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To estimate the concentrations, loads, and yields of nitrate from groundwater to streams for the Chesapeake Bay watershed, a regression model was developed based on measured nitrate concentrations from 156 small streams with watersheds less than 500 square miles (mi2 ) at baseflow. The regression model has three predictive variables: geologic unit, percent developed land, and percent agricultural land. Comparisons of estimated and actual values within geologic units were closely matched. The coefficient of determination (R2 ) for the model was 0.6906. The model was used to calculate baseflow nitrate concentrations at over 83,000 National Hydrography Dataset Plus Version 2 catchments and aggregated to 1,966 total 12-digit hydrologic units in the Chesapeake Bay watershed. The modeled output geospatial data layers provided estimated annual loads and yields of nitrate from groundwater into streams. The spatial distribution of annual nitrate yields from groundwater estimated by this method was compared to the total watershed yields of all sources estimated from a Chesapeake Bay SPAtially Referenced Regressions On Watershed attributes (SPARROW) water-quality model. The comparison showed similar spatial patterns. The regression model for groundwater contribution had similar but lower yields, suggesting that groundwater is an important source of nitrogen for streams in the Chesapeake Bay watershed.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175160","usgsCitation":"Terziotti, Silvia, Capel, P.D., Tesoriero, A.J., Hopple, J.A., and Kronholm, S.C., 2017, Estimates of nitrate loads and yields from groundwater to streams in the Chesapeake Bay watershed based on land use and geology: U.S. Geological Survey Scientific Investigations Report 2017–5160, 20 p., https://doi.org/10.3133/sir20175160.","productDescription":"Report: iv, 20 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086227","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":352267,"rank":3,"type":{"id":30,"text":"Data 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Division","active":true,"usgs":true}],"preferred":true,"id":724923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":724924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hopple, Jessica A. 0000-0003-3180-2252 jahopple@usgs.gov","orcid":"https://orcid.org/0000-0003-3180-2252","contributorId":198469,"corporation":false,"usgs":true,"family":"Hopple","given":"Jessica","email":"jahopple@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality 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,{"id":70195773,"text":"tm4A11 - 2018 - SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series","interactions":[],"lastModifiedDate":"2018-03-07T15:16:48","indexId":"tm4A11","displayToPublicDate":"2018-03-07T10:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-A11","title":"SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series","docAbstract":"<p>This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Statistical analysis in Book 4: <i>Hydrologic analysis and interpretation</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4A11","collaboration":"Prepared in cooperation with the U.S. Environment Protection Agency","usgsCitation":"Kiang, J.E., Flynn, K.M., Zhai, Tong, Hummel, Paul, and Granato, Gregory, 2018, SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series: U.S. Geological Survey Techniques and Methods, book 4, chap. A–11, 33 p., https://doi.org/10.3133/tm4A11.","productDescription":"Report: vii, 34 p.; Software Download and Release Notes","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-086817","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":352238,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/a11/coverthb.jpg"},{"id":352239,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/a11/tm4a11.pdf","text":"Report","size":"5.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-A11"},{"id":352240,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://water.usgs.gov/osw/swtoolbox/","text":"Software Download and Release Notes","linkHelpText":"- SWToolbox Software Information"}],"publicComments":"This report is Chapter 11 of Section A: Statistical analysis in Book 4: <i>Hydrologic analysis and interpretation</i>.","contact":"<p>Chief, Analysis and Prediction Branch<br> Water Mission Area<br> U.S. Geological Survey<br> 12201 Sunrise Valley Drive, MS 415<br> Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;</li><li>Preface&nbsp;</li><li>Abstract&nbsp;</li><li>Overview</li><li>Statistical Analysis Methods</li><li>Using SWToolbox: Getting Started&nbsp;</li><li>Using SWToolbox: Analysis Menu Tools&nbsp;</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2018-03-07","noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","scienceBaseUri":"5afee70ce4b0da30c1bfc069","contributors":{"authors":[{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":729930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Kate kmflynn@usgs.gov","contributorId":5026,"corporation":false,"usgs":true,"family":"Flynn","given":"Kate","email":"kmflynn@usgs.gov","affiliations":[],"preferred":true,"id":729931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhai, Tong","contributorId":127595,"corporation":false,"usgs":false,"family":"Zhai","given":"Tong","email":"","affiliations":[{"id":7072,"text":"Aqua Terra Consultants","active":true,"usgs":false}],"preferred":false,"id":729933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hummel, Paul","contributorId":202860,"corporation":false,"usgs":false,"family":"Hummel","given":"Paul","affiliations":[{"id":36536,"text":"RESPEC","active":true,"usgs":false}],"preferred":false,"id":729932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Granato, Gregory E. 0000-0002-2561-9913 ggranato@usgs.gov","orcid":"https://orcid.org/0000-0002-2561-9913","contributorId":197631,"corporation":false,"usgs":true,"family":"Granato","given":"Gregory","email":"ggranato@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729934,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70196885,"text":"70196885 - 2018 - Doublethink and scale mismatch polarize policies for an invasive tree","interactions":[],"lastModifiedDate":"2018-05-14T15:27:25","indexId":"70196885","displayToPublicDate":"2018-03-07T00:00:00","publicationYear":"2018","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":"Doublethink and scale mismatch polarize policies for an invasive tree","docAbstract":"<p><span>Mismatches between invasive species management policies and ecological knowledge can lead to profound societal consequences. For this reason, natural resource agencies have adopted the scientifically-based density-impact invasive species curve to guide invasive species management. We use the density-impact model to evaluate how well management policies for a native invader (</span><i>Juniperus virginiana</i><span>) match scientific guidelines.<span>&nbsp;</span></span><i>Juniperus virginiana</i><span><span>&nbsp;</span>invasion is causing a sub-continental regime shift from grasslands to woodlands in central North America, and its impacts span collapses in endemic diversity, heightened wildfire risk, and crashes in grazing land profitability. We (1) use land cover data to identify the stage of<span>&nbsp;</span></span><i>Juniperus virginiana</i><span><span>&nbsp;</span>invasion for three ecoregions within Nebraska, USA, (2) determine the range of invasion stages at individual land parcel extents within each ecoregion based on the density-impact model, and (3) determine policy alignment and mismatches relative to the density-impact model in order to assess their potential to meet sustainability targets and avoid societal impacts as<span>&nbsp;</span></span><i>Juniperus virginiana</i><span><span>&nbsp;</span>abundance increases. We found that nearly all policies evidenced doublethink and policy-ecology mismatches, for instance, promoting spread of<span>&nbsp;</span></span><i>Juniperus virginiana</i><span><span>&nbsp;</span>regardless of invasion stage while simultaneously managing it as a native invader in the same ecoregion. Like other invasive species, theory and literature for this native invader indicate that the consequences of invasion are unlikely to be prevented if policies fail to prioritize management at incipient invasion stages. Theory suggests a more realistic approach would be to align policy with the stage of invasion at local and ecoregion management scales. There is a need for scientists, policy makers, and ecosystem managers to move past ideologies governing native versus non-native invader classification and toward a framework that accounts for the uniqueness of native species invasions, their anthropogenic drivers, and their impacts on ecosystem services.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0189733","usgsCitation":"Roberts, C.P., Uden, D.R., Allen, C.R., and Twidwell, D., 2018, Doublethink and scale mismatch polarize policies for an invasive tree: PLoS ONE, v. 13, no. 3, p. 1-20, https://doi.org/10.1371/journal.pone.0189733.","productDescription":"e0189733; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-092986","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468930,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0189733","text":"Publisher Index Page"},{"id":354145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","volume":"13","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","scienceBaseUri":"5afee70ce4b0da30c1bfc06b","contributors":{"authors":[{"text":"Roberts, Caleb P. 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":197604,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","middleInitial":"P.","affiliations":[],"preferred":false,"id":735230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Twidwell, Dirac","contributorId":187431,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","email":"","affiliations":[],"preferred":false,"id":735232,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195864,"text":"70195864 - 2018 - Environmental conditions synchronize waterbird mortality events in the Great Lakes","interactions":[],"lastModifiedDate":"2023-06-20T16:00:24.022647","indexId":"70195864","displayToPublicDate":"2018-03-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental conditions synchronize waterbird mortality events in the Great Lakes","docAbstract":"<ol id=\"jpe13063-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Since the 1960s, periodic outbreaks of avian botulism type E have contributed to large-scale die-offs of thousands of waterbirds throughout the Great Lakes of the United States. In recent years, these events have become more common and widespread. Occurring during the summer and autumn months, the prevalence of these die-offs varies across years and is often associated with years of warmer lake temperatures and lower water levels. Little information exists on how environmental conditions mediate the spatial and temporal characteristics of mortality events.</li><li>In 2010, a citizen science programme, Avian Monitoring for Botulism Lakeshore Events (AMBLE), was launched to enhance surveillance efforts and detect the appearance of beached waterbird carcasses associated with avian botulism type E outbreaks in northern Lake Michigan. Using these data, our goal was to quantify the within-year characteristics of mortality events for multiple species, and to test whether the synchrony of these events corresponded to fluctuations in two environmental factors suspected to be important in the spread of avian botulism: water temperature and the prevalence of green macroalgae.</li><li>During two separate events of mass waterbird mortality, we found that the detection of bird carcasses was spatially synchronized at scales of<span>&nbsp;</span><i>c</i>. 40&nbsp;km. Notably, the extent of this spatial synchrony in avian mortality matched that of fluctuations in lake surface water temperatures and the prevalence of green macroalgae.</li><li><i>Synthesis and applications</i>. Our findings are suggestive of a synchronizing effect where warmer lake temperatures and the appearance of macroalgae mediate the characteristics of avian mortality. In future years, rising lake temperatures and a higher propensity of algal masses could lead to increases in the magnitude and synchronization of avian mortality due to botulism. We advocate that citizen-based monitoring efforts are critical for identifying the potential environmental conditions associated with widespread mortality events and estimating future risk to waterbird populations.