Pacific salmon Oncorhynchus spp. are adept at colonizing habitat that has been reopened to anadromous passage. Sockeye Salmon O. nerka are unique in that most populations require lakes to fulfill their life history. Thus, for Sockeye Salmon to colonize a system, projects like dam removals must provide access to lakes. However, if the lakes contain landlocked kokanee (lacustrine Sockeye Salmon), the recovery of Sockeye Salmon could be mediated by interactions between the two life history forms and the processes associated with the resumption of anadromy. Our objective was to evaluate the extent to which estimates of Sockeye Salmon smolt production and recovery are sensitive to the resumption of anadromy by kokanee after dam removal. We informed the analysis based on the abiotic and biotic features of Lake Sutherland, which was recently opened to passage after dam removal on the Elwha River, Washington. We first developed maximum expectations for the smolt-producing capacity of Lake Sutherland by using two predictive models developed from Sockeye Salmon populations in Alaska and British Columbia: one model was based on the mean seasonal biomass of macrozooplankton, and the other was based on the euphotic zone volume of the lake. We then constructed a bioenergetics-based simulation model to evaluate how the capacity of Lake Sutherland to rear yearling smolts could change with varying degrees of anadromy among O. nerka fry. We demonstrated that (1) the smolt-producing capacity of a nursery lake for juvenile Sockeye Salmon changes in nonlinear ways with changes in smolt growth, mortality, and the extent to which kokanee resume anadromy after dam removal; (2) kokanee populations may be robust to changes in abundance after dam removal, particularly if lakes are located higher in the watershed on tributaries separate from where dams were removed; and (3) the productivity of newly establishing Sockeye Salmon can vary considerably depending on whether the population becomes rearing limited or is recruitment limited and depending on how adult escapement is managed.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2016.1223752","usgsCitation":"Hansen, A., Gardner, J.R., Beauchamp, D.A., Paradis, R., and Quinn, T.P., 2016, Recovery of sockeye salmon in the Elwha River, Washington, after dam removal: Dependence of smolt production on the resumption of anadromy by landlocked kokanee: Transactions of the American Fisheries Society, v. 145, no. 6, p. 1303-1317, https://doi.org/10.1080/00028487.2016.1223752.","productDescription":"15 p.","startPage":"1303","endPage":"1317","ipdsId":"IP-072935","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":462059,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00028487.2016.1223752","text":"Publisher Index Page"},{"id":329734,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River, Lake Sutherland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.72493743896483,\n 48.07268823432358\n ],\n [\n -123.72493743896483,\n 48.08392779751268\n ],\n [\n -123.68605613708495,\n 48.08392779751268\n ],\n [\n -123.68605613708495,\n 48.07268823432358\n ],\n [\n -123.72493743896483,\n 48.07268823432358\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"58088687e4b0f497e78e24c1","contributors":{"authors":[{"text":"Hansen, Adam G.","contributorId":103947,"corporation":false,"usgs":true,"family":"Hansen","given":"Adam G.","affiliations":[],"preferred":false,"id":651337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Jennifer R.","contributorId":175505,"corporation":false,"usgs":false,"family":"Gardner","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":651338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":651194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paradis, Rebecca","contributorId":145488,"corporation":false,"usgs":false,"family":"Paradis","given":"Rebecca","affiliations":[{"id":13135,"text":"Lower Elwha Klallam Tribe, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":651339,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":651340,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70177056,"text":"sir20165139 - 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Statistical analyses of lake levels were completed to assess the effect of physical setting and climate on lake-level fluctuations of selected lakes. A field study of groundwater and surface-water interactions in selected lakes was completed to (1) estimate potential percentages of surface-water contributions to well water across the northeast Twin Cities Metropolitan Area, (2) estimate general ages for waters extracted from the wells, and (3) assess groundwater inflow to lakes and lake-water outflow to aquifers downgradient from White Bear Lake. Groundwater flow was simulated using a steady-state, groundwater-flow model to assess regional groundwater and surface-water exchanges and the effects of groundwater withdrawals, climate, and other factors on water levels of northeast Twin Cities Metropolitan Area lakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165139","collaboration":"Prepared in cooperation with the Metropolitan Council and Minnesota Department of Health","usgsCitation":"Jones, P.M., Trost, J.J., and Erickson, M.L., eds., 2016, Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015: U.S. Geological Survey Scientific Investigations Report 2016–5139, https://dx.doi.org/10.3133/sir20165139.","productDescription":"2 Chapters","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":329671,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5139/coverthb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Twin Cities Metropolitan Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.55957031249999,\n 45.29614310895674\n ],\n [\n -93.56231689453125,\n 45.464946600971466\n ],\n [\n -92.67791748046875,\n 45.464946600971466\n ],\n [\n -92.64907836914062,\n 45.4524242413431\n ],\n [\n -92.65045166015625,\n 45.427371178989084\n ],\n [\n -92.64770507812499,\n 45.40230699238177\n ],\n [\n -92.6806640625,\n 45.37337295384522\n ],\n [\n -92.69851684570312,\n 45.35407536661815\n ],\n [\n -92.70401000976562,\n 45.32704768567264\n ],\n [\n -92.72872924804688,\n 45.30387083299528\n ],\n [\n -92.76031494140625,\n 45.287448160456634\n ],\n [\n -92.7520751953125,\n 45.260388684823695\n ],\n [\n -92.75344848632812,\n 45.21687321093267\n ],\n [\n -92.76443481445311,\n 45.19268354749929\n ],\n [\n -92.75344848632812,\n 45.17041997262664\n ],\n [\n -92.74383544921875,\n 45.11520750294172\n ],\n [\n -92.78778076171874,\n 45.07836948371111\n ],\n [\n -92.79464721679688,\n 45.055091121730385\n ],\n [\n -92.76718139648438,\n 45.035685245316316\n ],\n [\n -92.76443481445311,\n 45.021126517829614\n ],\n [\n -92.7685546875,\n 44.992969144596394\n ],\n [\n -92.76168823242188,\n 44.959939425508466\n ],\n [\n -92.75619506835936,\n 44.92397370210939\n ],\n [\n -92.75894165039062,\n 44.90549606158295\n ],\n [\n -92.77267456054686,\n 44.89771422497743\n ],\n [\n -92.7740478515625,\n 44.88214739188459\n ],\n [\n -92.76168823242188,\n 44.87728189251396\n ],\n [\n -92.76580810546875,\n 44.860736117070026\n ],\n [\n -92.76718139648438,\n 44.83055216443822\n ],\n [\n -92.78366088867188,\n 44.80132682904856\n ],\n [\n -92.79602050781249,\n 44.77696106840196\n ],\n [\n -92.8070068359375,\n 44.74868389996833\n ],\n [\n -92.8619384765625,\n 44.75356026127114\n ],\n [\n -92.90176391601562,\n 44.77403648591521\n ],\n [\n -92.93746948242188,\n 44.7691618526244\n ],\n [\n -92.94433593749999,\n 44.76038647589176\n ],\n [\n -92.96218872070312,\n 44.75697346938202\n ],\n [\n -92.98553466796875,\n 44.762336674810996\n ],\n [\n -93.00544738769531,\n 44.76818687659432\n ],\n [\n -93.02261352539062,\n 44.77793589631623\n ],\n [\n -93.01437377929686,\n 44.82178611905465\n ],\n [\n -93.0157470703125,\n 44.86852295681338\n ],\n [\n -93.02536010742188,\n 44.89868701215517\n ],\n [\n -93.05419921875,\n 44.91327684489316\n ],\n [\n -93.05831909179688,\n 44.941473354802504\n ],\n [\n -93.08441162109374,\n 44.94438944516438\n ],\n [\n -93.11599731445312,\n 44.923001342833096\n ],\n [\n -93.16543579101562,\n 44.89382291168926\n ],\n [\n -93.18878173828125,\n 44.89479576469787\n ],\n [\n -93.2025146484375,\n 44.912304304581525\n ],\n [\n -93.2025146484375,\n 44.94924926661153\n ],\n [\n -93.218994140625,\n 44.96382626228214\n ],\n [\n -93.26019287109375,\n 44.97645666320777\n ],\n [\n -93.27392578125,\n 44.991026746594535\n ],\n [\n -93.28903198242188,\n 45.03665569548622\n ],\n [\n -93.28353881835938,\n 45.08418759300652\n ],\n [\n -93.27941894531249,\n 45.106484856646844\n ],\n [\n -93.31100463867188,\n 45.1394300814679\n ],\n [\n -93.34808349609375,\n 45.15686396890044\n ],\n [\n -93.36593627929688,\n 45.17526062079539\n ],\n [\n -93.394775390625,\n 45.1907479300741\n ],\n [\n -93.4222412109375,\n 45.205263456162385\n ],\n [\n -93.44284057617186,\n 45.215905821884036\n ],\n [\n -93.48129272460936,\n 45.22557897178979\n ],\n [\n -93.50601196289062,\n 45.24105258851866\n ],\n [\n -93.54446411132811,\n 45.25555527789205\n ],\n [\n -93.5540771484375,\n 45.263288531496876\n ],\n [\n -93.55957031249999,\n 45.29614310895674\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Probabilistic seismic‐hazard assessment (PSHA) requires an estimate of Mmax, the moment magnitude M of the largest earthquake that could occur within a specified area. Sparse seismicity hinders Mmax estimation in the central and eastern United States (CEUS) and tectonically similar regions worldwide (stable continental regions [SCRs]). A new global catalog of moderate‐to‐large SCR earthquakes is analyzed with minimal assumptions about enigmatic geologic controls on SCR Mmax. An earlier observation that SCR earthquakes of M 7.0 and larger occur in young (250–23 Ma) passive continental margins and associated rifts but not in cratons is not strongly supported by the new catalog. SCR earthquakes of M 7.5 and larger are slightly more numerous and reach slightly higher M in young passive margins and rifts than in cratons. However, overall histograms of M from young margins and rifts and from cratons are statistically indistinguishable. This conclusion is robust under uncertainties inM, the locations of SCR boundaries, and which of two available global SCR catalogs is used. The conclusion stems largely from recent findings that (1) large southeast Asian earthquakes once thought to be SCR were in actively deforming crust and (2) long escarpments in cratonic Australia were formed by prehistoric faulting. The 2014 seismic‐hazard model of the U.S. Geological Survey represents CEUS Mmax as four‐point probability distributions. The distributions have weighted averages of M 7.0 in cratons and M 7.4 in passive margins and rifts. These weighted averages are consistent with Mmax estimates of other SCR PSHAs of the CEUS, southeastern Canada, Australia, and India.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160048","usgsCitation":"Wheeler, R.L., 2016, Maximum magnitude (Mmax) in the central and eastern United States for the 2014 U.S. Geological Survey Hazard Model: Bulletin of the Seismological Society of America, v. 106, no. 5, p. 2154-2167, https://doi.org/10.1785/0120160048.","productDescription":"14 p.","startPage":"2154","endPage":"2167","ipdsId":"IP-076405","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":329732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-30","publicationStatus":"PW","scienceBaseUri":"58088686e4b0f497e78e24bd","contributors":{"authors":[{"text":"Wheeler, Russell L. wheeler@usgs.gov","contributorId":858,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":651258,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70176961,"text":"sir20165139A - 2016 - Statistical analysis of lake levels and field study of groundwater and surface-water exchanges in the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015: Chapter A of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","interactions":[{"subject":{"id":70176961,"text":"sir20165139A - 2016 - Statistical analysis of lake levels and field study of groundwater and surface-water exchanges in the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015: Chapter A of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","indexId":"sir20165139A","publicationYear":"2016","noYear":false,"chapter":"A","title":"Statistical analysis of lake levels and field study of groundwater and surface-water exchanges in the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015: Chapter A of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015"},"predicate":"IS_PART_OF","object":{"id":70177056,"text":"sir20165139 - 2016 - Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","indexId":"sir20165139","publicationYear":"2016","noYear":false,"title":"Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015"},"id":1}],"isPartOf":{"id":70177056,"text":"sir20165139 - 2016 - Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","indexId":"sir20165139","publicationYear":"2016","noYear":false,"title":"Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015"},"lastModifiedDate":"2016-11-01T10:46:11","indexId":"sir20165139A","displayToPublicDate":"2016-10-19T00:00:00","publicationYear":"2016","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":"2016-5139","chapter":"A","title":"Statistical analysis of lake levels and field study of groundwater and surface-water exchanges in the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015: Chapter A of Water levels and groundwater and surface-water exchanges in lakes of the northeast Twin Cities Metropolitan Area, Minnesota, 2002 through 2015","docAbstract":"Water levels declined from 2003 to 2011 in many lakes in Ramsey and Washington Counties in the northeast Twin Cities Metropolitan Area, Minnesota; however, water levels in other northeast Twin Cities Metropolitan Area lakes increased during the same period. Groundwater and surface-water exchanges can be important in determining lake levels where these exchanges are an important component of the water budget of a lake. An understanding of groundwater and surface-water exchanges in the northeast Twin Cities Metropolitan Area has been limited by the lack of hydrologic data. The U.S. Geological Survey, in cooperation with the Metropolitan Council and Minnesota Department of Health, completed a field and statistical study assessing lake-water levels and regional and local groundwater and surface-water exchanges near northeast Twin Cities Metropolitan Area lakes. This report documents the analysis of collected hydrologic, water-quality, and geophysical data; and existing hydrologic and geologic data to (1) assess the effect of physical setting and climate on lake-level fluctuations of selected lakes, (2) estimate potential percentages of surface-water contributions to well water across the northeast Twin Cities Metropolitan Area, (3) estimate general ages for waters extracted from the wells, and (4) assess groundwater inflow to lakes and lake-water outflow to aquifers downgradient from White Bear Lake.
