{"pageNumber":"538","pageRowStart":"13425","pageSize":"25","recordCount":40783,"records":[{"id":70187424,"text":"70187424 - 2015 - Early Holocene Great Salt Lake","interactions":[],"lastModifiedDate":"2017-05-02T14:51:22","indexId":"70187424","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Early Holocene Great Salt Lake","docAbstract":"<p><span>Shorelines and surficial deposits (including buried forest-floor mats and organic-rich wetland sediments) show that Great Salt Lake did not rise higher than modern lake levels during the earliest Holocene (11.5–10.2 cal ka BP; 10–9 </span><span class=\"sup\">14</span><span>C ka BP). During that period, finely laminated, organic-rich muds (sapropel) containing brine-shrimp cysts and pellets and interbedded sodium-sulfate salts were deposited on the lake floor. Sapropel deposition was probably caused by stratification of the water column — a freshwater cap possibly was formed by groundwater, which had been stored in upland aquifers during the immediately preceding late-Pleistocene deep-lake cycle (Lake Bonneville), and was actively discharging on the basin floor. A climate characterized by low precipitation and runoff, combined with local areas of groundwater discharge in piedmont settings, could explain the apparent conflict between evidence for a shallow lake (a dry climate) and previously published interpretations for a moist climate in the Great Salt Lake basin of the eastern Great Basin.</span></p>","language":"English","publisher":"Cambridge University Press","doi":"10.1016/j.yqres.2015.05.001","usgsCitation":"Oviatt, C., Madsen, D.B., Miller, D., Thompson, R.S., and McGeehin, J.P., 2015, Early Holocene Great Salt Lake: Quaternary Research, v. 84, no. 1, p. 57-68, https://doi.org/10.1016/j.yqres.2015.05.001.","productDescription":"12 p.","startPage":"57","endPage":"68","ipdsId":"IP-064151","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":340752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.20037841796875,\n              40.60978237983301\n            ],\n            [\n              -111.8023681640625,\n              40.60978237983301\n            ],\n            [\n              -111.8023681640625,\n              41.73033005046653\n            ],\n            [\n              -113.20037841796875,\n              41.73033005046653\n            ],\n            [\n              -113.20037841796875,\n              40.60978237983301\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"84","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-20","publicationStatus":"PW","scienceBaseUri":"59099aafe4b0fc4e449157f8","contributors":{"authors":[{"text":"Oviatt, Charles G.","contributorId":13503,"corporation":false,"usgs":true,"family":"Oviatt","given":"Charles G.","affiliations":[],"preferred":false,"id":694001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madsen, David B.","contributorId":191727,"corporation":false,"usgs":false,"family":"Madsen","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":694002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":694000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":694003,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGeehin, John P. 0000-0002-5320-6091 mcgeehin@usgs.gov","orcid":"https://orcid.org/0000-0002-5320-6091","contributorId":130967,"corporation":false,"usgs":true,"family":"McGeehin","given":"John","email":"mcgeehin@usgs.gov","middleInitial":"P.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":694004,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70155184,"text":"70155184 - 2015 - Can orchards help connect Mediterranean ecosystems? Animal movement data alter conservation priorities","interactions":[],"lastModifiedDate":"2015-08-05T11:12:12","indexId":"70155184","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Can orchards help connect Mediterranean ecosystems? Animal movement data alter conservation priorities","docAbstract":"<p><span>As natural habitats become fragmented by human activities, animals must increasingly move through human-dominated systems, particularly agricultural landscapes. Mapping areas important for animal movement has therefore become a key part of conservation planning. Models of landscape connectivity are often parameterized using expert opinion and seldom distinguish between the risks and barriers presented by different crop types. Recent research, however, suggests different crop types, such as row crops and orchards, differ in the degree to which they facilitate or impede species movements. Like many mammalian carnivores, bobcats (</span><i>Lynx rufus</i><span>) are sensitive to fragmentation and loss of connectivity between habitat patches. We investigated how distinguishing between different agricultural land covers might change conclusions about the relative conservation importance of different land uses in a Mediterranean ecosystem. Bobcats moved relatively quickly in row crops but relatively slowly in orchards, at rates similar to those in natural habitats of woodlands and scrub. We found that parameterizing a connectivity model using empirical data on bobcat movements in agricultural lands and other land covers, instead of parameterizing the model using habitat suitability indices based on expert opinion, altered locations of predicted animal movement routes. These results emphasize that differentiating between types of agriculture can alter conservation planning outcomes.</span></p>","language":"English","publisher":"University of Notre Dame","doi":"10.1674/0003-0031-174.1.105","usgsCitation":"Nogeire, T.M., Davis, F., Crooks, K.R., McRae, B.H., Lyren, L.M., and Boydston, E.E., 2015, Can orchards help connect Mediterranean ecosystems? Animal movement data alter conservation priorities: American Midland Naturalist, v. 174, no. 1, p. 105-116, https://doi.org/10.1674/0003-0031-174.1.105.","productDescription":"12 p.","startPage":"105","endPage":"116","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052372","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471968,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/0ps3x1b0","text":"External Repository"},{"id":306426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Orange County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.72262573242188,\n              33.592887216626245\n            ],\n            [\n              -117.72262573242188,\n              33.71862851510573\n            ],\n            [\n              -117.57843017578126,\n              33.71862851510573\n            ],\n            [\n              -117.57843017578126,\n              33.592887216626245\n            ],\n            [\n              -117.72262573242188,\n              33.592887216626245\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"174","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c333aae4b033ef52106a81","contributors":{"authors":[{"text":"Nogeire, Theresa M.","contributorId":83434,"corporation":false,"usgs":true,"family":"Nogeire","given":"Theresa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":565002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Frank W.","contributorId":36894,"corporation":false,"usgs":true,"family":"Davis","given":"Frank W.","affiliations":[],"preferred":false,"id":565003,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crooks, Kevin R.","contributorId":51137,"corporation":false,"usgs":false,"family":"Crooks","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":565004,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McRae, Brad H.","contributorId":145697,"corporation":false,"usgs":false,"family":"McRae","given":"Brad","email":"","middleInitial":"H.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":565005,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyren, Lisa M. llyren@usgs.gov","contributorId":2398,"corporation":false,"usgs":true,"family":"Lyren","given":"Lisa","email":"llyren@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":565001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boydston, Erin E. 0000-0002-8452-835X eboydston@usgs.gov","orcid":"https://orcid.org/0000-0002-8452-835X","contributorId":1705,"corporation":false,"usgs":true,"family":"Boydston","given":"Erin","email":"eboydston@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":565000,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70176119,"text":"70176119 - 2015 - Exposure and food web transfer of pharmaceuticals in ospreys (Pandion haliaetus): Predictive model and empirical data","interactions":[],"lastModifiedDate":"2018-09-04T15:59:22","indexId":"70176119","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Exposure and food web transfer of pharmaceuticals in ospreys (Pandion haliaetus): Predictive model and empirical data","docAbstract":"<p><span>The osprey (</span><i>Pandion haliaetus</i><span>) is a well-known sentinel of environmental contamination, yet no studies have traced pharmaceuticals through the water&ndash;fish&ndash;osprey food web. A screening-level exposure assessment was used to evaluate the bioaccumulation potential of 113 pharmaceuticals and metabolites, and an artificial sweetener in this food web. Hypothetical concentrations in water reflecting &ldquo;wastewater effluent dominated&rdquo; or &ldquo;dilution dominated&rdquo; scenarios were combined with pH-specific bioconcentration factors (BCFs) to predict uptake in fish. Residues in fish and osprey food intake rate were used to calculate the daily intake (DI) of compounds by an adult female osprey. Fourteen pharmaceuticals and a drug metabolite with a BCF greater than 100 and a DI greater than 20&thinsp;&micro;g/kg were identified as being most likely to exceed the adult human therapeutic dose (HTD). These 15 compounds were also evaluated in a 40 day cumulative dose exposure scenario using first-order kinetics to account for uptake and elimination. Assuming comparable absorption to humans, the half-lives (t</span><span>1/2</span><span>) for an adult osprey to reach the HTD within 40 days were calculated. For 3 of these pharmaceuticals, the estimated t</span><span>1/2</span><span>&nbsp;in ospreys was less than that for humans, and thus an osprey might theoretically reach or exceed the HTD in 3 to 7 days. To complement the exposure model, 24 compounds were quantified in water, fish plasma, and osprey nestling plasma from 7 potentially impaired locations in Chesapeake Bay. Of the 18 analytes detected in water, 8 were found in fish plasma, but only 1 in osprey plasma (the antihypertensive diltiazem). Compared to diltiazem detection rate and concentrations in water (10/12 detects, &lt;method detection limits [MDL]&ndash;173&thinsp;ng/L), there was a lower detection frequency in fish (31/233 detects, &lt;MDL&ndash;2400&thinsp;ng/L); however when present in fish, all values exceeded the maximum diltiazem concentration found in water. Diltiazem was found in all 69 osprey plasma samples (540&ndash;8630&thinsp;ng/L), with 41% of these samples exceeding maximum concentrations found in fish. Diltiazem levels in fish and osprey plasma were below the human therapeutic plasma concentration (30&thinsp;000&thinsp;ng/L). Effect thresholds for diltiazem are unknown in ospreys at this time, and there is no evidence to suggest adverse effects. This screening-level exposure model can help identify those compounds that warrant further investigation in high-trophic level species.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ieam.1570","usgsCitation":"Lazarus, R.S., Rattner, B.A., Du, B., McGowan, P.C., Blazer, V., and Ottinger, M.A., 2015, Exposure and food web transfer of pharmaceuticals in ospreys (Pandion haliaetus): Predictive model and empirical data: Integrated Environmental Assessment and Management, v. 11, no. 1, p. 118-129, https://doi.org/10.1002/ieam.1570.","productDescription":"12 p.","startPage":"118","endPage":"129","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057952","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":327898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-08-01","publicationStatus":"PW","scienceBaseUri":"57c16836e4b0f2f0ceb907db","contributors":{"authors":[{"text":"Lazarus, Rebecca S. 0000-0003-1731-6469 rlazarus@usgs.gov","orcid":"https://orcid.org/0000-0003-1731-6469","contributorId":5594,"corporation":false,"usgs":true,"family":"Lazarus","given":"Rebecca","email":"rlazarus@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":647180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":647181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Du, Bowen","contributorId":149285,"corporation":false,"usgs":false,"family":"Du","given":"Bowen","email":"","affiliations":[{"id":16605,"text":"Department of Environmental Science and the Center for Reservoir and Aquatic Systems Research (CRASR), Baylor University, Waco, TX","active":true,"usgs":false}],"preferred":false,"id":647182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":647183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":647184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ottinger, Mary Ann","contributorId":26422,"corporation":false,"usgs":false,"family":"Ottinger","given":"Mary","email":"","middleInitial":"Ann","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":647185,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70155921,"text":"70155921 - 2015 - Tectonic and sedimentary linkages between the Belt-Purcell basin and southwestern Laurentia during the Mesoproterozoic ca. 1.60-1.40 Ga","interactions":[],"lastModifiedDate":"2018-06-19T19:20:17","indexId":"70155921","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2626,"text":"Lithosphere","active":true,"publicationSubtype":{"id":10}},"title":"Tectonic and sedimentary linkages between the Belt-Purcell basin and southwestern Laurentia during the Mesoproterozoic ca. 1.60-1.40 Ga","docAbstract":"<p>Mesoproterozoic sedimentary basins in western North America provide key constraints on pre-Rodinia craton positions and interactions along the western rifted margin of Laurentia. One such basin, the Belt-Purcell basin, extends from southern Idaho into southern British Columbia and contains a &gt;18-km-thick succession of siliciclastic sediment deposited ca. 1.47&ndash;1.40 Ga. The ca. 1.47&ndash;1.45 Ga lower part of the succession contains abundant distinctive non-Laurentian 1.61&ndash;1.50 Ga detrital zircon populations derived from exotic cratonic sources. Contemporaneous metasedimentary successions in the southwestern United States&ndash;the Trampas and Yankee Joe basins in Arizona and New Mexico&ndash;also contain abundant 1.61&ndash;1.50 Ga detrital zircons. Similarities in depositional age and distinctive non-Laurentian detrital zircon populations suggest that both the Belt-Purcell and southwestern successions record sedimentary and tectonic linkages between western Laurentia and one or more cratons including North Australia, South Australia, and (or) East Antarctica. At ca. 1.45 Ga, both the Belt-Purcell and southwest successions underwent major sedimentological changes, with a pronounced shift to Laurentian provenance and the disappearance of the 1.61&ndash;1.50 Ga detrital zircon. Upper Belt-Purcell strata contain strongly unimodal ca. 1.73 Ga detrital zircon age populations that match the detrital zircon signature of Paleoproterozoic metasedimentary rocks of the Yavapai province to the south and southeast. We propose that the shift at ca. 1.45 Ga records the onset of orogenesis in southern Laurentia coeval with rifting along its northwestern margin. Bedrock uplift associated with orogenesis and widespread, coeval magmatism caused extensive exhumation and erosion of the Yavapai province ca. 1.45&ndash;1.36 Ga, providing a voluminous and areally extensive sediment source&ndash;with suitable zircon ages&ndash;during upper Belt deposition. This model provides a comprehensive and integrated view of the Mesoproterozoic tectonic evolution of western Laurentia and its position within the supercontinent Columbia as it evolved into Rodinia.