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13063","usgsCitation":"Prince, K., Chipault, J.G., White, C.L., and Zuckerberg, B., 2018, Environmental conditions synchronize waterbird mortality events in the Great Lakes: Journal of Applied Ecology, v. 55, no. 3, p. 1327-1338, https://doi.org/10.1111/1365-2664.13063.","productDescription":"12 p., Data release","startPage":"1327","endPage":"1338","ipdsId":"IP-076304","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":468932,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13063","text":"Publisher Index Page"},{"id":352271,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418242,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72806K3","text":"Environmental conditions synchronize waterbird mortality events in the Great Lakes: Data","description":"Data Release"}],"volume":"55","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-08","publicationStatus":"PW","scienceBaseUri":"5afee70ce4b0da30c1bfc072","contributors":{"authors":[{"text":"Prince, Karine","contributorId":202981,"corporation":false,"usgs":false,"family":"Prince","given":"Karine","email":"","affiliations":[{"id":36568,"text":"Paris-Sorbonne Univeristy","active":true,"usgs":false}],"preferred":false,"id":730358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chipault, Jennifer G. 0000-0002-1368-622X jchipault@usgs.gov","orcid":"https://orcid.org/0000-0002-1368-622X","contributorId":4765,"corporation":false,"usgs":true,"family":"Chipault","given":"Jennifer","email":"jchipault@usgs.gov","middleInitial":"G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":730357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":730359,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zuckerberg, Benjamin","contributorId":200298,"corporation":false,"usgs":false,"family":"Zuckerberg","given":"Benjamin","email":"","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":730360,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70195033,"text":"ofr20181015 - 2018 - Groundwater-level analysis of selected wells in the Hoosic River Valley near Hoosick Falls, New York, for aquifer framework and properties","interactions":[],"lastModifiedDate":"2018-03-05T14:27:58","indexId":"ofr20181015","displayToPublicDate":"2018-03-05T11:30:00","publicationYear":"2018","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":"2018-1015","title":"Groundwater-level analysis of selected wells in the Hoosic River Valley near Hoosick Falls, New York, for aquifer framework and properties","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, analyzed groundwater levels, drilling record logs, and field water-quality data from selected wells, and the surficial geology in the Hoosic River valley south of the village of Hoosick Falls, New York, to provide information about the framework and properties of a confined aquifer. The aquifer, which consists of ice-contact sand and gravel overlain by lacustrine clay and silt, was evaluated by the New York State Department of Environmental Conservation as part of their investigation of alternate water supplies for the village whose wellfield has been affected by perfluorooctanoic acid. Wells inventoried in the study area were classified as confined, water table, or transitional between the two aquifer conditions. Groundwater levels in three confined-aquifer wells and a transitional-aquifer well responded to pumping of a test production well finished in the confined aquifer. Groundwater levels in a water-table well showed no detectable water-level change in response to test-well pumping. Analysis of drawdown and recovery data from the three confined-aquifer wells and a transitional-aquifer well through the application of the Theis type-curve method provided estimates of aquifer properties. Representation of a constant-head boundary in the analysis where an unnamed pond and fluvial-terrace deposits abut the valley wall resulted in satisfactory matches of the Theis type curves with the observed water-level responses. Aquifer transmissivity estimates ranged from 1,160 to 1,370 feet squared per day. Aquifer storativity estimates ranged from 5.2×10<sup>–5</sup> to 1.1×10<sup>–3</sup> and were consistent with the inferred degree of confinement and distance from the represented recharge boundary.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181015","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Williams, J.H., and Heisig, P.M., 2018, Groundwater-level analysis of selected wells in the Hoosic River Valley near Hoosick Falls, New York, for aquifer framework and properties: U.S. Geological Survey Open-File Report 2018–1015, 14 p., https://doi.org/10.3133/ofr20181015. ","productDescription":"v, 14 p.","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092144","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":352081,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1015/ofr20181015.pdf","text":"Report","size":"741 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2018-1015"},{"id":352080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1015/coverthb.jpg"}],"country":"United States","state":"New York","city":"Hoosick Falls","otherGeospatial":"Hoosic River Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.37021827697754,\n              42.870680346240626\n            ],\n            [\n              -73.3417224884033,\n              42.870680346240626\n            ],\n            [\n              -73.3417224884033,\n              42.88961171193983\n            ],\n            [\n              -73.37021827697754,\n              42.88961171193983\n            ],\n            [\n              -73.37021827697754,\n              42.870680346240626\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://ny.water.usgs.gov\" data-mce-href=\"https://ny.water.usgs.gov\">New York Water Science Center</a><br> U.S. Geological Survey<br> 425 Jordan Road<br> Troy, NY 12180–8349</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Well Inventory and Field Water Quality</li><li>Groundwater-Level Data Collection</li><li>Groundwater-Level Analysis for Aquifer Framework</li><li>Groundwater-Level Analysis for Aquifer Properties</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2018-03-05","noUsgsAuthors":false,"publicationDate":"2018-03-05","publicationStatus":"PW","scienceBaseUri":"5afee70de4b0da30c1bfc082","contributors":{"authors":[{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heisig, Paul M. 0000-0003-0338-4970 pmheisig@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-4970","contributorId":793,"corporation":false,"usgs":true,"family":"Heisig","given":"Paul","email":"pmheisig@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":726660,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196799,"text":"70196799 - 2018 - Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes","interactions":[],"lastModifiedDate":"2018-05-01T16:01:37","indexId":"70196799","displayToPublicDate":"2018-03-05T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes","docAbstract":"<p><span>The interannual variability of tidal marsh plant phenology&nbsp;is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided a useful measure of aboveground biomass&nbsp;(r</span><sup>2</sup><span> = 0.72). We then used multiple measures of biomass each&nbsp;growing season<span><span><span>&nbsp;</span>over 20–25 years per study site and developed models to test how peak biomass and the date of peak biomass varied with 94 climate and sea-level metrics using generalized linear models and&nbsp;Akaike Information Criterion (AIC) model selection. Peak biomass was positively related to total annual precipitation, while the best predictor for date of peak biomass was average growing season temperature, with the peak 7.2 days earlier per degree C. Our study provides insight into how plants in maritime tidal marshes respond to interannual climate variation and demonstrates the utility of time-series&nbsp;remote sensing </span>data to assess ecological responses to climate stressors.</span></span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2018.01.006","usgsCitation":"Buffington, K., Dugger, B.D., and Thorne, K., 2018, Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes: Estuarine, Coastal and Shelf Science, v. 202, p. 212-221, https://doi.org/10.1016/j.ecss.2018.01.006.","productDescription":"10 p.","startPage":"212","endPage":"221","ipdsId":"IP-093014","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437990,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18XZR","text":"USGS data release","linkHelpText":"Data for climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes"},{"id":353900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.8486328125,\n              43.068887774169625\n            ],\n            [\n              -122.51953124999999,\n              43.068887774169625\n            ],\n            [\n              -122.51953124999999,\n              47.18971246448421\n            ],\n            [\n              -124.8486328125,\n              47.18971246448421\n            ],\n            [\n              -124.8486328125,\n              43.068887774169625\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"202","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70de4b0da30c1bfc084","contributors":{"authors":[{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugger, Bruce D.","contributorId":176167,"corporation":false,"usgs":false,"family":"Dugger","given":"Bruce","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":734452,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193917,"text":"sir20175139 - 2018 - Collection methods and quality assessment for Escherichia coli, water quality, and microbial source tracking data within Tumacácori National Historical Park and the upper Santa Cruz River, Arizona, 2015-16","interactions":[],"lastModifiedDate":"2018-07-23T08:55:22","indexId":"sir20175139","displayToPublicDate":"2018-03-05T00:00:00","publicationYear":"2018","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":"2017-5139","title":"Collection methods and quality assessment for Escherichia coli, water quality, and microbial source tracking data within Tumacácori National Historical Park and the upper Santa Cruz River, Arizona, 2015-16","docAbstract":"<div><span>Tumacácori National Historical Park protects the culturally important Mission, San José de Tumacácori, while also managing a portion of the ecologically diverse riparian corridor of the Santa Cruz River. This report describes the methods and quality assurance procedures used in the collection of water samples for the analysis of&nbsp;</span><i>Escherichia coli<span>&nbsp;</span></i><span>(</span><i>E. coli</i><span>), microbial source tracking markers, suspended sediment, water-quality parameters, turbidity, and the data collection for discharge and stage; the process for data review and approval is also described. Finally, this report provides a quantitative assessment of the quality of the&nbsp;</span><i>E. coli</i><span>, microbial source tracking, and suspended sediment data.</span></div><div><span><br data-mce-bogus=\"1\"></span></div><div>The data-quality assessment revealed that bias attributed to field and laboratory contamination was minimal, with<span>&nbsp;</span><i>E. coli<span>&nbsp;</span></i>detections in only 3 out of 33 field blank samples analyzed. Concentrations in the field blanks were several orders of magnitude lower than environmental concentrations. The microbial source tracking (MST) field blank was below the detection limit for all MST markers analyzed. Laboratory blanks for<span>&nbsp;</span><i>E. coli<span>&nbsp;</span></i>at the USGS Arizona Water Science Center and laboratory blanks for MST markers at the USGS Ohio Water Microbiology Laboratory were all below the detection limit. Irreplicate data for<span>&nbsp;</span><i>E. coli<span>&nbsp;</span></i>and suspended sediment indicated that bias was not introduced to the data by combining samples collected using discrete sampling methods with samples collected using automatic sampling methods.</div><div><br data-mce-bogus=\"1\"></div><div>The split and sequential<span>&nbsp;</span><i>E. coli<span>&nbsp;</span></i>replicate data showed consistent analytical variability and a single equation was developed to explain the variability of<span>&nbsp;</span><i>E. coli<span>&nbsp;</span></i>concentrations. An additional analysis of analytical variability for<span>&nbsp;</span><i>E. coli<span>&nbsp;</span></i>indicated analytical variability around 18 percent relative standard deviation and no trend was observed in the concentration during the processing and analysis of multiple split-replicates. Two replicate samples were collected for MST and individual markers were compared for a base flow and flood sample. For the markers found in common between the two types of samples, the relative standard deviation for the base flow sample was more than 3 times greater than the markers in the flood sample. Sequential suspended sediment replicates had a relative standard deviation of about 1.3 percent, indicating that environmental and analytical variability was minimal.</div><div><br data-mce-bogus=\"1\"></div><div>A holding time review and laboratory study analysis supported the extended holding times required for this investigation. Most concentrations for flood and base-flow samples were within the theoretical variability specified in the most probable number approach suggesting that extended hold times did not overly influence the final concentrations reported.</div><div><br></div>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175139","collaboration":"Prepared in cooperation with the National Park Service, Tumacácori National Historical Park","usgsCitation":"Paretti, N.V., Coes, A.L., Kephart, C.M., and Mayo, J.P., 2018, Collection methods and quality assessment for Escherichia coli, water quality, and microbial source tracking data within Tumacácori National Historical Park and the upper Santa Cruz River, Arizona, 2015-16: U.S. Geological Survey, Scientific Investigations Report 2017–5139, 30 p., https://doi.org/10.3133/sir20175139.","productDescription":"viii, 30 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-090526","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":352219,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5139/coverthb.jpg"},{"id":352220,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5139/sir20175139_.