Statistical analyses of lake levels during short-term (2002–10) and long-term (1925–2014) periods were completed to help understand lake-level changes across the northeast Twin Cities Metropolitan Area. Comparison of 2002–10 lake levels to several landscape and geologic characteristics explained variability in lake-level changes for 96 northeast Twin Cities Metropolitan Area lakes. Application of several statistical methods determined that (1) closed-basin lakes (without an active outlet) had larger lake-level declines than flow-through lakes with an outlet; (2) closed-basin lake-level changes reflected groundwater-level changes in the Quaternary, Prairie du Chien, and Jordan aquifers; (3) the installation of outlet-control structures, such as culverts and weirs, resulted in smaller multiyear lake-level changes than lakes without outlet-control structures; (4) water levels in lakes primarily overlying Superior Lobe deposits were significantly more variable than lakes primarily overlying Des Moines Lobe deposits; (5) lake-level declines were larger with increasing mean lake-level elevation; and (6) the frequency of some of these characteristics varies by landscape position. Flow-through lakes and lakes with outlet-control structures were more common in watersheds with more than 50 percent urban development compared to watersheds with less than 50 percent urban development. A comparison of two 35-year periods during 1925–2014 revealed that variability of annual mean lake levels in flow-through lakes increased when annual precipitation totals were more variable, whereas variability of annual mean lake levels in closed-basin lakes had the opposite pattern, being more variable when annual precipitation totals were less variable.
Oxygen-18/oxygen-16 and hydrogen-2/hydrogen-1 ratios for water samples from 40 wells indicated the well water was a mixture of surface water and groundwater in 31 wells, whereas ratios from water sampled from 9 other wells indicated that water from these wells receive no surface-water contribution. Of the 31 wells with a mixture of surface water and groundwater, 11 were downgradient from White Bear Lake, likely receiving water from deeper parts of the lake.
Age dating of water samples from wells indicated that the age of water in the Prairie du Chien and Jordan aquifers can vary widely across the northeast Twin Cities Metropolitan Area. Estimated ages of recharge for 9 of the 40 wells sampled for chlorofluorocarbon concentrations ranged widely from the early 1940s to mid-1970s. The wide range in estimated ages of recharge may have resulted from the wide range in the open-interval lengths and depths for the wells.
Results from stable isotope analyses of water samples, lake-sediment coring, continuous seismic-reflection profiling, and water-level and flow monitoring indicated that there is groundwater inflow from nearshore sites and lake-water outflow from deep-water sites in White Bear Lake. Continuous seismic-reflection profiling indicated that deep sections of White Bear, Pleasant, Turtle, and Big Marine Lakes have few trapped gases and little organic material, which indicates where groundwater and lake-water exchanges are more likely. Water-level differences between White Bear Lake and piezometer and seepage measurements in deep waters of the lake indicate that groundwater and lake-water exchange is happening in deep waters, predominantly downgradient from the lake and into the lake sediment. Seepage fluxes measured in the nearshore sites of White Bear Lake generally were higher than seepage fluxes measured in the deep-water sites, which indicates that groundwater-inflow rates at most of the nearshore sites are higher than lake-water outflow from the deep-water sites.
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U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Distributional limits of many tropical species in Florida are ultimately determined by tolerance to low temperature. An unprecedented cold spell during 2–11 January 2010, in South Florida provided an opportunity to compare the responses of tropical American crocodiles with warm-temperate American alligators and to compare the responses of nonnative Burmese pythons with native warm-temperate snakes exposed to prolonged cold temperatures. After the January 2010 cold spell, a record number of American crocodiles (n = 151) and Burmese pythons (n = 36) were found dead. In contrast, no American alligators and no native snakes were found dead. American alligators and American crocodiles behaved differently during the cold spell. American alligators stopped basking and retreated to warmer water. American crocodiles apparently continued to bask during extreme cold temperatures resulting in lethal body temperatures. The mortality of Burmese pythons compared to the absence of mortality for native snakes suggests that the current population of Burmese pythons in the Everglades is less tolerant of cold temperatures than native snakes. Burmese pythons introduced from other parts of their native range may be more tolerant of cold temperatures. We documented the direct effects of cold temperatures on crocodiles and pythons; however, evidence of long-term effects of cold temperature on their populations within their established ranges remains lacking. Mortality of crocodiles and pythons outside of their current established range may be more important in setting distributional limits.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1439","usgsCitation":"Mazzotti, F., Cherkiss, M.S., Parry, M., Beauchamp, J., Rochford, M., Smith, B.J., Hart, K.M., and Brandt, L.A., 2016, Large reptiles and cold temperatures: Do extreme cold spells set distributional limits for tropical reptiles in Florida?: Ecosphere, v. 7, no. 8, p. 1-9, https://doi.org/10.1002/ecs2.1439.","productDescription":"e01439; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-066802","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":470500,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1439","text":"Publisher Index Page"},{"id":329733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"8","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-17","publicationStatus":"PW","scienceBaseUri":"58088687e4b0f497e78e24bf","chorus":{"doi":"10.1002/ecs2.1439","url":"http://dx.doi.org/10.1002/ecs2.1439","publisher":"Wiley-Blackwell","authors":"Mazzotti Frank J., Cherkiss Michael S., Parry Mark, Beauchamp Jeff, Rochford Mike, Smith Brian, Hart Kristen, Brandt Laura A.","journalName":"Ecosphere","publicationDate":"8/2016"},"contributors":{"authors":[{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":651209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":651208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parry, Mark","contributorId":175457,"corporation":false,"usgs":false,"family":"Parry","given":"Mark","email":"","affiliations":[],"preferred":false,"id":651210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beauchamp, Jeff","contributorId":175458,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":651211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rochford, Mike","contributorId":175459,"corporation":false,"usgs":false,"family":"Rochford","given":"Mike","email":"","affiliations":[],"preferred":false,"id":651212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Brian J. 0000-0002-0531-0492 bjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":899,"corporation":false,"usgs":true,"family":"Smith","given":"Brian","email":"bjsmith@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":651213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":651214,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brandt, Laura A.","contributorId":146646,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":651215,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70177880,"text":"70177880 - 2016 - Identification and classification of very low frequency waves on a coral reef flat","interactions":[],"lastModifiedDate":"2016-12-01T13:24:49","indexId":"70177880","displayToPublicDate":"2016-10-18T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Identification and classification of very low frequency waves on a coral reef flat","docAbstract":"Very low frequency (VLF, 0.001–0.005 Hz) waves are important drivers of flooding of low-lying coral reef-islands. In particular, VLF wave resonance is known to drive large wave runup and subsequent overwash. Using a 5 month data set of water levels and waves collected along a cross-reef transect on Roi-Namur Island in the Republic of the Marshall Islands, the observed VLF motions were categorized into four different classes: (1) resonant, (2) (nonresonant) standing, (3) progressive-growing, and (4) progressive-dissipative waves. Each VLF class is set by the reef flat water depth and, in the case of resonance, the incident-band offshore wave period. Using an improved method to identify VLF wave resonance, we find that VLF wave resonance caused prolonged (∼0.5–6.0 h), large-amplitude water surface oscillations at the inner reef flat ranging in wave height from 0.14 to 0.83 m. It was induced by relatively long-period, grouped, incident-band waves, and occurred under both storm and nonstorm conditions. Moreover, observed resonant VLF waves had nonlinear, bore-like wave shapes, which likely have a larger impact on the shoreline than regular, sinusoidal waveforms. As an alternative technique to the commonly used Fast Fourier Transformation, we propose the Hilbert-Huang Transformation that is more computationally expensive but can capture the wave shape more accurately. This research demonstrates that understanding VLF waves on reef flats is important for evaluating coastal flooding hazards.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JC011834","usgsCitation":"Gawehn, M., van Dongeran, A., van Rooijen, A., Storlazzi, C.D., Cheriton, O., and Reniers, A., 2016, Identification and classification of very low frequency waves on a coral reef flat: Journal of Geophysical Research C: Oceans, v. 121, no. 10, p. 7560-7574, https://doi.org/10.1002/2016JC011834.","productDescription":"15 p.","startPage":"7560","endPage":"7574","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074557","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470502,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jc011834","text":"Publisher Index Page"},{"id":330435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Republic of the Marshall Islands","otherGeospatial":"Roi-Namur Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 167.47086524963376,\n 9.403254406542626\n ],\n [\n 167.47395515441895,\n 9.403000374334932\n ],\n [\n 167.47610092163083,\n 9.402831019426165\n ],\n [\n 167.4767017364502,\n 9.401391499354965\n ],\n [\n 167.4788475036621,\n 9.400883432017688\n ],\n [\n 167.48090744018555,\n 9.401052787879665\n ],\n [\n 167.48313903808594,\n 9.400883432017688\n ],\n [\n 167.48485565185547,\n 9.399359225530548\n ],\n [\n 167.48665809631345,\n 9.3976656548948\n ],\n [\n 167.48743057250977,\n 9.395125283406898\n ],\n [\n 167.48614311218262,\n 9.391314691232486\n ],\n [\n 167.48236656188965,\n 9.388520230330098\n ],\n [\n 167.4777317047119,\n 9.389959803912719\n ],\n [\n 167.47532844543457,\n 9.390721928682085\n ],\n [\n 167.47163772583008,\n 9.390467887278579\n ],\n [\n 167.4700927734375,\n 9.391822772611278\n ],\n [\n 167.46700286865234,\n 9.390467887278579\n ],\n [\n 167.46374130249023,\n 9.391145330607298\n ],\n [\n 167.46305465698242,\n 9.393855090673826\n ],\n [\n 167.4638271331787,\n 9.396818866469888\n ],\n [\n 167.4623680114746,\n 9.399782616894754\n ],\n [\n 167.46331214904785,\n 9.402322954202532\n ],\n [\n 167.46580123901367,\n 9.403423761244147\n ],\n [\n 167.46906280517578,\n 9.403762470398455\n ],\n [\n 167.47086524963376,\n 9.403254406542626\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-18","publicationStatus":"PW","scienceBaseUri":"5811c0efe4b0f497e79a5a67","contributors":{"authors":[{"text":"Gawehn, Matthijs","contributorId":176243,"corporation":false,"usgs":false,"family":"Gawehn","given":"Matthijs","email":"","affiliations":[],"preferred":false,"id":651982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Dongeran, Ap","contributorId":176244,"corporation":false,"usgs":false,"family":"van