</p>","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/L438.1","usgsCitation":"Jones, J.V., Dainel, C.G., and Doe, M., 2015, Tectonic and sedimentary linkages between the Belt-Purcell basin and southwestern Laurentia during the Mesoproterozoic ca. 1.60-1.40 Ga: Lithosphere, v. 7, no. 4, p. 465-472, https://doi.org/10.1130/L438.1.","productDescription":"8 p.","startPage":"465","endPage":"472","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058162","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":471981,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/l438.1","text":"Publisher Index Page"},{"id":306643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-05-21","publicationStatus":"PW","scienceBaseUri":"55cdbfbde4b08400b1fe143f","contributors":{"authors":[{"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":566869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dainel, Christohper G","contributorId":146260,"corporation":false,"usgs":false,"family":"Dainel","given":"Christohper","email":"","middleInitial":"G","affiliations":[{"id":16651,"text":"Bucknell University","active":true,"usgs":false}],"preferred":false,"id":566870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doe, Michael F","contributorId":146261,"corporation":false,"usgs":false,"family":"Doe","given":"Michael F","affiliations":[{"id":16652,"text":"Colorado  School of Mines","active":true,"usgs":false}],"preferred":false,"id":566871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182467,"text":"70182467 - 2015 - Tree mortality predicted from drought-induced vascular damage","interactions":[],"lastModifiedDate":"2017-02-23T12:46:12","indexId":"70182467","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Tree mortality predicted from drought-induced vascular damage","docAbstract":"<p><span>The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality</span><sup><a id=\"ref-link-2\" title=\"Cox, P. M. et al. Amazonian forest dieback under climate-carbon cycle projections for the 21st century. Theor. Appl. Clim. 78, 137-156 (2004).\" href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref1\" data-mce-href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref1\">1</a>, <a id=\"ref-link-3\" title=\"Scholze, M., Knorr, W., Arnell, N. W. &amp; Prentice, I. C. A climate-change risk analysis for world ecosystems. Proc. Natl Acad. Sci. USA 103, 13116-13120 (2006).\" href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref2\" data-mce-href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref2\">2</a>, <a id=\"ref-link-4\" title=\"Huntingford, C. et al. Simulated resilience of tropical rainforests to CO2-induced climate change. Nature Geosci. 6, 268-273 (2013).\" href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref3\" data-mce-href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref3\">3</a></sup><span>. Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality</span><sup><a id=\"ref-link-5\" title=\"McDowell, N. G. et al. The interdependence of mechanisms underlying climate-driven vegetation mortality. Trends Ecol. Evol. 26, 523-532 (2011).\" href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref4\" data-mce-href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref4\">4</a>, <a id=\"ref-link-6\" title=\"Powell, T. L. et al. Confronting model predictions of carbon fluxes with measurements of Amazon forests subjected to experimental drought. New Phytol. 200, 350-365 (2013).\" href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref5\" data-mce-href=\"http://www.nature.com/ngeo/journal/v8/n5/full/ngeo2400.html#ref5\">5</a></sup><span>. Here we assess the causes of tree mortality, using field measurements of branch hydraulic conductivity during ongoing mortality in </span><i>Populus tremuloides</i><span> in the southwestern United States and a detailed plant hydraulics model. We identify a lethal plant water stress threshold that corresponds with a loss of vascular transport capacity from air entry into the xylem. We then use this hydraulic-based threshold to simulate forest dieback during historical drought, and compare predictions against three independent mortality data sets. The hydraulic threshold predicted with 75% accuracy regional patterns of tree mortality as found in field plots and mortality maps derived from Landsat imagery. In a high-emissions scenario, climate models project that drought stress will exceed the observed mortality threshold in the southwestern United States by the 2050s. Our approach provides a powerful and tractable way of incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing&nbsp;climate.</span></p>","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/NGEO2400","usgsCitation":"Anderegg, W.R., Flint, A.L., Huang, C., Flint, L.E., Berry, J.A., Davis, F., Sperry, J.S., and Field, C.B., 2015, Tree mortality predicted from drought-induced vascular damage: Nature Geoscience, v. 8, p. 367-371, https://doi.org/10.1038/NGEO2400.","productDescription":"5 p.","startPage":"367","endPage":"371","ipdsId":"IP-059538","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":336106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-30","publicationStatus":"PW","scienceBaseUri":"58b002c7e4b01ccd54fb27d1","contributors":{"authors":[{"text":"Anderegg, William R.L.","contributorId":147089,"corporation":false,"usgs":false,"family":"Anderegg","given":"William","email":"","middleInitial":"R.L.","affiliations":[{"id":16784,"text":"Princeton U.","active":true,"usgs":false}],"preferred":false,"id":671207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":671208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huang, Cho-ying","contributorId":182348,"corporation":false,"usgs":false,"family":"Huang","given":"Cho-ying","email":"","affiliations":[],"preferred":false,"id":671209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":671206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berry, Joseph A.","contributorId":182349,"corporation":false,"usgs":false,"family":"Berry","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":671210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Frank W.","contributorId":127849,"corporation":false,"usgs":false,"family":"Davis","given":"Frank W.","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":671211,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sperry, John S.","contributorId":182350,"corporation":false,"usgs":false,"family":"Sperry","given":"John","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":671212,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Field, Christopher B.","contributorId":182351,"corporation":false,"usgs":false,"family":"Field","given":"Christopher","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":671213,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70173444,"text":"70173444 - 2015 - Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse","interactions":[],"lastModifiedDate":"2016-06-20T14:07:39","indexId":"70173444","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5091,"text":"GigaScience","active":true,"publicationSubtype":{"id":10}},"title":"Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse","docAbstract":"<p><span>Although there are considerable site-based data for individual or groups of ecosystems, these datasets are widely scattered, have different data formats and conventions, and often have limited accessibility. At the broader scale, national datasets exist for a large number of geospatial features of land, water, and air that are needed to fully understand variation among these ecosystems. However, such datasets originate from different sources and have different spatial and temporal resolutions. By taking an open-science perspective and by combining site-based ecosystem datasets and national geospatial datasets, science gains the ability to ask important research questions related to grand environmental challenges that operate at broad scales. Documentation of such complicated database integration efforts, through peer-reviewed papers, is recommended to foster reproducibility and future use of the integrated database. Here, we describe the major steps, challenges, and considerations in building an integrated database of lake ecosystems, called LAGOS (LAke multi-scaled GeOSpatial and temporal database), that was developed at the sub-continental study extent of 17 US states (1,800,000&nbsp;km</span><sup><span>2</span></sup><span>). LAGOS includes two modules: LAGOS</span><sub><span>GEO</span></sub><span>, with geospatial data on every lake with surface area larger than 4&nbsp;ha in the study extent (~50,000 lakes), including climate, atmospheric deposition, land use/cover, hydrology, geology, and topography measured across a range of spatial and temporal extents; and LAGOS</span><sub><span>LIMNO</span></sub><span>, with lake water quality data compiled from ~100 individual datasets for a subset of lakes in the study extent (~10,000 lakes). Procedures for the integration of datasets included: creating a flexible database design; authoring and integrating metadata; documenting data provenance; quantifying spatial measures of geographic data; quality-controlling integrated and derived data; and extensively documenting the database. Our procedures make a large, complex, and integrated database reproducible and extensible, allowing users to ask new research questions with the existing database or through the addition of new data. The largest challenge of this task was the heterogeneity of the data, formats, and metadata. Many steps of data integration need manual input from experts in diverse fields, requiring close collaboration.</span></p>","language":"English","publisher":"BioMed Central","doi":"10.1186/s13742-015-0067-4","usgsCitation":"Soranno, P.A., Bissell, E., Cheruvelil, K.S., Christel, S.T., Collins, S.M., Fergus, C.E., Filstrup, C.T., Lapierre, J., Lotting, N.R., Oliver, S., Scott, C.E., Smith, N.J., Stopyak, S., Yuan, S., Bremigan, M.T., Downing, J., Gries, C., Henry, E.N., Skaff, N.K., Stanley, E.H., Stow, C., Tan, P., Wagner, T., and Webster, K.E., 2015, Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science through data reuse: GigaScience, v. 4, no. 28, https://doi.org/10.1186/s13742-015-0067-4.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062339","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471979,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13742-015-0067-4","text":"Publisher Index Page"},{"id":324012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, Illinois, Indiana, Iowa, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, Wisconsin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.3388671875,\n              49.35375571830993\n            ],\n            [\n              -94.7900390625,\n              36.421282443649496\n            ],\n            [\n              -89.296875,\n              35.99578538642032\n            ],\n            [\n              -88.330078125,\n              37.19533058280065\n            ],\n            [\n              -87.3193359375,\n              37.64903402157866\n            ],\n            [\n              -84.5947265625,\n              38.71980474264239\n            ],\n            [\n              -82.6171875,\n              38.272688535980976\n            ],\n            [\n              -80.6396484375,\n              39.707186656826565\n            ],\n            [\n              -75.9375,\n              39.774769485295465\n            ],\n            [\n              -74.8388671875,\n              38.8225909761771\n            ],\n            [\n              -67.1044921875,\n              43.73935207915473\n            ],\n            [\n              -66.357421875,\n              45.398449976304086\n            ],\n            [\n              -68.15917968749999,\n              47.90161354142077\n            ],\n            [\n              -77.7392578125,\n              45.85941212790755\n            ],\n            [\n              -86.220703125,\n              49.410973199695846\n            ],\n            [\n              -97.3388671875,\n              49.35375571830993\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"28","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-01","publicationStatus":"PW","scienceBaseUri":"576913b1e4b07657d19fefae","contributors":{"authors":[{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bissell, E.G.","contributorId":88823,"corporation":false,"usgs":true,"family":"Bissell","given":"E.G.","email":"","affiliations":[],"preferred":false,"id":639829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cheruvelil, Kendra S.","contributorId":172029,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":639830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christel, Samuel T.","contributorId":169272,"corporation":false,"usgs":false,"family":"Christel","given":"Samuel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":639831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collins, Sarah M.","contributorId":172181,"corporation":false,"usgs":false,"family":"Collins","given":"Sarah","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":639832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":639833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":639834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lapierre, Jean-Francois","contributorId":172182,"corporation":false,"usgs":false,"family":"Lapierre","given":"Jean-Francois","email":"","affiliations":[],"preferred":false,"id":639835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lotting, Noah