{"pageNumber":"575","pageRowStart":"14350","pageSize":"25","recordCount":40783,"records":[{"id":70134476,"text":"70134476 - 2014 - 238U-230Th dating of chevkinite in high-silica rhyolites from La Primavera and Yellowstone calderas","interactions":[],"lastModifiedDate":"2020-12-21T18:03:10.742854","indexId":"70134476","displayToPublicDate":"2014-12-01T10:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"238U-230Th dating of chevkinite in high-silica rhyolites from La Primavera and Yellowstone calderas","title":"238U-230Th dating of chevkinite in high-silica rhyolites from La Primavera and Yellowstone calderas","docAbstract":"

Application of 238U-230Th disequilibrium dating of accessory minerals with contrasting stabilities and compositions can provide a unique perspective on magmatic evolution by placing the thermochemical evolution of magma within the framework of absolute time. Chevkinite, a Th-rich accessory mineral that occurs in peralkaline and metaluminous rhyolites, may be particularly useful as a chronometer of crystallization and differentiation because its composition may reflect the chemical changes of its host melt. Ion microprobe 128U-230Th dating of single chevkinite microphenocrysts from pre- and post-caldera La Primavera, Mexico, rhyolites yields model crystallization ages that are within 10's of k.y. of their corresponding K-Ar ages of ca. 125 ka to 85 ka, while chevkinite microphenocrysts from a post-caldera Yellowstone, USA, rhyolite yield a range of ages from ca. 110 ka to 250 ka, which is indistinguishable from the age distribution of coexisting zircon. Internal chevkinite-zircon isochrons from La Primavera yield Pleistocene ages with ~5% precision due to the nearly two order difference in Th/U between both minerals. Coupling chevkinite 238U-230Th ages and compositional analyses reveals a secular trend of Th/U and rare earth elements recorded in Yellowstone rhyolite, likely reflecting progressive compositional evolution of host magma. The relatively short timescale between chevkinite-zircon crystallization and eruption suggests that crystal-poor rhyolites at La Primavera were erupted shortly after differentiation and/or reheating. These results indicate that 238U-230Th dating of chevkinite via ion microprobe analysis may be used to date crystallization and chemical evolution of silicic magmas.

","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.chemgeo.2014.10.020","usgsCitation":"Vazquez, J.A., Velasco, N.O., Schmitt, A.K., Bleick, H.A., and Stelten, M.E., 2014, 238U-230Th dating of chevkinite in high-silica rhyolites from La Primavera and Yellowstone calderas: Chemical Geology, v. 390, p. 109-118, https://doi.org/10.1016/j.chemgeo.2014.10.020.","productDescription":"10 p.","startPage":"109","endPage":"118","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057469","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":296368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Jalisco, Wyoming","otherGeospatial":"La Primavera Caldera, Yellowstone Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.02783203125,\n 43.89789239125797\n ],\n [\n -109.423828125,\n 43.89789239125797\n ],\n [\n -109.423828125,\n 44.87144275016589\n ],\n [\n -111.02783203125,\n 44.87144275016589\n ],\n [\n -111.02783203125,\n 43.89789239125797\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.63677978515625,\n 20.55436654260967\n ],\n [\n -103.502197265625,\n 20.55436654260967\n ],\n [\n -103.502197265625,\n 20.65977117086933\n ],\n [\n -103.63677978515625,\n 20.65977117086933\n ],\n [\n -103.63677978515625,\n 20.55436654260967\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"390","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"547ee2b3e4b09357f05f8a34","contributors":{"authors":[{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":525973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Velasco, Noel O.","contributorId":127613,"corporation":false,"usgs":false,"family":"Velasco","given":"Noel","email":"","middleInitial":"O.","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":525974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmitt, Axel K.","contributorId":127614,"corporation":false,"usgs":false,"family":"Schmitt","given":"Axel","email":"","middleInitial":"K.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":525975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bleick, Heather A. hbleick@usgs.gov","contributorId":2484,"corporation":false,"usgs":true,"family":"Bleick","given":"Heather","email":"hbleick@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":525976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stelten, Mark E.","contributorId":127615,"corporation":false,"usgs":false,"family":"Stelten","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":525977,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70139355,"text":"70139355 - 2014 - A visualization tool to support decision making in environmental and biological planning","interactions":[],"lastModifiedDate":"2015-01-27T09:37:05","indexId":"70139355","displayToPublicDate":"2014-12-01T09:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A visualization tool to support decision making in environmental and biological planning","docAbstract":"

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

","language":"English","publisher":"Elsevier Science Ltd.","publisherLocation":"Oxford","doi":"10.1016/j.envsoft.2014.09.008","usgsCitation":"Romañach, S., McKelvy, M., Conzelmann, C., and Suir, K.J., 2014, A visualization tool to support decision making in environmental and biological planning: Environmental Modelling and Software, v. 62, p. 221-229, https://doi.org/10.1016/j.envsoft.2014.09.008.","productDescription":"9 p.","startPage":"221","endPage":"229","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046311","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472610,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2014.09.008","text":"Publisher Index Page"},{"id":297571,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":297563,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.envsoft.2014.09.008"}],"volume":"62","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a4fe4b08de9379b2fd5","contributors":{"authors":[{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":2331,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":539318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKelvy, Mark 0000-0001-5465-2571 mckelvym@usgs.gov","orcid":"https://orcid.org/0000-0001-5465-2571","contributorId":4865,"corporation":false,"usgs":true,"family":"McKelvy","given":"Mark","email":"mckelvym@usgs.gov","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":539317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conzelmann, Craig 0000-0002-4227-8719 conzelmannc@usgs.gov","orcid":"https://orcid.org/0000-0002-4227-8719","contributorId":2361,"corporation":false,"usgs":true,"family":"Conzelmann","given":"Craig","email":"conzelmannc@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":539344,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160460,"text":"70160460 - 2014 - Site selection and nest survival of the Bar-Headed Goose (Anser indicus) on the Mongolian Plateau","interactions":[],"lastModifiedDate":"2017-07-19T15:43:40","indexId":"70160460","displayToPublicDate":"2014-12-01T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Site selection and nest survival of the Bar-Headed Goose (Anser indicus) on the Mongolian Plateau","docAbstract":"

Waterbirds breeding on the Mongolian Plateau in Central Asia must find suitable wetland areas for nesting in a semiarid region characterized by highly variable water conditions. The first systematic nesting study of a waterbird dependent on this region for breeding was conducted on the Bar-headed Goose (Anser indicus). The purpose of this study was to document Bar-headed Goose nesting locations, characterize nests and nesting strategies, and estimate daily nest survival (n = 235 nests) from eight areas of west-central Mongolia across three summers (2009–2011) using a modified Mayfield estimator. Bar-headed Goose daily nest survival ranged from 0.94 to 0.98, with a 3-year average nest success of 42.6% during incubation. Bar-headed Geese were found to primarily nest on isolated pond and lake islands as previously reported, but were also documented regularly, though less frequently, along rocky cliffs in several regions of west-central Mongolia. Daily nest survival was higher for cliff nests than for island nests. Information-theoretic models indicated that nest survival decreased with nest age and varied annually with changing environmental conditions. Results of this study suggest that while Bar-headed Geese primarily rely on nesting island sites these sites may be more susceptible to anthropogenic disturbance and predation events influenced by seasonal variation in environmental conditions, and that higher daily nest survival values documented for the less frequent cliff nest strategy may provide an important alternative strategy during poor island nest success years. Thus, conservation efforts for this and other waterbird species in the semiarid region should be focused on conserving nesting islands and protecting them from disturbance in areas of high livestock densities experiencing a rapidly warming climate.

","language":"English","publisher":"The Waterbird Society","publisherLocation":"Washington D.C.","doi":"10.1675/063.037.0405","usgsCitation":"Batbayar, N., Takekawa, J.Y., Natsagdorj, T., Spragens, K., and Xiao, X., 2014, Site selection and nest survival of the Bar-Headed Goose (Anser indicus) on the Mongolian Plateau: Waterbirds, v. 37, no. 4, p. 381-393, https://doi.org/10.1675/063.037.0405.","productDescription":"13 p.","startPage":"381","endPage":"393","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054305","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":312563,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mongolia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[87.75126,49.2972],[88.80557,49.47052],[90.71367,50.33181],[92.23471,50.80217],[93.10422,50.49529],[94.14757,50.48054],[94.81595,50.01343],[95.81403,49.97747],[97.25973,49.72606],[98.23176,50.4224],[97.82574,51.011],[98.86149,52.04737],[99.98173,51.63401],[100.88948,51.51686],[102.06522,51.25992],[102.25591,50.51056],[103.67655,50.08997],[104.62155,50.27533],[105.88659,50.40602],[106.8888,50.2743],[107.86818,49.79371],[108.47517,49.28255],[109.40245,49.29296],[110.66201,49.13013],[111.58123,49.37797],[112.89774,49.54357],[114.36246,50.2483],[114.96211,50.14025],[115.4857,49.80518],[116.6788,49.88853],[116.1918,49.1346],[115.48528,48.13538],[115.74284,47.72654],[116.30895,47.85341],[117.29551,47.69771],[118.06414,48.06673],[118.86657,47.74706],[119.77282,47.04806],[119.66327,46.69268],[118.87433,46.80541],[117.4217,46.67273],[116.71787,46.3882],[115.9851,45.72724],[114.46033,45.33982],[113.46391,44.80889],[112.43606,45.01165],[111.87331,45.10208],[111.34838,44.45744],[111.66774,44.07318],[111.82959,43.74312],[111.12968,43.40683],[110.4121,42.87123],[109.2436,42.51945],[107.74477,42.48152],[106.12932,42.13433],[104.96499,41.59741],[104.52228,41.90835],[103.31228,41.90747],[101.83304,42.51487],[100.84587,42.6638],[99.51582,42.52469],[97.45176,42.74889],[96.3494,42.72564],[95.76245,43.31945],[95.30688,44.24133],[94.68893,44.35233],[93.48073,44.97547],[92.13389,45.11508],[90.94554,45.28607],[90.58577,45.71972],[90.97081,46.88815],[90.28083,47.69355],[88.8543,48.06908],[88.01383,48.59946],[87.75126,49.2972]]]},\"properties\":{\"name\":\"Mongolia\"}}]}","volume":"37","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567930d4e4b0da412f4fb597","contributors":{"authors":[{"text":"Batbayar, Nyambayar","contributorId":40338,"corporation":false,"usgs":true,"family":"Batbayar","given":"Nyambayar","affiliations":[],"preferred":false,"id":582967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":582966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Natsagdorj, Tseveenmyadag","contributorId":28729,"corporation":false,"usgs":true,"family":"Natsagdorj","given":"Tseveenmyadag","email":"","affiliations":[],"preferred":false,"id":582968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spragens, Kyle A.","contributorId":98452,"corporation":false,"usgs":true,"family":"Spragens","given":"Kyle A.","affiliations":[],"preferred":false,"id":582969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiao, Xiamgming","contributorId":150758,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiamgming","email":"","affiliations":[{"id":18094,"text":"Dep't Micorbiology & Plant Biology, and Center for Spatial Analysis, U of OK, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":582970,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168383,"text":"70168383 - 2014 - Assessing and managing freshwater ecosystems vulnerable to global change","interactions":[],"lastModifiedDate":"2016-02-11T13:05:37","indexId":"70168383","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":698,"text":"Ambio","active":true,"publicationSubtype":{"id":10}},"title":"Assessing and managing freshwater ecosystems vulnerable to global change","docAbstract":"

Freshwater ecosystems are important for global biodiversity and provide essential ecosystem services. There is consensus in the scientific literature that freshwater ecosystems are vulnerable to the impacts of environmental change, which may trigger irreversible regime shifts upon which biodiversity and ecosystem services may be lost. There are profound uncertainties regarding the management and assessment of the vulnerability of freshwater ecosystems to environmental change. Quantitative approaches are needed to reduce this uncertainty. We describe available statistical and modeling approaches along with case studies that demonstrate how resilience theory can be applied to aid decision-making in natural resources management. We highlight especially how long-term monitoring efforts combined with ecological theory can provide a novel nexus between ecological impact assessment and management, and the quantification of systemic vulnerability and thus the resilience of ecosystems to environmental change.

