{"pageNumber":"554","pageRowStart":"13825","pageSize":"25","recordCount":40783,"records":[{"id":70156234,"text":"70156234 - 2015 - Equation-free modeling unravels the behavior of complex ecological systems","interactions":[],"lastModifiedDate":"2015-08-19T10:55:00","indexId":"70156234","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Equation-free modeling unravels the behavior of complex ecological systems","docAbstract":"<p>Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.&rsquo;s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term &ldquo;equation-free&rdquo; in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka&ndash;Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing &ldquo;clarity and precision into conjecture&rdquo; (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.</p>","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.1503154112","usgsCitation":"DeAngelis, D., and Yurek, S., 2015, Equation-free modeling unravels the behavior of complex ecological systems: PNAS, v. 112, no. 13, p. 3856-3857, https://doi.org/10.1073/pnas.1503154112.","productDescription":"2 p.","startPage":"3856","endPage":"3857","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063709","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1503154112","text":"Publisher Index Page"},{"id":306924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","issue":"13","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-17","publicationStatus":"PW","scienceBaseUri":"55d5a8afe4b0518e3546a4be","chorus":{"doi":"10.1073/pnas.1503154112","url":"http://dx.doi.org/10.1073/pnas.1503154112","publisher":"Proceedings of the National Academy of Sciences","authors":"DeAngelis Donald L., Yurek Simeon","journalName":"Proceedings of the National Academy of Sciences","publicationDate":"3/17/2015"},"contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":568114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yurek, Simeon 0000-0002-6209-7915 syurek@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":103167,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","email":"syurek@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":568568,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70154774,"text":"70154774 - 2015 - Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon","interactions":[],"lastModifiedDate":"2022-11-14T17:37:39.358873","indexId":"70154774","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","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":"Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon","docAbstract":"<p><span>Dams and river regulation greatly alter the downstream environment for gross primary production (GPP) because of changes in water clarity, flow, and temperature regimes. We estimated reach-scale GPP in five locations of the regulated Colorado River in Grand Canyon using an open channel model of dissolved oxygen. Benthic GPP dominates in Grand Canyon due to fast transport times and low pelagic algal biomass. In one location, we used a 738 days time series of GPP to identify the relative contribution of different physical controls of GPP. We developed both linear and semimechanistic time series models that account for unmeasured temporal covariance due to factors such as algal biomass dynamics. GPP varied from 0 g O</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>&nbsp;to 3.0 g O</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>&nbsp;with a relatively low annual average of 0.8 g O</span><sub>2</sub><span>&nbsp;m</span><sup>−2</sup><span>&nbsp;d</span><sup>−1</sup><span>. Semimechanistic models fit the data better than linear models and demonstrated that variation in turbidity primarily controlled GPP. Lower solar insolation during winter and from cloud cover lowered GPP much further. Hydropeaking lowered GPP but only during turbid conditions. Using the best model and parameter values, the model accurately predicted seasonal estimates of GPP at 3 of 4 upriver sites and outperformed the linear model at all sites; discrepancies were likely from higher algal biomass at upstream sites. This modeling approach can predict how changes in physical controls will affect relative rates of GPP throughout the 385 km segment of the Colorado River in Grand Canyon and can be easily applied to other streams and rivers.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/lno.10031","usgsCitation":"Hall, R., Yackulic, C.B., Kennedy, T., Yard, M., Rosi-Marshall, E.J., Voichick, N., and Behn, K.E., 2015, Turbidity, light, temperature, and hydropeaking control primary productivity in the Colorado River, Grand Canyon: Limnology and Oceanography, v. 60, no. 2, p. 512-516, https://doi.org/10.1002/lno.10031.","productDescription":"5 p.","startPage":"512","endPage":"516","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056074","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472242,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10031","text":"Publisher Index Page"},{"id":306634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.97690643788997,\n              35.96223553892966\n            ],\n            [\n              -111.95607071326728,\n              36.15089215745617\n            ],\n            [\n              -112.47488025637692,\n              36.439732993660684\n            ],\n            [\n              -113.00202408933613,\n              36.35587791388548\n            ],\n            [\n              -113.62917940048527,\n              35.88968479994075\n            ],\n            [\n              -113.53125149475788,\n              35.705479139380046\n            ],\n            [\n              -113.28747351666969,\n              35.724088071319485\n            ],\n            [\n              -113.16870988631914,\n              35.9959573825395\n            ],\n            [\n              -112.61031246642614,\n              36.256812611305506\n            ],\n            [\n              -111.97690643788997,\n              35.96223553892966\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"60","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-30","publicationStatus":"PW","scienceBaseUri":"55cdbfc0e4b08400b1fe1456","chorus":{"doi":"10.1002/lno.10031","url":"http://dx.doi.org/10.1002/lno.10031","publisher":"Wiley-Blackwell","authors":"Hall Robert O., Yackulic Charles B., Kennedy Theodore A., Yard Michael D., Rosi-Marshall Emma J., Voichick Nicholas, Behn Kathrine E.","journalName":"Limnology and Oceanography","publicationDate":"1/30/2015","auditedOn":"1/29/2017","publiclyAccessibleDate":"1/30/2015"},"contributors":{"authors":[{"text":"Hall, Robert O. Jr.","contributorId":145459,"corporation":false,"usgs":false,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[{"id":16121,"text":"Uni. of Wyoming, Department of Zoology and Physiology","active":true,"usgs":false}],"preferred":false,"id":564095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":564094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":140027,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","email":"tkennedy@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":564096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yard, Michael D. 0000-0002-6580-6027 myard@usgs.gov","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":2889,"corporation":false,"usgs":true,"family":"Yard","given":"Michael D.","email":"myard@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":564097,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosi-Marshall, Emma J.","contributorId":17722,"corporation":false,"usgs":true,"family":"Rosi-Marshall","given":"Emma","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":564098,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Voichick, Nicholas nvoichick@usgs.gov","contributorId":5015,"corporation":false,"usgs":true,"family":"Voichick","given":"Nicholas","email":"nvoichick@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":564099,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Behn, Kathrine E.","contributorId":83839,"corporation":false,"usgs":true,"family":"Behn","given":"Kathrine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":564100,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70196455,"text":"70196455 - 2015 - Real-time validation of the Dst Predictor model","interactions":[],"lastModifiedDate":"2019-07-10T14:00:14","indexId":"70196455","displayToPublicDate":"2015-02-28T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5677,"text":"Air Force Research Laboratory Technical Report ","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"AFRL-RV-PS-TR-2015-0073","title":"Real-time validation of the Dst Predictor model","docAbstract":"<p>The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor. &nbsp;Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).</p>","language":"English","publisher":"Air Force Research Laboratory","usgsCitation":"McCollough, J.P., Young, S.L., Rigler, E.J., and Simpson, H.A., 2015, Real-time validation of the Dst Predictor model: Air Force Research Laboratory Technical Report  AFRL-RV-PS-TR-2015-0073, iii, 9 p.","productDescription":"iii, 9 p.","numberOfPages":"12","ipdsId":"IP-063134","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":422,"text":"National Geomagnetism Program","active":false,"usgs":true}],"links":[{"id":353266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeebcfe4b0da30c1bfc686","contributors":{"authors":[{"text":"McCollough, James P.","contributorId":204030,"corporation":false,"usgs":false,"family":"McCollough","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":732972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Shawn L.","contributorId":204031,"corporation":false,"usgs":false,"family":"Young","given":"Shawn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simpson, Hal A.","contributorId":204032,"corporation":false,"usgs":false,"family":"Simpson","given":"Hal","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":732975,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70142063,"text":"ofr20151019 - 2015 - Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada","interactions":[],"lastModifiedDate":"2015-02-27T13:07:46","indexId":"ofr20151019","displayToPublicDate":"2015-02-27T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1019","title":"Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada","docAbstract":"<p>We summarize the results of a three-dimensional (3-D) resistivity inversion simulation that we conducted with the intent of characterizing the subsurface 3-D distribution of volcanic composite units of Pahute Mesa, Nevada, without any a priori information on the actual 3-D distribution of the known subsurface geology. The 3-D methodology involved using a 3-D geologic model based on drillhole data and average electrical resistivities of the key hydrostratigraphic units at Pahute Mesa to create a 3-D resistivity forward (&ldquo;known&rdquo;) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was then assumed to represent observed magnetotelluric data and was used as input into a 3-D resistivity inverse model that was allowed to iteratively estimate in 3-D without any a priori geologic information, in particular, the thickness and resistivity of the volcanic composite units. The resulting 3-D resistivity inversion simulation was compared to the &ldquo;known&rdquo; model and the results evaluated.</p>\n<p>The 3-D inversion was generally able to reproduce the gross resistivity structure of the &ldquo;known&rdquo; model, but the simulated conductive volcanic composite unit horizons were often too shallow when compared to the &ldquo;known&rdquo; model. Additionally, the chosen computation parameters such as station spacing appear to have resulted in computational artifacts that are difficult to interpret but could potentially be removed with further refinements of the 3-D resistivity inversion modeling technique.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151019","usgsCitation":"Rodriguez, B.D., and Sweetkind, D., 2015, Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada: U.S. Geological Survey Open-File Report 2015-1019, iv, 104 p., https://doi.org/10.3133/ofr20151019.","productDescription":"iv, 104 p.","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051924","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":298187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151019.jpg"},{"id":298185,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1019/"},{"id":298186,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1019/pdf/ofr2015-1019.