{"pageNumber":"647","pageRowStart":"16150","pageSize":"25","recordCount":68919,"records":[{"id":70041913,"text":"70041913 - 2012 - Nearshore hydrodynamics as loading and forcing factors for <i>Escherichia coli</i> contamination at an embayed beach","interactions":[],"lastModifiedDate":"2013-02-28T14:06:40","indexId":"70041913","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","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":"Nearshore hydrodynamics as loading and forcing factors for <i>Escherichia coli</i> contamination at an embayed beach","docAbstract":"Numerical simulations of the transport and fate of <i>Escherichia coli</i> were conducted at Chicago's 63rd Street Beach, an embayed beach that had the highest mean <i>E. coli</i> concentration among 23 similar Lake Michigan beaches during summer months of 2000-2005, in order to find the cause for the high bacterial contamination. The numerical model was based on the transport of <i>E. coli</i> by current circulation patterns in the embayment driven by longshore main currents and the loss of <i>E. coli</i> in the water column, taking settling as well as bacterial dark- and solar-related decay into account. Two <i>E. coli</i> loading scenarios were considered: one from the open boundary north of the embayment and the other from the shallow water near the beachfront. Simulations showed that the embayed beach behaves as a sink for <i>E. coli</i> in that it generally receives <i>E. coli</i> more efficiently than it releases them. This is a result of the significantly different hydrodynamic forcing factors between the inside of the embayment and the main coastal flow outside. The settled <i>E. coli</i> inside the embayment can be a potential source of contamination during subsequent sediment resuspension events, suggesting that deposition-resuspension cycles of <i>E. coli</i> have resulted in excessive bacterial contamination of beach water. A further hypothetical case with a breakwater shortened to half its original length, which was anticipated to enhance the current circulation in the embayment, showed a reduction in <i>E. coli</i> concentrations of nearly 20%.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Limnology and Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ASLO","publisherLocation":"Waco, TX","doi":"10.4319/lo.2012.57.1.0362","usgsCitation":"Ge, Z., Whitman, R.L., Nevers, M.B., Phanikumar, M., and Byappanahalli, M., 2012, Nearshore hydrodynamics as loading and forcing factors for <i>Escherichia coli</i> contamination at an embayed beach: Limnology and Oceanography, v. 57, no. 1, p. 362-381, https://doi.org/10.4319/lo.2012.57.1.0362.","productDescription":"20 p.","startPage":"362","endPage":"381","ipdsId":"IP-017639","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":268568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268567,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4319/lo.2012.57.1.0362"}],"country":"United States","state":"Illinois","city":"Chicago","otherGeospatial":"63rd Street Beach","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.576581,41.781041 ], [ -87.576581,41.784475 ], [ -87.56869,41.784475 ], [ -87.56869,41.781041 ], [ -87.576581,41.781041 ] ] ] } } ] }","volume":"57","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-16","publicationStatus":"PW","scienceBaseUri":"51308a92e4b04c194073ae13","contributors":{"authors":[{"text":"Ge, Zhongfu","contributorId":29709,"corporation":false,"usgs":true,"family":"Ge","given":"Zhongfu","affiliations":[],"preferred":false,"id":470373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":470371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nevers, Meredith B.","contributorId":91803,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":470375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":470372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Byappanahalli, Muruleedhara N.","contributorId":47335,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara N.","affiliations":[],"preferred":false,"id":470374,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041918,"text":"70041918 - 2012 - Habitat use by fishes of Lake Superior. II. Consequences of diel habitat use for habitat linkages and habitat coupling in nearshore and offshore waters","interactions":[],"lastModifiedDate":"2017-10-20T11:16:44","indexId":"70041918","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Habitat use by fishes of Lake Superior. II. Consequences of diel habitat use for habitat linkages and habitat coupling in nearshore and offshore waters","docAbstract":"<p><span>Diel migration patterns of fishes in nearshore (15–80&nbsp;m depth) and offshore (&gt;80&nbsp;m) waters of Lake Superior were examined to assess the potential for diel migration to link benthic and pelagic, and nearshore and offshore habitats. In our companion article, we described three types of diel migration: diel vertical migration (DVM), diel bank migration (DBM), and no diel migration. DVM was expressed by fishes migrating from benthopelagic to pelagic positions and DBM was expressed by fishes migrating horizontally from deep to shallow waters at night. Fishes not exhibiting diel migration typically showed increased activity by moving from benthic to benthopelagic positions within demersal habitat. The distribution and biomass of fishes in Lake Superior was characterized by examining 704 bottom trawl samples collected between 2001 and 2008 from four depth zones: ≤40, 41–80, 81–160, and &gt;160&nbsp;m. Diel migration behaviors of fishes described in our companion article were applied to estimates of areal biomass (kg ha</span><sup>−1</sup><span>) for each species by depth zone. The relative strength of diel migrations were assessed by applying lake area to areal biomass estimates for each species by depth zone to yield estimates of lake-wide biomass (metric tonnes). Overall, species expressing DVM accounted for 83%, DBM 6%, and non-migration 11% of the total lake-wide community biomass. In nearshore waters, species expressing DVM represented 74% of the biomass, DBM 25%, and non-migration 1%. In offshore waters, species expressing DVM represented 85%, DBM 1%, and non-migration 14% of the biomass. Of species expressing DVM, 83% of total biomass occurred in offshore waters. Similarly, 97% of biomass of non-migrators occurred in offshore waters while 83% of biomass of species expressing DBM occurred in nearshore waters. A high correlation (R</span><sup>2</sup><span> = 0.996) between lake area and community biomass by depth zone resulted in 81% of the lake-wide biomass occurring in offshore waters. Accentuating this nearshore-offshore trend was one of increasing estimated total areal biomass of the fish community with depth zone, which ranged from 13.71&nbsp;kg ha</span><sup>−1</sup><span> at depths ≤40&nbsp;m to 18.81&nbsp;kg ha</span><sup>−1</sup><span> at depths &gt;160&nbsp;m, emphasizing the importance of the offshore fish community to the lake ecosystem. The prevalence of diel migration expressed by Lake Superior fishes increases the potential of fish to link benthic and pelagic and shallow and deepwater habitats. These linkages enhance the potential for habitat coupling, a condition where habitats become interconnected and interdependent through transfers of energy and nutrients. Habitat coupling facilitates energy and nutrient flow through a lake ecosystem, thereby increasing productivity, especially in large lakes where benthic and pelagic, and nearshore and offshore habitats are often well separated. We propose that the application of biomass estimates to patterns of diel migration in fishes can serve as a useful metric for assessing the potential for habitat linkages and habitat coupling in lake ecosystems, and provide an important indicator of ecosystem health and function. The decline of native Lake Trout and ciscoes and recent declines in exotic Alewife and Rainbow Smelt populations in other Great Lakes have likely reduced the capacity for benthic-pelagic coupling in these systems compared to Lake Superior. We recommend comparing the levels and temporal changes in diel migration in other Great Lakes as a means to assess changes in the relative health and function of these ecosystems.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/14634988.2012.711664","usgsCitation":"Gorman, O.T., Yule, D., and Stockwell, J.D., 2012, Habitat use by fishes of Lake Superior. II. Consequences of diel habitat use for habitat linkages and habitat coupling in nearshore and offshore waters: Aquatic Ecosystem Health & Management, v. 15, no. 3, p. 355-368, https://doi.org/10.1080/14634988.2012.711664.","productDescription":"14 p.","startPage":"355","endPage":"368","ipdsId":"IP-037747","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":274156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.48486328124999,\n              46.49839225859763\n            ],\n            [\n              -84.342041015625,\n              46.76244305208004\n            ],\n            [\n              -84.4189453125,\n              47.040182144806664\n            ],\n            [\n              -84.605712890625,\n              47.04766864046083\n            ],\n            [\n              -84.495849609375,\n              47.27177506640828\n            ],\n            [\n              -84.53979492187499,\n              47.4057852900587\n            ],\n            [\n              -84.869384765625,\n              47.60616304386874\n            ],\n            [\n              -84.88037109375,\n              47.79101617826261\n            ],\n            [\n              -84.759521484375,\n              47.97521412341618\n            ],\n            [\n              -84.847412109375,\n              48.04136507445029\n            ],\n            [\n              -85.374755859375,\n              47.99727386804474\n            ],\n            [\n              -85.7373046875,\n              47.97521412341618\n            ],\n            [\n              -85.93505859374999,\n              48.11476663187632\n            ],\n            [\n              -86.077880859375,\n              48.37084770238366\n            ],\n            [\n              -86.275634765625,\n              48.669198799260045\n            ],\n            [\n              -86.5283203125,\n              48.84302835299516\n            ],\n            [\n              -87.099609375,\n              48.87194147722911\n            ],\n            [\n              -87.440185546875,\n              48.879167148960214\n            ],\n            [\n              -87.879638671875,\n              48.980216985374994\n            ],\n            [\n              -88.26416015625,\n              49.03786794532644\n            ],\n            [\n              -88.59374999999999,\n              48.90805939965008\n            ],\n            [\n              -88.714599609375,\n              48.72720881940671\n            ],\n            [\n              -88.83544921874999,\n              48.61112192003074\n            ],\n            [\n              -89.14306640625,\n              48.516604348867475\n            ],\n            [\n              -89.3408203125,\n              48.46563710044979\n            ],\n            [\n              -89.3408203125,\n              48.31242790407178\n            ],\n            [\n              -89.40673828125,\n              48.122101028190805\n            ],\n            [\n              -89.791259765625,\n              47.989921667414194\n            ],\n            [\n              -90.318603515625,\n              47.78363463526376\n            ],\n            [\n              -90.791015625,\n              47.67278567576541\n            ],\n            [\n              -91.131591796875,\n              47.487513008956554\n            ],\n            [\n              -91.7138671875,\n              47.204642388766935\n            ],\n            [\n              -92.1533203125,\n              46.875213396722685\n            ],\n            [\n              -92.3291015625,\n              46.74738913515841\n            ],\n            [\n              -92.0654296875,\n              46.543749602738565\n            ],\n            [\n              -91.724853515625,\n              46.58906908309182\n            ],\n            [\n              -91.23046875,\n              46.73233101286786\n            ],\n            [\n              -91.021728515625,\n              46.822616668804926\n            ],\n            [\n              -90.98876953125,\n              46.66451741754235\n            ],\n            [\n              -91.01074218749999,\n              46.55130547880643\n            ],\n            [\n              -90.68115234375,\n              46.55130547880643\n            ],\n            [\n              -90.516357421875,\n              46.521075663842865\n            ],\n            [\n              -90.04394531249999,\n              46.50595444552049\n            ],\n            [\n              -89.769287109375,\n              46.67205646734499\n            ],\n            [\n              -89.549560546875,\n              46.7549166192819\n            ],\n            [\n              -89.01123046875,\n              46.882723010671945\n            ],\n            [\n              -88.670654296875,\n              47.06263847995432\n            ],\n            [\n              -88.53881835937499,\n              47.19717795172789\n            ],\n            [\n              -88.121337890625,\n              47.41322033016902\n            ],\n            [\n              -88.385009765625,\n              47.21956811231547\n            ],\n            [\n              -88.70361328125,\n              46.927758623434435\n            ],\n            [\n              -88.648681640625,\n              46.717268685073954\n            ],\n            [\n              -88.494873046875,\n              46.68713141244413\n            ],\n            [\n              -88.35205078124999,\n              46.81509864599243\n            ],\n            [\n              -88.099365234375,\n              46.852678248531106\n            ],\n            [\n              -87.923583984375,\n              46.830133640447386\n            ],\n            [\n              -87.7587890625,\n              46.76996843356982\n            ],\n            [\n              -87.62695312499999,\n              46.64189395892872\n            ],\n            [\n              -87.42919921875,\n              46.46813299215554\n            ],\n            [\n              -87.176513671875,\n              46.430285240839964\n            ],\n            [\n              -86.94580078125,\n              46.42271253466717\n            ],\n            [\n              -86.6162109375,\n              46.40756396630067\n            ],\n            [\n              -86.30859375,\n              46.4605655457854\n            ],\n            [\n              -85.902099609375,\n              46.619261036171515\n            ],\n            [\n              -85.462646484375,\n              46.65697731621612\n            ],\n            [\n              -85.1220703125,\n              46.67205646734499\n            ],\n            [\n              -85.05615234375,\n              46.475699386607516\n            ],\n            [\n              -84.825439453125,\n              46.34692761055676\n            ],\n            [\n              -84.48486328124999,\n              46.49839225859763\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cabbe2e4b0d298e5434c4e","contributors":{"authors":[{"text":"Gorman, Owen T. 0000-0003-0451-110X otgorman@usgs.gov","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":2888,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"otgorman@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yule, Daniel L.","contributorId":92130,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","affiliations":[],"preferred":false,"id":470382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":470381,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041988,"text":"70041988 - 2012 - Prey selection by the Lake Superior fish community","interactions":[],"lastModifiedDate":"2013-03-04T14:35:15","indexId":"70041988","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","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":"Prey selection by the Lake Superior fish community","docAbstract":"<i>Mysis diluviana</i> is an important prey item to the Lake Superior fish community as found through a recent diet study. We further evaluated this by relating the quantity of prey found in fish diets to the quantity of prey available to fish, providing insight into feeding behavior and prey preferences. We describe the seasonal prey selection of major fish species collected across 18 stations in Lake Superior in spring, summer, and fall of 2005. Of the major nearshore fish species, bloater (<i>Coregonus hoyi</i>), rainbow smelt (<i>Osmerus mordax</i>), and lake whitefish (<i>Coregonus clupeaformis</i>) consumed <i>Mysis</i>, and strongly selected <i>Mysis</i> over other prey items each season. However, lake whitefish also selected <i>Bythotrephes</i> in the fall when <i>Bythotrephes</i> were numerous. Cisco (<i>Coregonus artedi</i>), a major nearshore and offshore species, fed largely on calanoid copepods, and selected calanoid copepods (spring) and <i>Bythotrephes</i> (summer and fall). Cisco also targeted prey similarly across bathymetric depths. Other major offshore fish species such as kiyi (<i>Coregonus kiyi</i>) and deepwater sculpin (<i>Myoxocephalus thompsoni</i>) fed largely on <i>Mysis</i>, with kiyi targeting <i>Mysis</i> exclusively while deepwater sculpin did not prefer any single prey organism. The major offshore predator siscowet lake trout (<i>Salvelinus namaycush siscowet</i>) consumed deepwater sculpin and coregonines, but selected deepwater sculpin and <i>Mysis</i> each season, with juveniles having a higher selection for <i>Mysis</i> than adults. Our results suggest that <i>Mysis</i> is not only a commonly consumed prey item, but a highly preferred prey item for pelagic, benthic, and piscivorous fishes in nearshore and offshore waters of Lake Superior.