Dongeran","given":"Ap","email":"","affiliations":[],"preferred":false,"id":651983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Rooijen, Arnold","contributorId":148987,"corporation":false,"usgs":false,"family":"van Rooijen","given":"Arnold","affiliations":[{"id":12474,"text":"Deltares, Netherlands","active":true,"usgs":false}],"preferred":false,"id":651984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":651981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cheriton, Olivia 0000-0003-3011-9136 ocheriton@usgs.gov","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":149003,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","email":"ocheriton@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":651985,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reniers, Ad","contributorId":176245,"corporation":false,"usgs":false,"family":"Reniers","given":"Ad","affiliations":[],"preferred":false,"id":651986,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70177061,"text":"70177061 - 2016 - Biomarkers reveal sea turtles remained in oiled areas following the Deepwater Horizon oil spill","interactions":[],"lastModifiedDate":"2016-10-18T10:37:08","indexId":"70177061","displayToPublicDate":"2016-10-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Biomarkers reveal sea turtles remained in oiled areas following the Deepwater Horizon oil spill","docAbstract":"Assessments of large-scale disasters, such as the Deepwater Horizon oil spill, are problematic because while measurements of post-disturbance conditions are common, measurements of pre-disturbance baselines are only rarely available. Without adequate observations of pre-disaster organismal and environmental conditions, it is impossible to assess the impact of such catastrophes on animal populations and ecological communities. Here, we use long-term biological tissue records to provide pre-disaster data for a vulnerable marine organism. Keratin samples from the carapace of loggerhead sea turtles record the foraging history for up to 18 years, allowing us to evaluate the effect of the oil spill on sea turtle foraging patterns. Samples were collected from 76 satellite-tracked adult loggerheads in 2011 and 2012, approximately one to two years after the spill. Of the 10 individuals that foraged in areas exposed to surface oil, none demonstrated significant changes in foraging patterns post spill. The observed long-term fidelity to foraging sites indicates that loggerheads in the northern Gulf of Mexico likely remained in established foraging sites, regardless of the introduction of oil and chemical dispersants. More research is needed to address potential long-term health consequences to turtles in this region. Mobile marine organisms present challenges for researchers to monitor effects of environmental disasters, both spatially and temporally. We demonstrate that biological tissues can reveal long-term histories of animal behavior and provide critical pre-disaster baselines following an anthropogenic disturbance or natural disaster.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1366","usgsCitation":"Vander Zanden, H.B., Bolten, A.B., Tucker, A.D., Hart, K.M., Lamont, M.M., Fujisaki, I., Reich, K.J., Addison, D.S., Mansfield, K.L., Phillips, K.F., Pajuelo, M., and Bjorndal, K.A., 2016, Biomarkers reveal sea turtles remained in oiled areas following the Deepwater Horizon oil spill: Ecological Applications, v. 26, no. 7, p. 2145-2155, https://doi.org/10.1002/eap.1366.","productDescription":"11 p.","startPage":"2145","endPage":"2155","ipdsId":"IP-067050","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":501616,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://stars.library.ucf.edu/scopus2015/2884","text":"External Repository"},{"id":329660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-23","publicationStatus":"PW","scienceBaseUri":"5807351be4b0841e59e288a5","contributors":{"authors":[{"text":"Vander Zanden, Hannah B.","contributorId":138885,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"Hannah","email":"","middleInitial":"B.","affiliations":[{"id":12562,"text":"Department of Geology and Geophysics, University of Utah; Archie Carr Center for Sea Turtle Research, University of Florida","active":true,"usgs":false}],"preferred":false,"id":651175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bolten, Alan B.","contributorId":20247,"corporation":false,"usgs":false,"family":"Bolten","given":"Alan","email":"","middleInitial":"B.","affiliations":[{"id":12567,"text":"Archie Carr Center for Sea Turtle Research, Department of Biology, University of Florida","active":true,"usgs":false}],"preferred":false,"id":651176,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Anton D.","contributorId":79232,"corporation":false,"usgs":false,"family":"Tucker","given":"Anton","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":651177,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":651178,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lamont, Margaret M. 0000-0001-7520-6669 mlamont@usgs.gov","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":4525,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","email":"mlamont@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":651179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":651180,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reich, Kimberly J.","contributorId":175452,"corporation":false,"usgs":false,"family":"Reich","given":"Kimberly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":651181,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Addison, David S.","contributorId":138886,"corporation":false,"usgs":false,"family":"Addison","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":12563,"text":"Conservancy of Southwest Florida","active":true,"usgs":false}],"preferred":false,"id":651182,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mansfield, Katherine L.","contributorId":138887,"corporation":false,"usgs":false,"family":"Mansfield","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":12564,"text":"Department of Biology, University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":651183,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Phillips, Katrina F.","contributorId":138888,"corporation":false,"usgs":false,"family":"Phillips","given":"Katrina","email":"","middleInitial":"F.","affiliations":[{"id":12565,"text":"Rosenstiel School of Atomospheric Science, University of Miami","active":true,"usgs":false}],"preferred":false,"id":651184,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pajuelo, Mariela","contributorId":138890,"corporation":false,"usgs":false,"family":"Pajuelo","given":"Mariela","email":"","affiliations":[{"id":12567,"text":"Archie Carr Center for Sea Turtle Research, Department of Biology, University of Florida","active":true,"usgs":false}],"preferred":false,"id":651185,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bjorndal, Karen A.","contributorId":96997,"corporation":false,"usgs":false,"family":"Bjorndal","given":"Karen","email":"","middleInitial":"A.","affiliations":[{"id":12567,"text":"Archie Carr Center for Sea Turtle Research, Department of Biology, University of Florida","active":true,"usgs":false}],"preferred":false,"id":651186,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70177084,"text":"fs20163091 - 2016 - Science to support aquatic animal health","interactions":[],"lastModifiedDate":"2016-10-31T10:17:16","indexId":"fs20163091","displayToPublicDate":"2016-10-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3091","title":"Science to support aquatic animal health","docAbstract":"Healthy aquatic ecosystems are home to a diversity of plants, invertebrates, fish and wildlife. Aquatic animal populations face unprecedented threats to their health and survival from climate change, water shortages, habitat alteration, invasive species and environmental contaminants. These environmental stressors can directly impact the prevalence and severity of disease in aquatic populations. For example, periodic fish kills in the upper Chesapeake Bay Watershed are associated with many different opportunistic pathogens that proliferate in stressed fish populations. An estimated 80 percent of endangered juvenile Puget Sound steelhead trout die within two weeks of entering the marine environment, and a role for disease in these losses is being investigated. The introduction of viral hemorrhagic septicemia virus (VHSV) into the Great Lakes—a fishery worth an estimated 7 billion dollars annually—resulted in widespread fish die-offs and virus detections in 28 different fish species. Millions of dying sea stars along the west coast of North America have led to investigations into sea star wasting disease. U.S. Geological Survey (USGS) scientists are assisting managers with these issues through ecological investigations of aquatic animal diseases, field surveillance, and research to promote the development of mitigation strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163091","usgsCitation":"Purcell, M.K., and Harris, M.C., 2016, Science to support aquatic animal health: U.S. Geological Survey Fact Sheet 2016-3091, 2 p., https://dx.doi.org/10.3133/fs20163091.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-078523","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":329709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3091/fs20163091.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3091"},{"id":329708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3091/coverthb.jpg"}],"contact":"M. Camille Harris
USGS Wildlife Disease Coordinator
703-648-4019 mcharris@usgs.gov
Cynthia S. Kolar
Invasive Species Program Coordinator
703-648-4023 ckolar@usgs.gov
Deposits of the North Park Formation of late Oligocene and Miocene age are locally exposed at small, widely spaced outcrops along the margins of the roughly northwest-trending North Park syncline in the southern part of North Park, a large intermontane topographic basin in Jackson County in north-central Colorado. These outcrops suggest that rocks and sediments of the North Park Formation consist chiefly of poorly consolidated sand, weakly cemented sandstone, and pebbly sandstone; subordinate amounts of pebble conglomerate; minor amounts of cobbly pebble gravel, siltstone, and sandy limestone; and rare beds of cobble conglomerate and altered tuff. These deposits partly filled North Park as well as a few small nearby valleys and half grabens. In North Park, deposits of the North Park Formation probably once formed a broad and relatively thick sedimentary apron composed chiefly of alluvial slope deposits (mostly sheetwash and stream-channel alluvium) that extended, over a distance of at least 150 kilometers (km), northwestward from the Never Summer Mountains and northward from the Rabbit Ears Range across North Park and extended farther northwestward into the valley of the North Platte River slightly north of the Colorado-Wyoming border. The maximum preserved thickness of the formation in North Park is about 550 meters near the southeastern end of the North Park syncline.
The deposition of the North Park Formation was coeval in part with local volcanism, extensional faulting, development of half grabens, and deposition of the Browns Park Formation and Troublesome Formation and was accompanied by post-Laramide regional epeirogenic uplift. Regional deposition of extensive eolian sand sheets and loess deposits, coeval with the deposition of the North Park Formation, suggests that semiarid climatic conditions prevailed during the deposition of the North Park Formation during the late Oligocene and Miocene.
The North Park Formation locally contains a 28.1-mega-annum (Ma, million years ago) ash-flow tuff near its base at Owl Ridge and is interbedded with 29-Ma rhyodacite lava flows and volcanic breccia at Owl Mountain. The formation locally contains vertebrate fossils at least as young as Barstovian age (about 15.9–12.6 Ma) and overlies rocks as young as the White River Formation, which contains vertebrate fossils of Chadronian age (about 37–33.8 Ma) in North Park and a bed of 36.0-Ma volcanic ash in the upper part of the Laramie River valley about 30 km northeast of Walden, Colorado. Based on the ages of the vertebrate fossils, folding of the rocks and sediments in the North Park syncline may be much younger than about 16 Ma.