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"datum":"North American 1983 Continental United States (CONUS) datum","country":"United States","state":"Nevada","otherGeospatial":"Pahute Mesa","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -116.51687622070314,\n              37.22103367911787\n            ],\n            [\n              -116.51687622070314,\n              37.33795407160059\n            ],\n            [\n              -116.3733673095703,\n              37.33795407160059\n            ],\n            [\n              -116.3733673095703,\n              37.22103367911787\n            ],\n            [\n              -116.51687622070314,\n              37.22103367911787\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f19545e4b02419550ceaee","contributors":{"authors":[{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":541601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweetkind, Donald S. dsweetkind@usgs.gov","contributorId":130958,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","email":"dsweetkind@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":541602,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70143049,"text":"70143049 - 2015 - Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon","interactions":[],"lastModifiedDate":"2015-03-17T11:02:13","indexId":"70143049","displayToPublicDate":"2015-02-27T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon","docAbstract":"<p>To estimate the parameters that govern mass- and temperature-dependent growth, we conducted a meta-analysis of existing growth data from juvenile Chinook Salmon <i>Oncorhynchus tshawytscha</i> that were fed an ad libitum ration of a pelleted diet. Although the growth of juvenile Chinook Salmon has been well studied, research has focused on a single population, a narrow range of fish sizes, or a narrow range of temperatures. Therefore, we incorporated the Ratkowsky model for temperature-dependent growth into an allometric growth model; this model was then fitted to growth data from 11 data sources representing nine populations of juvenile Chinook Salmon. The model fit the growth data well, explaining 98% of the variation in final mass. The estimated allometric mass exponent (b) was 0.338 (SE = 0.025), similar to estimates reported for other salmonids. This estimate of b will be particularly useful for estimating mass-standardized growth rates of juvenile Chinook Salmon. In addition, the lower thermal limit, optimal temperature, and upper thermal limit for growth were estimated to be 1.8&deg;C (SE = 0.63&deg;C), 19.0&deg;C (SE = 0.27&deg;C), and 24.9&deg;C (SE = 0.02&deg;C), respectively. By taking a meta-analytical approach, we were able to provide a growth model that is applicable across populations of juvenile Chinook Salmon receiving an ad libitum ration of a pelleted diet.</p>","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2014.996667","usgsCitation":"Perry, R.W., Plumb, J.M., and Huntington, C., 2015, Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon: Transactions of the American Fisheries Society, v. 144, no. 2, p. 331-336, https://doi.org/10.1080/00028487.2014.996667.","productDescription":"6 p.","startPage":"331","endPage":"336","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053357","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":472258,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00028487.2014.996667","text":"Publisher Index Page"},{"id":298618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298587,"type":{"id":15,"text":"Index Page"},"url":"https://afs.tandfonline.com/doi/full/10.1080/00028487.2014.996667#.VQdH9cIRC70"}],"volume":"144","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"55095034e4b02e76d757e637","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":542446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":542447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntington, Charles","contributorId":139682,"corporation":false,"usgs":false,"family":"Huntington","given":"Charles","email":"","affiliations":[{"id":12878,"text":"Clearwater BioStudies, Inc., 1160 Old Ferry Rd., Shady Cove, OR  95616","active":true,"usgs":false}],"preferred":false,"id":542448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173406,"text":"70173406 - 2015 - Climate change implications in the northern coastal temperate rainforest of North America","interactions":[],"lastModifiedDate":"2016-06-20T21:21:47","indexId":"70173406","displayToPublicDate":"2015-02-27T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"Climate change implications in the northern coastal temperate rainforest of North America","docAbstract":"<p class=\"p1\"><span class=\"s1\">We synthesized an expert review of climate change implications for hydroecological and terrestrial ecological systems in the northern coastal temperate rainforest of North America. Our synthesis is based on an analysis of projected temperature, precipitation, and snowfall stratified by eight biogeoclimatic provinces and three vegetation zones. Five IPCC CMIP5 global climate models (GCMs) and two representative concentration pathways (RCPs) are the basis for projections of mean annual temperature increasing from a current average (1961&ndash;1990) of 3.2&nbsp;&deg;C to 4.9&ndash;6.9&nbsp;&deg;C (5 GCM range; RCP4.5 scenario) or 6.4&ndash;8.7&nbsp;&deg;C (RCP8.5), mean annual precipitation increasing from 3130&nbsp;mm to 3210&ndash;3400&nbsp;mm (3&ndash;9&nbsp;% increase) or 3320&ndash;3690&nbsp;mm (6&ndash;18&nbsp;% increase), and total precipitation as snow decreasing from 1200&nbsp;mm to 940&ndash;720&nbsp;mm (22&ndash;40&nbsp;% decrease) or 720&ndash;500&nbsp;mm (40&ndash;58&nbsp;% decrease) by the 2080s (2071&ndash;2100; 30-year normal period). These projected changes are anticipated to result in a cascade of ecosystem-level effects including: increased frequency of flooding and rain-on-snow events; an elevated snowline and reduced snowpack; changes in the timing and magnitude of stream flow, freshwater thermal regimes, and riverine nutrient exports; shrinking alpine habitats; altitudinal and latitudinal expansion of lowland and subalpine forest types; shifts&nbsp;in suitable habitat boundaries for vegetation and wildlife communities; adverse effects on species with rare ecological niches or limited dispersibility; and shifts in anadromous salmon distribution and productivity. Our collaborative synthesis of potential impacts highlights the coupling of social and ecological systems that characterize the region as well as a number of major information gaps to help guide assessments of future conditions and adaptive capacity.</span></p>","language":"English","publisher":"Kluwer Academic Publishers","doi":"10.1007/s10584-015-1355-9","usgsCitation":"Shanley, C.S., Pyare, S., Goldstein, M.I., Alaback, P.B., Albert, D.M., Beier, C.M., Brinkman, T.J., Edwards, R.T., Hood, E., MacKinnon, A., McPhee, M.V., Patterson, T., Suring, L.H., Tallmon, D., and Wipfli, M.S., 2015, Climate change implications in the northern coastal temperate rainforest of North America: Climate Change, v. 130, no. 2, p. 155-170, https://doi.org/10.1007/s10584-015-1355-9.","productDescription":"16 p.","startPage":"155","endPage":"170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052732","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10584-015-1355-9","text":"Publisher Index Page"},{"id":324056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -140,\n              50\n            ],\n            [\n              -140,\n              61\n            ],\n            [\n              -125,\n              61\n            ],\n            [\n              -125,\n              50\n            ],\n            [\n              -140,\n              50\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"130","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"576913b3e4b07657d19fefd3","contributors":{"authors":[{"text":"Shanley, Colin S.","contributorId":172216,"corporation":false,"usgs":false,"family":"Shanley","given":"Colin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":639962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pyare, Sanjay","contributorId":47135,"corporation":false,"usgs":true,"family":"Pyare","given":"Sanjay","email":"","affiliations":[],"preferred":false,"id":639963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldstein, Michael I.","contributorId":94641,"corporation":false,"usgs":true,"family":"Goldstein","given":"Michael","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":639964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alaback, Paul B.","contributorId":172217,"corporation":false,"usgs":false,"family":"Alaback","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":639965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Albert, David M.","contributorId":172218,"corporation":false,"usgs":false,"family":"Albert","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":639966,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beier, Colin M.","contributorId":17107,"corporation":false,"usgs":true,"family":"Beier","given":"Colin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":639967,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brinkman, Todd J.","contributorId":39696,"corporation":false,"usgs":true,"family":"Brinkman","given":"Todd","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":639968,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Edwards, Rick T.","contributorId":172219,"corporation":false,"usgs":false,"family":"Edwards","given":"Rick","email":"","middleInitial":"T.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":639969,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hood, Eran","contributorId":106802,"corporation":false,"usgs":false,"family":"Hood","given":"Eran","affiliations":[],"preferred":false,"id":639970,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"MacKinnon, Andy","contributorId":172221,"corporation":false,"usgs":false,"family":"MacKinnon","given":"Andy","email":"","affiliations":[],"preferred":false,"id":639971,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McPhee, Megan V.","contributorId":149335,"corporation":false,"usgs":false,"family":"McPhee","given":"Megan","email":"","middleInitial":"V.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":639972,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Patterson, Trista","contributorId":34763,"corporation":false,"usgs":true,"family":"Patterson","given":"Trista","email":"","affiliations":[],"preferred":false,"id":639973,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Suring, Lowell H.","contributorId":172223,"corporation":false,"usgs":false,"family":"Suring","given":"Lowell","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":639974,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Tallmon, David","contributorId":145920,"corporation":false,"usgs":false,"family":"Tallmon","given":"David","affiliations":[{"id":16298,"text":"University of Alaska Southeast","active":true,"usgs":false}],"preferred":false,"id":639975,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wipfli, Mark S. 0000-0002-4856-6068 mwipfli@usgs.gov","orcid":"https://orcid.org/0000-0002-4856-6068","contributorId":1425,"corporation":false,"usgs":true,"family":"Wipfli","given":"Mark","email":"mwipfli@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637090,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70144544,"text":"70144544 - 2015 - “Points requiring elucidation” about Hawaiian volcanism","interactions":[],"lastModifiedDate":"2021-02-17T22:41:21.781098","indexId":"70144544","displayToPublicDate":"2015-02-27T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5371,"text":"Geophysical Monograph","active":true,"publicationSubtype":{"id":24}},"chapter":"24","title":"“Points requiring elucidation” about Hawaiian volcanism","docAbstract":"<p>Hawaiian volcanoes, which are easily accessed and observed at close range, are among the most studied on the planet and have spurred great advances in the geosciences, from understanding deep Earth processes to forecasting volcanic eruptions. More than a century of continuous observation and study of Hawai&lsquo;i's volcanoes has also sharpened focus on those questions that remain unanswered. Although there is good evidence that volcanism in Hawai&lsquo;i is the result of a high-temperature upwelling plume from the mantle, the source composition and dynamics of the plume are controversial. Eruptions at the surface build the volcanoes of Hawai&lsquo;i, but important topics, including how the volcanoes grow and collapse and how magma is stored and transported, continue to be subjects of intense research. Forecasting volcanic activity is based mostly on pattern recognition, but determining and predicting the nature of eruptions, especially in serving the critical needs of hazards mitigation, require more realistic models and a greater understanding of what drives eruptive activity. These needs may be addressed by better integration among disciplines as well as by developing dynamic physics- and chemistry-based models that more thoroughly relate the physiochemical behavior of Hawaiian volcanism, from the deep Earth to the surface, to geological, geochemical, and geophysical data.