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jglr.2012.02.017","usgsCitation":"Isaac, E.J., Hrabik, T.R., Stockwell, J.D., and Gamble, A.E., 2012, Prey selection by the Lake Superior fish community: Journal of Great Lakes Research, v. 38, no. 2, p. 326-335, https://doi.org/10.1016/j.jglr.2012.02.017.","productDescription":"10 p.","startPage":"326","endPage":"335","ipdsId":"IP-035901","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":268719,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.02.017"},{"id":268720,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.5,46.25 ], [ -92.5,49.0 ], [ -84.33,49.0 ], [ -84.33,46.25 ], [ -92.5,46.25 ] ] ] } } ] }","volume":"38","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5135d092e4b03b8ec4025bad","contributors":{"authors":[{"text":"Isaac, Edmund J.","contributorId":64120,"corporation":false,"usgs":true,"family":"Isaac","given":"Edmund","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":470542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":470539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Jason D. 0000-0003-3393-6799","orcid":"https://orcid.org/0000-0003-3393-6799","contributorId":61004,"corporation":false,"usgs":false,"family":"Stockwell","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":470541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gamble, Allison E.","contributorId":56940,"corporation":false,"usgs":true,"family":"Gamble","given":"Allison","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":470540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70003678,"text":"70003678 - 2012 - How to overcome inter-electrode variability and instability to quantify dissolved oxygen, Fe(II), mn(II), and S(−II) in undisturbed soils and sediments using voltammetry","interactions":[],"lastModifiedDate":"2013-03-21T10:57:22","indexId":"70003678","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1755,"text":"Geochemical Transactions","active":true,"publicationSubtype":{"id":10}},"title":"How to overcome inter-electrode variability and instability to quantify dissolved oxygen, Fe(II), mn(II), and S(−II) in undisturbed soils and sediments using voltammetry","docAbstract":"Background -\n\nAlthough uniquely capable of measuring multiple redox constituents nearly simultaneously with no or minimal sample pretreatment, voltammetry is currently underutilized in characterizing redox conditions in aquatic and terrestrial systems. Investigation of undisturbed media such as pore water requires a solid-state electrode, and such electrodes can be difficult to fabricate reproducibly. An approach to determine the concentrations of electroactive constituents using indirectly calibrated electrodes has been developed, but the protocol for and accuracy of this approach—the pilot ion method—has not been documented in detail.\nResults - \n\nA detailed procedure for testing electrode quality is provided, and the application and limitations of the pilot ion method have been documented. To quantify Fe(II) and Mn(II), subtraction of non-linear baseline functions from voltammetric signals produced better calibration curves than did linear baselines, enabled lower detection limits and reliable deconvolution of overlapping signals, and was successfully applied to sediment pore water signals. We observed that electrode sensitivities often vary by tens of percent, and that the sensitivity declines over time. The ratio of calibration slopes of Mn(II) to Fe(II) varied by no more than 11% from one Hg/Au electrode to another and Fe(II) concentrations predicted by the Mn(II) pilot ion were, on average, 13% different from their actual values. However, concentration predictions by the pilot ion method were worse for less than 15 μM Fe(II) (46% different on average). The ratio of calibration slopes of Mn(II) to S(−II) varied by almost 20% from one Hg/Au electrode to another, and S(−II) predicted concentrations were as much as 58% different from their actual values. These predictions of Fe(II) and S(−II) concentrations indicate that the accuracy of the pilot ion method depends on how independent calibration slope ratios are from the electrode used. At medium-to-high concentration for the ocean, naturally derived dissolved organic carbon did not significantly affect the baseline-corrected electrode response of Mn(II) and Fe(II), but did significantly affect the response of S(−II).\nConclusions -\n\nDespite their intrinsic variability, Hg/Au electrodes fabricated by hand can be used to quantify O2, S(−II), Fe(II), and Mn(II) without calibrating every electrode for every constituent of interest. The pilot ion method can achieve accuracies to within 20% or less, provided that the underlying principle—the independence of slope ratios—is demonstrated for all voltammetric techniques used, and effects of the physicochemical properties of the system on voltammetric signals are addressed through baseline subtraction.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochemical Transactions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisherLocation":"Reston, VA","doi":"10.1186/1467-4866-13-6","usgsCitation":"Slowey, A.J., and Marvin-DiPasquale, M., 2012, How to overcome inter-electrode variability and instability to quantify dissolved oxygen, Fe(II), mn(II), and S(−II) in undisturbed soils and sediments using voltammetry: Geochemical Transactions, v. 13, no. 6, 20 p., https://doi.org/10.1186/1467-4866-13-6.","productDescription":"20 p.","ipdsId":"IP-026570","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":474176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/1467-4866-13-6","text":"Publisher Index Page"},{"id":269848,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1186/1467-4866-13-6"},{"id":269849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-06-25","publicationStatus":"PW","scienceBaseUri":"514c2be6e4b0cf4196fef30c","contributors":{"authors":[{"text":"Slowey, Aaron J.","contributorId":30706,"corporation":false,"usgs":true,"family":"Slowey","given":"Aaron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":348298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marvin-DiPasquale, Mark","contributorId":57423,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","affiliations":[],"preferred":false,"id":348299,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70003596,"text":"70003596 - 2012 - Estimating and predicting collection probability of fish at dams using multistate modeling","interactions":[],"lastModifiedDate":"2013-06-10T08:56:00","indexId":"70003596","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2012","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":"Estimating and predicting collection probability of fish at dams using multistate modeling","docAbstract":"Dams can be equipped with a bypass that routes a portion of the fish that enter the turbine intakes away\nfrom the powerhouse into flumes, where they can be counted. Daily passage abundance can be estimated by dividing\nthe number of fish counted in the bypass by the sampling rate and then dividing the resulting quotient by\nthe collection probability (i.e., the proportion of the fish population passing the dam that is bypassed). We used\nmultistate mark–recapture modeling to evaluate six candidate models for predicting the collection probabilities of\nradio-tagged subyearling fall Chinook salmon (n = 3,852) as a function of 1–2-d time periods (general model), four\ndifferent combinations of outflow (i.e., the total volume of water passing the dam) and turbine allocation (i.e., the\nproportion of outflow directed through the turbines), and a null (intercept only) model. The best-fit model was\nthe additive combination of turbine allocation and outflow, which explained 71% of the null deviance. Cross validation\nof the best-fit model accounted for the variation that may arise from different data sets and the ensuing\nparameter values on the collection probability estimates and yielded a standard error of 0.613 that can be used to\nconstruct approximate 95% prediction intervals in nonstudy years. Such estimates have been unavailable and will\nbe useful anywhere estimates of daily passage abundance at dams with bypasses are needed to manage migratory\nfishes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2012.694828","usgsCitation":"Plumb, J.M., Connor, W.P., Tiffan, K.F., Moffitt, C.M., Perry, R.W., and Adams, N.S., 2012, Estimating and predicting collection probability of fish at dams using multistate modeling: Transactions of the American Fisheries Society, v. 141, no. 5, p. 1364-1373, https://doi.org/10.1080/00028487.2012.694828.","productDescription":"10 p.","startPage":"1364","endPage":"1373","ipdsId":"IP-028831","costCenters":[{"id":342,"text":"Idaho Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":273464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273463,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/00028487.2012.694828"}],"volume":"141","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-08-16","publicationStatus":"PW","scienceBaseUri":"51b6f566e4b0097a7158e5aa","contributors":{"authors":[{"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":347881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connor, William P.","contributorId":107589,"corporation":false,"usgs":false,"family":"Connor","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID  83544","active":true,"usgs":false}],"preferred":false,"id":347882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":347879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moffitt, Christine M. 0000-0001-6020-9728 cmoffitt@usgs.gov","orcid":"https://orcid.org/0000-0001-6020-9728","contributorId":2583,"corporation":false,"usgs":true,"family":"Moffitt","given":"Christine","email":"cmoffitt@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":347877,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":347878,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":347880,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039733,"text":"70039733 - 2012 - Wintering waterfowl respond to Wetlands Reserve Program lands in the Central Valley of California","interactions":[],"lastModifiedDate":"2019-08-27T11:50:48","indexId":"70039733","displayToPublicDate":"2012-12-31T11:44:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13,"text":"CEAP Conservation Insight","active":false,"publicationSubtype":{"id":1}},"title":"Wintering waterfowl respond to Wetlands Reserve Program lands in the Central Valley of California","docAbstract":"<p>Daytime use by wintering waterfowl at Wetlands Reserve Program (WRP) sites within the northern Central Valley of California (CVC) increased dramatically after wetland restoration and was sustained for up to 8 years post-restoration. The magnitude of the increase in waterfowl density at WRP sites after wetland restoration was greater with greater densities of birds in the local area before restoration, lower amount of surrounding wetland habitat within a 1.5-km radius, greater increase in flooding after restoration, and closer proximity to flooded rice fields. Estimates of waterfowl distribution within areas sampled by weather surveillance radar suggest that 18 percent of wintering waterfowl use the more than 67,900 acres of restored and unrestored land enrolled in the WRP. Restored wetland habitat within WRP sites made up about 8 percent (30,360 acres) of the total wetland habitat within the CVC in 2007. Waterfowl use of flooded rice fields during the daytime and during wetter winters nearly tripled from 1995 to 2007 relative to use of natural wetland habitats. Recommendations An additional 104,000 acres of seasonal wetland restoration are needed to meet waterfowl conservation objectives in the CVC ( Central Valley Joint Venture 2006). Active restoration of hydrology and moist-soil management on WRP sites can help meet this objective. Waterfowl use of WRP sites can also be improved by locating sites close to flooded rice fields within local landscapes that have high pre-existing waterfowl abundance and relatively little wetland habitat. The assessment team developed spatially explicit decision support tools for prioritizing future WRP enrollments. The tools map the predicted post-restoration magnitude of waterfowl use based on site and local landscape variables.