Bedding characteristics of the North Park Formation suggest that (1) some or much of the sand, sandstone, and pebbly sandstone may have been deposited as sheetwash alluvium; (2) much of the siltstone may have been deposited as sheetwash alluvium or ephemeral pond or marsh deposits; (3) beds of sandy limestone probably were deposited as ephemeral pond or marsh deposits; and (4) altered tuff probably was deposited in ephemeral ponds or marshes. Most of the conglomerate and gravel in the North Park Formation are stream-channel deposits that were deposited by high-energy ephemeral or intermittent streams that issued from volcanic terrain rather than debris-flow deposits in relatively near-source fan deposits dominated by sediment gravity flow. Laccolithic doming, uplift, and tilting in the Never Summer Mountains near the Mount Richthofen stock, as well as the formation of volcanic edifices in the Never Summer Mountains and the Rabbit Ears Range during the late Oligocene and Miocene, significantly steepened stream gradients and greatly increased the erosive power and transport capacity of streams that transported large rock fragments and finer sediment eroded from volcanic and sedimentary sources and deposited them in the North Park Formation.
Much of the material that makes up the rocks and sediments of the North Park Formation was derived from the erosion of volcanic, intrusive, and sedimentary rocks. Clasts in the North Park Formation were derived chiefly from the erosion of volcanic and intrusive igneous rocks of late Oligocene and Miocene age that range in composition from rhyolite to trachybasalt. These rocks are locally exposed along the west flank of the Never Summer Mountains, the north flank of the Rabbit Ears Range, and the east flank of the Park Range at and near Rabbit Ears Peak. The minor amount of igneous and metamorphic clasts of Proterozoic age in the North Park Formation are commonly composed of durable rock types that are resistant to both physical and chemical weathering. Many of these clasts may have been derived from the erosion of conglomerate and conglomeratic sandstone in the Coalmont Formation rather than from basement rocks currently at or near the ground surface in the Never Summer Mountains. Much of the sand and finer grained particles in the North Park Formation probably were derived from the erosion of sandstone, shale, and sandy claystone of the Coalmont Formation. Likewise, much of the abundant sand-sized quartz and feldspar in sand, sandstone, and pebbly sandstone of the North Park Formation probably was derived from the erosion of sandstone, conglomeratic sandstone, and conglomerate of the Coalmont Formation. Some of the fine sand, very fine sand, and silt in very fine grained sandstone and siltstone of the North Park Formation may be derived from the erosion of coeval eolian sand and loess in the Browns Park Formation that was transported across the Park Range by westerly or southwesterly winds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165126","usgsCitation":"Shroba, R.R., 2016, Geologic framework, age, and lithologic characteristics of the North Park Formation in North Park, north-central Colorado: U.S. Geological Survey Scientific Investigations Report 2016–5126, 28 p., https://dx.doi.org/10.3133/sir20165126.","productDescription":"v, 28 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-059910","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":329640,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5126/coverthb.jpg"},{"id":329637,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5126/sir20165126.pdf","text":"Report","size":"5.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5126"}],"country":"United States","state":"Colorado","otherGeospatial":"North Park Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.45820617675781,\n 40.558156335842106\n ],\n [\n -106.45820617675781,\n 40.689229364982054\n ],\n [\n -106.19453430175781,\n 40.689229364982054\n ],\n [\n -106.19453430175781,\n 40.558156335842106\n ],\n [\n -106.45820617675781,\n 40.558156335842106\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, Geosciences and Environmental Change Science Center
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Bayesian statistics, in contrast to classical statistics, uses probability to represent uncertainty about the state of knowledge. Bayesian statistics has often been associated with the idea that knowledge is subjective and that a probability distribution represents a personal degree of belief. Dr. Daniel Goodman considered this viewpoint problematic for issues of public policy. He sought to ground his Bayesian approach in data, and advocated the construction of a prior as an empirical histogram of “similar” cases. In this way, the posterior distribution that results from a Bayesian analysis combined comparable previous data with case-specific current data, using Bayes’ formula. Goodman championed such a data-based approach, but he acknowledged that it was difficult in practice. If based on a true representation of our knowledge and uncertainty, Goodman argued that risk assessment and decision-making could be an exact science, despite the uncertainties. In his view, Bayesian statistics is a critical component of this science because a Bayesian analysis produces the probabilities of future outcomes. Indeed, Goodman maintained that the Bayesian machinery, following the rules of conditional probability, offered the best legitimate inference from available data. We give an example of an informative prior in a recent study of Steller sea lion spatial use patterns in Alaska.
","language":"English","doi":"10.7287/peerj.preprints.1755v1","usgsCitation":"Gerrodette, T., Ward, E., Taylor, R.L., Schwarz, L.K., Eguchi, T., Wade, P., and Himes Boor, G., 2016, Daniel Goodman’s empirical approach to Bayesian statistics: PeerJ, 18 p., https://doi.org/10.7287/peerj.preprints.1755v1.","productDescription":"18 p.","ipdsId":"IP-055681","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":462061,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.7287/peerj.preprints.1755v1","text":"External Repository"},{"id":340166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ff0e9ce4b006455f2d61b8","contributors":{"authors":[{"text":"Gerrodette, Tim","contributorId":167034,"corporation":false,"usgs":false,"family":"Gerrodette","given":"Tim","email":"","affiliations":[{"id":7054,"text":"NOAA/NMFS, Silver Spring, MD","active":true,"usgs":false}],"preferred":false,"id":692524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, Eric 0000-0002-5047-5464","orcid":"https://orcid.org/0000-0002-5047-5464","contributorId":167035,"corporation":false,"usgs":true,"family":"Ward","given":"Eric","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":620821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":620819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwarz, Lisa K.","contributorId":167036,"corporation":false,"usgs":false,"family":"Schwarz","given":"Lisa","email":"","middleInitial":"K.","affiliations":[{"id":6641,"text":"University of California at Merced","active":true,"usgs":false}],"preferred":false,"id":692525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eguchi, Tomoharu","contributorId":167037,"corporation":false,"usgs":false,"family":"Eguchi","given":"Tomoharu","email":"","affiliations":[{"id":7054,"text":"NOAA/NMFS, Silver Spring, MD","active":true,"usgs":false}],"preferred":false,"id":620823,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wade, Paul","contributorId":167038,"corporation":false,"usgs":false,"family":"Wade","given":"Paul","email":"","affiliations":[{"id":7054,"text":"NOAA/NMFS, Silver Spring, MD","active":true,"usgs":false}],"preferred":false,"id":620824,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Himes Boor, Gina","contributorId":167039,"corporation":false,"usgs":false,"family":"Himes Boor","given":"Gina","affiliations":[{"id":5120,"text":"Montana State University, Department of Mathematical Sciences, Bozeman, MT 59717","active":true,"usgs":false}],"preferred":false,"id":620825,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188604,"text":"70188604 - 2016 - Developments in new fluid rotational seismometers: Instrument performance and future directions","interactions":[],"lastModifiedDate":"2017-06-23T16:16:24","indexId":"70188604","displayToPublicDate":"2016-10-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Developments in new fluid rotational seismometers: Instrument performance and future directions","docAbstract":"In this article we describe prototype designs and tests for low-cost rota- tional medium- and strong-motion seismometers using three types of proof mass (two liquid and one solid) and a number of transducer configurations. This article describes the third set of designs and tests in our development program. The details of our results for most of these are in the E electronic supplement to this article, whereas here we concentrate on three of the most promising and representative design combinations.\nMost of our results pertain to sensors with water or silicon oil as the proof mass, though we also tested a torsion-bar design with a solid proof mass. We find that most mass–transducer combinations lead to output proportional to rotational acceleration, with varying degrees of fidelity. Most combinations we tested can be dismissed from further development for reasons of performance or inconvenience during analysis of acceleration response (compare with E electronic supplement). In this article, we describe three of the more promising combinations, one each for the three types of response functions we measured. Of these three, one mass–transducer combination in particular (a hinged sensing element and capacitive transduction) has output voltage closely proportional to rotational displacement (angle) over a wide frequency range; such displacement proportionality obviates two of the integration steps normally re- quired to solve for continuum single-point motions or correct for tilt-induced errors in horizontal translational sensors. Thus, although we illustrate two other designs of some promise, we propose a new design that follows this displacement-proportional path while increasing the device’s sensitivity to on-axis rotations, improving its manu- facturing ease and lowering its sensitivity to translational motions.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150265","usgsCitation":"Evans, J.R., Kozak, J.T., and Jedlicka, P., 2016, Developments in new fluid rotational seismometers: Instrument performance and future directions: Bulletin of the Seismological Society of America, v. 106, no. 6, p. 2865-2878, https://doi.org/10.1785/0120150265.","productDescription":"12 p. ","startPage":"2865","endPage":"2878","ipdsId":"IP-068731","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"106","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-18","publicationStatus":"PW","scienceBaseUri":"5944ee17e4b062508e33360f","contributors":{"authors":[{"text":"Evans, John R. jrevans@usgs.gov","contributorId":529,"corporation":false,"usgs":true,"family":"Evans","given":"John","email":"jrevans@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698552,"contributorType":{"id":1,"text":"Authors"},"rank":0},{"text":"Kozak, Jan T.","contributorId":193040,"corporation":false,"usgs":false,"family":"Kozak","given":"Jan","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":698553,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jedlicka, Petr","contributorId":193041,"corporation":false,"usgs":false,"family":"Jedlicka","given":"Petr","email":"","affiliations":[],"preferred":false,"id":698554,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162047,"text":"70162047 - 2016 - Book review: Mapping gendered routes and spaces in the early modern world","interactions":[],"lastModifiedDate":"2017-04-03T10:41:50","indexId":"70162047","displayToPublicDate":"2016-10-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5120,"text":"Renaissance Quarterly","active":true,"publicationSubtype":{"id":10}},"title":"Book review: Mapping gendered routes and spaces in the early modern world","docAbstract":"This book encapsulates and extends many seminal ideas presented at the eighth “Attending to Early Modern Women” conference held at the University of Wisconsin–Milwaukee in June 2012. Merry Wiesner-Hanks has done a masterful job editing these papers within a central theme of the interaction of spatial domains with gender-based phenomena. The fifteen chapters of this book are organized into four sections: “Framework,” discussing theoretical concepts; “Embodied Environments,” focusing on physicality; “Communities and Networks” of social patterns; and “Exchanges” across geographic space. Together, a global society shaped by gender and sexuality and intersected by race and class emerges.
