Hydraulic connection between channels and floodplains (“connectivity”) is a fundamental determinant of ecosystem function in large floodplain rivers. Factors controlling material processing in these rivers depend not only on the degree of connectivity but also on the sediment conditions, nutrient loads, and source. Nutrient cycling in the nutrient‐rich upper Mississippi River (MISS) is relatively well studied, whereas that of less eutrophic tributaries is not (e.g., St Croix River; SACN). We examined components of nitrogen cycling in 2 floodplain rivers of contrasting nutrient enrichment and catchment land use to test the hypothesis that N‐cycling rates will be greater in the MISS with elevated nutrient loads and productivity in contrast to the relatively nutrient‐poor SACN. Nitrate (NO3−‐N) concentrations were greatest in flowing habitats in the MISS and often undetectable in isolated backwaters except where groundwater inputs occurred. In the SACN, NO3−‐N concentrations were greatest in the flowing backwater where groundwater inputs were high. Ambient nitrification in the MISS was twice that in the SACN and tended to be lowest in the main channel. Denitrification was 3× greater in the MISS than that in the SACN, N‐limited in both rivers. Community production/respiration was >1 in the MISS and likely provisioned labile C to fuel microbial metabolism and dissimilatory NO3−‐N reduction, whereas the heterotrophic (production/respiration < 1) nature of the SACN likely limited microbial metabolism and NO3−‐N dissimilation. It appears that N‐cycling in the SACN was driven by groundwater, whereas that in the MISS was supported mainly by water column N‐sources.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3267","usgsCitation":"Richardson, W.B., Bartsch, L., Bartsch, M., Kiesling, R.L., and Mroska-LaFrancois, B., 2019, Nitrogen cycling in large temperate floodplain rivers of contrasting nutrient regimes and management: River Research and Applications, v. 35, no. 5, p. 529-539, https://doi.org/10.1002/rra.3267.","productDescription":"11 p.","startPage":"529","endPage":"539","ipdsId":"IP-086420","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468130,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3267","text":"Publisher Index Page"},{"id":364703,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Mississippi River, St. Croix River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.955322265625,\n 45.22848059584359\n ],\n [\n -92.515869140625,\n 45.22848059584359\n ],\n [\n -92.515869140625,\n 45.56021795715051\n ],\n [\n -92.955322265625,\n 45.56021795715051\n ],\n [\n -92.955322265625,\n 45.22848059584359\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.09814453125,\n 44.61393394730626\n ],\n [\n -92.8125,\n 44.61393394730626\n ],\n [\n -92.8125,\n 44.879228141635245\n ],\n [\n -93.09814453125,\n 44.879228141635245\n ],\n [\n -93.09814453125,\n 44.61393394730626\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"5","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":764289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartsch, Lynn A. 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":149360,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn A.","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":764290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartsch, Michelle 0000-0002-9571-5564 mbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-9571-5564","contributorId":216242,"corporation":false,"usgs":true,"family":"Bartsch","given":"Michelle","email":"mbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":764291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":764292,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mroska-LaFrancois, Brenda","contributorId":216243,"corporation":false,"usgs":false,"family":"Mroska-LaFrancois","given":"Brenda","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":764293,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227896,"text":"70227896 - 2019 - Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement","interactions":[],"lastModifiedDate":"2022-02-02T17:14:09.501322","indexId":"70227896","displayToPublicDate":"2018-04-17T11:00:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement","title":"Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement","docAbstract":"The specificity and accuracy of inferred fish origin and movement relies on describing spatial heterogeneity and temporal stability of environmental signatures. But the cost and logistics of sample collection often precludes the complete quantification of environmental signature temporal stability and spatial heterogeneity. We used repeated sampling and a novel approach (Bayesian ridge regression, BRR) to quantify the temporal stability and spatial heterogeneity of 87Sr/86Sr, respectively. We explained 86% of observed variation in 87Sr/86Sr using a BRR model and estimated 87Sr/86Sr throughout the Upper North Platte River Basin with high accuracy (±0.00106). Year to year variation in 87Sr/86Sr signatures ranged from 0.00007 to 0.00073 (SD), while seasonal variation ranged from 0.00091 to 0.00134 (SD). We then assessed the specificity and discussed the accuracy of inferring movement using three scenarios of described spatial heterogeneity. Our results indicate reliable inference of fish movement requires comprehensive quantification of spatial heterogeneity and temporal variation in environmental signatures.