</p>","language":"English","publisher":"CEAP Conservation Insight (NRCS)","publisherLocation":"Reston, VA","usgsCitation":"Buler, J.J., Barrow, W., and Randall, L.A., 2012, Wintering waterfowl respond to Wetlands Reserve Program lands in the Central Valley of California: CEAP Conservation Insight, 7 p.","productDescription":"7 p.","ipdsId":"IP-033833","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":366966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366965,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1048508.pdf"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.95349121093749,\n              37.79676317682161\n            ],\n            [\n              -120.7672119140625,\n              37.79676317682161\n            ],\n            [\n              -120.7672119140625,\n              40.451127265872316\n            ],\n            [\n              -122.95349121093749,\n              40.451127265872316\n            ],\n            [\n              -122.95349121093749,\n              37.79676317682161\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":769368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barrow, Wylie C. Jr. 0000-0003-4671-2823 barroww@usgs.gov","orcid":"https://orcid.org/0000-0003-4671-2823","contributorId":168953,"corporation":false,"usgs":true,"family":"Barrow","given":"Wylie C.","suffix":"Jr.","email":"barroww@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":769369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Randall, Lori A. 0000-0003-0100-994X randalll@usgs.gov","orcid":"https://orcid.org/0000-0003-0100-994X","contributorId":2678,"corporation":false,"usgs":true,"family":"Randall","given":"Lori","email":"randalll@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":769370,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70211072,"text":"70211072 - 2012 - Helicopter electromagnetic data map ice thickness at Mount Adams and Mount Baker, Washington, USA","interactions":[],"lastModifiedDate":"2020-07-13T16:31:59.34607","indexId":"70211072","displayToPublicDate":"2012-12-31T11:18:58","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Helicopter electromagnetic data map ice thickness at Mount Adams and Mount Baker, Washington, USA","docAbstract":"<p><span>Ice-thickness measurements critical for flood and mudflow hazard studies are very sparse on Cascade Range (North America) volcanoes. Helicopter electromagnetic (HEM) data collected to detect hydrothermal alteration are used to determine ice thickness over portions of Mount Baker and Mount Adams volcanoes. A laterally continuous inversion method provides good estimates of ice &lt;100 m thick over water-saturated and altered regions where the resistivity of the basement is &lt;200 Ωm. For areas with ice overlying fresh, resistive rocks with small resistivity contrasts between ice and rock, ice thickness is not well resolved. The ice thicknesses derived from HEM data are consistent with the previous drillhole data from Mount Adams and radar data from both volcanoes, with mean thicknesses of 57 m for Mount Adams and 68 m for Mount Baker. The thickest ice on Mount Baker rests on the gentle lower slopes whereas the thickest ice at Mount Adams lies on the flat summit. Ice volume calculations suggest that Mount Baker contains ∽710 × 10</span><span class=\"sup\">6</span><span>&nbsp;m</span><sup><span class=\"sup\">3</span></sup><span>&nbsp;of ice in the HEM survey area, with a crude estimate of ∽1800 × 10</span><span class=\"sup\">6</span><span>m</span><sup><span class=\"sup\">3</span></sup><span>&nbsp;for the entire volcano. Ice volume on Mount Adams is 65 × 10</span><span class=\"sup\">6</span><span>m</span><sup><span class=\"sup\">3</span></sup><span><sup>&nbsp;</sup>in parts of the HEM survey area and ∽200 × 10</span><span class=\"sup\">6</span><span>m</span><sup><span class=\"sup\">3</span></sup><span>&nbsp;overall.</span></p>","language":"English","publisher":"International Glaciology Society","doi":"10.3189/2012JoG11J098","usgsCitation":"Finn, C.A., Deszcz-Pan, M., and Bedrosian, P.A., 2012, Helicopter electromagnetic data map ice thickness at Mount Adams and Mount Baker, Washington, USA: Journal of Glaciology, v. 58, no. 212, p. 1133-1143, https://doi.org/10.3189/2012JoG11J098.","productDescription":"11 p.","startPage":"1133","endPage":"1143","ipdsId":"IP-018539","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3189/2012jog11j098","text":"Publisher Index Page"},{"id":376337,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Adams, Mount Baker","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.66122436523436,\n              46.059891147620725\n            ],\n            [\n              -121.38381958007812,\n              46.059891147620725\n            ],\n            [\n              -121.38381958007812,\n              46.31848113932307\n            ],\n            [\n              -121.66122436523436,\n              46.31848113932307\n            ],\n            [\n              -121.66122436523436,\n              46.059891147620725\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.91734313964844,\n              48.70410346344752\n            ],\n            [\n              -121.7401885986328,\n              48.70410346344752\n            ],\n            [\n              -121.7401885986328,\n              48.849806364881616\n            ],\n            [\n              -121.91734313964844,\n              48.849806364881616\n            ],\n            [\n              -121.91734313964844,\n              48.70410346344752\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"58","issue":"212","noUsgsAuthors":false,"publicationDate":"2017-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Finn, Carol A. 0000-0002-6178-0405 cfinn@usgs.gov","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":1326,"corporation":false,"usgs":true,"family":"Finn","given":"Carol","email":"cfinn@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":792685,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deszcz-Pan, Maria 0000-0002-6298-5314 maryla@usgs.gov","orcid":"https://orcid.org/0000-0002-6298-5314","contributorId":1263,"corporation":false,"usgs":true,"family":"Deszcz-Pan","given":"Maria","email":"maryla@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":792686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":792687,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209742,"text":"70209742 - 2012 - Impacts of climate change on ecosystem services","interactions":[],"lastModifiedDate":"2020-04-23T16:12:44.458258","indexId":"70209742","displayToPublicDate":"2012-12-31T11:03:21","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"4","title":"Impacts of climate change on ecosystem services","docAbstract":"<p>Key Findings </p><p>By 2050, climate change will triple the fraction of counties in the U.S. that are at high or extremely high risk of outstripping their water supplies (from 10 percent to 32 percent). The most at risk areas in the U.S. are the West, Southwest and Great Plains regions. </p><p>Regulation of drinking water quality will be strained as high rainfall and river discharge conditions may lead to higher levels of nitrogen in rivers and greater risk of waterborne disease outbreaks. </p><p>Climate change will have uneven effects on timber production across the U.S. Recent increases in tree mortality due to disease and pests, and the intensity of fires and area burned will continue to destroy productive forests. On the other hand, in some regions climate change is expected to boost overall forest productivity due to longer growing seasons. </p><p>There is a better than 50 percent chance that climate change will overwhelm the ability of natural systems to mitigate the harm to people resulting from extreme weather events (such as heat waves, heavy rains, and drought). </p><p>Vulnerability of people and property in coastal areas is highly likely to increase dramatically – due to the effects of sea-level rise, storm surge, and the loss of habitats that provide protection from flooding and erosion. The areas at greatest risk to coastal hazards in the U.S. are the Atlantic and Gulf coasts. </p><p>The human communities most vulnerable to climate-related increases in coastal hazards are the elderly and the poor who are less able to respond quickly before and during hazards and to respond over the long term through relocation. </p><p>Changes in abundance and ranges of commercially important marine fish are highly likely to result in loss of some local fisheries, and increases in value for others if fishing communities and management practices can adapt. </p><p>In recreation and tourism, the greatest negative climate impacts will continue to be felt in winter sports and beach recreation (due to coastal erosion). Other forms of recreation are highly likely to increase due to better weather, leading to a redistribution of the industry and its economic impacts, with visitors and tourism dollars shifting away from some communities in favor of others. </p><p>Supporting, regulating, and provisioning ecosystem services all contribute to food security in the United States, and the fate of the nation’s food production are very likely to depend on the interplay of these services and how the agriculture and fishery sectors respond to climate stresses. </p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts of climate change on biodiversity, ecosystems, and ecosystem services: technical input to the 2013 National Climate Assessment","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"United States Global Change Research Program","usgsCitation":"Kareiva, P., Ruckleshaus, M., Arkema, K.K., Geller, G., Girvetz, E., Goodrich, D., Nelson, E., Matzek, V., Pinsky, M., Reid, W., Saunders, M., Semmens, D.J., and Tallis, H., 2012, Impacts of climate change on ecosystem services, chap. 4 <i>of</i> Impacts of climate change on biodiversity, ecosystems, and ecosystem services: technical input to the 2013 National Climate Assessment, p. 4.1-4.41.","productDescription":"41 p.","startPage":"4.1","endPage":"4.41","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":374227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":374226,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://downloads.globalchange.gov/nca/technical_inputs/Biodiversity-Ecosystems-and-Ecosystem-Services-Technical-Input.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kareiva, Peter","contributorId":58160,"corporation":false,"usgs":true,"family":"Kareiva","given":"Peter","email":"","affiliations":[],"preferred":false,"id":787781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruckleshaus, Mary","contributorId":224332,"corporation":false,"usgs":false,"family":"Ruckleshaus","given":"Mary","email":"","affiliations":[],"preferred":false,"id":787782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arkema, Katie K.","contributorId":191584,"corporation":false,"usgs":false,"family":"Arkema","given":"Katie","middleInitial":"K.","affiliations":[],"preferred":false,"id":787783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geller, Gary","contributorId":81395,"corporation":false,"usgs":true,"family":"Geller","given":"Gary","affiliations":[],"preferred":false,"id":787784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Girvetz, Evan","contributorId":104764,"corporation":false,"usgs":true,"family":"Girvetz","given":"Evan","email":"","affiliations":[],"preferred":false,"id":787785,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goodrich, Dave","contributorId":191587,"corporation":false,"usgs":false,"family":"Goodrich","given":"Dave","email":"","affiliations":[],"preferred":false,"id":787786,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, Erik","contributorId":224331,"corporation":false,"usgs":false,"family":"Nelson","given":"Erik","affiliations":[],"preferred":false,"id":787787,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Matzek, Virginia","contributorId":191588,"corporation":false,"usgs":false,"family":"Matzek","given":"Virginia","email":"","affiliations":[],"preferred":false,"id":787788,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pinsky, Malin","contributorId":191589,"corporation":false,"usgs":false,"family":"Pinsky","given":"Malin","email":"","affiliations":[],"preferred":false,"id":787789,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reid, Walt","contributorId":191590,"corporation":false,"usgs":false,"family":"Reid","given":"Walt","email":"","affiliations":[],"preferred":false,"id":787790,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Saunders, Martin","contributorId":191591,"corporation":false,"usgs":false,"family":"Saunders","given":"Martin","email":"","affiliations":[],"preferred":false,"id":787791,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787792,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Tallis, Heather","contributorId":176800,"corporation":false,"usgs":false,"family":"Tallis","given":"Heather","email":"","affiliations":[],"preferred":false,"id":787793,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70259358,"text":"70259358 - 2012 - Bedrock basins in the Sierra Nevada, Alta California","interactions":[],"lastModifiedDate":"2024-10-07T11:04:29.20218","indexId":"70259358","displayToPublicDate":"2012-12-31T09:02:47","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5361,"text":"California Archaeology","active":true,"publicationSubtype":{"id":10}},"title":"Bedrock basins in the Sierra Nevada, Alta California","docAbstract":"A 360-km-long belt of more than 1,400 meter-sized granitic bedrock\nbasins occurs at 1,200 to 2,500 m elevation on the west flank of the Sierra Nevada.\nThe circular, smooth basins are 0.7 to 1.7 min diameter and are commonly\n50 to 1,000 liters in volume. They are man-made as shown by their restricted size\nand elevation range, uniform circular shape, distinct basin shapes in different\ncultural areas, and the presence of bedrock mortars at 80 percent of the basin\nsites. Moreover, the juxtaposition of a northern cluster of basins to the vicinity\nof a rare salt spring suggests that these basins were constructed to evaporate salt.\nSeveral basins contain an A.O. 1350 volcanic ash, indicating that some existed\nbefore the end of the Medieval Climatic Anomaly (MCA; A.O. 800-1350). The basin\nbelt was more productive in terms of food sources during the MCA, and it is\npostulated that warmer, drier conditions promoted the construction of cisterns\nto contain fresh water in order to prolong the time of occupation of mountain\ncamps in late summer. Construction of the granitic basins required enormous\nenergy and produced one of the largest and better preserved sets of Native\nCalifornian features.","language":"English","publisher":"Society for California Archaeology","usgsCitation":"Moore, J.G., Gorden, M., and Sisson, T.W., 2012, Bedrock basins in the Sierra Nevada, Alta California: California Archaeology, v. 4, no. 1, p. 99-122.","productDescription":"24 p.","startPage":"99","endPage":"122","ipdsId":"IP-029928","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":462595,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, James G. 0000-0002-7543-2401 jmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-7543-2401","contributorId":2892,"corporation":false,"usgs":true,"family":"Moore","given":"James","email":"jmoore@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":915028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorden, Mary A.","contributorId":344940,"corporation":false,"usgs":false,"family":"Gorden","given":"Mary A.","affiliations":[{"id":82438,"text":"Southern Sierra Archeological Society","active":true,"usgs":false}],"preferred":false,"id":915030,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sisson, Thomas W. 0000-0003-3380-6425 tsisson@usgs.gov","orcid":"https://orcid.org/0000-0003-3380-6425","contributorId":2341,"corporation":false,"usgs":true,"family":"Sisson","given":"Thomas","email":"tsisson@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":915029,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189078,"text":"70189078 - 2012 - Arsenic-induced biochemical and genotoxic effects and distribution in tissues of Sprague-Dawley rats","interactions":[],"lastModifiedDate":"2017-06-29T17:49:12","indexId":"70189078","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2732,"text":"Microchemical Journal","active":true,"publicationSubtype":{"id":10}},"title":"Arsenic-induced biochemical and genotoxic effects and distribution in tissues of Sprague-Dawley rats","docAbstract":"<p><span>Arsenic (As) is a well documented human carcinogen. However, its mechanisms of toxic action and carcinogenic potential in animals have not been conclusive. In this research, we investigated the biochemical and genotoxic effects of As and studied its distribution in selected tissues of Sprague–Dawley rats. Four groups of six male rats, each weighing approximately 60</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>2</span><span>&nbsp;</span><span>g, were injected intraperitoneally, once a day for 5</span><span>&nbsp;</span><span>days with doses of 5, 10, 15, 20</span><span>&nbsp;</span><span>mg/kg BW of arsenic trioxide. A control group was also made of 6 animals injected with distilled water. Following anaesthetization, blood was collected and enzyme analysis was performed by spectrophotometry following standard protocols. At the end of experimentation, the animals were sacrificed, and the lung, liver, brain and kidney were collected 24</span><span>&nbsp;</span><span>h after the fifth day treatment. Chromosome and micronuclei preparation was obtained from bone marrow cells. Arsenic exposure significantly increased (</span><i>p</i><span>&nbsp;</span><span>&lt;</span><span>&nbsp;</span><span>0.05) the activities of plasma alanine aminotransferase–glutamate pyruvate transaminase (ALT/GPT), and aspartate aminotransferase–glutamate oxaloacetate transaminase (AST/GOT), as well as the number of structural chromosomal aberrations (SCA) and frequency of micronuclei (MN) in the bone marrow cells. In contrast, the mitotic index in these cells was significantly reduced (</span><i>p</i><span>&nbsp;</span><span>&lt;</span><span>&nbsp;</span><span>0.05). These findings indicate that aminotransferases are candidate biomarkers for arsenic-induced hepatotoxicity. Our results also demonstrate that As has a strong genotoxic potential, as measured by the bone marrow SCA and MN tests in Sprague–Dawley rats. Total arsenic concentrations in tissues were measured by inductively coupled plasma mass spectrometry (ICP-MS). A dynamic reaction cell (DRC) with hydrogen gas was used to eliminate the ArCl interference at mass 75, in the measurement of total As. Total As doses in tissues tended to correlate with specific exposure levels.