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hawaiian volcanoes: From source to surface","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"AGU Chapman Conference","conferenceDate":"August 20-24, 2012","conferenceLocation":"Waikoloa, Hawai'i","language":"English","publisher":"American Geophysical Union; John Wiley & Sons","publisherLocation":"Washington, D.C.","doi":"10.1002/9781118872079.ch24","usgsCitation":"Poland, M.P., 2015, “Points requiring elucidation” about Hawaiian volcanism, chap. 24 <i>of</i> Hawaiian volcanoes: From source to surface: Geophysical Monograph, v. 208, p. 533-562, 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Center","active":true,"usgs":true}],"preferred":false,"id":692157,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Weis, Dominique","contributorId":121531,"corporation":false,"usgs":true,"family":"Weis","given":"Dominique","affiliations":[],"preferred":false,"id":692158,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":127857,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":692183,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70142547,"text":"70142547 - 2015 - Landslide modeling and forecasting—recent progress by the u.s. geological survey","interactions":[],"lastModifiedDate":"2015-10-19T15:08:19","indexId":"70142547","displayToPublicDate":"2015-02-27T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Landslide modeling and forecasting—recent progress by the u.s. geological survey","docAbstract":"<p>Landslide studies by the U.S. Geological Survey (USGS) are focused on two main objectives: scientific understanding and forecasting. The first objective is to gain better understanding of the physical processes involved in landslide initiation and movement. This objective is largely in support of the second objective, to develop predictive capabilities to answer the main hazard questions. Answers to the following six questions are needed to characterize the hazard from landslides: (1) Where will landslides occur? (2) What kind(s) of landslides will occur? (3) When will landslides occur? (4) How big will the landslides be? (5) How fast will the landslides travel? (6) How far will the landslides go? Although these questions are sometimes recast in different terms, such as frequency or recurrence rather than timing (when), the questions or their variants address the spatial, physical, and temporal aspects of landslide hazards. Efforts to develop modeling and forecasting capabilities by the USGS are primarily focused on specific landslide types that pose a high degree of hazard and show relatively high potential for predictability.</p>","largerWorkTitle":"Proceedings of Time to Face the Landslide Hazard Dilemma—Bridging Science, Policy, Public Safety, and Potential Loss","conferenceTitle":"Time to Face the Landslide Hazard Dilemma—Bridging Science, Policy, Public Safety, and Potential Loss","conferenceDate":"February 26-27, 2015","conferenceLocation":"Seattle, Washington","language":"English","publisher":"Association of Environmental and Engineering Geologists","usgsCitation":"Baum, R.L., and Kean, J.W., 2015, Landslide modeling and forecasting—recent progress by the u.s. geological survey, <i>in</i> Proceedings of Time to Face the Landslide Hazard Dilemma—Bridging Science, Policy, Public Safety, and Potential Loss, Seattle, Washington, February 26-27, 2015, p. 57-64.","productDescription":"8 p.","startPage":"57","endPage":"64","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062927","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":310075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298335,"type":{"id":15,"text":"Index Page"},"url":"https://www.aegweb.org/docs/default-source/events/aeg-ls-forum-program-abstracts.pdf"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56261475e4b0fb9a11dd7638","contributors":{"authors":[{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":541950,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":541951,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70142998,"text":"70142998 - 2015 - Wide-ranging phylogeographic structure of invasive red lionfish in the Western Atlantic and Greater Caribbean","interactions":[],"lastModifiedDate":"2016-11-22T18:37:58","indexId":"70142998","displayToPublicDate":"2015-02-26T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"title":"Wide-ranging phylogeographic structure of invasive red lionfish in the Western Atlantic and Greater Caribbean","docAbstract":"<p class=\"Para\">The red lionfish (<i class=\"EmphasisTypeItalic \">Pterois volitans</i>) is an invasive predatory marine fish that has rapidly expanded its presence in the Western Hemisphere. We collected 214 invasive red lionfish samples from nine countries and territories, including seven unpublished locations. To more comprehensively evaluate connectivity, we compiled our d-loop sequence&nbsp;data with 846 published sequences, resulting in 1,060 samples from 14 locations. We found low nucleotide diversity (<i class=\"EmphasisTypeItalic \">π</i>&nbsp;=&nbsp;0.003) and moderate haplotype diversity (<i class=\"EmphasisTypeItalic \">h</i>&nbsp;=&nbsp;0.59). Using haplotype population pairwise <i class=\"EmphasisTypeItalic \">Φ</i><sub>ST</sub> tests, we analyzed possible phylogeographic breaks that were previously proposed based on other reef organisms. We found support for the Bahamas/Turks/Caicos versus Caribbean break (<i class=\"EmphasisTypeItalic \">Φ</i><sub>ST</sub>&nbsp;=&nbsp;0.12) but not for the Northwestern Caribbean, Eastern Caribbean, or US East Coast versus Bahamas breaks. The Northern Region had higher variation and more haplotypes, supporting introductions of at least five haplotypes to the region. Our wide-ranging samples showed that a lower-frequency haplotype in the Northern Region dominated the Southern Region and suggested multiple introductions, possibly to the south. We tested multiple scenarios of phylogeographic structure with analyses of molecular variance and found support for a Northern and Southern Region split at the Bahamas/Turks/Caicos versus Caribbean break (percentage of variation among regions&nbsp;=&nbsp;8.49&nbsp;%). We found that Puerto Rico clustered with the Southern Region more strongly than with the Northern Region, as opposed to previous reports. We also found the rare haplotype H03 for the first time in the southern Caribbean (Panama), indicating that either secondary releases occurred or that the low-frequency haplotypes have had time to disperse to extreme southern Caribbean locations.</p><div class=\"HeaderArticleNotes\"><br data-mce-bogus=\"1\"></div>","language":"English","publisher":"Springer-Verlag Heidelberg","doi":"10.1007/s00227-015-2623-y","usgsCitation":"Butterfield, J.S., Diaz-Ferguson, E., Silliman, B.R., Saunders, J.W., Buddo, D., Mignucci-Giannoni, A., Searle, L., Allen, A.C., and Hunter, M., 2015, Wide-ranging phylogeographic structure of invasive red lionfish in the Western Atlantic and Greater Caribbean: Marine Biology, v. 162, no. 4, p. 773-781, https://doi.org/10.1007/s00227-015-2623-y.","productDescription":"9 p.","startPage":"773","endPage":"781","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059439","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":298621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"162","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-26","publicationStatus":"PW","scienceBaseUri":"55095034e4b02e76d757e639","contributors":{"authors":[{"text":"Butterfield, John S. jbutterfield@usgs.gov","contributorId":5593,"corporation":false,"usgs":true,"family":"Butterfield","given":"John","email":"jbutterfield@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":542400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diaz-Ferguson, Edgardo","contributorId":139668,"corporation":false,"usgs":false,"family":"Diaz-Ferguson","given":"Edgardo","email":"","affiliations":[{"id":12873,"text":"U.S. Fish and Wildlife Service, Conservation Genetics Laboratory, Warm Springs, Georgia","active":true,"usgs":false}],"preferred":false,"id":542402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silliman, Brian R.","contributorId":53659,"corporation":false,"usgs":true,"family":"Silliman","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":542403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Jonathan W.","contributorId":91378,"corporation":false,"usgs":true,"family":"Saunders","given":"Jonathan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":542491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buddo, Dayne","contributorId":139669,"corporation":false,"usgs":false,"family":"Buddo","given":"Dayne","email":"","affiliations":[{"id":12874,"text":"Centre for Marine Sciences, University of the West Indies, Queen’s Highway, P.O Box 35, Discovery Bay, St. Ann, Jamaica","active":true,"usgs":false}],"preferred":false,"id":542404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mignucci-Giannoni, Antonio A.","contributorId":53645,"corporation":false,"usgs":true,"family":"Mignucci-Giannoni","given":"Antonio A.","affiliations":[],"preferred":false,"id":542405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Searle, Linda","contributorId":139670,"corporation":false,"usgs":false,"family":"Searle","given":"Linda","email":"","affiliations":[{"id":12875,"text":"ECOMAR, PO Box 1234 Belize City, Belize","active":true,"usgs":false}],"preferred":false,"id":542406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allen, Aarin Conrad","contributorId":139671,"corporation":false,"usgs":false,"family":"Allen","given":"Aarin","email":"","middleInitial":"Conrad","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":542407,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hunter, Margaret E. 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":139667,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret E.","email":"mhunter@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":542401,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70133470,"text":"sir20145215 - 2015 - Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2015-02-26T11:49:18","indexId":"sir20145215","displayToPublicDate":"2015-02-26T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5215","title":"Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project","docAbstract":"<p>Groundwater quality in the 633-square-mile (1,639-square-kilometer) Northern Coast Ranges (NOCO) study unit was investigated as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program and the U.S. Geological Survey (USGS) National Water-Quality Assessment Program. The study unit is composed of two study areas (Interior Basins and Coastal Basins) and is located in northern California in Napa, Sonoma, Lake, Colusa, Mendocino, Glenn, Humboldt, and Del Norte Counties. The GAMA-PBP is being conducted by the California State Water Resources Control Board in collaboration with the USGS and the Lawrence Livermore National Laboratory.</p>\n<p>The GAMA NOCO study was designed to provide a spatially unbiased assessment of the quality of untreated (ambient) groundwater in the primary aquifer system within the study unit. The assessment is based on water-quality and ancillary data collected in 2009 by the USGS from 58 sites and on water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer system is defined by the perforation intervals of sites listed in the CDPH water-quality database for the NOCO study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallow or deep water-bearing zones.</p>\n<p>The first component of this study, the&nbsp;<i>status assessment</i>&nbsp;of the current quality of the groundwater resource, was performed by using data from samples analyzed for inorganic constituents (such as trace elements and major and minor ions), organic constituents (volatile organic compounds and pesticides and pesticide degradates), the special-interest constituent perchlorate, and microbial indicators. This status assessment is intended to characterize the quality of groundwater resources in the primary aquifer system of the NOCO study unit, not the quality of treated drinking water delivered to consumers by water purveyors.