","language":"English","publisher":"Renaissance Society of America","publisherLocation":"New York, NY","doi":"10.1086/689092","usgsCitation":"Varanka, D.E., 2016, Book review: Mapping gendered routes and spaces in the early modern world: Renaissance Quarterly, v. 69, no. 3, https://doi.org/10.1086/689092.","productDescription":"1 p.","startPage":"1092","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069367","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":339002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","scienceBaseUri":"58e35f7fe4b09da67997eca9","contributors":{"authors":[{"text":"Varanka, Dalia E. 0000-0003-2857-9600 dvaranka@usgs.gov","orcid":"https://orcid.org/0000-0003-2857-9600","contributorId":1296,"corporation":false,"usgs":true,"family":"Varanka","given":"Dalia","email":"dvaranka@usgs.gov","middleInitial":"E.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":588401,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70171470,"text":"sir20165068 - 2016 - Estimating spatially and temporally varying recharge and runoff from precipitation and urban irrigation in the Los Angeles Basin, California","interactions":[],"lastModifiedDate":"2018-07-05T12:42:08","indexId":"sir20165068","displayToPublicDate":"2016-10-17T13:00:00","publicationYear":"2016","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":"2016-5068","title":"Estimating spatially and temporally varying recharge and runoff from precipitation and urban irrigation in the Los Angeles Basin, California","docAbstract":"A daily precipitation-runoff model, referred to as the Los Angeles Basin watershed model (LABWM), was used to estimate recharge and runoff for a 5,047 square kilometer study area that included the greater Los Angeles area and all surface-water drainages potentially contributing recharge to a 1,450 square kilometer groundwater-study area underlying the greater Los Angeles area, referred to as the Los Angeles groundwater-study area. The recharge estimates for the Los Angeles groundwater-study area included spatially distributed recharge in response to the infiltration of precipitation, runoff, and urban irrigation, as well as mountain-front recharge from surface-water drainages bordering the groundwater-study area. The recharge and runoff estimates incorporated a new method for estimating urban irrigation, consisting of residential and commercial landscape watering, based on land use and the percentage of pervious land area.
The LABWM used a 201.17-meter gridded discretization of the study area to represent spatially distributed climate and watershed characteristics affecting the surface and shallow sub-surface hydrology for the Los Angeles groundwater study area. Climate data from a local network of 201 monitoring sites and published maps of 30-year-average monthly precipitation and maximum and minimum air temperature were used to develop the climate inputs for the LABWM. Published maps of land use, land cover, soils, vegetation, and surficial geology were used to represent the physical characteristics of the LABWM area. The LABWM was calibrated to available streamflow records at six streamflow-gaging stations.
Model results for a 100-year target-simulation period, from water years 1915 through 2014, were used to quantify and evaluate the spatial and temporal variability of water-budget components, including evapotranspiration (ET), recharge, and runoff. The largest outflow of water from the LABWM was ET; the 100-year average ET rate of 362 millimeters per year (mm/yr) accounted for 66 percent of the combined water inflow of 551 mm/yr, including 488 mm/yr from precipitation and 63 mm/yr from urban irrigation. The simulated ET rate varied from a minimum of 0 mm/yr for impervious areas to high values of more than 1,000 mm/yr for many areas, including the south-facing slopes of the San Gabriel Mountains, stream channels underlain by permeable soils and thick root zones, and pervious locations receiving inflows both from urban irrigation and surface water. Runoff was the next largest outflow, averaging 145 mm/yr for the 100-year period, or 26 percent of the combined precipitation and urban-irrigation inflow. Recharge averaged 45 mm/yr, or about 8 percent of the combined inflow from precipitation and urban irrigation.
Simulation results indicated that recharge in response to urban irrigation was an important component of spatially distributed recharge, contributing an average of 56 percent of the total recharge to the eight LABWM subdomains containing the Los Angeles groundwater study area. The 100‑year average recharge rate for the eight subdomains was 41 mm/yr, or 8,473 hectare-meters per year (ha-m/yr), with urban irrigation included in the simulation compared to a recharge rate of 18 mm/yr, or 3,741 ha-m/yr, with urban irrigation excluded. In contrast to recharge, the effect of urban irrigation on runoff was slight; runoff was 72,667 ha-m/yr with urban irrigation included compared to 72,618 ha-m/yr with urban irrigation excluded, an increase of only 48 ha-m/yr (about 0.1 percent).
Simulation results also indicated that potential recharge from hilly drainages outside of, but bordering and tributary to, the lower-lying area of the Los Angeles groundwater study area, in this study referred to as mountain-front recharge, could provide an important contribution to the total recharge for the groundwater basins. The time-averaged recharge rate was similar to the combined direct and mountain-front recharge components estimated in a previous study and used as input for a calibrated groundwater model. The annual (water year) recharge estimates simulated in this study, however, indicated much greater year-to-year variability, which was dependent on year-to-year variability in the magnitude and distribution of daily precipitation, compared to the previous estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165068","collaboration":"Prepared in cooperation with the Water Replenishment District of Southern California","usgsCitation":"Hevesi, J.A., and Johnson, T.D., 2016, Estimating spatially and temporally varying recharge and runoff from precipitation and urban irrigation in the Los Angeles Basin, California: U.S. Geological Survey Scientific Investigations Report 2016–5068, 192 p., https://dx.doi.org/10.3133/sir20165068.","productDescription":"x, 192 p.","numberOfPages":"208","onlineOnly":"Y","ipdsId":"IP-053146","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":328887,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5068/coverthb.jpg"},{"id":328888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5068/sir20165068_.pdf","text":"Report","size":"32.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5068"}],"country":"United States","state":"California","otherGeospatial":"Los Angeles Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.59078979492186,\n 34.29353023058858\n ],\n [\n -117.97531127929688,\n 33.631772324639655\n ],\n [\n -118.15246582031249,\n 33.75288969455201\n ],\n [\n -118.29666137695312,\n 33.70035029271861\n ],\n [\n -118.41339111328125,\n 33.74032885072381\n ],\n [\n -118.43673706054688,\n 33.775722878425604\n ],\n [\n -118.39828491210936,\n 33.82023008524739\n ],\n [\n -118.44223022460938,\n 33.9285481685662\n ],\n [\n -118.50952148437499,\n 34.016241889667015\n ],\n [\n -118.60565185546874,\n 34.03672867489511\n ],\n [\n -118.67706298828125,\n 34.34230217446123\n ],\n [\n -118.40377807617189,\n 34.426168904360736\n ],\n [\n -117.87368774414064,\n 34.38197934098774\n ],\n [\n -117.59078979492186,\n 34.29353023058858\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Energy production in the Williston Basin, USA, results in the coproduction of highly saline, sodium chloride-dominated water (brine). The Prairie Pothole Region (PPR) overlies the northeastern portion of the Williston Basin. Although PPR wetlands span a range of salinity, the dominant salt is sodium sulfate, and salinities are much lower than brine. Introduction of brine to wetlands can result in pronounced water-quality changes; however, the ecological effects of such contamination are poorly understood. We examined the effects of brine contamination on primary productivity, emergent macrophyte tissue chemistry, and invertebrate communities from 10 wetlands in the PPR. Based on a recognized Contamination Index (CI) used to identify brine contamination in the PPR, water-quality samples indicated that six wetlands were uncontaminated while four were contaminated. Across this gradient, we observed a significant decrease in above-ground biomass and a significant increase in tissue chloride concentrations of hardstem bulrush (Schoenoplectus acutus) with increased CI values. Additionally, a significant decrease in macroinvertebrate taxonomic richness with increased CI values was observed. These findings provide needed insight on the biological effects of brine contamination on PPR wetlands.
","language":"English","publisher":"Informa UK","doi":"10.1080/02705060.2016.1231137","usgsCitation":"Preston, T.M., and Ray, A.M., 2016, Effects of energy development on wetland plants and macroinvertebrate communities in Prairie Pothole Region wetlands: Journal of Freshwater Ecology, 7 p., https://doi.org/10.1080/02705060.2016.1231137.","productDescription":"7 p.","ipdsId":"IP-073505","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470503,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2016.1231137","text":"Publisher Index Page"},{"id":335190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-17","publicationStatus":"PW","scienceBaseUri":"589fff1ae4b099f50d3e044b","chorus":{"doi":"10.1080/02705060.2016.1231137","url":"http://dx.doi.org/10.1080/02705060.2016.1231137","publisher":"Informa UK Limited","authors":"Preston Todd M., Ray Andrew M.","journalName":"Journal of Freshwater Ecology","publicationDate":"10/17/2016"},"contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233 tmpreston@usgs.gov","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":1664,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"tmpreston@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":663158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":663159,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182772,"text":"70182772 - 2016 - Interaction between climate, volcanism, and isostatic rebound in Southeast Alaska during the last deglaciation","interactions":[],"lastModifiedDate":"2017-03-01T14:56:17","indexId":"70182772","displayToPublicDate":"2016-10-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Interaction between climate, volcanism, and isostatic rebound in Southeast Alaska during the last deglaciation","docAbstract":"Observations of enhanced volcanic frequency during the last deglaciation have led to the hypothesis that ice unloading in glaciated volcanic terrains can promote volcanism through decompression melting in the shallow mantle or a reduction in crustal magma storage time. However, a direct link between regional climate change, isostatic adjustment, and the initiation of volcanism remains to be demonstrated due to the difficulty of obtaining high-resolution well-dated records that capture short-term climate and volcanic variability traced to a particular source region. Here we present an exceptionally resolved record of 19 tephra layers paired with foraminiferal oxygen isotopes and alkenone paleotemperatures from marine sediment cores along the Southeast Alaska margin spanning the last deglacial transition. Major element compositions of the tephras indicate a predominant source from the nearby Mt. Edgecumbe Volcanic Field (MEVF). We constrain the timing of this regional eruptive sequence to 14.6–13.1 ka. The sudden increase in volcanic activity from the MEVF coincides with the onset of Bølling–Allerød interstadial warmth, the disappearance of ice-rafted detritus, and rapid vertical land motion associated with modeled regional isostatic rebound in response to glacier retreat. These data support the hypothesis that regional deglaciation can rapidly trigger volcanic activity. Rapid sea surface temperature fluctuations and an increase in local salinity (i.e., δ18Osw) variability are associated with the interval of intense volcanic activity, consistent with a two-way interaction between climate and volcanism in which rapid volcanic response to ice unloading may in turn enhance short-term melting of the glaciers, plausibly via albedo effects on glacier ablation zones.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.07.033","usgsCitation":"Praetorius, S., Mix, A., Jensen, B., Froese, D., Milne, G.A., Wolhowe, M., Addison, J.A., and Prahl, F., 2016, Interaction between climate, volcanism, and isostatic rebound in Southeast Alaska during the last deglaciation: Earth and Planetary Science Letters, v. 452, p. 79-89, https://doi.org/10.1016/j.epsl.2016.07.033.","productDescription":"11 p.","startPage":"79","endPage":"89","ipdsId":"IP-071002","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":336780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"452","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba5e4b01ccd5500baf7","contributors":{"authors":[{"text":"Praetorius, Summer","contributorId":184162,"corporation":false,"usgs":false,"family":"Praetorius","given":"Summer","affiliations":[],"preferred":false,"id":673695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":673696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jensen, Britta","contributorId":184164,"corporation":false,"usgs":false,"family":"Jensen","given":"Britta","affiliations":[],"preferred":false,"id":673697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Froese, Duane","contributorId":184165,"corporation":false,"usgs":false,"family":"Froese","given":"Duane","affiliations":[],"preferred":false,"id":673698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milne, Glenn A.","contributorId":178028,"corporation":false,"usgs":false,"family":"Milne","given":"Glenn","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":673699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wolhowe, Matthew","contributorId":184166,"corporation":false,"usgs":false,"family":"Wolhowe","given":"Matthew","affiliations":[],"preferred":false,"id":673700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":673694,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prahl, Fred","contributorId":184167,"corporation":false,"usgs":false,"family":"Prahl","given":"Fred","email":"","affiliations":[],"preferred":false,"id":673701,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70178936,"text":"70178936 - 2016 - Comparison of mercury mass loading in streams to atmospheric deposition in watersheds of Western North America: Evidence for non-atmospheric mercury sources","interactions":[],"lastModifiedDate":"2018-08-07T12:24:30","indexId":"70178936","displayToPublicDate":"2016-10-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of mercury mass loading in streams to atmospheric deposition in watersheds of Western North America: Evidence for non-atmospheric mercury sources","docAbstract":"Annual stream loads of mercury (Hg) and inputs of wet and dry atmospheric Hg deposition to the landscape were investigated in watersheds of the Western United States and the Canadian-Alaskan Arctic. Mercury concentration and discharge data from flow gauging stations were used to compute annual mass loads with regression models. Measured wet and modeled dry deposition were compared to annual stream loads to compute ratios of Hg stream load to total Hg atmospheric deposition. Watershed land uses or cover included mining, undeveloped, urbanized, and mixed. Of 27 watersheds that were investigated, 15 had some degree of mining, either of Hg or precious metals (gold or silver), where Hg was used in the amalgamation process. Stream loads in excess of annual Hg atmospheric deposition (ratio > 1) were observed in watersheds containing Hg mines and in relatively small and medium-sized watersheds with gold or silver mines, however, larger watersheds containing gold or silver mines, some of which also contain large dams that trap sediment, were sometimes associated with lower load ratios (< 0.2). In the non-Arctic regions, watersheds with natural vegetation tended to have low ratios of stream load to Hg deposition (< 0.1), whereas urbanized areas had higher ratios (0.34–1.0) because of impervious surfaces. This indicated that, in ecosystems with natural vegetation, Hg is retained in the soil and may be transported subsequently to streams as a result of erosion or in association with dissolved organic carbon. Arctic watersheds (Mackenzie and Yukon Rivers) had a relatively elevated ratio of stream load to atmospheric deposition (0.27 and 0.74), possibly because of melting glaciers or permafrost releasing previously stored Hg to the streams. Overall, our research highlights the important role of watershed characteristics in determining whether a landscape is a net source of Hg or a net sink of atmospheric Hg.