{"pageNumber":"899","pageRowStart":"22450","pageSize":"25","recordCount":165521,"records":[{"id":70193710,"text":"70193710 - 2017 - Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana","interactions":[],"lastModifiedDate":"2017-11-03T10:56:17","indexId":"70193710","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1198,"text":"Catena","active":true,"publicationSubtype":{"id":10}},"title":"Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana","docAbstract":"

Floodplain lakes are important wetlands on many lowland floodplains of the world but depressional floodplain lakes are rare in the Mississippi River Alluvial Valley. One of the largest is Catahoula Lake, which has existed with seasonally fluctuating water levels for several thousand years but is now in an increasingly hydrologically altered floodplain. Woody vegetation has been encroaching into the lake bed and the rate of this expansion has increased since major human hydrologic modifications, such as channelization, levee construction, and dredging for improvement of navigation, but it remains unknown what role those modifications may have played in altering lake sedimentation processes. Profiles of thirteen 137Cs sediment cores indicate sedimentation has been about 0.26 cm y− 1 over the past 60 years and has been near this rate since land use changes began about 200 years ago (210Pb, and 14C in Tedford, 2009). Carbon sequestration was low (10.4 g m− 2 y− 1), likely because annual drying promotes mineralization and export. Elemental composition (high Zr and Ti and low Ca and K) and low pH of recent (<~60 y) or surface sediments suggest Gulf Coastal Plain origin, but below the recent sediment deposits, 51% of sediment profiles showed influence of Mississippi River alluvium, rich in base cations such as K+, Ca2 +, and Mg2 +. The recent shift to dominance of Coastal Plain sediments on the lake-bed surface suggests hydrologic modification has disconnected the lake from sediment-bearing flows from the Mississippi River. Compared to its condition prior to hydrologic alterations that intensified in the 1930s, Catahoula Lake is about 15 cm shallower and surficial sediments are more acidic. Although these results are not sufficient to attribute ecological changes directly to sedimentological changes, it is likely the altered sedimentary and hydrologic environment is contributing to the increased dominance of woody vegetation.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.catena.2017.04.020","usgsCitation":"Latuso, K.D., Keim, R.F., King, S.L., Weindorf, D.C., and DeLaune, R.D., 2017, Sediment deposition and sources into a Mississippi River floodplain lake; Catahoula Lake, Louisiana: Catena, v. 156, p. 290-297, https://doi.org/10.1016/j.catena.2017.04.020.","productDescription":"8 p.","startPage":"290","endPage":"297","ipdsId":"IP-061448","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Catahoula Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.1697998046875,\n 31.42749129448044\n ],\n [\n -92.04277038574219,\n 31.502458420817206\n ],\n [\n -91.99607849121094,\n 31.552793227677334\n ],\n [\n -91.99745178222656,\n 31.613626970322684\n ],\n [\n -92.06748962402344,\n 31.610703179979982\n ],\n [\n -92.12448120117188,\n 31.577950455417472\n ],\n [\n -92.17666625976562,\n 31.52411741833466\n ],\n [\n -92.22198486328125,\n 31.48313670206181\n ],\n [\n -92.23915100097656,\n 31.454439514853256\n ],\n [\n -92.22335815429688,\n 31.433350262414404\n ],\n [\n -92.19863891601562,\n 31.42749129448044\n ],\n [\n -92.1697998046875,\n 31.42749129448044\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"156","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fd8027e4b0531197b5013b","contributors":{"authors":[{"text":"Latuso, Karen D.","contributorId":113984,"corporation":false,"usgs":false,"family":"Latuso","given":"Karen","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keim, Richard F.","contributorId":117125,"corporation":false,"usgs":false,"family":"Keim","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weindorf, David C.","contributorId":140924,"corporation":false,"usgs":false,"family":"Weindorf","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":27688,"text":"Texas Tech University, Lubbock, TX 79409","active":true,"usgs":false}],"preferred":false,"id":720025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeLaune, Ronald D.","contributorId":61581,"corporation":false,"usgs":false,"family":"DeLaune","given":"Ronald","email":"","middleInitial":"D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":720026,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193728,"text":"70193728 - 2017 - Oiling accelerates loss of salt marshes, southeastern Louisiana","interactions":[],"lastModifiedDate":"2017-11-03T18:59:09","indexId":"70193728","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","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":"Oiling accelerates loss of salt marshes, southeastern Louisiana","docAbstract":"

The 2010 BP Deepwater Horizon (DWH) oil spill damaged thousands of km2 of intertidal marsh along shorelines that had been experiencing elevated rates of erosion for decades. Yet, the contribution of marsh oiling to landscape-scale degradation and subsequent land loss has been difficult to quantify. Here, we applied advanced remote sensing techniques to map changes in marsh land cover and open water before and after oiling. We segmented the marsh shorelines into non-oiled and oiled reaches and calculated the land loss rates for each 10% increase in oil cover (e.g. 0% to >70%), to determine if land loss rates for each reach oiling category were significantly different before and after oiling. Finally, we calculated background land-loss rates to separate natural and oil-related erosion and land loss. Oiling caused significant increases in land losses, particularly along reaches of heavy oiling (>20% oil cover). For reaches with ≥20% oiling, land loss rates increased abruptly during the 2010–2013 period, and the loss rates during this period are significantly different from both the pre-oiling (p < 0.0001) and 2013–2016 post-oiling periods (p < 0.0001). The pre-oiling and 2013–2016 post-oiling periods exhibit no significant differences in land loss rates across oiled and non-oiled reaches (p = 0.557). We conclude that oiling increased land loss by more than 50%, but that land loss rates returned to background levels within 3–6 years after oiling, suggesting that oiling results in a large but temporary increase in land loss rates along the shoreline.

","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0181197","usgsCitation":"Beland, M., Biggs, T.W., Roberts, D.A., Peterson, S.H., Kokaly, R.F., and Piazza, S., 2017, Oiling accelerates loss of salt marshes, southeastern Louisiana: PLoS ONE, v. 12, no. 8, Article e0181197; 20 p., https://doi.org/10.1371/journal.pone.0181197.","productDescription":"Article e0181197; 20 p.","ipdsId":"IP-084021","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":469352,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0181197","text":"Publisher Index Page"},{"id":348181,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.95139,\n 29.5\n ],\n [\n -89.82083,\n 29.5\n ],\n [\n -89.82083,\n 29.415\n ],\n [\n -89.95139,\n 29.415\n ],\n [\n -89.95139,\n 29.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-02","publicationStatus":"PW","scienceBaseUri":"59fd8026e4b0531197b50136","contributors":{"authors":[{"text":"Beland, Michael","contributorId":139569,"corporation":false,"usgs":false,"family":"Beland","given":"Michael","email":"","affiliations":[{"id":12805,"text":"Univ. of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":720086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggs, Trent W.","contributorId":187592,"corporation":false,"usgs":false,"family":"Biggs","given":"Trent","email":"","middleInitial":"W.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":720087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":720088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Seth H.","contributorId":139568,"corporation":false,"usgs":false,"family":"Peterson","given":"Seth","email":"","middleInitial":"H.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":720089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":150717,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"raymond@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":720085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Piazza, Sarai 0000-0001-6962-9008 piazzas@usgs.gov","orcid":"https://orcid.org/0000-0001-6962-9008","contributorId":169024,"corporation":false,"usgs":true,"family":"Piazza","given":"Sarai","email":"piazzas@usgs.gov","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":720090,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193700,"text":"70193700 - 2017 - Taphonomic problems in reconstructing sea-level history from the late Quaternary marine terraces of Barbados","interactions":[],"lastModifiedDate":"2017-11-03T10:34:24","indexId":"70193700","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Taphonomic problems in reconstructing sea-level history from the late Quaternary marine terraces of Barbados","docAbstract":"

Although uranium series (U-series) ages of growth-position fossil corals are important to Quaternary sea-level history, coral clast reworking from storms can yield ages on a terrace dating to more than one high-sea stand, confounding interpretations of sea-level history. On northern Barbados, U-series ages corals from a thick storm deposit are not always younger with successively higher stratigraphic positions, but all date to the last interglacial period (~127 ka to ~112 ka), Marine Isotope Substage (MIS) 5.5. The storm deposit ages are consistent with the ages of growth-position corals found at the base of the section and at landward localities on this terrace. Thus, in this case, analysis of only a few corals would not have led to an error in interpreting sea-level history. In contrast, a notch cut into older Pleistocene limestone below the MIS 5.5 terrace contains corals that date to both MIS 5.5 (~125 ka) and MIS 5.3 (~108 ka). We infer that the notch formed during MIS 5.3 and the MIS 5.5 corals are reworked. Similar multiple ages of corals on terraces have been reported elsewhere on Barbados. Thus, care must be taken in interpreting U-series ages of corals that are reported without consideration of taphonomy.

","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2017.70","usgsCitation":"Muhs, D., and Simmons, K.R., 2017, Taphonomic problems in reconstructing sea-level history from the late Quaternary marine terraces of Barbados: Quaternary Research, v. 88, no. 3, p. 409-429, https://doi.org/10.1017/qua.2017.70.","productDescription":"21 p.","startPage":"409","endPage":"429","ipdsId":"IP-077778","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":348167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Barbados","volume":"88","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-11","publicationStatus":"PW","scienceBaseUri":"59fd8028e4b0531197b5013d","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":168575,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel R.","email":"dmuhs@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":719984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simmons, Kathleen R. 0000-0002-7920-094X ksimmons@usgs.gov","orcid":"https://orcid.org/0000-0002-7920-094X","contributorId":199770,"corporation":false,"usgs":true,"family":"Simmons","given":"Kathleen","email":"ksimmons@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":719986,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193737,"text":"70193737 - 2017 - Biocrust ecology: Unifying micro- and macro-scales to confront global change","interactions":[],"lastModifiedDate":"2017-11-03T17:49:33","indexId":"70193737","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Biocrust ecology: Unifying micro- and macro-scales to confront global change","docAbstract":"

Biological soil crusts (biocrusts) are communities of microbes, lichens and bryophytes living at the soil surface in drylands (Fig. 1; Belnap et al., 2016). Biocrusts occur on all continents and can comprise a majority of cover in some systems (Belnap et al., 2016). While species diversity and distributions have long been a research focus, interest in controls on community composition and cover has expanded as biocrusts are increasingly recognized for their roles in ecosystem functioning (Deane-Coe and Stanton, 2017). For example, biocrust organisms can stabilize soils (Belnap et al., 2016; Faist et al., 2017), fix atmospheric carbon (C) (Sancho et al., 2016), and serve as the foremost source of ‘new’ soil nitrogen (N) in drylands, via N2 fixation (Barger et al., 2016) These contributions to gross primary production and soil fertility could be quite large, as high-end estimates suggest biocrusts and similar communities of bryophytes and lichens might account for 10% of terrestrial C- and 50% of N-fixation globally (Elbert et al., 2012). Yet verifying these and other biocrust roles in ecosystem functioning is complicated by limited knowledge of biocrust cover and composition across the vast dryland biome (Ferrenberg et al., 2017).