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0124","usgsCitation":"Ciepiela, L.R., and Walters, A.W., 2019, Quantifying 87Sr/86Sr temporal stability and spatial heterogeneity for use in tracking fish movement: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 6, p. 928-936, https://doi.org/10.1139/cjfas-2018-0124.","productDescription":"9 p.","startPage":"928","endPage":"936","ipdsId":"IP-094459","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501331,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/93571","text":"External Repository"},{"id":395283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Upper North Platte River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.138671875,\n 40.74725696280421\n ],\n [\n -106,\n 40.74725696280421\n ],\n [\n -106,\n 42.48830197960227\n ],\n [\n -107.138671875,\n 42.48830197960227\n ],\n [\n -107.138671875,\n 40.74725696280421\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"76","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ciepiela, Lindsy R.","contributorId":273061,"corporation":false,"usgs":false,"family":"Ciepiela","given":"Lindsy","email":"","middleInitial":"R.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":832549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832548,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70229751,"text":"70229751 - 2019 - Application of an updated atmospheric model to explore volcano infrasound propagation and detection in Alaska","interactions":[],"lastModifiedDate":"2022-03-16T14:28:52.392954","indexId":"70229751","displayToPublicDate":"2018-04-05T09:22:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Application of an updated atmospheric model to explore volcano infrasound propagation and detection in Alaska","docAbstract":"Winds and temperature gradients greatly affect the long-range propagation of infrasound. The spatio-temporal variability of these parameters must therefore be accurately characterized to correctly interpret recorded infrasound at long distances, specifically to differentiate between source and propagation effects. Here we present the first results of an open source reanalysis model, termed Alaska Volcano Observatory Ground-to-Space (AVO-G2S), constructed to accurately characterize the atmosphere and model long-range infrasound propagation from volcanic eruptions in Alaska. We select a number of case studies to examine recent eruptions of Alaskan volcanoes whose ash emissions posed a threat to air traffic, including the two most recent eruptions of Pavlof Volcano and two typical explosions from Cleveland Volcano. Strong tropospheric ducting and low noise at the station during the 21 July 2015 explosion of Cleveland Volcano led to an automated detection of the explosion at an infrasound array 992 km away, whereas low signal-to-noise ratio for the 6 November 2014 Cleveland Volcano explosion helps explain the non-detection in real-time of a predicted strong stratospheric arrival. For the November 2014 Pavlof eruption, discrepancies between local seismic data and a distal infrasound array 460 km away cannot be solely explained by changes in atmospheric conditions, though some features of the complex propagation predictions follow the trends in long-range infrasound signals. The most recent eruption of Pavlof Volcano in March 2016 shows minimal changes in propagation conditions throughout the eruption and therefore indicates that the signals detected at long-range primarily reflect source processes. These results show how detailed examination of the acoustic propagation conditions provides insight into detection capability and eruption dynamics. Future work will implement AVO-G2S and high-resolution long-range infrasound propagation modeling in real-time for Alaskan volcanoes of interest.
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Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":838178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwaiger, Hans 0000-0001-7397-8833","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":214983,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":838179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":838180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":838181,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70200426,"text":"70200426 - 2019 - Desert wetlands record hydrologic variability within the Younger Dryas chronozone, Mojave Desert, USA","interactions":[],"lastModifiedDate":"2023-03-27T22:46:23.462905","indexId":"70200426","displayToPublicDate":"2018-04-04T10:43:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Desert wetlands record hydrologic variability within the Younger Dryas chronozone, Mojave Desert, USA","docAbstract":"One of the enduring questions in the field of paleohydrology is how quickly desert wetland ecosystems responded to past episodes of abrupt climate change. Recent investigations in the Las Vegas Valley of southern Nevada have revealed that wetlands expanded and contracted on millennial and sub-millennial