</p>\n<p><i>Relative-concentrations</i>&nbsp;(sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or nonregulatory benchmarks for drinking-water quality. A relative-concentration greater than (&gt;) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (&le;) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents and perchlorate were classified as &ldquo;high&rdquo; (relative-concentration &gt;1.0), &ldquo;moderate&rdquo; (0.1 &lt; relative-concentration &le;1.0), or &ldquo;low&rdquo; (relative-concentration &le;0.1). Relative-concentrations of inorganic constituents were classified as &ldquo;high&rdquo; (relative-concentration &gt;1.0), &ldquo;moderate&rdquo; (0.5 &lt; relative-concentration &le;1.0), or &ldquo;low&rdquo; (relative-concentration &le;0.5).</p>\n<p><i>Aquifer-scale proportion</i>&nbsp;was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion was defined as the percentage of the area of the primary aquifer system with a relative-concentration &gt;1.0 for a particular constituent or class of constituents; the percentage is based on an aerial rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifer system with moderate and low relative-concentrations, respectively. Two statistical approaches&mdash;grid-based and spatially weighted&mdash;were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the NOCO study unit (within 90 percent confidence intervals).</p>\n<p>Inorganic constituents (one or more) with health-based benchmarks were detected at high relative-concentrations in 10.3 percent and at moderate relative-concentrations in 13.8 percent of the primary aquifer system. The high aquifer-scale proportion of inorganic constituents primarily reflected high aquifer-scale proportions of boron (in 8.6 percent of the primary aquifer system), arsenic (in 3.4 percent), and barium (in 1.7 percent). Inorganic constituents with aesthetic-based benchmarks were detected at high relative-concentrations in 39.7 percent and at moderate relative-concentrations in 10.3 percent of the primary aquifer system. The constituents present at high relative-concentrations were iron (25.9 percent) and manganese (39.7 percent).</p>\n<p>Relative-concentrations of organic constituents with health-based benchmarks (one or more) were high in 0.2 percent, moderate in 1.7 percent, and low in 39.7 percent of the primary aquifer system. Organic constituents were not detected in 58.4 percent of the primary aquifer system. Of the 168 organic constituents analyzed, 11 constituents were detected. Two organic constituents had detection frequencies &gt;10 percent: the trihalomethane chloroform and the herbicide simazine. For the 10 detected organic constituents that had health-based benchmarks, nearly all detections had low relative-concentrations. The special-interest constituent perchlorate was detected at moderate relative-concentrations in 1.7 percent and at low relative-concentrations in 22.4 percent of the primary aquifer system. Perchlorate was not detected in 75.9 percent of the primary aquifer system.</p>\n<p>The second component of this study, the&nbsp;<i>understanding assessment</i>, evaluated relations between constituent concentrations and values of selected potential explanatory factors to identify the factors potentially affecting the concentrations and occurrences of constituents found at high relative-concentrations or, for organic constituents, with detection frequencies &gt;10 percent. The potential explanatory factors evaluated were land use (including density of septic tanks and leaking or formerly leaking underground fuel tanks), well construction (well depth and depth to the top of the perforated interval in the well), hydrologic conditions (aridity index, field water temperature, and distance to nearest hot spring and geothermal well), pH, dissolved oxygen concentration, study area, groundwater age distribution, and geochemical conditions.</p>\n<p>High and moderate relative-concentrations of boron primarily occurred in the Interior Basins study area and may be attributed to groundwater interacting with hydrothermal systems. High and moderate relative-concentrations of boron were associated with elevated groundwater temperatures, groundwater chemistry characteristics similar to those of geothermal waters, and distance to known geothermal areas. Boron concentrations generally were higher where low dissolved oxygen concentrations or anoxic conditions exist. High and moderate relative-concentrations of arsenic predominantly occur in the Interior Basins study area under reducing conditions. Arsenic concentrations also may be influenced by hydrothermal systems (when present).</p>\n<p>Chloroform, simazine, and perchlorate were observed in the Interior Basins and Coastal Basins study areas, predominantly at shallow sites with top-of-perforation depths &le;70 feet below land surface, with modern water (post-1950s), and with oxic groundwater conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145215","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and the U.S. Geological Survey National Water-Quality Assessment Program","usgsCitation":"Mathany, T.M., and Belitz, K., 2015, Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5215, x, 86 p., https://doi.org/10.3133/sir20145215.","productDescription":"x, 86 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2009-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-030141","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145215.jpg"},{"id":298169,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5215/pdf/sir2014-5215.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298148,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5215/"}],"country":"United States","state":"California","county":"Colusa County, Del Norte County, Glenn County, Humboldt County, Lake County, Mendocino County, Napa County, Sonoma County","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -124.541015625,\n              38.66835610151509\n            ],\n            [\n              -124.541015625,\n              41.96765920367816\n            ],\n            [\n              -121.79443359375,\n              41.96765920367816\n            ],\n            [\n              -121.79443359375,\n              38.66835610151509\n            ],\n            [\n              -124.541015625,\n              38.66835610151509\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publicComments":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043afe4b02419550ce86c","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113 tmathany@usgs.gov","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":1713,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy","email":"tmathany@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":541550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"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":541551,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70116921,"text":"ofr20141109 - 2015 - GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids","interactions":[],"lastModifiedDate":"2015-02-26T10:52:37","indexId":"ofr20141109","displayToPublicDate":"2015-02-26T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1109","title":"GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids","docAbstract":"<p><span>GRIDGEN is a computer program for creating layered quadtree grids for use with numerical models, such as the MODFLOW&ndash;USG program for simulation of groundwater flow. The program begins by reading a three-dimensional base grid, which can have variable row and column widths and spatially variable cell top and bottom elevations. From this base grid, GRIDGEN will continuously divide into four any cell intersecting user-provided refinement features (points, lines, and polygons) until the desired level of refinement is reached. GRIDGEN will then smooth, or balance, the grid so that no two adjacent cells, including overlying and underlying cells, differ by more than a user-specified level tolerance. Once these gridding processes are completed, GRIDGEN saves a tree structure file so that the layered quadtree grid can be quickly reconstructed as needed. Once a tree structure file has been created, GRIDGEN can then be used to (1) export the layered quadtree grid as a shapefile, (2) export grid connectivity and cell information as ASCII text files for use with MODFLOW&ndash;USG or other numerical models, and (3) intersect the grid with shapefiles of points, lines, or polygons, and save intersection output as ASCII text files and shapefiles. The GRIDGEN program is demonstrated by creating a layered quadtree grid for the Biscayne aquifer in Miami-Dade County, Florida, using hydrologic features to control where refinement is added.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141109","collaboration":"Prepared in cooperation with George Mason University","usgsCitation":"Lien, J., Liu, G., and Langevin, C.D., 2015, GRIDGEN Version 1.0: a computer program for generating unstructured finite-volume grids: U.S. Geological Survey Open-File Report 2014-1109, vi, 26 p., https://doi.org/10.3133/ofr20141109.","productDescription":"vi, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055584","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":298168,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141109.jpg"},{"id":298166,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1109/"},{"id":298167,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1109/pdf/ofr2014-1109.pdf","text":"Report","size":"1.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aae4b02419550ce862","contributors":{"authors":[{"text":"Lien, Jyh-Ming","contributorId":139494,"corporation":false,"usgs":true,"family":"Lien","given":"Jyh-Ming","email":"","affiliations":[],"preferred":false,"id":541557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Gaisheng","contributorId":15158,"corporation":false,"usgs":true,"family":"Liu","given":"Gaisheng","email":"","affiliations":[],"preferred":false,"id":541558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":519055,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70141633,"text":"pp1650G - 2015 - Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: <i>Revisions for all taxa from the United States and Canada and new taxa from the western United States</i>","interactions":[],"lastModifiedDate":"2023-08-29T14:10:23.523993","indexId":"pp1650G","displayToPublicDate":"2015-02-26T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1650","chapter":"G","title":"Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: <i>Revisions for all taxa from the United States and Canada and new taxa from the western United States</i>","docAbstract":"<p>This is the seventh volume in an atlas series that explores the relations between the geographic distributions of woody plant species and climatic variables in North America. A 25-kilometer (km) equal-area grid of modern climatic and bioclimatic variables was constructed from weather data. The geographic distributions of selected tree and shrub species were digitized, and the presence or absence of each species was determined for each point on the 25-km grid, thus providing a basis for comparing climatic data and species' distributions. The relations between climate and plant distributions are presented in graphical and tabular form. The results of this effort are intended primarily for use in biogeographic, ecologic, paleoclimatic, and global-change research.</p>\n<p>This volume of the atlas provides numerous changes, updates, and enhancements from previous volumes. Its geographic coverage is now restricted to Canada and the continental United States, and the source and time period of the climatic data have changed. New variables were added, including monthly values for temperature and precipitation, and measures of interannual variability. The distribution maps for all previously published species were redigitized, some distribution maps were revised, and 148 new species were added from the arid and semiarid western United States. The graphical displays were expanded to illustrate the new climatic variables, and the data tables were modified to provide more detail on the population distributions of plant taxa relative to climatic variables.