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5139"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper Santa Cruz River, Tumacácori National Historical Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.1,\n              31.25\n            ],\n            [\n              -110.75,\n              31.25\n            ],\n            [\n              -110.75,\n              31.67\n            ],\n            [\n              -111.1,\n              31.67\n            ],\n            [\n              -111.1,\n              31.25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>,<br><a href=\"http://az.water.usgs.gov/\" data-mce-href=\"http://az.water.usgs.gov/\">Arizona Water Science Center</a><br><a href=\"http://usgs.gov/\" data-mce-href=\"http://usgs.gov/\">U.S. Geological Survey</a><br>520 N. Park Avenue<br>Tucson, AZ 85719<br></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Methods<br></li><li>Data-Quality Assessment<br></li><li>Summary<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2018-03-05","noUsgsAuthors":false,"publicationDate":"2018-03-05","publicationStatus":"PW","scienceBaseUri":"5afee70de4b0da30c1bfc086","contributors":{"authors":[{"text":"Paretti, Nicholas V. 0000-0003-2178-4820 nparetti@usgs.gov","orcid":"https://orcid.org/0000-0003-2178-4820","contributorId":173412,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas","email":"nparetti@usgs.gov","middleInitial":"V.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":721470,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coes, Alissa L. 0000-0001-6682-5417 alcoes@usgs.gov","orcid":"https://orcid.org/0000-0001-6682-5417","contributorId":4231,"corporation":false,"usgs":true,"family":"Coes","given":"Alissa","email":"alcoes@usgs.gov","middleInitial":"L.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":721471,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kephart, Christopher M. 0000-0002-3369-5596 ckephart@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-5596","contributorId":1932,"corporation":false,"usgs":true,"family":"Kephart","given":"Christopher","email":"ckephart@usgs.gov","middleInitial":"M.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":721472,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayo, Justine P. 0000-0002-2684-5031 jmayo@usgs.gov","orcid":"https://orcid.org/0000-0002-2684-5031","contributorId":197035,"corporation":false,"usgs":true,"family":"Mayo","given":"Justine","email":"jmayo@usgs.gov","middleInitial":"P.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":721473,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70265020,"text":"70265020 - 2018 - Performance metrics for the assessment of satellite data products: An ocean color case study","interactions":[],"lastModifiedDate":"2025-03-28T14:10:39.577867","indexId":"70265020","displayToPublicDate":"2018-03-04T09:08:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5953,"text":"Optics Express","active":true,"publicationSubtype":{"id":10}},"title":"Performance metrics for the assessment of satellite data products: An ocean color case study","docAbstract":"<p><span>Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r</span><sup>2</sup><span>), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multi-metric and user-dependent approach that can be applied within science, modeling, and resource management communities.</span></p>","language":"English","publisher":"Optica Publishing Group","doi":"10.1364/OE.26.007404","usgsCitation":"Seegers, B.N., Stumpf, R., Schaeffer, B., Loftin, K.A., and Werdell, P., 2018, Performance metrics for the assessment of satellite data products: An ocean color case study: Optics Express, v. 26, no. 6, p. 7404-7422, https://doi.org/10.1364/OE.26.007404.","productDescription":"19 p.","startPage":"7404","endPage":"7422","ipdsId":"IP-093210","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":488729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1364/oe.26.007404","text":"Publisher Index Page"},{"id":483985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Seegers, Bridget N.","contributorId":334288,"corporation":false,"usgs":false,"family":"Seegers","given":"Bridget","email":"","middleInitial":"N.","affiliations":[{"id":80107,"text":"Morgan State University, National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":932328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stumpf, Richard P.","contributorId":193799,"corporation":false,"usgs":false,"family":"Stumpf","given":"Richard P.","affiliations":[],"preferred":false,"id":932329,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaeffer, Blake A.","contributorId":334287,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake A.","affiliations":[{"id":35215,"text":"Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":932330,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":932331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Werdell, P. Jeremy","contributorId":269868,"corporation":false,"usgs":false,"family":"Werdell","given":"P. Jeremy","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":932332,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70195813,"text":"70195813 - 2018 - Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation","interactions":[],"lastModifiedDate":"2018-03-02T16:06:47","indexId":"70195813","displayToPublicDate":"2018-03-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling intrinsic potential for beaver (<i>Castor canadensis</i>) habitat to inform restoration and climate change adaptation","title":"Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation","docAbstract":"<p><span>Through their dam-building activities and subsequent water storage, beaver have the potential to restore riparian ecosystems and offset some of the predicted effects of climate change by modulating streamflow. Thus, it is not surprising that reintroducing beaver to watersheds from which they have been extirpated is an often-used restoration and climate-adaptation strategy. Identifying sites for reintroduction, however, requires detailed information about habitat factors—information that is not often available at broad spatial scales. Here we explore the potential for beaver relocation throughout the Snohomish River Basin in Washington, USA with a model that identifies some of the basic building blocks of beaver habitat suitability and does so by relying solely on remotely sensed data. More specifically, we developed a generalized intrinsic potential model that draws on remotely sensed measures of stream gradient, stream width, and valley width to identify where beaver could become established if suitable vegetation were to be present. Thus, the model serves as a preliminary screening tool that can be applied over relatively large extents. We applied the model to 5,019 stream km and assessed the ability of the model to correctly predict beaver habitat by surveying for beavers in 352 stream reaches. To further assess the potential for relocation, we assessed land ownership, use, and land cover in the landscape surrounding stream reaches with varying levels of intrinsic potential. Model results showed that 33% of streams had moderate or high intrinsic potential for beaver habitat. We found that no site that was classified as having low intrinsic potential had any sign of beavers and that beaver were absent from nearly three quarters of potentially suitable sites, indicating that there are factors preventing the local population from occupying these areas. Of the riparian areas around streams with high intrinsic potential for beaver, 38% are on public lands and 17% are on large tracts of privately-owned timber land. Thus, although there are a large number of areas that could be suitable for relocation and restoration using beavers, current land use patterns may substantially limit feasibility in these areas.</span></p>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0192538","usgsCitation":"Dittbrenner, B.J., Pollack, M.M., Schilling, J.W., Olden, J., Lawler, J.J., and Torgersen, C.E., 2018, Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation: PLoS ONE, v. 13, no. 2, e0192538; 15 p., https://doi.org/10.1371/journal.pone.0192538.","productDescription":"e0192538; 15 p.","ipdsId":"IP-093284","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0192538","text":"Publisher Index Page"},{"id":352193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Snohomish River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.37945556640624,\n              47.372314620566925\n            ],\n            [\n              -120.9979248046875,\n              47.372314620566925\n            ],\n            [\n              -120.9979248046875,\n              48.08908799881762\n            ],\n            [\n              -122.37945556640624,\n              48.08908799881762\n            ],\n            [\n              -122.37945556640624,\n              47.372314620566925\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee70ee4b0da30c1bfc088","contributors":{"authors":[{"text":"Dittbrenner, Benjamin J.","contributorId":202890,"corporation":false,"usgs":false,"family":"Dittbrenner","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":730022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollack, Michael M.","contributorId":202891,"corporation":false,"usgs":false,"family":"Pollack","given":"Michael","email":"","middleInitial":"M.","affiliations":[{"id":36546,"text":"National Oceanic and Atmospheric Administration – Northwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":730023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schilling, Jason W.","contributorId":202892,"corporation":false,"usgs":false,"family":"Schilling","given":"Jason","email":"","middleInitial":"W.","affiliations":[{"id":36547,"text":"Tulalip Tribes Natural Resources","active":true,"usgs":false}],"preferred":false,"id":730024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":730025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":730026,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":730021,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70201617,"text":"70201617 - 2018 - Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America","interactions":[],"lastModifiedDate":"2018-12-18T15:53:14","indexId":"70201617","displayToPublicDate":"2018-03-01T15:53:23","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America","docAbstract":"<p><span>Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59&nbsp;±&nbsp;12% (± 2 standard errors) of the carbon entering is from rivers and 41&nbsp;±&nbsp;12% is from the atmosphere, while 80&nbsp;±&nbsp;9% of the carbon leaving is exported to the open ocean and 20&nbsp;±&nbsp;9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO</span><sub>2</sub><span>uptake split evenly between tidal wetlands and shelf waters, and estuarine CO</span><sub>2</sub><span>outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2017GB005790","usgsCitation":"Najjar, R., Herrmann, M., Alexander, R.B., Boyer, E., Burdige, D., Butman, D., Cai, W., Canuel, E., Chen, R., Friedrichs, M.A., Feagin, R., Griffith, P.C., Hinson, A., Holmquist, J., Hu, X., Kemp, W., Kroeger, K.D., Mannino, A., McCallister, S., McGillis, W., Mulholland, M., Pilskaln, C.H., Salisbury, J., Signorini, S., St. Laurent, P., Tian, H., Tzortziou, M., Vlahos, P., Wan, Z., and Zimmerman, R.C., 2018, Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America: Global Biogeochemical Cycles, v. 32, no. 3, p. 389-416, https://doi.org/10.1002/2017GB005790.","productDescription":"28 p.","startPage":"389","endPage":"416","ipdsId":"IP-092980","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468939,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/2017gb005790","text":"External Repository"},{"id":360518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"32","issue":"3","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","scienceBaseUri":"5c1a1534e4b0708288c23542","contributors":{"authors":[{"text":"Najjar, R.G.","contributorId":211647,"corporation":false,"usgs":false,"family":"Najjar","given":"R.G.","affiliations":[{"id":38295,"text":"Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania, USA.","active":true,"usgs":false}],"preferred":false,"id":754585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herrmann, M.","contributorId":211648,"corporation":false,"usgs":false,"family":"Herrmann","given":"M.","email":"","affiliations":[{"id":38295,"text":"Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania, USA.","active":true,"usgs":false}],"preferred":false,"id":754586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Richard B. 0000-0001-9166-0626 ralex@usgs.gov","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":541,"corporation":false,"usgs":true,"family":"Alexander","given":"Richard","email":"ralex@usgs.gov","middleInitial":"B.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":754587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyer, E.W.","contributorId":56358,"corporation":false,"usgs":false,"family":"Boyer","given":"E.W.","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":754588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burdige, D. J.","contributorId":211649,"corporation":false,"usgs":true,"family":"Burdige","given":"D. 