timescales in response to changes in climate during the late Quaternary. Here, we evaluate geologic evidence from multiple localities in the Mojave Desert and southern Great Basin that suggests the response of wetland systems to climate change is even faster, occurring at centennial, and possibly decadal, timescales. Paleowetland deposits at Dove Springs Wash, Mesquite Springs, and Little Dixie Wash, California, contain evidence of multiple wet and dry cycles in the form of organic-rich black mats, representing periods of past groundwater discharge and wet conditions, interbedded with colluvial, alluvial, and aeolian sediments, each representing dry conditions. Many of these wet-dry cycles date to within the Younger Dryas (YD) chronozone (12.9–11.7 ka), marking the first time intra-YD hydrologic variability has been documented in paleowetland deposits. Our results illustrate that desert wetland ecosystems are exceptionally sensitive to climate change and respond to climatic perturbations on timescales that are relevant to human society.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2018.14","usgsCitation":"Pigati, J.S., Springer, K.B., and Honke, J.S., 2019, Desert wetlands record hydrologic variability within the Younger Dryas chronozone, Mojave Desert, USA: Quaternary Research, v. 91, no. 1, p. 51-62, https://doi.org/10.1017/qua.2018.14.","productDescription":"12 p.","startPage":"51","endPage":"62","ipdsId":"IP-091234","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":358470,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119,\n 34\n ],\n [\n -113,\n 34\n ],\n [\n -113,\n 37\n ],\n [\n -119,\n 37\n ],\n [\n -119,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-04","publicationStatus":"PW","scienceBaseUri":"5bed4274e4b0b3fc5cf91c94","contributors":{"authors":[{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":748781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":748782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Honke, Jeffrey S. 0000-0003-4357-9297 jhonke@usgs.gov","orcid":"https://orcid.org/0000-0003-4357-9297","contributorId":201389,"corporation":false,"usgs":true,"family":"Honke","given":"Jeffrey","email":"jhonke@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":748783,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205109,"text":"70205109 - 2019 - A new indicator framework for quantifying the intensity of the terrestrialwater cycle","interactions":[],"lastModifiedDate":"2019-09-03T15:14:53","indexId":"70205109","displayToPublicDate":"2018-04-02T15:10:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A new indicator framework for quantifying the intensity of the terrestrialwater cycle","docAbstract":"A quantitative framework for characterizing the intensity of the water cycle over land is presented, and illustrated using a spatially distributed water-balance model of the conterminous United States (CONUS). We approach water cycle intensity (WCI) from a landscape perspective; WCI is defined as the sum of precipitation (P) and actual evapotranspiration (AET) over a spatially explicit landscape unit of interest, averaged over a specified time period (step) of interest. The time step may be of any length for which data or simulation results are available (e.g., sub-daily to multi-decadal). We define the storage-adjusted runoff (Q0) as the sum of actual runoff (Q) and the rate of change in soil moisture storage (DS/Dt, positive or negative) during the time step of interest. The Q0 indicator is demonstrated to be mathematically complementary to WCI, in a manner that allows graphical interpretation of their relationship. For the purposes of this study, the indicators were demonstrated using long-term, spatially distributed model simulations with an annual time step. WCI was found to increase over most of the CONUS between the 1945 to 1974 and 1985 to 2014 periods, driven primarily by increases in P. In portions of the western and southeastern CONUS, Q0 decreased because of decreases in Q and soil moisture storage. Analysis of WCI and Q0 at temporal scales ranging from sub-daily to multi-decadal could improve understanding of the wide spectrum of hydrologic responses that have been attributed to water cycle intensification, as well as trends in those responses.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2018.02.048","usgsCitation":"Huntington, T.G., Weiskel, P., Wolock, D.M., and McCabe, G.J., 2019, A new indicator framework for quantifying the intensity of the terrestrialwater cycle: Journal of Hydrology, v. 559, p. 361-372, https://doi.org/10.1016/j.jhydrol.2018.02.048.","productDescription":"12 p.","startPage":"361","endPage":"372","ipdsId":"IP-070433","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science 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dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":770058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":770059,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196326,"text":"70196326 - 2019 - Gene flow connects coastal populations of a habitat specialist, the Clapper Rail Rallus crepitans","interactions":[],"lastModifiedDate":"2019-01-28T09:56:08","indexId":"70196326","displayToPublicDate":"2018-04-02T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1961,"text":"Ibis","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Gene