062,38.275489],[-109.054648,38.244921],[-109.041762,38.16469],[-109.041837,38.153022],[-109.04282,37.999301],[-109.042819,37.997068],[-109.043121,37.97426],[-109.041058,37.907236],[-109.041653,37.88117],[-109.041844,37.872788],[-109.041723,37.842051],[-109.041754,37.835826],[-109.041461,37.800105],[-109.042098,37.74999],[-109.041636,37.74021],[-109.04176,37.713182],[-109.041732,37.711214],[-109.042269,37.666067],[-109.042089,37.623795],[-109.042131,37.617662],[-109.041806,37.604171],[-109.041865,37.530726],[-109.041915,37.530653],[-109.043137,37.499992],[-109.043464,37.484711],[-109.04581,37.374993],[-109.046039,37.249993],[-109.045584,37.249351],[-109.045487,37.210844],[-109.045978,37.201831],[-109.045995,37.177279],[-109.045156,37.112064],[-109.045203,37.111958],[-109.045173,37.109464],[-109.045189,37.096271],[-109.044995,37.086429],[-109.045058,37.074661],[-109.045166,37.072742],[-109.045223,36.999084],[-109.181196,36.999271],[-109.233848,36.999266],[-109.246917,36.999346],[-109.26339,36.999263],[-109.268213,36.999242],[-109.270097,36.999266],[-109.378039,36.999135],[-109.381226,36.999148],[-109.495338,36.999105],[-109.625668,36.998308],[-109.875673,36.998504],[-110.000677,36.997968],[-110.000876,36.998502],[-110.021778,36.998602],[-110.47019,36.997997],[-110.490908,37.003566],[-110.50069,37.00426],[-110.599512,37.003448],[-110.625605,37.003416],[-110.62569,37.003721],[-110.75069,37.003197],[-111.066496,37.002389],[-111.133718,37.000779],[-111.254853,37.001077],[-111.278286,37.000465],[-111.405517,37.001497],[-111.405869,37.001481],[-111.412784,37.001478],[-112.35769,37.001025],[-112.368946,37.001125],[-112.534545,37.000684],[-112.538593,37.000674],[-112.540368,37.000669],[-112.545094,37.000734],[-112.558974,37.000692],[-112.609787,37.000753],[-112.899366,37.000319],[-112.966471,37.000219],[-113.965907,36.999976],[-113.965907,37.000025],[-114.0506,37.000396],[-114.051749,37.088434],[-114.051822,37.090976],[-114.052827,37.103961],[-114.051867,37.134292],[-114.052179,37.14711],[-114.051673,37.172368],[-114.051405,37.233854],[-114.051974,37.283848],[-114.051974,37.284511],[-114.0518,37.293044],[-114.0518,37.293548],[-114.051927,37.370459],[-114.051927,37.370734],[-114.051765,37.418083],[-114.052448,37.43144],[-114.052701,37.492014],[-114.052685,37.502513],[-114.052718,37.517264],[-114.052689,37.517859],[-114.052962,37.592783],[-114.052472,37.604776],[-114.051728,37.745997],[-114.051785,37.746249],[-114.05167,37.746958],[-114.051109,37.756276],[-114.049919,37.765586],[-114.048473,37.809861],[-114.049677,37.823645],[-114.049928,37.852508],[-114.049658,37.881368],[-114.050423,37.999961],[-114.049903,38.148601],[-114.050138,38.24996],[-114.049417,38.2647],[-114.05012,38.404536],[-114.050091,38.404673],[-114.050485,38.499955],[-114.049834,38.543784],[-114.049862,38.547764],[-114.050154,38.57292],[-114.049883,38.677365],[-114.049749,38.72921],[-114.049168,38.749951],[-114.049465,38.874949],[-114.048521,38.876197],[-114.048054,38.878693],[-114.049104,39.005509],[-114.047079,39.499943],[-114.047728,39.542742],[-114.047273,39.759413],[-114.047783,39.79416],[-114.047214,39.821024],[-114.047134,39.906037],[-114.046555,39.996899],[-114.046835,40.030131],[-114.046386,40.097896],[-114.046741,40.104231],[-114.046683,40.116931],[-114.046153,40.231971],[-114.046178,40.398313],[-114.045826,40.424823],[-114.045218,40.430282],[-114.045518,40.494474],[-114.045577,40.495801],[-114.045281,40.506586],[-114.043505,40.726292]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 \"}}]}","volume":"45","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877b8e4b0b7ea54521c18","contributors":{"editors":[{"text":"Comer, John B.","contributorId":147613,"corporation":false,"usgs":false,"family":"Comer","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":692018,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Inkenbrandt, Paul C.","contributorId":191156,"corporation":false,"usgs":false,"family":"Inkenbrandt","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692019,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Krahulec, K.A.","contributorId":42429,"corporation":false,"usgs":true,"family":"Krahulec","given":"K.A.","affiliations":[],"preferred":false,"id":692020,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Pinnell, Michael L.","contributorId":191157,"corporation":false,"usgs":false,"family":"Pinnell","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692021,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Rowley, Peter D.","contributorId":27435,"corporation":false,"usgs":true,"family":"Rowley","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":673660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dixon, Gary L.","contributorId":23571,"corporation":false,"usgs":true,"family":"Dixon","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":673661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watrus, James M.","contributorId":184152,"corporation":false,"usgs":false,"family":"Watrus","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Andrews G.","contributorId":184154,"corporation":false,"usgs":false,"family":"Burns","given":"Andrews","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":673664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKee, Edwin H. mckee@usgs.gov","contributorId":3728,"corporation":false,"usgs":true,"family":"McKee","given":"Edwin","email":"mckee@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":673665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pari, Keith T.","contributorId":184155,"corporation":false,"usgs":false,"family":"Pari","given":"Keith","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":673666,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ekren, E. Bartlett","contributorId":47644,"corporation":false,"usgs":true,"family":"Ekren","given":"E.","email":"","middleInitial":"Bartlett","affiliations":[],"preferred":false,"id":673667,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Patrick, William G.","contributorId":184151,"corporation":false,"usgs":false,"family":"Patrick","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673668,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70185023,"text":"70185023 - 2016 - Circumpolar distribution and carbon storage of thermokarst landscapes","interactions":[],"lastModifiedDate":"2017-03-14T13:44:37","indexId":"70185023","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Circumpolar distribution and carbon storage of thermokarst landscapes","docAbstract":"<p><span>Thermokarst is the process whereby the thawing of ice-rich permafrost ground causes land subsidence, resulting in development of distinctive landforms. Accelerated thermokarst due to climate change will damage infrastructure, but also impact hydrology, ecology and biogeochemistry. Here, we present a circumpolar assessment of the distribution of thermokarst landscapes, defined as landscapes comprised of current thermokarst landforms and areas susceptible to future thermokarst development. At 3.6 × 10</span><sup>6</sup><span> km</span><sup>2</sup><span>, thermokarst landscapes are estimated to cover </span><span class=\"stix\">∼</span><span>20% of the northern permafrost region, with approximately equal contributions from three landscape types where characteristic wetland, lake and hillslope thermokarst landforms occur. We estimate that approximately half of the below-ground organic carbon within the study region is stored in thermokarst landscapes. Our results highlight the importance of explicitly considering thermokarst when assessing impacts of climate change, including future landscape greenhouse gas emissions, and provide a means for assessing such impacts at the circumpolar scale.