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.02.112","usgsCitation":"Domagalski, J.L., Majewski, M.S., Alpers, C.N., Eckley, C.S., Eagles-Smith, C.A., Schenk, L.N., and Wherry, S., 2016, Comparison of mercury mass loading in streams to atmospheric deposition in watersheds of Western North America: Evidence for non-atmospheric mercury sources: Science of the Total Environment, v. 568, p. 638-650, https://doi.org/10.1016/j.scitotenv.2016.02.112.","productDescription":"13 p.","startPage":"638","endPage":"650","ipdsId":"IP-069584","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":332020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"568","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585116bbe4b08138bf1abd56","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Majewski, Michael S. majewski@usgs.gov","contributorId":440,"corporation":false,"usgs":true,"family":"Majewski","given":"Michael","email":"majewski@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eckley, Chris S.","contributorId":167256,"corporation":false,"usgs":false,"family":"Eckley","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":655593,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","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":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655594,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655595,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wherry, Susan 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":140159,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655707,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176941,"text":"70176941 - 2016 - Colonial waterbird predation on Lost River and Shortnose suckers in the Upper Klamath Basin","interactions":[],"lastModifiedDate":"2016-10-13T10:51:47","indexId":"70176941","displayToPublicDate":"2016-10-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Colonial waterbird predation on Lost River and Shortnose suckers in the Upper Klamath Basin","docAbstract":"We evaluated predation on Lost River Suckers Deltistes luxatus and Shortnose Suckers Chasmistes brevirostris by American white pelicans Pelecanus erythrorhynchos and double-crested cormorants Phalacrocorax auritus nesting at mixed-species colonies in the Upper Klamath Basin of Oregon and California during 2009–2014. Predation was evaluated by recovering (detecting) PIT tags from tagged fish on bird colonies and calculating minimum predation rates, as the percentage of available suckers consumed, adjusted for PIT tag detection probabilities but not deposition probabilities (i.e., probability an egested tag was deposited on- or off-colony). Results indicate that impacts of avian predation varied by sucker species, age-class (adult, juvenile), bird colony location, and year, demonstrating dynamic predator–prey interactions. Tagged suckers ranging in size from 72 to 730 mm were susceptible to cormorant or pelican predation; all but the largest Lost River Suckers were susceptible to bird predation. Minimum predation rate estimates ranged annually from <0.1% to 4.6% of the available PIT-tagged Lost River Suckers and from <0.1% to 4.2% of the available Shortnose Suckers, and predation rates were consistently higher on suckers in Clear Lake Reservoir, California, than on suckers in Upper Klamath Lake, Oregon. There was evidence that bird predation on juvenile suckers (species unknown) in Upper Klamath Lake was higher than on adult suckers in Upper Klamath Lake, where minimum predation rates ranged annually from 5.7% to 8.4% of available juveniles. Results suggest that avian predation is a factor limiting the recovery of populations of Lost River and Shortnose suckers, particularly juvenile suckers in Upper Klamath Lake and adult suckers in Clear Lake Reservoir. Additional research is needed to measure predator-specific PIT tag deposition probabilities (which, based on other published studies, could increase predation rates presented herein by a factor of roughly 2.0) and to better understand biotic and abiotic factors that regulate sucker susceptibility to bird predation.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2016.1208123","usgsCitation":"Evans, A.F., Hewitt, D.A., Payton, Q., Cramer, B.M., Collis, K., and Roby, D.D., 2016, Colonial waterbird predation on Lost River and Shortnose suckers in the Upper Klamath Basin: North American Journal of Fisheries Management, v. 36, no. 6, p. 1254-1268, https://doi.org/10.1080/02755947.2016.1208123.","startPage":"1254","endPage":"1268","numberOfPages":"15","ipdsId":"IP-072319","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":470505,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02755947.2016.1208123","text":"Publisher Index Page"},{"id":329524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28332519531249,\n 41.693424216151314\n ],\n [\n -122.28332519531249,\n 42.67435857693381\n ],\n [\n -120.91278076171874,\n 42.67435857693381\n ],\n [\n -120.91278076171874,\n 41.693424216151314\n ],\n [\n -122.28332519531249,\n 41.693424216151314\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-07","publicationStatus":"PW","scienceBaseUri":"57ffdefde4b0824b2d179cee","contributors":{"authors":[{"text":"Evans, Allen F.","contributorId":171691,"corporation":false,"usgs":false,"family":"Evans","given":"Allen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":650813,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":650812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Payton, Quinn","contributorId":149990,"corporation":false,"usgs":false,"family":"Payton","given":"Quinn","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":650814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cramer, Bradley M.","contributorId":171692,"corporation":false,"usgs":false,"family":"Cramer","given":"Bradley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":650815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collis, Ken","contributorId":149991,"corporation":false,"usgs":false,"family":"Collis","given":"Ken","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":650816,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":650817,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70181005,"text":"70181005 - 2016 - Spatial variation in nutrient and water color effects on lake chlorophyll at macroscales","interactions":[],"lastModifiedDate":"2017-02-11T18:48:16","indexId":"70181005","displayToPublicDate":"2016-10-13T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Spatial variation in nutrient and water color effects on lake chlorophyll at macroscales","docAbstract":"The nutrient-water color paradigm is a framework to characterize lake trophic status by relating lake primary productivity to both nutrients and water color, the colored component of dissolved organic carbon. Total phosphorus (TP), a limiting nutrient, and water color, a strong light attenuator, influence lake chlorophyll a concentrations (CHL). But, these relationships have been shown in previous studies to be highly variable, which may be related to differences in lake and catchment geomorphology, the forms of nutrients and carbon entering the system, and lake community composition. Because many of these factors vary across space it is likely that lake nutrient and water color relationships with CHL exhibit spatial autocorrelation, such that lakes near one another have similar relationships compared to lakes further away. Including this spatial dependency in models may improve CHL predictions and clarify how well the nutrient-water color paradigm applies to lakes distributed across diverse landscape settings. However, few studies have explicitly examined spatial heterogeneity in the effects of TP and water color together on lake CHL. In this study, we examined spatial variation in TP and water color relationships with CHL in over 800 north temperate lakes using spatially-varying coefficient models (SVC), a robust statistical method that applies a Bayesian framework to explore space-varying and scale-dependent relationships. We found that TP and water color relationships were spatially autocorrelated and that allowing for these relationships to vary by individual lakes over space improved the model fit and predictive performance as compared to models that did not vary over space. The magnitudes of TP effects on CHL differed across lakes such that a 1 μg/L increase in TP resulted in increased CHL ranging from 2–24 μg/L across lake locations. Water color was not related to CHL for the majority of lakes, but there were some locations where water color had a positive effect such that a unit increase in water color resulted in a 2 μg/L increase in CHL and other locations where it had a negative effect such that a unit increase in water color resulted in a 2 μg/L decrease in CHL. In addition, the spatial scales that captured variation in TP and water color effects were different for our study lakes. Variation in TP–CHL relationships was observed at intermediate distances (~20 km) compared to variation in water color–CHL relationships that was observed at regional distances (~200 km). These results demonstrate that there are lake-to-lake differences in the effects of TP and water color on lake CHL and that this variation is spatially structured. Quantifying spatial structure in these relationships furthers our understanding of the variability in these relationships at macroscales and would improve model prediction of chlorophyll a to better meet lake management goals.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0164592","usgsCitation":"Fergus, C.E., Finley, A.O., Soranno, P.A., and Wagner, T., 2016, Spatial variation in nutrient and water color effects on lake chlorophyll at macroscales: PLoS ONE, e0164592; 20 p., https://doi.org/10.1371/journal.pone.0164592.","productDescription":"e0164592; 20 p.","ipdsId":"IP-072158","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0164592","text":"Publisher Index Page"},{"id":335187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine, Michigan, New York, Wisconsin","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-13","publicationStatus":"PW","scienceBaseUri":"589fff1ae4b099f50d3e044d","contributors":{"authors":[{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":663408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finley, Andrew O.","contributorId":39310,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":663409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":663410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":663163,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176306,"text":"sir20165124 - 2016 - FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region","interactions":[],"lastModifiedDate":"2019-12-30T14:43:18","indexId":"sir20165124","displayToPublicDate":"2016-10-13T00:00:00","publicationYear":"2016","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":"2016-5124","title":"FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region","docAbstract":"Climate change is expected to alter the distributions and community composition of stream fishes in the Great Lakes region in the 21st century, in part as a result of altered hydrological systems (stream temperature, streamflow, and habitat). Resource managers need information and tools to understand where fish species and stream habitats are expected to change under future conditions. Fish sample collections and environmental variables from multiple sources across the United States Great Lakes Basin were integrated and used to develop empirical models to predict fish species occurrence under present-day climate conditions. Random Forests models were used to predict the probability of occurrence of 13 lotic fish species within each stream reach in the study area. Downscaled climate data from general circulation models were integrated with the fish species occurrence models to project fish species occurrence under future climate conditions. The 13 fish species represented three ecological guilds associated with water temperature (cold, cool, and warm), and the species were distributed in streams across the Great Lakes region. Vulnerability (loss of species) and opportunity (gain of species) scores were calculated for all stream reaches by evaluating changes in fish species occurrence from present-day to future climate conditions. The 13 fish species included 4 cold-water species, 5 cool-water species, and 4 warm-water species. Presently, the 4 cold-water species occupy from 15 percent (55,000 kilometers [km]) to 35 percent (130,000 km) of the total stream length (369,215 km) across the study area; the 5 cool-water species, from 9 percent (33,000 km) to 58 percent (215,000 km); and the 4 warm-water species, from 9 percent (33,000 km) to 38 percent (141,000 km).