It was against this backdrop that ‘Biocrust3: the 3rd International workshop on biological soil crusts’ was held in Moab, UT, USA, on 26-30 September 2016. The workshop brought together over 50 scientists from 21 countries and six continents, and included numerous biocrust science pioneers (Fig. 2). The meeting was notable for its cross-scale focus, discussion of novel molecular and imaging techniques, and sessions on mapping and restoring biocrusts in a changing world. Here, we synthesize a central theme that emerged from Biocrust3, namely the potential for combining cutting edge tools with studies focused on organismal traits, ecosystem functions, and global change biology to advance the frontier of biocrust ecology.

","language":"English","publisher":"Wiley","doi":"10.1111/nph.14826","usgsCitation":"Ferrenberg, S., and Reed, S.C., 2017, Biocrust ecology: Unifying micro- and macro-scales to confront global change: New Phytologist, v. 216, no. 3, p. 643-646, https://doi.org/10.1111/nph.14826.","productDescription":"4 p.","startPage":"643","endPage":"646","ipdsId":"IP-088643","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469351,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.14826","text":"Publisher Index Page"},{"id":348175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-16","publicationStatus":"PW","scienceBaseUri":"59fd8024e4b0531197b5012f","contributors":{"authors":[{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":720122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":720123,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70191563,"text":"ds1071 - 2017 - Groundwater data collection for the Quinault Indian Nation, Grays Harbor and Jefferson Counties, Washington","interactions":[],"lastModifiedDate":"2017-11-06T10:01:13","indexId":"ds1071","displayToPublicDate":"2017-11-03T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1071","title":"Groundwater data collection for the Quinault Indian Nation, Grays Harbor and Jefferson Counties, Washington","docAbstract":"

Groundwater data were collected on the Quinault Indian Reservation to provide the Quinualt Indian Nation (QIN) with basic knowledge of the existing wells and springs on the reservation, and to establish a water-level network to be monitored by QIN to begin building a long-term groundwater dataset. The 327 mi2 Quinault Indian Reservation is located within the heavily forested Queets-Quinault watershed along the west-central coast of Washington and includes the coastal communities of Taholah and Queets, and the inland community of Amanda Park. Groundwater data were collected or compiled for 87 sites—82 wells and 5 springs. In October 2016, a field inventory was done to locate the sites and acquire site data. Groundwater levels were measured in 15 of the field-inventoried wells and 3 of those wells were observed as flowing (artesian). A monthly groundwater‑level monitoring network of 13 wells was established by the U.S. Geological Survey in March 2017, and the network was transferred to QIN in June 2017 for continued measurements.

Several data needs were identified that would provide a more complete understanding of the groundwater system of the Quinault Indian Reservation. The collection of monthly water-level data for multiple years is an important first step in understanding seasonal and long term changes in water levels. Additionally, the collection of baseline groundwater chemistry and quality data across the reservation would help with future efforts to monitor existing and potentially changing groundwater quality conditions. Development of a water budget of the Queets-Quinault Watershed and the reservation within that area would provide water users with a better understanding of this important resource and provide needed information about the competing demands on local water sources.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1071","collaboration":"Prepared in cooperation with the Quinault Indian Nation","usgsCitation":"Kahle, S.C., Fasser, E.T., and Olsen, T.D., 2017, Groundwater data collection for the Quinault Indian Nation, Grays Harbor and Jefferson Counties, Washington: U.S. Geological Survey Data Series 1071, 13 p., https://doi.org/10.3133/ds1071.","productDescription":"iv, 13 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-088886","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":348178,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1071/coverthb.jpg"},{"id":348179,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1071/ds1071.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1071"}],"country":"United States","state":"Washington","county":" Grays Harbor County, Jefferson County","otherGeospatial":" Quinault Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.36386108398438,\n 47.245678021018755\n ],\n [\n -123.87359619140624,\n 47.245678021018755\n ],\n [\n -123.87359619140624,\n 47.56726060598141\n ],\n [\n -124.36386108398438,\n 47.56726060598141\n ],\n [\n -124.36386108398438,\n 47.245678021018755\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2017-11-03","noUsgsAuthors":false,"publicationDate":"2017-11-03","publicationStatus":"PW","scienceBaseUri":"59fd8029e4b0531197b50141","contributors":{"authors":[{"text":"Kahle, Sue C. 0000-0003-1262-4446 sckahle@usgs.gov","orcid":"https://orcid.org/0000-0003-1262-4446","contributorId":3096,"corporation":false,"usgs":true,"family":"Kahle","given":"Sue","email":"sckahle@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fasser, Elisabeth T. 0000-0002-3945-6633 efasser@usgs.gov","orcid":"https://orcid.org/0000-0002-3945-6633","contributorId":3973,"corporation":false,"usgs":true,"family":"Fasser","given":"Elisabeth","email":"efasser@usgs.gov","middleInitial":"T.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Theresa D. 0000-0003-4099-4057 tdolsen@usgs.gov","orcid":"https://orcid.org/0000-0003-4099-4057","contributorId":1644,"corporation":false,"usgs":true,"family":"Olsen","given":"Theresa","email":"tdolsen@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":712771,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191040,"text":"ds1068 - 2017 - Vulnerable transportation and utility assets near actively migrating streams in Indiana","interactions":[],"lastModifiedDate":"2017-11-03T11:16:31","indexId":"ds1068","displayToPublicDate":"2017-11-02T11:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1068","title":"Vulnerable transportation and utility assets near actively migrating streams in Indiana","docAbstract":"

An investigation was completed by the U.S. Geological Survey in cooperation with the Indiana Office of Community and Rural Affairs that found 1,132 transportation and utility assets in Indiana are vulnerable to fluvial erosion hazards due to close proximity to actively migrating streams. Locations of transportation assets (bridges, roadways, and railroad lines) and selected utility assets (high-capacity overhead power-transmission lines, underground pipelines, water treatment facilities, and in-channel dams) were determined using aerial imagery hosted by the Google Earth platform. Identified assets were aggregated by stream reach, county, and class. Accompanying the report is a polyline shapefile of the stream reaches documented by Robinson. The shapefile, derived from line work in the National Hydrography Dataset and attributed with channel migration rates, is released with complete Federal Geographic Data Committee metadata. The data presented in this report are intended to help stakeholders and others identify high-risk areas where transportation and utility assets may be threatened by fluvial erosion hazards thus warranting consideration for mitigation strategies.

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\"}}]}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-11-02","noUsgsAuthors":false,"publicationDate":"2017-11-02","publicationStatus":"PW","scienceBaseUri":"59fc2e9fe4b0531197b27f71","contributors":{"authors":[{"text":"Sperl, Benjamin J. 0000-0002-3294-6189 bsperl@usgs.gov","orcid":"https://orcid.org/0000-0002-3294-6189","contributorId":196659,"corporation":false,"usgs":true,"family":"Sperl","given":"Benjamin J.","email":"bsperl@usgs.gov","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":711040,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191274,"text":"ofr20171122 - 2017 - Monitoring storm tide and flooding from Hurricane Matthew along the Atlantic coast of the United States, October 2016","interactions":[],"lastModifiedDate":"2017-11-02T13:40:33","indexId":"ofr20171122","displayToPublicDate":"2017-11-02T10:30:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1122","title":"Monitoring storm tide and flooding from Hurricane Matthew along the Atlantic coast of the United States, October 2016","docAbstract":"

Introduction

Hurricane Matthew moved adjacent to the coasts of Florida, Georgia, South Carolina, and North Carolina. The hurricane made landfall once near McClellanville, South Carolina, on October 8, 2016, as a Category 1 hurricane on the Saffir-Simpson Hurricane Wind Scale. The U.S. Geological Survey (USGS) deployed a temporary monitoring network of storm-tide sensors at 284 sites along the Atlantic coast from Florida to North Carolina to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Matthew. Storm tide, as defined by the National Oceanic and Atmospheric Administration, is the water-level rise generated by a combination of storm surge and astronomical tide during a coastal storm.

The deployment for Hurricane Matthew was the largest deployment of storm-tide sensors in USGS history and was completed as part of a coordinated Federal emergency response as outlined by the Stafford Act (Public Law 92–288, 42 U.S.C. 5121–5207) under a directed mission assignment by the Federal Emergency Management Agency. In total, 543 high-water marks (HWMs) also were collected after Hurricane Matthew, and this was the second largest HWM recovery effort in USGS history after Hurricane Sandy in 2012.