","language":"English","publisher":"The Royal Swedish Academy of Sciences","doi":"10.1007/s13280-014-0566-z","usgsCitation":"Angeler, D., Allen, C.R., Birge, H.E., Drakare, S., McKie, B.G., and Johnson, R.K., 2014, Assessing and managing freshwater ecosystems vulnerable to global change: Ambio, v. 43, no. Supplement 1, p. 113-125, https://doi.org/10.1007/s13280-014-0566-z.","productDescription":"13 p.","startPage":"113","endPage":"125","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059657","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472626,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13280-014-0566-z","text":"Publisher Index Page"},{"id":317954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden, United States","otherGeospatial":"Florida Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 20.5224609375,\n 69.09993967425089\n ],\n [\n 22.060546874999996,\n 68.54431504077692\n ],\n [\n 23.4228515625,\n 68.23682270936281\n ],\n [\n 23.6865234375,\n 67.87554134672945\n ],\n [\n 23.7744140625,\n 67.39059859150743\n ],\n [\n 24.08203125,\n 66.73990169639414\n ],\n [\n 23.818359375,\n 66.24916310923315\n ],\n [\n 24.2578125,\n 65.82078234733756\n ],\n [\n 23.1591796875,\n 65.69447579373418\n ],\n [\n 22.543945312499996,\n 65.73062649311031\n ],\n [\n 21.97265625,\n 65.33017791526855\n ],\n [\n 21.4013671875,\n 64.86760781632728\n ],\n [\n 21.665039062499996,\n 64.45384948864441\n ],\n [\n 21.26953125,\n 64.03374392176401\n ],\n [\n 19.3798828125,\n 63.27318217465046\n ],\n [\n 18.1494140625,\n 62.512317938386914\n ],\n [\n 17.3583984375,\n 61.85614879566797\n ],\n [\n 17.3583984375,\n 61.18562468142283\n ],\n [\n 17.578125,\n 60.73768583450925\n ],\n [\n 18.4130859375,\n 60.56537850464181\n ],\n [\n 18.80859375,\n 60.13056361691419\n ],\n [\n 19.1162109375,\n 59.7563950493563\n ],\n [\n 18.80859375,\n 59.377988012638895\n ],\n [\n 18.0615234375,\n 58.81374171570782\n ],\n [\n 17.1826171875,\n 58.58543569119917\n ],\n [\n 16.875,\n 58.21702494960191\n ],\n [\n 16.875,\n 57.53941679447497\n ],\n [\n 16.6552734375,\n 56.992882804633986\n ],\n [\n 16.1279296875,\n 56.1210604250441\n ],\n [\n 15.556640624999998,\n 56.072035471800866\n ],\n [\n 14.809570312499998,\n 56.04749958329888\n ],\n [\n 14.501953124999998,\n 55.85064987433714\n ],\n [\n 14.5458984375,\n 55.47885346331034\n ],\n [\n 13.886718749999998,\n 55.30413773740139\n ],\n [\n 12.6123046875,\n 55.32914440840507\n ],\n [\n 12.6123046875,\n 55.801280971180454\n ],\n [\n 12.3046875,\n 56.389583525613055\n ],\n [\n 12.568359375,\n 56.68037378950137\n ],\n [\n 11.953125,\n 57.350237477396824\n ],\n [\n 11.337890625,\n 58.07787626787517\n ],\n [\n 11.074218749999998,\n 58.90464570302001\n ],\n [\n 11.6015625,\n 58.99531118795094\n ],\n [\n 11.8212890625,\n 59.33318942659219\n ],\n [\n 11.689453125,\n 59.57885104663186\n ],\n [\n 12.568359375,\n 60.34869562531862\n ],\n [\n 12.1728515625,\n 61.079544234557304\n ],\n [\n 12.65625,\n 61.16443708638275\n ],\n [\n 12.7880859375,\n 61.39671887310411\n ],\n [\n 12.0849609375,\n 61.71070595883174\n ],\n [\n 12.216796875,\n 62.34960927573045\n ],\n [\n 12.041015625,\n 62.71446210149774\n ],\n [\n 12.041015625,\n 63.05495931065107\n ],\n [\n 11.865234375,\n 63.35212928507874\n ],\n [\n 12.3486328125,\n 63.918058296491104\n ],\n [\n 13.095703125,\n 64.11060221954631\n ],\n [\n 13.974609375,\n 64.11060221954631\n ],\n [\n 14.0185546875,\n 64.41592147626879\n ],\n [\n 13.6669921875,\n 64.60503753178526\n ],\n [\n 14.0625,\n 65.10914820386473\n ],\n [\n 14.414062499999998,\n 65.58572002329473\n ],\n [\n 14.414062499999998,\n 66.17826596326798\n ],\n [\n 15.2490234375,\n 66.30220547599842\n ],\n [\n 15.556640624999998,\n 66.67038675925365\n ],\n [\n 16.34765625,\n 67.22105296735408\n ],\n [\n 16.171875,\n 67.55894799883033\n ],\n [\n 16.3916015625,\n 67.75939813204413\n ],\n [\n 17.1826171875,\n 68.15520923883976\n ],\n [\n 17.9296875,\n 68.00757101804004\n ],\n [\n 18.0615234375,\n 68.51214331858073\n ],\n [\n 18.544921875,\n 68.6245436634471\n ],\n [\n 19.5556640625,\n 68.52823492039876\n ],\n [\n 19.86328125,\n 68.46379955520322\n ],\n [\n 19.951171875,\n 68.56038368664157\n ],\n [\n 20.3466796875,\n 68.83180177092166\n ],\n [\n 19.9951171875,\n 69.05285807666016\n ],\n [\n 20.5224609375,\n 69.09993967425089\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.990966796875,\n 25.095548539604252\n ],\n [\n -81.990966796875,\n 26.54922257769204\n ],\n [\n -80.0189208984375,\n 26.54922257769204\n ],\n [\n -80.0189208984375,\n 25.095548539604252\n ],\n [\n -81.990966796875,\n 25.095548539604252\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"Supplement 1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-15","publicationStatus":"PW","scienceBaseUri":"56bdbebfe4b06458514aeebf","contributors":{"authors":[{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":619934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":619842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birge, Hannah E.","contributorId":166737,"corporation":false,"usgs":false,"family":"Birge","given":"Hannah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":619935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drakare, Stina","contributorId":166738,"corporation":false,"usgs":false,"family":"Drakare","given":"Stina","email":"","affiliations":[],"preferred":false,"id":619936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKie, Brendan G.","contributorId":166739,"corporation":false,"usgs":false,"family":"McKie","given":"Brendan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":619937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Richard K.","contributorId":21810,"corporation":false,"usgs":true,"family":"Johnson","given":"Richard","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":619938,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70156296,"text":"70156296 - 2014 - Approximations of stand water use versus evapotranspiration from three mangrove forests in southwest Florida, USA","interactions":[],"lastModifiedDate":"2015-08-25T14:20:18","indexId":"70156296","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"Approximations of stand water use versus evapotranspiration from three mangrove forests in southwest Florida, USA","docAbstract":"

Leaves from mangrove forests are often considered efficient in the use of water during photosynthesis, but less is known about whole-tree and stand-level water use strategies. Are mangrove forests as conservative in water use as experimental studies on seedlings imply? Here, we apply a simple model to estimate stand water use (S), determine the contribution of S to evapotranspiration (ET), and approximate the distribution of S versus ET over annual cycles for three mangrove forests in southwest Florida, USA. The value of S ranged from 350 to 511 mm year−1 for two mangrove forests in Rookery Bay to 872 mm year−1 for a mangrove forest along the Shark River in Everglades National Park. This represents 34–49% of ET for Rookery Bay mangroves, a rather conservative rate ofS, and 63–66% of ET for the Shark River mangroves, a less conservative rate of S. However, variability in estimates of S in mangroves is high enough to require additional study on the spatial changes related to forest structural shifts, different tidal regimes, and variable site-specific salinity concentrations in multiple mangrove forests before a true account of water use conservation strategies can be understood at the landscape scale. Evidence does suggest that large, well-developed mangrove forests have the potential to contribute considerably to the ET balance; however, regionally most mangrove forests are much smaller in stature in Florida and likely contribute less to regional water losses through stand-level transpiration.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2014.11.014","usgsCitation":"Krauss, K.W., Barr, J.G., Engel, V.C., Fuentes, J.D., and Wang, H., 2014, Approximations of stand water use versus evapotranspiration from three mangrove forests in southwest Florida, USA: Agricultural and Forest Meteorology, v. 213, p. 291-303, https://doi.org/10.1016/j.agrformet.2014.11.014.","productDescription":"13 p.","startPage":"291","endPage":"303","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054911","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":306919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Hall Bay, Henderson Creek, Shark River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.7719268798828,\n 26.005881361953136\n ],\n [\n -81.7719268798828,\n 26.05061418062293\n ],\n [\n -81.71150207519531,\n 26.05061418062293\n ],\n [\n -81.71150207519531,\n 26.005881361953136\n ],\n [\n -81.7719268798828,\n 26.005881361953136\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.1007308959961,\n 25.34542227782849\n ],\n [\n -81.1007308959961,\n 25.372103043852388\n ],\n [\n -81.0516357421875,\n 25.372103043852388\n ],\n [\n -81.0516357421875,\n 25.34542227782849\n ],\n [\n -81.1007308959961,\n 25.34542227782849\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"213","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d5a8ade4b0518e3546a4af","contributors":{"authors":[{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":568549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barr, Jordan G.","contributorId":85809,"corporation":false,"usgs":false,"family":"Barr","given":"Jordan","email":"","middleInitial":"G.","affiliations":[{"id":13531,"text":"South Florida Natural Resource Center, Everglades National Park","active":true,"usgs":false}],"preferred":false,"id":568562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engel, Victor C. 0000-0002-3858-7308 vengel@usgs.gov","orcid":"https://orcid.org/0000-0002-3858-7308","contributorId":2329,"corporation":false,"usgs":true,"family":"Engel","given":"Victor","email":"vengel@usgs.gov","middleInitial":"C.","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":568563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fuentes, Jose D.","contributorId":97231,"corporation":false,"usgs":true,"family":"Fuentes","given":"Jose","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":568564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":140432,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":568565,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155253,"text":"70155253 - 2014 - Understanding recent eastern Horn of Africa rainfall variability and change","interactions":[],"lastModifiedDate":"2018-03-23T13:50:22","indexId":"70155253","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"Understanding recent eastern Horn of Africa rainfall variability and change","docAbstract":"

Observations and sea surface temperature (SST)-forced ECHAM5 simulations are examined to study the seasonal cycle of eastern Africa rainfall and its SST sensitivity during 1979–2012, focusing on interannual variability and trends. The eastern Horn is drier than the rest of equatorial Africa, with two distinct wet seasons, and whereas the October–December wet season has become wetter, the March–May season has become drier.

\n

The climatological rainfall in simulations driven by observed SSTs captures this bimodal regime. The simulated trends also qualitatively reproduce the opposite-sign changes in the two rainy seasons, suggesting that SST forcing has played an important role in the observed changes. The consistency between the sign of 1979–2012 trends and interannual SST–precipitation correlations is exploited to identify the most likely locations of SST forcing of precipitation trends in the model, and conceivably also in nature. Results indicate that the observed March–May drying since 1979 is due to sensitivity to an increased zonal gradient in SST between Indonesia and the central Pacific. In contrast, the October–December precipitation increase is mostly due to western Indian Ocean warming.

\n

The recent upward trend in the October–December wet season is rather weak, however, and its statistical significance is compromised by strong year-to-year fluctuations. October–December eastern Horn rain variability is strongly associated with El Niño–Southern Oscillation and Indian Ocean dipole phenomena on interannual scales, in both model and observations. The interannual October–December correlation between the ensemble-average and observed Horn rainfall 0.87. By comparison, interannual March–May Horn precipitation is only weakly constrained by SST anomalies.