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/ncomms13043","usgsCitation":"Olefeldt, D., Goswami, S., Grosse, G., Hayes, D., Hugelius, G., Kuhry, P., McGuire, A.D., Romanovsky, V., Sannel, A.B., Schuur, E., and Turetsky, M., 2016, Circumpolar distribution and carbon storage of thermokarst landscapes: Nature Communications, v. 7, p. 1-11, https://doi.org/10.1038/ncomms13043.","productDescription":"Article number 13043; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-069482","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470527,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/ncomms13043","text":"Publisher Index Page"},{"id":337514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abcd3","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":684239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goswami, S.","contributorId":189252,"corporation":false,"usgs":false,"family":"Goswami","given":"S.","email":"","affiliations":[],"preferred":false,"id":684240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, G.","contributorId":82140,"corporation":false,"usgs":true,"family":"Grosse","given":"G.","affiliations":[],"preferred":false,"id":684241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, D.","contributorId":15275,"corporation":false,"usgs":true,"family":"Hayes","given":"D.","email":"","affiliations":[],"preferred":false,"id":684242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hugelius, G.","contributorId":27338,"corporation":false,"usgs":true,"family":"Hugelius","given":"G.","affiliations":[],"preferred":false,"id":684243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuhry, P.","contributorId":57277,"corporation":false,"usgs":false,"family":"Kuhry","given":"P.","affiliations":[],"preferred":false,"id":684244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":683987,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Romanovsky, V.E.","contributorId":54721,"corporation":false,"usgs":true,"family":"Romanovsky","given":"V.E.","email":"","affiliations":[],"preferred":false,"id":684245,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sannel, A. B. K.","contributorId":38450,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"B. K.","affiliations":[],"preferred":false,"id":684246,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schuur, E.A.G.","contributorId":106679,"corporation":false,"usgs":true,"family":"Schuur","given":"E.A.G.","affiliations":[],"preferred":false,"id":684247,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Turetsky, M.R.","contributorId":107470,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":684248,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70176901,"text":"70176901 - 2016 - Considerations for building climate-based species distribution models","interactions":[],"lastModifiedDate":"2016-10-20T14:11:27","indexId":"70176901","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Considerations for building climate-based species distribution models","docAbstract":"Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.","language":"English","publisher":"University of Florida IFAS Extension","usgsCitation":"Bucklin, D.N., Basille, M., Romanach, S.S., Brandt, L.A., Mazzotti, F., and Watling, J.I., 2016, Considerations for building climate-based species distribution models, 8 p.","productDescription":"8 p","ipdsId":"IP-075201","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":330262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":329494,"type":{"id":15,"text":"Index Page"},"url":"https://edis.ifas.ufl.edu/UW420"}],"publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5809d7c3e4b0f497e78fca5d","contributors":{"authors":[{"text":"Bucklin, David N.","contributorId":175273,"corporation":false,"usgs":false,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":650661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Basille, Mathieu","contributorId":175274,"corporation":false,"usgs":false,"family":"Basille","given":"Mathieu","email":"","affiliations":[],"preferred":false,"id":650662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":140419,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","email":"sromanach@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":650660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Laura A.","contributorId":146646,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":650663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":650664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watling, James I.","contributorId":175275,"corporation":false,"usgs":false,"family":"Watling","given":"James","email":"","middleInitial":"I.","affiliations":[{"id":27555,"text":"John Carroll University","active":true,"usgs":false}],"preferred":false,"id":650665,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70178043,"text":"70178043 - 2016 - Simulation modeling to explore the effects of length-based harvest regulations for <i>Ictalurus</i> fisheries","interactions":[],"lastModifiedDate":"2016-11-01T12:54:35","indexId":"70178043","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Simulation modeling to explore the effects of length-based harvest regulations for <i>Ictalurus</i> fisheries","docAbstract":"<p><span>Management of Blue Catfish </span><i>Ictalurus furcatus</i><span> and Channel Catfish </span><i>I. punctatus</i><span> for trophy production has recently become more common. Typically, trophy management is attempted with length-based regulations that allow for the moderate harvest of small fish but restrict the harvest of larger fish. However, the specific regulations used vary considerably across populations, and no modeling efforts have evaluated their effectiveness. We used simulation modeling to compare total yield, trophy biomass (</span><i>B<sub>trophy</sub></i><span>), and sustainability (spawning potential ratio [SPR] &gt; 0.30) of Blue Catfish and Channel Catfish populations under three scenarios: (1) current regulation (typically a length-based trophy regulation), (2) the best-performing minimum length regulation (MLR</span><i><sub>best</sub></i><span>), and (3) the best-performing length-based trophy catfish regulation (LTR</span><i><sub>best</sub></i><span>; “best performing” was defined as the regulation that maximized yield, </span><i>B<sub>trophy</sub></i><span>, and sustainability). The </span><i>B<sub>trophy</sub></i><span> produced did not differ among the three scenarios. For each fishery, the MLR</span><i><sub>best</sub></i><span> and LTR</span><i><sub>best</sub></i><span> produced greater yield (&gt;22% more) than the current regulation and maintained sustainability at higher finite exploitation rates (&gt;0.30) than the current regulation. The MLR</span><i><sub>best</sub></i><span> and LTR</span><i><sub>best</sub></i><span> produced similar yields and SPRs for Channel Catfish and similar yields for Blue Catfish; however, the MLR</span><i><sub>best</sub></i><span> for Blue Catfish produced more resilient fisheries (higher SPR) than the LTR</span><i><sub>best</sub></i><span>. Overall, the variation in yield, </span><i>B<sub>trophy</sub></i><span>, and SPR among populations was greater than the variation among regulations applied to any given population, suggesting that population-specific regulations may be preferable to regulations applied to geographic regions. We conclude that LTRs are useful for improving catfish yield and maintaining sustainability without overly restricting harvest but are not effective at increasing the </span><i>B<sub>trophy</sub></i><span> of catfish.