flow connects coastal populations of a habitat specialist, the Clapper Rail Rallus crepitans","title":"Gene flow connects coastal populations of a habitat specialist, the Clapper Rail Rallus crepitans","docAbstract":"Examining population genetic structure can reveal patterns of reproductive isolation or population mixing and inform conservation management. Some avian species are predicted to exhibit minimal genetic differentiation among populations as a result of the species high mobility, with habitat specialists tending to show greater fine‐scale genetic structure. To explore the relationship between habitat specialization and gene flow, we investigated the genetic structure of a saltmarsh specialist with high potential mobility across a wide geographic range of fragmented habitat. Little variation among mitochondrial sequences (620 bp from ND2) was observed among 149 individual Clapper Rails Rallus crepitans sampled along the Atlantic coast of North America, with the majority of individuals at all sampling sites sharing a single haplotype. Genotyping of nine microsatellite loci across 136 individuals revealed moderate genetic diversity, no evidence of bottlenecks, and a weak pattern of genetic differentiation that increased with geographic distance. Multivariate analyses, Bayesian clustering and an AMOVA all suggested a lack of genetic structuring across the North American Atlantic coast, with all individuals grouped into a single interbreeding population. Spatial autocorrelation analyses showed evidence of weak female philopatry and a lack of male philopatry. We conclude that high gene flow connecting populations of this habitat specialist may result from the interaction of ecological and behavioral factors that promote dispersal and limit natal philopatry and breeding‐site fidelity. As climate change threatens saltmarshes, the genetic diversity and population connectivity of Clapper Rails may promote resilience of their populations. This finding helps inform about potential fates of other similarly behaving saltmarsh specialists on the Atlantic coast.
","language":"English","publisher":"Wiley","doi":"10.1111/ibi.12599","usgsCitation":"Coster, S.S., Welsh, A.B., Costanzo, G.R., Harding, S.R., Anderson, J.T., and Katzner, T., 2019, Gene flow connects coastal populations of a habitat specialist, the Clapper Rail Rallus crepitans: Ibis, v. 161, no. 1, p. 66-78, https://doi.org/10.1111/ibi.12599.","productDescription":"13 p.","startPage":"66","endPage":"78","ipdsId":"IP-095851","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":468131,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ibi.12599","text":"Publisher Index Page"},{"id":353068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"161","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-06","publicationStatus":"PW","scienceBaseUri":"5afee6eae4b0da30c1bfbf5d","contributors":{"authors":[{"text":"Coster, Stephanie S. 0000-0002-5170-4548","orcid":"https://orcid.org/0000-0002-5170-4548","contributorId":203794,"corporation":false,"usgs":false,"family":"Coster","given":"Stephanie","email":"","middleInitial":"S.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":732332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Amy B.","contributorId":192239,"corporation":false,"usgs":false,"family":"Welsh","given":"Amy","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":732333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costanzo, Gary R.","contributorId":198907,"corporation":false,"usgs":false,"family":"Costanzo","given":"Gary","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":732334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harding, Sergio R.","contributorId":198906,"corporation":false,"usgs":false,"family":"Harding","given":"Sergio","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":732335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":732336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":732331,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203571,"text":"70203571 - 2019 - Appalachian Basin stratigraphy, tectonics, and eustasy from the Blue Ridge to the Allegheny Front, Virginia and West Virginia","interactions":[],"lastModifiedDate":"2019-05-22T16:10:37","indexId":"70203571","displayToPublicDate":"2018-03-30T15:23:24","publicationYear":"2019","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"seriesTitle":{"id":5835,"text":"Field Trip Guide","active":true,"publicationSubtype":{"id":15}},"seriesNumber":"FTG-10","title":"Appalachian Basin stratigraphy, tectonics, and eustasy from the Blue Ridge to the Allegheny Front, Virginia and West Virginia","docAbstract":"This guide is from a two-day field trip in western Virginia and eastern West Virginia held before the 2015 Geological Society of America annual meeting in Baltimore, Maryland. The field trip examines exposures of Paleozoic sedimentary strata in the Appalachian Basin starting in the Blue Ridge physiographic province, going through the Valley and Ridge physiographic province, and ending in the Appalachian Plateau physiographic province. Most of the field-trip stops are along US 