","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JCLI-D-13-00714.1","usgsCitation":"Liebmann, B., Hoerling, M.P., Funk, C.C., Blade, I., Dole, R.M., Allured, D., Quan, X., and Eischeid, J.K., 2014, Understanding recent eastern Horn of Africa rainfall variability and change: Journal of Climate, v. 27, p. 8660-8645, https://doi.org/10.1175/JCLI-D-13-00714.1.","productDescription":"16 p.","startPage":"8660","endPage":"8645","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056089","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-13-00714.1","text":"Publisher Index Page"},{"id":306510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Horn of Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 40.166015625,\n -2.811371193331128\n ],\n [\n 42.275390625,\n -0.7031073524364783\n ],\n [\n 48.69140625,\n 5.266007882805511\n ],\n [\n 51.064453125,\n 10.487811882056683\n ],\n [\n 50.9765625,\n 12.21118019150401\n ],\n [\n 49.21875,\n 11.60919340793894\n ],\n [\n 46.93359375,\n 11.350796722383684\n ],\n [\n 45.17578125,\n 10.746969318460001\n ],\n [\n 43.41796875,\n 11.005904459659464\n ],\n [\n 43.2421875,\n 12.811801316582619\n ],\n [\n 41.8359375,\n 13.923403897723347\n ],\n [\n 40.25390625,\n 14.774882506516272\n ],\n [\n 36.298828125,\n 14.519780046326085\n ],\n [\n 35.77148437499999,\n 12.640338306846802\n ],\n [\n 34.80468749999999,\n 11.005904459659464\n ],\n [\n 34.1015625,\n 10.31491928581316\n ],\n [\n 33.92578125,\n 8.233237111274553\n ],\n [\n 33.22265625,\n 7.710991655433229\n ],\n [\n 33.486328125,\n 5.9657536710655235\n ],\n [\n 34.013671875,\n 2.7235830833483856\n ],\n [\n 33.92578125,\n -1.0546279422758742\n ],\n [\n 33.92578125,\n -2.5479878714713835\n ],\n [\n 33.92578125,\n -4.214943141390639\n ],\n [\n 39.19921875,\n -4.653079918274038\n ],\n [\n 40.166015625,\n -2.811371193331128\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-05","publicationStatus":"PW","scienceBaseUri":"57f7f023e4b0bc0bec09f59a","contributors":{"authors":[{"text":"Liebmann, Brant","contributorId":145807,"corporation":false,"usgs":false,"family":"Liebmann","given":"Brant","email":"","affiliations":[{"id":16238,"text":"NOAA Earth Systems Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":565379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoerling, Martin P.","contributorId":145817,"corporation":false,"usgs":false,"family":"Hoerling","given":"Martin","email":"","middleInitial":"P.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":565380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blade, Ileana","contributorId":145806,"corporation":false,"usgs":false,"family":"Blade","given":"Ileana","email":"","affiliations":[{"id":16237,"text":"Institut Catala de Ciencies del Clima","active":true,"usgs":false}],"preferred":false,"id":567573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dole, Randall M.","contributorId":146364,"corporation":false,"usgs":false,"family":"Dole","given":"Randall","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":567574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allured, Dave","contributorId":146365,"corporation":false,"usgs":false,"family":"Allured","given":"Dave","email":"","affiliations":[],"preferred":false,"id":567575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quan, Xiaowei","contributorId":146366,"corporation":false,"usgs":false,"family":"Quan","given":"Xiaowei","affiliations":[],"preferred":false,"id":567576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eischeid, Jon K.","contributorId":70214,"corporation":false,"usgs":true,"family":"Eischeid","given":"Jon","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":567577,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70147001,"text":"70147001 - 2014 - Ecohydrology of dry regions: storage versus pulse soil water dynamics","interactions":[],"lastModifiedDate":"2015-04-24T14:17:53","indexId":"70147001","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrology of dry regions: storage versus pulse soil water dynamics","docAbstract":"

Although arid and semiarid regions are defined by low precipitation, the seasonal timing of temperature and precipitation can influence net primary production and plant functional type composition. The importance of precipitation seasonality is evident in semiarid areas of the western U.S., which comprise the Intermountain (IM) zone, a region that receives important winter precipitation and is dominated by woody plants and the Great Plains (GP), a region that receives primarily summer precipitation and is dominated by perennial grasses. Although these general relationships are well recognized, specific differences in water cycling between these regions have not been well characterized. We used a daily time step soil water simulation model and twenty sites from each region to analyze differences in soil water dynamics and ecosystem water balance. IM soil water patterns are characterized by storage of water during fall, winter, and spring resulting in relatively reliable available water during spring and early summer, particularly in deep soil layers. By contrast, GP soil water patterns are driven by pulse precipitation events during the warm season, resulting in fluctuating water availability in all soil layers. These contrasting patterns of soil water—storage versus pulse dynamics—explain important differences between the two regions. Notably, the storage dynamics of the IN sites increases water availability in deep soil layers, favoring the deeper rooted woody plants in that region, whereas the pulse dynamics of the Great Plains sites provide water primarily in surface layers, favoring the shallow-rooted grasses in that region. In addition, because water received when plants are either not active or only partially so is more vulnerable to evaporation and sublimation than water delivered during the growing season, IM ecosystems use a smaller fraction of precipitation for transpiration (47%) than GP ecosystems (49%). Recognizing the pulse-storage dichotomy in soil water regimes between the IM and GP regions may be useful for understanding the potential influence of climate changes on soil water patterns and resulting dominant plant functional groups in both regions.

","language":"English","publisher":"Springer","doi":"10.1007/s10021-014-9808-y","usgsCitation":"Lauenroth, W.K., Schlaepfer, D., and Bradford, J.B., 2014, Ecohydrology of dry regions: storage versus pulse soil water dynamics: Ecosystems, v. 17, no. 8, p. 1469-1479, https://doi.org/10.1007/s10021-014-9808-y.","productDescription":"11 p.","startPage":"1469","endPage":"1479","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-029594","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":299874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-01","publicationStatus":"PW","scienceBaseUri":"553b6943e4b0a658d79371b4","contributors":{"authors":[{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":545573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":545572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":545571,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70144504,"text":"70144504 - 2014 - Volcanology: Lessons learned from Synthetic Aperture Radar imagery","interactions":[],"lastModifiedDate":"2019-03-13T09:40:53","indexId":"70144504","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Volcanology: Lessons learned from Synthetic Aperture Radar imagery","docAbstract":"

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work – for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2014.10.010","usgsCitation":"Pinel, V., Poland, M.P., and Hooper, A., 2014, Volcanology: Lessons learned from Synthetic Aperture Radar imagery: Journal of Volcanology and Geothermal Research, v. 289, p. 81-113, https://doi.org/10.1016/j.jvolgeores.2014.10.010.","productDescription":"33 p.","startPage":"81","endPage":"113","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057840","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":299207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"289","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551bc52fe4b0323842783a5e","contributors":{"authors":[{"text":"Pinel, Virginie","contributorId":139984,"corporation":false,"usgs":false,"family":"Pinel","given":"Virginie","email":"","affiliations":[{"id":13343,"text":"Université de Savoie · ISTerre Sciences Institute EARTH","active":true,"usgs":false}],"preferred":false,"id":543663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":127857,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":543662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooper, Andrew","contributorId":139985,"corporation":false,"usgs":false,"family":"Hooper","given":"Andrew","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":543664,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189809,"text":"70189809 - 2014 - Paleogeomorphology of the early Colorado River inferred from relationships in Mohave and Cottonwood Valleys, Arizona, California and Nevada","interactions":[],"lastModifiedDate":"2017-07-26T15:40:00","indexId":"70189809","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Paleogeomorphology of the early Colorado River inferred from relationships in Mohave and Cottonwood Valleys, Arizona, California and Nevada","docAbstract":"

Geologic investigations of late Miocene–early Pliocene deposits in Mohave and Cottonwood valleys provide important insights into the early evolution of the lower Colorado River system. In the latest Miocene these valleys were separate depocenters; the floor of Cottonwood Valley was ∼200 m higher than the floor of Mohave Valley. When Colorado River water arrived from the north after 5.6 Ma, a shallow lake in Cottonwood Valley spilled into Mohave Valley, and the river then filled both valleys to ∼560 m above sea level (asl) and overtopped the bedrock divide at the southern end of Mohave Valley. Sediment-starved water spilling to the south gradually eroded the outlet as siliciclastic Bouse deposits filled the lake upstream. When sediment accumulation reached the elevation of the lowering outlet, continued erosion of the outlet resulted in recycling of stored lacustrine sediment into downstream basins; depth of erosion of the outlet and upstream basins was limited by the water levels in downstream basins. The water level in the southern Bouse basin was ∼300 m asl (modern elevation) at 4.8 Ma. It must have drained and been eroded to a level <150 m asl soon after that to allow for deep erosion of bedrock divides and basins upstream, leading to removal of large volumes of Bouse sediment prior to massive early Pliocene Colorado River aggradation. Abrupt lowering of regional base level due to spilling of a southern Bouse lake to the Gulf of California could have driven observed upstream river incision without uplift. Rapid uplift of the entire region immediately after 4.8 Ma would have been required to drive upstream incision if the southern Bouse was an estuary.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00988.1","usgsCitation":"Pearthree, P., and House, K., 2014, Paleogeomorphology of the early Colorado River inferred from relationships in Mohave and Cottonwood Valleys, Arizona, California and Nevada: Geosphere, v. 10, no. 6, p. 1139-1160, https://doi.org/10.1130/GES00988.1.","productDescription":"22 p.","startPage":"1139","endPage":"1160","ipdsId":"IP-053171","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00988.1","text":"Publisher Index Page"},{"id":344345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River, Cottonwood Valley, Mohave Valley","volume":"10","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-12","publicationStatus":"PW","scienceBaseUri":"5979aa56e4b0ec1a488b8c19","contributors":{"authors":[{"text":"Pearthree, Philip","contributorId":195166,"corporation":false,"usgs":false,"family":"Pearthree","given":"Philip","affiliations":[],"preferred":false,"id":706436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"House, Kyle 0000-0002-0019-8075 khouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0019-8075","contributorId":2293,"corporation":false,"usgs":true,"family":"House","given":"Kyle","email":"khouse@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":706435,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189303,"text":"70189303 - 2014 - The future of nearshore processes research","interactions":[],"lastModifiedDate":"2017-11-12T11:04:59","indexId":"70189303","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"The future of nearshore processes research","docAbstract":"

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment.

Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes:

  1. Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability.
  2. Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities.
  3. The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies.

The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.

","language":"English","publisher":"The Nearshore Processes Community","usgsCitation":"2014, The future of nearshore processes research, 32 p.","productDescription":"32 p.","ipdsId":"IP-063052","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":343516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343509,"type":{"id":11,"text":"Document"},"url":"https://scripps.ucsd.edu/centers/nearshorefuture/wp-content/uploads/sites/37/2014/12/Future_Nearshore_Processes_Research.pdf"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59649235e4b0d1f9f05acd48","contributors":{"editors":[{"text":"Elko, Nicole A.","contributorId":50960,"corporation":false,"usgs":true,"family":"Elko","given":"Nicole","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704063,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Feddersen, Falk","contributorId":194420,"corporation":false,"usgs":false,"family":"Feddersen","given":"Falk","email":"","affiliations":[],"preferred":false,"id":704064,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Foster, Diane","contributorId":194421,"corporation":false,"usgs":false,"family":"Foster","given":"Diane","affiliations":[],"preferred":false,"id":704065,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":704066,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"McNinch, Jesse E.","contributorId":93804,"corporation":false,"usgs":true,"family":"McNinch","given":"Jesse E.","affiliations":[],"preferred":false,"id":704067,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":704068,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Tuba Ozkan-Haller, H.","contributorId":194424,"corporation":false,"usgs":false,"family":"Tuba Ozkan-Haller","given":"H.","email":"","affiliations":[],"preferred":false,"id":704069,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":704070,"contributorType":{"id":2,"text":"Editors"},"rank":8},{"text":"Raubenheimer, Britt","contributorId":194340,"corporation":false,"usgs":false,"family":"Raubenheimer","given":"Britt","email":"","affiliations":[],"preferred":false,"id":704071,"contributorType":{"id":2,"text":"Editors"},"rank":9}]}} ,{"id":70186668,"text":"70186668 - 2014 - Widespread gas hydrate instability on the upper U.S. Beaufort margin","interactions":[],"lastModifiedDate":"2017-04-07T10:25:50","indexId":"70186668","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Widespread gas hydrate instability on the upper U.S. Beaufort margin","docAbstract":"

The most climate-sensitive methane hydrate deposits occur on upper continental slopes at depths close to the minimum pressure and maximum temperature for gas hydrate stability. At these water depths, small perturbations in intermediate ocean water temperatures can lead to gas hydrate dissociation. The Arctic Ocean has experienced more dramatic warming than lower latitudes, but observational data have not been used to study the interplay between upper slope gas hydrates and warming ocean waters. Here we use (a) legacy seismic data that constrain upper slope gas hydrate distributions on the U.S. Beaufort Sea margin, (b) Alaskan North Slope borehole data and offshore thermal gradients determined from gas hydrate stability zone thickness to infer regional heat flow, and (c) 1088 direct measurements to characterize multidecadal intermediate ocean warming in the U.S. Beaufort Sea. Combining these data with a three-dimensional thermal model shows that the observed gas hydrate stability zone is too deep by 100 to 250 m. The disparity can be partially attributed to several processes, but the most important is the reequilibration (thinning) of gas hydrates in response to significant (~0.5°C at 2σ certainty) warming of intermediate ocean temperatures over 39 years in a depth range that brackets the upper slope extent of the gas hydrate stability zone. Even in the absence of additional ocean warming, 0.44 to 2.2 Gt of methane could be released from reequilibrating gas hydrates into the sediments underlying an area of ~5–7.5 × 103 km2 on the U.S. Beaufort Sea upper slope during the next century.