R.","contributorId":172183,"corporation":false,"usgs":false,"family":"Lotting","given":"Noah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":639836,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":639837,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Scott, Caren E.","contributorId":172184,"corporation":false,"usgs":false,"family":"Scott","given":"Caren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":639838,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smith, Nicole J.","contributorId":172185,"corporation":false,"usgs":false,"family":"Smith","given":"Nicole","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":639839,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Stopyak, Scott","contributorId":172186,"corporation":false,"usgs":false,"family":"Stopyak","given":"Scott","affiliations":[],"preferred":false,"id":639840,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Yuan, Shuai","contributorId":172187,"corporation":false,"usgs":false,"family":"Yuan","given":"Shuai","affiliations":[],"preferred":false,"id":639841,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bremigan, Mary Tate","contributorId":172173,"corporation":false,"usgs":false,"family":"Bremigan","given":"Mary","email":"","middleInitial":"Tate","affiliations":[],"preferred":false,"id":639842,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Downing, John A.","contributorId":70348,"corporation":false,"usgs":true,"family":"Downing","given":"John A.","affiliations":[],"preferred":false,"id":639843,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Gries, Corinna","contributorId":106525,"corporation":false,"usgs":true,"family":"Gries","given":"Corinna","affiliations":[],"preferred":false,"id":639844,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Henry, Emily N.","contributorId":172189,"corporation":false,"usgs":false,"family":"Henry","given":"Emily","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":639845,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Skaff, Nick K.","contributorId":172190,"corporation":false,"usgs":false,"family":"Skaff","given":"Nick","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":639846,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":639847,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":639848,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Tan, Pang-Ning","contributorId":172193,"corporation":false,"usgs":false,"family":"Tan","given":"Pang-Ning","affiliations":[],"preferred":false,"id":639849,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637138,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Webster, Katherine E.","contributorId":147903,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":639850,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}}
,{"id":70175563,"text":"70175563 - 2015 - Sea level and turbidity controls on mangrove soil surface elevation change","interactions":[],"lastModifiedDate":"2017-05-03T13:32:27","indexId":"70175563","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Sea level and turbidity controls on mangrove soil surface elevation change","docAbstract":"<p><span>Increases in sea level are a threat to seaward fringing mangrove forests if levels of inundation exceed the physiological tolerance of the trees; however, tidal wetlands can keep pace with sea level rise if soil surface elevations can increase at the same pace as sea level rise. Sediment accretion on the soil surface and belowground production of roots are proposed to increase with increasing sea level, enabling intertidal habitats to maintain their position relative to mean sea level, but there are few tests of these predictions in mangrove forests. Here we used variation in sea level and the availability of sediments caused by seasonal and inter-annual variation in the intensity of La Nina-El Nino to assess the effects of increasing sea level on surface elevation gains and contributing processes (accretion on the surface, subsidence and root growth) in mangrove forests. We found that soil surface elevation increased with mean sea level (which varied over 250&nbsp;mm during the study) and with turbidity at sites where fine sediment in the water column is abundant. In contrast, where sediments were sandy, rates of surface elevation gain were high, but not significantly related to variation in turbidity, and were likely to be influenced by other factors that deliver sand to the mangrove forest. Root growth was not linked to soil surface elevation gains, although it was associated with reduced shallow subsidence, and therefore may contribute to the capacity of mangroves to keep pace with sea level rise. Our results indicate both surface (sedimentation) and subsurface (root growth) processes can influence mangrove capacity to keep pace with sea level rise within the same geographic location, and that current models of tidal marsh responses to sea level rise capture the major feature of the response of mangroves where fine, but not coarse, sediments are abundant.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2014.11.026","usgsCitation":"Lovelock, C.E., Fernanda Adame, M., Bennion, V., Hayes, M., Reef, R., Santini, N., and Cahoon, D.R., 2015, Sea level and turbidity controls on mangrove soil surface elevation change: Estuarine, Coastal and Shelf Science, v. 153, p. 1-9, https://doi.org/10.1016/j.ecss.2014.11.026.","productDescription":"9 p.","startPage":"1","endPage":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059638","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":326619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"153","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b58b58e4b03bcb0104bc64","contributors":{"authors":[{"text":"Lovelock, Catherine E.","contributorId":64787,"corporation":false,"usgs":true,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":645715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fernanda Adame, Maria","contributorId":131125,"corporation":false,"usgs":false,"family":"Fernanda Adame","given":"Maria","email":"","affiliations":[],"preferred":false,"id":645716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennion, Vicki","contributorId":12174,"corporation":false,"usgs":true,"family":"Bennion","given":"Vicki","email":"","affiliations":[],"preferred":false,"id":645717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Matthew","contributorId":173749,"corporation":false,"usgs":false,"family":"Hayes","given":"Matthew","affiliations":[],"preferred":false,"id":645718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reef, Ruth","contributorId":44826,"corporation":false,"usgs":true,"family":"Reef","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":645719,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Santini, Nadia","contributorId":131126,"corporation":false,"usgs":false,"family":"Santini","given":"Nadia","email":"","affiliations":[],"preferred":false,"id":645720,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":645721,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70192580,"text":"70192580 - 2015 - Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape","interactions":[],"lastModifiedDate":"2017-11-17T11:43:17","indexId":"70192580","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","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":"Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape","docAbstract":"<p id=\"sp0005\">Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type).</p><p id=\"sp0010\">Catchment area (0.18–47,000&nbsp;km<sup>2</sup>) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6&nbsp;years of monthly water quality observations between 1990 and 2010. Statistically significant models (p&nbsp;&lt;&nbsp;0.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3&nbsp;mg&nbsp;l<sup>−&nbsp;1</sup><span>&nbsp;</span>(13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17&nbsp;mg&nbsp;l<sup>−&nbsp;1</sup>&nbsp;year<sup>−&nbsp;1</sup><span>&nbsp;</span>(1.6% year<sup>−&nbsp;1</sup>).</p><p id=\"sp0015\">Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality.</p><p id=\"sp0020\">Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of climatic variability and change on TOC concentration should be predictable if the studied catchments continue to respond similarly.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2015.03.041","usgsCitation":"Hytteborn, J.K., Temnerud, J., Alexander, R.B., Boyer, E.W., Futter, M.N., Froberg, M., Dahne, J., and Bishop, K.H., 2015, Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape: Science of the Total Environment, v. 520, p. 260-269, https://doi.org/10.1016/j.scitotenv.2015.03.041.","productDescription":"10 p.","startPage":"260","endPage":"269","ipdsId":"IP-062350","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":349066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"520","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fe80e4b06e28e9c25309","contributors":{"authors":[{"text":"Hytteborn, Julia K.","contributorId":198524,"corporation":false,"usgs":false,"family":"Hytteborn","given":"Julia","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":716323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Temnerud, Johan","contributorId":198525,"corporation":false,"usgs":false,"family":"Temnerud","given":"Johan","email":"","affiliations":[],"preferred":false,"id":716324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":716322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":716325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Futter, Martyn N.","contributorId":198527,"corporation":false,"usgs":false,"family":"Futter","given":"Martyn","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":716326,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Froberg, Mats","contributorId":198528,"corporation":false,"usgs":false,"family":"Froberg","given":"Mats","email":"","affiliations":[],"preferred":false,"id":716327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dahne, Joel","contributorId":198529,"corporation":false,"usgs":false,"family":"Dahne","given":"Joel","email":"","affiliations":[],"preferred":false,"id":716328,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bishop, Kevin H.","contributorId":198530,"corporation":false,"usgs":false,"family":"Bishop","given":"Kevin","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":716329,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70156876,"text":"70156876 - 2015 - Soil surface organic layers in Arctic Alaska: spatial distribution, rates of formation, and microclimatic effects","interactions":[],"lastModifiedDate":"2018-04-04T16:07:37","indexId":"70156876","displayToPublicDate":"2015-07-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Soil surface organic layers in Arctic Alaska: spatial distribution, rates of formation, and microclimatic effects","docAbstract":"<p><span>Organic layers of living and dead vegetation cover the ground surface in many permafrost landscapes and play important roles in ecosystem processes. These soil surface organic layers (SSOLs) store large amounts of carbon and buffer the underlying permafrost and&nbsp;</span><i>its</i><span>&nbsp;contained carbon from changes in aboveground climate. Understanding the dynamics of SSOLs is a prerequisite for predicting how permafrost and carbon stocks will respond to warming climate. Here we ask three questions about SSOLs in a representative area of the Arctic Foothills region of northern Alaska: (1) What environmental factors control the thickness of SSOLs and the carbon they store? (2) How long do SSOLs take to develop on newly stabilized point bars? (3) How do SSOLs affect temperature in the underlying ground? Results show that SSOL thickness and distribution correlate with elevation, drainage area, vegetation productivity, and incoming solar radiation. A multiple regression model based on these correlations can simulate spatial distribution of SSOLs and estimate the organic carbon stored there. SSOLs develop within a few decades after a new, sandy, geomorphic surface stabilizes but require 500&ndash;700&thinsp;years to reach steady state thickness. Mature SSOLs lower the growing season temperature and mean annual temperature of the underlying mineral soil by 8 and 3&deg;C, respectively. We suggest that the proximate effects of warming climate on permafrost landscapes now covered by SSOLs will occur indirectly via climate's effects on the frequency, extent, and severity of disturbances like fires and landslides that disrupt the SSOLs and interfere with their protection of the underlying permafrost.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JG002983","usgsCitation":"Baughman, C., Mann, D., Verbyla, D.L., and Kunz, M.L., 2015, Soil surface organic layers in Arctic Alaska: spatial distribution, rates of formation, and microclimatic effects: Journal of Geophysical Research: Biogeosciences, v. 120, no. 6, p. 1150-1164, https://doi.org/10.1002/2015JG002983.","productDescription":"15 p.","startPage":"1150","endPage":"1164","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064795","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":471970,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jg002983","text":"Publisher Index Page"},{"id":307786,"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              -158.466796875,\n              67.19551751715585\n            ],\n            [\n              -158.466796875,\n              69.12344255014861\n            ],\n            [\n              -155.01708984375,\n              69.12344255014861\n            ],\n            [\n              -155.01708984375,\n              67.19551751715585\n            ],\n            [\n              -158.466796875,\n              67.19551751715585\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"120","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-30","publicationStatus":"PW","scienceBaseUri":"55e6cc37e4b05561fa20a02b","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":570920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mann, Daniel H.","contributorId":97441,"corporation":false,"usgs":true,"family":"Mann","given":"Daniel H.","affiliations":[],"preferred":false,"id":570921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verbyla, David L.","contributorId":84611,"corporation":false,"usgs":true,"family":"Verbyla","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":570922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kunz, Michael L.","contributorId":50820,"corporation":false,"usgs":true,"family":"Kunz","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":570923,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70148422,"text":"sir20155077 - 2015 - Flood Map for the Winooski River in Waterbury, Vermont, 2014","interactions":[],"lastModifiedDate":"2015-07-01T10:40:01","indexId":"sir20155077","displayToPublicDate":"2015-06-30T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5077","title":"Flood Map for the Winooski River in Waterbury, Vermont, 2014","docAbstract":"<p>From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from approximately 4 to more than 7 inches in the Winooski River Basin in Vermont. The rainfall resulted in severe flooding throughout the basin and significant damage along the Winooski River. In response to the flooding, the U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in flood recovery and restoration and to assist in flood forecasting. The study resulted in two sets of flood maps that depict the flooding for an 8.3-mile reach of the Winooski River from about 1,000 feet downstream of the Waterbury-Bolton, Vermont, town line upstream to about 2,000 feet upstream of the Waterbury-Middlesex, Vt., town line.