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1204391","usgsCitation":"Stewart, D., Long, J.M., and Shoup, D.E., 2016, Simulation modeling to explore the effects of length-based harvest regulations for <i>Ictalurus</i> fisheries: North American Journal of Fisheries Management, v. 36, no. 5, p. 1190-1204, https://doi.org/10.1080/02755947.2016.1204391.","productDescription":"15 p.","startPage":"1190","endPage":"1204","ipdsId":"IP-068502","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":330607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-13","publicationStatus":"PW","scienceBaseUri":"5819a9c2e4b0bb36a4c91015","contributors":{"authors":[{"text":"Stewart, David R.","contributorId":141323,"corporation":false,"usgs":false,"family":"Stewart","given":"David R.","affiliations":[],"preferred":false,"id":652624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":652588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoup, Daniel E.","contributorId":141325,"corporation":false,"usgs":false,"family":"Shoup","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":652625,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192358,"text":"70192358 - 2016 - Book review: Foundations of wildlife diseases","interactions":[],"lastModifiedDate":"2017-10-25T10:33:08","indexId":"70192358","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Book review: Foundations of wildlife diseases","docAbstract":"<p><span>A new textbook for practitioners and students of wildlife disease is available. Rick Botzler and Richard Brown have provided an excellent addition to the wildlife disease literature with&nbsp;</span><i>Foundations of Wildlife Diseases</i><span>. It has been 8 years since the last major wildlife disease book (</span><a class=\"ref\" onclick=\"popRef2('i0090-3558-52-4-976-Wobeser1','','','' ); return false;\">Wobeser 2006</a><span>), and over 40 years since the first major wildlife disease compilation (</span><a class=\"ref\" onclick=\"popRef2('i0090-3558-52-4-976-Page1','','','' ); return false;\">Page 1975</a><span>), an edited summary of the 3rd International Wildlife Disease meeting in Munich, Germany. Many people interested in wildlife diseases have waited eagerly for this book, and they will not be disappointed.</span></p><p><span>Book information:&nbsp;<strong>Foundations of Wildlife Diseases.</strong><span><span>&nbsp;</span>By Richard G. Botzler and Richard N. Brown. University of California Press, Oakland, California, USA. 2014. 429 pp., viii preface material. ISBN: 9780520276093.&nbsp;</span></span></p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/0090-3558-52.4.976","usgsCitation":"van Riper, C., 2016, Book review: Foundations of wildlife diseases: Journal of Wildlife Diseases, v. 52, no. 4, p. 976-979, https://doi.org/10.7589/0090-3558-52.4.976.","productDescription":"4 p.","startPage":"976","endPage":"979","ipdsId":"IP-072993","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":347319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a7e4b0220bbd9d9f77","contributors":{"authors":[{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":715510,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70160312,"text":"70160312 - 2016 - Expert elicitation of population-level effects of disturbance","interactions":[],"lastModifiedDate":"2016-10-13T14:14:04","indexId":"70160312","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Expert elicitation of population-level effects of disturbance","docAbstract":"<p><span>Expert elicitation is a rigorous method for synthesizing expert knowledge to inform decision making and is reliable and practical when field data are limited. We evaluated the feasibility of applying expert elicitation to estimate population-level effects of disturbance on marine mammals. Diverse experts estimated parameters related to mortality and sublethal injury of North Atlantic right whales (</span><i class=\"EmphasisTypeItalic \">Eubalaena glacialis</i><span>). We are now eliciting expert knowledge on the movement of right whales among geographic regions to parameterize a spatial model of health. Expert elicitation complements methods such as simulation models or extrapolations from other species, sometimes with greater accuracy and less uncertainty.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The effects of noise on aquatic life II","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-1-4939-2981-8_35","usgsCitation":"Fleishman, E., Burgman, M., Runge, M.C., Schick, R.S., and Krauss, S., 2016, Expert elicitation of population-level effects of disturbance, chap. <i>of</i> The effects of noise on aquatic life II, v. 875, p. 295-302, https://doi.org/10.1007/978-1-4939-2981-8_35.","productDescription":"8 p.","startPage":"295","endPage":"302","ipdsId":"IP-071243","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":329543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"875","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf2","contributors":{"editors":[{"text":"Popper, Arthur N.","contributorId":175351,"corporation":false,"usgs":false,"family":"Popper","given":"Arthur","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":650845,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hawkins, Anthony","contributorId":175352,"corporation":false,"usgs":false,"family":"Hawkins","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":650846,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Fleishman, Erica","contributorId":11863,"corporation":false,"usgs":true,"family":"Fleishman","given":"Erica","affiliations":[],"preferred":false,"id":582502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgman, Mark","contributorId":150633,"corporation":false,"usgs":false,"family":"Burgman","given":"Mark","email":"","affiliations":[{"id":13336,"text":"University of Melbourne","active":true,"usgs":false}],"preferred":false,"id":582503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":582501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schick, Robert S","contributorId":149294,"corporation":false,"usgs":false,"family":"Schick","given":"Robert","email":"","middleInitial":"S","affiliations":[{"id":12470,"text":"University of St. Andrews","active":true,"usgs":false}],"preferred":false,"id":582504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krauss, Scott","contributorId":43250,"corporation":false,"usgs":true,"family":"Krauss","given":"Scott","affiliations":[],"preferred":false,"id":582505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70189515,"text":"70189515 - 2016 - A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity","interactions":[],"lastModifiedDate":"2020-09-01T14:28:24.754124","indexId":"70189515","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity","docAbstract":"<p id=\"sp0045\">A synthesis of published vegetation mercury (Hg) data across 11 contiguous states in the western United States showed that aboveground biomass concentrations followed the order: leaves (26&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup>)&nbsp;~&nbsp;branches (26&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup>)&nbsp;&gt;&nbsp;bark (16&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup>)&nbsp;&gt;&nbsp;bole wood (1&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup>). No spatial trends of Hg in aboveground biomass distribution were detected, which likely is due to very sparse data coverage and different sampling protocols. Vegetation data are largely lacking for important functional vegetation types such as shrubs, herbaceous species, and grasses.</p><p id=\"sp0050\">Soil concentrations collected from the published literature were high in the western United States, with 12% of observations exceeding 100&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup>, reflecting a bias toward investigations in Hg-enriched sites. In contrast, soil Hg concentrations from a randomly distributed data set (1911 sampling points; Smith et al., 2013a) averaged 24&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup><span>&nbsp;</span>(A-horizon) and 22&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup><span>&nbsp;</span>(C-horizon), and only 2.6% of data exceeded 100&nbsp;μg&nbsp;kg<sup>−&nbsp;1</sup>. Soil Hg concentrations significantly differed among land covers, following the order: forested upland&nbsp;&gt;&nbsp;planted/cultivated&nbsp;&gt;&nbsp;herbaceous upland/shrubland&nbsp;&gt;&nbsp;barren soils. Concentrations in forests were on average 2.5 times higher than in barren locations. Principal component analyses showed that soil Hg concentrations were not or weakly related to modeled dry and wet Hg deposition and proximity to mining, geothermal areas, and coal-fired power plants. Soil Hg distribution also was not closely related to other trace metals, but strongly associated with organic carbon, precipitation, canopy greenness, and foliar Hg pools of overlying vegetation. These patterns indicate that soil Hg concentrations are related to atmospheric deposition and reflect an overwhelming influence of plant productivity — driven by water availability — with productive landscapes showing high soil Hg accumulation and unproductive barren soils and shrublands showing low soil Hg values. Large expanses of low-productivity, arid ecosystems across the western U.S. result in some of the lowest soil Hg concentrations observed worldwide.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.11.104","usgsCitation":"Obrist, D., Pearson, C., Webster, J., Kane, T., Lin, C., Aiken, G.R., and Alpers, C.N., 2016, A synthesis of terrestrial mercury in the western United States: Spatial distribution defined by land cover and plant productivity: Science of the Total Environment, v. 568, p. 522-535, https://doi.org/10.1016/j.scitotenv.2015.11.104.","productDescription":"14 p.","startPage":"522","endPage":"535","ipdsId":"IP-070736","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":470615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2015.11.104","text":"Publisher Index Page"},{"id":343856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5969d82ae4b0d1f9f060a184","contributors":{"authors":[{"text":"Obrist, Daniel","contributorId":172155,"corporation":false,"usgs":false,"family":"Obrist","given":"Daniel","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":704988,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, Christopher","contributorId":49278,"corporation":false,"usgs":true,"family":"Pearson","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":704989,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Jackson","contributorId":172157,"corporation":false,"usgs":false,"family":"Webster","given":"Jackson","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":704990,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Tyler J. 0000-0003-2511-7312","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":194675,"corporation":false,"usgs":false,"family":"Kane","given":"Tyler J.","affiliations":[],"preferred":false,"id":704991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Che-Jen","contributorId":167257,"corporation":false,"usgs":false,"family":"Lin","given":"Che-Jen","email":"","affiliations":[{"id":24666,"text":"Lamar University","active":true,"usgs":false}],"preferred":false,"id":704992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704993,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704994,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70178644,"text":"70178644 - 2016 - Effects of lake trout refuges on lake whitefish and cisco in the Apostle Islands Region of Lake Superior","interactions":[],"lastModifiedDate":"2017-04-27T10:09:10","indexId":"70178644","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of lake trout refuges on lake whitefish and cisco in the Apostle Islands Region of Lake Superior","docAbstract":"<p><span>Lake trout refuges in the Apostle Islands region of Lake Superior are analogous to the concept of marine protected areas. These refuges, established specifically for lake trout (</span><i>Salvelinus namaycush</i><span>) and closed to most forms of recreational and commercial fishing, were implicated as one of several management actions leading to successful rehabilitation of Lake Superior lake trout. To investigate the potential significance of Gull Island Shoal and Devils Island Shoal refuges for populations of not only lake trout but also other fish species, relative abundances of lake trout, lake whitefish </span><i>(Coregonus clupeaformis)</i><span>, and cisco </span><i>(Coregonus artedi)</i><span> were compared between areas sampled inside versus outside of refuge boundaries. During 1982–2010, lake trout relative abundance was higher and increased faster inside the refuges, where lake trout fishing was prohibited, than outside the refuges. Over the same period, lake whitefish relative abundance increased faster inside than outside the refuges. Both evaluations provided clear evidence that refuges protected these species. In contrast, trends in relative abundance of cisco, a prey item of lake trout, did not differ significantly between areas inside and outside the refuges. This result did not suggest indirect or cascading refuge effects due to changes in predator levels. Overall, this study highlights the potential of species-specific refuges to benefit other fish species beyond those that were the refuges' original target. Improved understanding of refuge effects on multiple species of Great Lakes fishes can be valuable for developing rationales for refuge establishment and predicting associated fish community-level effects.