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However, the relative importance of intrinsic versus extrinsic factors remains elusive. We analyze a global dataset of ∼2.8 million locations from &gt;2,600 tracked individuals across 50 marine vertebrates evolutionarily separated by millions of years and using different locomotion modes (fly, swim, walk/paddle). Strikingly, movement patterns show a remarkable convergence, being strongly conserved across species and independent of body length and mass, despite these traits ranging over 10 orders of magnitude among the species studied. This represents a fundamental difference between marine and terrestrial vertebrates not previously identified, likely linked to the reduced costs of locomotion in water. Movement patterns were primarily explained by the interaction between species-specific traits and the habitat(s) they move through, resulting in complex movement patterns when moving close to coasts compared with more predictable patterns when moving in open oceans. This distinct difference may be associated with greater complexity within coastal microhabitats, highlighting a critical role of preferred habitat in shaping marine vertebrate global movements. Efforts to develop understanding of the characteristics of vertebrate movement should consider the habitat(s) through which they move to identify how movement patterns will alter with forecasted severe ocean changes, such as reduced Arctic sea ice cover, sea level rise, and declining oxygen content.</span></p>","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1716137115","usgsCitation":"Sequeira, A., Rodriguez, J., Eguíluz, V., Harcourt, R., Hindell, M., Sims, D., Duarte, C., Costa, D., Fernandez-Gracia, J., Ferreira, L., Hays, G., Heupel, M., Meekan, M., Aven, A., Bailleul, F., Baylis, A.M., Berumen, M.L., Braun, C.D., Burns, J., Caley, M., Campbell, R., Carmichael, R., Clua, E., Einoder, L.D., Friedlaender, A., Goebel, M.E., Goldsworthy, S., Guinet, C., Gunn, J., Hamer, D., Hammerschlag, N., Hammill, M., Hückstädt, L., Humphries, N., Lea, M., Lowther, A., Mackay, A., McHuron, E., Mckenzie, J., McLeay, L., McMahon, C., Mengersen, K., Muelbert, M.M., Pagano, A.M., Page, B., Queiroz, N., Robinson, P.W., Shaffer, S.A., Shivji, M., Skomal, G., Thorrold, S., Villegas-Amtmann, S., Weise, M., Wells, R., Wetherbee, B., Wiebkin, A., Wienecke, B., and Thums, M., 2018, Convergence of marine megafauna movement patterns in coastal and open oceans: Proceedings of the National Academy of Sciences, v. 115, no. 12, p. 3072-3077, https://doi.org/10.1073/pnas.1716137115.","productDescription":"6 p.","startPage":"3072","endPage":"3077","ipdsId":"IP-089008","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":468941,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1716137115","text":"Publisher Index Page"},{"id":437992,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RV0MK4","text":"USGS data release","linkHelpText":"Locations Collected 1985-2015 from Female Polar Bears (Ursus maritimus) with Dependent Young Instrumented in the Southern Beaufort Sea with Satellite-linked Transmitters by the USGS"},{"id":357121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-26","publicationStatus":"PW","scienceBaseUri":"5b98a2eae4b0702d0e84300e","contributors":{"authors":[{"text":"Sequeira, A. 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C.","affiliations":[{"id":18107,"text":"Sydney Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":744442,"contributorType":{"id":1,"text":"Authors"},"rank":43},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":744400,"contributorType":{"id":1,"text":"Authors"},"rank":44},{"text":"Page, B.","contributorId":207686,"corporation":false,"usgs":false,"family":"Page","given":"B.","email":"","affiliations":[{"id":37598,"text":"South Australian Research and Development Institute","active":true,"usgs":false}],"preferred":false,"id":744443,"contributorType":{"id":1,"text":"Authors"},"rank":45},{"text":"Queiroz, N.","contributorId":207687,"corporation":false,"usgs":false,"family":"Queiroz","given":"N.","affiliations":[{"id":37595,"text":"Marine Biological Association of the United Kingdom","active":true,"usgs":false}],"preferred":false,"id":744444,"contributorType":{"id":1,"text":"Authors"},"rank":46},{"text":"Robinson, P. W.","contributorId":207723,"corporation":false,"usgs":false,"family":"Robinson","given":"P.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":744445,"contributorType":{"id":1,"text":"Authors"},"rank":47},{"text":"Shaffer, S. A.","contributorId":207689,"corporation":false,"usgs":false,"family":"Shaffer","given":"S.","email":"","middleInitial":"A.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":744446,"contributorType":{"id":1,"text":"Authors"},"rank":48},{"text":"Shivji, M.","contributorId":207690,"corporation":false,"usgs":false,"family":"Shivji","given":"M.","email":"","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":744447,"contributorType":{"id":1,"text":"Authors"},"rank":49},{"text":"Skomal, G. B.","contributorId":207676,"corporation":false,"usgs":false,"family":"Skomal","given":"G. B.","affiliations":[{"id":37606,"text":"Massachusetts Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":744433,"contributorType":{"id":1,"text":"Authors"},"rank":50},{"text":"Thorrold, S.","contributorId":207691,"corporation":false,"usgs":false,"family":"Thorrold","given":"S.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":744448,"contributorType":{"id":1,"text":"Authors"},"rank":51},{"text":"Villegas-Amtmann, S.","contributorId":207692,"corporation":false,"usgs":false,"family":"Villegas-Amtmann","given":"S.","email":"","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":744449,"contributorType":{"id":1,"text":"Authors"},"rank":52},{"text":"Weise, M.","contributorId":147175,"corporation":false,"usgs":false,"family":"Weise","given":"M.","email":"","affiliations":[],"preferred":false,"id":744450,"contributorType":{"id":1,"text":"Authors"},"rank":53},{"text":"Wells, R.","contributorId":40403,"corporation":false,"usgs":true,"family":"Wells","given":"R.","affiliations":[],"preferred":false,"id":744451,"contributorType":{"id":1,"text":"Authors"},"rank":54},{"text":"Wetherbee, B.","contributorId":207693,"corporation":false,"usgs":false,"family":"Wetherbee","given":"B.","email":"","affiliations":[{"id":37608,"text":"Australian Antarctic Division","active":true,"usgs":false}],"preferred":false,"id":744452,"contributorType":{"id":1,"text":"Authors"},"rank":55},{"text":"Wiebkin, A.","contributorId":207694,"corporation":false,"usgs":false,"family":"Wiebkin","given":"A.","email":"","affiliations":[{"id":37598,"text":"South Australian Research and Development Institute","active":true,"usgs":false}],"preferred":false,"id":744453,"contributorType":{"id":1,"text":"Authors"},"rank":56},{"text":"Wienecke, B.","contributorId":207695,"corporation":false,"usgs":false,"family":"Wienecke","given":"B.","email":"","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":744454,"contributorType":{"id":1,"text":"Authors"},"rank":57},{"text":"Thums, M.","contributorId":207696,"corporation":false,"usgs":false,"family":"Thums","given":"M.","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":744455,"contributorType":{"id":1,"text":"Authors"},"rank":58}]}}
,{"id":70198481,"text":"70198481 - 2018 - A phylogenetic overview of the genus Vertigo O. F. Müller, 1773 (Gastropoda: Pulmonata: Pupillidae: Vertigininae)","interactions":[],"lastModifiedDate":"2018-08-06T12:41:18","indexId":"70198481","displayToPublicDate":"2018-03-01T12:41:11","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2648,"text":"Malacologia","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A phylogenetic overview of the genus <i>Vertigo</i> O. F. Müller, 1773 (Gastropoda: Pulmonata: Pupillidae: Vertigininae)","title":"A phylogenetic overview of the genus Vertigo O. F. Müller, 1773 (Gastropoda: Pulmonata: Pupillidae: Vertigininae)","docAbstract":"<p><span>We document global phylogenetic pattern in the pupillid land snail genus&nbsp;</span><i>Vertigo</i><span>&nbsp;by analyses of nDNA (ITS1 and ITS2) and mtDNA (CytB and 16S) sequence from 424 individuals representing 91 putative specific and subspecific&nbsp;</span><i>Vertigo</i><span>&nbsp;taxa. nDNA and mtDNA data were separately subjected to neighbor-joining, minimum evolution, maximum likelihood and Bayesian reconstruction methods, with conclusions being drawn from shared topological structures. Six highly supported, reciprocally monophyletic subgeneric level clades were identified:&nbsp;</span><i>Vertigo</i><span>,&nbsp;</span><i>Alaea</i><span>,&nbsp;</span><strong><i>Boreovertigo</i></strong><span>&nbsp;new subgenus,&nbsp;</span><i>Isthmia</i><span>,&nbsp;</span><i>Staurodon</i><span>&nbsp;and&nbsp;</span><i>Vertilla</i><span>. 88 species or subspecies were also confirmed, nine of which are new and formally described herein:&nbsp;</span><strong><i>V. beringiana</i></strong><span>,&nbsp;</span><strong><i>V. chiricahuensis</i></strong><span>,&nbsp;</span><strong><i>V. chytryi</i></strong><span>,&nbsp;</span><strong><i>V. genesioides</i></strong><span>,&nbsp;</span><strong><i>V. kodamai</i></strong><span>,&nbsp;</span><strong><i>V. kurilensis</i></strong><span>,&nbsp;</span><strong><i>V. lilljeborgi vinlandica</i></strong><span>,&nbsp;</span><strong><i>V. pimuensis</i></strong><span>&nbsp;and&nbsp;</span><strong><i>V. pisewensis</i></strong><span>. Thirteen taxa were synonymized:&nbsp;</span><i>V. arthuri basidens</i><span>,&nbsp;</span><i>V. arthuri hubrichti</i><span>,&nbsp;</span><i>V. arthuri paradoxa</i><span>&nbsp;(=&nbsp;</span><i>V. arthuri</i><span>);&nbsp;</span><i>V. allyniana</i><span>(=&nbsp;</span><i>V. modesta</i><span>);&nbsp;</span><i>V. andrusiana</i><span>&nbsp;(=&nbsp;</span><i>V. columbiana</i><span>);&nbsp;</span><i>V. conecuhensis</i><span>&nbsp;(=&nbsp;</span><i>V. alabamensis</i><span>);&nbsp;</span><i>V. dedecora tamagonari</i><span>&nbsp;(=&nbsp;</span><i>V. dedecora</i><span>);&nbsp;</span><i>V. elatior</i><span>,&nbsp;</span><i>V. idahoensis</i><span>&nbsp;(=&nbsp;</span><i>V. ventricosa</i><span>);&nbsp;</span><i>V. eogea</i><span>&nbsp;(=&nbsp;</span><i>V. ovata</i><span>);&nbsp;</span><i>V. modesta insculpta</i><span>&nbsp;(=&nbsp;</span><i>V. modesta concinnula</i><span>),&nbsp;</span><i>V. modesta microphasma</i><span>,&nbsp;</span><i>V. modesta sculptilis</i><span>&nbsp;(=&nbsp;</span><i>V. modesta castanea</i><span>). Qualitative observations of conchological features, ecological preferences and geographic coverage were conducted for each subgenus and genetically supported species or subspecies-level taxon. These demonstrated that: (1) a suite of diagnostic shell features usually exists to demarcate each species-level taxon; (2) shell features were incapable of defining genetically validated subgenera; (3) all subgenera had transcontinental ranges; (4) ⅓ of all species possess continental or trans-continental ranges, with very few having range extents &lt; 1,000 km; (5) all subgenera and fully ⅔ of global&nbsp;</span><i>Vertigo</i><span>&nbsp;species and subspecies are found in North America, more than 2.5 times the number found in central and eastern Asia, the second most diverse region. This is similar to several other molluscan groups, such as the polygyrid land snails and unionid bivalves for which North America is the global biodiversity hotspot.</span></p>","language":"English","publisher":"Institute of Malacology","doi":"10.4002/040.062.0104","usgsCitation":"Nekola, J.C., Chiba, S., Coles, B.F., Drost, C.A., von Proschwitz, T., and Horsak, M., 2018, A phylogenetic overview of the genus Vertigo O. F. Müller, 1773 (Gastropoda: Pulmonata: Pupillidae: Vertigininae): Malacologia, v. 62, no. 1, p. 21-161, https://doi.org/10.4002/040.062.0104.","productDescription":"141 p.","startPage":"21","endPage":"161","ipdsId":"IP-081461","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":356193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc483e4b0f5d57878ea98","contributors":{"authors":[{"text":"Nekola, Jeffrey C.","contributorId":26214,"corporation":false,"usgs":false,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":741710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chiba, Satoshi","contributorId":206770,"corporation":false,"usgs":false,"family":"Chiba","given":"Satoshi","email":"","affiliations":[],"preferred":false,"id":741711,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coles, Brian F.","contributorId":206771,"corporation":false,"usgs":false,"family":"Coles","given":"Brian","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":741712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":741713,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"von Proschwitz, Ted","contributorId":206772,"corporation":false,"usgs":false,"family":"von Proschwitz","given":"Ted","email":"","affiliations":[],"preferred":false,"id":741714,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Horsak, Michal","contributorId":206773,"corporation":false,"usgs":false,"family":"Horsak","given":"Michal","email":"","affiliations":[],"preferred":false,"id":741715,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70236613,"text":"70236613 - 2018 - Application of imaging spectroscopy for mineral exploration in Alaska: A study over porphyry Cu deposits in the eastern Alaska Range","interactions":[],"lastModifiedDate":"2022-09-13T11:58:59.256404","indexId":"70236613","displayToPublicDate":"2018-03-01T06:50:06","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Application of imaging spectroscopy for mineral exploration in Alaska: A study over porphyry Cu deposits in the eastern Alaska Range","docAbstract":"<div id=\"114214517\" class=\"article-section-wrapper js-article-section js-content-section  \"><p>The U.S. Geological Survey tested the utility of imaging spectroscopy (also referred to as hyperspectral remote sensing) as an aid to regional mineral exploration efforts in remote parts of Alaska. Airborne imaging spectrometer data were collected in 2014 over unmined porphyry Cu deposits in the eastern Alaska Range using the HyMap™ sensor. Maps of the distributions of predominant minerals, made by matching reflectance signatures in the remotely sensed data to reference spectra in the shortwave infrared region, do not uniquely discriminate individual rock units. However, they do highlight hydrothermal alteration associated with porphyry deposits and prospects hosted mostly within the Nabesna pluton. In and around porphyry Cu deposits at Orange Hill and Bond Creek, unique spectral signatures are related to variations in chlorite and white mica abundance and their chemical composition. This is best revealed in the longer-wavelength 2,200-nm Al-OH absorption feature positions in pixels spectrally dominated by white mica proximal to porphyry deposits. Similar spectral signatures of chlorite and white mica wavelength positions were also recognized away from the porphyry deposits; follow-up sampling identified these satellite areas to also contain Cu-Mo-Au mineralized rock. Our study confirms that airborne imaging spectroscopy has application for regional mineral exploration in exposed mountainous terrain in Alaska.