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1650G","usgsCitation":"Thompson, R.S., Anderson, K.H., Pelltier, R.T., Strickland, L.E., Shafer, S.L., Bartlein, P.J., and McFadden, A., 2015, Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: <i>Revisions for all taxa from the United States and Canada and new taxa from the western United States</i>: U.S. Geological Survey Professional Paper 1650, HTML Document; Downloads Directory, https://doi.org/10.3133/pp1650G.","productDescription":"HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-048941","costCenters":[{"id":318,"text":"Geosciences and Environmental 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Current address:  TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":541547,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70141966,"text":"70141966 - 2015 - Wildlife, urban inputs, and landscape configuration are responsible for degraded swimming water quality at an embayed beach","interactions":[],"lastModifiedDate":"2015-02-25T12:49:21","indexId":"70141966","displayToPublicDate":"2015-02-25T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Wildlife, urban inputs, and landscape configuration are responsible for degraded swimming water quality at an embayed beach","docAbstract":"<p><span>Jeorse Park Beach, on southern Lake Michigan, experiences frequent closures due to high&nbsp;</span><i>Escherichia coli&nbsp;</i><span>(</span><i>E. coli</i><span>) levels since regular monitoring was implemented in 2005. During the summer of 2010, contaminant source tracking techniques, such as the conventional microbial and physical surveys and hydrodynamic models, were used to determine the reasons for poor water quality at Jeorse Park. Fecal indicator bacteria (</span><i>E. coli</i><span>, enterococci) were high throughout the season, with densities ranging from 12&ndash;2419 (culturable&nbsp;</span><i>E. coli</i><span>) and 1&ndash;2550 and &lt;&nbsp;1&ndash;5831 (culturable and qPCR enterococci, respectively). Genetic markers for human (</span><i>Bacteroides</i><span>&nbsp;HF183) and gull (</span><i>Catellicoccus marimammalium</i><span>) fecal contamination were found in 15% and 37% of the samples indicating multiple sources contributing to poor water quality. Nesting colonies of double-crested cormorants (</span><i>Phalacrocorax auritus</i><span>) have steadily increased since 2005, coinciding with high&nbsp;</span><i>E. coli</i><span>levels. A hydrodynamic model indicated that limited circulation allows bacteria entering the embayed area to be retained in nearshore areas; and bacterial resuspension from sand and stranded beach wrack during storm events compounds the problem. The integration of hydrodynamics, expanded use of chemical and biological markers, as well as more complex statistical multivariate techniques can improve microbial source tracking, informing management actions to improve recreational water quality. Alterations to embayed structures to improve circulation and reduce nuisance algae as well as growing native plants to retain sand to improve beach morphometry are among some of the restoration strategies under consideration in ongoing multi-agency collaborations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2014.11.027","usgsCitation":"Byappanahalli, M.N., Nevers, M., Whitman, R.L., Ge, Z., Shively, D.A., Spoljaric, A., and Przybyla-Kelly, K., 2015, Wildlife, urban inputs, and landscape configuration are responsible for degraded swimming water quality at an embayed beach: Journal of Great Lakes Research, v. 41, no. 1, p. 156-163, https://doi.org/10.1016/j.jglr.2014.11.027.","productDescription":"8 p.","startPage":"156","endPage":"163","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056382","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":298142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Lake Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.4563217163086,\n              41.631995715210444\n            ],\n            [\n              -87.4563217163086,\n              41.6916296425077\n            ],\n            [\n              -87.39160537719727,\n              41.6916296425077\n            ],\n            [\n              -87.39160537719727,\n              41.631995715210444\n            ],\n            [\n              -87.4563217163086,\n              41.631995715210444\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54eef22ae4b02d776a684b0b","contributors":{"authors":[{"text":"Byappanahalli, Muruleedhara N. byappan@usgs.gov","contributorId":139462,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","middleInitial":"N.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":541525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ge, Zhongfu","contributorId":139463,"corporation":false,"usgs":false,"family":"Ge","given":"Zhongfu","email":"","affiliations":[{"id":12773,"text":"American Bureau of Shipping, Corporate Marine Technology","active":true,"usgs":false}],"preferred":false,"id":541528,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shively, Dawn A. dshively@usgs.gov","contributorId":2051,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spoljaric, Ashley 0000-0001-6262-030X aspoljaric@usgs.gov","orcid":"https://orcid.org/0000-0001-6262-030X","contributorId":139464,"corporation":false,"usgs":true,"family":"Spoljaric","given":"Ashley","email":"aspoljaric@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541530,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Przybyla-Kelly, Katarzyna kprzybyla-kelly@usgs.gov","contributorId":3613,"corporation":false,"usgs":true,"family":"Przybyla-Kelly","given":"Katarzyna","email":"kprzybyla-kelly@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":541531,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70141967,"text":"70141967 - 2015 - The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes","interactions":[],"lastModifiedDate":"2018-04-02T15:24:19","indexId":"70141967","displayToPublicDate":"2015-02-25T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes","docAbstract":"<p><span>Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330&nbsp;m</span><sup>2</sup><span>&nbsp;surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.</span></p>","conferenceTitle":"46th Annual Binghamton Geomorphology Symposium","conferenceDate":"September 18-20, 2015","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2015.01.020","usgsCitation":"Pangle, L.A., DeLong, S.B., Abramson, N., Adams, J., Barron-Gafford, G.A., Breshears, D.D., Brooks, P.D., Chorover, J., Dietrich, W., Dontsova, K., Durcik, M., Espeleta, J., Ferre, T., Ferriere, R., Henderson, W., Hunt, E.A., Huxman, T.E., Millar, D., Murphy, B., Niu, G., Pavao-Zuckerman, M., Pelletier, J.D., Rasmussen, C., Ruiz, J., Saleska, S., Schaap, M., Sibayan, M., Troch, P.A., Tuller, M., van Haren, J., and Zeng, X., 2015, The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes: Geomorphology, v. 244, p. 190-203, 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,{"id":70141968,"text":"70141968 - 2015 - Large-scale dam removal on the Elwha River, Washington, USA: river channel and floodplain geomorphic change","interactions":[],"lastModifiedDate":"2017-05-04T10:57:38","indexId":"70141968","displayToPublicDate":"2015-02-25T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale dam removal on the Elwha River, Washington, USA: river channel and floodplain geomorphic change","docAbstract":"<p>A substantial increase in fluvial sediment supply relative to transport capacity causes complex, large-magnitude changes in river and floodplain morphology downstream. Although sedimentary and geomorphic responses to sediment pulses are a fundamental part of landscape evolution, few opportunities exist to quantify those processes over field scales. We investigated the downstream effects of sediment released during the largest dam removal in history, on the Elwha River, Washington, USA, by measuring changes in riverbed elevation and topography, bed sediment grain size, and channel planform as two dams were removed in stages over two years.</p>\n<p>As 10.5&nbsp;million&nbsp;t (7.1&nbsp;million&nbsp;m<sup>3</sup>) of sediment was released from two former reservoirs, downstream dispersion of a sediment wave caused widespread bed aggradation of ~&nbsp;1&nbsp;m (greater where pools filled), changed the river from pool&ndash;riffle to braided morphology, and decreased the slope of the lowermost river. The newly deposited sediment, which was finer than most of the pre-dam-removal bed, formed new bars (largely pebble, granule, and sand material), prompting aggradational channel avulsion that increased the channel braiding index by almost 50%. As a result of mainstem bed aggradation, floodplain channels received flow and accumulated new sediment even during low to moderate flow conditions. The river system showed a two- to tenfold greater geomorphic response to dam removal (in terms of bed elevation change magnitude) than it had to a 40-year flood event four years before dam removal. Two years after dam removal began, as the river had started to incise through deposits of the initial sediment wave, ~&nbsp;1.2&nbsp;million&nbsp;t of new sediment (~&nbsp;10% of the amount released from the two reservoirs) was stored along 18&nbsp;river&nbsp;km of the mainstem channel and 25&nbsp;km of floodplain channels. The Elwha River thus was able to transport most of the released sediment to the river mouth. The geomorphic alterations and changing bed sediment grain size along the Elwha River have important ecological implications, affecting aquatic habitat structure, benthic fauna, salmonid fish spawning and rearing potential, and riparian vegetation. The response of the river to dam removal represents a unique opportunity to observe and quantify fundamental geomorphic processes associated with a massive sediment influx, and also provides important lessons for future river-restoration endeavors.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2014.08.028","usgsCitation":"East, A., Pess, G.R., Bountry, J.A., Magirl, C.S., Ritchie, A., Logan, J.B., Randle, T.J., Mastin, M.C., Minear, J.T., Duda, J., Liermann, M.C., McHenry, M.L., Beechie, T.J., and Shafroth, P.B., 2015, Large-scale dam removal on the Elwha River, Washington, USA: river channel and floodplain geomorphic change: Geomorphology, v. 228, p. 765-786, https://doi.org/10.1016/j.geomorph.2014.08.028.","productDescription":"22 p.","startPage":"765","endPage":"786","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068997","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science 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,{"id":70141965,"text":"70141965 - 2015 - Toxicity of sediments from lead-zinc mining areas to juvenile freshwater mussels (Lampsilis siliquoidea) compared to standard test organisms","interactions":[],"lastModifiedDate":"2018-09-04T15:34:38","indexId":"70141965","displayToPublicDate":"2015-02-25T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Toxicity of sediments from lead-zinc mining areas to juvenile freshwater mussels (<i>Lampsilis siliquoidea</i>) compared to standard test organisms","title":"Toxicity of sediments from lead-zinc mining areas to juvenile freshwater mussels (Lampsilis siliquoidea) compared to standard test organisms","docAbstract":"<p><span>Sediment toxicity tests compared chronic effects on survival, growth, and biomass of juvenile freshwater mussels (28-d exposures with </span><i>Lampsilis siliquoidea</i><span>) to the responses of standard test organisms&mdash;amphipods (28-d exposures with<span>&nbsp;</span></span><i>Hyalella azteca</i><span>) and midges (10-d exposures with<span>&nbsp;</span></span><i>Chironomus dilutus</i><span>)&mdash;in sediments from 2 lead&ndash;zinc mining areas: the Tri-State Mining District and Southeast Missouri Mining District. Mussel tests were conducted in sediments sieved to &lt;0.25&thinsp;mm to facilitate recovery of juvenile mussels (2&ndash;4 mo old). Sediments were contaminated primarily with lead, zinc, and cadmium, with greater zinc and cadmium concentrations in Tri-State sediments and greater lead concentrations in southeast Missouri sediments. The frequency of highly toxic responses (reduced 10% or more relative to reference sites) in Tri-State sediments was greatest for amphipod survival (25% of samples), midge biomass (20%), and mussel survival (14%). In southeast Missouri sediments, the frequency of highly toxic samples was greatest for mussel biomass (25%) and amphipod biomass (13%). Thresholds for metal toxicity to mussels, expressed as hazard quotients based on probable effect concentrations, were lower for southeast Missouri sediments than for Tri-State sediments. Southeast Missouri sites with toxic sediments had 2 or fewer live mussel taxa in a concurrent mussel population survey, compared with 7 to 26 taxa at reference sites. These results demonstrate that sediment toxicity tests with juvenile mussels can be conducted reliably by modifying existing standard methods; that the sensitivity of mussels to metals can be similar to or greater than standard test organisms; and that responses of mussels in laboratory toxicity tests are consistent with effects on wild mussel populations.