48 (Corridor H) in West Virginia.","language":"English","publisher":"West Virginia Geological and Economic Survey","usgsCitation":"Haynes, J.T., Pitts, A.D., Doctor, D.H., Diecchio, R.J., and Blake, M.B., 2019, Appalachian Basin stratigraphy, tectonics, and eustasy from the Blue Ridge to the Allegheny Front, Virginia and West Virginia: Field Trip Guide FTG-10, 86 p.","productDescription":"86 p.","ipdsId":"IP-077232","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":364098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364097,"type":{"id":15,"text":"Index Page"},"url":"https://downloads.wvgs.wvnet.edu/pubcat/docs/FTG-10%20Corridor%20H%20guidebook%20%20lo-res.pdf"}],"country":"United States","state":"Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.5,\n 38.5\n ],\n [\n -77.5,\n 38.5\n ],\n [\n -77.5,\n 39.5\n ],\n [\n -79.5,\n 39.5\n ],\n [\n -79.5,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Haynes, John T.","contributorId":197407,"corporation":false,"usgs":false,"family":"Haynes","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":763193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pitts, Alan D.","contributorId":215769,"corporation":false,"usgs":false,"family":"Pitts","given":"Alan","email":"","middleInitial":"D.","affiliations":[{"id":39316,"text":"University of Camerino, Italy","active":true,"usgs":false}],"preferred":false,"id":763194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":763192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diecchio, Richard J.","contributorId":215770,"corporation":false,"usgs":false,"family":"Diecchio","given":"Richard","email":"","middleInitial":"J.","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":763195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blake, Mitchell B.","contributorId":215771,"corporation":false,"usgs":false,"family":"Blake","given":"Mitchell","email":"","middleInitial":"B.","affiliations":[{"id":35742,"text":"West Virginia Geological and Economic Survey","active":true,"usgs":false}],"preferred":false,"id":763196,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215594,"text":"70215594 - 2019 - The influence of land-cover changes on the variability of saturated hydraulic conductivity in tropical peatlands","interactions":[],"lastModifiedDate":"2020-10-25T18:10:30.770026","indexId":"70215594","displayToPublicDate":"2018-03-29T13:03:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7177,"text":"Mitigation and Adaption Strategies for Global Change","active":true,"publicationSubtype":{"id":10}},"title":"The influence of land-cover changes on the variability of saturated hydraulic conductivity in tropical peatlands","docAbstract":"Understanding the movement of water through peat is essential for effective conservation and management strategies for peatlands. Saturated hydraulic conductivity, Ks, describes water movement through the peat profile. However, the spatial variability of Ks in tropical peatlands and the effects of land conversion on peat characteristics are poorly understood. Utilizing the slug test method, we estimated hydraulic conductivity in tropical peatlands in West Kalimantan, Indonesia, at three depths (0.75, 3.5, and 5.5 m) across four different land-cover types (undrained forests, recently burned forests, early seral communities, and oil palm (Elaeis guineensis Jacq.) plantations). We found strong spatial autocorrelation among measurements collected at our 19 study sites and evaluated the relationship between hydraulic conductivity and land-cover types, peat properties, and depth of measurement with a hierarchical linear model. Hydraulic conductivity varied greatly (c. 0.001–13.9 m d−1). The best approximating model for estimating Ks contained depth, forest cover, a depth and forest cover interaction, and the von Post degree of decomposition (Ks ~ depth + forest + depth × forest + von Post). Parameter estimates indicated that Ks was greater in forested than non-forested sites and decreased with increasing depth and decomposition stage. There was no evidence that Ks differed among the non-forested sites or was related to other physical and chemical peat properties. Our results suggest that Ks should be measured directly in tropical peatlands rather than estimated as a function of peat properties. Additionally, the strong spatial dependence suggests that similar research designs should examine the sample data for spatial dependence and, if necessary, incorporate hierarchical models.