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.microc.2012.08.013","usgsCitation":"Patlolla, A.K., Todorov, T.I., Tchounwou, P.B., van der Voet, G., and Centeno, J.A., 2012, Arsenic-induced biochemical and genotoxic effects and distribution in tissues of Sprague-Dawley rats: Microchemical Journal, v. 105, p. 101-107, https://doi.org/10.1016/j.microc.2012.08.013.","productDescription":"7 p.","startPage":"101","endPage":"107","ipdsId":"IP-038074","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474182,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3500913","text":"External Repository"},{"id":343198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"105","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595611c5e4b0d1f9f05067d7","contributors":{"authors":[{"text":"Patlolla, Anita K.","contributorId":194031,"corporation":false,"usgs":false,"family":"Patlolla","given":"Anita","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":702965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Todorov, Todor I. ttodorov@usgs.gov","contributorId":1605,"corporation":false,"usgs":true,"family":"Todorov","given":"Todor","email":"ttodorov@usgs.gov","middleInitial":"I.","affiliations":[],"preferred":true,"id":702787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tchounwou, Paul B.","contributorId":194032,"corporation":false,"usgs":false,"family":"Tchounwou","given":"Paul","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":702966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Voet, Gijsbert","contributorId":194033,"corporation":false,"usgs":false,"family":"van der Voet","given":"Gijsbert","email":"","affiliations":[],"preferred":false,"id":702967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Centeno, Jose A.","contributorId":107724,"corporation":false,"usgs":true,"family":"Centeno","given":"Jose","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":702968,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70040532,"text":"70040532 - 2012 - Thermal infrared remote sensing of water temperature in riverine landscapes","interactions":[],"lastModifiedDate":"2022-12-20T17:07:02.696739","indexId":"70040532","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"5","title":"Thermal infrared remote sensing of water temperature in riverine landscapes","docAbstract":"<p>Water temperature in riverine landscapes is an important regional indicator of water quality that is influenced by both ground- and surface-water inputs, and indirectly by land use in the surrounding watershed (Brown and Krygier, 1970; Beschta et al., 1987; Chen et al., 1998; Poole and Berman, 2001). Coldwater fishes such as salmon and trout are sensitive to elevated water temperature; therefore, water temperature must meet management guidelines and quality standards, which aim to create a healthy environment for endangered populations (McCullough et al., 2009). For example, in the USA, the Environmental Protection Agency (EPA) has established water quality standards to identify specific temperature criteria to protect coldwater fishes (Environmental Protection Agency, 2003). Trout and salmon can survive in cool-water refugia even when temperatures at other measurement locations are at or above the recommended maximums (Ebersole et al., 2001; Baird and Krueger, 2003; High et al., 2006). Spatially extensive measurements of water temperature are necessary to locate these refugia, to identify the location of ground- and surface-water inputs to the river channel, and to identify thermal pollution sources. Regional assessment of water temperature in streams and rivers has been limited by sparse sampling in both space and time. Water temperature has typically been measured using a network of widely distributed instream gages, which record the temporal change of the bulk, or kinetic, temperature of the water (Tk) at specific locations. For example, the State of Washington (USA) recorded water quality conditions at 76 stations within the Puget Lowlands eco region, which contains 12,721 km of streams and rivers (Washington Department of Ecology, 1998). Such gages are sparsely distributed, are typically located only in larger streams and rivers, and give limited information about the spatial distribution of water temperature (Cherkauer et al., 2005).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fluvial remote sensing for science and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Wiley","doi":"10.1002/9781119940791.ch5","usgsCitation":"Handcock, R., Torgersen, C.E., Cherkauer, K.A., Gillespie, A.R., Tockner, K., Faux, R., and Tan, J., 2012, Thermal infrared remote sensing of water temperature in riverine landscapes, chap. 5 <i>of</i> Fluvial remote sensing for science and management, p. 85-113, https://doi.org/10.1002/9781119940791.ch5.","productDescription":"29 p.","startPage":"85","endPage":"113","ipdsId":"IP-031079","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":350336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-08-14","publicationStatus":"PW","scienceBaseUri":"5a61053fe4b06e28e9c25528","contributors":{"editors":[{"text":"Carbonneau, Patrice E.","contributorId":147604,"corporation":false,"usgs":false,"family":"Carbonneau","given":"Patrice","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":859740,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Piégay, Hervé","contributorId":147605,"corporation":false,"usgs":false,"family":"Piégay","given":"Hervé","affiliations":[],"preferred":false,"id":859741,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Handcock, R. N","contributorId":120699,"corporation":false,"usgs":false,"family":"Handcock","given":"R. N","affiliations":[],"preferred":false,"id":514720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":3578,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":725427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherkauer, K. A","contributorId":117853,"corporation":false,"usgs":false,"family":"Cherkauer","given":"K.","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":514717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillespie, A. R","contributorId":118218,"corporation":false,"usgs":true,"family":"Gillespie","given":"A.","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":514718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tockner, K","contributorId":119480,"corporation":false,"usgs":true,"family":"Tockner","given":"K","affiliations":[],"preferred":false,"id":514719,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Faux, R. N.","contributorId":115182,"corporation":false,"usgs":true,"family":"Faux","given":"R. N.","affiliations":[],"preferred":false,"id":514716,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tan, Jing","contributorId":147609,"corporation":false,"usgs":false,"family":"Tan","given":"Jing","email":"","affiliations":[],"preferred":false,"id":725428,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70189363,"text":"70189363 - 2012 - Using computational modeling of river flow with remotely sensed data to infer channel bathymetry","interactions":[],"lastModifiedDate":"2017-07-11T16:17:30","indexId":"70189363","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using computational modeling of river flow with remotely sensed data to infer channel bathymetry","docAbstract":"<p><span>As part of an ongoing investigation into the use of computational river flow and morphodynamic models for the purpose of correcting and extending remotely sensed river datasets, a simple method for inferring channel bathymetry is developed and discussed. The method is based on an inversion of the equations expressing conservation of mass and momentum to develop equations that can be solved for depth given known values of vertically-averaged velocity and water-surface elevation. The ultimate goal of this work is to combine imperfect remotely sensed data on river planform, water-surface elevation and water-surface velocity in order to estimate depth and other physical parameters of river channels. In this paper, the technique is examined using synthetic data sets that are developed directly from the application of forward two-and three-dimensional flow models. These data sets are constrained to satisfy conservation of mass and momentum, unlike typical remotely sensed field data sets. This provides a better understanding of the process and also allows assessment of how simple inaccuracies in remotely sensed estimates might propagate into depth estimates. The technique is applied to three simple cases: First, depth is extracted from a synthetic dataset of vertically averaged velocity and water-surface elevation; second, depth is extracted from the same data set but with a normally-distributed random error added to the water-surface elevation; third, depth is extracted from a synthetic data set for the same river reach using computed water-surface velocities (in place of depth-integrated values) and water-surface elevations. In each case, the extracted depths are compared to the actual measured depths used to construct the synthetic data sets (with two- and three-dimensional flow models). Errors in water-surface elevation and velocity that are very small degrade depth estimates and cannot be recovered. Errors in depth estimates associated with assuming water-surface velocities equal to depth-integrated velocities are substantial, but can be reduced with simple corrections.</span></p>","largerWorkTitle":"IAHR Riverflow 2012 Conference Proceedings","conferenceTitle":"IAHR Riverflow 2012 Conference","language":"English","usgsCitation":"Nelson, J.M., McDonald, R.R., Kinzel, P.J., and Shimizu, Y., 2012, Using computational modeling of river flow with remotely sensed data to infer channel bathymetry, <i>in</i> IAHR Riverflow 2012 Conference Proceedings, p. 761-768.","productDescription":"8 p.","startPage":"761","endPage":"768","ipdsId":"IP-036984","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343612,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcnetbase.com/doi/abs/10.1201/b13250-115"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965babce4b0d1f9f05b38d3","contributors":{"authors":[{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":704373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":704374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shimizu, Y.","contributorId":88177,"corporation":false,"usgs":true,"family":"Shimizu","given":"Y.","affiliations":[],"preferred":false,"id":704376,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70193242,"text":"70193242 - 2012 - Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope","interactions":[],"lastModifiedDate":"2017-10-31T12:21:00","indexId":"70193242","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3002,"text":"Paleoceanography","active":true,"publicationSubtype":{"id":10}},"title":"Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope","docAbstract":"<p><span>Biogenic opal, organic carbon, organic matter stable isotope, and trace metal data from a well-dated, high-resolution jumbo piston core (EW0408–85JC; 59° 33.3′N, 144° 9.21′W, 682 m water depth) recovered from the northern Gulf of Alaska continental slope reveal changes in productivity and nutrient utilization over the last 17,000 years. Maximum values of opal concentration (∼10%) occur during the deglacial Bølling-Allerød (B-A) interval and earliest Holocene (11.2 to 10.8 cal ka BP), moderate values (∼6%) occur during the Younger Dryas (13.0 to 11.2 cal ka BP) and Holocene, and minimum values (∼3.5%) occur during the Late Glacial Interval (LGI). When converted to opal mass accumulation rates, the highest values (∼5000 g cm</span><sup>−2</sup><span><span>&nbsp;</span>kyr</span><sup>−1</sup><span>) occur during the LGI prior to 16.7 cal ka BP, which points to a strong influence by LGI glacimarine sedimentation regimes. Similar patterns are also observed in total organic carbon and cadmium paleoproductivity proxies. Mid-Holocene peaks in the terrestrial organic matter fraction at 5.5, 4.7, 3.5, and 1.2 cal ka BP indicate periods of enhanced delivery of glaciomarine sediments by the Alaska Coastal Current. The B-A and earliest Holocene intervals are laminated, and enrichments of redox-sensitive elements suggest dysoxic-to-anoxic conditions in the water column. The laminations are also associated with mildly enriched sedimentary<span>&nbsp;</span></span><i>δ</i><sup>15</sup><span>N ratios, indicating a link between productivity, nitrogen cycle dynamics, and sedimentary anoxia. After applying a correction for terrestrial<span>&nbsp;</span></span><i>δ</i><sup>15</sup><span>N contributions based on end-member mixing models of terrestrial and marine organic matter, the resulting B-A marine<span>&nbsp;</span></span><i>δ</i><sup>15</sup><span>N (6.3 ± 0.4 ‰) ratios are consistent with either mild denitrification, or increased nitrate utilization. These findings can be explained by increased micronutrient (Fe) availability during episodes of rapid rising sea level that released iron from the previously subaerial coastal plain; iron input from enhanced terrestrial runoff; and/or the intermittent presence of seasonal sea ice resulting from altered ocean/atmospheric circulation during the B-A in the Gulf of Alaska.