</span></p>","language":"English","publisher":"John Wiley & Sons, Inc.","doi":"10.1002/etc.2849","usgsCitation":"Besser, J.M., Ingersoll, C.G., Brumbaugh, W.G., Kemble, N.E., May, T.W., Wang, N., MacDonald, D., and Roberts, A.D., 2015, Toxicity of sediments from lead-zinc mining areas to juvenile freshwater mussels (Lampsilis siliquoidea) compared to standard test organisms: Environmental Toxicology and Chemistry, v. 34, no. 3, p. 626-639, https://doi.org/10.1002/etc.2849.","productDescription":"14 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nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":541447,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"MacDonald, Donald D.","contributorId":49911,"corporation":false,"usgs":true,"family":"MacDonald","given":"Donald D.","affiliations":[],"preferred":false,"id":541448,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roberts, Andrew D.","contributorId":52304,"corporation":false,"usgs":true,"family":"Roberts","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":541449,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70156181,"text":"70156181 - 2015 - A plant toxin mediated mechanism for the lag in snowshoe hare population recovery following cyclic declines","interactions":[],"lastModifiedDate":"2019-07-25T15:04:27","indexId":"70156181","displayToPublicDate":"2015-02-25T01:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"A plant toxin mediated mechanism for the lag in snowshoe hare population recovery following cyclic declines","docAbstract":"<p>A necessary condition for a snowshoe hare population to cycle is reduced reproduction after the population declines. But the cause of a cyclic snowshoe hare population's reduced reproduction during the low phase of the cycle, when predator density collapses, is not completely understood. We propose that moderate-severe browsing by snowshoe hares upon preferred winter-foods could increase the toxicity of some of the hare's best winter-foods during the following hare low, with the result being a decline in hare nutrition that could reduce hare reproduction. We used a combination of modeling and experiments to explore this hypothesis. Using the shrub birch <i>Betula glandulosa</i> as the plant of interest, the model predicted that browsing by hares during a hare cycle peak, by increasing the toxicity <i>B. glandulosa</i> twigs during the following hare low, could cause a hare population to cycle. The model's assumptions were verified with assays of dammarane triterpenes in segments of <i>B. glandulosa</i> twigs and captive hare feeding experiments conducted in Alaska during February and March 1986. The model's predictions were tested with estimates of hare density and measurements of <i>B. glandulosa</i> twig growth made at Kluane, Yukon from 1988&ndash;2008. The empirical tests supported the model's predictions. Thus, we have concluded that a browsing-caused increase in twig toxicity that occurs during the hare cycle's low phase could reduce hare reproduction during the low phase of the hare cycle.</p>","language":"English","publisher":"Wiley","doi":"10.1111/oik.01671","usgsCitation":"DeAngelis, D., Bryant, J.P., Liu, R., Gourley, S.A., Krebs, C., and Reichardt, P.B., 2015, A plant toxin mediated mechanism for the lag in snowshoe hare population recovery following cyclic declines: Oikos, v. 124, no. 6, p. 796-805, https://doi.org/10.1111/oik.01671.","productDescription":"10 p.","startPage":"796","endPage":"805","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056126","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":306815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Yukon","otherGeospatial":"Kluane","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -141.04248046875,\n              59.789579955087405\n            ],\n            [\n              -141.04248046875,\n              61.95961583829658\n            ],\n            [\n              -134.97802734374997,\n              61.95961583829658\n            ],\n            [\n              -134.97802734374997,\n              59.789579955087405\n            ],\n            [\n              -141.04248046875,\n              59.789579955087405\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"124","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-25","publicationStatus":"PW","scienceBaseUri":"55d305abe4b0518e35468cd4","contributors":{"authors":[{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":138934,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":567938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bryant, John P.","contributorId":39227,"corporation":false,"usgs":false,"family":"Bryant","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":567939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Rongsong","contributorId":43480,"corporation":false,"usgs":false,"family":"Liu","given":"Rongsong","email":"","affiliations":[],"preferred":false,"id":567940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gourley, Stephen A.","contributorId":60487,"corporation":false,"usgs":true,"family":"Gourley","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":567941,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krebs, Charles J","contributorId":146456,"corporation":false,"usgs":false,"family":"Krebs","given":"Charles J","affiliations":[{"id":16701,"text":"Dept. of Zoology, University of British Columbia, Vancouver","active":true,"usgs":false}],"preferred":false,"id":567942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reichardt, Paul B","contributorId":146457,"corporation":false,"usgs":false,"family":"Reichardt","given":"Paul","email":"","middleInitial":"B","affiliations":[{"id":16702,"text":"Dept. of Chemistry and Biochemistry, University of Alaska, Fairbanks","active":true,"usgs":false}],"preferred":false,"id":567943,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70141845,"text":"sir20145241 - 2015 - Conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers, Pine Ridge Indian Reservation area, South Dakota, water years 1980-2009","interactions":[],"lastModifiedDate":"2017-10-12T20:05:15","indexId":"sir20145241","displayToPublicDate":"2015-02-23T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5241","title":"Conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers, Pine Ridge Indian Reservation area, South Dakota, water years 1980-2009","docAbstract":"<p>The Ogallala and Arikaree aquifers are the largest sources of groundwater on the Pine Ridge Indian Reservation and are used extensively for irrigation and public and domestic water supplies. To assess the potential for decreased water levels and discharge to streams in the Pine Ridge Indian Reservation, conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers in southwestern South Dakota were developed by the U.S. Geological Survey in cooperation with the Oglala Sioux Tribe. The study area includes most of the Pine Ridge Reservation in Jackson and Shannon Counties and Indian trust lands in Bennett County in southwestern South Dakota.</p>\n<p>The High Plains aquifer, which includes the Ogallala and Arikaree aquifers, generally is less developed in South Dakota compared with other areas underlain by this aquifer; therefore, water levels in the High Plains aquifer in South Dakota generally fluctuated by less than 5 feet (ft) from 1980 to 1999. Despite minimal water-level changes in the High Plains aquifer in South Dakota, extensive withdrawals of groundwater for irrigation have caused water-level declines in many areas and increased concerns about the long-term sustainability of the aquifer; therefore, continued or increased withdrawals from the aquifer or prolonged drought may have the potential to affect water levels within the aquifer and discharge to important streams in the area.</p>\n<p>The Ogallala and Arikaree aquifers generally consist of poorly consolidated claystones, siltstones, sandstones, and shale deposited in fluvial and lacustrine environments. Saturated thicknesses ranged from 10 to 314 ft for the Ogllala aquifer and from 10 to 862 ft for the Arikaree aquifer. Previous hydraulic conductivity estimates ranged from less than 1 to 180 feet per day (ft/d) for the Ogallala aquifer and from less than 1 to 13 ft/d for the Arikaree aquifer.</p>\n<p>Recharge to the Ogallala and Arikaree aquifers is from precipitation on the outcrop areas, and discharge occurs through evapotranspiration, discharge to streams, and well withdrawals. Evapotranspiration generally occurs in topographically low areas along streams, and maximum evapotranspiration occurs when the water level is at the land surface.</p>\n<p>The generalized groundwater-flow direction is to the northeast with local flow towards streams. Precipitation for water years 1980&ndash;2009 ranged from about 11 to 39 inches per year (in/yr) and averaged about 19 in/yr. Estimated mean recharge for water years 1980&ndash;2009 was about 17.3 percent of precipitation for the Ogallala aquifer and 7.9 percent of precipitation for the Arikaree aquifer. The estimated mean maximum evapotranspiration for water years 1980&ndash;2009 was about 35 in/yr. Estimated mean base flow for gaged streams was about 0.06 cubic foot per second (ft<sup>3</sup>/s) per square mile of drainage area. Estimated mean total water use for water years 1980&ndash;2009 was 5.4 ft<sup>3</sup>/s from the Ogallala aquifer and 7.1 ft<sup>3</sup>/s from the Arikaree aquifer.</p>\n<p>A two-layer numerical groundwater-flow model was constructed using MODFLOW&ndash;NWT with a uniformly spaced grid consisting of 166 rows and 288 columns with cells 1,640 ft on a side. The numerical model of the Ogallala and Arikaree aquifers was used to simulate steady-state and transient conditions for water years 1980&ndash;2009. Model calibration was accomplished using the Parameter ESTimation (PEST) program that adjusted individual model input parameters and assessed the difference between estimated and model-simulated values of hydraulic head and base flow. Aquifer boundaries were no-flow on the northern and western sides and constant-head on the southern and eastern sides. The mean arithmetic difference was 1.4 ft between the 731 simulated and observed hydraulic heads in the Ogallala aquifer and 9.8 ft between the 2,754 simulated and observed hydraulic heads in the Arikaree aquifer. Simulated mean discharge from the Ogallala and Arikaree aquifers to selected stream reaches was 92.1 ft<sup>3</sup>/s compared to estimated discharge of 88.7 ft<sup>3</sup>/s.</p>\n<p>Calibrated recharge for the transient simulation averaged 3.3 in/yr for the Ogallala aquifer and 1.1 in/yr for the Arikaree aquifer. The mean maximum potential evapotranspiration rate was 35.4 in/yr. Streambed conductance for perennial stream reaches averaged 530 feet squared per day. Horizontal hydraulic conductivity averaged 27 ft/d for the Ogallala aquifer and 1.0 ft/d for the Arikaree aquifer. The vertical hydraulic conductivity averaged 1.4 ft/d for the Ogallala aquifer and 0.004 ft/d for the Arikaree aquifer. Specific yield for the Ogallala aquifer was 0.15 (dimensionless) and averaged 0.02 for the Arikaree aquifer. Specific storage for the Arikaree aquifer was 1.7x10<sup>-6</sup>&nbsp;per foot. Simulated steady-state model inflow and outflow was 459 ft<sup>3</sup>/s. The percentages of inflows were 17 percent from constant-head boundaries, 9 percent from streams, and 74 percent from recharge. Percentages of outflow were 8 percent to constant-head boundaries, 1 percent to wells, 31 percent to streams, and 59 percent to evapotranspiration. Simulated net inflow from the Ogallala aquifer to the Arikaree aquifer ranged from about 22 ft<sup>3</sup>/s in dry years to about 37 ft<sup>3</sup>/s in wet years.</p>\n<p>Two hypothetical future stress scenarios were simulated using input from the 30-year calibrated simulation of water years 1980&ndash;2009. The first hypothetical scenario represented an increase in groundwater withdrawals from 50 hypothetical production wells completed in the Arikaree aquifer. At the end of the 30-year hypothetical increased pumping simulation, water levels declined as much as 66 ft in the Arikaree aquifer, decreased discharge to streams accounted for about 26 percent (2.6 ft<sup>3</sup>/s) of increased withdrawals, and decreased evapotranspiration accounted for about 53 (5.3 ft<sup>3</sup>/s) percent of increased withdrawals.</p>\n<p>The second hypothetical scenario represented a 30-year period of decreased recharge (drought) by decreasing recharge 0.2 inch (24 ft<sup>3</sup>/s) for each water year. At the end of the hypothetical drought simulation, water levels declined as much as 10.9 ft in the Arikaree aquifer, decreased discharge to streams accounted for about 23 percent (5.5 ft<sup>3</sup>/s) of decreased recharge, and decreased evapotranspiration accounted for about 72 percent (17.3 ft<sup>3</sup>/s) of decreased recharge.