</p>\n<p>The first set of maps consists of flood-recovery maps depicting the boundaries of floodwaters at the 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) discharges, the boundaries of the floodway, and the boundaries of floodwaters from Tropical Storm Irene as estimated by a hydraulic model. The second set of maps consists of flood-inundation maps depicting the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS Winooski River above Crossett Bk at Waterbury, VT (04288040) streamgage. The maps correspond to streamgage water levels ranging from 417.0 to 431.0 feet in 2-foot increments. The availability of these flood-inundation maps along with current stage from the USGS streamgage obtained from a USGS Web site will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts. These flood inundation maps can be accessed through the USGS Flood Inundation Mapping Science Web site (<a href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a>).</p>\n<p>To generate the maps, flood profiles for the Winooski River were developed. The U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model (HEC&ndash;RAS), was used to compute the water-surface profiles along the study reach. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a vertical accuracy that meets or exceeds vertical national map accuracy standards for 2-foot contour mapping to delineate the area flooded for each water-surface profile.</p>\n<p>High-water marks from Tropical Storm Irene were available for seven locations along the study reach. The highwater marks were used to estimate water-surface profiles and discharges resulting from Tropical Storm Irene throughout the study reach. From a comparison of the estimated water-surface profile for Tropical Storm Irene with the water-surface profiles for the 1- and 0.2-percent annual exceedance probability (AEP) floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the Winooski River study reach but did not exceed the estimated 0.2-percent AEP flood at any location within the study reach.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155077","collaboration":"Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2015, Flood Map for the Winooski River in Waterbury, Vermont, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5077, Report: vi, 25 p.; Readme; Appendix; Metadata, https://doi.org/10.3133/sir20155077.","productDescription":"Report: vi, 25 p.; Readme; Appendix; Metadata","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061798","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":305492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155077.jpg"},{"id":305487,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5077/pdf/sir20155077.pdf","text":"Report","size":"5.48 MB","description":"Report"},{"id":305490,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5077/attachments/metadata_floodinundationmap.zip","text":"Metadata for flood inundation map","size":"123 KB","description":"Metadata for flood inundation map","linkHelpText":"Metadata for flood inundation map"},{"id":305488,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2015/5077/attachments/readme.txt","text":"Read me","size":"1 KB","description":"Read Me"},{"id":305489,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5077/attachments/sir2015-5077_appendix1.zip","text":"Map file and dataset","size":"715 MB","description":"Map file and dataset","linkHelpText":"Contains the published map file and the map dataset."},{"id":305491,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5077/attachments/metadata_floodrecoverymap.zip","text":"Metadata for flood recovery map","size":"132 KB","description":"Metadata for flood recovery map","linkHelpText":"Metadata for flood recovery map"},{"id":305486,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5077/"}],"country":"United States","state":"Vermont","city":"Waterbury","otherGeospatial":"Winooski River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.75833129882812,\n              44.319672489734806\n            ],\n            [\n              -72.75833129882812,\n              44.334408514149914\n            ],\n            [\n              -72.73258209228516,\n              44.334408514149914\n            ],\n            [\n              -72.73258209228516,\n              44.319672489734806\n            ],\n            [\n              -72.75833129882812,\n              44.319672489734806\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publicComments":"Prepared in cooperation with the Federal Emergency Management Agency","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5593afa9e4b0b6d21dd68220","contributors":{"authors":[{"text":"Olson, Scott A. 0000-0002-1064-2125 solson@usgs.gov","orcid":"https://orcid.org/0000-0002-1064-2125","contributorId":2059,"corporation":false,"usgs":true,"family":"Olson","given":"Scott","email":"solson@usgs.gov","middleInitial":"A.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548153,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70155517,"text":"70155517 - 2015 - Integrating multiple distribution models to guide conservation efforts of an endangered toad","interactions":[],"lastModifiedDate":"2015-08-10T11:35:56","indexId":"70155517","displayToPublicDate":"2015-06-30T12:30:00","publicationYear":"2015","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":"Integrating multiple distribution models to guide conservation efforts of an endangered toad","docAbstract":"<p><span>Species distribution models are used for numerous purposes such as predicting changes in species&rsquo; ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (</span><i>Anaxyrus californicus</i><span>), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species&rsquo; current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.</span></p>","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0131628","usgsCitation":"Treglia, M.L., Fisher, R.N., and Fitzgerald, L., 2015, Integrating multiple distribution models to guide conservation efforts of an endangered toad: PLoS ONE, v. 10, no. 6, p. 1-18, https://doi.org/10.1371/journal.pone.0131628.","productDescription":"18 p.","startPage":"1","endPage":"18","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064868","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471988,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0131628","text":"Publisher Index Page"},{"id":306534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.49304199218749,\n              33.99347299511967\n            ],\n            [\n              -118.01513671875,\n              34.50655662164561\n            ],\n            [\n              -116.98242187499999,\n              34.610605760914666\n            ],\n            [\n              -116.26831054687501,\n              34.49750272138159\n            ],\n            [\n              -115.94970703125,\n              34.20271636159618\n            ],\n            [\n              -115.9332275390625,\n              33.73804486328909\n            ],\n            [\n              -115.81787109375,\n              33.44060944370356\n            ],\n            [\n              -115.62561035156249,\n              33.30757713015298\n            ],\n            [\n              -115.51574707031249,\n              33.06852769197118\n            ],\n            [\n              -115.34545898437499,\n              32.68099643258195\n            ],\n            [\n              -117.15270996093749,\n              32.54681317351514\n            ],\n            [\n              -117.158203125,\n              32.62549671451373\n            ],\n            [\n              -117.29553222656249,\n              32.694865977875075\n            ],\n            [\n              -117.31201171875001,\n              32.838058359277056\n            ],\n            [\n              -117.31201171875001,\n              32.98102014898148\n            ],\n            [\n              -117.49877929687499,\n              33.27084277265288\n            ],\n            [\n              -117.7569580078125,\n              33.458942753687644\n            ],\n            [\n              -118.15246582031249,\n              33.706062655101206\n            ],\n            [\n              -118.333740234375,\n              33.67406853374198\n            ],\n            [\n              -118.48205566406251,\n              33.747180448149855\n            ],\n            [\n              -118.4600830078125,\n              33.8247936182649\n            ],\n            [\n              -118.49304199218749,\n              33.99347299511967\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-30","publicationStatus":"PW","scienceBaseUri":"55c9cb34e4b08400b1fdb713","contributors":{"authors":[{"text":"Treglia, Michael L.","contributorId":145921,"corporation":false,"usgs":false,"family":"Treglia","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":16299,"text":"Dep't Wildlife and Fisheries, Texas A&M U, College Station, Texas","active":true,"usgs":false}],"preferred":false,"id":565660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":565659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzgerald, Lee A.","contributorId":145922,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Lee A.","affiliations":[{"id":16300,"text":"Dep't of Wildlife and Fisheries, Texas A&M U, College Station, Texas","active":true,"usgs":false}],"preferred":false,"id":565661,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70214971,"text":"70214971 - 2015 - Holocene diatom-derived climate history of Medicine Lake, northern California, USA","interactions":[],"lastModifiedDate":"2020-10-05T14:24:09.709844","indexId":"70214971","displayToPublicDate":"2015-06-30T09:17:12","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7133,"text":"CIRMOUNT Mountain Views","active":true,"publicationSubtype":{"id":10}},"title":"Holocene diatom-derived climate history of Medicine Lake, northern California, USA","docAbstract":"The Medicine Lake record is unusual because it responds not only to local and regional climate signals, but changes in conditions on Medicine Lake volcano during the Holocene. Ice retreated within the Medicine Lake volcano occurred around 11,400 years ago, followed by filling of two sub-basins. The absence of Cyclotella indicates that the early lake was probably less than 5 m deep. The low Abies/Artemisia ratio suggests that the climate was relatively dry. Over the next 4000 years, the level of the lake rose as relatively organic-rich fine-grained sediments filled the basin. The increase in abundance of Cyclotella also suggests that the lake gradually deepened. The abundance of Abies in the basin also increased, suggesting the presence of a deeper snowpack that existed into the late spring and summer. The increased snowpack was likely the primary water source that filled the lake during this period. About 5500 years ago, the lake flooded the shallow shelf area surrounding the two sub-basins. Variations in the abundance of Cyclotella and benthic taxa, dominated by Navicula, indicate that the area of the flooded shelf fluctuated during this interval. The abundance of Isoetes and Abies responded similarly to changes in the basin, both suggesting an increase in effective moisture. Their increase corresponds to an increase in Sequoia pollen observed at ODP Site 1019, which records the establishment of modern climatic conditions along the northern California coast (relatively warm wet winters and cool, foggy summers). A connection between coastal and inland 6 climates appears to have strengthened at about this time. These fluctuations are in part due to these changes in moisture availability, but may also be due to changes in the shape of the lake basin brought about by the movement of magma within the Medicine Lake volcano.","language":"English","publisher":"USDA","usgsCitation":"Starratt, S.W., 2015, Holocene diatom-derived climate history of Medicine Lake, northern California, USA: CIRMOUNT Mountain Views, v. 9, p. 12-20.","productDescription":"9 p.","startPage":"12","endPage":"20","ipdsId":"IP-066136","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379029,"type":{"id":11,"text":"Document"},"url":"https://www.fs.fed.us/psw/cirmount/publications/pdf/Mtn_Views_june_15.pdf"}],"country":"United States","state":"California","county":"Siskiyou County","otherGeospatial":"Medicine 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,{"id":70148366,"text":"fs20153043 - 2015 - Sediment conditions in the San Antonio River Basin downstream from San Antonio, Texas, 2000-13","interactions":[],"lastModifiedDate":"2016-08-05T11:59:58","indexId":"fs20153043","displayToPublicDate":"2015-06-30T02:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3043","title":"Sediment conditions in the San Antonio River Basin downstream from San Antonio, Texas, 2000-13","docAbstract":"<p>Sediment plays an important role in the ecological health of rivers and estuaries and consequently is an important issue for water-resource managers. To better understand sediment characteristics in the San Antonio River Basin, the U.S. Geological Survey, in cooperation with the San Antonio River Authority, completed a two-part study in the San Antonio River Basin downstream from San Antonio, Texas, to (1) collect and analyze sediment data to characterize sediment conditions and (2) develop and calibrate a watershed model to simulate hydrologic conditions and suspended-sediment loads during 2000&ndash;12.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153043","usgsCitation":"Ockerman, D.J., Banta, J., Crow, C.L., and Opsahl, S.P., 2015, Sediment conditions in the San Antonio River Basin downstream from San Antonio, Texas, 2000-13: U.S. Geological Survey Fact Sheet 2015-3043, 4 p., https://doi.org/10.3133/fs20153043.