</p></div>","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.2018.4559","usgsCitation":"Graham, G.E., Kokaly, R.F., Kelley, K.D., Hoefen, T.M., Johnson, M., and Hubbard, B.E., 2018, Application of imaging spectroscopy for mineral exploration in Alaska: A study over porphyry Cu deposits in the eastern Alaska Range: Economic Geology, v. 113, no. 2, p. 489.-510, https://doi.org/10.5382/econgeo.2018.4559.","productDescription":"22 p.","startPage":"489.","endPage":"510","ipdsId":"IP-087274","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":468946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5382/econgeo.2018.4559","text":"Publisher Index Page"},{"id":406586,"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              -155.7421875,\n              57.7041472343419\n            ],\n            [\n              -140.5810546875,\n              57.7041472343419\n            ],\n            [\n              -140.5810546875,\n              65.38514722188857\n            ],\n            [\n              -155.7421875,\n              65.38514722188857\n            ],\n            [\n              -155.7421875,\n              57.7041472343419\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"113","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":851501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":851502,"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":851503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","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":true,"id":851504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Michaela 0000-0001-6133-0247 mrjohns@usgs.gov","orcid":"https://orcid.org/0000-0001-6133-0247","contributorId":182462,"corporation":false,"usgs":true,"family":"Johnson","given":"Michaela","email":"mrjohns@usgs.gov","affiliations":[],"preferred":true,"id":851505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hubbard, Bernard E. 0000-0002-9315-2032","orcid":"https://orcid.org/0000-0002-9315-2032","contributorId":213146,"corporation":false,"usgs":true,"family":"Hubbard","given":"Bernard","email":"","middleInitial":"E.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":851506,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70193270,"text":"70193270 - 2018 - Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations","interactions":[],"lastModifiedDate":"2018-03-28T15:17:43","indexId":"70193270","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3544,"text":"The Auk","onlineIssn":"1938-4254","printIssn":"0004-8038","active":true,"publicationSubtype":{"id":10}},"title":"Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations","docAbstract":"<p><span>Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken (</span><i>Tympanuchus pallidicinctus</i><span>) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.</span></p>","language":"English","publisher":"American Ornithological Society","doi":"10.1642/AUK-17-113.1","usgsCitation":"Ross, B., Haukos, D.A., Hagen, C.A., and Pitman, J., 2018, Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations: The Auk, v. 135, no. 2, p. 228-239, https://doi.org/10.1642/AUK-17-113.1.","productDescription":"12 p.","startPage":"228","endPage":"239","ipdsId":"IP-077342","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":352873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee713e4b0da30c1bfc0da","contributors":{"authors":[{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":731942,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagen, Christian A.","contributorId":177795,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":731943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitman, James","contributorId":176512,"corporation":false,"usgs":false,"family":"Pitman","given":"James","affiliations":[],"preferred":false,"id":731944,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70196225,"text":"70196225 - 2018 - Stability and change in kelp forest habitats at San Nicolas Island","interactions":[],"lastModifiedDate":"2020-12-16T16:29:35.001376","indexId":"70196225","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Stability and change in kelp forest habitats at San Nicolas Island","docAbstract":"<p><span>Kelp forest communities are highly variable over space and time. Despite this complexity it has been suggested that kelp forest communities can be classified into one of 2 states: kelp dominated or sea urchin dominated. It has been further hypothesized that these represent “alternate stable states” because a site can remain in either of these states for decades before some perturbation causes a rapid shift to the other state. Our research group has maintained a subtidal community monitoring program for 38 years at San Nicolas Island consisting of twice-annual scuba-based surveys at 6 sites distributed within 4 regions around the island. Three types of perturbations are thought to be relevant to subtidal community dynamics at San Nicolas: (1) physical disturbances in the form of major storm and El Niño/Southern Oscillation (ENSO) events; (2) invertebrate diseases, which periodically decimate urchin populations; and (3) the reintroduction and subsequent increase of sea otters (</span><i>Enhydra lutris nereis</i><span>). These 3 perturbations differ in spatial and temporal specificity; physical disturbances and disease outbreaks occur periodically and could affect all 4 regions, while sea otter predation has been concentrated primarily at the West End sites over the last 15 years. The different types of perturbations and the duration of the time series at the kelp forests at San Nicolas make the data set ideal for testing the “alternate stable state” hypothesis. We use nonmetric multidimensional scaling (NMDS) to examine spatial and temporal patterns of community similarity at the 4 regions. In particular, we evaluate support for the existence of stable states, which are represented on NMDS plots as distinct spatial clusters. Community dynamics at each site approximated a biased random walk in NMDS space, with one or more basins of attraction and occasional jumps between basins. We found evidence for alternative stable states at some sites, and we show that transitions from one stable state to another may be influenced by interactions between multiple perturbations.</span></p>","language":"English","publisher":"Western North American Naturalist Publications","doi":"10.3398/064.078.0407","usgsCitation":"Kenner, M.C., and Tinker, M.T., 2018, Stability and change in kelp forest habitats at San Nicolas Island: Western North American Naturalist, v. 78, no. 4, p. 633-643, https://doi.org/10.3398/064.078.0407.","productDescription":"11 p.","startPage":"633","endPage":"643","ipdsId":"IP-086463","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":488846,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol78/iss4/14","text":"External Repository"},{"id":352844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -119.58824157714842,\n              33.20881849225547\n            ],\n            [\n              -119.42893981933592,\n              33.20881849225547\n            ],\n            [\n              -119.42893981933592,\n              33.289785856885224\n            ],\n            [\n              -119.58824157714842,\n              33.289785856885224\n            ],\n            [\n              -119.58824157714842,\n              33.20881849225547\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"78","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee710e4b0da30c1bfc0b6","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":203543,"corporation":false,"usgs":false,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":731747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tinker, M. Tim 0000-0002-3314-839X ttinker@usgs.gov","orcid":"https://orcid.org/0000-0002-3314-839X","contributorId":2796,"corporation":false,"usgs":true,"family":"Tinker","given":"M.","email":"ttinker@usgs.gov","middleInitial":"Tim","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70195819,"text":"70195819 - 2018 - Species distribution modeling in regions of high need and limited data: waterfowl of China","interactions":[],"lastModifiedDate":"2018-03-05T10:59:14","indexId":"70195819","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5641,"text":"Avian Research","active":true,"publicationSubtype":{"id":10}},"title":"Species distribution modeling in regions of high need and limited data: waterfowl of China","docAbstract":"<div id=\"ASec1\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Background</strong></p><p id=\"Par1\" class=\"Para\">A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources. Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China.</p></div><div id=\"ASec2\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Methods</strong></p><p id=\"Par2\" class=\"Para\">Faced with limited data, we built species distribution models using a habitat suitability approach for China’s breeding and non-breeding (hereafter, wintering) waterfowl. An extensive review of the literature was used to determine model parameters for habitat modeling. Habitat relationships were implemented in GIS using land cover covariates. Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available.</p></div><div id=\"ASec3\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Results</strong></p><p id=\"Par3\" class=\"Para\">We developed suitability models for 42 waterfowl species (30 breeding and 39 wintering) at 1&nbsp;km resolution for the extent of China, along with cumulative and genus level species richness maps. Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China. Wintering waterfowl suitability was highest in the lowland regions of southeastern China. Validation measures indicated strong performance in predicting species presence. Comparing our model outputs to China’s protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized.</p></div><div id=\"ASec4\" class=\"AbstractSection\"><p class=\"Heading\"><strong>Conclusions</strong></p><p id=\"Par4\" class=\"Para\">These suitability models are the first available for many of China’s waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically important areas, providing an example of how this approach may aid others faced with the challenge of addressing conservation issues with little data to inform decision making.</p></div>","language":"English","publisher":"BMC","doi":"10.1186/s40657-018-0099-4","usgsCitation":"Prosser, D.J., Ding, C., Erwin, R.M., Mundkur, T., Sullivan, J.D., and Ellis, E.C., 2018, Species distribution modeling in regions of high need and limited data: waterfowl of China: Avian Research, v. 9, p. 1-14, https://doi.org/10.1186/s40657-018-0099-4.","productDescription":"Article 7; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-080933","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468961,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40657-018-0099-4","text":"Publisher Index Page"},{"id":437996,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P904APIK","text":"USGS data release","linkHelpText":"Species distribution models from a habitat suitability approach: waterfowl of China"},{"id":352210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","volume":"9","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-05","publicationStatus":"PW","scienceBaseUri":"5afee712e4b0da30c1bfc0cc","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":730162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ding, Changqing","contributorId":202909,"corporation":false,"usgs":false,"family":"Ding","given":"Changqing","email":"","affiliations":[],"preferred":false,"id":730175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erwin, R. Michael","contributorId":87854,"corporation":false,"usgs":true,"family":"Erwin","given":"R.