","language":"English","publisher":"AGU","doi":"10.1002/2014JB011290","usgsCitation":"Phrampus, B.J., Hornbach, M.J., Ruppel, C., and Hart, P.E., 2014, Widespread gas hydrate instability on the upper U.S. Beaufort margin: Journal of Geophysical Research B: Solid Earth, v. 119, no. 12, p. 8594-8609, https://doi.org/10.1002/2014JB011290.","productDescription":"16 p.","startPage":"8594","endPage":"8609","ipdsId":"IP-059791","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472616,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1402351","text":"External Repository"},{"id":339397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160,\n 69.5\n ],\n [\n -140,\n 69.5\n ],\n [\n -140,\n 72.5\n ],\n [\n -160,\n 72.5\n ],\n [\n -160,\n 69.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","issue":"12","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-09","publicationStatus":"PW","scienceBaseUri":"58e8a545e4b09da6799d63b1","chorus":{"doi":"10.1002/2014jb011290","url":"http://dx.doi.org/10.1002/2014jb011290","publisher":"Wiley-Blackwell","authors":"Phrampus Benjamin J., Hornbach Matthew J., Ruppel Carolyn D., Hart Patrick E.","journalName":"Journal of Geophysical Research: Solid Earth","publicationDate":"12/2014","auditedOn":"12/7/2014"},"contributors":{"authors":[{"text":"Phrampus, Benjamin J.","contributorId":190655,"corporation":false,"usgs":false,"family":"Phrampus","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":690219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hornbach, Matthew J.","contributorId":14258,"corporation":false,"usgs":true,"family":"Hornbach","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":690220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppel, Carolyn D. 0000-0003-2284-6632 cruppel@usgs.gov","orcid":"https://orcid.org/0000-0003-2284-6632","contributorId":145770,"corporation":false,"usgs":true,"family":"Ruppel","given":"Carolyn D.","email":"cruppel@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":690218,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":690221,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187301,"text":"70187301 - 2014 - Hidden Markov model for dependent mark loss and survival estimation","interactions":[],"lastModifiedDate":"2017-04-27T15:03:46","indexId":"70187301","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Hidden Markov model for dependent mark loss and survival estimation","docAbstract":"

Mark-recapture estimators assume no loss of marks to provide unbiased estimates of population parameters. We describe a hidden Markov model (HMM) framework that integrates a mark loss model with a Cormack–Jolly–Seber model for survival estimation. Mark loss can be estimated with single-marked animals as long as a sub-sample of animals has a permanent mark. Double-marking provides an estimate of mark loss assuming independence but dependence can be modeled with a permanently marked sub-sample. We use a log-linear approach to include covariates for mark loss and dependence which is more flexible than existing published methods for integrated models. The HMM approach is demonstrated with a dataset of black bears (Ursus americanus) with two ear tags and a subset of which were permanently marked with tattoos. The data were analyzed with and without the tattoo. Dropping the tattoos resulted in estimates of survival that were reduced by 0.005–0.035 due to tag loss dependence that could not be modeled. We also analyzed the data with and without the tattoo using a single tag. By not using.

","language":"English","publisher":"Springer","doi":"10.1007/s13253-014-0190-1","usgsCitation":"Laake, J.L., Johnson, D., Diefenbach, D.R., and Ternent, M.A., 2014, Hidden Markov model for dependent mark loss and survival estimation: Journal of Agricultural, Biological, and Environmental Statistics, v. 19, no. 4, p. 522-538, https://doi.org/10.1007/s13253-014-0190-1.","productDescription":"17 p.","startPage":"522","endPage":"538","ipdsId":"IP-057112","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-02","publicationStatus":"PW","scienceBaseUri":"59030328e4b0e862d230f74f","contributors":{"authors":[{"text":"Laake, Jeffrey L.","contributorId":83851,"corporation":false,"usgs":false,"family":"Laake","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":693246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":693247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693233,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ternent, Mark A.","contributorId":150194,"corporation":false,"usgs":false,"family":"Ternent","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":693248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187391,"text":"70187391 - 2014 - Mark-resight abundance estimation under incomplete identification of marked individuals","interactions":[],"lastModifiedDate":"2017-05-01T12:22:50","indexId":"70187391","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Mark-resight abundance estimation under incomplete identification of marked individuals","docAbstract":"
  1. Often less expensive and less invasive than conventional mark–recapture, so-called 'mark-resight' methods are popular in the estimation of population abundance. These methods are most often applied when a subset of the population of interest is marked (naturally or artificially), and non-invasive sighting data can be simultaneously collected for both marked and unmarked individuals. However, it can often be difficult to identify marked individuals with certainty during resighting surveys, and incomplete identification of marked individuals is potentially a major source of bias in mark-resight abundance estimators. Previously proposed solutions are ad hoc and will tend to underperform unless marked individual identification rates are relatively high (>90%) or individual sighting heterogeneity is negligible.
  2. Based on a complete data likelihood, we present an approach that properly accounts for uncertainty in marked individual detection histories when incomplete identifications occur. The models allow for individual heterogeneity in detection, sampling with (e.g. Poisson) or without (e.g. Bernoulli) replacement, and an unknown number of marked individuals. Using a custom Markov chain Monte Carlo algorithm to facilitate Bayesian inference, we demonstrate these models using two example data sets and investigate their properties via simulation experiments.
  3. We estimate abundance for grassland sparrow populations in Pennsylvania, USA when sampling was conducted with replacement and the number of marked individuals was either known or unknown. To increase marked individual identification probabilities, extensive territory mapping was used to assign incomplete identifications to individuals based on location. Despite marked individual identification probabilities as low as 67% in the absence of this territorial mapping procedure, we generally found little return (or need) for this time-consuming investment when using our proposed approach. We also estimate rookery abundance from Alaskan Steller sea lion counts when sampling was conducted without replacement, the number of marked individuals was unknown, and individual heterogeneity was suspected as non-negligible.
  4. In terms of estimator performance, our simulation experiments and examples demonstrated advantages of our proposed approach over previous methods, particularly when marked individual identification probabilities are low and individual heterogeneity levels are high. Our methodology can also reduce field effort requirements for marked individual identification, thus, allowing potential investment into additional marking events or resighting surveys.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12140","usgsCitation":"McClintock, B.T., Hill, J.M., Fritz, L., Chumbley, K., Luxa, K., and Diefenbach, D.R., 2014, Mark-resight abundance estimation under incomplete identification of marked individuals: Methods in Ecology and Evolution, v. 5, no. 12, p. 1294-1304, https://doi.org/10.1111/2041-210X.12140.","productDescription":"11 p.","startPage":"1294","endPage":"1304","ipdsId":"IP-045819","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"12","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-14","publicationStatus":"PW","scienceBaseUri":"5908492ce4b0fc4e448ffd68","contributors":{"authors":[{"text":"McClintock, Brett T. 0000-0001-6154-4376","orcid":"https://orcid.org/0000-0001-6154-4376","contributorId":83785,"corporation":false,"usgs":true,"family":"McClintock","given":"Brett","email":"","middleInitial":"T.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":true,"id":693737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Jason M.","contributorId":191616,"corporation":false,"usgs":false,"family":"Hill","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":693738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritz, Lowell","contributorId":191659,"corporation":false,"usgs":false,"family":"Fritz","given":"Lowell","email":"","affiliations":[],"preferred":false,"id":693739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chumbley, Kathryn","contributorId":191660,"corporation":false,"usgs":false,"family":"Chumbley","given":"Kathryn","email":"","affiliations":[],"preferred":false,"id":693740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luxa, Katie","contributorId":191661,"corporation":false,"usgs":false,"family":"Luxa","given":"Katie","email":"","affiliations":[],"preferred":false,"id":693741,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693733,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192528,"text":"70192528 - 2014 - What do we gain from simplicity versus complexity in species distribution models?","interactions":[],"lastModifiedDate":"2017-10-26T13:28:48","indexId":"70192528","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"What do we gain from simplicity versus complexity in species distribution models?","docAbstract":"

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

","language":"English","publisher":"Wiley","doi":"10.1111/ecog.00845","usgsCitation":"Merow, C., Smith, M.J., Edwards, T., Guisan, A., McMahon, S.M., Normand, S., Thuiller, W., Wuest, R.O., Zimmermann, N.E., and Elith, J., 2014, What do we gain from simplicity versus complexity in species distribution models?: Ecography, v. 37, no. 12, p. 1267-1281, https://doi.org/10.1111/ecog.00845.","productDescription":"15 p.","startPage":"1267","endPage":"1281","ipdsId":"IP-055634","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472622,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/ecog.00845","text":"External Repository"},{"id":347474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-16","publicationStatus":"PW","scienceBaseUri":"5a07ece2e4b09af898c8cd32","contributors":{"authors":[{"text":"Merow, Cory","contributorId":198540,"corporation":false,"usgs":false,"family":"Merow","given":"Cory","email":"","affiliations":[],"preferred":false,"id":716369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Matthew J.","contributorId":61701,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":716370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guisan, Antoine","contributorId":47943,"corporation":false,"usgs":true,"family":"Guisan","given":"Antoine","email":"","affiliations":[],"preferred":false,"id":716371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Sean M. 0000-0001-8302-6908","orcid":"https://orcid.org/0000-0001-8302-6908","contributorId":197833,"corporation":false,"usgs":false,"family":"McMahon","given":"Sean","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716372,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Normand, Signe","contributorId":30545,"corporation":false,"usgs":true,"family":"Normand","given":"Signe","email":"","affiliations":[],"preferred":false,"id":716373,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thuiller, Wilfried","contributorId":38059,"corporation":false,"usgs":true,"family":"Thuiller","given":"Wilfried","email":"","affiliations":[],"preferred":false,"id":716374,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wuest, Rafael O.","contributorId":198544,"corporation":false,"usgs":false,"family":"Wuest","given":"Rafael","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":716375,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zimmermann, Niklaus E.","contributorId":68446,"corporation":false,"usgs":true,"family":"Zimmermann","given":"Niklaus","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":716376,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Elith, Jane","contributorId":14546,"corporation":false,"usgs":true,"family":"Elith","given":"Jane","email":"","affiliations":[],"preferred":false,"id":716377,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70192530,"text":"70192530 - 2014 - Does probability of occurrence relate to population dynamics?","interactions":[],"lastModifiedDate":"2017-10-26T13:24:45","indexId":"70192530","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Does probability of occurrence relate to population dynamics?","docAbstract":"

Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate (r) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range-wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions.

The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K ) and population density (N ) relate to occurrence probability (Pocc ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, western USA, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments.

Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with Pocc, while N, and for most regions K, was generally positively correlated with Pocc. Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models.