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.07.011","usgsCitation":"Zuccarino-Crowe, C.M., Taylor, W., Hansen, M.J., Seider, M.J., and Krueger, C., 2016, Effects of lake trout refuges on lake whitefish and cisco in the Apostle Islands Region of Lake Superior: Journal of Great Lakes Research, v. 42, no. 5, p. 1092-1101, https://doi.org/10.1016/j.jglr.2016.07.011.","productDescription":"10 p.","startPage":"1092","endPage":"1101","ipdsId":"IP-077304","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470535,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2016.07.011","text":"Publisher Index Page"},{"id":331412,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Apostle Islands, Lake Superior","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.05194091796875,\n              46.67299877463589\n            ],\n            [\n              -91.05194091796875,\n              47.26338813315702\n            ],\n            [\n              -90.21697998046875,\n              47.26338813315702\n            ],\n            [\n              -90.21697998046875,\n              46.67299877463589\n            ],\n            [\n              -91.05194091796875,\n              46.67299877463589\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"42","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584144dfe4b04fc80e50739e","contributors":{"authors":[{"text":"Zuccarino-Crowe, Chiara M.","contributorId":177118,"corporation":false,"usgs":false,"family":"Zuccarino-Crowe","given":"Chiara","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":654690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, William W.","contributorId":113795,"corporation":false,"usgs":true,"family":"Taylor","given":"William W.","affiliations":[],"preferred":false,"id":654691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Michael J. 0000-0001-8522-3876 michaelhansen@usgs.gov","orcid":"https://orcid.org/0000-0001-8522-3876","contributorId":5006,"corporation":false,"usgs":true,"family":"Hansen","given":"Michael","email":"michaelhansen@usgs.gov","middleInitial":"J.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":654692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seider, Michael J.","contributorId":19452,"corporation":false,"usgs":true,"family":"Seider","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":654694,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70178556,"text":"70178556 - 2016 - Field guide to Laramide basin evolution and drilling activity in North Park and Middle Park, Colorado","interactions":[],"lastModifiedDate":"2016-11-30T15:02:40","indexId":"70178556","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Field guide to Laramide basin evolution and drilling activity in North Park and Middle Park, Colorado","docAbstract":"<p>Overview of the geologic history of the North Park–Middle Park area and its past and recent drilling activity. Field trip stops highlight basin formation and the consequences of geologic configuration on oil and gas plays and development. The starting point is the west flank of the Denver Basin to compare and contrast the latest Cretaceous through Eocene basin fill on both flanks of the Front Range, before exploring sediments of the same age in the North Park – Middle Park intermontane basin.</p>","language":"English","publisher":"Rocky Mountain Association of Geologists","usgsCitation":"Dechesne, M., Cole, J.C., and Martin, C.B., 2016, Field guide to Laramide basin evolution and drilling activity in North Park and Middle Park, Colorado: Mountain Geologist, v. 53, no. 4, p. 283-329.","productDescription":"47 p.","startPage":"283","endPage":"329","ipdsId":"IP-076161","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":331335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":331334,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.rmag.org/current-mountain-geologist-issues"}],"country":"United States","state":"Colorado","otherGeospatial":"Middle Park, North Park","volume":"53","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583ff34de4b04fc80e437262","contributors":{"authors":[{"text":"Dechesne, Marieke 0000-0002-4468-7495 mdechesne@usgs.gov","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":5036,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","email":"mdechesne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":654342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, James C. jimcole@usgs.gov","contributorId":1256,"corporation":false,"usgs":true,"family":"Cole","given":"James","email":"jimcole@usgs.gov","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":654343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Christopher B.","contributorId":177078,"corporation":false,"usgs":false,"family":"Martin","given":"Christopher","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":654344,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70179072,"text":"70179072 - 2016 - A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-12-20T11:43:51","indexId":"70179072","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin","docAbstract":"An investigation of the change in groundwater recharge in response to potential climate change\nwas performed for the UCRB using the SWB groundwater recharge model and downscaled\nclimate data from the CMIP5 multi-model dataset. Climate projections from 97 downscaled\nCMIP5 datasets were assumed to be equally likely and recharge simulation results were\ncombined. Results for the UCRB suggest that projected increases in actual ET from higher\ntemperatures may be offset by increases in precipitation, resulting in increased groundwater\nrecharge for many areas in the basin in future time periods.","language":"English","publisher":"Bureau of Reclamation","collaboration":"Bureau of Reclamation","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2016, A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin, ii., 20 p.","productDescription":"ii., 20 p.","ipdsId":"IP-066612","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":332339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332146,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/watersmart/wcra/docs/techmemoclimatechangeongroundwaterresources.pdf"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.2802734375,\n              37.142803443716836\n            ],\n            [\n              -110.3466796875,\n              39.50404070558415\n            ],\n            [\n              -107.81982421874999,\n              40.111688665595956\n            ],\n            [\n              -105.556640625,\n              39.8928799002948\n            ],\n            [\n              -106.01806640624999,\n              37.03763967977139\n            ],\n            [\n              -108.25927734375,\n              36.50963615733049\n            ],\n            [\n              -112.30224609374999,\n              36.70365959719456\n            ],\n            [\n              -112.2802734375,\n              37.142803443716836\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51bee4b01224f329b5e7","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":655927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":655928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70179551,"text":"70179551 - 2016 - Trends in mercury wet deposition and mercury air concentrations across the U.S. and Canada","interactions":[],"lastModifiedDate":"2017-02-21T15:53:27","indexId":"70179551","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Trends in mercury wet deposition and mercury air concentrations across the U.S. and Canada","docAbstract":"<div class=\"abstract svAbstract \" data-etype=\"ab\"><p id=\"sp0045\">This study examined the spatial and temporal trends of mercury (Hg) in wet deposition and air concentrations in the United States (U.S.) and Canada between 1997 and 2013. Data were obtained from the National Atmospheric Deposition Program (NADP) and Environment Canada monitoring networks, and other sources. Of the 19 sites with data records from 1997–2013, 53% had significant negative trends in Hg concentration in wet deposition, while no sites had significant positive trends, which is in general agreement with earlier studies that considered NADP data up until about 2010. However, for the time period 2007–2013 (71 sites), 17% and 13% of the sites had significant positive and negative trends, respectively, and for the time period 2008–2013 (81 sites) 30% and 6% of the sites had significant positive and negative trends, respectively. Non-significant positive tendencies were also widespread. Regional trend analyses revealed significant positive trends in Hg concentration in the Rocky Mountains, Plains, and Upper Midwest regions for the recent time periods in addition to significant positive trends in Hg deposition for the continent as a whole. Sulfate concentration trends in wet deposition were negative in all regions, suggesting a lower importance of local Hg sources. The trend in gaseous elemental Hg from short-term datasets merged as one continuous record was broadly consistent with trends in Hg concentration in wet deposition, with the early time period (1998–2007) producing a significantly negative trend (−&nbsp;1.5&nbsp;±&nbsp;0.2%&nbsp;year<sup>−&nbsp;1</sup>) and the recent time period (2008–2013) displaying a flat slope (−&nbsp;0.3&nbsp;±&nbsp;0.1%&nbsp;year<sup>−&nbsp;1</sup>, not significant). The observed shift to more positive or less negative trends in Hg wet deposition primarily seen in the Central-Western regions is consistent with the effects of rising Hg emissions from regions outside the U.S. and Canada and the influence of long-range transport in the free troposphere.</p></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.01.061","usgsCitation":"Weiss-Penzias, P.S., Gay, D.A., Brigham, M.E., Parsons, M.T., Gustin, M.S., and ter Shure, A., 2016, Trends in mercury wet deposition and mercury air concentrations across the U.S. and Canada: Science of the Total Environment, v. 568, p. 546-556, https://doi.org/10.1016/j.scitotenv.2016.01.061.","productDescription":"11 p.","startPage":"546","endPage":"556","ipdsId":"IP-066427","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":332906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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Center","active":true,"usgs":true}],"preferred":true,"id":657671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parsons, Matthew T.","contributorId":177964,"corporation":false,"usgs":false,"family":"Parsons","given":"Matthew","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":657674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustin, Mae S.","contributorId":177966,"corporation":false,"usgs":false,"family":"Gustin","given":"Mae","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":657676,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"ter Shure, Arnout","contributorId":177965,"corporation":false,"usgs":false,"family":"ter Shure","given":"Arnout","email":"","affiliations":[],"preferred":false,"id":657675,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70191981,"text":"70191981 - 2016 - Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear","interactions":[],"lastModifiedDate":"2017-10-19T10:50:38","indexId":"70191981","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear","docAbstract":"<p><span>The capacity to describe and quantify predation by large carnivores expanded considerably with the advent of GPS technology. Analyzing clusters of GPS locations formed by carnivores facilitates the detection of predation events by identifying characteristics which distinguish predation sites. We present a performance assessment of GPS cluster analysis as applied to the predation and scavenging of an omnivore, the American black bear (</span><i>Ursus americanus</i><span>), on ungulate prey and carrion. Through field investigations of 6854 GPS locations from 24 individual bears, we identified 54 sites where black bears formed a cluster of locations while predating or scavenging elk (</span><i>Cervus elaphus</i><span>), mule deer (</span><i>Odocoileus hemionus</i><span>), or cattle (</span><i>Bos</i><span><span>&nbsp;</span>spp.). We developed models for three data sets to predict whether a GPS cluster was formed at a carnivory site vs. a non-carnivory site (e.g., bed sites or non-ungulate foraging sites). Two full-season data sets contained GPS locations logged at either 3-h or 30-min intervals from April to November, and a third data set contained 30-min interval data from April through July corresponding to the calving period for elk. Longer fix intervals resulted in the detection of fewer carnivory sites. Clusters were more likely to be carnivory sites if they occurred in open or edge habitats, if they occurred in the early season, if the mean distance between all pairs of GPS locations within the cluster was less, and if the cluster endured for a longer period of time. Clusters were less likely to be carnivory sites if they were initiated in the morning or night compared to the day. The top models for each data set performed well and successfully predicted 71–96% of field-verified carnivory events, 55–75% of non–carnivory events, and 58–76% of clusters overall. Refinement of this method will benefit from further application across species and ecological systems.