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":730176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mundkur, Taej","contributorId":199127,"corporation":false,"usgs":false,"family":"Mundkur","given":"Taej","email":"","affiliations":[],"preferred":false,"id":730177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":730178,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellis, Erle C.","contributorId":67400,"corporation":false,"usgs":true,"family":"Ellis","given":"Erle","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":730179,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70196830,"text":"70196830 - 2018 - Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients","interactions":[],"lastModifiedDate":"2018-05-04T11:41:55","indexId":"70196830","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients","docAbstract":"<p><span>Nitrogen (N) and phosphorus (P) commonly stimulate phytoplankton production in lakes, but recent observations from lakes from an agricultural region suggest that nitrate may have a subsidy‐stress effect on chlorophyll&nbsp;</span><i>a</i><span><span>&nbsp;</span>(Chl<span>&nbsp;</span></span><i>a</i><span>). It is unclear, however, how generalizable this effect might be. Here, we analyzed a large water quality dataset of 2385 lakes spanning 60 regions across 17 states in the Northeastern and Midwestern U.S. to determine if N subsidy‐stress effects on phytoplankton are common and to identify regional landscape characteristics promoting N stress effects in lakes. We used a Bayesian hierarchical modeling framework to test our hypothesis that Chl<span>&nbsp;</span></span><i>a</i><span>–total N (TN) threshold relationships would be common across the central agricultural region of the U.S. (“the Corn Belt”), where lake N and P concentrations are high. Data aggregated across all regions indicated that high TN concentrations had a negative effect on Chl<span>&nbsp;</span></span><i>a</i><span><span>&nbsp;</span>in lakes with concurrent high total P. This large‐scale pattern was driven by relationships within only a subset of regions, however. Eight regions were identified as having Chl<span>&nbsp;</span></span><i>a</i><span>–TN threshold relationships, but only two of these regions located within the Corn Belt clearly demonstrated this subsidy‐stress relationship. N stress effects were not consistent across other intense agricultural regions, as we hypothesized. These findings suggest that interactions among regional land use and land cover, climate, and hydrogeology may be important in determining the synergistic conditions leading to N subsidy‐stress effects on lake phytoplankton.</span></p>","language":"English","publisher":"ASLO","doi":"10.1002/lno.10742","usgsCitation":"Filstrup, C.T., Wagner, T., Oliver, S., Stow, C.A., Webster, K.E., Stanley, E.H., and Downing, J., 2018, Evidence for regional nitrogen stress on chlorophyll a in lakes across large landscape and climate gradients: Limnology and Oceanography, v. 63, no. S1, p. 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 \"}}]}","volume":"63","issue":"S1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-14","publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc09e","contributors":{"authors":[{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":734713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oliver, Samantha K.","contributorId":169273,"corporation":false,"usgs":false,"family":"Oliver","given":"Samantha K.","affiliations":[],"preferred":false,"id":734714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stow, Craig A.","contributorId":204103,"corporation":false,"usgs":false,"family":"Stow","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":36843,"text":"NOAA, Great Lakes Environmental Research Lab","active":true,"usgs":false}],"preferred":false,"id":734715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webster, Katherine E.","contributorId":147903,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734716,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":734717,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Downing, John A.","contributorId":70348,"corporation":false,"usgs":true,"family":"Downing","given":"John A.","affiliations":[],"preferred":false,"id":734718,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196435,"text":"70196435 - 2018 - Golden Eagle Monitoring Plan for the Desert Renewable Energy Conservation Plan","interactions":[],"lastModifiedDate":"2018-04-06T16:37:36","indexId":"70196435","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesNumber":"CEC-500-2018-008","title":"Golden Eagle Monitoring Plan for the Desert Renewable Energy Conservation Plan","docAbstract":"<p>This report describes options for monitoring the status and population trends of the golden eagle (Aquila chrysaetos) within the Desert Renewable Energy Conservation Plan (DRECP) area of Southern California in maintaining stable or increasing population in the planning area. The report profiles the ecology of golden eagles in the region and provides a range of potential sampling options to address monitoring needs and objectives. This approach also focused on links between changes in human land-use, golden eagle nesting and foraging habitat conditions, and population dynamics. The report outlines how monitoring data from demographic, prey, and habitat studies were used to develop a predictive demographic model for golden eagles in the DRECP area. Results from the model simulations suggest increases in renewable energy development could have negative consequences for population trajectories. Results also suggest site-specific conservation actions could reduce the magnitude of negative impacts to the local population of eagles. </p><p>A monitoring framework is proposed including: (1) annual assessments of site-occupancy and reproduction by territorial pairs of golden eagles (including rates at which sites become colonized or vacated over time); (2) estimates of survival, movements, and intensity of use of landscapes by breeding and non-breeding golden eagles; (3) periodic (conducted every two to four years) assessments of nesting and foraging habitats, prey populations, and associations with land-use and management activities; and (4) updating the predictive demographic model with new information obtained on eagles and associated population stressors. </p><p>The results of this research were published in the Journal of Rapture Research, Wiens, David,Inman, Rich D., Esque, Todd C., Longshore, Kathleen M. and Nussear, Kenneth (2017). Spatial Demographic Models to Inform Conservation Planning of Golden Eagles in Renewable Energy Landscapes. 51(3):234-257. </p>","language":"English","publisher":"California Energy Commission","usgsCitation":"Wiens, D., Kolar, P., and Katzner, T., 2018, Golden Eagle Monitoring Plan for the Desert Renewable Energy Conservation Plan, 99 p.","productDescription":"99 p.","ipdsId":"IP-086130","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":353243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353224,"type":{"id":11,"text":"Document"},"url":"https://www.energy.ca.gov/2018publications/CEC-500-2018-008/CEC-500-2018-008.pdf"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0aa","contributors":{"authors":[{"text":"Wiens, David 0000-0002-2020-038X jwiens@usgs.gov","orcid":"https://orcid.org/0000-0002-2020-038X","contributorId":167538,"corporation":false,"usgs":true,"family":"Wiens","given":"David","email":"jwiens@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":732901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolar, Patrick 0000-0002-0076-7565 pkolar@usgs.gov","orcid":"https://orcid.org/0000-0002-0076-7565","contributorId":189512,"corporation":false,"usgs":true,"family":"Kolar","given":"Patrick","email":"pkolar@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":732902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":732903,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70197461,"text":"70197461 - 2018 - Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management","interactions":[],"lastModifiedDate":"2018-06-06T11:28:19","indexId":"70197461","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management","docAbstract":"<p style=\"text-align: left;\" data-mce-style=\"text-align: left;\"><span>Geology and hydrology are drivers of water chemistry and thus important considerations for fish otolith chemistry research. However, other factors such as species and habitat identity may have predictive ability, enabling selection of appropriate elemental signatures prior to costly, perhaps unnecessary water/age‐0 fish sampling. The goal of this study was to develop a predictive methodology for using species and habitat identity to design efficient otolith chemistry studies. Duplicate water samples and age‐0 fish were collected from 61 sites in 4 Missouri River reservoirs for walleye&nbsp;</span><i>Sander vitreus</i><span><span>&nbsp;</span>and one impoundment (Lake Sharpe, South Dakota) for other fishes (bluegill<span>&nbsp;</span></span><i>Lepomis macrochirus</i><span>, black crappie<span>&nbsp;</span></span><i>Pomoxis nigromaculatus</i><span>, gizzard shad<span>&nbsp;</span></span><i>Dorosoma cepedianum</i><span>, largemouth bass<span>&nbsp;</span></span><i>Micropterus salmoides</i><span>, smallmouth bass<span>&nbsp;</span></span><i>M.&nbsp;dolomieu</i><span>, white bass<span>&nbsp;</span></span><i>Morone chrysops</i><span>, white crappie<span>&nbsp;</span></span><i>P.&nbsp;annularis</i><span>, and yellow perch<span>&nbsp;</span></span><i>Perca flavescens</i><span>). Water chemistry (barium:calcium [Ba:Ca], strontium:calcium [Sr:Ca]) was temporally stable, spatially variable, and highly correlated with otolith chemistry for all species except yellow perch. Classification accuracies based on bivariate Ba:Ca and Sr:Ca signatures were high (84% across species) yet varied between floodplain and main‐channel habitats in a species‐specific manner. Thus, to maximize the reliability of otolith chemistry, researchers can use species classifications presented herein to inform habitat selection (e.g., study reservoir‐oriented species such as white bass in main‐channel environments) and habitat‐based classifications to inform species selection (e.g., focus floodplain studies on littoral species such as largemouth bass). Overall, species and habitat identity are important considerations for efficient, effective otolith chemistry studies that inform and advance fisheries and aquatic resource management.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3248","usgsCitation":"Radigan, W., Carlson, A.K., Kientz, J., Chipps, S.R., Fincel, M.J., and Graeb, B.D., 2018, Species‐ and habitat‐specific otolith chemistry patterns inform riverine fisheries management: River Research and Applications, v. 34, no. 3, p. 279-287, https://doi.org/10.1002/rra.3248.","productDescription":"9 p.","startPage":"279","endPage":"287","ipdsId":"IP-092404","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":354760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.27,\n              42.49\n            ],\n            [\n              -96.45,\n              42.49\n            ],\n            [\n              -96.45,\n              47.39\n            ],\n            [\n              -103.27,\n              47.39\n            ],\n            [\n              -103.27,\n              42.49\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","scienceBaseUri":"5b46e5ade4b060350a15d200","contributors":{"authors":[{"text":"Radigan, William","contributorId":205424,"corporation":false,"usgs":false,"family":"Radigan","given":"William","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":737249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Andrew K.","contributorId":172103,"corporation":false,"usgs":false,"family":"Carlson","given":"Andrew","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":737250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kientz, Jeremy","contributorId":205425,"corporation":false,"usgs":false,"family":"Kientz","given":"Jeremy","email":"","affiliations":[{"id":37104,"text":"South Dakota Department of Game, Fish and Parks","active":true,"usgs":false}],"preferred":false,"id":737251,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":737248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fincel, Mark J.","contributorId":171853,"corporation":false,"usgs":false,"family":"Fincel","given":"Mark","email":"","middleInitial":"J.","affiliations":[{"id":26957,"text":"South Dakota Game, Fish and Parks, Ft. Pierre, SD","active":true,"usgs":false}],"preferred":false,"id":737252,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graeb, Brian D. S.","contributorId":171851,"corporation":false,"usgs":false,"family":"Graeb","given":"Brian","email":"","middleInitial":"D. S.","affiliations":[{"id":26956,"text":"Departement of Natural Resource Management, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":737253,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70197450,"text":"70197450 - 2018 - Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana","interactions":[],"lastModifiedDate":"2018-06-05T10:33:23","indexId":"70197450","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana","docAbstract":"<p><span>The relative roles of science and human values can be difficult to distinguish when informal processes are used to make complex and contentious decisions in wildlife management. Structured Decision Making (SDM) offers a formal process for making such decisions, where scientific results and concepts can be disentangled from the values of differing stakeholders. We used SDM to formally integrate science and human values for a citizen working group of ungulate hunting advocates, lion hunting advocates, and outfitters convened to address the contentious allocation of harvest quotas for mountain lions (</span><i>Puma concolor</i><span>) in west‐central Montana, USA, during 2014. A science team consisting of mountain lion biologists and population ecologists convened to support the working group. The science team used integrated population models that incorporated 4 estimates of mountain lion density to estimate population trajectories for 5 alternative harvest quotas developed by the working group. Results of the modeling predicted that effects of each harvest quota were consistent across the 4 density estimates; harvest quotas affected predicted population trajectories for 5 years after implementation but differences were not strong. Based on these results, the focus of the working group changed to differences in values among stakeholders that were the true impediment to allocating harvest quotas. By distinguishing roles of science and human values in this process, the working group was able to collaboratively recommend a compromise solution. This solution differed little from the status quo that had been the focus of debate, but the SDM process produced understanding and buy‐in among stakeholders involved, reducing disagreements, misunderstanding, and unproductive arguments founded on informal application of scientific data and concepts. Whereas investments involved in conducting SDM may be unnecessary for many decisions in wildlife management, the investment may be beneficial for complex, contentious, and multiobjective decisions that integrate science and human values.