</p>\n<p>The numerical model is a tool that could be used to better understand the flow system of the Ogallala and Arikaree aquifers, to approximate hydraulic heads in the aquifer, and to estimate discharge to rivers, springs, and seeps in the Pine Ridge Reservation area in Bennett, Jackson, and Shannon Counties. The model also is useful to help assess the response of the aquifer to additional stress, including potential increased well withdrawals and potential drought conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145241","collaboration":"Prepared in cooperation with the Oglala Sioux Tribe","usgsCitation":"Davis, K.W., Putnam, L.D., and LaBelle, A.R., 2015, Conceptual and numerical models of groundwater flow in the Ogallala and Arikaree aquifers, Pine Ridge Indian Reservation area, South Dakota, water years 1980-2009: U.S. Geological Survey Scientific Investigations Report 2014-5241, x, 68 p., https://doi.org/10.3133/sir20145241.","productDescription":"x, 68 p.","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1979-10-01","temporalEnd":"2009-09-30","ipdsId":"IP-045449","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":298106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145241.jpg"},{"id":298103,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5241/pdf/sir2014-5241.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298101,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5241/"}],"projection":"Universal Transverse Mercator projection, Zone 14","country":"United States","state":"South Dakota","otherGeospatial":"Arikaree Aquifer, Ogallala Aquifer, Pine Ridge Indian Reservation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -102.98858642578125,\n              42.99862111927107\n            ],\n            [\n              -102.98858642578125,\n              43.7294293330051\n            ],\n            [\n              -101.19781494140625,\n              43.7294293330051\n            ],\n            [\n              -101.19781494140625,\n              42.99862111927107\n            ],\n            [\n              -102.98858642578125,\n              42.99862111927107\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54ec4f2de4b02d776a67da93","contributors":{"authors":[{"text":"Davis, Kyle W. 0000-0002-8723-0110 kyledavis@usgs.gov","orcid":"https://orcid.org/0000-0002-8723-0110","contributorId":3987,"corporation":false,"usgs":true,"family":"Davis","given":"Kyle","email":"kyledavis@usgs.gov","middleInitial":"W.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":541124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaBelle, Anneka R.","contributorId":139410,"corporation":false,"usgs":false,"family":"LaBelle","given":"Anneka","email":"","middleInitial":"R.","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":541125,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70155505,"text":"70155505 - 2015 - A comparison of hydrologic models for ecological flows and water availability","interactions":[],"lastModifiedDate":"2015-12-07T10:24:59","indexId":"70155505","displayToPublicDate":"2015-02-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of hydrologic models for ecological flows and water availability","docAbstract":"<p><span>Robust hydrologic models are needed to help manage water resources for healthy aquatic ecosystems and reliable water supplies for people, but there is a lack of comprehensive model comparison studies that quantify differences in streamflow predictions among model applications developed to answer management questions. We assessed differences in daily streamflow predictions by four fine-scale models and two regional-scale monthly time step models by comparing model fit statistics and bias in ecologically relevant flow statistics (ERFSs) at five sites in the Southeastern USA. Models were calibrated to different extents, including uncalibrated (level A), calibrated to a downstream site (level B), calibrated specifically for the site (level C) and calibrated for the site with adjusted precipitation and temperature inputs (level D). All models generally captured the magnitude and variability of observed streamflows at the five study sites, and increasing level of model calibration generally improved performance. All models had at least 1 of 14 ERFSs falling outside a +/&minus;30% range of hydrologic uncertainty at every site, and ERFSs related to low flows were frequently over-predicted. Our results do not indicate that any specific hydrologic model is superior to the others evaluated at all sites and for all measures of model performance. Instead, we provide evidence that (1) model performance is as likely to be related to calibration strategy as it is to model structure and (2) simple, regional-scale models have comparable performance to the more complex, fine-scale models at a monthly time step.</span></p>","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, West Sussex, UK","doi":"10.1002/eco.1602","usgsCitation":"Caldwell, P.V., Kennen, J., Sun, G., Kiang, J.E., Butcher, J.B., Eddy, M.C., Hay, L.E., LaFontaine, J.H., Hain, E.F., Nelson, S.C., and McNulty, S., 2015, A comparison of hydrologic models for ecological flows and water availability: Ecohydrology, v. 8, no. 8, p. 1525-1546, https://doi.org/10.1002/eco.1602.","productDescription":"22 p.","startPage":"1525","endPage":"1546","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062207","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":306514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-23","publicationStatus":"PW","scienceBaseUri":"55c9cb2ee4b08400b1fdb6e1","contributors":{"authors":[{"text":"Caldwell, Peter V","contributorId":145892,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":565591,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":565592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":565593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Butcher, John B","contributorId":145894,"corporation":false,"usgs":false,"family":"Butcher","given":"John","email":"","middleInitial":"B","affiliations":[{"id":16286,"text":"Tetra Tech","active":true,"usgs":false}],"preferred":false,"id":565594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eddy, Michelle C","contributorId":145895,"corporation":false,"usgs":false,"family":"Eddy","given":"Michelle","email":"","middleInitial":"C","affiliations":[{"id":7151,"text":"RTI International","active":true,"usgs":false}],"preferred":false,"id":565595,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":565596,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565597,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hain, Ernie F.","contributorId":141247,"corporation":false,"usgs":false,"family":"Hain","given":"Ernie","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":565598,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nelson, Stacy C","contributorId":145896,"corporation":false,"usgs":false,"family":"Nelson","given":"Stacy","email":"","middleInitial":"C","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":565599,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"McNulty, Steve G","contributorId":145897,"corporation":false,"usgs":false,"family":"McNulty","given":"Steve G","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":567588,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70125445,"text":"ofr20141200 - 2015 - Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado","interactions":[],"lastModifiedDate":"2015-02-20T15:25:16","indexId":"ofr20141200","displayToPublicDate":"2015-02-20T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1200","title":"Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado","docAbstract":"<p>Great Sand Dunes National Park and Preserve and the neighboring Baca National Wildlife Refuge constitute an extraordinary setting that offers a variety of opportunities for outdoor recreation and natural resource preservation in the San Luis Valley of Colorado. Adjacent to these federal lands, the Nature Conservancy (TNC) manages the historic Medano Ranch. The total land area of these three conservation properties is roughly 121,500 hectares (ha). It is a remote and rugged area in which resource managers must balance the protection of natural resources with recreation and neighboring land uses. The management of wild ungulates in this setting presents challenges, as wild ungulates move freely across public and private landscapes.</p>\n<p>The San Luis Valley was historically used for irrigated agriculture and ranching. Historically, livestock, including sheep (<i>Ovis aries</i>) and cattle (<i>Bos taurus</i>), were grazed throughout the valley. The former Luis Marie &ldquo;Baca&rdquo; Ranch, which makes up the northern part of Great Sand Dunes National Park (hereafter &ldquo;Park&rdquo;) and all of the Baca National Wildlife Refuge (hereafter &ldquo;Refuge&rdquo;), was actively grazed by cattle until 2004. Bison (<i>Bison bison</i>), elk (<i>Cervus elaphus</i>), mule deer (<i>Odocoileus hemionus</i>), and pronghorn (<i>Antilocapra americana</i>) were native to the area until about the 1840s, when bison, elk, and pronghorn were extirpated.</p>\n<p>Elk and pronghorn likely moved back into the area from surrounding populations to the north and south, and mule deer populations have varied through time. A population of 4,400 elk currently inhabits the area. The current bison population was established in 1986 for meat production. In 1999 TNC purchased the ranch and established a bison conservation herd, and eventually subcontracted management to a private rancher in 2005. A population of bison ranging in size from 1,200&ndash;2,000 ranges freely within the 16,100 ha Medano Ranch. Ungulate populations in the valley are regulated by hunting, with the exception of bison, which are rounded up and culled annually to maintain population levels.</p>\n<p>In an effort to create and form the basis of a multi-agency ungulate management plan for the region, the Park sought the development of an elk and bison ecological carrying capacity model to provide guidance to resource managers.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141200","collaboration":"In cooperation with the National Park Service","usgsCitation":"Wockner, G., Boone, R., Schoenecker, K.A., and Zeigenfuss, L., 2015, Modeling elk and bison carrying capacity for Great Sand Dunes National Park, Baca National Wildlife Refuge, and The Nature Conservancy's Medano Ranch, Colorado: U.S. Geological Survey Open-File Report 2014-1200, iv, 23 p., https://doi.org/10.3133/ofr20141200.","productDescription":"iv, 23 p.","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056689","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141200.jpg"},{"id":298073,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1200/"},{"id":298074,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1200/pdf/ofr2014-1200.pdf","text":"Report","size":"7.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Colorado","otherGeospatial":"Baca National Wildlife Refuge, Great Sand Dunes National Park, San Luis Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.15264892578125,\n              37.477037796698056\n            ],\n            [\n              -106.15264892578125,\n              38.52023522875919\n            ],\n            [\n              -105.018310546875,\n              38.52023522875919\n            ],\n            [\n              -105.018310546875,\n              37.477037796698056\n            ],\n            [\n              -106.15264892578125,\n              37.477037796698056\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e85aade4b02d776a67c5b7","contributors":{"authors":[{"text":"Wockner, Gary","contributorId":118967,"corporation":false,"usgs":true,"family":"Wockner","given":"Gary","email":"","affiliations":[],"preferred":false,"id":541072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boone, Randall","contributorId":121404,"corporation":false,"usgs":true,"family":"Boone","given":"Randall","email":"","affiliations":[],"preferred":false,"id":541073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":541070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zeigenfuss, Linda 0000-0002-6700-8563 linda_zeigenfuss@usgs.gov","orcid":"https://orcid.org/0000-0002-6700-8563","contributorId":2079,"corporation":false,"usgs":true,"family":"Zeigenfuss","given":"Linda","email":"linda_zeigenfuss@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":541071,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70177028,"text":"70177028 - 2015 - Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches","interactions":[],"lastModifiedDate":"2016-10-19T15:22:25","indexId":"70177028","displayToPublicDate":"2015-02-20T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches","docAbstract":"As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms.  