During the hurricane, real-time water-level data collected at temporary rapid deployment gages (RDGs) and long-term USGS streamgage stations were relayed immediately for display on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#MatthewOctober2016). These data provided emergency managers and responders with critical information for tracking flood-effected areas and directing assistance to effected communities. Data collected from this hurricane can be used to calibrate and evaluate the performance of storm-tide models for maximum and incremental water level and flood extent, and the site-specific effects of storm tide on natural and anthropogenic features of the environment.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171122","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Frantz, E.R., Byrne, M.J., Sr., Caldwell, A.W., and Harden, S.L., 2017, Monitoring storm tide and flooding from Hurricane Matthew along the Atlantic coast of the United States, October 2016: U.S. Geological Survey Open-File Report 2017–1122, 37 p., https://doi.org/10.3133/ofr20171122.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081187","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":347956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1122/ofr20171122.pdf","text":"Report","size":"5.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1122"},{"id":347955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1122/coverthb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.57421875,\n 36.56260003738545\n ],\n [\n -78.50830078125,\n 35.585851593232356\n ],\n [\n -79.69482421875,\n 34.903952965590065\n ],\n [\n -81.9140625,\n 33.358061612778876\n ],\n [\n -82.44140625,\n 31.70947636001935\n ],\n [\n -82.7490234375,\n 30.713503990354965\n ],\n [\n -82.0458984375,\n 28.998531814051795\n ],\n [\n -81.2548828125,\n 27.00040800352175\n ],\n [\n -81.650390625,\n 25.224820176765036\n ],\n [\n -80.595703125,\n 24.666986385216273\n ],\n [\n -79.3212890625,\n 25.20494115356912\n ],\n [\n -79.4970703125,\n 26.96124577052697\n ],\n [\n -79.82666015625,\n 27.994401411046148\n ],\n [\n -80.26611328125,\n 29.592565403314087\n ],\n [\n -80.35400390625,\n 31.259769987394286\n ],\n [\n -78.57421875,\n 32.80574473290688\n ],\n [\n -76.3330078125,\n 33.46810795527896\n ],\n [\n -74.619140625,\n 34.397844946449865\n ],\n [\n -73.32275390625,\n 36.56260003738545\n ],\n [\n -78.57421875,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-11-02","noUsgsAuthors":false,"publicationDate":"2017-11-02","publicationStatus":"PW","scienceBaseUri":"59fc2ea0e4b0531197b27f73","contributors":{"authors":[{"text":"Frantz, Eric R. 0000-0002-1867-886X efrantz@usgs.gov","orcid":"https://orcid.org/0000-0002-1867-886X","contributorId":196863,"corporation":false,"usgs":true,"family":"Frantz","given":"Eric R.","email":"efrantz@usgs.gov","affiliations":[],"preferred":false,"id":711814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrne, Michael J. Sr. 0000-0001-9190-2728 mbyrne@usgs.gov","orcid":"https://orcid.org/0000-0001-9190-2728","contributorId":959,"corporation":false,"usgs":true,"family":"Byrne","given":"Michael","suffix":"Sr.","email":"mbyrne@usgs.gov","middleInitial":"J.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true},{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true},{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"preferred":false,"id":711816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":138690,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral W.","email":"acaldwel@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":711817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harden, Stephen L. 0000-0001-6886-0099 slharden@usgs.gov","orcid":"https://orcid.org/0000-0001-6886-0099","contributorId":2212,"corporation":false,"usgs":true,"family":"Harden","given":"Stephen","email":"slharden@usgs.gov","middleInitial":"L.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":711815,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210912,"text":"70210912 - 2017 - Towards a comprehensive water quality modeling of Barnegat Bay: Development of ROMS to WASP Coupler","interactions":[],"lastModifiedDate":"2022-01-20T18:28:25.074392","indexId":"70210912","displayToPublicDate":"2017-11-02T09:12:28","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Towards a comprehensive water quality modeling of Barnegat Bay: Development of ROMS to WASP Coupler","docAbstract":"

The Regional Ocean Modeling System (ROMS) has been coupled with the Water Quality Analysis Simulation Program (WASP) to be used in a comprehensive analysis of water quality in Barnegat Bay, New Jersey. The coupler can spatially aggregate hydrodynamic information in ROMS cells into larger WASP segments. It can also be used to resample ROMS output at a finer temporal scale to meet WASP time-stepping requirements. The coupler aggregates flow components, temperature, and salinity in ROMS output for input to WASP via a hydrodynamic linkage file. The coupler was tested initially with idealized cases designed to verify the water mass balance and conservation of constituent mass using one-to-one and one-to-many connectivity options between segments. A realistic example from the Toms River embayment, a subdomain of Barnegat Bay, was used to demonstrate the functionality of the coupling. A WASP eutrophication model accounting for dissolved oxygen (DO), nitrogen, and constant phytoplankton concentrations was applied to explore the distribution and trends in DO and nitrogen in the embayment for the period of July–August 2012. Results of DO modeling indicate satisfactory agreement with measurements collected at in-bay stations and also indicate that this coupled approach, despite substantial differences in spatiotemporal discretization between the models, provides adequate predictive capabilities.

","language":"English","publisher":"BioOne","doi":"10.2112/SI78-004.1","usgsCitation":"Define, Z., Spitz, F.J., DePaul, V.T., and Wool, T.A., 2017, Towards a comprehensive water quality modeling of Barnegat Bay: Development of ROMS to WASP Coupler: Journal of Coastal Research, v. 78, no. Spec issue 1, p. 34-45, https://doi.org/10.2112/SI78-004.1.","productDescription":"12 p.","startPage":"34","endPage":"45","ipdsId":"IP-079333","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469353,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/9456","text":"External Repository"},{"id":376091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.17556762695312,\n 39.65698468403725\n ],\n [\n -74.15016174316406,\n 39.6834113242346\n ],\n [\n -74.10758972167969,\n 39.7642140375156\n ],\n [\n -74.09385681152344,\n 39.812755695478124\n ],\n [\n -74.07806396484375,\n 39.93975130761637\n ],\n [\n -74.12406921386719,\n 39.948174225938324\n ],\n [\n -74.1522216796875,\n 39.93711893299021\n ],\n [\n -74.10140991210938,\n 39.92606185382841\n ],\n [\n -74.13848876953125,\n 39.90762941952987\n ],\n [\n -74.15496826171874,\n 39.87338459498892\n ],\n [\n -74.20372009277344,\n 39.796930657340724\n ],\n [\n -74.21951293945312,\n 39.743098286948275\n ],\n [\n -74.19273376464844,\n 39.70031906859748\n ],\n [\n -74.21401977539062,\n 39.680240661158805\n ],\n [\n -74.2181396484375,\n 39.66808510414671\n ],\n [\n -74.17762756347656,\n 39.65116946667103\n ],\n [\n -74.17556762695312,\n 39.65698468403725\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"Spec issue 1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Define, Zafer","contributorId":228801,"corporation":false,"usgs":false,"family":"Define","given":"Zafer","email":"","affiliations":[],"preferred":false,"id":792106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spitz, Frederick J. 0000-0002-1391-2127 fspitz@usgs.gov","orcid":"https://orcid.org/0000-0002-1391-2127","contributorId":2777,"corporation":false,"usgs":true,"family":"Spitz","given":"Frederick","email":"fspitz@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":792104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DePaul, Vincent T. 0000-0002-7977-5217 vdepaul@usgs.gov","orcid":"https://orcid.org/0000-0002-7977-5217","contributorId":2778,"corporation":false,"usgs":true,"family":"DePaul","given":"Vincent","email":"vdepaul@usgs.gov","middleInitial":"T.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wool, Tim A.","contributorId":228800,"corporation":false,"usgs":false,"family":"Wool","given":"Tim","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":792107,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191750,"text":"sir20175123 - 2017 - Flood-inundation maps for the White River at Noblesville, Indiana","interactions":[],"lastModifiedDate":"2017-11-06T09:55:58","indexId":"sir20175123","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5123","title":"Flood-inundation maps for the White River at Noblesville, Indiana","docAbstract":"

Digital flood-inundation maps for a 7.5-mile reach of the White River at Noblesville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the White River at Noblesville, Ind., streamgage (USGS station number 03349000). Real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at the same site as the USGS streamgage (NWS site NBLI3).

Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current (2016) stage-discharge rating at the USGS streamgage 03349000, White River at Noblesville, Ind., and documented high-water marks from the floods of September 4, 2003, and May 6, 2017. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 10.0 ft (the NWS “action stage”) to 24.0 ft, which is the highest stage interval of the current (2016) USGS stage-discharge rating curve and 2 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each stage.

The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175123","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the White River at Noblesville, Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5123, 11 p., https://doi.org/10.3133/sir20175123.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086871","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":347858,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5123/sir20175123.pdf","text":"Report","size":"1.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5123"},{"id":347859,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MG7N0J","text":"USGS data release","description":"USGS Data Release","linkHelpText":"White River at Noblesville, Indiana, flood-inundation model and GIS data"},{"id":347857,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5123/coverthb.jpg"}],"country":"United States","state":"Indiana","city":"Noblesville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.03616714477539,\n 40.033792168980135\n ],\n [\n -85.95720291137695,\n 40.033792168980135\n ],\n [\n -85.95720291137695,\n 40.10919420673381\n ],\n [\n -86.03616714477539,\n 40.10919420673381\n ],\n [\n -86.03616714477539,\n 40.033792168980135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278–1996

","tableOfContents":"","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"publishedDate":"2017-11-02","noUsgsAuthors":false,"publicationDate":"2017-11-02","publicationStatus":"PW","scienceBaseUri":"59fc2ea2e4b0531197b27f79","contributors":{"authors":[{"text":"Martin, Zachary W. 0000-0001-5779-3548 zmartin@usgs.gov","orcid":"https://orcid.org/0000-0001-5779-3548","contributorId":156296,"corporation":false,"usgs":true,"family":"Martin","given":"Zachary","email":"zmartin@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":713197,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70193690,"text":"70193690 - 2017 - Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?","interactions":[],"lastModifiedDate":"2017-11-22T16:55:01","indexId":"70193690","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?","docAbstract":"

Conserving wide-ranging animals requires knowledge about their year-round movements and resource use. Golden Eagles (Aquila chrysaetos) exhibit a wide range of movement patterns across North America. We combined tracking data from 571 Golden Eagles from multiple independent satellite-telemetry projects from North America to provide a comprehensive look at the magnitude and extent of these movements on a continental scale. We compared patterns of use relative to four alternative administrative and ecological mapping systems, namely Bird Conservation Regions (BCRs), U.S. administrative migratory bird flyways, Migratory Bird Joint Ventures, and Landscape Conservation Cooperatives. Our analyses suggested that eagles initially captured in eastern North America used space differently than those captured in western North America. Other groups of eagles that exhibited distinct patterns in space use included long-distance migrants from northern latitudes, and southwestern and Californian desert residents. There were also several groupings of eagles in the Intermountain West. Using this collaborative approach, we have identified large-scale movement patterns that may not have been possible with individual studies. These results will support landscape-scale conservation measures for Golden Eagles across North America.