","language":"English","publisher":"Wiley","doi":"10.1111/ecog.00836","usgsCitation":"Thuiller, W., Munkemuller, T., Schiffers, K.H., Georges, D., Dullinger, S., Eckhart, V.M., Edwards, T., Gravel, D., Kunstler, G., Merow, C., Moore, K., Piedallu, C., Vissault, S., Zimmermann, N.E., Zurell, D., and Schurr, F.M., 2014, Does probability of occurrence relate to population dynamics?: Ecography, v. 37, no. 12, p. 1155-1166, https://doi.org/10.1111/ecog.00836.","productDescription":"12 p.","startPage":"1155","endPage":"1166","ipdsId":"IP-055287","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472625,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.00836","text":"Publisher Index Page"},{"id":347473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-23","publicationStatus":"PW","scienceBaseUri":"5a07ece2e4b09af898c8cd30","contributors":{"authors":[{"text":"Thuiller, Wilfried","contributorId":38059,"corporation":false,"usgs":true,"family":"Thuiller","given":"Wilfried","email":"","affiliations":[],"preferred":false,"id":716354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munkemuller, Tamara","contributorId":57768,"corporation":false,"usgs":true,"family":"Munkemuller","given":"Tamara","email":"","affiliations":[],"preferred":false,"id":716355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schiffers, Katja H.","contributorId":79019,"corporation":false,"usgs":true,"family":"Schiffers","given":"Katja","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":716356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Georges, Damien","contributorId":198537,"corporation":false,"usgs":false,"family":"Georges","given":"Damien","email":"","affiliations":[],"preferred":false,"id":716357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dullinger, Stefan","contributorId":19080,"corporation":false,"usgs":true,"family":"Dullinger","given":"Stefan","email":"","affiliations":[],"preferred":false,"id":716358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eckhart, Vincent M.","contributorId":198538,"corporation":false,"usgs":false,"family":"Eckhart","given":"Vincent","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716359,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Edwards, Thomas C. Jr. 0000-0002-0773-0909 tce@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-0909","contributorId":191916,"corporation":false,"usgs":true,"family":"Edwards","given":"Thomas C.","suffix":"Jr.","email":"tce@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716130,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gravel, Dominique","contributorId":24277,"corporation":false,"usgs":true,"family":"Gravel","given":"Dominique","email":"","affiliations":[],"preferred":false,"id":716360,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kunstler, Georges","contributorId":198539,"corporation":false,"usgs":false,"family":"Kunstler","given":"Georges","email":"","affiliations":[],"preferred":false,"id":716361,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Merow, Cory","contributorId":198540,"corporation":false,"usgs":false,"family":"Merow","given":"Cory","email":"","affiliations":[],"preferred":false,"id":716362,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Moore, Kara","contributorId":196898,"corporation":false,"usgs":false,"family":"Moore","given":"Kara","email":"","affiliations":[],"preferred":false,"id":716363,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Piedallu, Christian","contributorId":198541,"corporation":false,"usgs":false,"family":"Piedallu","given":"Christian","email":"","affiliations":[],"preferred":false,"id":716364,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vissault, Steve","contributorId":198542,"corporation":false,"usgs":false,"family":"Vissault","given":"Steve","email":"","affiliations":[],"preferred":false,"id":716365,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Zimmermann, Niklaus E.","contributorId":68446,"corporation":false,"usgs":true,"family":"Zimmermann","given":"Niklaus","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":716366,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Zurell, Damaris","contributorId":198543,"corporation":false,"usgs":false,"family":"Zurell","given":"Damaris","email":"","affiliations":[],"preferred":false,"id":716367,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Schurr, Frank M.","contributorId":72708,"corporation":false,"usgs":true,"family":"Schurr","given":"Frank","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":716368,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70187401,"text":"70187401 - 2014 - On the effects of scale for ecosystem services mapping","interactions":[],"lastModifiedDate":"2017-05-01T15:56:58","indexId":"70187401","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","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":"On the effects of scale for ecosystem services mapping","docAbstract":"

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0112601","usgsCitation":"Gret-Regamey, A., Weibel, B., Bagstad, K.J., Ferrari, M., Geneletti, D., Klug, H., Schirpke, U., and Tappeiner, U., 2014, On the effects of scale for ecosystem services mapping: PLoS ONE, v. 9, no. 12, e112601; 26 p., https://doi.org/10.1371/journal.pone.0112601.","productDescription":"e112601; 26 p.","ipdsId":"IP-056762","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":472615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0112601","text":"Publisher Index Page"},{"id":340707,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"12","noUsgsAuthors":false,"publicationDate":"2014-12-30","publicationStatus":"PW","scienceBaseUri":"5908492ce4b0fc4e448ffd66","contributors":{"authors":[{"text":"Gret-Regamey, Adrienne","contributorId":191685,"corporation":false,"usgs":false,"family":"Gret-Regamey","given":"Adrienne","email":"","affiliations":[],"preferred":false,"id":693849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weibel, Bettina","contributorId":108378,"corporation":false,"usgs":true,"family":"Weibel","given":"Bettina","email":"","affiliations":[],"preferred":false,"id":693850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferrari, Marika","contributorId":191686,"corporation":false,"usgs":false,"family":"Ferrari","given":"Marika","email":"","affiliations":[],"preferred":false,"id":693852,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geneletti, Davide","contributorId":191687,"corporation":false,"usgs":false,"family":"Geneletti","given":"Davide","email":"","affiliations":[],"preferred":false,"id":693853,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klug, Hermann","contributorId":189515,"corporation":false,"usgs":false,"family":"Klug","given":"Hermann","email":"","affiliations":[],"preferred":false,"id":693854,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schirpke, Uta","contributorId":191688,"corporation":false,"usgs":false,"family":"Schirpke","given":"Uta","email":"","affiliations":[],"preferred":false,"id":693855,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tappeiner, Ulrike","contributorId":191689,"corporation":false,"usgs":false,"family":"Tappeiner","given":"Ulrike","email":"","affiliations":[],"preferred":false,"id":693856,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187377,"text":"70187377 - 2014 - A comparison of passive and active acoustic sampling for a bat community impacted by White-nose syndrome","interactions":[],"lastModifiedDate":"2017-05-01T10:31:47","indexId":"70187377","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of passive and active acoustic sampling for a bat community impacted by White-nose syndrome","docAbstract":"

In the summers of 2011 and 2012, we compared passive and active acoustic sampling for bats at 31 sites at Fort Drum Military Installation, New York. We defined active sampling as acoustic sampling that occurred in 30-min intervals between the hours of sunset and 0200 with a user present to manipulate the directionality of the microphone. We defined passive sampling as acoustic sampling that occurred over a 12-h period (1900–0700 hours) without a user present and with the microphone set in a predetermined direction. We detected seven of the nine possible species at Fort Drum, including the federally endangered Indiana bat Myotis sodalis, the proposed-for-listing northern bat M. septentrionalis, the little brown bat M. lucifugus, and the big brown bat Eptesicus fuscus, which are impacted by white-nose syndrome (WNS); and the eastern red bat Lasiurus borealis, the hoary bat L. cinereus, and the silver-haired bat Lasionycteris noctivagans, which are not known to be impacted by WNS. We did not detect two additional WNS-impacted species known to historically occur in the area: the eastern small-footed bat Myotis leibii and the tri-colored bat Perimyotis subflavus. Single-season occupancy models revealed lower detection probabilities of all detected species using active sampling versus passive sampling. Additionally, overall detection probabilities declined in detected WNS-impacted species between years. A paired t-test of simultaneous sampling on 21 occasions revealed that overall recorded foraging activity per hour was greater using active than passive sampling for big brown bats and greater using passive than active sampling for little brown bats. There was no significant difference in recorded activity between methods for other WNS-impacted species, presumably because these species have been so reduced in number that their “apparency” on the landscape is lower. Finally, a cost analysis of standard passive and active sampling protocols revealed that passive sampling is substantially more cost-effective than active sampling per hour of data collection. We recommend passive sampling over active sampling methodologies as they are defined in our study for detection probability and/or occupancy studies focused on declining bat species in areas that have experienced severe WNS-associated impacts.

","language":"English","publisher":"Scientific Journals","doi":"10.3996/082013-JFWM-057","usgsCitation":"Coleman, L.S., Ford, W.M., Dobony, C.A., and Britzke, E.R., 2014, A comparison of passive and active acoustic sampling for a bat community impacted by White-nose syndrome: Journal of Fish and Wildlife Management, v. 5, no. 2, p. 217-226, https://doi.org/10.3996/082013-JFWM-057.","productDescription":"10 p.","startPage":"217","endPage":"226","ipdsId":"IP-051164","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":472614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/082013-jfwm-057","text":"Publisher Index Page"},{"id":340656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-01","publicationStatus":"PW","scienceBaseUri":"5908492de4b0fc4e448ffd6a","contributors":{"authors":[{"text":"Coleman, Laci S.","contributorId":171672,"corporation":false,"usgs":false,"family":"Coleman","given":"Laci","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dobony, Christopher A.","contributorId":171455,"corporation":false,"usgs":false,"family":"Dobony","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Britzke, Eric R.","contributorId":8327,"corporation":false,"usgs":true,"family":"Britzke","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":693702,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189185,"text":"70189185 - 2014 - The effects of changing land cover on streamflow simulation in Puerto Rico","interactions":[],"lastModifiedDate":"2017-07-06T14:43:52","indexId":"70189185","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"The effects of changing land cover on streamflow simulation in Puerto Rico","docAbstract":"

This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.