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2013-05-31","ipdsId":"IP-061350","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":305524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":305448,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3043/"},{"id":305470,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3043/pdf/fs2015-3043.pdf","text":"Report","size":"3.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Texas","otherGeospatial":"San Antonio River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -96.74011230468749,\n              28.41555985166584\n            ],\n            [\n              -96.9268798828125,\n              28.386567819657213\n            ],\n            [\n              -97.4212646484375,\n              28.565225490654658\n            ],\n            [\n              -97.6409912109375,\n              28.69058765425071\n            ],\n            [\n              -97.76184082031249,\n              28.767659105691255\n            ],\n            [\n              -97.943115234375,\n              28.969700808694157\n            ],\n            [\n              -98.1298828125,\n              29.156958511360703\n            ],\n            [\n              -98.2232666015625,\n              29.224096165685452\n            ],\n            [\n              -98.2342529296875,\n              29.406105055709293\n            ],\n            [\n              -98.32763671875,\n              29.6880527498568\n            ],\n            [\n              -98.3111572265625,\n              29.740532166753606\n            ],\n            [\n              -98.1793212890625,\n              29.88351825335318\n            ],\n            [\n              -97.88818359375,\n              29.950175057288813\n            ],\n            [\n              -97.76184082031249,\n              29.969211659636663\n            ],\n            [\n              -97.657470703125,\n              29.869228848968312\n            ],\n            [\n              -97.459716796875,\n              29.67850809103362\n            ],\n            [\n              -97.31689453125,\n              29.501768632523287\n            ],\n            [\n              -97.1685791015625,\n              29.28160772298835\n            ],\n            [\n              -97.1356201171875,\n              29.08977693862319\n            ],\n            [\n              -97.0587158203125,\n              28.878349647602047\n            ],\n            [\n              -96.94335937499999,\n              28.603814407841327\n            ],\n            [\n              -96.74011230468749,\n              28.41555985166584\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5593afaae4b0b6d21dd68224","contributors":{"authors":[{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":563968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banta, J. 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,{"id":70148460,"text":"ofr20151114 - 2015 - California State Waters Map Series — Offshore of Point Reyes, California","interactions":[],"lastModifiedDate":"2022-04-18T20:56:05.493853","indexId":"ofr20151114","displayToPublicDate":"2015-06-30T01:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1114","title":"California State Waters Map Series — Offshore of Point Reyes, California","docAbstract":"<p>This publication about the Offshore of Point Reyes map area includes ten map sheets that contain explanatory text, in addition to this descriptive pamphlet and a data catalog of geographic information system (GIS) files. Sheets 1, 2, and 3 combine data from four different sonar surveys to generate comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic features (highlighted in the perspective views on sheet 4) such as the flat, sediment-covered seafloor in Drakes Bay, as well as abundant &ldquo;scour depressions&rdquo; on the Bodega Head&ndash;Tomales Point shelf (see sheet 9) and local, tectonically controlled bedrock uplifts. To validate geological and biological interpretations of the sonar data shown in sheets 1, 2, and 3, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these &ldquo;ground-truth&rdquo; surveying data are summarized on sheet 6. Sheet 5 is a &ldquo;seafloor character&rdquo; map, which classifies the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. Sheet 7 is a map of &ldquo;potential habitats,&rdquo; which are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Sheet 8 compiles representative seismic-reflection profiles from the map area, providing information on the subsurface stratigraphy and structure of the map area. Sheet 9 shows the distribution and thickness of young sediment (deposited over the last about 21,000 years, during the most recent sea-level rise) in both the map area and the larger Salt Point to Drakes Bay region, interpreted on the basis of the seismic-reflection data, and it identifies the Offshore of Point Reyes map area as lying within the Bodega Head&ndash;Tomales Point shelf, Point Reyes bar, and Bolinas shelf domains. Sheet 10 is a geologic map that merges onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery (sheets 1, 2, 3), seafloor-sediment and rock samples (Reid and others, 2006), digital camera and video imagery (sheet 6), and high-resolution seismic-reflection profiles (sheet 8), as well as aerial-photographic interpretation of nearshore areas. The information provided by the map sheets, pamphlet, and data catalog have a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151114","usgsCitation":"Watt, J., Dartnell, P., Golden, N., Greene, H., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S., Kvitek, R.G., Manson, M., Endris, C.A., Dieter, B.E., Sliter, R.W., Krigsman, L., Lowe, E., and Chinn, J.L., 2015, California State Waters Map Series — Offshore of Point Reyes, California: U.S. Geological Survey Open-File Report 2015-1114, Pamphlet: iv, 39 p.; 10 Sheets: 52 x 36 inches or smaller ; Metadata; Data Catalog, https://doi.org/10.3133/ofr20151114.","productDescription":"Pamphlet: iv, 39 p.; 10 Sheets: 52 x 36 inches or smaller ; Metadata; Data Catalog","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055336","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":305464,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 8","linkHelpText":"Seismic-Reflection Profiles, Offshore of Point Reyes Map Area, California By Janet T. Watt, Samuel Y. Johnson, John L. Chin, and Ray W. Sliter"},{"id":305458,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 2","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Point Reyes Map Area, California By Peter Dartnell and Rikk G. Kvitek"},{"id":305457,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 1","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Point Reyes Map Area, California By Peter Dartnell and Rikk G. Kvitek"},{"id":305459,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 3","linkHelpText":"Acoustic Backscatter, Offshore of Point Reyes Map Area, California By Peter Dartnell, Mercedes D. Erdey, and Rikk G. Kvitek"},{"id":305456,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"Pamphlet"},{"id":305455,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1114/"},{"id":305467,"rank":13,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1114/ofr20151114_metadata.html"},{"id":305468,"rank":14,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html","text":"Data Catalog-Offshore of Point Reyes, California","description":"Data Catalog-Offshore of Point Reyes, California","linkHelpText":"Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":305460,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 4","linkHelpText":"Data Integration and Visualization, Offshore of Point Reyes Map Area, California By Peter Dartnell"},{"id":305461,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 5","linkHelpText":"Seafloor Character, Offshore of Point Reyes Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":305462,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 6","linkHelpText":"Ground-Truth Studies, Offshore of Point Reyes Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Lisa M. Krigsman"},{"id":305463,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 7","linkHelpText":"Potential Marine Benthic Habitats, Offshore of Point Reyes Map Area, California By Charles A. Endris, H. Gary Greene, Bryan E. Dieter, Erik N. Lowe, and Mercedes D. Erdey"},{"id":305465,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 9","linkHelpText":"Local (Offshore of Point Reyes Map Area) and Regional (Offshore from Salt Point to Drakes Bay) Shallow-Subsurface Geology and Structure, California By Janet T. Watt, Samuel Y. Johnson, Stephen R. Hartwell, and Ray W. Sliter"},{"id":305466,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2015/1114/pdf/ofr20151114_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 10","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Point Reyes Map Area, California By Janet T. Watt, Michael W. Manson, and H. Gary Greene"},{"id":305469,"rank":15,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1114/images/coverthb.jpg"},{"id":399004,"rank":16,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_102082.htm"}],"scale":"24000","projection":"Universal Transverse Mercator projection, Zone 10N","country":"United States","state":"California","city":"Point Reyes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.0936,\n              37.9389\n            ],\n            [\n              -123.0936,\n              38.0981\n            ],\n            [\n              -122.8931,\n              38.0981\n            ],\n            [\n              -122.8931,\n              37.9389\n            ],\n            [\n              -123.0936,\n              37.9389\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5593afa7e4b0b6d21dd6821e","contributors":{"editors":[{"text":"Watt, Janet 0000-0002-4759-3814 jwatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":146222,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"jwatt@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":564023,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":564024,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Watt, Janet 0000-0002-4759-3814 jwatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":146222,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"jwatt@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":548272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golden, Nadine E. ngolden@usgs.gov","contributorId":140878,"corporation":false,"usgs":true,"family":"Golden","given":"Nadine E.","email":"ngolden@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":548273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greene, H. Gary","contributorId":38958,"corporation":false,"usgs":true,"family":"Greene","given":"H. 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,{"id":70155864,"text":"70155864 - 2015 - Ocean circulation and biogeochemistry moderate interannual and decadal surface water pH changes in the Sargasso Sea","interactions":[],"lastModifiedDate":"2015-08-17T09:58:34","indexId":"70155864","displayToPublicDate":"2015-06-28T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ocean circulation and biogeochemistry moderate interannual and decadal surface water pH changes in the Sargasso Sea","docAbstract":"<p>The oceans absorb anthropogenic CO<sub>2</sub> from the atmosphere, lowering surface ocean pH, a concern for calcifying marine organisms. The impact of ocean acidification is challenging to predict as each species appears to respond differently and because our knowledge of natural changes to ocean pH is limited in both time and space. Here we reconstruct 222 years of biennial seawater pH variability in the Sargasso Sea from a brain coral, <i>Diploria labyrinthiformis</i>. Using hydrographic data from the Bermuda Atlantic Time-series Study and the coral-derived pH record, we are able to differentiate pH changes due to surface temperature versus those from ocean circulation and biogeochemical changes. We find that ocean pH does not simply reflect atmospheric CO<sub>2</sub> trends but rather that circulation/biogeochemical changes account for &gt;90% of pH variability in the Sargasso Sea and more variability in the last century than would be predicted from anthropogenic uptake of CO<sub>2</sub> alone.</p>","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015GL064431","collaboration":"Asian School of the Environment, Nanyang Technological Unicersity, Singapore\nEarth Observatory of Singapore, Singapore\nNational Cheung Kung University, Tainan, Taiwan\nWoods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA\nBermuda Institute of Ocean Sciences, St. George’s, Bermuda\nAcademia Sinica, Taipei, Taiwan","usgsCitation":"Goodkin, N.F., Wang, B., You, C., Hughen, K., Prouty, N.G., Bates, N., and Doney, S., 2015, Ocean circulation and biogeochemistry moderate interannual and decadal surface water pH changes in the Sargasso Sea: Geophysical Research Letters, v. 42, no. 12, p. 4931-4939, https://doi.org/10.1002/2015GL064431.","productDescription":"9 p.","startPage":"4931","endPage":"4939","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064178","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064431","text":"Publisher Index Page"},{"id":306776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-25","publicationStatus":"PW","scienceBaseUri":"55d305b8e4b0518e35468d13","contributors":{"authors":[{"text":"Goodkin, Nathalie F.","contributorId":146214,"corporation":false,"usgs":false,"family":"Goodkin","given":"Nathalie","email":"","middleInitial":"F.","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":566627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Bo-Shian","contributorId":146215,"corporation":false,"usgs":false,"family":"Wang","given":"Bo-Shian","email":"","affiliations":[{"id":16632,"text":"National Cheung Kung University","active":true,"usgs":false}],"preferred":false,"id":566628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"You, Chen-Feng","contributorId":146216,"corporation":false,"usgs":false,"family":"You","given":"Chen-Feng","email":"","affiliations":[{"id":16632,"text":"National Cheung Kung University","active":true,"usgs":false}],"preferred":false,"id":566629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughen, Konrad","contributorId":146217,"corporation":false,"usgs":false,"family":"Hughen","given":"Konrad","email":"","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":566630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":566626,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bates, Nicholas","contributorId":146218,"corporation":false,"usgs":false,"family":"Bates","given":"Nicholas","email":"","affiliations":[{"id":16634,"text":"Bermuda