","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-72.1","usgsCitation":"Brown, J.L., Bedrosian, B., Bell, D.A., Braham, M.A., Cooper, J., Crandall, R.H., DiDonato, J., Domenech, R., Duerr, A.E., Katzner, T., Lanzone, M.J., LaPlante, D.W., McIntyre, C.L., Miller, T.A., Murphy, R.K., Shreading, A., Slater, S.J., Smith, J.P., Smith, B.W., Watson, J.W., and Woodbridge, B., 2017, Patterns of spatial distribution of golden eagles across North America: How do they fit into existing landscape-scale mapping systems?: Journal of Raptor Research, v. 51, no. 3, p. 197-215, https://doi.org/10.3356/JRR-16-72.1.","productDescription":"19 p.","startPage":"197","endPage":"215","ipdsId":"IP-082399","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":461353,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-16-72.1","text":"Publisher Index 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Center","active":true,"usgs":false}],"preferred":false,"id":719896,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Douglas A.","contributorId":199739,"corporation":false,"usgs":false,"family":"Bell","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":24634,"text":"East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":719897,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braham, Melissa A.","contributorId":199740,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":34303,"text":"West Virginia University, Department of Geology & Geography","active":true,"usgs":false}],"preferred":false,"id":719898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, Jeff","contributorId":199741,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":719899,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crandall, Ross H.","contributorId":198926,"corporation":false,"usgs":false,"family":"Crandall","given":"Ross","email":"","middleInitial":"H.","affiliations":[{"id":6657,"text":"Craighead Beringia South","active":true,"usgs":false}],"preferred":false,"id":719900,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DiDonato, Joe","contributorId":199742,"corporation":false,"usgs":false,"family":"DiDonato","given":"Joe","email":"","affiliations":[{"id":35593,"text":"Wildlife Consulting and Photography","active":true,"usgs":false}],"preferred":false,"id":719901,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Domenech, Robert","contributorId":199743,"corporation":false,"usgs":false,"family":"Domenech","given":"Robert","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":719902,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Duerr, Adam E.","contributorId":190590,"corporation":false,"usgs":false,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719903,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":719894,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lanzone, Michael J.","contributorId":147851,"corporation":false,"usgs":false,"family":"Lanzone","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13392,"text":"Cellular Tracking Technologies","active":true,"usgs":false}],"preferred":false,"id":719904,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"LaPlante, David W.","contributorId":199744,"corporation":false,"usgs":false,"family":"LaPlante","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":35595,"text":"Natural Resource Geospatial","active":true,"usgs":false}],"preferred":false,"id":719905,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McIntyre, Carol L.","contributorId":196673,"corporation":false,"usgs":false,"family":"McIntyre","given":"Carol","email":"","middleInitial":"L.","affiliations":[{"id":20307,"text":"US National Park Service","active":true,"usgs":false}],"preferred":false,"id":719906,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miller, Tricia A.","contributorId":190591,"corporation":false,"usgs":false,"family":"Miller","given":"Tricia","email":"","middleInitial":"A.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":719907,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Murphy, Robert K.","contributorId":67643,"corporation":false,"usgs":false,"family":"Murphy","given":"Robert","email":"","middleInitial":"K.","affiliations":[{"id":56253,"text":"Eagle Environmental, Inc","active":true,"usgs":false}],"preferred":false,"id":719908,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Shreading, Adam","contributorId":199745,"corporation":false,"usgs":false,"family":"Shreading","given":"Adam","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":719909,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Slater, Steven J.","contributorId":199746,"corporation":false,"usgs":false,"family":"Slater","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":35596,"text":"HawkWatch International","active":true,"usgs":false}],"preferred":false,"id":719910,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Smith, Jeff P.","contributorId":199747,"corporation":false,"usgs":false,"family":"Smith","given":"Jeff","email":"","middleInitial":"P.","affiliations":[{"id":35597,"text":"H.T. Harvey & Associates","active":true,"usgs":false}],"preferred":false,"id":719911,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Smith, Brian W.","contributorId":199748,"corporation":false,"usgs":false,"family":"Smith","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":719912,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Watson, James W.","contributorId":198921,"corporation":false,"usgs":false,"family":"Watson","given":"James","email":"","middleInitial":"W.","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":719913,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Woodbridge, Brian","contributorId":198923,"corporation":false,"usgs":false,"family":"Woodbridge","given":"Brian","email":"","affiliations":[{"id":17821,"text":"U.S. Fish and Wildlife Service, Division of Migratory Birds","active":true,"usgs":false}],"preferred":false,"id":719914,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70193559,"text":"70193559 - 2017 - Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)","interactions":[],"lastModifiedDate":"2017-11-02T15:47:54","indexId":"70193559","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)","title":"Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)","docAbstract":"

Context: Understanding habitat selection is important for determining conservation and management strategies for endangered species. The Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) is an endangered subspecies found in the high-elevation montane forests of the southern Appalachians, USA. The primary use of nest boxes to monitor CNFS has provided biased information on habitat use for this subspecies, as nest boxes are typically placed in suitable denning habitat.

Aims: We conducted a radio-telemetry study on CNFS to determine home range, den site selection and habitat use at multiple spatial scales.

Methods: We radio-collared 21 CNFS in 2012 and 2014–15. We tracked squirrels to diurnal den sites and during night-time activity.

Key results: The MCP (minimum convex polygon) home range at 95% for males was 5.2 ± 1.2 ha and for females was 4.0 ± 0.7. The BRB (biased random bridge) home range at 95% for males was 10.8 ± 3.8 ha and for females was 8.3 ± 2.1. Den site (n = 81) selection occurred more frequently in montane conifer dominate forests (81.4%) vs northern hardwood forests or conifer–northern hardwood forests (9.9% and 8.7%, respectively). We assessed habitat selection using Euclidean distance-based analysis at the 2nd order and 3rd order scale. We found that squirrels were non-randomly selecting for habitat at both 2nd and 3rd order scales.

Conclusions: At both spatial scales, CNFS preferentially selected for montane conifer forests more than expected based on availability on the landscape. Squirrels selected neither for nor against northern hardwood forests, regardless of availability on the landscape. Additionally, CNFS denned in montane conifer forests more than other habitat types.

Implications: Our results highlight the importance of montane conifer to CNFS in the southern Appalachians. Management and restoration activities that increase the quality, connectivity and extent of this naturally rare forest type may be important for long-term conservation of this subspecies, especially with the impending threat of anthropogenic climate change.

","language":"English","publisher":"Csiro Publishing","doi":"10.1071/WR16203","usgsCitation":"Diggins, C.A., Silvis, A., Kelly, C.A., and Ford, W.M., 2017, Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus): Wildlife Research, v. 44, no. 5, p. 427-237, https://doi.org/10.1071/WR16203.","productDescription":"11 p.","startPage":"427","endPage":"237","ipdsId":"IP-078733","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Mountains","volume":"44","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea2e4b0531197b27f77","contributors":{"authors":[{"text":"Diggins, Corinne A.","contributorId":171667,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne","email":"","middleInitial":"A.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":719359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":719360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelly, Christine A.","contributorId":171661,"corporation":false,"usgs":false,"family":"Kelly","given":"Christine","email":"","middleInitial":"A.","affiliations":[{"id":35598,"text":"North Carolina Wildlife Resources Commission ","active":true,"usgs":false}],"preferred":false,"id":719361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":719358,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190730,"text":"fs20173073 - 2017 - The 3D Elevation Program national indexing scheme","interactions":[],"lastModifiedDate":"2022-04-22T16:08:11.241298","indexId":"fs20173073","displayToPublicDate":"2017-11-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3073","title":"The 3D Elevation Program national indexing scheme","docAbstract":"

The 3D Elevation Program (3DEP) of the U.S. Geological Survey (USGS) acquires high-resolution elevation data for the Nation. This program has been operating under an opportunity-oriented approach, acquiring light detection and ranging (lidar) projects of varying sizes scattered across the United States. As a result, the national 3DEP elevation layer is subject to data gaps or unnecessary overlap between adjacent collections. To mitigate this problem, 3DEP is adopting a strategic, systematic approach to national data acquisition that will create efficiencies in efforts to achieve nationwide elevation data coverage and help capture additional Federal and non-Federal investments resulting from advance awareness of proposed acquisitions and partnership opportunities. The 3DEP Working Group, an interagency group managed by the USGS, has agreed that all future 3DEP collections within the lower 48 States should be coordinated by using a 1-kilometer by 1-kilometer tiling scheme for the conterminous United States. Fiscal Year 2018 is being considered a transition year, and in Fiscal Year 2019 the national indexing scheme will be fully implemented, so that all 3DEP-supported projects will be acquired and delivered in the national indexing scheme and projected into the Albers Equal Area projection. 