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1513","usgsCitation":"Kindschuh, S.R., Cain, J.W., Daniel, D., and Peyton, M.A., 2016, Efficacy of GPS cluster analysis for predicting carnivory sites of a wide-ranging omnivore: the American black bear: Ecosphere, v. 7, no. 10, p. 1-17, https://doi.org/10.1002/ecs2.1513.","productDescription":"e01513; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-074517","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1513","text":"Publisher Index Page"},{"id":346948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jemez Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.93954467773438,\n              35.53781387714839\n            ],\n            [\n              -106.39434814453125,\n              35.53781387714839\n            ],\n            [\n              -106.39434814453125,\n              35.99578538642032\n            ],\n            [\n              -106.93954467773438,\n              35.99578538642032\n            ],\n            [\n              -106.93954467773438,\n              35.53781387714839\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-19","publicationStatus":"PW","scienceBaseUri":"59e9b997e4b05fe04cd65ccb","contributors":{"authors":[{"text":"Kindschuh, Sarah R.","contributorId":197601,"corporation":false,"usgs":false,"family":"Kindschuh","given":"Sarah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":713887,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniel, David","contributorId":197602,"corporation":false,"usgs":false,"family":"Daniel","given":"David","email":"","affiliations":[],"preferred":false,"id":713888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peyton, Mark A.","contributorId":197603,"corporation":false,"usgs":false,"family":"Peyton","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":713889,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70179746,"text":"70179746 - 2016 - Flow reconstructions in the Upper Missouri River Basin using riparian tree rings","interactions":[],"lastModifiedDate":"2017-01-17T10:51:33","indexId":"70179746","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Flow reconstructions in the Upper Missouri River Basin using riparian tree rings","docAbstract":"<p><span>River flow reconstructions are typically developed using tree rings from montane conifers that cannot reflect flow regulation or hydrologic inputs from the lower portions of a watershed. Incorporating lowland riparian trees may improve the accuracy of flow reconstructions when these trees are physically linked to the alluvial water table. We used riparian plains cottonwoods (</span><i>Populus deltoides</i><span> ssp. </span><i>monilifera</i><span>) to reconstruct discharge for three neighboring rivers in the Upper Missouri River Basin: the Yellowstone (</span><i>n</i><span> = 389 tree cores), Powder (</span><i>n</i><span> = 408), and Little Missouri Rivers (</span><i>n</i><span> = 643). We used the Regional Curve Standardization approach to reconstruct log-transformed discharge over the 4 months in early summer that most highly correlated to tree ring growth. The reconstructions explained at least 57% of the variance in historical discharge and extended back to 1742, 1729, and 1643. These are the first flow reconstructions for the Lower Yellowstone and Powder Rivers, and they are the furthest downstream among Rocky Mountain rivers in the Missouri River Basin. Although mostly free-flowing, the Yellowstone and Powder Rivers experienced a shift from early-summer to late-summer flows within the last century. This shift is concurrent with increasing irrigation and reservoir storage, and it corresponds to decreased cottonwood growth. Low-frequency flow patterns revealed wet conditions from 1870 to 1980, a period that includes the majority of the historical record. The 1816–1823 and 1861–1865 droughts were more severe than any recorded, revealing that drought risks are underestimated when using the instrumental record alone.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016WR018845","usgsCitation":"Schook, D.M., Friedman, J.M., and Rathburn, S.L., 2016, Flow reconstructions in the Upper Missouri River Basin using riparian tree rings: Water Resources Research, v. 52, no. 10, p. 8159-8173, https://doi.org/10.1002/2016WR018845.","productDescription":"15 p.","startPage":"8159","endPage":"8173","ipdsId":"IP-073511","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":462071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr018845","text":"Publisher Index Page"},{"id":333238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-21","publicationStatus":"PW","scienceBaseUri":"587f3c31e4b0d96de2564549","contributors":{"authors":[{"text":"Schook, Derek M.","contributorId":178325,"corporation":false,"usgs":false,"family":"Schook","given":"Derek","email":"","middleInitial":"M.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":658512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":658511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rathburn, Sara L.","contributorId":140606,"corporation":false,"usgs":false,"family":"Rathburn","given":"Sara","email":"","middleInitial":"L.","affiliations":[{"id":13539,"text":"Department of Geosciences, Colorado State University, Fort Collins, Colorado","active":true,"usgs":false}],"preferred":false,"id":658513,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193041,"text":"70193041 - 2016 - Comparative use of side and main channels by small-bodied fish in a large, unimpounded river","interactions":[],"lastModifiedDate":"2017-11-06T16:39:50","indexId":"70193041","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Comparative use of side and main channels by small-bodied fish in a large, unimpounded river","docAbstract":"<ol id=\"fwb12796-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Ecological theory and field studies suggest that lateral floodplain connectivity and habitat heterogeneity provided by side channels impart favourable habitat conditions for lotic fishes, especially fluvial fishes dependent on large patches of shallow, slow velocity habitats for some portion of their life cycle. However, anthropogenic modification of large, temperate floodplain rivers has led to extensive channel simplification and side-channel loss. Highly modified rivers consist of simplified channels in contracted, less dynamic floodplains.</li><li>Most research examining the seasonal importance of side channels for fish assemblages in large rivers has been carried out in heavily modified rivers, where side-channel extents are substantially reduced from pre-settlement times, and has often overlooked small-bodied fishes. Inferences about the ecological importance of side channels for small-bodied fishes in large rivers can be ascertained only from investigations of large rivers with largely intact floodplains. The Yellowstone River, our study area, is a rare example of one such river.</li><li>We targeted small-bodied fishes and compared their habitat use in side and main channels in two geomorphically distinct types of river bends during early and late snowmelt runoff, and autumn base flow. Species compositions of side and main channels differed throughout hydroperiods concurrent with the seasonal redistribution of the availability of shallow, slow current-velocity habitats. More species of fish used side channels than main channels during runoff. Additionally, catch rates of small fishes were generally greater in side channels than in main channels and quantitative assemblage compositions differed between channel types during runoff, but not during base flow. Presence of and access to diverse habitats facilitated the development and persistence of diverse fish assemblages in our study area.</li><li>Physical dissimilarities between side and main channels may have differentially structured the side- and main-channel fish assemblages during runoff. Patches of shallow, slow current-velocity (SSCV) habitats in side channels were larger and had slightly slower water velocities than SSCV habitat patches in main channels during runoff, but not during base flow.