","language":"English","publisher":"Wiley","doi":"10.1111/jawr.12227","usgsCitation":"Van Beusekom, A.E., Hay, L.E., Viger, R.J., Gould, W.A., Collazo, J., and Henareh Khalyani, A., 2014, The effects of changing land cover on streamflow simulation in Puerto Rico: Journal of the American Water Resources Association, v. 50, no. 6, p. 1575-1593, https://doi.org/10.1111/jawr.12227.","productDescription":"19 p.","startPage":"1575","endPage":"1593","ipdsId":"IP-054092","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Puerto Rico","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-65.3277,18.295843],[-65.337451,18.308308],[-65.327318,18.323666],[-65.342068,18.34529],[-65.335701,18.349535],[-65.329334,18.341955],[-65.321754,18.338316],[-65.309833,18.337973],[-65.304409,18.332054],[-65.298328,18.330529],[-65.255933,18.342117],[-65.221568,18.320959],[-65.222853,18.310464],[-65.249857,18.296691],[-65.260282,18.290823],[-65.283269,18.280214],[-65.3277,18.295843]]],[[[-67.89174,18.11397],[-67.887099,18.112574],[-67.87643,18.114157],[-67.869804,18.118851],[-67.861548,18.122144],[-67.848245,18.10832],[-67.843202,18.094858],[-67.843615,18.085099],[-67.845293,18.081938],[-67.853098,18.078195],[-67.865598,18.06544],[-67.871462,18.0578],[-67.895921,18.052342],[-67.904431,18.05913],[-67.918778,18.063116],[-67.927841,18.068572],[-67.940799,18.079716],[-67.934479,18.111306],[-67.932185,18.113221],[-67.91088,18.119668],[-67.89174,18.11397]]],[[[-65.308717,18.145172],[-65.302295,18.141089],[-65.294896,18.14283],[-65.287962,18.148097],[-65.275165,18.13443],[-65.276214,18.131936],[-65.283248,18.132999],[-65.296036,18.12799],[-65.322794,18.126589],[-65.327184,18.124106],[-65.338506,18.112439],[-65.342037,18.11138],[-65.350493,18.111914],[-65.364733,18.120377],[-65.397837,18.110873],[-65.399791,18.108832],[-65.411767,18.106211],[-65.423765,18.097764],[-65.426311,18.093749],[-65.45138,18.086096],[-65.45681,18.087778],[-65.465849,18.087715],[-65.468768,18.092643],[-65.47979,18.096352],[-65.507265,18.091646],[-65.524209,18.081977],[-65.542087,18.081177],[-65.558646,18.08566],[-65.569305,18.091616],[-65.570628,18.097325],[-65.57686,18.103224],[-65.575579,18.115669],[-65.546199,18.119329],[-65.511712,18.13284],[-65.489829,18.135912],[-65.46791,18.143767],[-65.437058,18.15766],[-65.399517,18.161935],[-65.371373,18.157517],[-65.334289,18.147761],[-65.313476,18.144296],[-65.308717,18.145172]]],[[[-66.438813,18.485713],[-66.420921,18.488639],[-66.410344,18.489886],[-66.394287,18.489748],[-66.377286,18.488044],[-66.37282,18.487726],[-66.349647,18.486335],[-66.337728,18.48562],[-66.315477,18.474724],[-66.31503,18.47468],[-66.291225,18.472347],[-66.283675,18.472203],[-66.276599,18.478129],[-66.269799,18.480281],[-66.258015,18.476906],[-66.251547,18.472464],[-66.241797,18.46874],[-66.220148,18.466],[-66.199032,18.466163],[-66.192664,18.466212],[-66.183886,18.460506],[-66.179218,18.455305],[-66.172315,18.451462],[-66.159796,18.451706],[-66.153037,18.454457],[-66.14395,18.459761],[-66.139572,18.462317],[-66.139451,18.462387],[-66.139443,18.462315],[-66.138532,18.453305],[-66.133085,18.445881],[-66.127938,18.444632],[-66.125198,18.451209],[-66.124284,18.456324],[-66.123188,18.45943],[-66.123343,18.460363],[-66.125015,18.470435],[-66.118338,18.469581],[-66.092098,18.466535],[-66.083254,18.462022],[-66.073987,18.4581],[-66.043272,18.453655],[-66.03944,18.454441],[-66.036559,18.450216],[-66.036491,18.450117],[-66.023221,18.443875],[-66.006523,18.444347],[-65.99718,18.449895],[-65.992935,18.457489],[-65.992793,18.458102],[-65.992349,18.460024],[-65.99079,18.460419],[-65.958492,18.451354],[-65.92567,18.444881],[-65.916843,18.444619],[-65.907756,18.446893],[-65.904988,18.450926],[-65.878683,18.438322],[-65.838825,18.431865],[-65.831476,18.426849],[-65.828457,18.423543],[-65.816691,18.410663],[-65.794556,18.402845],[-65.787666,18.402544],[-65.774937,18.413951],[-65.77053,18.41294],[-65.769749,18.409473],[-65.771695,18.406277],[-65.750455,18.385208],[-65.750179,18.38505],[-65.742154,18.380459],[-65.733567,18.382211],[-65.699069,18.368156],[-65.669636,18.362102],[-65.668845,18.361939],[-65.634431,18.369835],[-65.627246,18.376436],[-65.626527,18.381728],[-65.624975,18.386553],[-65.622761,18.387771],[-65.618229,18.386496],[-65.614891,18.382473],[-65.619068,18.367755],[-65.628198,18.353711],[-65.63419,18.338965],[-65.628047,18.328252],[-65.626456,18.298982],[-65.634389,18.292349],[-65.635826,18.288271],[-65.634893,18.283923],[-65.630833,18.264989],[-65.623111,18.248012],[-65.597618,18.234289],[-65.589947,18.228225],[-65.593795,18.224059],[-65.615981,18.227389],[-65.626731,18.235484],[-65.638181,18.229121],[-65.637565,18.224444],[-65.628414,18.205149],[-65.635281,18.199975],[-65.639688,18.205656],[-65.662185,18.207018],[-65.664127,18.207136],[-65.690749,18.19499],[-65.694515,18.187011],[-65.691021,18.178998],[-65.695856,18.179324],[-65.710895,18.186963],[-65.712533,18.189146],[-65.717999,18.190176],[-65.728471,18.185588],[-65.734664,18.180368],[-65.738834,18.174066],[-65.739125,18.173453],[-65.743632,18.163957],[-65.758728,18.156601],[-65.766919,18.148424],[-65.777584,18.129239],[-65.796711,18.083746],[-65.796289,18.079835],[-65.794686,18.078607],[-65.795028,18.073561],[-65.796711,18.069842],[-65.801831,18.058527],[-65.809174,18.056818],[-65.817107,18.063378],[-65.825848,18.057482],[-65.83109,18.050664],[-65.834274,18.038988],[-65.832429,18.014916],[-65.839591,18.015077],[-65.850913,18.011954],[-65.870335,18.006597],[-65.875122,18.002826],[-65.884937,17.988521],[-65.896102,17.99026],[-65.905319,17.983974],[-65.910537,17.981855],[-65.924738,17.976087],[-65.976611,17.967669],[-65.98455,17.969411],[-65.985358,17.971854],[-65.995185,17.978989],[-66.007731,17.980541],[-66.017308,17.979583],[-66.019539,17.978354],[-66.024,17.975896],[-66.046585,17.954853],[-66.049033,17.954561],[-66.058217,17.959238],[-66.068678,17.966335],[-66.069979,17.966357],[-66.08141,17.966552],[-66.116194,17.949141],[-66.127009,17.946953],[-66.140661,17.94102],[-66.147912,17.933963],[-66.155387,17.929406],[-66.159742,17.928613],[-66.161232,17.931747],[-66.175626,17.933565],[-66.186914,17.935363],[-66.189726,17.933936],[-66.200174,17.929515],[-66.206961,17.932268],[-66.213374,17.944614],[-66.202655,17.944753],[-66.185554,17.940997],[-66.179548,17.943727],[-66.174839,17.948214],[-66.176814,17.950438],[-66.206207,17.96305],[-66.206807,17.963307],[-66.215355,17.959376],[-66.218081,17.95729],[-66.231519,17.943912],[-66.229181,17.934651],[-66.232013,17.931154],[-66.252737,17.934574],[-66.260684,17.936083],[-66.270905,17.947098],[-66.275651,17.94826],[-66.290782,17.946491],[-66.297679,17.959148],[-66.31695,17.976683],[-66.323659,17.978536],[-66.338152,17.976492],[-66.33839,17.976458],[-66.362511,17.968231],[-66.365098,17.964832],[-66.368777,17.957717],[-66.371591,17.951469],[-66.385059,17.939004],[-66.391227,17.945819],[-66.398945,17.950925],[-66.412131,17.957286],[-66.445481,17.979379],[-66.450368,17.983226],[-66.454888,17.986784],[-66.461342,17.990273],[-66.491396,17.990262],[-66.510143,17.985618],[-66.540537,17.975476],[-66.583233,17.961229],[-66.589658,17.969386],[-66.594392,17.970682],[-66.605035,17.969015],[-66.623788,17.98105],[-66.631944,17.982746],[-66.645651,17.98026],[-66.657797,17.974605],[-66.664391,17.968259],[-66.672819,17.966451],[-66.699115,17.977568],[-66.709856,17.982109],[-66.713394,17.987763],[-66.716957,17.990344],[-66.731118,17.991658],[-66.746248,17.990349],[-66.750427,17.995443],[-66.753964,17.99959],[-66.755341,18.001203],[-66.764491,18.006317],[-66.770307,18.005955],[-66.799656,17.99245],[-66.806866,17.983786],[-66.807924,17.979606],[-66.806903,17.976046],[-66.805683,17.975052],[-66.795106,17.977438],[-66.789302,17.980793],[-66.784953,17.978326],[-66.787245,17.972914],[-66.80827,17.965635],[-66.8224,17.954499],[-66.838584,17.949931],[-66.852288,17.955004],[-66.856474,17.956553],[-66.859471,17.954316],[-66.862545,17.952022],[-66.871697,17.952707],[-66.88344,17.952526],[-66.899639,17.948298],[-66.904585,17.950527],[-66.906532,17.955356],[-66.906276,17.963368],[-66.924529,17.972808],[-66.928651,17.970204],[-66.930414,17.963127],[-66.916127,17.959102],[-66.909483,17.952559],[-66.909359,17.94988],[-66.912522,17.947446],[-66.930313,17.943389],[-66.932636,17.939998],[-66.931581,17.9369],[-66.919298,17.932062],[-66.923826,17.926923],[-66.927261,17.926875],[-66.959998,17.940216],[-66.980516,17.951648],[-66.98105,17.952505],[-66.982669,17.9551],[-66.982206,17.961192],[-66.987287,17.970663],[-66.996738,17.972899],[-67.003972,17.970799],[-67.014744,17.968468],[-67.024522,17.970722],[-67.062478,17.973819],[-67.076534,17.967759],[-67.089827,17.951418],[-67.101468,17.946621],[-67.109985,17.945806],[-67.109986,17.945806],[-67.128251,17.948153],[-67.133733,17.951919],[-67.167031,17.963073],[-67.178566,17.964792],[-67.183508,17.962706],[-67.188717,17.950989],[-67.187474,17.946252],[-67.183694,17.937982],[-67.183457,17.931135],[-67.194785,17.932826],[-67.196924,17.935651],[-67.197273,17.937461],[-67.197517,17.941514],[-67.197668,17.943549],[-67.198988,17.94782],[-67.200973,17.949896],[-67.210034,17.953595],[-67.212101,17.956027],[-67.21433,17.962436],[-67.215271,17.983464],[-67.211973,17.992993],[-67.207694,17.998019],[-67.177893,18.008882],[-67.174299,18.011149],[-67.172397,18.014906],[-67.172138,18.021422],[-67.173761,18.024548],[-67.193269,18.03185],[-67.209887,18.035439],[-67.196694,18.066491],[-67.190656,18.064269],[-67.184589,18.06775],[-67.183938,18.069914],[-67.186465,18.074195],[-67.192999,18.076877],[-67.198212,18.076828],[-67.199314,18.091135],[-67.19529,18.096149],[-67.183921,18.103683],[-67.182182,18.108507],[-67.176554,18.151046],[-67.178618,18.159318],[-67.180822,18.168055],[-67.180701,18.168182],[-67.155185,18.195001],[-67.152665,18.203493],[-67.158001,18.216719],[-67.173,18.230666],[-67.175429,18.248008],[-67.187843,18.266671],[-67.187873,18.266874],[-67.189971,18.281015],[-67.196056,18.290443],[-67.209963,18.294974],[-67.225403,18.296648],[-67.226081,18.296722],[-67.235137,18.299935],[-67.267484,18.353149],[-67.27135,18.362329],[-67.268259,18.366989],[-67.260671,18.370197],[-67.23909,18.375318],[-67.226744,18.378247],[-67.216998,18.382078],[-67.202167,18.389908],[-67.160144,18.415587],[-67.159608,18.415915],[-67.156599,18.418983],[-67.155245,18.424401],[-67.156619,18.439562],[-67.161746,18.453462],[-67.169011,18.466352],[-67.169016,18.478488],[-67.164144,18.487396],[-67.14283,18.505485],[-67.138249,18.507776],[-67.125655,18.511706],[-67.103468,18.514523],[-67.093752,18.515757],[-67.07929,18.513256],[-67.020276,18.510603],[-66.988958,18.497724],[-66.95954,18.489878],[-66.957733,18.489129],[-66.957517,18.489171],[-66.944636,18.491693],[-66.906872,18.483556],[-66.90143,18.484552],[-66.867386,18.490785],[-66.849673,18.490745],[-66.83694,18.487659],[-66.836635,18.487701],[-66.79932,18.492775],[-66.780311,18.491411],[-66.764893,18.484097],[-66.749301,18.476701],[-66.742067,18.474681],[-66.733986,18.473457],[-66.710743,18.472611],[-66.683719,18.481367],[-66.679876,18.484944],[-66.664364,18.487809],[-66.645839,18.488777],[-66.624618,18.494199],[-66.586778,18.484948],[-66.584074,18.484287],[-66.565241,18.485523],[-66.562916,18.48845],[-66.563485,18.490512],[-66.558503,18.489987],[-66.53484,18.481253],[-66.533487,18.481663],[-66.529476,18.482877],[-66.511609,18.476848],[-66.470292,18.46907],[-66.456486,18.46892],[-66.449184,18.470991],[-66.441852,18.479751],[-66.439961,18.485525],[-66.438813,18.485713]]]]},\"properties\":{\"name\":\"Puerto Rico\",\"nation\":\"USA \"}}]}","volume":"50","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-22","publicationStatus":"PW","scienceBaseUri":"595f4c41e4b0d1f9f057e35c","contributors":{"authors":[{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gould, William A.","contributorId":103535,"corporation":false,"usgs":true,"family":"Gould","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collazo, Jaime jaime_collazo@usgs.gov","contributorId":2613,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":703403,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henareh Khalyani, Azad","contributorId":194189,"corporation":false,"usgs":false,"family":"Henareh Khalyani","given":"Azad","email":"","affiliations":[],"preferred":false,"id":703404,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187408,"text":"70187408 - 2014 - Composition of dust deposited to snow cover in the Wasatch Range (Utah, USA): Controls on radiative properties of snow cover and comparison to some dust-source sediments","interactions":[],"lastModifiedDate":"2017-05-02T10:28:03","indexId":"70187408","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"Composition of dust deposited to snow cover in the Wasatch Range (Utah, USA): Controls on radiative properties of snow cover and comparison to some dust-source sediments","docAbstract":"