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173073","issn":"2327-6916","usgsCitation":"Thatcher, C.A., Heidemann, H.K., Stoker, J.M., and Eldridge, D.F., 2017, The 3D Elevation Program national indexing scheme: U.S. Geological Survey Fact Sheet 2017-3073, 2 p., https://doi.org/10.3133/fs20173073.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088200","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":346327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3073/fs20173073.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3073"},{"id":346326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3073/coverthb.jpg"}],"contact":"

Director, National Geospatial Program
U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov

Or visit the National Geospatial Program website at https://www2.usgs.gov/ngpo/

","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2017-11-02","noUsgsAuthors":false,"publicationDate":"2017-11-02","publicationStatus":"PW","scienceBaseUri":"59fc2ea2e4b0531197b27f7b","contributors":{"authors":[{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":710269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heidemann, Hans Karl 0000-0003-4306-359X kheidemann@usgs.gov","orcid":"https://orcid.org/0000-0003-4306-359X","contributorId":3755,"corporation":false,"usgs":true,"family":"Heidemann","given":"Hans","email":"kheidemann@usgs.gov","middleInitial":"Karl","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":710272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":710270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eldridge, Diane F. 0000-0002-2821-6239 deldridge@usgs.gov","orcid":"https://orcid.org/0000-0002-2821-6239","contributorId":196409,"corporation":false,"usgs":true,"family":"Eldridge","given":"Diane","email":"deldridge@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":false,"id":710271,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200597,"text":"70200597 - 2017 - Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana","interactions":[],"lastModifiedDate":"2018-10-24T16:27:54","indexId":"70200597","displayToPublicDate":"2017-11-01T16:27:46","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana","docAbstract":"

The Upper Mississippian Heath Formation, which accumulated in the Big Snowy Trough of central Montana, has been known for three decades to contain mudrocks highly enriched in Zn, V, Mo, Ni and other metals, and source rocks for oil. The unit has more recently been recognized as a prospective tight oil play. Here we present petrographic, paleontologic, geochemical, and carbon and sulfur isotope data on seven continuous drill cores spanning ≤146 m of immature to marginally mature strata in order to improve understanding of the depositional setting of the Heath.

The unit consists of five third-order transgressive-regressive cycles (C1–C5 from bottom to top) that were deposited during a fluctuating climatic regime. Cycles comprise thinly interbedded gray to black mudrock and carbonate strata capped by either coal, implying a humid climate (C1, C3 and C4), or gypsum, implying more arid conditions (C2); the upper part of C5 is not preserved in our study area. Mfs (maximum flooding surfaces) in C1, C2, C4, and C5 lie within black mudrock beds ~0.5–3-m thick with >10% TOC (total organic carbon), type I and type II kerogen (determined by programmed pyrolysis), high contents of Zn, V, Mo, and other metals, relatively low values of δ13CTOC and δ34Spyrite, and a limited-diversity fauna of locally abundant, thin-shelled pelecypods (Dunbarella? sp.).

The mfs in C2 is within the Cox Ranch oil shale bed, which is known from previous studies to be metalliferous; new analyses reported here show ≤28 wt % TOC, 5140 ppm Zn, 1910 ppm V, 1590 ppm Mo, and 509 ppm Ni. Strata that contain the mfs of C1, C4, and C5 are shown here for the first time to also have high metal contents, with maximum values of 1030–7340 ppm Zn, 446–1980 ppm V, 72–859 ppm Mo, and 221–452 ppm Ni. Cycle C3, which contains more gray mudrock and carbonate beds than the other cycles, has lower TOC (≤4.2 wt %), lower metals, and mainly type III kerogen. Carbonate beds include normal-marine crinoidal mudstone to packstone and lesser (dolo)mudstone with fenestral fabric, peloids, intraclasts, and a euryhaline fauna. Mid-Chesterian (early Serpukhovian) foraminifers in C3, combined with previously published fossil data, suggest that third-order cycles in the Heath Formation were ~1–2 myr in duration. They formed during a time of active block faulting in the Big Snowy Trough and global cooling linked to Gondwanan glaciation.

Tectonic, climatic, and paleogeographic factors shaped the cycles of the Heath Formation. Faunal and geochemical evidence indicate that conditions were most favorable for marine life during C3. Molybdenum concentrations >100 ppm and organic geochemical data suggest euxinic conditions during deposition of the black mudrock in C2, C4, and C5, but the presence of shell beds (1 mm–6-cm thick) within this mudrock requires bottom water with sufficient oxygen to support life, at least periodically. The apparent conflict between the geochemical and paleontologic observations likely reflects the different time scales of these two environmental proxies: 1000s of yrs vs <1–10s of yrs, respectively.

Metal- and organic-rich strata in the Heath Formation formed by slow, condensed sedimentation from periodically anoxic or euxinic bottom waters in a marine basin. Fossil data indicate that anoxia was episodic, perhaps seasonal and/or linked to longer-duration climate shifts. On a millennial time scale, metal enrichments in the Heath reflect a balance between primary productivity that was high enough for oxygen to be consumed by sinking organic matter and oxic seawater inflow that was strong enough to maintain a supply of metals without compromising anoxia. Organic-rich mudrock in the Heath shares intriguing lithologic and geochemical similarities with mudrock in other Middle to Upper Paleozoic units such as the Devonian-Mississippian Bakken Formation and Pennsylvanian cyclothems (e.g., Excello Shale).

","language":"English","publisher":"Micropress","doi":"10.29041/strat.14.1-4.97-122","usgsCitation":"Dumoulin, J.A., Johnson, C.A., Kelley, K.D., Botterell, P.J., Hackley, P.C., Scott, C., and Slack, J.F., 2017, Transgressive-regressive cycles in the metalliferous, oil-shale-bearing Heath Formation (Upper Mississippian), central Montana: Stratigraphy, v. 14, no. 1-4, p. 97-122, https://doi.org/10.29041/strat.14.1-4.97-122.","productDescription":"26 p.","startPage":"97","endPage":"122","ipdsId":"IP-077939","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":438158,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7668BPP","text":"USGS data release","linkHelpText":"Appendices for Transgressive-regressive cycles in the metalliferous, oil shale-bearing Heath Formation (Upper Mississippian), central Montana"},{"id":358777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Heath Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.75,\n 46.75\n ],\n [\n -108.8,\n 46.75\n ],\n [\n -108.8,\n 47\n ],\n [\n -109.75,\n 47\n ],\n [\n -109.75,\n 46.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1-4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-28","publicationStatus":"PW","scienceBaseUri":"5c10aacce4b034bf6a7e5cfd","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":749684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":749685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Karen D. 0000-0002-3232-5809 kdkelley@usgs.gov","orcid":"https://orcid.org/0000-0002-3232-5809","contributorId":179012,"corporation":false,"usgs":true,"family":"Kelley","given":"Karen","email":"kdkelley@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":749686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Botterell, Palma J. 0000-0001-7140-0915 pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":749688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Clint 0000-0003-2778-2711 clintonscott@usgs.gov","orcid":"https://orcid.org/0000-0003-2778-2711","contributorId":5332,"corporation":false,"usgs":true,"family":"Scott","given":"Clint","email":"clintonscott@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":749689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":749690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70199247,"text":"70199247 - 2017 - Synopsis of the Fourth International Percid Fishes Symposia","interactions":[],"lastModifiedDate":"2018-09-13T15:48:43","indexId":"70199247","displayToPublicDate":"2017-11-01T15:48:37","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Synopsis of the Fourth International Percid Fishes Symposia","docAbstract":"
Percids play an integral role in food webs and freshwater fisheries of the world. Anthropogenic stressors such as pollution, overfishing, invasive species, and climate change threaten percid diversity and the sustainability of economically important fisher-ies. The International Percid Fish Symposium is the only scien-tific conference dedicated to this family of fishes, offering unique opportunities for communication, discussion, and collaboration among scientists studying these valuable fishes. In this synopsis, we review the history of the percid symposia with an emphasis on the recent Fourth International Percid Fish Symposium held in Tartu, Estonia, during April 2016 and discuss future needs and direction for this important scientific conference.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/03632415.2017.1377562","usgsCitation":"Schmidt, B., Castle, D., Roseman, E.F., Saat, T., and Lehtonen, H., 2017, Synopsis of the Fourth International Percid Fishes Symposia: Fisheries, v. 42, no. 11, p. 567-570, https://doi.org/10.1080/03632415.2017.1377562.","productDescription":"4 p.","startPage":"567","endPage":"570","ipdsId":"IP-079508","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":357287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"11","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-08","publicationStatus":"PW","scienceBaseUri":"5bc030c3e4b0fc368eb53a0f","contributors":{"authors":[{"text":"Schmidt, Brian 0000-0001-7067-6194","orcid":"https://orcid.org/0000-0001-7067-6194","contributorId":207822,"corporation":false,"usgs":true,"family":"Schmidt","given":"Brian","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":744813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castle, Dana 0000-0003-1982-2920 dcastle@usgs.gov","orcid":"https://orcid.org/0000-0003-1982-2920","contributorId":207821,"corporation":false,"usgs":true,"family":"Castle","given":"Dana","email":"dcastle@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":744812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roseman, Edward F. 0000-0002-5315-9838 eroseman@usgs.gov","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":168428,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward","email":"eroseman@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":744811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saat, Toomas","contributorId":207824,"corporation":false,"usgs":false,"family":"Saat","given":"Toomas","email":"","affiliations":[{"id":37641,"text":"Estonian Marine Institute, University of Tartu","active":true,"usgs":false}],"preferred":false,"id":744815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lehtonen, Hannu","contributorId":207823,"corporation":false,"usgs":false,"family":"Lehtonen","given":"Hannu","email":"","affiliations":[{"id":18162,"text":"University of Helsinki","active":true,"usgs":false}],"preferred":false,"id":744814,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70237026,"text":"70237026 - 2017 - Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data","interactions":[],"lastModifiedDate":"2022-09-27T18:16:34.534927","indexId":"70237026","displayToPublicDate":"2017-11-01T13:04:44","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data","docAbstract":"A sparsely instrumented 55-story building in Osaka, Japan had recorded unprecedented, severe and long-duration long-period resonating responses during the March 11, 2011 M9.0 Tohoku earthquake that occurred at 767 km distance. Thereafter, studies of the records resulted in implementation of a significant retrofit design, comprising dampers and buckling restrained braces (BRBs). The responses of the retrofitted building were also recorded during the April 24, 2016 M7.3 Kumamoto earthquake that occurred at 478 km. The earthquake and on-demand acquired ambient response data are analyzed in this study to assess the impact of this rare, retrofitted and instrumented tall building subjected to long period strong shaking from events originating at far distances. As expected, the fundamental frequency and critical damping ratio of the building increased, albeit small, after the retrofit as compared to before the retrofit. Increase of damping percentage is a positive finding and indicates that even larger percentages may be attained under shaking stronger than the 2016 event. The records indicate that the building still experiences significant resonance, torsion, as well as a beating effect.","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/122216EQS249M","usgsCitation":"Celebi, M., Kashima, T., Ghahari, S., Koyama, S., Taciroğlu, E., and Okawa, I., 2017, Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data: Earthquake Spectra, v. 33, no. 4, p. 1599-1626, https://doi.org/10.1193/122216EQS249M.","productDescription":"28 p.","startPage":"1599","endPage":"1626","ipdsId":"IP-081004","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","city":"Osaka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 135.28289794921875,\n 34.482788036293435\n ],\n [\n 135.62828063964844,\n 34.482788036293435\n ],\n [\n 135.62828063964844,\n 34.80083618518153\n ],\n [\n 135.28289794921875,\n 34.80083618518153\n ],\n [\n 135.28289794921875,\n 34.482788036293435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":853104,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kashima, Toshihide","contributorId":176614,"corporation":false,"usgs":false,"family":"Kashima","given":"Toshihide","email":"","affiliations":[],"preferred":false,"id":853105,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ghahari, S. Farid","contributorId":296977,"corporation":false,"usgs":false,"family":"Ghahari","given":"S. Farid","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":853106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koyama, Shin","contributorId":149525,"corporation":false,"usgs":false,"family":"Koyama","given":"Shin","email":"","affiliations":[],"preferred":false,"id":853107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taciroğlu, Ertuğrul","contributorId":168418,"corporation":false,"usgs":false,"family":"Taciroğlu","given":"Ertuğrul","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":853108,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okawa, Izuru","contributorId":65508,"corporation":false,"usgs":true,"family":"Okawa","given":"Izuru","affiliations":[],"preferred":false,"id":853143,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70236853,"text":"70236853 - 2017 - Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data","interactions":[],"lastModifiedDate":"2022-09-20T13:28:51.954428","indexId":"70236853","displayToPublicDate":"2017-11-01T08:21:29","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data","docAbstract":"