</span></p>","language":"English","publisher":"Wiley","doi":"10.1029/2011PA002161","usgsCitation":"Addison, J.A., Finney, B., Dean, W.E., Davies, M., Mix, A.C., and Jaeger, J.M., 2012, Productivity and sedimentary δ15N variability for the last 17,000 years along the northern Gulf of Alaska continental slope: Paleoceanography, v. 27, PA1206; 17 p., https://doi.org/10.1029/2011PA002161.","productDescription":"PA1206; 17 p.","ipdsId":"IP-029801","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011pa002161","text":"Publisher Index Page"},{"id":347853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149,\n              57.76\n            ],\n            [\n              -136,\n              57.76\n            ],\n            [\n              -136,\n              63\n            ],\n            [\n              -149,\n              63\n            ],\n            [\n              -149,\n             57.76\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"27","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-02-09","publicationStatus":"PW","scienceBaseUri":"59f98bbee4b0531197afa045","contributors":{"authors":[{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":718342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finney, Bruce P.","contributorId":88074,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce P.","affiliations":[],"preferred":false,"id":718344,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dean, Walter E. dean@usgs.gov","contributorId":1801,"corporation":false,"usgs":true,"family":"Dean","given":"Walter","email":"dean@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":718347,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Davies, Maureen H.","contributorId":91311,"corporation":false,"usgs":true,"family":"Davies","given":"Maureen H.","affiliations":[],"preferred":false,"id":718346,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mix, Alan C.","contributorId":83346,"corporation":false,"usgs":true,"family":"Mix","given":"Alan","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":718343,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jaeger, John M.","contributorId":11423,"corporation":false,"usgs":true,"family":"Jaeger","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":718345,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70157463,"text":"70157463 - 2012 - Genetic variation reveals influence of landscape connectivity on population dynamics and resiliency of western trout in disturbance-prone habitats","interactions":[],"lastModifiedDate":"2017-05-10T09:33:18","indexId":"70157463","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":295,"text":"Technical Report","active":false,"publicationSubtype":{"id":4}},"seriesNumber":" RMRS-GTR-290","title":"Genetic variation reveals influence of landscape connectivity on population dynamics and resiliency of western trout in disturbance-prone habitats","docAbstract":"Salmonid fishes have evolved and persisted in dynamic ecosystems where disturbance events vary in frequency, magnitude, timing, and duration, as well as the specific nature of associated effects (e.g., changes in thermal or flow regimes, geomorphology, or water chemistry). In the western United States, one of the major drivers of disturbance in stream ecosystems is fire. Although there is a growing consensus that fish populations can ultimately benefit from the productive and heterogeneous habitats created by fire, to persist they obviously have to withstand the immediate and shorter-term effects of fire, which can reduce or even extirpate local populations. Movement among interconnected stream habitats is thought to be an important strategy enabling persistence during and following fire, and there is mounting concern that the extensive isolation of salmonid populations in fragmented habitats is reducing their resiliency to fire. In spite of this concern, there are few direct observations of salmonid responses to fire. In fact, guidance is based largely on a broader understanding of the influences of landscape structure and disturbance in general on salmonid fishes, and there is considerable uncertainty about how best to manage for salmonid resilience to wildfire. Studies are limited by the difficult logistics of following fish responses in the face of unpredictable events such as wildfires. Therefore, BACI (Before-After-Control-Impact) study designs are nearly impossible, and replication is similarly challenging because fires are often low-frequency events. Furthermore, conventional ecological study approaches (e.g., studies of fish distribution, abundance, life histories, and movement) are logistically difficult to implement. Overall, a major challenge to understanding resilience of salmonid populations in fire-prone environments is related to moving beyond localized case studies to those with broader applicability in wildfire management . Genetic data can be useful for overcoming many of the limitations inherent in ecological studies. Here we review several case studies of western trout where population genetic data have provided insight about fish responses to fragmentation and disturbance more generally, and specifically in relation to fire. Results of these studies confirm the importance of movement and landscape connectivity for ensuring fish persistence in fire-prone landscapes, and highlight the usefulness of genetic approaches for broad-scale evaluation and monitoring of population responses to fire and related management actions.","largerWorkType":{"id":18,"text":"Report"},"largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"US Forest Service","usgsCitation":"Helen M. Neville, Gresswell, R.E., and Dunham, J.B., 2012, Genetic variation reveals influence of landscape connectivity on population dynamics and resiliency of western trout in disturbance-prone habitats: Technical Report  RMRS-GTR-290, 10 p.","productDescription":"10 p.","startPage":"177","endPage":"186","ipdsId":"IP-013149","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":341048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":341046,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.treesearch.fs.fed.us/pubs/41932"}],"country":"United States","publishingServiceCenter":{"id":3,"text":"Helena PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591426c0e4b0e541a03e961c","contributors":{"authors":[{"text":"Helen M. Neville","contributorId":147922,"corporation":false,"usgs":false,"family":"Helen M. Neville","affiliations":[{"id":6579,"text":"Trout Unlimited, Boise, ID, USA","active":true,"usgs":false}],"preferred":false,"id":573240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gresswell, Robert E. 0000-0003-0063-855X bgresswell@usgs.gov","orcid":"https://orcid.org/0000-0003-0063-855X","contributorId":147914,"corporation":false,"usgs":true,"family":"Gresswell","given":"Robert","email":"bgresswell@usgs.gov","middleInitial":"E.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":573238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":573239,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70192274,"text":"70192274 - 2012 - Mineralogy and environmental geochemistry of historical iron slag, Hopewell Furnace National Historic Site, Pennsylvania, USA","interactions":[],"lastModifiedDate":"2020-06-19T16:56:09.928533","indexId":"70192274","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Mineralogy and environmental geochemistry of historical iron slag, Hopewell Furnace National Historic Site, Pennsylvania, USA","docAbstract":"<p id=\"sp010\">The Hopewell Furnace National Historic Site in southeastern Pennsylvania, which features an Fe smelter that was operational in the 18th and 19th centuries, is dominated by three slag piles. Pile 1 slag, from the Hopewell Furnace, and pile 2 slag, likely from the nearby Cornwall Furnace, were both produced in cold-blast charcoal-fired smelters. In contrast, pile 3 slag was produced in an anthracite furnace. Ore samples from the nearby Jones and Hopewell mines that fed the smelter are mainly magnetite-rich with some sulfides (pyrite, chalcopyrite, sphalerite) and accessory silicates (quartz, garnet, feldspar, and clay minerals). Slag piles 1 and 2 are similar mineralogically containing predominantly skeletal and dendritic aluminian diopside and augite, skeletal forsteritic olivine, glass, rounded blebs of metallic Fe, and exotic quartz. Olivine is a major phase in all samples from pile 2, whereas it occurs in only a few samples from pile 1. Samples of the &lt;2&nbsp;mm-size fraction of surface composite slag material or crushed slag from at depth in piles 1 and 2 are mineralogically similar to the large surface slag fragments from those piles with the addition of phases such as feldspars, Fe oxides, and clay minerals that are either secondary weathering products or entrained from the underlying bedrock. Pile 3 slag contains mostly skeletal forsteritic olivine and Ti-bearing aluminian diopside, dendritic or fine-grained subhedral melilite, glass, euhedral spinel, metallic Fe, alabandite–oldhamite solid solution, as well as a sparse Ti carbonitride phase. The bulk chemistry of the slag is dominated by Al<sub>2</sub>O<sub>3</sub><span>&nbsp;</span>(8.5–16.2&nbsp;wt.%), CaO (8.2–26.2&nbsp;wt.%), MgO (4.2–24.7&nbsp;wt.%), and SiO<sub>2</sub><span>&nbsp;</span>(36.4–59.8&nbsp;wt.%), constituting between 81% and 97% of the mass of the samples. Piles 1 and 2 are chemically similar; pile 1 slag overall contains the highest Fe<sub>2</sub>O<sub>3</sub>, K<sub>2</sub>O and MnO, and the lowest MgO concentrations. Pile 3 slag is high in Al<sub>2</sub>O<sub>3</sub>, CaO and S, and low in Fe<sub>2</sub>O<sub>3</sub>, K<sub>2</sub>O and SiO<sub>2</sub><span>&nbsp;</span>compared to the other piles. In general, piles 1 and 2 are chemically similar to each other, whereas pile 3 is distinct – a conclusion that reflects their mineralogy. The similarities and differences among piles in terms of mineralogy and major element chemistry result from the different smelting conditions under which the slag formed and include the fuel source, the composition of the ore and flux, the type of blast (cold versus hot), which affects the furnace temperature, and other beneficiation methods.</p><p id=\"sp015\">The three distinct slag piles at Hopewell are enriched in numerous trace elements, such as As (up to 12&nbsp;mg/kg), Cd (up to 0.4&nbsp;mg/kg), Co (up to 31.8&nbsp;mg/kg), Cu (up to 647&nbsp;mg/kg), Mn (up to 0.69&nbsp;wt.%), Pb (up to 172&nbsp;mg/kg) and Zn (up to 393&nbsp;mg/kg), together with Fe (13.9&nbsp;wt.%), when compared to the average for the continental crust, with the &lt;2&nbsp;mm-size fraction commonly containing the highest concentrations. Enrichments in various elements (e.g., Cd, Co, Cu, Pb, Zn) were also found in the ore samples. Despite these enrichments, comparison of bulk chemistry trace-element concentrations to the environmental guidelines suggests most elements are likely not problematic with the exception of As, Co, Fe and Mn. Leachate tests that simulate weathering indicate Fe (up to 973&nbsp;μg/L) and Mn (up to 133&nbsp;μg/L) are readily released in potentially harmful concentrations compared to secondary drinking water and some aquatic ecosystem toxicity criteria. Aluminum and Cu, although not high in the solid compared to environmental guidelines, also exceed relevant criteria in leachate extracts with maximum concentrations of 2700&nbsp;μg/L and 17.7&nbsp;μg/L, respectively. In contrast, As and Co, which are significant in the solids, are not leached in concentrations that exceed guidelines (i.e., 3&nbsp;μg/L or less for both elements). The weathering rates of the Fe metal and Fe oxides, which host Cu and some Fe, are likely higher than the silicate glass, which hosts the majority of Al, Mn and some Fe, and the crystalline silicates and spinels affecting which elements and how much are released into the environment and surrounding aquatic ecosystem. The mineral assemblages and their chemical composition, the bulk sample chemistry, and leachability of trace elements are all important components in understanding the potential environmental impacts of the slag piles.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2011.12.011","usgsCitation":"Piatak, N.M., and Seal, R.R., 2012, Mineralogy and environmental geochemistry of historical iron slag, Hopewell Furnace National Historic Site, Pennsylvania, USA: Applied Geochemistry, v. 27, no. 3, p. 623-643, https://doi.org/10.1016/j.apgeochem.2011.12.011.","productDescription":"21 p.","startPage":"623","endPage":"643","ipdsId":"IP-030685","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":347196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Hopewell Furnace National Historic Site","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.904541015625,\n              40\n            ],\n            [\n              -75.025634765625,\n              40\n            ],\n            [\n              -75.025634765625,\n              40.3\n            ],\n            [\n              -75.904541015625,\n              40.3\n            ],\n            [\n              -75.904541015625,\n              40\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"27","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f05124e4b0220bbd9a1dc0","contributors":{"authors":[{"text":"Piatak, Nadine M. 0000-0002-1973-8537 npiatak@usgs.gov","orcid":"https://orcid.org/0000-0002-1973-8537","contributorId":193010,"corporation":false,"usgs":true,"family":"Piatak","given":"Nadine","email":"npiatak@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":715094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seal, Robert R. 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":193011,"corporation":false,"usgs":true,"family":"Seal","given":"Robert","email":"rseal@usgs.gov","middleInitial":"R.","affiliations":[{"id":250,"text":"Eastern Water Science Field Team","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":715095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70042191,"text":"70042191 - 2012 - <i>Mysis diluviana</i> and <i>Hemimysis anomala</i>: reviewing the roles of a native and invasive mysid in the Laurentian Great Lakes region","interactions":[],"lastModifiedDate":"2012-12-31T15:17:00","indexId":"70042191","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","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":"<i>Mysis diluviana</i> and <i>Hemimysis anomala</i>: reviewing the roles of a native and invasive mysid in the Laurentian Great Lakes region","docAbstract":"<i>Mysis diluviana</i> and <i>Hemimysis anomala</i> are the only two species of mysid shrimps in the order Mysidacea that are present in the Laurentian Great Lakes of North America. <i>M. diluviana</i> has inhabited the deep, cold waters of this region since Pleistocene-era glacial retreat and is widely considered to have a central role in the functioning of offshore food webs in systems they inhabit. More recently, the Great Lakes were invaded by the Ponto-Caspian native <i>Hemimysis</i>, a species that inhabits warmer water and shallower depths relative to <i>M. diluviana</i>. <i>Hemimysis</i> has rapidly expanded throughout the Great Lakes region and has become integrated into nearshore food webs as both food for planktivorous fish and predators and competitors of zooplankton. This special issue is composed of 14 papers that represent the most recent advances in our understanding of the ecological importance of both species of mysids to lake and river ecosystems in the Great Lakes region of North America. Topics discussed in this special issue will inform future research in all systems influenced by mysid ecology.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Ann Arbor, MI","doi":"10.1016/j.jglr.2012.03.003","usgsCitation":"Walsh, M.G., Boscarino, B.T., Marty, J., and Johannsson, O.E., 2012, <i>Mysis diluviana</i> and <i>Hemimysis anomala</i>: reviewing the roles of a native and invasive mysid in the Laurentian Great Lakes region: Journal of Great Lakes Research, v. 38, no. Supplement 2, p. 1-6, https://doi.org/10.1016/j.jglr.2012.03.003.