Fish models linked to projections from 13 downscaled climate models projected that in the mid to late 21st century (2046–65 and 2081–2100, respectively) habitats suitable for all 4 cold-water species and 4 of 5 cool-water species under present-day conditions will decline as much as 86 percent and as little as 33 percent, and habitats suitable for all 4 warm-water species will increase as much as 33 percent and as little as 7 percent. This report documents the approach and data used to predict and project fish species occurrence under present-day and future climate conditions for 13 lotic fish species in the United States Great Lakes Basin. A Web-based decision support mapping application termed “FishVis” was developed to provide a means to integrate, visualize, query, and download the results of these projected climate-driven responses and help inform conservation planning efforts within the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165124","collaboration":"Prepared in cooperation with Michigan State University, Michigan Department of Natural Resources Institute of Fisheries Research, and the Wisconsin Department of Natural Resources","usgsCitation":"Stewart, J.S., Covert, S.A., Estes, N.J., Westenbroek, S.M., Krueger, Damon, Wieferich, D.J., Slattery, M.T., Lyons, J.D., McKenna, J.E., Jr., Infante, D.M., and Bruce, J.L., 2016, FishVis, A regional decision support tool for identifying vulnerabilities of riverine habitat and fishes to climate change in the Great Lakes Region: U.S. Geological Survey Scientific Investigations Report 2016–5124, 15 p., with appendixes, https://dx.doi.org/10.3133/sir20165124.","productDescription":"Report: viii, 15 p.; Appendixes 1-4","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071837","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":438537,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F74T6GGG","text":"USGS data release","linkHelpText":"FishVis, predicted occurrence and vulnerability for 13 fish species for current (1961 - 1990) and future (2046 - 2100) climate conditions in Great Lakes streams."},{"id":329488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5124/coverthb.jpg"},{"id":329489,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5124/sir20165124.pdf","text":"Report","size":"2.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5124"},{"id":329490,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5124/sir20165124_appendixes1to4.xlsx","text":"Appendixes 1–4","size":"34.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5124 Appendixes"}],"country":"United States","otherGeospatial":"Great Lakes Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.94433593749999,\n 46.5286346952717\n ],\n [\n -86.66015624999999,\n 46.164614496897094\n ],\n [\n -88.24218749999999,\n 44.715513732021336\n ],\n [\n -87.978515625,\n 43.004647127794435\n ],\n [\n -87.5390625,\n 41.47566020027821\n ],\n [\n -86.484375,\n 41.44272637767212\n ],\n [\n -85.869140625,\n 44.465151013519616\n ],\n [\n -84.55078125,\n 45.30580259943578\n ],\n [\n -83.671875,\n 44.715513732021336\n ],\n [\n -83.935546875,\n 43.51668853502906\n ],\n [\n -83.14453125,\n 42.90816007196054\n ],\n [\n -83.6279296875,\n 41.705728515237524\n ],\n [\n -81.34277343749999,\n 41.44272637767212\n ],\n [\n -78.6181640625,\n 42.779275360241904\n ],\n [\n -75.76171875,\n 43.67581809328341\n ],\n [\n -76.37695312499999,\n 44.465151013519616\n ],\n [\n -78.837890625,\n 43.866218006556394\n ],\n [\n -81.03515625,\n 42.87596410238256\n ],\n [\n -82.177734375,\n 42.74701217318067\n ],\n [\n -81.2109375,\n 44.5278427984555\n ],\n [\n -79.62890625,\n 44.402391829093915\n ],\n [\n -81.73828125,\n 46.255846818480315\n ],\n [\n -83.8916015625,\n 46.6795944656402\n ],\n [\n -84.5947265625,\n 47.754097979680026\n ],\n [\n -86.3525390625,\n 48.66194284607006\n ],\n [\n -87.8466796875,\n 49.26780455063753\n ],\n [\n -89.912109375,\n 48.42920055556841\n ],\n [\n -92.021484375,\n 47.15984001304432\n ],\n [\n -92.94433593749999,\n 46.5286346952717\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
This report updates and revises the 2010 “ Status of Fish Habitats in the United States” that summarized initial results of a comprehensive national assessment of aquatic habitats at an unprecedented scale and level of detail. This 2015 report provides even greater detail and improves our knowledge of the condition of fish habitat in the United States. The 2010 inland streams assessment characterized fish habitat condition using stream fish data from more than 26,000 stream reaches, while the 2015 assessment was based on fish data from more than 39,000 stream reaches nationally. To increase accuracy, the 2015 inland stream assessment incorporated 12 additional human disturbance variables into the fish analysis when compared to the 2010 assessment. Associations between all human disturbance variables summarized in both catchments as well as stream buffers were tested against stream fish metrics to develop assessment scores. Additional variables incorporated into the 2015 assessment and their summary within catchments and buffers allowed for more explicit characterization of the diverse set of disturbances to stream fish habitats occurring across the Nation than what occurred in 2010, and this was made possible due in part to advances in available GIS layers. With the incorporation of these additional disturbances, managers and decision makers can use assessment results to more explicitly identify limits to stream fish habitats. Even with the additional disturbances incorporated into 2015 assessment, results may overestimate fish habitat condition, as localized and regionally-specific disturbances are still not available in some cases.
","language":"English","publisher":"National Fish Habitat Partnership","usgsCitation":"Crawford, S., Whelan, G., Infante, D.M., Blackhart, K., Daniel, W.M., Fuller, P., Birdsong, T.W., Wieferich, D.J., McClees-Funinan, R., Stedman, S., Herreman, K., and Ruhl, P.M., 2016, Through a fish's eye: The status of fish habitats in the United States 2015, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-077455 ","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":358334,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://assessment.fishhabitat.org/ "},{"id":358335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c10ada0e4b034bf6a7e78db","contributors":{"authors":[{"text":"Crawford, Steve","contributorId":209632,"corporation":false,"usgs":false,"family":"Crawford","given":"Steve","email":"","affiliations":[],"preferred":false,"id":748439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whelan, Gary","contributorId":146115,"corporation":false,"usgs":false,"family":"Whelan","given":"Gary","email":"","affiliations":[{"id":16584,"text":"Fisheries Division, Michigan Department of Natural Resources, P.O. Box 30446, Lansing, MI 48909","active":true,"usgs":false}],"preferred":false,"id":748440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Infante, Dana M. 0000-0003-1385-1587","orcid":"https://orcid.org/0000-0003-1385-1587","contributorId":150821,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":18112,"text":"Dept. of Fisheries and Wildlife,","active":true,"usgs":false}],"preferred":false,"id":748441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackhart, Kristan","contributorId":209633,"corporation":false,"usgs":false,"family":"Blackhart","given":"Kristan","email":"","affiliations":[],"preferred":false,"id":748448,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Daniel, Wesley M. 0000-0002-7656-8474 wdaniel@usgs.gov","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":194723,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","email":"wdaniel@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":748442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuller, Pam 0000-0002-9389-9144 pfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9389-9144","contributorId":167676,"corporation":false,"usgs":true,"family":"Fuller","given":"Pam","email":"pfuller@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":748443,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Birdsong, Timothy W.","contributorId":172473,"corporation":false,"usgs":false,"family":"Birdsong","given":"Timothy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":748444,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wieferich, Daniel J. 0000-0003-1554-7992 dwieferich@usgs.gov","orcid":"https://orcid.org/0000-0003-1554-7992","contributorId":176205,"corporation":false,"usgs":true,"family":"Wieferich","given":"Daniel","email":"dwieferich@usgs.gov","middleInitial":"J.","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":5069,"text":"Office of the AD Core Science Systems","active":true,"usgs":true}],"preferred":true,"id":748438,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClees-Funinan, Ricardo 0000-0002-3254-1843 rmcclees-funinan@usgs.gov","orcid":"https://orcid.org/0000-0002-3254-1843","contributorId":5988,"corporation":false,"usgs":true,"family":"McClees-Funinan","given":"Ricardo","email":"rmcclees-funinan@usgs.gov","affiliations":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"preferred":true,"id":748445,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stedman, Susan","contributorId":209634,"corporation":false,"usgs":false,"family":"Stedman","given":"Susan","email":"","affiliations":[],"preferred":false,"id":748449,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Herreman, Kyle","contributorId":187650,"corporation":false,"usgs":false,"family":"Herreman","given":"Kyle","email":"","affiliations":[],"preferred":false,"id":748450,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ruhl, Peter M. 0000-0002-5032-6266 pmruhl@usgs.gov","orcid":"https://orcid.org/0000-0002-5032-6266","contributorId":4300,"corporation":false,"usgs":true,"family":"Ruhl","given":"Peter","email":"pmruhl@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":748451,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70215549,"text":"70215549 - 2016 - Detecting and inferring cause of change in an Alaska nearshore marine ecosystem","interactions":[],"lastModifiedDate":"2020-10-22T13:57:43.359142","indexId":"70215549","displayToPublicDate":"2016-10-12T08:51:47","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Detecting and inferring cause of change in an Alaska nearshore marine ecosystem","docAbstract":"Community composition, species abundance, and species distribution are expected to change while monitoring ecosystems over time, and effective management of natural resources requires understanding mechanisms contributing to change. Marine ecosystems in particular can be difficult to monitor, in part due to large, multidimensional spatial scales and complex dynamics. However, within the temperate marine ecosystems, the nearshore food web is reasonably well described. This food web is ecologically and socially important, spatially constrained, and has been the focus of extensive experimental research that describes the underlying mechanisms important to system dynamics. Here, we describe a monitoring program initiated in 2006 that focuses on the nearshore benthic food web in the Gulf of Alaska, whose design anticipates potential causes of ecosystem change to improve rigor, resolution, and confidence in understanding the mechanisms underlying change. We established 15 long‐term monitoring sites across more than 1000 km of coastline, including 10 within two national parks and 5 within Prince William Sound, area of the 1989 Exxon Valdez oil spill. The program evaluates six ecological indicators and more than 200 species that range from primary producers to top‐level consumers, and is designed to examine both bottom‐up and top‐down dynamics. Employing a design that allows broad spatial inference and selecting species with direct food‐web linkages, we demonstrate the ability of our monitoring program to simultaneously detect change and assess potential mechanisms underlying that change. Detecting change and understanding mechanisms can help guide management and conservation policy. Specifically, we provide an example focusing on the sea otter (Enhydra lutris) that illustrates how (1) analytical methods are used to evaluate changes on various scales and infer potential mechanisms of change, (2) food‐web linkages can enhance the understanding of changes and their effects, and (3) data can be used to inform management.