A sparsely instrumented 55-story building in Osaka, Japan, had recorded unprecedented, severe, and long-duration, long-period resonating responses during the 11 March 2011 M9.0 Tohoku earthquake that occurred at 767 km distance. Thereafter, studies of the records resulted in the implementation of a significant retrofit design, comprising dampers and buckling restrained braces (BRBs). The responses of the retrofitted building were also recorded during the 24 April 2016 M7.3 Kumamoto earthquake that occurred at 478 km. The earthquake and on-demand acquired ambient response data are analyzed in this study to assess the impact of this rare, retrofitted and instrumented tall building subjected to long period strong shaking from events originating at far distances. As expected, the fundamental frequency and critical damping ratio of the building increased, albeit small, after the retrofit as compared to before the retrofit. Increase of damping percentage is a positive finding and indicates that even larger percentages may be attained under shaking stronger than the 2016 event. The records indicate that the building still experiences significant resonance, torsion, as well as a beating effect.

","language":"English","publisher":"Sage","doi":"10.1193/122216EQS249M","usgsCitation":"Celebi, M., Kashima, T., Ghahari, S.F., Koyama, S., Tacirogle, E., and Okawa, I., 2017, Before and after retrofit behavior and performance of a 55-story tall building inferred from distant earthquake and ambient vibration data: Earthquake Spectra, v. 33, no. 4, p. 1599-1626, https://doi.org/10.1193/122216EQS249M.","productDescription":"28 p.","startPage":"1599","endPage":"1626","ipdsId":"IP-082394","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":407053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 140.86669921875,\n 41.623655390686395\n ],\n [\n 140.11962890625,\n 41.22824901518529\n ],\n [\n 139.74609375,\n 40.68063802521456\n ],\n [\n 139.6142578125,\n 39.50404070558415\n ],\n [\n 137.8564453125,\n 38.09998264736481\n ],\n [\n 136.40625,\n 37.33522435930639\n ],\n [\n 135.59326171875,\n 35.99578538642032\n ],\n [\n 132.25341796875,\n 35.65729624809628\n ],\n [\n 129.00146484375,\n 33.119150226768866\n ],\n [\n 130.166015625,\n 30.637912028341123\n ],\n [\n 131.50634765625,\n 31.372399104880525\n ],\n [\n 134.560546875,\n 33.284619968887675\n ],\n [\n 136.31835937499997,\n 33.32134852669881\n ],\n [\n 139.4384765625,\n 34.59704151614417\n ],\n [\n 140.77880859374997,\n 35.28150065789119\n ],\n [\n 141.13037109375,\n 35.99578538642032\n ],\n [\n 142.14111328125,\n 39.65645604812829\n ],\n [\n 141.63574218749997,\n 41.409775832009565\n ],\n [\n 140.86669921875,\n 41.623655390686395\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2017-11-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":852361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kashima, Toshihide","contributorId":176614,"corporation":false,"usgs":false,"family":"Kashima","given":"Toshihide","email":"","affiliations":[],"preferred":false,"id":852362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ghahari, S. F.","contributorId":147707,"corporation":false,"usgs":false,"family":"Ghahari","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koyama, Shin","contributorId":149525,"corporation":false,"usgs":false,"family":"Koyama","given":"Shin","email":"","affiliations":[],"preferred":false,"id":852364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tacirogle, Ertugrul","contributorId":296749,"corporation":false,"usgs":false,"family":"Tacirogle","given":"Ertugrul","email":"","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":852365,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Okawa, Izuru","contributorId":65508,"corporation":false,"usgs":true,"family":"Okawa","given":"Izuru","affiliations":[],"preferred":false,"id":852384,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208431,"text":"70208431 - 2017 - Assessing the risk of non-native marine species in the Bering Sea","interactions":[],"lastModifiedDate":"2020-02-11T06:42:26","indexId":"70208431","displayToPublicDate":"2017-11-01T06:52:53","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Assessing the risk of non-native marine species in the Bering Sea","docAbstract":"

Invasive species are one of the leading global conservation concerns, which can have strong, negative impacts on ecosystems, vulnerable species, and valuable natural resources. Arctic regions have experienced a relatively low number of biological introductions to date. Their geographical remoteness, cold waters, and presence of sea ice present challenging conditions for both non-native organisms and the vessels that transport them, presumably leading to low rates of introduction and establishment. However, observed increases in water temperatures reductions in sea ice, and projected increases in shipping traffic are expected to render arctic marine regions more susceptible to the arrival and colonization of marine invasives. Risk assessments for these Arctic regions are important to inform management and monitoring priorities by determining which species pose the greatest risk. To this end, we developed a ranking system for non-native marine species and used this system to assess the risk of non-native species to the Bering Sea. Using species’ published physiological tolerances, we mapped habitat suitability under current and future climate scenarios to identify geographic areas of current and future concern. In addition, we described shipping traffic from commercial and fishing vessels to identify ports of entry for non-native species. Collectively, these analyses identify which marine species have the greatest risk for invasion, where in the Bering Sea invasion risk and species establishment is greatest, and which ports are most likely to serve as an entry point for marine invasives into Alaska’s Bering Sea. The ranking system we developed for non-native marine species consists of 33 questions grouped into five categories. The first four categories evaluate a species’ ability to arrive and establish in the Bering Sea, its reliance on humans for introductions, its biology, and its impacts on ecological and human systems. The fifth category is not included in the total ranking score, but provides information on management considerations. The ranking system has methods to account for data deficiencies and calculates these deficiencies to allow readers to weigh the lack of knowledge with the ranking score. We prioritized non-native species for ranking based on their geographic proximity to the Bering Sea. We evaluated 46 species and ranking scores ranged from 29.1 to 74.3 (out of a possible 100), with highest scores indicating greatest risk. Taxonomy at the level of phylum did not explain variation in ranking values, likely due to the substantial biological variation relative to our ranking criteria among members of the same phylum. To investigate where non-native species may survive and persist in the Bering Sea, we compared species’ temperature and salinity thresholds to environmental conditions of the Bering Sea. Environmental conditions were obtained from three Regional Ocean Modeling Systems (ROMS) and investigated under two time periods: current (2003-2012) and mid-century (2030-2039). We identified potential habitat for survival for 42 species, and potential habitat for reproduction for 29 species. Under current conditions, all species had temperature and salinity thresholds that would allow survival in the Bering Sea for at least part of the year, and most species (79% to 83%) had thresholds that would allow for survival year-round. For species with temperature and salinity thresholds unsuitable for survival in the Bering Sea, winter temperatures appear to be the limiting factor. Most species had six to nine weeks of suitable conditions for reproduction. Future increases in water temperatures are expected to open more habitat for marine invasives. Two of the three ROMs project an increase in the number of non-native species that would be able to survive year-round by mid-century. Moreover, models project between 37% and 60% of the Bering Sea shelf habitat to become more suitable under mid-century climate condition.