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/wsb.861","usgsCitation":"Mitchell, M.S., Cooley, H., Gude, J., Kolbe, J., Nowak, J.J., Proffitt, K.M., Sells, S.N., and Thompson, M., 2018, Distinguishing values from science in decision making: Setting harvest quotas for mountain lions in Montana: Wildlife Society Bulletin, v. 42, no. 1, p. 13-21, https://doi.org/10.1002/wsb.861.","productDescription":"9 p.","startPage":"13","endPage":"21","ipdsId":"IP-089989","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":499990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/821cf25d1bd94a54a95a168864e646fc","text":"External Repository"},{"id":354717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.740966796875,\n              45.433153642271385\n            ],\n            [\n              -112.093505859375,\n              45.433153642271385\n            ],\n            [\n              -112.093505859375,\n              47.45037978769006\n            ],\n            [\n              -115.740966796875,\n              47.45037978769006\n            ],\n            [\n              -115.740966796875,\n              45.433153642271385\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"42","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","scienceBaseUri":"5b46e5ade4b060350a15d202","contributors":{"authors":[{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":737199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooley, Hilary","contributorId":205414,"corporation":false,"usgs":false,"family":"Cooley","given":"Hilary","affiliations":[],"preferred":false,"id":737227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":737228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolbe, Jay","contributorId":205415,"corporation":false,"usgs":false,"family":"Kolbe","given":"Jay","email":"","affiliations":[],"preferred":false,"id":737229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nowak, J. Joshua","contributorId":171707,"corporation":false,"usgs":false,"family":"Nowak","given":"J.","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":737230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Proffitt, Kelly M.","contributorId":106783,"corporation":false,"usgs":true,"family":"Proffitt","given":"Kelly","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":737231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sells, Sarah N.","contributorId":171706,"corporation":false,"usgs":false,"family":"Sells","given":"Sarah","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":737232,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Mike","contributorId":205416,"corporation":false,"usgs":false,"family":"Thompson","given":"Mike","email":"","affiliations":[],"preferred":false,"id":737233,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70193856,"text":"70193856 - 2018 - Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock","interactions":[],"lastModifiedDate":"2018-03-29T15:13:48","indexId":"70193856","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock","docAbstract":"<ol class=\"\"><li><p>Switchgrass (<i>Panicum virgatum</i>) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (<i>Pinus taeda</i>) plantations in Mississippi, USA.</p></li><li><p>We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum<span>&nbsp;</span><i>n&nbsp;</i>=<i>&nbsp;</i>5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.</p></li><li><p>Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.</p></li><li><p>Covariates of nest placement indicated that switchgrass at the nest site (&lt;4&nbsp;m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.</p></li><li><p><i>Synthesis and applications</i>. Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1&nbsp;km<sup>2</sup>), although at a local scale (50&nbsp;m<sup>2</sup>) switchgrass negatively influenced nest survival. A likely explanation is intercropping shifted community composition, favouring species with greater disturbance tolerance.</p></li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.13015","usgsCitation":"Loman, Z., Monroe, A., Riffell, S.K., Miller, D.A., Vilella, F., Wheat, B.R., Rush, S.A., and Martin, J.A., 2018, Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock: Journal of Applied Ecology, v. 55, no. 2, p. 937-946, https://doi.org/10.1111/1365-2664.13015.","productDescription":"10 p.","startPage":"937","endPage":"946","ipdsId":"IP-067146","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.13015","text":"Publisher Index Page"},{"id":352961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-19","publicationStatus":"PW","scienceBaseUri":"5afee713e4b0da30c1bfc0d8","contributors":{"authors":[{"text":"Loman, Zachary G.","contributorId":145932,"corporation":false,"usgs":false,"family":"Loman","given":"Zachary G.","affiliations":[],"preferred":false,"id":720689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":720690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riffell, Samuel K.","contributorId":102386,"corporation":false,"usgs":true,"family":"Riffell","given":"Samuel","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":720691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Darren A.","contributorId":203650,"corporation":false,"usgs":false,"family":"Miller","given":"Darren","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wheat, Bradley R.","contributorId":145933,"corporation":false,"usgs":false,"family":"Wheat","given":"Bradley","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":720693,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rush, Scott A.","contributorId":92139,"corporation":false,"usgs":true,"family":"Rush","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720694,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, James A.","contributorId":145934,"corporation":false,"usgs":false,"family":"Martin","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720695,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70196051,"text":"70196051 - 2018 - Developing a framework for evaluating tallgrass prairie reconstruction methods and management","interactions":[],"lastModifiedDate":"2018-03-15T11:44:40","indexId":"70196051","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1462,"text":"Ecological Restoration","active":true,"publicationSubtype":{"id":10}},"title":"Developing a framework for evaluating tallgrass prairie reconstruction methods and management","docAbstract":"<p><span>The thousands of hectares of prairie reconstructed each year in the tallgrass prairie biome can provide a valuable resource for evaluation of seed mixes, planting methods, and post-planting management if methods used and resulting characteristics of the prairies are recorded and compiled in a publicly accessible database. The objective of this study was to evaluate the use of such data to understand the outcomes of reconstructions over a 10-year period at two U.S. Fish and Wildlife Service refuges. Variables included number of species planted, seed source (combine-harvest or combine-harvest plus hand-collected), fire history, and planting method and season. In 2015 we surveyed vegetation on 81 reconstructions and calculated proportion of planted species observed; introduced species richness; native species richness, evenness and diversity; and mean coefficient of conservatism. We conducted exploratory analyses to learn how implied communities based on seed mix compared with observed vegetation; which seeding or management variables were influential in the outcome of the reconstructions; and consistency of responses between the two refuges. Insights from this analysis include: 1) proportion of planted species observed in 2015 declined as planted richness increased, but lack of data on seeding rate per species limited conclusions about value of added species; 2) differing responses to seeding and management between the two refuges suggest the importance of geographic variability that could be addressed using a public database; and 3) variables such as fire history are difficult to quantify consistently and should be carefully evaluated in the context of a public data repository.</span></p>","language":"English","publisher":"University of Wisconsin Press","doi":"10.3368/er.36.1.6","usgsCitation":"Larson, D.L., Ahlering, M., Drobney, P., Esser, R., Larson, J.L., and Viste-Sparkman, K., 2018, Developing a framework for evaluating tallgrass prairie reconstruction methods and management: Ecological Restoration, v. 36, no. 1, p. 6-18, https://doi.org/10.3368/er.36.1.6.","productDescription":"13 p.","startPage":"6","endPage":"18","ipdsId":"IP-082530","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":352555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-28","publicationStatus":"PW","scienceBaseUri":"5afee712e4b0da30c1bfc0c4","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahlering, Marissa 0000-0002-3913-428X","orcid":"https://orcid.org/0000-0002-3913-428X","contributorId":171943,"corporation":false,"usgs":false,"family":"Ahlering","given":"Marissa","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":731144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drobney, Pauline","contributorId":178447,"corporation":false,"usgs":false,"family":"Drobney","given":"Pauline","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":731146,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Esser, Rebecca","contributorId":197592,"corporation":false,"usgs":false,"family":"Esser","given":"Rebecca","affiliations":[],"preferred":false,"id":731145,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Jennifer L.","contributorId":178444,"corporation":false,"usgs":false,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":731148,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viste-Sparkman, Karen","contributorId":197593,"corporation":false,"usgs":false,"family":"Viste-Sparkman","given":"Karen","email":"","affiliations":[],"preferred":false,"id":731147,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70195850,"text":"70195850 - 2018 - Environmental contaminants of health-care origin: Exposure and potential effects in wildlife","interactions":[],"lastModifiedDate":"2018-03-07T15:10:25","indexId":"70195850","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Environmental contaminants of health-care origin: Exposure and potential effects in wildlife","docAbstract":"A diverse range of fauna could be exposed to active pharmaceutical ingredients (APIs) via diet, dermal absorption or bioconcentration. Low level exposures of free-ranging wildlife to APIs has only been demonstrated for a few pathways (e.g., ingestion of fish in estuaries by piscivorous birds), and many remain hypothetical (e.g., ingestion of invertebrates in sludge amended fields by terrestrial vertebrates). Our understanding of API dose-response relationships in wildlife have only been assessed for endocrine disrupting compounds and a few veterinary therapeutics. Drug specific responses at various levels of biological organization are poorly characterized for nearly all wildlife species, and thus our understanding of risk is limited. There is interest in using a read-across approach to fill knowledge gaps for risk. This approach, using data collected in laboratory mammals and humans, would enable predictions for likelihood of adverse effects in wildlife. Given the great diversities in physiologies among species, a combination of in vivo, in vitro and in silico approaches will be required to fill the knowledge gaps for exposure, hazard and risk.