Institute of Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":566631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Doney, Scott","contributorId":146219,"corporation":false,"usgs":false,"family":"Doney","given":"Scott","email":"","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":566632,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70188820,"text":"70188820 - 2015 - Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Inmachuk, Kugruk, Kiwalik, and Koyuk River drainages, Granite Mountain, and the northern Darby Mountains, Bendeleben, Candle, Kotzebue, and Solomon quadrangles, Alaska","interactions":[],"lastModifiedDate":"2017-06-27T13:33:22","indexId":"70188820","displayToPublicDate":"2015-06-27T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Inmachuk, Kugruk, Kiwalik, and Koyuk River drainages, Granite Mountain, and the northern Darby Mountains, Bendeleben, Candle, Kotzebue, and Solomon quadrangles, Alaska","docAbstract":"<p>The State of Alaska’s Strategic and Critical Minerals (SCM) Assessment project, a State-funded Capital Improvement Project (CIP), is designed to evaluate Alaska’s statewide potential for SCM resources. The SCM Assessment is being implemented by the Alaska Division of Geological &amp; Geophysical Surveys (DGGS), and involves obtaining new airborne-geophysical, geological, and geochemical data. As part of the SCM Assessment, thousands of historical geochemical samples from DGGS, U.S. Geological Survey (USGS), and U.S. Bureau of Mines archives are being reanalyzed by DGGS using modern, quantitative, geochemical-analytical methods. The objective is to update the statewide geochemical database to more clearly identify areas in Alaska with SCM potential. </p><p>The USGS is also undertaking SCM-related geologic studies in Alaska through the federally funded Alaska Critical Minerals cooperative project. DGGS and USGS share the goal of evaluating Alaska’s strategic and critical minerals potential and together created a Letter of Agreement (signed December 2012) and a supplementary Technical Assistance Agreement (#14CMTAA143458) to facilitate the two agencies’ cooperative work. Under these agreements, DGGS contracted the USGS in Denver to reanalyze historical USGS sediment samples from Alaska.</p><p> For this report, DGGS funded reanalysis of 653 historical USGS sediment samples from the statewide Alaska Geochemical Database Version 2.0 (AGDB2; Granitto and others, 2013). Samples were chosen from an area covering portions of the Inmachuk, Kugruk, Kiwalik, and Koyuk river drainages, Granite Mountain, and the northern Darby Mountains, located in the Bendeleben, Candle, Kotzebue, and Solomon quadrangles of eastern Seward Peninsula, Alaska (fig. 1). The USGS was responsible for sample retrieval from the National Geochemical Sample Archive (NGSA) in Denver, Colorado through the final quality assurance/quality control (QA/QC) of the geochemical analyses obtained through the USGS contract lab. The new geochemical data are published in this report as a coauthored DGGS report, and will be incorporated into the statewide geochemical databases of both agencies.</p>","language":"English","publisher":"Alaska Division of Geological & Geophysical Surveys","doi":"10.14509/29448","collaboration":"Alaska Division of Geological & Geophysical Surveys; Melanie B. Werdon, lead author","usgsCitation":"Werdon, M.B., Granitto, M., and Azain, J.S., 2015, Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Inmachuk, Kugruk, Kiwalik, and Koyuk River drainages, Granite Mountain, and the northern Darby Mountains, Bendeleben, Candle, Kotzebue, and Solomon quadrangles, Alaska, 5 p. , https://doi.org/10.14509/29448.","productDescription":"5 p. 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,{"id":70173907,"text":"70173907 - 2015 - An empirical evaluation of landscape energetic models: Mallard and American black duck space use during the non-breeding period","interactions":[],"lastModifiedDate":"2016-06-15T11:16:51","indexId":"70173907","displayToPublicDate":"2015-06-26T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"An empirical evaluation of landscape energetic models: Mallard and American black duck space use during the non-breeding period","docAbstract":"<p><span>Bird conservation Joint Ventures are collaborative partnerships between public agencies and private organizations that facilitate habitat management to support waterfowl and other bird populations. A subset of Joint Ventures has developed energetic carrying capacity models (ECCs) to translate regional waterfowl population goals into habitat objectives during the non-breeding period. Energetic carrying capacity models consider food biomass, metabolism, and available habitat to estimate waterfowl carrying capacity within an area. To evaluate Joint Venture ECCs in the context of waterfowl space use, we monitored 33 female mallards (</span><i>Anas platyrhynchos</i><span>) and 55 female American black ducks (</span><i>A. rubripes</i><span>) using global positioning system satellite telemetry in the central and eastern United States. To quantify space use, we measured first-passage time (FPT: time required for an individual to transit across a circle of a given radius) at biologically relevant spatial scales for mallards (3.46&thinsp;km) and American black ducks (2.30&thinsp;km) during the non-breeding period, which included autumn migration, winter, and spring migration. We developed a series of models to predict FPT using Joint Venture ECCs and compared them to a biological null model that quantified habitat composition and a statistical null model, which included intercept and random terms. Energetic carrying capacity models predicted mallard space use more efficiently during autumn and spring migrations, but the statistical null was the top model for winter. For American black ducks, ECCs did not improve predictions of space use; the biological null was top ranked for winter and the statistical null was top ranked for spring migration. Thus, ECCs provided limited insight into predicting waterfowl space use during the non-breeding season. Refined estimates of spatial and temporal variation in food abundance, habitat conditions, and anthropogenic disturbance will likely improve ECCs and benefit conservation planners in linking non-breeding waterfowl habitat objectives with distribution and population parameters. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.</span></p>","language":"English","publisher":"Washington Wildlife Society","doi":"10.1002/jwmg.920","usgsCitation":"Beatty, W.S., Webb, E.B., Kesler, D.C., Naylor, L.W., Raedeke, A.H., Humburg, D.D., Coluccy, J.M., and Soulliere, G., 2015, An empirical evaluation of landscape energetic models: Mallard and American black duck space use during the non-breeding period: Journal of Wildlife Management, v. 79, no. 7, p. 1141-1151, https://doi.org/10.1002/jwmg.920.","productDescription":"11 p.","startPage":"1141","endPage":"1151","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058474","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":323669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Arkansas, Delaware, Louisiana, Michigan, New Jersey, New York, Ohio, Oklahoma, Saskatchewan, Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.251953125,\n              31.914867503276223\n            ],\n            [\n              -94.39453125,\n              36.20882309283712\n            ],\n            [\n              -107.0068359375,\n              49.95121990866206\n            ],\n            [\n              -84.55078125,\n              44.653024159812\n            ],\n            [\n              -80.9912109375,\n              41.73852846935917\n            ],\n            [\n              -74.091796875,\n              44.84029065139799\n            ],\n            [\n              -75.5419921875,\n              38.92522904714054\n            ],\n            [\n              -77.95898437499999,\n              37.055177106660814\n            ],\n            [\n              -93.251953125,\n              31.914867503276223\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"79","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-26","publicationStatus":"PW","scienceBaseUri":"57627c2de4b07657d19a69c0","contributors":{"authors":[{"text":"Beatty, William S. 0000-0003-0013-3113","orcid":"https://orcid.org/0000-0003-0013-3113","contributorId":146301,"corporation":false,"usgs":false,"family":"Beatty","given":"William","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":638980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":638981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kesler, Dylan C.","contributorId":14358,"corporation":false,"usgs":false,"family":"Kesler","given":"Dylan","email":"","middleInitial":"C.","affiliations":[{"id":6769,"text":"University of Missouri, Columbia, MO","active":true,"usgs":false}],"preferred":false,"id":638982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naylor, Luke W.","contributorId":145840,"corporation":false,"usgs":false,"family":"Naylor","given":"Luke","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":638983,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raedeke, Andrew H.","contributorId":94083,"corporation":false,"usgs":true,"family":"Raedeke","given":"Andrew","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":638984,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Humburg, Dale D.","contributorId":79357,"corporation":false,"usgs":false,"family":"Humburg","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":13073,"text":"Ducks Unlimited, Inc.","active":true,"usgs":false}],"preferred":false,"id":638985,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Coluccy, John M.","contributorId":111382,"corporation":false,"usgs":true,"family":"Coluccy","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638986,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Soulliere, G.","contributorId":31107,"corporation":false,"usgs":true,"family":"Soulliere","given":"G.","email":"","affiliations":[],"preferred":false,"id":638987,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70188821,"text":"70188821 - 2015 - Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Kougarok area, Bendeleben and Teller quadrangles, Seward Peninsula, Alaska","interactions":[],"lastModifiedDate":"2017-06-27T13:24:02","indexId":"70188821","displayToPublicDate":"2015-06-26T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Kougarok area, Bendeleben and Teller quadrangles, Seward Peninsula, Alaska","docAbstract":"<p>The State of Alaska’s Strategic and Critical Minerals (SCM) Assessment project, a State-funded Capital Improvement Project (CIP), is designed to evaluate Alaska’s statewide potential for SCM resources. The SCM Assessment is being implemented by the Alaska Division of Geological &amp; Geophysical Surveys (DGGS), and involves obtaining new airborne-geophysical, geological, and geochemical data. As part of the SCM Assessment, thousands of historical geochemical samples from DGGS, U.S. Geological Survey (USGS), and U.S. Bureau of Mines archives are being reanalyzed by DGGS using modern, quantitative, geochemical-analytical methods. The objective is to update the statewide geochemical database to more clearly identify areas in Alaska with SCM potential.</p><p> The USGS is also undertaking SCM-related geologic studies in Alaska through the federally funded Alaska Critical Minerals cooperative project. DGGS and USGS share the goal of evaluating Alaska’s strategic and critical minerals potential and together created a Letter of Agreement (signed December 2012) and a supplementary Technical Assistance Agreement (#14CMTAA143458) to facilitate the two agencies’ cooperative work. Under these agreements, DGGS contracted the USGS in Denver to reanalyze historical USGS sediment samples from Alaska.</p><p> For this report, DGGS funded reanalysis of 302 historical USGS sediment samples from the statewide Alaska Geochemical Database Version 2.0 (AGDB2; Granitto and others, 2013). Samples were chosen from the Kougarok River drainage as well as smaller adjacent drainages in the Bendeleben and Teller quadrangles, Seward Peninsula, Alaska (fig. 1). The USGS was responsible for sample retrieval from the National Geochemical Sample Archive (NGSA) in Denver, Colorado through the final quality assurance/quality control (QA/QC) of the geochemical analyses obtained through the USGS contract lab. The new geochemical data are published in this report as a coauthored DGGS report, and will be incorporated into the statewide geochemical databases of both agencies.</p>","largerWorkTitle":"Alaska Division of Geological & Geophysical Surveys","language":"English","publisher":"Alaska Division of Geological & Geophysical Surveys","doi":"10.14509/29450","collaboration":"Alaska Division of Geological & Geophysical Surveys; Melanie B. Werdon, lead author","usgsCitation":"Werdon, M.B., Granitto, M., and Azain, J.S., 2015, Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Kougarok area, Bendeleben and Teller quadrangles, Seward Peninsula, Alaska, Report: 5 p. , https://doi.org/10.14509/29450.","productDescription":"Report: 5 p. 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,{"id":70155915,"text":"70155915 - 2015 - Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor","interactions":[],"lastModifiedDate":"2017-02-13T14:15:49","indexId":"70155915","displayToPublicDate":"2015-06-25T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor","docAbstract":"<p>Myriad field, laboratory, and modeling studies show that nutrient availability plays a fundamental role in regulating CO<sub>2</sub> exchange between the Earth's biosphere and atmosphere, and in determining how carbon pools and fluxes respond to climatic change. Accordingly, global models that incorporate coupled climate&ndash;carbon cycle feedbacks made a significant advance with the introduction of a prognostic nitrogen cycle. Here we propose that incorporating phosphorus cycling represents an important next step in coupled climate&ndash;carbon cycling model development, particularly for lowland tropical forests where phosphorus availability is often presumed to limit primary production. We highlight challenges to including phosphorus in modeling efforts and provide suggestions for how to move forward.