","language":"English","publisher":"North Pacific Research Board","collaboration":"University of Alaska Anchorage, NOAA, Aleutian Bering Sea Islands Landscape Conservation Cooperative","usgsCitation":"Reimer, J., Droghini, A., Fischbach, A., Watson, J., Bernard, B., and Poe, A., 2017, Assessing the risk of non-native marine species in the Bering Sea, 46 p.","productDescription":"46 p.","ipdsId":"IP-094656","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":372180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372163,"type":{"id":15,"text":"Index Page"},"url":"https://accs.uaa.alaska.edu/wp-content/uploads/Reimeretal2017_FinalReport.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -172.79296875,\n 51.890053935216926\n ],\n [\n -161.89453125,\n 51.890053935216926\n ],\n [\n -161.89453125,\n 65.94647177615738\n ],\n [\n -172.79296875,\n 65.94647177615738\n ],\n [\n -172.79296875,\n 51.890053935216926\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Reimer, Jesika","contributorId":222311,"corporation":false,"usgs":false,"family":"Reimer","given":"Jesika","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Droghini, Amanda 0000-0001-6692-2348","orcid":"https://orcid.org/0000-0001-6692-2348","contributorId":222312,"corporation":false,"usgs":false,"family":"Droghini","given":"Amanda","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":200780,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony S.","email":"afischbach@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":781852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watson, Jordan 0000-0002-1686-0377","orcid":"https://orcid.org/0000-0002-1686-0377","contributorId":222313,"corporation":false,"usgs":false,"family":"Watson","given":"Jordan","email":"","affiliations":[{"id":40517,"text":"NOAA Alaska Fisheries Science Center Auke Bay Laboratories","active":true,"usgs":false}],"preferred":false,"id":781855,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernard, Bonnie","contributorId":222314,"corporation":false,"usgs":false,"family":"Bernard","given":"Bonnie","email":"","affiliations":[{"id":40516,"text":"Alaska Center for Conservation Science University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":781856,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poe, Aaron","contributorId":222315,"corporation":false,"usgs":false,"family":"Poe","given":"Aaron","email":"","affiliations":[{"id":40518,"text":"Aleutian and Bering Sea Islands LCC U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":781857,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192845,"text":"70192845 - 2017 - Effects of industrial and investigator disturbance on Arctic-nesting geese","interactions":[],"lastModifiedDate":"2017-11-01T16:54:00","indexId":"70192845","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of industrial and investigator disturbance on Arctic-nesting geese","docAbstract":"

Oil and gas development on the Arctic Coastal Plain (ACP) of Alaska, USA may have effects on Arctic-nesting birds. To estimate effects of industrial activity and investigator disturbance on avian productivity, we monitored nests of greater white-fronted geese (Anser albifrons) with digital cameras and periodic nest visits during 2013–2014 at 2 sites on the ACP. A disturbed site was adjacent to human-made infrastructure and industrial clean-up activities initiated at the onset of the study and a control site was >2 km from sources of industrial disturbance. We assessed variation in estimates of incubation constancy, nest survival, and predator behavior relative to site, year, and distance from industrial activity using nest photographs obtained at 1-minute intervals. We compared analysis of hourly nest survival informed by intensive monitoring with cameras to analysis of daily nest survival informed by traditional nest visit data obtained at intervals of 5–7 days to assess how method and time scale of sampling affect ecological inference. Geese in both sites exhibited high levels of nest attendance and initiated incubation breaks less than once per day. Observer-caused incubation breaks associated with nest visits (\"math = 37.8 min) were longer than other types of incubation breaks (\"math = 8.7 min), demonstrating a differential response by nesting geese to direct human encroachment versus indirect vehicular and aircraft traffic. During both years, geese were absent from nests more frequently in the disturbed (\"math = 0.9 breaks/day) than control (\"math = 0.6 breaks/day) site, and this break frequency was slightly higher for nests closer to industrial activity. In the year with high rates of depredation, nest survival was positively related to distance from industrial activity and abandoned infrastructure, consistent with predictions of industry-caused effects. This relationship, however, was not evident in the year with reduced predation pressure, likely because of annual variation in arctic fox (Vulpes lagopus) behavior. Analysis of nest survival probability informed by camera data allowed for detection of detailed patterns of variation that were not supported when using only visit data for the same nests. Observer visits were responsible for reductions of 7–35% in nest survival probability, highlighting the importance of minimizing, and controlling for, observer effects in studies of avian productivity. Indirect vehicular and aircraft disturbance posed less risk to nest survival than direct encroachment by observers at nest sites. Therefore, effects of industrial activities on avian productivity in the Arctic can be minimized through practices that limit direct encounters with nests. 

","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21312","usgsCitation":"Meixell, B.W., and Flint, P.L., 2017, Effects of industrial and investigator disturbance on Arctic-nesting geese: Journal of Wildlife Management, v. 81, no. 8, p. 1372-1385, https://doi.org/10.1002/jwmg.21312.","productDescription":"14 p.","startPage":"1372","endPage":"1385","ipdsId":"IP-082311","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438162,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NV9GP9","text":"USGS data release","linkHelpText":"Greater White-fronted Goose (Anser albifrons) Nest Characteristics and Nesting Behavior Classifications from Time-lapse Photographs; Point Lonely, Alaska, 2013-2014"},{"id":348059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.31369400024414,\n 70.89024547571003\n ],\n [\n -153.21224212646484,\n 70.89024547571003\n ],\n [\n -153.21224212646484,\n 70.91613598862408\n ],\n [\n -153.31369400024414,\n 70.91613598862408\n ],\n [\n -153.31369400024414,\n 70.89024547571003\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-17","publicationStatus":"PW","scienceBaseUri":"59fadd1ee4b0531197b13c6c","contributors":{"authors":[{"text":"Meixell, Brandt W. 0000-0002-6738-0349 bmeixell@usgs.gov","orcid":"https://orcid.org/0000-0002-6738-0349","contributorId":138716,"corporation":false,"usgs":true,"family":"Meixell","given":"Brandt","email":"bmeixell@usgs.gov","middleInitial":"W.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":717170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Paul L. 0000-0002-8758-6993 pflint@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-6993","contributorId":3284,"corporation":false,"usgs":true,"family":"Flint","given":"Paul","email":"pflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":717171,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193595,"text":"70193595 - 2017 - Dynamic optimization of landscape connectivity embedding spatial-capture-recapture information","interactions":[],"lastModifiedDate":"2017-11-16T11:37:23","indexId":"70193595","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Dynamic optimization of landscape connectivity embedding spatial-capture-recapture information","docAbstract":"Maintaining landscape connectivity is increasingly important\nin wildlife conservation, especially for species experiencing\nthe effects of habitat loss and fragmentation. We propose a\nnovel approach to dynamically optimize landscape connectivity.\nOur approach is based on a mixed integer program formulation,\nembedding a spatial capture-recapture model that\nestimates the density, space usage, and landscape connectivity\nfor a given species. Our method takes into account the\nfact that local animal density and connectivity change dynamically\nand non-linearly with different habitat protection\nplans. In order to scale up our encoding, we propose a sampling\nscheme via random partitioning of the search space using\nparity functions. We show that our method scales to realworld\nsize problems and dramatically outperforms the solution\nquality of an expectation maximization approach and a\nsample average approximation approach.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI-17)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Thirty-First Conference on Artificial Intelligence (AAAI-17)","conferenceLocation":"San Francisco, CA","language":"English","publisher":"Association for the Advancement of Artificial Intelligence","usgsCitation":"Xue, Y., Wu, X., Morin, D.J., Dilkina, B., Fuller, A.K., Royle, J., and Gomes, C.P., 2017, Dynamic optimization of landscape connectivity embedding spatial-capture-recapture information, in Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI-17), San Francisco, CA, 7 p.","productDescription":"7 p.","ipdsId":"IP-081147","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d18","contributors":{"authors":[{"text":"Xue, Yexiang","contributorId":200458,"corporation":false,"usgs":false,"family":"Xue","given":"Yexiang","email":"","affiliations":[],"preferred":false,"id":722407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Xiaojian","contributorId":200459,"corporation":false,"usgs":false,"family":"Wu","given":"Xiaojian","email":"","affiliations":[],"preferred":false,"id":722408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morin, Dana J.","contributorId":200306,"corporation":false,"usgs":false,"family":"Morin","given":"Dana","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":722409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dilkina, Bistra","contributorId":177110,"corporation":false,"usgs":false,"family":"Dilkina","given":"Bistra","affiliations":[],"preferred":false,"id":722410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719549,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"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":719550,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gomes, Carla P.","contributorId":177112,"corporation":false,"usgs":false,"family":"Gomes","given":"Carla","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":722411,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192908,"text":"70192908 - 2017 - Survival, movement, and distribution of juvenile Burbot in a tributary of the Kootenai River","interactions":[],"lastModifiedDate":"2017-11-07T14:16:46","indexId":"70192908","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Survival, movement, and distribution of juvenile Burbot in a tributary of the Kootenai River","docAbstract":"

Burbot Lota lota in the lower Kootenai River, Idaho, have been the focus of extensive conservation efforts, particularly the release of hatchery-reared juvenile Burbot into small tributaries. The Idaho Department of Fish and Game installed a fixed PIT antenna on Deep Creek, a tributary of the Kootenai River, to evaluate movement of juvenile Burbot to the Kootenai River. Since then, approximately 12,000 juvenile Burbot have been PIT-tagged and released into Deep Creek, but few Burbot have been detected at the antenna, thus raising questions about their fate in the creek. The objectives of this study were to evaluate survival, movement, and distribution of Burbot released into Deep Creek. During 2014, 3,000 age-0, 200 age-1, 16 age-2, and 16 age-4 Burbot were released at two different locations; during 2015, 3,000 age-0 Burbot were released at six different locations (i.e., 500 fish/site). Five additional stationary PIT tag antennas were installed on Deep Creek prior to stocking in 2014. Mobile PIT tag antennas were used to survey the creek in 2015 and 2016. A Barker model in Program MARK was used to estimate survival. Stationary and mobile PIT tag antennas relocated 3,372 (56%) of the Burbot released in Deep Creek during 2014 and 2015. Eighty-eight percent of PIT tags relocated during mobile surveys were relocated within 1 km of a release location. Mobile surveys of release locations in Deep Creek suggested poor dispersal from stocking locations. Survival did not vary across years or release groups. Initial 7-month survival in Deep Creek was 0.27, and survival improved to 0.63 after the first 7 months. Although survival did not differ between years or among release groups, managers may consider releasing Burbot at lower densities across multiple locations.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2017.1376010","usgsCitation":"Beard, Z.S., Quist, M.C., Hardy, R.S., and Ross, T.J., 2017, Survival, movement, and distribution of juvenile Burbot in a tributary of the Kootenai River: North American Journal of Fisheries Management, v. 37, no. 6, p. 1274-1288, https://doi.org/10.1080/02755947.2017.1376010.","productDescription":"15 p.","startPage":"1274","endPage":"1288","ipdsId":"IP-084417","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.58279418945312,\n 48.50386733939323\n ],\n [\n -116.2847900390625,\n 48.50386733939323\n ],\n [\n -116.2847900390625,\n 48.700931311842744\n ],\n [\n -116.58279418945312,\n 48.700931311842744\n ],\n [\n -116.58279418945312,\n 48.50386733939323\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5a07e84ce4b09af898c8cb46","contributors":{"authors":[{"text":"Beard, Zachary S.","contributorId":198840,"corporation":false,"usgs":false,"family":"Beard","given":"Zachary","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":720981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":717343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":720982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ross, Tyler J.","contributorId":171777,"corporation":false,"usgs":false,"family":"Ross","given":"Tyler","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":720983,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192604,"text":"70192604 - 2017 - Remote sensing for wetland mapping and historical change detection at the Nisqually River Delta","interactions":[],"lastModifiedDate":"2017-11-10T18:03:33","indexId":"70192604","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing for wetland mapping and historical change detection at the Nisqually River Delta","docAbstract":"