In the upper Chattahoochee River basin, where some populations of shoal bass, Micropterus cataractae Williams & Burgess, are imperilled, age and growth data are lacking. Age and growth of shoal bass in this basin were assessed with non‐lethal means using scales and mark–recapture. Mark–recapture data allowed for estimation of accuracy and determination of effects of any scale‐based inaccuracies on growth models. Scale‐based age estimates were accurate for 57% of the samples, and errors of 1 to 3 years included equal numbers of over‐ and underestimates of age. von Bertalanffy growth models based on scale ages were similar to those based on mark–recapture ages for ages 3–8 but noticeably divergent for younger and older fish. Scales provided estimates of longevity up to 12 years of age, and growth models produced from mark–recapture suggest scale ages underestimated age, especially for older fish. These populations of shoal bass live longer and grow slower than other populations, suggesting regional management strategies may be needed.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12274","usgsCitation":"Long, J.M., Holley, C.T., and Taylor, A.T., 2019, Evaluation of ageing accuracy with complementary non‐lethal methods for slow‐growing, northern populations of shoal bass: Fisheries Management and Ecology, v. 25, no. 2, p. 150-157, https://doi.org/10.1111/fme.12274.","productDescription":"7 p.","startPage":"150","endPage":"157","ipdsId":"IP-080326","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":365774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Gerogia","otherGeospatial":"Chattahoochee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.91357421875,\n 34.939985151560435\n ],\n [\n -85.95703125,\n 33.63291573870479\n ],\n [\n -86.02294921875,\n 32.175612478499325\n ],\n [\n -85.62744140625,\n 30.619004797647808\n ],\n [\n -84.74853515625,\n 29.611670115197377\n ],\n [\n -83.75976562499999,\n 29.859701442126756\n ],\n [\n -83.95751953125,\n 30.600093873550072\n ],\n [\n -84.52880859375,\n 32.30570601389429\n ],\n [\n -84.83642578125,\n 33.137551192346145\n ],\n [\n -82.96875,\n 34.59704151614417\n ],\n [\n -83.91357421875,\n 34.939985151560435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":766516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holley, C. T.","contributorId":217373,"corporation":false,"usgs":false,"family":"Holley","given":"C.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":766517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, A. T.","contributorId":217377,"corporation":false,"usgs":false,"family":"Taylor","given":"A.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":766670,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204121,"text":"70204121 - 2019 - Long-term assessment of ichthyoplankton in a large North American river system reveals changes in fish community dynamics","interactions":[],"lastModifiedDate":"2019-07-08T11:06:22","indexId":"70204121","displayToPublicDate":"2018-03-07T10:58:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Long-term assessment of ichthyoplankton in a large North American river system reveals changes in fish community dynamics","docAbstract":"Larval fishes are sensitive to abiotic conditions and provide a direct measure of spawning success. The St. Clair – Detroit River System, a Laurentian Great Lakes connecting channel with a history of environmental degradation, has undergone improvements in habitat and water quality since the 1970s. We compared 2006–2015 ichthyoplankton community data with those collected prior to remediation efforts (1977–1978) to identify patterns in spatial and temporal variability. Both assemblages exhibited a predictable phenology, with taxa from the subfamily Coregoninae dominant in early spring followed by families Osmeridae, Percidae, and Moronidae (May–June) and Cyprinidae and Clupeidae (June–August). While higher densities of larval fish were found in the Detroit River, greater taxa richness and Shannon diversity were observed in the St. Clair River. System wide, 14 new taxa were observed in the 2000s study period. In addition, relative densities of two nonnative species, alewife (Alosa pseudoharengus) and rainbow smelt (Osmerus mordax), declined since the 1970s. Increased larval fish richness and decreased densities of nonnative taxa in the 2000s are consistent with improvements to environmental conditions.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2017-0511","usgsCitation":"Taaja R. Tucker, Roseman, E.F., DeBruyne, R.L., Jeremy J. Pritt, Bennion, D., Hondorp, D.W., and Boase, J.C., 2019, Long-term assessment of ichthyoplankton in a large North American river system reveals changes in fish community dynamics: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 12, p. 2255-2270, https://doi.org/10.1139/cjfas-2017-0511.","productDescription":"16 p.","startPage":"2255","endPage":"2270","ipdsId":"IP-092433","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":468132,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2017-0511","text":"Publisher Index Page"},{"id":365334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"Detroit River, Lake St Claire, St Claire River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.5675048828125,\n 41.89409955811395\n ],\n [\n -82.353515625,\n 41.89409955811395\n ],\n [\n -82.353515625,\n 43.0287452513488\n ],\n [\n -83.5675048828125,\n 43.0287452513488\n ],\n [\n -83.5675048828125,\n 41.89409955811395\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"12","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taaja R. 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Individual birds that are heavily oiled lose their ability to fly and may become ill or die from hypothermia, starvation, exhaustion, or drowning (Clark 1984, Rocke 1999). For example, large-scale oiling from the Exxon Valdez spill caused local declines in populations of many avian taxa (Irons et al. 2000). Although most oiling reports involve marine wildlife exposed to oil leaked from vessels or oil rigs, oiling also can occur in terrestrial environments, for example, via birds drinking water in puddles on asphalt roadways (Clark and Gorney 1987) or landing in oil field wastewater disposal facilities (Trail 2006, Ramírez 2010).