</p>","language":"English","publisher":"Wiley","doi":"10.1111/nph.13521","usgsCitation":"Reed, S.C., Yang, X., and Thornton, P.E., 2015, Incorporating phosphorus cycling into global modeling efforts: a worthwhile, tractable endeavor: New Phytologist, v. 208, no. 2, p. 324-329, https://doi.org/10.1111/nph.13521.","productDescription":"6 p.","startPage":"324","endPage":"329","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061435","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":471994,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1335328","text":"External Repository"},{"id":306872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"208","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-25","publicationStatus":"PW","scienceBaseUri":"55d45731e4b0518e354694cd","contributors":{"authors":[{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":566809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Xiaojuan","contributorId":146256,"corporation":false,"usgs":false,"family":"Yang","given":"Xiaojuan","email":"","affiliations":[{"id":16649,"text":"Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN 37831-6335, USA","active":true,"usgs":false}],"preferred":false,"id":566810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thornton, Peter E.","contributorId":146257,"corporation":false,"usgs":false,"family":"Thornton","given":"Peter","email":"","middleInitial":"E.","affiliations":[{"id":16649,"text":"Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN 37831-6335, USA","active":true,"usgs":false}],"preferred":false,"id":566811,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188822,"text":"70188822 - 2015 - Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Haines area, Juneau and Skagway quadrangles, southeast Alaska","interactions":[],"lastModifiedDate":"2017-06-27T13:20:08","indexId":"70188822","displayToPublicDate":"2015-06-25T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Haines area, Juneau and Skagway quadrangles, southeast Alaska","docAbstract":"<p>The State of Alaska’s Strategic and Critical Minerals (SCM) Assessment project, a State-funded Capital Improvement Project (CIP), is designed to evaluate Alaska’s statewide potential for SCM resources. The SCM Assessment is being implemented by the Alaska Division of Geological &amp; Geophysical Surveys (DGGS), and involves obtaining new airborne-geophysical, geological, and geochemical data. As part of the SCM Assessment, thousands of historical geochemical samples from DGGS, U.S. Geological Survey (USGS), and U.S. Bureau of Mines archives are being reanalyzed by DGGS using modern, quantitative, geochemical-analytical methods. The objective is to update the statewide geochemical database to more clearly identify areas in Alaska with SCM potential. </p><p>The USGS is also undertaking SCM-related geologic studies in Alaska through the federally funded Alaska Critical Minerals cooperative project. DGGS and USGS share the goal of evaluating Alaska’s strategic and critical minerals potential and together created a Letter of Agreement (signed December 2012) and a supplementary Technical Assistance Agreement (#14CMTAA143458) to facilitate the two agencies’ cooperative work. Under these agreements, DGGS contracted the USGS in Denver to reanalyze historical USGS sediment samples from Alaska.</p><p> For this report, DGGS funded reanalysis of 212 historical USGS sediment samples from the statewide Alaska Geochemical Database Version 2.0 (AGDB2; Granitto and others, 2013). Samples were chosen from the Chilkat, Klehini, Tsirku, and Takhin river drainages, as well as smaller drainages flowing into Chilkat and Chilkoot Inlets near Haines, Skagway Quadrangle, Southeast Alaska. Additionally some samples were also chosen from the Juneau gold belt, Juneau Quadrangle, Southeast Alaska (fig. 1). The USGS was responsible for sample retrieval from the National Geochemical Sample Archive (NGSA) in Denver, Colorado through the final quality assurance/quality control (QA/QC) of the geochemical analyses obtained through the USGS contract lab. The new geochemical data are published in this report as a coauthored DGGS report, and will be incorporated into the statewide geochemical databases of both agencies.</p>","language":"English","publisher":"Alaska Division of Geological & Geophysical Surveys","doi":"10.14509/29449","collaboration":"Alaska Division of Geological & Geophysical Surveys; Melanie B. Werdon, lead author","usgsCitation":"Werdon, M.B., Granitto, M., and Azain, J.S., 2015, Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the Haines area, Juneau and Skagway quadrangles, southeast Alaska, Report: 5 p. , https://doi.org/10.14509/29449.","productDescription":"Report: 5 p. ","startPage":"1","endPage":"5","numberOfPages":"7","ipdsId":"IP-064893","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":471993,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14509/29449","text":"Publisher Index Page"},{"id":342977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Juneau, Skagway","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -136.834716796875,\n              58.274843152138224\n            ],\n            [\n              -136.61499023437497,\n              57.87981645527839\n            ],\n            [\n              -136.197509765625,\n              57.326521225217064\n            ],\n            [\n              -135.9228515625,\n              56.9149999944584\n            ],\n            [\n              -135.692138671875,\n              56.90900226702048\n            ],\n            [\n              -135.384521484375,\n              56.926992558907564\n            ],\n            [\n              -134.80224609375,\n              57.00485033534416\n            ],\n            [\n              -134.373779296875,\n              57.088515327886505\n            ],\n            [\n              -133.978271484375,\n              57.15411997029898\n            ],\n            [\n              -133.450927734375,\n              57.231502991478926\n            ],\n            [\n              -132.82470703125,\n              57.38578314962142\n            ],\n            [\n              -132.74780273437497,\n              57.52172277909666\n            ],\n            [\n              -133.011474609375,\n              57.66303463288711\n            ],\n            [\n              -133.23120117187497,\n              57.850597609050936\n            ],\n            [\n              -133.648681640625,\n              58.228596132481435\n            ],\n            [\n              -133.857421875,\n              58.53386043181558\n            ],\n            [\n              -134.329833984375,\n              58.808052288384594\n            ],\n            [\n              -134.736328125,\n              59.0009698708429\n            ],\n            [\n              -135.032958984375,\n              59.10266722885381\n            ],\n            [\n              -135.516357421875,\n              59.383583679536315\n            ],\n            [\n              -136.087646484375,\n              59.271494782025684\n            ],\n            [\n              -136.61499023437497,\n              59.06315402462662\n            ],\n            [\n              -137.164306640625,\n              58.91599192355906\n            ],\n            [\n              -137.70263671875,\n              58.619777025081675\n            ],\n            [\n              -136.834716796875,\n              58.274843152138224\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536eabe4b062508e3c7a8d","contributors":{"authors":[{"text":"Werdon, Melanie B.","contributorId":193448,"corporation":false,"usgs":false,"family":"Werdon","given":"Melanie","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":700499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granitto, Matthew 0000-0003-3445-4863 granitto@usgs.gov","orcid":"https://orcid.org/0000-0003-3445-4863","contributorId":1224,"corporation":false,"usgs":true,"family":"Granitto","given":"Matthew","email":"granitto@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":700498,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Azain, Jaime S. 0000-0002-8256-7494 jsazain@usgs.gov","orcid":"https://orcid.org/0000-0002-8256-7494","contributorId":5963,"corporation":false,"usgs":true,"family":"Azain","given":"Jaime","email":"jsazain@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700500,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70150405,"text":"70150405 - 2015 - Context-dependent survival, fecundity and predicted population-level consequences of brucellosis in African buffalo","interactions":[],"lastModifiedDate":"2018-08-09T12:51:26","indexId":"70150405","displayToPublicDate":"2015-06-24T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Context-dependent survival, fecundity and predicted population-level consequences of brucellosis in African buffalo","docAbstract":"<ol id=\"jane12356-list-0001\" class=\"numbered\">\n<li>Chronic infections may have negative impacts on wildlife populations, yet their effects are difficult to detect in the absence of long-term population monitoring.&nbsp;<i>Brucella abortus</i>, the bacteria responsible for bovine brucellosis, causes chronic infections and abortions in wild and domestic ungulates, but its impact on population dynamics is not well understood.</li>\n<li>We report infection patterns and fitness correlates of bovine brucellosis in African buffalo based on (1) 7&nbsp;years of cross-sectional disease surveys and (2) a 4-year longitudinal study in Kruger National Park (KNP), South Africa. We then used a matrix population model to translate these observed patterns into predicted population-level effects.</li>\n<li>Annual brucellosis seroprevalence ranged from 8&middot;7% (95% CI&nbsp;=&nbsp;1&middot;8&ndash;15&middot;6) to 47&middot;6% (95% CI&nbsp;=&nbsp;35&middot;1&ndash;60&middot;1) increased with age until adulthood (&gt;6) and varied by location within KNP. Animals were on average in worse condition after testing positive for brucellosis (<i>F</i>&nbsp;=&nbsp;&minus;5&middot;074,&nbsp;<i>P</i>&nbsp;&lt;&nbsp;0&middot;0001), and infection was associated with a 2&middot;0 (95% CI&nbsp;=&nbsp;1&middot;1&ndash;3&middot;7) fold increase in mortality (&chi;<sup>2</sup>&nbsp;=&nbsp;2&middot;039,&nbsp;<i>P</i>&nbsp;=&nbsp;0&middot;036). Buffalo in low body condition were associated with lower reproductive success (<i>F</i>&nbsp;=&nbsp;2&middot;683,&nbsp;<i>P</i>&nbsp;=&nbsp;0&middot;034), but there was no association between brucellosis and pregnancy or being observed with a calf.</li>\n<li>For the range of body condition scores observed in the population, the model-predicted growth rate was &lambda;&nbsp;=&nbsp;1&middot;11 (95% CI&nbsp;=&nbsp;1&middot;02&ndash;1&middot;21) in herds without brucellosis and &lambda;&nbsp;=&nbsp;1&middot;00 (95% CI&nbsp;=&nbsp;0&middot;85&ndash;1&middot;16) when brucellosis seroprevalence was 30%.</li>\n<li>Our results suggest that brucellosis infection can potentially result in reduced population growth rates, but because these effects varied with demographic and environmental conditions, they may remain unseen without intensive, longitudinal monitoring.</li>\n</ol>","language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12356","usgsCitation":"Gorsich, E.E., Ezenwa, V.O., Cross, P.C., Bengis, R.G., and Jolles, A.E., 2015, Context-dependent survival, fecundity and predicted population-level consequences of brucellosis in African buffalo: Journal of Animal Ecology, v. 84, p. 999-1009, https://doi.org/10.1111/1365-2656.12356.","productDescription":"11 p.","startPage":"999","endPage":"1009","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058077","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":302280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"South Africa","otherGeospatial":"Kruger National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            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PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-18","publicationStatus":"PW","scienceBaseUri":"558bc6b0e4b0b6d21dd6528c","contributors":{"authors":[{"text":"Gorsich, Erin E.","contributorId":143680,"corporation":false,"usgs":false,"family":"Gorsich","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":15301,"text":"Department of Integrative Biology, Oregon State University, Corvallis, USA","active":true,"usgs":false}],"preferred":false,"id":556774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ezenwa, Vanessa O.","contributorId":143681,"corporation":false,"usgs":false,"family":"Ezenwa","given":"Vanessa","email":"","middleInitial":"O.","affiliations":[{"id":15302,"text":"Odum School of Ecology and Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, USA","active":true,"usgs":false}],"preferred":false,"id":556775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":556773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bengis, Roy G.","contributorId":29636,"corporation":false,"usgs":true,"family":"Bengis","given":"Roy","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":556776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jolles, Anna E.","contributorId":40421,"corporation":false,"usgs":true,"family":"Jolles","given":"Anna","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":556777,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70150362,"text":"70150362 - 2015 - Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru","interactions":[],"lastModifiedDate":"2015-06-24T10:14:50","indexId":"70150362","displayToPublicDate":"2015-06-24T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru","docAbstract":"<p><span>Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.