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-035532","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264993,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.03.003"},{"id":264994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie;Lake Huron;Lake Michigan;Lake Ontario;Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.12,41.4 ], [ -92.12,49.0 ], [ -76.0,49.0 ], [ -76.0,41.4 ], [ -92.12,41.4 ] ] ] } } ] }","volume":"38","issue":"Supplement 2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfd0e4b0a4aa5bb0ae40","contributors":{"authors":[{"text":"Walsh, Maureen G.","contributorId":92506,"corporation":false,"usgs":true,"family":"Walsh","given":"Maureen","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":470919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boscarino, Brent T.","contributorId":104361,"corporation":false,"usgs":true,"family":"Boscarino","given":"Brent","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":470920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marty, Jerome","contributorId":24661,"corporation":false,"usgs":true,"family":"Marty","given":"Jerome","email":"","affiliations":[],"preferred":false,"id":470917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johannsson, Ora E.","contributorId":25527,"corporation":false,"usgs":true,"family":"Johannsson","given":"Ora","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":470918,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70042268,"text":"ofr20121237 - 2012 - Establishment of sentinel sampling sites to monitor changes in water and sediment quality and biota related to visitor use at Lake Powell, Arizona and Utah, 2004-2006","interactions":[],"lastModifiedDate":"2012-12-31T11:58:49","indexId":"ofr20121237","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","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":"2012-1237","title":"Establishment of sentinel sampling sites to monitor changes in water and sediment quality and biota related to visitor use at Lake Powell, Arizona and Utah, 2004-2006","docAbstract":"Twenty sentinel sampling sites were established and sampled during 2004–06 at Lake Powell, Arizona and Utah, by the U.S. Geological Survey and the National Park Service—Glen Canyon National Recreation Area. The sentinel sampling sites provide sampling locations on Lake Powell, the Nation’s second largest reservoir that can be visited and sampled repeatedly over time to monitor changes in water and sediment quality and also biota. The sites were established in response to an Environmental Impact Statement that addressed the use of personal watercraft on Lake Powell. The use of personal watercraft can potentially introduce hydrocarbons and other contaminants and are of concern to the health of visitors and aquatic habitats of these environments. Data from this initial sampling period (2004–06) include (1) discrete measurements of water temperature, specific conductance, pH, and water clarity; (2) major ions, nutrients, and organic carbon; (3) trace elements including rare earths; (4) organic compounds including oil and grease, total petroleum hydrocarbons, and volatile organic compounds; (5) polycyclic aromatic hydrocarbons in lakebed sediments; and (6) continuous depth profile measurements of water temperature, specific conductance, pH, dissolved oxygen, and turbidity. Also, the National Park Service-Glen Canyon National Recreation Area collected bacteria samples during this initial sampling period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121237","collaboration":"Prepared in cooperation with the National Park Service, <a href=\"http://www.nps.gov/glca/\" target=\"_blank\">Glen Canyon National Recreation Area</a>","usgsCitation":"Hart, R.J., Taylor, H.E., and Anderson, G., 2012, Establishment of sentinel sampling sites to monitor changes in water and sediment quality and biota related to visitor use at Lake Powell, Arizona and Utah, 2004-2006: U.S. Geological Survey Open-File Report 2012-1237, Report: vi, 25 p.; Table 1; 6 Appendixes: A-F, https://doi.org/10.3133/ofr20121237.","productDescription":"Report: vi, 25 p.; Table 1; 6 Appendixes: A-F","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2004-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":264959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1237.gif"},{"id":264957,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2012/1237/of2012-1237_appendixes_a_c-f.xlsx"},{"id":264958,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2012/1237/of2012-1237_appendix_b.xlsx"},{"id":264955,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1237/"},{"id":264956,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1237/of2012-1237_text.pdf"}],"country":"United States","state":"Arizona;Utah","otherGeospatial":"Glen Canyon National Recreation Area;Lake Powell","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.75,36.75 ], [ -111.75,38.0 ], [ -110.25,38.0 ], [ -110.25,36.75 ], [ -111.75,36.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cff6e4b0a4aa5bb0aeda","contributors":{"authors":[{"text":"Hart, Robert J. bhart@usgs.gov","contributorId":598,"corporation":false,"usgs":true,"family":"Hart","given":"Robert","email":"bhart@usgs.gov","middleInitial":"J.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Howard E. hetaylor@usgs.gov","contributorId":1551,"corporation":false,"usgs":true,"family":"Taylor","given":"Howard","email":"hetaylor@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":471139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, G.M.","contributorId":106373,"corporation":false,"usgs":true,"family":"Anderson","given":"G.M.","email":"","affiliations":[],"preferred":false,"id":471140,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042253,"text":"70042253 - 2012 - Analysis of host genetic diversity and viral entry as sources of between-host variation in viral load","interactions":[],"lastModifiedDate":"2012-12-31T10:19:45","indexId":"70042253","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3699,"text":"Virus Research","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of host genetic diversity and viral entry as sources of between-host variation in viral load","docAbstract":"Little is known about the factors that drive the high levels of between-host variation in pathogen burden that are frequently observed in viral infections. Here, two factors thought to impact viral load variability, host genetic diversity and stochastic processes linked with viral entry into the host, were examined. This work was conducted with the aquatic vertebrate virus, <i>Infectious hematopoietic necrosis virus</i> (IHNV), in its natural host, rainbow trout. It was found that in controlled in vivo infections of IHNV, a suggestive trend of reduced between-fish viral load variation was observed in a clonal population of isogenic trout compared to a genetically diverse population of out-bred trout. However, this trend was not statistically significant for any of the four viral genotypes examined, and high levels of fish-to-fish variation persisted even in the isogenic trout population. A decrease in fish-to-fish viral load variation was also observed in virus injection challenges that bypassed the host entry step, compared to fish exposed to the virus through the natural water-borne immersion route of infection. This trend was significant for three of the four virus genotypes examined and suggests host entry may play a role in viral load variability. However, high levels of viral load variation also remained in the injection challenges. Together, these results indicate that although host genetic diversity and viral entry may play some role in between-fish viral load variation, they are not major factors. Other biological and non-biological parameters that may influence viral load variation are discussed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Virus Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.virusres.2012.01.010","usgsCitation":"Wargo, A.R., Kell, A.M., Scott, R., Thorgaard, G.H., and Kurath, G., 2012, Analysis of host genetic diversity and viral entry as sources of between-host variation in viral load: Virus Research, v. 165, no. 1, p. 71-80, https://doi.org/10.1016/j.virusres.2012.01.010.","productDescription":"10 p.","startPage":"71","endPage":"80","ipdsId":"IP-034640","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":474186,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3314121","text":"External Repository"},{"id":264941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264940,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.virusres.2012.01.010"}],"country":"United States","volume":"165","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfe0e4b0a4aa5bb0ae76","contributors":{"authors":[{"text":"Wargo, Andrew R.","contributorId":47260,"corporation":false,"usgs":true,"family":"Wargo","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":471119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kell, Alison M. amkell@usgs.gov","contributorId":4553,"corporation":false,"usgs":true,"family":"Kell","given":"Alison","email":"amkell@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":471117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scott, Robert J.","contributorId":45600,"corporation":false,"usgs":true,"family":"Scott","given":"Robert J.","affiliations":[],"preferred":false,"id":471118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorgaard, Gary H.","contributorId":60512,"corporation":false,"usgs":true,"family":"Thorgaard","given":"Gary","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":471120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":471116,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042232,"text":"70042232 - 2012 - Repeat surveys of spawning cisco (Coregonus artedi) in western Lake Superior: Timing, distribution and composition of spawning stocks","interactions":[],"lastModifiedDate":"2023-02-14T11:47:59.376547","indexId":"70042232","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":656,"text":"Advances in Limnology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Repeat surveys of spawning cisco (<i>Coregonus artedi</i>) in western Lake Superior: Timing, distribution and composition of spawning stocks","title":"Repeat surveys of spawning cisco (Coregonus artedi) in western Lake Superior: Timing, distribution and composition of spawning stocks","docAbstract":"Acoustic (AC) and midwater trawl (MT) surveys of spawning cisco (<i>Coregonus artedi</i>) in Lake Superior have been combined with commercial yield to estimate exploitation. To time surveys properly, it is important to understand when adults typically arrive at spawning grounds and how numbers change as the spawning season progresses. We conducted repeat autumn surveys during nighttime hours at coastal sites where commercial roe fisheries occur. Spawner densities increased significantly from October to mid-November, but differences measured at sites sampled from mid- to late-November were comparatively small. Spawners occupied the upper 20–30 m of the water column during mid-November before utilizing a wider range of depths by late-November. We compared repeat AC densities to temporal trends of catch-per-unit-effort (CPUE) in suspended commercial gillnets and found good agreement within sites. Because different gillnet mesh sizes were used in each roe fishery. CPUE and AC density were poorly correlated among sites. We recommend that future surveys be conducted between mid- and late-November, and that MT gear be used to measure cisco densities in the uppermost 10 m of the water column where AC estimates may be conservative. Given the short temporal window for assessing spawner density, we believe both AC-MT and gillnet surveys will be needed to ensure that harvest of different stocks is kept at a sustainable level.","language":"English","publisher":"Schweizerbart Science Publishers","publisherLocation":"Stuttgart, Germany","doi":"10.1127/advlim/63/2012/65","usgsCitation":"Yule, D., Schreiner, D.R., Addison, P.A., Seider, M.J., Evrard, L.M., Geving, S.A., and Quinlan, H., 2012, Repeat surveys of spawning cisco (Coregonus artedi) in western Lake Superior: Timing, distribution and composition of spawning stocks: Advances in Limnology, v. 63, p. 65-87, https://doi.org/10.1127/advlim/63/2012/65.","productDescription":"23 p.","startPage":"65","endPage":"87","ipdsId":"IP-008339","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":265006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,46.41 ], [ -92.11,48.88 ], [ -84.35,48.88 ], [ -84.35,46.41 ], [ -92.11,46.41 ] ] ] } } ] }","volume":"63","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a8dee4b0e8fec6cdc83f","contributors":{"authors":[{"text":"Yule, Daniel L.","contributorId":92130,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","affiliations":[],"preferred":false,"id":471056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schreiner, Donald R.","contributorId":108051,"corporation":false,"usgs":true,"family":"Schreiner","given":"Donald","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":471059,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Addison, Peter A.","contributorId":105987,"corporation":false,"usgs":true,"family":"Addison","given":"Peter","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seider, Michael J.","contributorId":19452,"corporation":false,"usgs":true,"family":"Seider","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":471054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evrard, Lori M. 0000-0001-8582-5818 levrard@usgs.gov","orcid":"https://orcid.org/0000-0001-8582-5818","contributorId":2720,"corporation":false,"usgs":true,"family":"Evrard","given":"Lori","email":"levrard@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":471053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geving, Steven A.","contributorId":38040,"corporation":false,"usgs":true,"family":"Geving","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Quinlan, Henry R.","contributorId":93447,"corporation":false,"usgs":true,"family":"Quinlan","given":"Henry R.","affiliations":[],"preferred":false,"id":471057,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70040182,"text":"70040182 - 2012 - Loss and modification of habitat","interactions":[],"lastModifiedDate":"2022-12-20T17:01:04.013581","indexId":"70040182","displayToPublicDate":"2012-12-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Loss and modification of habitat","docAbstract":"Amphibians live in a wide variety of habitats around the world, many of which have been modified or destroyed by human activities. Most species have unique life history characteristics adapted to specific climates, habitats (e.g., lentic, lotic, terrestrial, arboreal, fossorial, amphibious), and local conditions that provide suitable areas for reproduction, development and growth, shelter from environmental extremes, and predation, as well as connectivity to other populations or habitats. Although some species are entirely aquatic or terrestrial, most amphibians, as their name implies, lead a dual life and require a mosaic of habitats in both aquatic and terrestrial ecosystems. With over 6 billion people on Earth, most species are now persisting in habitats that have been directly or indirectly influenced by human activities. Some species have disappeared where their habitats have been completely destroyed, reduced, or rendered unsuitable. Habitat loss and degradation are widely considered by most researchers as the most important causes of amphibian population decline globally (Barinaga 1990; Wake and Morowitz 1991; Alford and Richards 1999). In this chapter, a background on the diverse habitat requirements of amphibians is provided, followed by a discussion of the effects of urbanization, agriculture, livestock grazing, timber production and harvesting, fire and hazardous fuel management, and roads on amphibians and their habitats. Also briefly discussed is the influence on amphibian habitats of natural disturbances, such as extreme weather events and climate change, given the potential for human activities to impact climate in the longer term. For amphibians in general, microhabitats are of greater importance than for other vertebrates. As ectotherms with a skin that is permeable to water and with naked gelatinous eggs, amphibians are physiologically constrained to be active during environmental conditions that provide appropriate body temperatures and adequate water balance (Thorson and Svihla 1943; Brattstrom 1963; Tracy 1976). Hence, individuals require and seek specific microhabitats that maintain their preferred body temperature while at the same time reducing water loss or allowing individuals to re-hydrate. Amphibians also possess relatively few physical attributes that protect them from predators. Although they may avoid predators behaviourally or deter them by skin toxins, amphibians lack defensive shells or hardened cuticles, do not have protective teeth or claws, and most are insufficiently fast to escape predators. Hence, they are relatively dependent on sites that conceal or protect them from predation. Most amphibians also differ significantly from other vertebrates in possessing a complex two-phase life cycle: the pre-metamorphic larval (tadpole) stage and the post-metamorphic juvenile and adult stage (Wilbur 1980, 1984). Most amphibian species have two distinct econes (Heatwole 1989), each with different habitat requirements, the larvae being aquatic and the post-metamorphic animals more terrestrial. The habitats required by the two phases can differ greatly, but both are essential to the survival of a species. However, amphibian diversity is great and exceptions to this general pattern exist. For example, some species have direct development without going through a larval stage and are fully terrestrial, whereas the larvae of other species can reach sexual maturity without going through metamorphosis (i.e., neoteny) and are fully aquatic.