Coastal wetlands are important ecosystems for carbon storage and coastal resilience to climate change and sea-level rise. As such, changes in wetland habitat types can also impact ecosystem functions. Our goal was to quantify historical vegetation change within the Nisqually River watershed relevant to carbon storage, wildlife habitat, and wetland sustainability, and identify watershed-scale anthropogenic and hydrodynamic drivers of these changes. To achieve this, we produced time-series classifications of habitat, photosynthetic pathway functional types and species in the Nisqually River Delta for the years 1957, 1980, and 2015. Using an object-oriented approach, we performed a hierarchical classification on historical and current imagery to identify change within the watershed and wetland ecosystems. We found a 188.4 ha (79%) increase in emergent marsh wetland within the Nisqually River Delta between 1957 and 2015 as a result of restoration efforts that occurred in several phases through 2009. Despite these wetland gains, a total of 83.1 ha (35%) of marsh was lost between 1957 and 2015, particularly in areas near the Nisqually River mouth due to erosion and shifting river channels, resulting in a net wetland gain of 105.4 ha (44%). We found the trajectory of wetland recovery coincided with previous studies, demonstrating the role of remote sensing for historical wetland change detection as well as future coastal wetland monitoring.

","language":"English","publisher":"MDPI","doi":"10.3390/su9111919","usgsCitation":"Ballanti, L., Byrd, K.B., Woo, I., and Ellings, C., 2017, Remote sensing for wetland mapping and historical change detection at the Nisqually River Delta: Sustainability, v. 9, no. 11, p. 1-32, https://doi.org/10.3390/su9111919.","productDescription":"Article 1919; 32 p.","startPage":"1","endPage":"32","ipdsId":"IP-090392","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":461355,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su9111919","text":"Publisher Index Page"},{"id":438166,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8JN3","text":"USGS data release","linkHelpText":"Historical Time-series Classification of Habitat for 1957, 1980 and 2015 in the Nisqually River Delta, Washington"},{"id":348593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.74440765380858,\n 47.022631553729966\n ],\n [\n -122.66407012939452,\n 47.022631553729966\n ],\n [\n -122.66407012939452,\n 47.11172875008271\n ],\n [\n -122.74440765380858,\n 47.11172875008271\n ],\n [\n -122.74440765380858,\n 47.022631553729966\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-26","publicationStatus":"PW","scienceBaseUri":"5a06c8c7e4b09af898c860f4","contributors":{"authors":[{"text":"Ballanti, Laurel 0000-0002-6478-8322 lballanti@usgs.gov","orcid":"https://orcid.org/0000-0002-6478-8322","contributorId":198603,"corporation":false,"usgs":true,"family":"Ballanti","given":"Laurel","email":"lballanti@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":716528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":716529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":716530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellings, Christopher","contributorId":146989,"corporation":false,"usgs":false,"family":"Ellings","given":"Christopher","affiliations":[{"id":16766,"text":"Nisqually Indian Tribe, Dep't of Natural Resources, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":716531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192497,"text":"70192497 - 2017 - Estimating the high-arsenic domestic-well population in the conterminous United States","interactions":[],"lastModifiedDate":"2017-12-14T16:34:10","indexId":"70192497","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the high-arsenic domestic-well population in the conterminous United States","docAbstract":"

Arsenic concentrations from 20 450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic >10 μg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic >10 μg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration >10 μg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national data sets were used to estimate high arsenic in unsampled areas. Additionally, by predicting to all of the conterminous U.S., we identify areas of high and low potential exposure in areas of limited arsenic data. These areas may be viewed as potential areas to investigate further or to compare to more detailed local information. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells.

","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.7b02881","usgsCitation":"Ayotte, J.D., Medalie, L., Qi, S.L., Backer, L.C., and Nolan, B.T., 2017, Estimating the high-arsenic domestic-well population in the conterminous United States: Environmental Science & Technology, v. 51, no. 21, p. 12443-12454, https://doi.org/10.1021/acs.est.7b02881.","productDescription":"12 p.","startPage":"12443","endPage":"12454","ipdsId":"IP-085175","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":469369,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8842838","text":"Publisher Index Page"},{"id":349554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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movement","interactions":[],"lastModifiedDate":"2017-11-10T11:12:34","indexId":"70192620","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2527,"text":"Journal of the American Statistical Association","active":true,"publicationSubtype":{"id":10}},"title":"Basis function models for animal movement","docAbstract":"

Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01621459.2016.1246250","usgsCitation":"Hooten, M., and Johnson, D., 2017, Basis function models for animal movement: Journal of the American Statistical Association, v. 112, no. 518, p. 578-589, https://doi.org/10.1080/01621459.2016.1246250.","productDescription":"12 p.","startPage":"578","endPage":"589","ipdsId":"IP-072343","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469371,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Basis_Function_Models_for_Animal_Movement/4052175","text":"External Repository"},{"id":348569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"518","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-13","publicationStatus":"PW","scienceBaseUri":"5a06c8c7e4b09af898c860ee","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716569,"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":716570,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193280,"text":"70193280 - 2017 - Drivers and environmental responses to the changing annual snow cycle of northern Alaska","interactions":[],"lastModifiedDate":"2018-01-05T14:18:35","indexId":"70193280","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"Drivers and environmental responses to the changing annual snow cycle of northern Alaska","docAbstract":"

On the North Slope of Alaska, earlier spring snowmelt and later onset of autumn snow accumulation are tied to atmospheric dynamics and sea ice conditions, and result in environmental responses.

Linkages between atmospheric, ecological and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation and cloud cover, as well as the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik due mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-year snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid- 1970s (-2.86 days/decade, 1975-2016). At nearby Cooper Island, where a colony of seabirds, Black Guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-year record. Ice-out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend towards later dates (+4.6 days/decade, 1975-2016), with 2016 the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales, and to anticipate coupled environmental responses.

","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-16-0201.1","usgsCitation":"Cox, C.J., Stone, R.S., Douglas, D.C., Stanitski, D., Divoky, G.J., Dutton, G.S., Sweeney, C., George, J.C., and Longenecker, D.U., 2017, Drivers and environmental responses to the changing annual snow cycle of northern Alaska: Bulletin of the American Meteorological Society, v. 98, p. 2559-2577, https://doi.org/10.1175/BAMS-D-16-0201.1.","productDescription":"29 p.","startPage":"2559","endPage":"2577","ipdsId":"IP-082498","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":348056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.94970703125,\n 68.22052325573338\n ],\n [\n -148.07373046875,\n 68.22052325573338\n ],\n [\n -148.07373046875,\n 71.73266202440855\n ],\n [\n -160.94970703125,\n 71.73266202440855\n ],\n [\n -160.94970703125,\n 68.22052325573338\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd1ee4b0531197b13c65","contributors":{"authors":[{"text":"Cox, Christopher J.","contributorId":199259,"corporation":false,"usgs":false,"family":"Cox","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":718516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Robert S.","contributorId":199260,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":718517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718515,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanitski, Diane","contributorId":199261,"corporation":false,"usgs":false,"family":"Stanitski","given":"Diane","email":"","affiliations":[],"preferred":false,"id":718518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Divoky, George J.","contributorId":100912,"corporation":false,"usgs":false,"family":"Divoky","given":"George","email":"","middleInitial":"J.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":718519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dutton, Geoff S.","contributorId":199262,"corporation":false,"usgs":false,"family":"Dutton","given":"Geoff","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":718520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sweeney, Colm","contributorId":176387,"corporation":false,"usgs":false,"family":"Sweeney","given":"Colm","email":"","affiliations":[],"preferred":false,"id":718521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"George, J. Craig","contributorId":199263,"corporation":false,"usgs":false,"family":"George","given":"J.","email":"","middleInitial":"Craig","affiliations":[],"preferred":false,"id":718522,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Longenecker, David U.","contributorId":199264,"corporation":false,"usgs":false,"family":"Longenecker","given":"David","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":718523,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70193180,"text":"70193180 - 2017 - Concepts: Assessing tiger population dynamics using capture–recapture sampling","interactions":[],"lastModifiedDate":"2017-12-21T09:46:04","indexId":"70193180","displayToPublicDate":"2017-11-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Concepts: Assessing tiger population dynamics using capture–recapture sampling","docAbstract":"Capture-recapture can be viewed as an animal survey method in which the count statistic is the total number of animals caught, and the associated detection probability is the probability of capture.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods for monitoring tiger and prey populations","language":"English","publisher":"Springer","doi":"10.1007/978-981-10-5436-5_9","usgsCitation":"Royle, J., Gopalaswamy, A.M., Dorazio, R., Nichols, J., Jathanna, D., and Parameshwaran, R., 2017, Concepts: Assessing tiger population dynamics using capture–recapture sampling, chap. of Methods for monitoring tiger and prey populations, p. 163-189, https://doi.org/10.1007/978-981-10-5436-5_9.","productDescription":"27 p.","startPage":"163","endPage":"189","ipdsId":"IP-086080","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":349593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-28","publicationStatus":"PW","scienceBaseUri":"5a60fb22e4b06e28e9c22d20","contributors":{"authors":[{"text":"Royle, J. 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