</span></p>","language":"English","publisher":"SPIE","doi":"10.1117/1.JRS.9.096040","usgsCitation":"Shermeyer, J.S., and Haack, B.N., 2015, Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru: Journal of Applied Remote Sensing, v. 9, no. 1, e096040: 15 p., https://doi.org/10.1117/1.JRS.9.096040.","productDescription":"e096040: 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059192","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":302274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","state":"Madre de Dios","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -68.8623046875,\n              -13.004557745339769\n            ],\n            [\n              -69.60937499999999,\n              -13.346865014577924\n            ],\n            [\n              -70.4443359375,\n              -13.090179355733726\n            ],\n            [\n              -70.83984375,\n              -13.068776734357694\n            ],\n            [\n              -71.12548828125,\n              -13.2399454992863\n            ],\n            [\n              -71.2353515625,\n              -12.940322128384627\n            ],\n            [\n              -71.630859375,\n              -12.661777510388525\n            ],\n            [\n              -71.78466796874999,\n              -12.790374787613588\n            ],\n            [\n              -72.1142578125,\n              -12.44730485070126\n            ],\n            [\n              -71.96044921875,\n              -12.275598890561733\n            ],\n            [\n              -72.158203125,\n              -12.08229583736359\n            ],\n            [\n              -72.421875,\n              -11.73830237143684\n            ],\n            [\n              -72.158203125,\n              -11.005904459659451\n            ],\n            [\n              -71.3671875,\n              -10.919617760254685\n            ],\n            [\n              -71.19140625,\n              -10.552621801948709\n            ],\n            [\n              -70.6201171875,\n              -10.033766870069249\n            ],\n            [\n              -70.6201171875,\n              -10.941191793456534\n            ],\n            [\n              -70.33447265624999,\n              -11.027472194117934\n            ],\n            [\n              -69.9169921875,\n              -10.919617760254685\n            ],\n            [\n              -69.5654296875,\n              -10.962764256386809\n            ],\n            [\n              -68.64257812499999,\n              -12.40438894466978\n            ],\n            [\n              -68.8623046875,\n              -13.004557745339769\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"9","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"558bc6b2e4b0b6d21dd6529a","contributors":{"authors":[{"text":"Shermeyer, Jacob S. 0000-0002-8143-2790 jshermeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8143-2790","contributorId":5825,"corporation":false,"usgs":true,"family":"Shermeyer","given":"Jacob","email":"jshermeyer@usgs.gov","middleInitial":"S.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":556736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haack, Barry N. bhaack@usgs.gov","contributorId":4261,"corporation":false,"usgs":true,"family":"Haack","given":"Barry","email":"bhaack@usgs.gov","middleInitial":"N.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":556737,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70150365,"text":"70150365 - 2015 - Improving estimates of tree mortality probability using potential growth rate","interactions":[],"lastModifiedDate":"2015-06-24T09:58:08","indexId":"70150365","displayToPublicDate":"2015-06-24T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Improving estimates of tree mortality probability using potential growth rate","docAbstract":"<p><span>Tree growth rate is frequently used to estimate mortality probability. Yet, growth metrics can vary in form, and the justification for using one over another is rarely clear. We tested whether a growth index (GI) that scales the realized diameter growth rate against the potential diameter growth rate (PDGR) would give better estimates of mortality probability than other measures. We also tested whether PDGR, being a function of tree size, might better correlate with the baseline mortality probability than direct measurements of size such as diameter or basal area. Using a long-term dataset from the Sierra Nevada, California, U.S.A., as well as existing species-specific estimates of PDGR, we developed growth&ndash;mortality models for four common species. For three of the four species, models that included GI, PDGR, or a combination of GI and PDGR were substantially better than models without them. For the fourth species, the models including GI and PDGR performed roughly as well as a model that included only the diameter growth rate. Our results suggest that using PDGR can improve our ability to estimate tree survival probability. However, in the absence of PDGR estimates, the diameter growth rate was the best empirical predictor of mortality, in contrast to assumptions often made in the literature.</span></p>","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfr-2014-0368","usgsCitation":"Das, A., and Stephenson, N.L., 2015, Improving estimates of tree mortality probability using potential growth rate: Canadian Journal of Forest Research, v. 45, p. 920-928, https://doi.org/10.1139/cjfr-2014-0368.","productDescription":"9 p.","startPage":"920","endPage":"928","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059276","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":302273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada, Sequoia National Park, Yosemite National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.201416015625,\n              37.302460074782296\n            ],\n            [\n              -120.201416015625,\n              37.99183365313853\n            ],\n            [\n              -119.036865234375,\n              37.99183365313853\n            ],\n            [\n              -119.036865234375,\n              37.302460074782296\n            ],\n            [\n              -120.201416015625,\n              37.302460074782296\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.30603027343749,\n              35.22318504970181\n            ],\n            [\n              -119.30603027343749,\n              36.87522650673951\n            ],\n            [\n              -117.90527343750001,\n              36.87522650673951\n            ],\n            [\n              -117.90527343750001,\n              35.22318504970181\n            ],\n            [\n              -119.30603027343749,\n              35.22318504970181\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"558bc6b2e4b0b6d21dd65296","contributors":{"authors":[{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":556739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, Nathan L. 0000-0003-0208-7229 nstephenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0208-7229","contributorId":2836,"corporation":false,"usgs":true,"family":"Stephenson","given":"Nathan","email":"nstephenson@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":556738,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70150465,"text":"70150465 - 2015 - Linking dynamic habitat selection with wading bird foraging distributions across resource gradients","interactions":[],"lastModifiedDate":"2015-06-26T09:48:07","indexId":"70150465","displayToPublicDate":"2015-06-24T10:45:00","publicationYear":"2015","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":"Linking dynamic habitat selection with wading bird foraging distributions across resource gradients","docAbstract":"<p>Species distribution models (SDM) link species occurrence with a suite of environmental predictors and provide an estimate of habitat quality when the variable set captures the biological requirements of the species. SDMs are inherently more complex when they include components of a species' ecology such as conspecific attraction and behavioral flexibility to exploit resources that vary across time and space. Wading birds are highly mobile, demonstrate flexible habitat selection, and respond quickly to changes in habitat quality; thus serving as important indicator species for wetland systems. We developed a spatio-temporal, multi-SDM framework using Great Egret (<i>Ardea alba</i>), White Ibis (<i>Eudocimus albus</i>), and Wood Stork (<i>Mycteria Americana</i>) distributions over a decadal gradient of environmental conditions to predict species-specific abundance across space and locations used on the landscape over time. In models of temporal dynamics, species demonstrated conditional preferences for resources based on resource levels linked to differing temporal scales. Wading bird abundance was highest when prey production from optimal periods of inundation was concentrated in shallow depths. Similar responses were observed in models predicting locations used over time, accounting for spatial autocorrelation. Species clustered in response to differing habitat conditions, indicating that social attraction can co-vary with foraging strategy, water-level changes, and habitat quality. This modeling framework can be applied to evaluate the multi-annual resource pulses occurring in real-time, climate change scenarios, or restorative hydrological regimes by tracking changing seasonal and annual distribution and abundance of high quality foraging patches.</p>","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0128182","usgsCitation":"Beerens, J.M., Noonberg, E.G., and Gawlik, D.E., 2015, Linking dynamic habitat selection with wading bird foraging distributions across resource gradients: PLoS ONE, v. 10, no. 6, p. 1-25, https://doi.org/10.1371/journal.pone.0128182.","productDescription":"25 p.","startPage":"1","endPage":"25","numberOfPages":"25","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060476","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":471995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0128182","text":"Publisher Index Page"},{"id":302361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-24","publicationStatus":"PW","scienceBaseUri":"558e77b8e4b0b6d21dd65963","contributors":{"authors":[{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","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":556926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noonberg, Erik G.","contributorId":143723,"corporation":false,"usgs":false,"family":"Noonberg","given":"Erik","email":"","middleInitial":"G.","affiliations":[{"id":15312,"text":"Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":556927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gawlik, Dale E.","contributorId":88055,"corporation":false,"usgs":true,"family":"Gawlik","given":"Dale","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":556928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188823,"text":"70188823 - 2015 - Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the northeastern Alaska Range, Healy, Mount Hayes, Nabesna, and Tanacross quadrangles, Alaska","interactions":[],"lastModifiedDate":"2017-06-27T13:12:42","indexId":"70188823","displayToPublicDate":"2015-06-24T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the northeastern Alaska Range, Healy, Mount Hayes, Nabesna, and Tanacross quadrangles, Alaska","docAbstract":"<p>The State of Alaska’s Strategic and Critical Minerals (SCM) Assessment project, a State-funded Capital Improvement Project (CIP), is designed to evaluate Alaska’s statewide potential for SCM resources. The SCM Assessment is being implemented by the Alaska Division of Geological &amp; Geophysical Surveys (DGGS), and involves obtaining new airborne-geophysical, geological, and geochemical data. As part of the SCM Assessment, thousands of historical geochemical samples from DGGS, U.S. Geological Survey (USGS), and U.S. Bureau of Mines archives are being reanalyzed by DGGS using modern, quantitative, geochemical-analytical methods. The objective is to update the statewide geochemical database to more clearly identify areas in Alaska with SCM potential.</p><p> The USGS is also undertaking SCM-related geologic studies in Alaska through the federally funded Alaska Critical Minerals cooperative project. DGGS and USGS share the goal of evaluating Alaska’s strategic and critical minerals potential and together created a Letter of Agreement (signed December 2012) and a supplementary Technical Assistance Agreement (#14CMTAA143458) to facilitate the two agencies’ cooperative work. Under these agreements, DGGS contracted the USGS in Denver to reanalyze historical USGS sediment samples from Alaska. </p><p>For this report, DGGS funded reanalysis of 670 historical USGS sediment samples from the statewide Alaska Geochemical Database Version 2.0 (AGDB2; Granitto and others, 2013). Samples were chosen from the northeastern Alaska Range, in the Healy, Mount Hayes, Nabesna, and Tanacross quadrangles, Alaska (fig. 1). The USGS was responsible for sample retrieval from the National Geochemical Sample Archive (NGSA) in Denver, Colorado through the final quality assurance/quality control (QA/QC) of the geochemical analyses obtained through the USGS contract lab. The new geochemical data are published in this report as a coauthored DGGS report, and will be incorporated into the statewide geochemical databases of both agencies.</p>","language":"English","publisher":"Alaska Division of Geological & Geophysical Surveys","doi":"10.14509/29451","collaboration":"Alaska Division of Geological & Geophysical Surveys; Melanie B. Werdon, lead author","usgsCitation":"Werdon, M.B., Granitto, M., and Azain, J.S., 2015, Geochemical reanalysis of historical U.S. Geological Survey sediment samples from the northeastern Alaska Range, Healy, Mount Hayes, Nabesna, and Tanacross quadrangles, Alaska, Report: 6 p. , https://doi.org/10.14509/29451.","productDescription":"Report: 6 p. ","startPage":"1","endPage":"6","numberOfPages":"8","ipdsId":"IP-064896","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":471998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14509/29451","text":"Publisher Index Page"},{"id":342976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Hayes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -150.17211914062497,\n              64.46332329319623\n            ],\n            [\n              -150.18310546875,\n              64.29229248039543\n            ],\n            [\n              -150.27099609375003,\n              62.70942526220763\n            ],\n            [\n              -141.48193359375,\n              62.6791861968537\n            ],\n            [\n              -141.690673828125,\n              64.52482316878356\n            ],\n            [\n              -150.18310546875,\n              64.62387720204688\n            ],\n            [\n              -150.17211914062497,\n              64.46332329319623\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59536eabe4b062508e3c7a91","contributors":{"authors":[{"text":"Werdon, Melanie B.","contributorId":193448,"corporation":false,"usgs":false,"family":"Werdon","given":"Melanie","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":700502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granitto, Matthew 0000-0003-3445-4863 granitto@usgs.gov","orcid":"https://orcid.org/0000-0003-3445-4863","contributorId":1224,"corporation":false,"usgs":true,"family":"Granitto","given":"Matthew","email":"granitto@usgs.gov","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":700501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Azain, Jaime S. 0000-0002-8256-7494 jsazain@usgs.gov","orcid":"https://orcid.org/0000-0002-8256-7494","contributorId":5963,"corporation":false,"usgs":true,"family":"Azain","given":"Jaime","email":"jsazain@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":700503,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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