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Conservation and decline of amphibians: Ecological aspects, effect of humans, and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Surrey Beatty & Sons","usgsCitation":"Lemckert, F., Hecnar, S., and Pilliod, D., 2012, Loss and modification of habitat, chap. 1 <i>of</i> Conservation and decline of amphibians: Ecological aspects, effect of humans, and management, v. 10, 52 p.","productDescription":"52 p.","ipdsId":"IP-040483","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":349743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61053fe4b06e28e9c2552c","contributors":{"authors":[{"text":"Lemckert, Francis","contributorId":147197,"corporation":false,"usgs":false,"family":"Lemckert","given":"Francis","email":"","affiliations":[],"preferred":false,"id":724509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hecnar, Stephen","contributorId":147198,"corporation":false,"usgs":false,"family":"Hecnar","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":724510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":147050,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":724511,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70049351,"text":"70049351 - 2012 - Stochastic analyses to identify wellfield withdrawal effects on surface-water and groundwater in Miami-Dade County, Florida","interactions":[],"lastModifiedDate":"2014-02-05T15:21:15","indexId":"70049351","displayToPublicDate":"2012-12-30T15:14:54","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic analyses to identify wellfield withdrawal effects on surface-water and groundwater in Miami-Dade County, Florida","docAbstract":"Several stochastic analyses were conducted in Miami-Dade County, Florida, to evaluate the effects of\nwellfield withdrawal on aquifer water levels, canal stage, and canal flow. Multiyear data for withdrawals\nat four water-supply wellfields, water levels at the S-121 canal control structure and groundwater head at\na nearby monitoring well were used to determine the interrelation between wellfield withdrawals and\nwater levels in the canal and aquifer. A spectral analysis was performed first on the wellfield withdrawals,\nshowing similar patterns of fluctuations, but no well-defined seasonality. In order to compare\nwater-level response with withdrawals at each wellfield, the intercorrelation effects between wellfields\nwas removed through a ‘causal chain’ approach where the inter-wellfield correlation is used to isolate\nthe wellfield/water-level correlation.\n<br/>\n<p>Most computed correlations have magnitudes less than 5 percent, but with statistical significance\nabove 90 percent. Results indicate that withdrawals from the wellfields most distant from the canal had\nno significant correlation to the canal levels. However the highest correlation was not at the wellfield\nclosest to the canal, but at the two wellfields at the intermediate distance that have higher withdrawal\nrates. The hydraulic interconnectivity of the canal with the rest of the canal network, covering the study\narea, allows the canal equalizes with all connected canals. This explains why proximity to a particular\ncanal location does not appear to be as important a factor as the withdrawal rate. Groundwater levels are\nmore highly correlated to a wellfield on the same side of the canal, and to pumping wells in the same\nwellfield on the same side of the canal. This indicates that canals are an effective barrier and source/sink\nfor the groundwater. Further nonlinear correlation analysis indicates that high withdrawal rates disproportionally\naffect water levels and are the predominant effect on the canal.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2012.08.033","usgsCitation":"Swain, E., 2012, Stochastic analyses to identify wellfield withdrawal effects on surface-water and groundwater in Miami-Dade County, Florida: Journal of Environmental Management, v. 113, p. 15-21, https://doi.org/10.1016/j.jenvman.2012.08.033.","productDescription":"7 p.","startPage":"15","endPage":"21","ipdsId":"IP-021978","costCenters":[{"id":286,"text":"Florida Water Science Center-Ft. Lauderdale","active":false,"usgs":true}],"links":[{"id":282057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282056,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jenvman.2012.08.033"}],"country":"United States","state":"Florida","county":"Miami-dade County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.8736,25.1374 ], [ -80.8736,25.9794 ], [ -80.1179,25.9794 ], [ -80.1179,25.1374 ], [ -80.8736,25.1374 ] ] ] } } ] }","volume":"113","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7428e4b0b29085109606","contributors":{"authors":[{"text":"Swain, Eric 0000-0001-7168-708X","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":23347,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","affiliations":[],"preferred":false,"id":486106,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70042217,"text":"sir20125262 - 2012 - Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California","interactions":[],"lastModifiedDate":"2012-12-28T13:48:13","indexId":"sir20125262","displayToPublicDate":"2012-12-28T00:00:00","publicationYear":"2012","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":"2012-5262","title":"Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California","docAbstract":"Rapid growth and development within Carson Valley in Douglas County, Nevada, and Alpine County, California, has caused concern over the continued availability of groundwater, and whether the increased municipal demand could either impact the availability of water or result in decreased flow in the Carson River. Annual pumpage of groundwater has increased from less than 10,000 acre feet per year (acre-ft/yr) in the 1970s to about 31,000 acre-ft/yr in 2004, with most of the water used in agriculture. Municipal use of groundwater totaled about 10,000 acre-feet in 2000. In comparison, average streamflow entering the valley from 1940 to 2006 was 344,100 acre-ft/yr, while average flow exiting the valley was 297,400 acre-ft/yr. Carson Valley is underlain by semi-consolidated Tertiary sediments that are exposed on the eastern side and dip westward. Quaternary fluvial and alluvial deposits overlie the Tertiary sediments in the center and western side of the valley. The hydrology of Carson Valley is dominated by the Carson River, which supplies irrigation water for about 39,000 acres of farmland and maintains the water table less than 5 feet (ft) beneath much of the valley floor. Perennial and ephemeral watersheds drain the Carson Range and the Pine Nut Mountains, and mountain-front recharge to the groundwater system from these watersheds is estimated to average 36,000 acre-ft/yr. Groundwater in Carson Valley flows toward the Carson River and north toward the outlet of the Carson Valley. An upward hydraulic gradient exists over much of the valley, and artesian wells flow at land surface in some areas. Water levels declined as much as 15 ft since 1980 in some areas on the eastern side of the valley. Median estimated transmissivities of Quaternary alluvial-fan and fluvial sediments, and Tertiary sediments are 316; 3,120; and 110 feet squared per day (ft<sup>2</sup>/d), respectively, with larger transmissivity values in the central part of the valley and smaller values near the valley margins. A groundwater-flow model of Quaternary and Tertiary sediments in Carson Valley was developed using MODFLOW and calibrated to simulate historical conditions from water years 1971 through 2005. The 35-year transient simulation represented quarterly changes in precipitation, streamflow, pumping and irrigation. Inflows to the groundwater system simulated in the model include mountain-front recharge from watersheds in the Carson Range and Pine Nut Mountains, valley recharge from precipitation and land application of wastewater, agricultural recharge from irrigation, and septic-tank discharge. Outflows from the groundwater system simulated in the model include evapotranspiration from the water table and groundwater withdrawals for municipal, domestic, irrigation and other water supplies. The exchange of water between groundwater, the Carson River, and the irrigation system was represented with a version of the Streamflow Routing (SFR) package that was modified to apply diversions from the irrigation network to irrigated areas as recharge. The groundwater-flow model was calibrated through nonlinear regression with UCODE to measured water levels and streamflow to estimate values of hydraulic conductivity, recharge and streambed hydraulic-conductivity that were represented by 18 optimized parameters. The aquifer system was simulated as confined to facilitate numerical convergence, and the hydraulic conductivity of the top active model layers that intersect the water table was multiplied by a factor to account for partial saturation. Storage values representative of specific yield were specified in parts of model layers where unconfined conditions are assumed to occur. The median transmissivity (<i>T</i>) values (11,000 and 800 ft<sup>2</sup>/d for the fluvial and alluvial-fan sediments, respectively) are both within the third quartile of <i>T</i> values estimated from specific-capacity data, but <i>T</i> values for Tertiary sediments are larger than the third quartile estimated from specific-capacity data. The estimated vertical anisotropy for the Quaternary fluvial sediments (9,000) is comparable to the value estimated for a previous model of Carson Valley. The estimated total volume of mountain-front recharge is equivalent to a previous estimate from the Precipitation-Runoff Modeling System (PRMS) watershed models, but less recharge is estimated for the Carson Range and more recharge is estimated for the Pine Nut Mountains than the previous estimate. Simulated flow paths indicate that groundwater flows faster through the center of Carson Valley and slower through the lower hydraulic-conductivity Tertiary sediments to the east. Shallow flow in the center of the valley is towards drainage channels, but deeper flow is generally directed toward the basin outlet to the north. The aquifer system is in a dynamic equilibrium with large inflows from storage in dry years and large outflows to storage in wet years. Pumping has historically been less than 10 percent of outflows from the groundwater system, and agricultural recharge has been less than 10 percent of inflows to the groundwater system. Three principal sources of uncertainty that affect model results are: (1) the hydraulic characteristics of the Tertiary sediments on the eastern side of the basin, (2) the composition of sediments beneath the alluvial fans and (3) the extent of the confining unit represented within fluvial sediments in the center of the basin. The groundwater-flow model was used in five 55-year predictive simulations to evaluate the long-term effects of different water-use scenarios on water-budget components, groundwater levels, and streamflow in the Carson River. The predictive simulations represented water years 2006 through 2060 using quarterly stress periods with boundary conditions that varied cyclically to represent the transition from wet to dry conditions observed from water years 1995 through 2004. The five scenarios included a base scenario with 2005 pumping rates held constant throughout the simulation period and four other scenarios using: (1) pumping rates increased by 70 percent, including an additional 1,340 domestic wells, (2A) pumping rates more than doubled with municipal pumping increased by a factor of four over the base scenario, (2B) pumping rates of 2A with 2,040 fewer domestic wells, and (3) pumping rates of 2A with 3,700 acres removed from irrigation. The 55-year predictive simulations indicate that increasing groundwater withdrawals under the scenarios considered would result in as much as 40 ft and 60 ft of water-table decline on the west and east sides of Carson Valley, respectively. The water table in the central part of the valley would remain essentially unchanged, but water-level declines of as much as 30 ft are predicted for the deeper, confined aquifer. The increased withdrawals would reduce the volume of groundwater storage and decrease the mean downstream flow in the Carson River by as much as 16,500 acre-ft/yr. If, in addition, 3,700 acres were removed from irrigation, the reduction in mean downstream flow in the Carson River would be only 6,500 acre-ft/yr. The actual amount of flow reduction is uncertain because of potential changes in irrigation practices that may not be accounted for in the model. The projections of the predictive simulations are sensitive to rates of mountain-front recharge specified for the Carson Range and the Pine Nut Mountains. The model provides a tool that can be used to aid water managers and planners in making informed decisions. A prudent management approach would include continued monitoring of water levels on both the east and west sides of Carson Valley to either verify the predictions of the groundwater-flow model or to provide additional data for recalibration of the model if the predictions prove inaccurate.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125262","collaboration":"Prepared in cooperation with the Carson Water Subconservancy District","usgsCitation":"Yager, R.M., Maurer, D.K., and Mayers, C., 2012, Assessing potential effects of changes in water use with a numerical groundwater-flow model of Carson Valley, Douglas County, Nevada, and Alpine County, California: U.S. Geological Survey Scientific Investigations Report 2012-5262, x,  84 p., https://doi.org/10.3133/sir20125262.","productDescription":"x,  84 p.","numberOfPages":"98","additionalOnlineFiles":"N","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":264890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5262.jpg"},{"id":264888,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5262/"},{"id":264889,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5262/pdf/sir2012-5262.pdf"}],"country":"United States","state":"California;Nevada","county":"Alpine;Churchill;Douglas;Storey;Washoe","otherGeospatial":"Carson River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0,38.25 ], [ -120.0,40.5 ], [ -118.0,40.5 ], [ -118.0,38.25 ], [ -120.0,38.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfe1e4b0a4aa5bb0ae7d","contributors":{"authors":[{"text":"Yager, Richard M. 0000-0001-7725-1148 ryager@usgs.gov","orcid":"https://orcid.org/0000-0001-7725-1148","contributorId":950,"corporation":false,"usgs":true,"family":"Yager","given":"Richard","email":"ryager@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maurer, Douglas K. dkmaurer@usgs.gov","contributorId":2308,"corporation":false,"usgs":true,"family":"Maurer","given":"Douglas","email":"dkmaurer@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":471009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayers, C.J.","contributorId":17410,"corporation":false,"usgs":true,"family":"Mayers","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":471010,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042219,"text":"sir20125283 - 2012 - Floods of June 2012 in northeastern Minnesota","interactions":[],"lastModifiedDate":"2012-12-28T14:06:05","indexId":"sir20125283","displayToPublicDate":"2012-12-28T00:00:00","publicationYear":"2012","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":"2012-5283","title":"Floods of June 2012 in northeastern Minnesota","docAbstract":"During June 19–20, 2012, heavy rainfall, as much as 10 inches locally reported, caused severe flooding across northeastern Minnesota. The floods were exacerbated by wet antecedent conditions from a relatively rainy spring, with May 2012 as one of the wettest Mays on record in Duluth. The June 19–20, 2012, rainfall event set new records in Duluth, including greatest 2-day precipitation with 7.25 inches of rain. The heavy rains fell on three major watersheds: the Mississippi Headwaters; the St. Croix, which drains to the Mississippi River; and Western Lake Superior, which includes the St. Louis River and other tributaries to Lake Superior. Widespread flash and river flooding that resulted from the heavy rainfall caused evacuations of residents, and damages to residences, businesses, and infrastructure. In all, nine counties in northeastern Minnesota were declared Federal disaster areas as a result of the flooding. Peak-of-record streamflows were recorded at 13 U.S. Geological Survey streamgages as a result of the heavy rainfall. Flood-peak gage heights, peak streamflows, and annual exceedance probabilities were tabulated for 35 U.S. Geological Survey streamgages. Flood-peak streamflows in June 2012 had annual exceedance probabilities estimated to be less than 0.002 (0.2 percent; recurrence interval greater than 500 years) for five streamgages, and between 0.002 and 0.01 (1 percent; recurrence interval greater than 100 years) for four streamgages. High-water marks were identified and tabulated for the most severely affected communities of Barnum (Moose Horn River), Carlton (Otter Creek), Duluth Heights neighborhood of Duluth (Miller Creek), Fond du Lac neighborhood of Duluth (St. Louis River), Moose Lake (Moose Horn River and Moosehead Lake), and Thomson (Thomson Reservoir outflow near the St. Louis River). Flood-peak inundation maps and water-surface profiles were produced for these six severely affected communities. The inundation maps were constructed in a geographic information system by combining high-water-mark data with high-resolution digital elevation model data. The flood maps and profiles show the extent and depth of flooding through the communities and can be used for flood response and recovery efforts by local, county, State, and Federal agencies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125283","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency.  