Dust layers deposited to snow cover of the Wasatch Range (northern Utah) in 2009 and 2010 provide rare samples to determine the relations between their compositions and radiative properties. These studies are required to comprehend and model how such dust-on-snow (DOS) layers affect rates of snow melt through changes in the albedo of snow surfaces. We evaluated several constituents as potential contributors to the absorption of solar radiation indicated by values of absolute reflectance determined from bi-conical reflectance spectroscopy. Ferric oxide minerals and carbonaceous matter appear to be the primary influences on lowering snow-cover albedo. Techniques of reflectance and Mössbauer spectroscopy as well as rock magnetism provide information about the types, amounts, and grain sizes of ferric oxide minerals. Relatively high amounts of ferric oxide, indicated by hard isothermal remanent magnetization (HIRM), are associated with relatively low average reflectance (<0.25) across the visible wavelengths of the electromagnetic spectrum. Mössbauer spectroscopy indicates roughly equal amounts of hematite and goethite, representing about 35% of the total Fe-bearing phases. Nevertheless, goethite (α-FeOOH) is the dominant ferric oxide found by reflectance spectroscopy and thus appears to be the main iron oxide control on absorption of solar radiation. At least some goethite occurs as nano-phase grain coatings less than about 50 nm thick. Relatively high amounts of organic carbon, indicating as much as about 10% organic matter, are also associated with lower reflectance values. The organic matter, although not fully characterized by type, correlates strongly with metals (e.g., Cu, Pb, As, Cd, Mo, Zn) derived from distal urban and industrial settings, probably including mining and smelting sites. This relation suggests anthropogenic sources for at least some of the carbonaceous matter, such as emissions from transportation and industrial activities. The composition of the DOS samples can be compared with sediments in a likely dust-source setting at the Milford Flat Fire (MFF) area about 225 km southwest of Salt Lake City. The MFF area represents geologically and physiographically similar and widespread dust sources west-southwest of the Wasatch Range and heavily populated Wasatch Front. The DOS layers and MFF sediments are similar in some textural, chemical, and magnetic properties, as well as in the common presence of goethite, hematite, magnetite-bearing basalt fragments, quartz, plagioclase, illite, and kaolinite. Textural and some chemical differences among these deposits can be explained by atmospheric sorting as well as by inputs from other settings, such as salt-crusted playas and contaminant sources.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2013.08.001","usgsCitation":"Reynolds, R.L., Goldstein, H.L., Moskowitz, B.M., Bryant, A.C., Skiles, S.M., Kokaly, R., Flagg, C.B., Yauk, K., Berquo, T.S., Breit, G.N., Ketterer, M., Fernandez, D., Miller, M.E., and Painter, T.H., 2014, Composition of dust deposited to snow cover in the Wasatch Range (Utah, USA): Controls on radiative properties of snow cover and comparison to some dust-source sediments: Aeolian Research, v. 15, p. 73-90, https://doi.org/10.1016/j.aeolia.2013.08.001.","productDescription":"18 p.","startPage":"73","endPage":"90","ipdsId":"IP-039361","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":340723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Wasatch Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.20886230468749,\n 40.233411907115055\n ],\n [\n -111.59912109375,\n 40.233411907115055\n ],\n [\n -111.59912109375,\n 40.93011520598305\n ],\n [\n -112.20886230468749,\n 40.93011520598305\n ],\n [\n -112.20886230468749,\n 40.233411907115055\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59099ab0e4b0fc4e44915804","contributors":{"authors":[{"text":"Reynolds, Richard L. 0000-0002-4572-2942 rreynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-4572-2942","contributorId":139068,"corporation":false,"usgs":true,"family":"Reynolds","given":"Richard","email":"rreynolds@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldstein, Harland L. 0000-0002-6092-8818 hgoldstein@usgs.gov","orcid":"https://orcid.org/0000-0002-6092-8818","contributorId":807,"corporation":false,"usgs":true,"family":"Goldstein","given":"Harland","email":"hgoldstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moskowitz, Bruce M.","contributorId":191599,"corporation":false,"usgs":false,"family":"Moskowitz","given":"Bruce","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":693894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bryant, Ann C.","contributorId":191698,"corporation":false,"usgs":false,"family":"Bryant","given":"Ann","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":693895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skiles, S. McKenzie","contributorId":147878,"corporation":false,"usgs":false,"family":"Skiles","given":"S.","email":"","middleInitial":"McKenzie","affiliations":[{"id":16952,"text":"University of California- Los Angeles, Joint Intitute for Regional Earth System Science and Engineering","active":true,"usgs":false}],"preferred":false,"id":693896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":1785,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","email":"raymond@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":693897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flagg, Cody B. cflagg@usgs.gov","contributorId":4573,"corporation":false,"usgs":true,"family":"Flagg","given":"Cody","email":"cflagg@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":693898,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yauk, Kimberly","contributorId":75415,"corporation":false,"usgs":true,"family":"Yauk","given":"Kimberly","email":"","affiliations":[],"preferred":false,"id":693899,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Berquo, Thelma S.","contributorId":40106,"corporation":false,"usgs":true,"family":"Berquo","given":"Thelma","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693900,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":693901,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ketterer, Michael","contributorId":191699,"corporation":false,"usgs":false,"family":"Ketterer","given":"Michael","affiliations":[],"preferred":false,"id":693902,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fernandez, Daniel","contributorId":80588,"corporation":false,"usgs":true,"family":"Fernandez","given":"Daniel","affiliations":[],"preferred":false,"id":693903,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":693904,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Painter, Thomas H.","contributorId":12378,"corporation":false,"usgs":true,"family":"Painter","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":693905,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70174166,"text":"70174166 - 2014 - Population dynamics modeling of introduced smallmouth bass in the upper Colorado River basin","interactions":[],"lastModifiedDate":"2016-07-18T15:14:13","indexId":"70174166","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":295,"text":"Technical Report","active":false,"publicationSubtype":{"id":4}},"title":"Population dynamics modeling of introduced smallmouth bass in the upper Colorado River basin","docAbstract":"
The purpose of these analyses was to identify an effective control strategy to further reduce smallmouth bass in the upper Colorado River basin from the current level. Our simulation results showed that “the surge”, an early to mid-summer increase in electrofishing effort targeting nest-guarding male smallmouth bass, should be made a core component of any future smallmouth bass management strategy in the upper basin. Immigration from off channel reservoirs is supporting smallmouth bass popualtions in the Yampa River and our modeling analyses suggest that smallmouth bass  in Little Yampa Canyon might go extinct in a few years under the present level of exploitation.
","language":"English","doi":"10.13140/RG.2.1.3965.0167","usgsCitation":"Breton, A., Winkelman, D.L., Bestgen, K.R., and Hawkins, J.A., 2014, Population dynamics modeling of introduced smallmouth bass in the upper Colorado River basin: Technical Report, 150 p., https://doi.org/10.13140/RG.2.1.3965.0167.","productDescription":"150 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060589","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":325388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.291748046875,\n 41.86137915587359\n ],\n [\n -112.2802734375,\n 36.99377838872517\n ],\n [\n -106.85302734374999,\n 37.10776507118514\n ],\n [\n -105.809326171875,\n 39.487084981687495\n ],\n [\n -108.13842773437499,\n 40.40513069752789\n ],\n [\n -108.56689453125,\n 41.244772343082104\n ],\n [\n -110.291748046875,\n 41.86137915587359\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Recovery Program Project #161 Bureau of Reclamation Agreement # 9 -FG-81-0143 R09AC40885 Larval Fish Laboratory Contribution #186November 2015","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"578dfdb6e4b0f1bea0e0f8dc","contributors":{"authors":[{"text":"Breton, André R.","contributorId":47682,"corporation":false,"usgs":false,"family":"Breton","given":"André R.","affiliations":[],"preferred":false,"id":642763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":641015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bestgen, Kevin R. 0000-0001-8691-2227","orcid":"https://orcid.org/0000-0001-8691-2227","contributorId":171573,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":642764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkins, John A.","contributorId":50076,"corporation":false,"usgs":true,"family":"Hawkins","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":642765,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70138832,"text":"70138832 - 2014 - Estimating true instead of apparent survival using spatial Cormack-Jolly-Seber models","interactions":[],"lastModifiedDate":"2015-01-23T09:51:16","indexId":"70138832","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating true instead of apparent survival using spatial Cormack-Jolly-Seber models","docAbstract":"
    \n
  1. Survival is often estimated from capture–recapture data using Cormack–Jolly–Seber (CJS) models, where mortality and emigration cannot be distinguished, and the estimated apparent survival probability is the product of the probabilities of true survival and of study area fidelity. Consequently, apparent survival is lower than true survival unless study area fidelity equals one. Underestimation of true survival from capture–recapture data is a main limitation of the method.
    2. \n
  2. We develop a spatial version of the CJS model that allows estimation of true survival. Besides the information about whether a specific individual was encountered at a given occasion, it is often recorded where the encounter occurred. Thus, information is available about the fraction of dispersal that occurs within the study area, and we use it to model dispersal and estimate true survival. Our model is formulated hierarchically and consists of survival, dispersal and observation submodels, assuming that encounters are possible anywhere within a study area.
    3. \n
  3. In a simulation study, our new spatial CJS model produced accurate estimates of true survival and dispersal behaviour for various sizes and shapes of the study area, even if emigration is substantial. However, when the information about dispersal is scarce due to low survival, low recapture probabilities and high emigration, the estimators are positively biased. Moreover, survival estimates are sensitive to the assumed dispersal kernel.
    4. \n
  4. We applied the spatial CJS model to a data set of adult red-backed shrikes (Lanius collurio). Apparent survival of males (c. 0·5) estimated with the CJS model was larger than in females (c. 0·4), but the application of the spatial CJS model revealed that both sexes had similar survival probabilities (c. 0·6). The mean breeding dispersal distance in females was c. 700 m, while males dispersed only c. 250 m between years.
    5. \n
  5. Spatial CJS models enable study of dispersal and survival independent of study design constraints such as imperfect detection and size of the study area provided that some of the dispersing individuals remain in the study area. We discuss possible extensions of our model: alternative dispersal models and the inclusion of covariates and of a habitat suitability map.
    6. \n
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.12134","usgsCitation":"Schaub, M., and Royle, J., 2014, Estimating true instead of apparent survival using spatial Cormack-Jolly-Seber models: Methods in Ecology and Evolution, v. 5, no. 12, p. 1316-1326, https://doi.org/10.1111/2041-210X.12134.","productDescription":"11 p.","startPage":"1316","endPage":"1326","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052069","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":297476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"12","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-29","publicationStatus":"PW","scienceBaseUri":"54dd2a74e4b08de9379b306d","contributors":{"authors":[{"text":"Schaub, Michael","contributorId":138861,"corporation":false,"usgs":false,"family":"Schaub","given":"Michael","email":"","affiliations":[{"id":12551,"text":"Swiss Ornithological Institute, Sempach, Switzerland","active":true,"usgs":false}],"preferred":false,"id":539030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew aroyle@usgs.gov","contributorId":138860,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":539029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70128627,"text":"70128627 - 2014 - Potential reduction in terrestrial salamander ranges associated with Marcellus shale development","interactions":[],"lastModifiedDate":"2016-07-08T14:45:20","indexId":"70128627","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Potential reduction in terrestrial salamander ranges associated with Marcellus shale development","docAbstract":"