Water samples were collected and analyzed for arsenic and radon from 36 private, mostly domestic wells that tap the Rancocas aquifer in southern New Castle and northern Kent Counties, Delaware, during the summer of 2015. Both arsenic and radon are from natural mineral sources, in particular glauconitic and other marine-derived sediments, which are important components of the geologic formations comprising the Rancocas aquifer. Routine testing of domestic wells is not required in Delaware; as a result, many homeowners are not aware of potential water-quality problems with these chemicals in their well water. Arsenic has previously been detected at levels of potential concern for human health in this aquifer in adjacent parts of Maryland where it is referred to as the Aquia aquifer. Arsenic and radon also have previously been detected in several Rancocas aquifer wells in Delaware. The Delaware Department of Natural Resources and Environmental Control intends to use the data from this project to better identify areas with potential for levels of concern for domestic well owners. This report includes chemical results and maps showing the distribution of sampled wells and concentrations of arsenic and radon. All data collected for this study also are available in the U.S. Geological Survey’s National Water Information System database.
Arsenic was detected above the minimum reporting limit of 0.1 micrograms per liter (µg/L) in 34 of the 36 wells sampled with concentrations ranging from about 0.11 to 27 µg/L. In 15 of the samples, arsenic concentrations were at or above the U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL) of 10 µg/L for public wells. Most of the higher concentrations are clustered along a band running from the southwest to northeast in the southern part of the study area.
Radon, which is an inert gas derived from radium, was detected in all water samples with concentrations ranging from 85 to 1,870 picocuries per liter (pCi/L). Currently, the EPA has not set a MCL for radon in public water systems. There were no samples where radon was detected at a concentration exceeding the proposed alternative MCL of 4,000 pCi/L. Samples from 16 of 36 wells were above the lower proposed MCL of 300 pCi/L. Most of these samples were from wells greater than 200 feet deep located in a similar part of the aquifer as the higher concentrations of arsenic along an east-northeasterly line in the southern part of the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161143","isbn":"978-1-4113 4086-2","collaboration":"Prepared in cooperation with the Delaware Department of Natural Resources and Environmental Control (DNREC) Water Supply Section, Groundwater Protection Branch","usgsCitation":"Denver, J.M., 2016, Occurrence and distribution of arsenic and radon in water from private wells in the Rancocas aquifer, southern New Castle and northern Kent Counties, Delaware, 2015: U.S. Geological Survey Open-File Report 2016–1143, 15 p., https://dx.doi.org/10.3133/ofr20161143. ","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"N","ipdsId":"IP-076094","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":329414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1143/ofr20161143.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1143"},{"id":329413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1143/coverthb.jpg"}],"country":"United States","state":"Delaware","county":"Kent County, New Castle County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.43624877929688,\n 39.310925412127155\n ],\n [\n -75.76034545898438,\n 39.298705113102244\n ],\n [\n -75.77888488769531,\n 39.50827899034114\n ],\n [\n -75.57220458984375,\n 39.51834388059882\n ],\n [\n -75.43624877929688,\n 39.310925412127155\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Or visit our Web site at:
http://md.water.usgs.gov
The occurrence of fish species may be strongly influenced by a stream’s thermal regime (magnitude, frequency, variation, and timing). For instance, magnitude and frequency provide information about sublethal temperatures, variability in temperature can affect behavioral thermoregulation and bioenergetics, and timing of thermal events may cue life history events, such as spawning and migration. We explored the relationship between thermal regimes and the occurrences of native Bull Trout Salvelinus confluentus and nonnative Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta across 87 sites in the upper Klamath River basin, Oregon. Our objectives were to associate descriptors of the thermal regime with trout occurrence, predict the probability of Bull Trout occurrence, and estimate upper thermal tolerances of the trout species. We found that each species was associated with a different suite of thermal regime descriptors. Bull Trout were present at sites that were cooler, had fewer high-temperature events, had less variability, and took longer to warm. Brook Trout were also observed at cooler sites with fewer high-temperature events, but the sites were more variable and Brook Trout occurrence was not associated with a timing descriptor. In contrast, Brown Trout were present at sites that were warmer and reached higher temperatures faster, but they were not associated with frequency or variability descriptors. Among the descriptors considered, magnitude (specifically June degree-days) was the most important in predicting the probability of Bull Trout occurrence, and model predictions were strengthened by including Brook Trout occurrence. Last, all three trout species exhibited contrasting patterns of tolerating longer exposures to lower temperatures. Tolerance limits for Bull Trout were lower than those for Brook Trout and Brown Trout, with contrasts especially evident for thermal maxima. Our results confirm the value of exploring a suite of thermal regime descriptors for understanding the distribution and occurrence of fishes. Moreover, these descriptors and their relationships to fish should be considered with future changes in land use, water use, or climate.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/00028487.2016.1219677","usgsCitation":"Benjamin, J.R., Heltzel, J., Dunham, J.B., Heck, M., and Banish, N.P., 2016, Thermal regimes, nonnative trout, and their influences on native Bull Trout in the Upper Klamath River Basin, Oregon: Transactions of the American Fisheries Society, v. 145, no. 6, p. 1318-1330, https://doi.org/10.1080/00028487.2016.1219677.","productDescription":"13 p.","startPage":"1318","endPage":"1330","ipdsId":"IP-073755","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470507,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Thermal_Regimes_Nonnative_Trout_and_Their_Influences_on_Native_Bull_Trout_in_the_Upper_Klamath_River_Basin_Oregon/4007463","text":"External Repository"},{"id":329486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.2283935546875,\n 42.0125705565935\n ],\n [\n -122.2283935546875,\n 42.91620643817353\n ],\n [\n -120.970458984375,\n 42.91620643817353\n ],\n [\n -120.970458984375,\n 42.0125705565935\n ],\n [\n -122.2283935546875,\n 42.0125705565935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"57ff4bf5e4b0824b2d159761","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":650613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heltzel, Jeannie","contributorId":175260,"corporation":false,"usgs":false,"family":"Heltzel","given":"Jeannie","email":"","affiliations":[{"id":27548,"text":"D.J. Warren & Associates Inc.","active":true,"usgs":false}],"preferred":false,"id":650614,"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":650612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heck, Michael 0000-0001-8858-7325 mheck@usgs.gov","orcid":"https://orcid.org/0000-0001-8858-7325","contributorId":4796,"corporation":false,"usgs":true,"family":"Heck","given":"Michael","email":"mheck@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":650615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Banish, Nolan P.","contributorId":168511,"corporation":false,"usgs":false,"family":"Banish","given":"Nolan","email":"","middleInitial":"P.","affiliations":[{"id":25313,"text":"U.S. Fish and Wildlife Service, Klamath Falls Fish and Wildlife Office, 1936 California Avenue, Klamath Falls, Oregon, 97601, USA","active":true,"usgs":false}],"preferred":false,"id":650616,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70175527,"text":"sir20165119 - 2016 - Flood inundation maps for the Wabash River at New Harmony, Indiana","interactions":[],"lastModifiedDate":"2016-10-11T15:52:58","indexId":"sir20165119","displayToPublicDate":"2016-10-11T15:45:00","publicationYear":"2016","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":"2016-5119","title":"Flood inundation maps for the Wabash River at New Harmony, Indiana","docAbstract":"Digital flood-inundation maps for a 3.68-mile reach of the Wabash River extending 1.77 miles upstream and 1.91 miles downstream from streamgage 03378500 at New Harmony, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Wabash River at New Harmony, Ind. (station 03378500). Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NHRI3).
Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at the Wabash River at New Harmony, Ind., streamgage and the documented high-water marks from the flood of April 27–28, 2013. The calibrated hydraulic model was then used to compute 17 water-surface profiles for flood stages at approximately 1-foot intervals referenced to the streamgage datum and ranging from 10.0 feet, or near bankfull, to 25.4 feet, the highest stage of the stage-discharge rating curve used in the model. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging (lidar) data having a 0.98-ft vertical accuracy and 4.9-ft horizontal resolution) to delineate the area flooded at each water level.
The availability of these maps along with Internet information regarding current stage from the USGS streamgage at Wabash River at New Harmony, Ind., and forecasted stream stages from the NWS will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165119","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Fowler, K.K., 2016, Flood-inundation maps for the Wabash River at New Harmony, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5119, 14 p., https://dx.doi.org/10.3133/sir20165119.","productDescription":"Report: vii, 14 p.; Metadata; Read Me; Spatial Data","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066894","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":329430,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/metadata_depth_grids.pdf","text":"Metadata Depth Grids","size":"94.3 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"},{"id":329431,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/metadata_shapefile.pdf","text":"Metadata Shapefiles","size":"94.9 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"},{"id":329432,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/00Readme.pdf","text":"Readme","size":"82.6 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"},{"id":329433,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/depth_grids.zip","text":"Depth Grids","size":"144 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5119"},{"id":329434,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2016/5119/downloads/shapefiles.zip","text":"Shape File","size":"2.40 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5119"},{"id":329410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5119/coverthb.jpg"},{"id":329411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5119/sir20165119.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5119"}],"country":"United States","state":"Indiana","city":"New Harmony","otherGeospatial":"Wabash River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.03173065185545,\n 38.10700680156137\n ],\n [\n -88.03173065185545,\n 38.171003529816126\n ],\n [\n -87.8580093383789,\n 38.171003529816126\n ],\n [\n -87.8580093383789,\n 38.10700680156137\n ],\n [\n -88.03173065185545,\n 38.10700680156137\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana-Kentucky Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
http://in.water.usgs.gov/
The Alaskan breeding population of Steller’s eiders (Polysticta stelleri) was listed as threatened under the Endangered Species Act in 1997 in response to perceived declines in abundance throughout their breeding and nesting range. Aerial surveys suggest the breeding population is small and highly variable in number, with zero birds counted in 5 of the last 25 years. Research was conducted to evaluate competing population process models of Alaskan-breeding Steller’s eiders through comparison of model projections to aerial survey data. To evaluate model efficacy and estimate demographic parameters, a Bayesian state-space modeling framework was used and each model was fit to counts from the annual aerial surveys, using sequential importance sampling and resampling. The results strongly support that the Alaskan breeding population experiences population level nonbreeding events and is open to exchange with the larger Russian-Pacific breeding population. Current recovery criteria for the Alaskan breeding population rely heavily on the ability to estimate population viability. The results of this investigation provide an informative model of the population process that can be used to examine future population states and assess the population in terms of the current recovery and reclassification criteria.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161062","usgsCitation":"Dunham, Kylee, and Grand, J.B., 2016, Evaluating models of population process in a threatened population of Steller’s eiders—A retrospective approach: U.S. Geological Survey Open-File Report 2016–1062, 14 p., https://dx.doi.org/10.3133/ofr20161062.","productDescription":"vi, 14 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074896","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":329250,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/preview/ofr20161084","text":"Open-File Report 2016–1084","description":"Open-File Report 2016–1084","linkHelpText":"- Viability of the Alaskan Breeding Population of Steller’s Eiders"},{"id":329247,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1062/ofr20161062.pdf","text":"Report","size":"355 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1062"},{"id":329246,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1062/coverthb.jpg"}],"contact":"Chief, Cooperative Research Units
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192-0002
https://www.usgs.gov/science/mission-areas/ecosystems