The Downloads Directory contains the 6 figures from Appendix 2.  For more information, see the \"View companion files\" link above.","usgsCitation":"Czuba, C.R., Fallon, J.D., and Kessler, E.W., 2012, Floods of June 2012 in northeastern Minnesota: U.S. Geological Survey Scientific Investigations Report 2012-5283, Report: vi, 42 p.; Downloads Directory, https://doi.org/10.3133/sir20125283.","productDescription":"Report: vi, 42 p.; Downloads Directory","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-06-19","temporalEnd":"2012-06-20","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":264894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5283.gif"},{"id":264893,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5283/downloads/"},{"id":264891,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5283/"},{"id":264892,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5283/sir2012-5283.pdf"}],"projection":"Universal Transverse Mercator projection, Zone 15","country":"United States","state":"Minnesota","county":"Aitkin;Carlton;Cass;Cook;Crow Wing;Itasca;Lake;Pine;St. Louis","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.0,45.5 ], [ -95.0,48.75 ], [ -89.0,48.75 ], [ -89.0,45.5 ], [ -95.0,45.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cffde4b0a4aa5bb0aef9","contributors":{"authors":[{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":471015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fallon, James D. jfallon@usgs.gov","contributorId":3417,"corporation":false,"usgs":true,"family":"Fallon","given":"James","email":"jfallon@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":471014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kessler, Erich W. 0000-0002-0869-4743 ekessler@usgs.gov","orcid":"https://orcid.org/0000-0002-0869-4743","contributorId":2871,"corporation":false,"usgs":true,"family":"Kessler","given":"Erich","email":"ekessler@usgs.gov","middleInitial":"W.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042221,"text":"sir20125285 - 2012 - Borehole geophysical, fluid, and hydraulic properties within and surrounding the freshwater/saline-water transition zone, San Antonio segment of the Edwards aquifer, south-central Texas, 2010-11","interactions":[],"lastModifiedDate":"2016-08-10T10:51:07","indexId":"sir20125285","displayToPublicDate":"2012-12-28T00:00:00","publicationYear":"2012","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":"2012-5285","title":"Borehole geophysical, fluid, and hydraulic properties within and surrounding the freshwater/saline-water transition zone, San Antonio segment of the Edwards aquifer, south-central Texas, 2010-11","docAbstract":"<p>The freshwater zone of the San Antonio segment of the Edwards aquifer is used by residents of San Antonio and numerous other rapidly growing communities in south-central Texas as their primary water supply source. This freshwater zone is bounded to the south and southeast by a saline-water zone with an intermediate zone transitioning from freshwater to saline water, the transition zone. As demands on this water supply increase, there is concern that the transition zone could potentially move, resulting in more saline water in current supply wells. Since 1985, the U.S. Geological Survey (USGS), San Antonio Water System (SAWS), and other Federal and State agencies have conducted studies to better understand the transition zone.</p>\n<p>During 2010 and 2011, the USGS, in cooperation with SAWS, conducted a study to further assess the potential for movement of the transition zone in part of the San Antonio segment of the Edwards aquifer. Equivalent freshwater heads were computed to investigate the transition from saline to freshwater zones in the San Antonio segment and evaluate the potential for lateral flow at the freshwater/saline-water interface. Data were collected within and surrounding the transition zone from 13 wells in four transects (East Uvalde, Tri-County, Fish Hatchery, and Kyle).</p>\n<p>Hydraulic head and geophysical log data were used to calculate equivalent freshwater heads and then analyzed to identify possible horizontal gradients across the transition zone and thus flow. Unlike previous studies that used indirect methods to calculate fluid conductivity from fluid resistivity, in this study geophysical tools that directly measured fluid conductivity were used. Electromagnetic (EM) flowmeter logs were collected under both ambient and stressed (pumping) conditions and were processed to identify vertical flow zones within the borehole.</p>\n<p>The San Antonio segment of the Edwards aquifer (the study area) is about 175 miles long and extends from the western groundwater divide near Brackettville in Kinney County to the eastern groundwater divide near Kyle in Hays County. The four transects consist of two to five wells per transect and were configured approximately perpendicular to and across the expected trace of the freshwater/saline-water interface.</p>\n<p>The deep flow zone indicated by the EM flowmeter data for East Uvalde transect well EU2 corresponds directly with a large, negative deflection of the fluid logs, indicating an inflow of fresher water from the Devils River Limestone. To the southwest, towards the freshwater/saline-water interface, this same flow zone was observed in well EU1, but with a reduction of flow, and displayed no apparent fluid curve deflections.</p>\n<p>The highest observed transmissivity of the study area was observed in the saline zone of the Tri-County transect, at well TC3, which had a total transmissivity of 24,900 square feet per day. Zones of high transmissivity throughout the study site were observed to not be continuous and are likely caused by localized secondary porosity such as intersecting faults or karst features.</p>\n<p>Although analyses of daily mean equivalent freshwater heads for the East Uvalde transect indicated that the gradient across the freshwater/saline-water interface varied between into and out of the freshwater zone, the data indicate that there was a slightly longer period during which the gradient was out of the freshwater zone. Analyses of all daily mean equivalent freshwater heads for the Tri-County transect indicated that the lateral-head gradients across the freshwater/saline-water interface were typically mixed (not indicative of flow into or out of freshwater zone). Assessment of the daily mean equivalent freshwater heads indicated that, although the lateral-head gradient at the Kyle transect varied between into and out of the freshwater zone, the lateral-head gradient was typically from the transition zone into the freshwater zone.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125285","collaboration":"Prepared in cooperation with the San Antonio Water System","usgsCitation":"Thomas, J.V., Stanton, G.P., and Lambert, R.B., 2012, Borehole geophysical, fluid, and hydraulic properties within and surrounding the freshwater/saline-water transition zone, San Antonio segment of the Edwards aquifer, south-central Texas, 2010-11: U.S. Geological Survey Scientific Investigations Report 2012-5285, Report: viii, 65 p.; 3 Appendixes, https://doi.org/10.3133/sir20125285.","productDescription":"Report: viii, 65 p.; 3 Appendixes","numberOfPages":"77","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2010-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":264903,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5285/pdf/sir2012-5285-app2.pdf","text":"Appendix 2"},{"id":264904,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5285/pdf/sir2012-5285-app3.pdf","text":"Appendix 3"},{"id":264905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5285.gif"},{"id":264902,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5285/downloads/sir2012-5285-app1.xlsx","text":"Appendix 1"},{"id":264900,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5285/"},{"id":264901,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5285/pdf/sir2012-5285.pdf"}],"scale":"250000","projection":"Universal Transverse Mercator projection, Zone 14","datum":"North American Datum of 1927","country":"United States","state":"Texas","county":"Atascosa County, Bexar County, Caldwell County, Comal County, Frio County, Guadalupe County, Hays County, Kinney County, Maverick County, Medina County, Travis County, Uvalde County, Wilson County, Zavala County","city":"San Antonio","otherGeospatial":"Edwards Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.75,28.5 ], [ -100.75,30.25 ], [ -97.25,30.25 ], [ -97.25,28.5 ], [ -100.75,28.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e5cfe5e4b0a4aa5bb0ae90","contributors":{"authors":[{"text":"Thomas, Jonathan V. 0000-0003-0903-9713 jvthomas@usgs.gov","orcid":"https://orcid.org/0000-0003-0903-9713","contributorId":2194,"corporation":false,"usgs":true,"family":"Thomas","given":"Jonathan","email":"jvthomas@usgs.gov","middleInitial":"V.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanton, Gregory P. 0000-0001-8622-0933 gstanton@usgs.gov","orcid":"https://orcid.org/0000-0001-8622-0933","contributorId":1583,"corporation":false,"usgs":true,"family":"Stanton","given":"Gregory","email":"gstanton@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":471022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lambert, Rebecca B. 0000-0002-0611-1591 blambert@usgs.gov","orcid":"https://orcid.org/0000-0002-0611-1591","contributorId":1135,"corporation":false,"usgs":true,"family":"Lambert","given":"Rebecca","email":"blambert@usgs.gov","middleInitial":"B.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471021,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042197,"text":"70042197 - 2012 - Seasonal zooplankton dynamics in Lake Michigan: disentangling impacts of resource limitation, ecosystem engineering, and predation during a critical ecosystem transition","interactions":[],"lastModifiedDate":"2012-12-28T13:44:37","indexId":"70042197","displayToPublicDate":"2012-12-28T00:00:00","publicationYear":"2012","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":"Seasonal zooplankton dynamics in Lake Michigan: disentangling impacts of resource limitation, ecosystem engineering, and predation during a critical ecosystem transition","docAbstract":"We examined seasonal dynamics of zooplankton at an offshore station in Lake Michigan from 1994 to 2003 and 2007 to 2008. This period saw variable weather, declines in planktivorous fish abundance, the introduction and expansion of dreissenid mussels, and a slow decline in total phosphorus concentrations. After the major expansion of mussels into deep water (2007–2008), chlorophyll in spring declined sharply, Secchi depth increased markedly in all seasons, and planktivorous fish biomass declined to record-low levels. Overlaying these dramatic ecosystem-level changes, the zooplankton community exhibited complex seasonal dynamics between 1994–2003 and 2007–2008. Phenology of the zooplankton maximum was affected by onset of thermal stratification, but there was no other discernable effect due to temperature. Interannual variability in zooplankton biomass during 1994 and 2003 was strongly driven by planktivorous fish abundance, particularly age-0 and age-1 alewives. In 2007–2008, there were large decreases in <i>Diacyclops thomasi</i> and <i>Daphnia mendotae</i> possibly caused by food limitation as well as increased predation and indirect negative effects from increases in <i>Bythotrephes</i> longimanus abundance and in foraging efficiency associated with increased light penetration. The <i>Bythotrephes</i> increase was likely driven in part by decreased predation from yearling and older alewife. While there was a major decrease in epilimnetic–metalimnetic herbivorous cladocerans in 2007–2008, there was an increase in large omnivorous and predacious calanoid copepods, especially those in the hypolimnion. Thus, changes to the zooplankton community are the result of cascading, synergistic interactions, including a shift from vertebrate to invertebrate planktivory and mussel ecosystem impacts on light climate and chlorophyll.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jglr.2012.02.005","usgsCitation":"Vanderploeg, H., Pothoven, S.A., Fahnenstiel, G.L., Cavaletto, J.F., Liebig, J.R., Stow, C.S., Nalepa, T., Madenjian, C.P., and Bunnell, D., 2012, Seasonal zooplankton dynamics in Lake Michigan: disentangling impacts of resource limitation, ecosystem engineering, and predation during a critical ecosystem transition: Journal of Great Lakes Research, v. 38, no. 2, p. 336-352, https://doi.org/10.1016/j.jglr.2012.02.005.","productDescription":"17 p.","startPage":"336","endPage":"352","ipdsId":"IP-035739","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":264887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":264886,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.02.005"}],"otherGeospatial":"Lake Michigan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.91,41.61 ], [ -87.91,46.05 ], [ -84.95,46.05 ], [ -84.95,41.61 ], [ -87.91,41.61 ] ] ] } } ] }","volume":"38","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4b94ce4b0e8fec6cdefb9","contributors":{"authors":[{"text":"Vanderploeg, Henry A.","contributorId":85929,"corporation":false,"usgs":true,"family":"Vanderploeg","given":"Henry A.","affiliations":[],"preferred":false,"id":470937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":470938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fahnenstiel, Gary L.","contributorId":32491,"corporation":false,"usgs":true,"family":"Fahnenstiel","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":470935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cavaletto, Joann F.","contributorId":93356,"corporation":false,"usgs":true,"family":"Cavaletto","given":"Joann","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":470939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liebig, James R.","contributorId":25052,"corporation":false,"usgs":true,"family":"Liebig","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":470933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stow, Craig Stow","contributorId":65737,"corporation":false,"usgs":true,"family":"Stow","given":"Craig","email":"","middleInitial":"Stow","affiliations":[],"preferred":false,"id":470936,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nalepa, Thomas F.","contributorId":28212,"corporation":false,"usgs":true,"family":"Nalepa","given":"Thomas F.","affiliations":[],"preferred":false,"id":470934,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470931,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bunnell, David B.","contributorId":14360,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","affiliations":[],"preferred":false,"id":470932,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
]}