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Health care and environmental contamination","language":"English","publisher":"Elsevier","isbn":"9780444638571","usgsCitation":"Bean, T., and Rattner, B.A., 2018, Environmental contaminants of health-care origin: Exposure and potential effects in wildlife, chap. <i>of</i> Health care and environmental contamination, p. 87-122.","productDescription":"36 p.","startPage":"87","endPage":"122","ipdsId":"IP-075358","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":352302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee712e4b0da30c1bfc0c8","contributors":{"authors":[{"text":"Bean, Thomas","contributorId":202972,"corporation":false,"usgs":false,"family":"Bean","given":"Thomas","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":730299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":730298,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70196763,"text":"70196763 - 2018 - Timber harvest as the predominant disturbance regime in northeastern U.S. forests: Effects of harvest intensification","interactions":[],"lastModifiedDate":"2018-04-30T13:06:26","indexId":"70196763","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Timber harvest as the predominant disturbance regime in northeastern U.S. forests: Effects of harvest intensification","docAbstract":"<p><span>Harvesting is the leading cause of adult tree mortality in forests of the northeastern United States. While current rates of timber harvest are generally sustainable, there is considerable pressure to increase the contribution of forest biomass to meet renewable energy goals. We estimated current harvest regimes for different forest types and regions across the U.S. states of New York, Vermont, New Hampshire, and Maine using data from the U.S. Forest Inventory and Analysis Program. We implemented the harvest regimes in SORTIE‐ND, an individual‐based model of forest dynamics, and simulated the effects of current harvest regimes and five additional harvest scenarios that varied by harvest frequency and intensity over 150&nbsp;yr. The best statistical model for the harvest regime described the annual probability of harvest as a function of forest type/region, total plot basal area, and distance to the nearest improved road. Forests were predicted to increase in adult aboveground biomass in all harvest scenarios in all forest type and region combinations. The magnitude of the increase, however, varied dramatically—increasing from 3% to 120% above current landscape averages as harvest frequency and intensity decreased. The variation can be largely explained by the disproportionately high harvest rates estimated for Maine as compared with the rest of the region. Despite steady biomass accumulation across the landscape, stands that exhibited old‐growth characteristics (defined as ≥300 metric tons of biomass/hectare) were rare (8% or less of stands). Intensified harvest regimes had little effect on species composition due to widespread partial harvesting in all scenarios, resulting in dominance by late‐successional species over time. Our analyses indicate that forest biomass can represent a sustainable, if small, component of renewable energy portfolios in the region, although there are tradeoffs between carbon sequestration in forest biomass and sustainable feedstock supply. Integrating harvest regimes into a disturbance theory framework is critical to understanding the dynamics of forested landscapes, especially given the predominance of logging as a disturbance agent and the increasing pressure to meet renewable energy needs.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2062","usgsCitation":"Brown, M.L., Canham, C.D., Murphy, L., and Donovan, T.M., 2018, Timber harvest as the predominant disturbance regime in northeastern U.S. forests: Effects of harvest intensification: Ecosphere, v. 9, no. 3, p. 1-19, https://doi.org/10.1002/ecs2.2062.","productDescription":"e02062; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-086575","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468953,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2062","text":"Publisher Index Page"},{"id":353856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-30","publicationStatus":"PW","scienceBaseUri":"5afee70fe4b0da30c1bfc0a2","contributors":{"authors":[{"text":"Brown, Michelle L.","contributorId":168990,"corporation":false,"usgs":false,"family":"Brown","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":734289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Canham, Charles D.","contributorId":152138,"corporation":false,"usgs":false,"family":"Canham","given":"Charles","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Lora","contributorId":196420,"corporation":false,"usgs":false,"family":"Murphy","given":"Lora","email":"","affiliations":[],"preferred":false,"id":734291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734288,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159602,"text":"sir20155164 - 2018 - Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models","interactions":[],"lastModifiedDate":"2023-06-08T16:40:09.114831","indexId":"sir20155164","displayToPublicDate":"2018-03-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5164","displayTitle":"Volcanic Aquifers of Hawai‘i—Hydrogeology, Water budgets, and Conceptual Models","title":"Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models","docAbstract":"<p>Hawai‘i’s aquifers have limited capacity to store fresh groundwater because each island is small and surrounded by saltwater. Saltwater also underlies much of the fresh groundwater. Fresh groundwater resources are, therefore, particularly vulnerable to human activity, short-term climate cycles, and long-term climate change. Availability of fresh groundwater for human use is constrained by the degree to which the impacts of withdrawal—such as lowering of the water table, saltwater intrusion, and reduction in the natural discharge to springs, streams, wetlands, and submarine seeps—are deemed acceptable. This report describes the hydrogeologic framework, groundwater budgets (inflows and outflows), conceptual models of groundwater occurrence and movement, and the factors limiting groundwater availability for the largest and most populated of the Hawaiian Islands—Kaua‘i, O‘ahu, Maui, and Hawai‘i Island.</p><p>The bulk of each of Hawai‘i’s islands is built of many thin lava flows erupted from shield volcanoes; the great piles of lava flows form highly permeable aquifers. In some areas, low-permeability dikes cutting across the lava flows, or low-permeability ash and soil horizons interlayered with the lava flows, can substantially alter groundwater flow. On some islands, sedimentary rocks form thick semiconfining coastal-plain deposits, locally known as caprock, that impede natural groundwater discharge to the ocean. In some regions, thick lava flows that ponded in preexisting depressions form aquifers that are much less permeable than aquifers formed by thin lava flows.</p><p>Fresh groundwater inflow to Hawai‘i’s aquifers comes from recharge. For predevelopment conditions (1870), estimates of groundwater recharge from this study are 871, 675, 1,279, and 5,291 million gallons per day (Mgal/d) for Kaua‘i, O‘ahu, Maui, and Hawai‘i Island, respectively. Estimates of recharge for recent conditions (2010 land cover and 1978–2007 rainfall for Kaua‘i, O‘ahu, and Maui; 2008 land cover and 1916–1983 rainfall for Hawai‘i Island) are 875, 660, 1,308, and 6,595 Mgal/d for Kaua‘i, O‘ahu, Maui, and Hawai‘i Island, respectively. Recent recharge values differ from predevelopment recharge values by only a few percent for all islands except Hawai‘i Island, where changes in forest cover affected recharge. Spatial distribution of recharge mimics the orographic rainfall pattern—recharge is high on&nbsp;windward slopes and mountain peaks below the top of the trade-wind inversion. Human activity such as irrigation also contributes to recharge in some areas.</p><p>Outflows from Hawai‘i’s aquifers include withdrawals from wells and natural groundwater discharge to springs, streams, wetlands, and submarine seeps. Under predevelopment conditions, groundwater withdrawal is assumed to be negligible and natural groundwater discharge probably was equal, or close, to recharge. Under recent conditions (2000–2010), groundwater withdrawal averaged 19, 209, 104, and 103 Mgal/d on Kaua‘i, O‘ahu, Maui, and Hawai‘i Island, respectively. If recent withdrawal and recharge rates are maintained until steady state is achieved, natural groundwater discharge will be reduced by an amount equal to the withdrawal rate. Total recent withdrawal for the four islands is only about 5 percent of total recharge, but about half of the withdrawal comes from O‘ahu, whereas O‘ahu receives only 7 percent of the total recharge. Effects of high withdrawals on O‘ahu cannot be mitigated by the lower withdrawals on other islands because no freshwater flows between islands. Even within an island, high withdrawals from one area cannot be completely mitigated by recharge in another area. Water-level, saltwater/freshwater-transition-zone, spring, and stream base-flow data indicate an overall reduction in storage for most areas where groundwater has been developed.</p><p>Groundwater occurrence and movement in Hawai‘i’s volcanic aquifers can be described in terms of four conceptual models: (1) fresh groundwater lenses in high-permeability lava-flow aquifers, (2) aquifers with groundwater impounded by dikes, (3) thickly saturated low-permeability aquifers, and (4) perched aquifers. In Hawai‘i, most fresh groundwater withdrawn for human use comes from freshwater lenses in the dike-free high-permeability lava-flow aquifers where the principal limiting factor to groundwater availability is saltwater intrusion, but impacts of reduced natural groundwater discharge may also limit availability. Dike-impounded groundwater is common near the center of Hawaiian shield volcanoes, where water moves and is stored in permeable lava flows between the dikes; groundwater availability in these aquifers is primarily limited by storage depletion and reduction of flow to adjacent aquifers and natural groundwater discharge. Thickly saturated low-permeability aquifers have been identified on Kaua‘i and Maui; groundwater availability is primarily limited by streamflow depletion and water-table decline. Perched groundwater is postulated to exist in some areas of Hawai‘i, but store much less water than other modes ofgroundwater occurrence. Limits on groundwater availability in perched aquifers include the potential of reducing inflow to other groundwater settings and reducing natural discharge and stream seepage. Some groundwater bodies in Hawai‘i are enigmatic; consequences of groundwater development in these bodies and their relation to groundwater availability are not completely understood.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155164","usgsCitation":"Izuka, S.K., Engott, J.A., Rotzoll, Kolja, Bassiouni, Maoya, Johnson, A.G., Miller, L.D., and Mair, Alan, 2018, Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models (ver. 2.0, March 2018): U.S. Geological Survey Scientific Investigations Report 2015-5164, 158 p., https://doi.org/10.3133/sir20155164.","productDescription":"Report: ix, 158 p.; Data Releases","numberOfPages":"172","ipdsId":"IP-058142","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":351940,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72F7KH4","linkHelpText":"Mean annual 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 \"}}]}","edition":"Version 1.0: June 13, 2016; Version 2.0: March 1, 2018","contact":"<p><a href=\"mailto:dc_hi@usgs.gov\" data-mce-href=\"mailto:dc_hi@usgs.gov\">Director</a>,&nbsp;<br><a href=\"https://hi.water.usgs.gov/\" data-mce-href=\"https://hi.water.usgs.gov/\">Pacific Islands Water Science Center</a><br><a href=\"https://usgs.gov/\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>Inouye Regional Center<br>1845 Wasp Blvd., B176<br>Honolulu, HI 96818</p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Study Area<br></li><li>Hydrogeologic Framework of the Islands<br></li><li>Fresh Groundwater-Flow Budget<br></li><li>Conceptual Models of Groundwater Occurrence and Movement<br></li><li>Study Limitations<br></li><li>Summary<br></li><li>References Cited<br></li><li>Appendix 1. Calculation of Groundwater Recharge<br></li><li>Appendix 2. Annual Groundwater Recharge, 2001–2010<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-06-13","revisedDate":"2018-03-01","noUsgsAuthors":false,"publicationDate":"2016-06-13","publicationStatus":"PW","scienceBaseUri":"575fcb20e4b04f417c2b2683","contributors":{"authors":[{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rotzoll, Kolja 0000-0002-5910-888X","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":201087,"corporation":false,"usgs":false,"family":"Rotzoll","given":"Kolja","affiliations":[],"preferred":false,"id":729255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bassiouni, Maoya 0000-0001-5795-9894 mbassiou@usgs.gov","orcid":"https://orcid.org/0000-0001-5795-9894","contributorId":4639,"corporation":false,"usgs":true,"family":"Bassiouni","given":"Maoya","email":"mbassiou@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":729256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Lisa D. 0000-0002-3523-0768 ldmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-3523-0768","contributorId":1125,"corporation":false,"usgs":true,"family":"Miller","given":"Lisa","email":"ldmiller@usgs.gov","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729258,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mair, Alan 0000-0003-0302-6647 dmair@usgs.gov","orcid":"https://orcid.org/0000-0003-0302-6647","contributorId":4975,"corporation":false,"usgs":true,"family":"Mair","given":"Alan","email":"dmair@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729259,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
]}