Natural gas production from the Marcellus shale is rapidly increasing in the northeastern United States. Most of the endemic terrestrial salamander species in the region are classified as ‘globally secure’ by the IUCN, primarily because much of their ranges include state- and federally protected lands, which have been presumed to be free from habitat loss. However, the proposed and ongoing development of the Marcellus gas resources may result in significant range restrictions for these and other terrestrial forest salamanders. To begin to address the gaps in our knowledge of the direct impacts of shale gas development, we developed occurrence models for five species of terrestrial plethodontid salamanders found largely within the Marcellus shale play. We predicted future Marcellus shale development under several scenarios. Under scenarios of 10,000, 20,000, and 50,000 new gas wells, we predict 4%, 8%, and 20% forest loss, respectively, within the play. Predictions of habitat loss vary among species, but in general, Plethodon electromorphus and Plethodonwehrlei are predicted to lose the greatest proportion of forested habitat within their ranges if future Marcellus development is based on characteristics of the shale play. If development is based on current well locations,Plethodonrichmondi is predicted to lose the greatest proportion of habitat. Models showed high uncertainty in species’ ranges and emphasize the need for distribution data collected by widespread and repeated, randomized surveys.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2014.10.008","usgsCitation":"Brand, A.B., Wiewel, A., and Grant, E., 2014, Potential reduction in terrestrial salamander ranges associated with Marcellus shale development: Biological Conservation, v. 180, p. 233-240, https://doi.org/10.1016/j.biocon.2014.10.008.","productDescription":"8 p.","startPage":"233","endPage":"240","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060365","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":324946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"180","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780cebde4b08116168223a0","contributors":{"authors":[{"text":"Brand, Adrianne B. 0000-0003-2664-0041 abrand@usgs.gov","orcid":"https://orcid.org/0000-0003-2664-0041","contributorId":3352,"corporation":false,"usgs":true,"family":"Brand","given":"Adrianne","email":"abrand@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":519740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiewel, Amber N. M. awiewel@usgs.gov","contributorId":146573,"corporation":false,"usgs":true,"family":"Wiewel","given":"Amber N. M.","email":"awiewel@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":641978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Evan H. Campbell ehgrant@usgs.gov","contributorId":3696,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","email":"ehgrant@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":519741,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70138541,"text":"70138541 - 2014 - Estimating the volcanic emission rate and atmospheric lifetime of SO2 from space: a case study for Kīlauea volcano, Hawai'i","interactions":[],"lastModifiedDate":"2019-02-25T13:46:09","indexId":"70138541","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":922,"text":"Atmospheric Chemistry and Physics","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the volcanic emission rate and atmospheric lifetime of SO2 from space: a case study for Kīlauea volcano, Hawai'i","docAbstract":"

We present an analysis of SO2 column densities derived from GOME-2 satellite measurements for the Kīlauea volcano (Hawai`i) for 2007–2012. During a period of enhanced degassing activity in March–November 2008, monthly mean SO2 emission rates and effective SO2 lifetimes are determined simultaneously from the observed downwind plume evolution and meteorological wind fields, without further model input. Kīlauea is particularly suited for quantitative investigations from satellite observations owing to the absence of interfering sources, the clearly defined downwind plumes caused by steady trade winds, and generally low cloud fractions. For March–November 2008, the effective SO2 lifetime is 1–2 days, and Kīlauea SO2 emission rates are 9–21 kt day−1, which is about 3 times higher than initially reported from ground-based monitoring systems.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/acp-14-8309-2014","usgsCitation":"Beirle, S., Hormann, C., Penning de Vries, M., Dorner, S., Kern, C., and Wagner, T., 2014, Estimating the volcanic emission rate and atmospheric lifetime of SO2 from space: a case study for Kīlauea volcano, Hawai'i: Atmospheric Chemistry and Physics, v. 14, p. 8309-8322, https://doi.org/10.5194/acp-14-8309-2014.","productDescription":"14 p.","startPage":"8309","endPage":"8322","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049545","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472612,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/acp-14-8309-2014","text":"Publisher Index Page"},{"id":297384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3111457824707,\n 19.37933243547929\n ],\n [\n -155.3111457824707,\n 19.45056843698827\n ],\n [\n -155.23029327392578,\n 19.45056843698827\n ],\n [\n -155.23029327392578,\n 19.37933243547929\n ],\n [\n -155.3111457824707,\n 19.37933243547929\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-19","publicationStatus":"PW","scienceBaseUri":"54dd2a73e4b08de9379b306b","contributors":{"authors":[{"text":"Beirle, Steffen","contributorId":138808,"corporation":false,"usgs":false,"family":"Beirle","given":"Steffen","email":"","affiliations":[{"id":12534,"text":"Max-Planck-Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":538803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hormann, Christoph","contributorId":138809,"corporation":false,"usgs":false,"family":"Hormann","given":"Christoph","email":"","affiliations":[{"id":12535,"text":"Max-Planck-Institute for Chemistry, Mainz, and Univ. Heidelberg, Germany","active":true,"usgs":false}],"preferred":false,"id":538804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Penning de Vries, Malouse","contributorId":138810,"corporation":false,"usgs":false,"family":"Penning de Vries","given":"Malouse","email":"","affiliations":[{"id":12534,"text":"Max-Planck-Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":538805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dorner, Stefan","contributorId":138811,"corporation":false,"usgs":false,"family":"Dorner","given":"Stefan","email":"","affiliations":[{"id":12534,"text":"Max-Planck-Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":538806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":538802,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Thomas","contributorId":138812,"corporation":false,"usgs":false,"family":"Wagner","given":"Thomas","email":"","affiliations":[{"id":12534,"text":"Max-Planck-Institute for Chemistry, Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":538807,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70139547,"text":"70139547 - 2014 - Anuran site occupancy and species richness as tools for evaluating restoration of a hydrologically-modified landscape","interactions":[],"lastModifiedDate":"2015-01-28T14:28:41","indexId":"70139547","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3751,"text":"Wetlands Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Anuran site occupancy and species richness as tools for evaluating restoration of a hydrologically-modified landscape","docAbstract":"

A fundamental goal of wetland restoration is to reinstate pre-disturbance hydrological conditions to degraded landscapes, facilitating recolonization by native species and the production of resilient, functional ecosystems. To evaluate restoration success, baseline conditions need to be determined and a reference target needs to be established that will serve as an ecological blueprint in the restoration process. During the summer wet seasons of 2010 and 2011, we used automated recording units to monitor a community of calling anuran amphibians in the Picayune Strand State Forest of Southwest Florida, USA. This area is undergoing hydrological restoration as part of the Comprehensive Everglades Restoration Plan. We compared occurrence of anurans at sites in the restoration area, to nearby locations in relatively undisturbed habitat (reference sites). We assessed the utility of the latter as restoration targets, using a hierarchical model of community species occupancy to estimate the probability of occurrence of anurans in restoration and reference locations. We detected 14 species, 13 of which were significantly more likely to occur in reference areas. All 14 species were estimated by our model to occur at these sites but, across both years, only 8–13 species were estimated to occur at restoration sites. The composition and structure of these habitats within and adjacent to the Picayune Strand State Forest indicate that they are suitable targets for habitat restoration, as measured by amphibian occurrence and species richness. These areas are important sources for recolonization of anuran amphibians as the hydrologically degraded Picayune Strand undergoes restoration to mitigate the effects of overdrainage and habitat loss.

","language":"English","publisher":"Springer Netherlands","doi":"10.1007/s11273-014-9356-4","usgsCitation":"Walls, S.C., Waddle, J.H., Barichivich, W.J., Bartoszek, I.A., Brown, M., Hefner, J.M., and Schuman, M., 2014, Anuran site occupancy and species richness as tools for evaluating restoration of a hydrologically-modified landscape: Wetlands Ecology and Management, v. 22, no. 6, p. 625-639, https://doi.org/10.1007/s11273-014-9356-4.","productDescription":"15 p.","startPage":"625","endPage":"639","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045360","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":297598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Picayune Strand State Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.617431640625,\n 25.942609332852275\n ],\n [\n -81.617431640625,\n 26.19795726272403\n ],\n [\n -81.32972717285156,\n 26.19795726272403\n ],\n [\n -81.32972717285156,\n 25.942609332852275\n ],\n [\n -81.617431640625,\n 25.942609332852275\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-14","publicationStatus":"PW","scienceBaseUri":"54dd2a55e4b08de9379b2fe9","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133 waddleh@usgs.gov","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":138953,"corporation":false,"usgs":true,"family":"Waddle","given":"J.","email":"waddleh@usgs.gov","middleInitial":"Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":539435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barichivich, William J. 0000-0003-1103-6861 wbarichivich@usgs.gov","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":3697,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","email":"wbarichivich@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bartoszek, Ian A.","contributorId":138954,"corporation":false,"usgs":false,"family":"Bartoszek","given":"Ian","email":"","middleInitial":"A.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":539437,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brown, Mary E. 0000-0002-5580-137X","orcid":"https://orcid.org/0000-0002-5580-137X","contributorId":38112,"corporation":false,"usgs":true,"family":"Brown","given":"Mary E.","affiliations":[],"preferred":false,"id":539438,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hefner, J. M.","contributorId":39427,"corporation":false,"usgs":true,"family":"Hefner","given":"J.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":539439,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schuman, Melinda J.","contributorId":138955,"corporation":false,"usgs":false,"family":"Schuman","given":"Melinda J.","affiliations":[{"id":12592,"text":"Conservancy of Southwest Florida, Naples, FL","active":true,"usgs":false}],"preferred":false,"id":539440,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70117702,"text":"70117702 - 2014 - Predicting occupancy for pygmy rabbits in Wyoming: an independent evaluation of two species distribution models","interactions":[],"lastModifiedDate":"2018-08-10T16:16:49","indexId":"70117702","displayToPublicDate":"2014-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Predicting occupancy for pygmy rabbits in Wyoming: an independent evaluation of two species distribution models","docAbstract":"

Species distribution models are an important component of natural-resource conservation planning efforts. Independent, external evaluation of their accuracy is important before they are used in management contexts. We evaluated the classification accuracy of two species distribution models designed to predict the distribution of pygmy rabbit Brachylagus idahoensis habitat in southwestern Wyoming, USA. The Nature Conservancy model was deductive and based on published information and expert opinion, whereas the Wyoming Natural Diversity Database model was statistically derived using historical observation data. We randomly selected 187 evaluation survey points throughout southwestern Wyoming in areas predicted to be habitat and areas predicted to be nonhabitat for each model. The Nature Conservancy model correctly classified 39 of 77 (50.6%) unoccupied evaluation plots and 65 of 88 (73.9%) occupied plots for an overall classification success of 63.3%. The Wyoming Natural Diversity Database model correctly classified 53 of 95 (55.8%) unoccupied plots and 59 of 88 (67.0%) occupied plots for an overall classification success of 61.2%. Based on 95% asymptotic confidence intervals, classification success of the two models did not differ. The models jointly classified 10.8% of the area as habitat and 47.4% of the area as nonhabitat, but were discordant in classifying the remaining 41.9% of the area. To evaluate how anthropogenic development affected model predictive success, we surveyed 120 additional plots among three density levels of gas-field road networks. Classification success declined sharply for both models as road-density level increased beyond 5 km of roads per km-squared area. Both models were more effective at predicting habitat than nonhabitat in relatively undeveloped areas, and neither was effective at accounting for the effects of gas-energy-development road networks. Resource managers who wish to know the amount of pygmy rabbit habitat present in an area or wanting to direct gas-drilling efforts away from pygmy rabbit habitat may want to consider both models in an ensemble manner, where more confidence is placed in mapped areas (i.e., pixels) for which both models agree than for areas where there is model disagreement.

","language":"English","publisher":"Scientific Journals","doi":"10.3996/022014-JFWM-016","usgsCitation":"Germaine, S., Ignizio, D., Keinath, D., and Copeland, H., 2014, Predicting occupancy for pygmy rabbits in Wyoming: an independent evaluation of two species distribution models: Journal of Fish and Wildlife Management, v. 5, no. 2, p. 298-314, https://doi.org/10.3996/022014-JFWM-016.","productDescription":"17 p.","startPage":"298","endPage":"314","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053665","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":472611,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/022014-jfwm-016","text":"Publisher Index Page"},{"id":297449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 45.120052841530516\n ],\n [\n -103.974609375,\n 45.120052841530516\n ],\n [\n -104.1064453125,\n 41.07935114946899\n ],\n [\n -111.26953125,\n 41.07935114946899\n ],\n [\n -111.0498046875,\n 45.120052841530516\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-08-01","publicationStatus":"PW","scienceBaseUri":"54dd2aa4e4b08de9379b315c","contributors":{"authors":[{"text":"Germaine, Steve 0000-0002-7614-2676 germaines@usgs.gov","orcid":"https://orcid.org/0000-0002-7614-2676","contributorId":4743,"corporation":false,"usgs":true,"family":"Germaine","given":"Steve","email":"germaines@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":519112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ignizio, Drew 0000-0001-8054-5139","orcid":"https://orcid.org/0000-0001-8054-5139","contributorId":94602,"corporation":false,"usgs":true,"family":"Ignizio","given":"Drew","affiliations":[],"preferred":false,"id":519113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keinath, Doug","contributorId":115136,"corporation":false,"usgs":true,"family":"Keinath","given":"Doug","email":"","affiliations":[],"preferred":false,"id":519114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Copeland, Holly","contributorId":120920,"corporation":false,"usgs":true,"family":"Copeland","given":"Holly","email":"","affiliations":[],"preferred":false,"id":519115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}