</li><li>Our findings establish a baseline importance of side channels to riverine fishes in a large, temperate river without heavy anthropogenic modification. Establishing this baseline contributes to basic fluvial ecology and provides empirical justification for restoration efforts that reconnect large rivers with their floodplains.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12796","usgsCitation":"Reinhold, A.M., Bramblett, R.G., Zale, A.V., Roberts, D.W., and Poole, G., 2016, Comparative use of side and main channels by small-bodied fish in a large, unimpounded river: Freshwater Biology, v. 61, no. 10, p. 1611-1626, https://doi.org/10.1111/fwb.12796.","productDescription":"16 p.","startPage":"1611","endPage":"1626","ipdsId":"IP-064958","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":482071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fwb.12796","text":"Publisher Index Page"},{"id":348310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Yellowstone River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.0498046875,\n              45.01141864227728\n            ],\n            [\n              -104.0185546875,\n              45.01141864227728\n            ],\n            [\n              -104.0185546875,\n              47.83528342275264\n            ],\n            [\n              -111.0498046875,\n              47.83528342275264\n            ],\n            [\n              -111.0498046875,\n              45.01141864227728\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"61","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"5a07e9c5e4b09af898c8cc4b","contributors":{"authors":[{"text":"Reinhold, Ann Marie","contributorId":200043,"corporation":false,"usgs":false,"family":"Reinhold","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":720781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bramblett, Robert G.","contributorId":169857,"corporation":false,"usgs":false,"family":"Bramblett","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":720782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roberts, David W.","contributorId":56235,"corporation":false,"usgs":true,"family":"Roberts","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":720783,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poole, Geoffrey C.","contributorId":25540,"corporation":false,"usgs":true,"family":"Poole","given":"Geoffrey C.","affiliations":[],"preferred":false,"id":720784,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70178034,"text":"70178034 - 2016 - Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat","interactions":[],"lastModifiedDate":"2016-11-01T13:42:50","indexId":"70178034","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat","docAbstract":"<div class=\"abstract toc-section\"><p><span>Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (</span><i>Sus scrofa</i><span>) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.</span></p></div>","language":"English","publisher":"PloS One","doi":"10.1371/journal.pone.0155615","usgsCitation":"Keiter, D.A., Cunningham, F.L., Rhodes, O.E., Irwin, B.J., and Beasley, J., 2016, Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat: PLoS ONE, v. 25, no. 11, e0155615; 14 p., https://doi.org/10.1371/journal.pone.0155615.","productDescription":"e0155615; 14 p.","onlineOnly":"N","ipdsId":"IP-069727","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":470610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0155615","text":"Publisher Index Page"},{"id":330625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"11","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-25","publicationStatus":"PW","scienceBaseUri":"5819a9c3e4b0bb36a4c91017","contributors":{"authors":[{"text":"Keiter, David A.","contributorId":176521,"corporation":false,"usgs":false,"family":"Keiter","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":652652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cunningham, Fred L.","contributorId":176522,"corporation":false,"usgs":false,"family":"Cunningham","given":"Fred","email":"","middleInitial":"L.","affiliations":[{"id":36282,"text":"USDA National Wildlife Research Center (NWRC) Mississippi Field Station, Starkville, MS","active":true,"usgs":false}],"preferred":false,"id":652650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rhodes, Olin E. Jr.","contributorId":113775,"corporation":false,"usgs":true,"family":"Rhodes","given":"Olin","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":652651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":652577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beasley, James","contributorId":172814,"corporation":false,"usgs":false,"family":"Beasley","given":"James","affiliations":[{"id":27094,"text":"University of Georgia, Savannah River Ecology Laboratory, Warnell School of Forestry and Natural Resources, PO Drawer E, Aiken, SC 29802","active":true,"usgs":false}],"preferred":false,"id":652653,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70177947,"text":"70177947 - 2016 - Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015","interactions":[],"lastModifiedDate":"2017-01-17T19:09:07","indexId":"70177947","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3230,"text":"Rangelands","active":true,"publicationSubtype":{"id":10}},"title":"Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015","docAbstract":"<ul><li>Cheatgrass (<i>Bromus tectorum</i> L.) dramatically changes shrub steppe ecosystems in the Northern Great Basin, United States.<br></li><li>Current-season cheatgrass location and percent cover are difficult to estimate rapidly.<br></li><li>We explain the development of a near-real-time cheatgrass percent cover dataset and map in the Northern Great Basin for the current year (2015), display the current year’s map, provide analysis of the map, and provide a website link to download the map (as a PDF) and the associated dataset.<br></li><li>The near-real-time cheatgrass percent cover dataset and map were consistent with non-expedited, historical cheatgrass percent cover datasets and maps.<br></li><li>Having cheatgrass maps available mid-summer can help land managers, policy makers, and Geographic Information Systems personnel as they work to protect socially relevant areas such as critical wildlife habitats.<br></li></ul><p></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rala.2016.08.002","usgsCitation":"Boyte, S.P., and Wylie, B.K., 2016, Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015: Rangelands, v. 38, no. 5, p. 278-284, https://doi.org/10.1016/j.rala.2016.08.002.","productDescription":"7 p.","startPage":"278","endPage":"284","ipdsId":"IP-077313","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470543,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.rala.2016.08.002","text":"External Repository"},{"id":330624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5819a9c3e4b0bb36a4c91019","contributors":{"authors":[{"text":"Boyte, Stephen P. 0000-0002-5462-3225 sboyte@usgs.gov","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":139238,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen","email":"sboyte@usgs.gov","middleInitial":"P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":652455,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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