A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein.  Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response).  Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters.  The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results.  Less-than-additive toxicity was more difficult to describe with the available models.  Because of limitations in the available datasets and the strong inter-relationships among the model parameters (log KM values, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.2820","usgsCitation":"Farley, K.J., Meyer, J., Balistrieri, L.S., DeSchamphelaere, K., Iwasaki, Y., Janssen, C., Kamo, M., Lofts, S., Mebane, C.A., Naito, W., Ryan, A.C., Santore, R.C., and Tipping, E., 2015, Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches: Environmental Toxicology and Chemistry, v. 34, no. 4, p. 741-753, https://doi.org/10.1002/etc.2820.","productDescription":"13 p.","startPage":"741","endPage":"753","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056635","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472265,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/etc.2820","text":"External Repository"},{"id":329768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-24","publicationStatus":"PW","scienceBaseUri":"58088688e4b0f497e78e24d3","contributors":{"authors":[{"text":"Farley, Kevin J.","contributorId":175407,"corporation":false,"usgs":false,"family":"Farley","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":27565,"text":"Manhattan College","active":true,"usgs":false}],"preferred":false,"id":651038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Joe","contributorId":175408,"corporation":false,"usgs":false,"family":"Meyer","given":"Joe","email":"","affiliations":[{"id":27566,"text":"ARCADIS US","active":true,"usgs":false}],"preferred":false,"id":651039,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balistrieri, Laurie S. 0000-0002-6359-3849 balistri@usgs.gov","orcid":"https://orcid.org/0000-0002-6359-3849","contributorId":1406,"corporation":false,"usgs":true,"family":"Balistrieri","given":"Laurie","email":"balistri@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":651037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeSchamphelaere, Karl","contributorId":175409,"corporation":false,"usgs":false,"family":"DeSchamphelaere","given":"Karl","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":651040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwasaki, Yuichi","contributorId":175410,"corporation":false,"usgs":false,"family":"Iwasaki","given":"Yuichi","email":"","affiliations":[{"id":27568,"text":"Tokyo Institute of Tecnology","active":true,"usgs":false}],"preferred":false,"id":651041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janssen, Colin","contributorId":175411,"corporation":false,"usgs":false,"family":"Janssen","given":"Colin","email":"","affiliations":[{"id":27567,"text":"Ghent University","active":true,"usgs":false}],"preferred":false,"id":651042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kamo, Masashi","contributorId":175412,"corporation":false,"usgs":false,"family":"Kamo","given":"Masashi","email":"","affiliations":[],"preferred":false,"id":651043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lofts, Steve","contributorId":175413,"corporation":false,"usgs":false,"family":"Lofts","given":"Steve","affiliations":[],"preferred":false,"id":651044,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Naito, Wataru","contributorId":175563,"corporation":false,"usgs":false,"family":"Naito","given":"Wataru","email":"","affiliations":[],"preferred":false,"id":651433,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ryan, Adam C.","contributorId":175564,"corporation":false,"usgs":false,"family":"Ryan","given":"Adam","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":651434,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Santore, Robert C.","contributorId":53206,"corporation":false,"usgs":true,"family":"Santore","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":651435,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tipping, Edward","contributorId":36405,"corporation":false,"usgs":true,"family":"Tipping","given":"Edward","email":"","affiliations":[],"preferred":false,"id":651436,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70141650,"text":"70141650 - 2015 - Likelihood analysis of spatial capture-recapture models for stratified or class structured populations","interactions":[],"lastModifiedDate":"2015-02-20T09:24:10","indexId":"70141650","displayToPublicDate":"2015-02-20T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Likelihood analysis of spatial capture-recapture models for stratified or class structured populations","docAbstract":"<p><span>We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.</span><span><br /></span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES14-00148.1","usgsCitation":"Royle, J., Sutherland, C.S., Fuller, A.K., and Sun, C.C., 2015, Likelihood analysis of spatial capture-recapture models for stratified or class structured populations: Ecosphere, v. 6, no. 2, 11 p., https://doi.org/10.1890/ES14-00148.1.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060022","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472267,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es14-00148.1","text":"Publisher Index Page"},{"id":298061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-12","publicationStatus":"PW","scienceBaseUri":"54e85aace4b02d776a67c5b5","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":540944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sutherland, Christopher S.","contributorId":139375,"corporation":false,"usgs":false,"family":"Sutherland","given":"Christopher","email":"","middleInitial":"S.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":540945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":540946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sun, Catherine C.","contributorId":70274,"corporation":false,"usgs":false,"family":"Sun","given":"Catherine","email":"","middleInitial":"C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":540947,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70141812,"text":"70141812 - 2015 - Coping with earthquakes induced by fluid injection","interactions":[],"lastModifiedDate":"2017-02-13T14:33:11","indexId":"70141812","displayToPublicDate":"2015-02-20T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Coping with earthquakes induced by fluid injection","docAbstract":"<p>Large areas of the United States long considered geologically stable with little or no detected seismicity have recently become seismically active. The increase in earthquake activity began in the mid-continent starting in 2001 (<i>1</i>) and has continued to rise. In 2014, the rate of occurrence of earthquakes with magnitudes (<i>M</i>) of 3 and greater in Oklahoma exceeded that in California (see the figure). This elevated activity includes larger earthquakes, several with <i>M</i> &gt; 5, that have caused significant damage (<i>2</i>,&nbsp;<i>3</i>). To a large extent, the increasing rate of earthquakes in the mid-continent is due to fluid-injection activities used in modern energy production (<i>1</i>, <i>4</i>, <i>5</i>). We explore potential avenues for mitigating effects of induced seismicity. Although the United States is our focus here, Canada, China, the UK, and others confront similar problems associated with oil and gas production, whereas quakes induced by geothermal activities affect Switzerland, Germany, and others.</p>","language":"English","publisher":"American Association for the Advancement of Science","publisherLocation":"New York, NY","doi":"10.1126/science.aaa0494","usgsCitation":"McGarr, A.F., Bekins, B., Burkardt, N., Dewey, J.W., Earle, P.S., Ellsworth, W.L., Ge, S., Hickman, S.H., Holland, A.F., Majer, E., Rubinstein, J.L., and Sheehan, A., 2015, Coping with earthquakes induced by fluid injection: Science, v. 347, no. 6224, p. 830-831, https://doi.org/10.1126/science.aaa0494.","productDescription":"2 p.","startPage":"830","endPage":"831","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059959","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":298084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298082,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencemag.org/content/347/6224/830"}],"volume":"347","issue":"6224","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54ec5d3be4b02d776a67da9c","contributors":{"authors":[{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":541110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":139407,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - 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,{"id":70113702,"text":"70113702 - 2015 - Reducing soluble phosphorus in dairy effluents through application of mine drainage residuals","interactions":[],"lastModifiedDate":"2015-04-03T15:27:49","indexId":"70113702","displayToPublicDate":"2015-02-19T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1281,"text":"Communications in Soil Science and Plant Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Reducing soluble phosphorus in dairy effluents through application of mine drainage residuals","docAbstract":"<p><span>Three different dairy manure wastewater effluent samples were amended with mine drainage residuals (MDR) to evaluate the suitability of MDR for sequestration of phosphorus (P). Geochemical modeling of the manure wastewater compositions indicated that partially soluble P-bearing minerals including hydroxyapatite, octacalcium phosphate, and vivianite were all oversaturated in each of the manure wastewater samples. Initial MDR amendment test results indicated that these partially soluble P minerals suspended in the wastewater replenished P in the water phase as it was sorbed by the MDR samples. Further investigations revealed that the MDR samples were effective in decreasing soluble P when the amended manure was tested using the water-extractable P procedure. Under these conditions, up to 90 percent of the soluble P in the manure was converted to a sorbed, water-insoluble state. Water contamination and large-scale validation tests of the process were also conducted.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00103624.2014.998339","usgsCitation":"Sibrell, P.L., Penn, C.J., and Hedin, R.S., 2015, Reducing soluble phosphorus in dairy effluents through application of mine drainage residuals: Communications in Soil Science and Plant Analysis, v. 46, no. 5, p. 545-563, https://doi.org/10.1080/00103624.2014.998339.","productDescription":"19 p.","startPage":"545","endPage":"563","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057556","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":299372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"5","noUsgsAuthors":false,"publicationDate":"2015-02-19","publicationStatus":"PW","scienceBaseUri":"551fb9c1e4b027f0aee3bb29","contributors":{"authors":[{"text":"Sibrell, Philip L. psibrell@usgs.gov","contributorId":2006,"corporation":false,"usgs":true,"family":"Sibrell","given":"Philip","email":"psibrell@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":518979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penn, Chad J.","contributorId":116060,"corporation":false,"usgs":false,"family":"Penn","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":518980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hedin, Robert S.","contributorId":118146,"corporation":false,"usgs":false,"family":"Hedin","given":"Robert","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":518981,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70141438,"text":"70141438 - 2015 - Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change","interactions":[],"lastModifiedDate":"2017-10-30T11:07:49","indexId":"70141438","displayToPublicDate":"2015-02-18T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change","docAbstract":"<p><span>Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. 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Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1) Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2) What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a strategy considering sea-level rise and storms explicitly in wetland restoration planning and designs was optimal, and it was robust to uncertainties about management effectiveness and budgets. We found that strategies that avoided explicitly accounting for future climate change had the lowest expected performance based on input from the team. 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