","language":"English","publisher":"BioOne","doi":"10.3356/JRR-17-23.1","usgsCitation":"Katzner, T., Driscoll, D., Jackman, R.E., Bloom, P., Thomas, S., Cooper, J., Livingstone, S.J., Grubb, T., Doyle, J.M., Bell, D.A., Didonato, J., and DeWoody, J.A., 2019, Non-anthropogenic diet-based oiling of predatory birds: Journal of Raptor Research, v. 52, no. 1, p. 82-88, https://doi.org/10.3356/JRR-17-23.1.","productDescription":"7 p.","startPage":"82","endPage":"88","ipdsId":"IP-076711","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":365011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365005,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.3356/JRR-17-23.1"}],"volume":"52","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":765016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Daniel","contributorId":140137,"corporation":false,"usgs":false,"family":"Driscoll","given":"Daniel","affiliations":[],"preferred":false,"id":765017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackman, Ronald E.","contributorId":190827,"corporation":false,"usgs":false,"family":"Jackman","given":"Ronald","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":765018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bloom, Peter","contributorId":182414,"corporation":false,"usgs":false,"family":"Bloom","given":"Peter","affiliations":[],"preferred":false,"id":765019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thomas, Scott","contributorId":216553,"corporation":false,"usgs":false,"family":"Thomas","given":"Scott","affiliations":[{"id":39474,"text":"Bloom Biological Inc.","active":true,"usgs":false}],"preferred":false,"id":765020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cooper, Jeff","contributorId":199741,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":765021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Livingstone, Stephen J.","contributorId":179162,"corporation":false,"usgs":false,"family":"Livingstone","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":765022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grubb, Teryl","contributorId":216554,"corporation":false,"usgs":false,"family":"Grubb","given":"Teryl","email":"","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":765023,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Doyle, Jacqueline M.","contributorId":175099,"corporation":false,"usgs":false,"family":"Doyle","given":"Jacqueline","email":"","middleInitial":"M.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":765024,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bell, Douglas A.","contributorId":199739,"corporation":false,"usgs":false,"family":"Bell","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":24634,"text":"East Bay Regional Park District","active":true,"usgs":false}],"preferred":false,"id":765025,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Didonato, Joseph","contributorId":216555,"corporation":false,"usgs":false,"family":"Didonato","given":"Joseph","email":"","affiliations":[{"id":39475,"text":"Wildlife Consulting & Photography","active":true,"usgs":false}],"preferred":false,"id":765026,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"DeWoody, J. Andrew","contributorId":175103,"corporation":false,"usgs":false,"family":"DeWoody","given":"J.","email":"","middleInitial":"Andrew","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":765027,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70204202,"text":"70204202 - 2019 - Evidence of repeated long-distance movements by lake charr Salvelinus namaycush in Lake Huron","interactions":[],"lastModifiedDate":"2019-07-12T08:59:40","indexId":"70204202","displayToPublicDate":"2018-02-20T15:27:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evidence of repeated long-distance movements by lake charr Salvelinus namaycush in Lake Huron","title":"Evidence of repeated long-distance movements by lake charr Salvelinus namaycush in Lake Huron","docAbstract":"Movements and dispersal distances of acoustically-tagged adult lake charr Salvelinus namaycush were estimated based on detections at acoustic receivers in Lake Huron during 2010–2014. Most lake charr were detected only at receivers proximate to their release location or were not detected at all, but 3–9% of tagged lake charr were detected at receivers located over 100 km from their release location. Several fish made extensive repeated migrations within the lake, some at the scale of the entire main basin. Our observations show that some lake charr individuals repeat a similar pattern each year of moving long distances, and some fish were observed to show annual fidelity to presumed foraging sites in the spring at a spatial scale of approximately 200 km. Our telemetry-based estimates were minimum estimates of dispersal, as the placement of receivers within Lake Huron was not optimal for detection of lake charr and did not cover the majority of the lake. Further study of long-distance movement in lake charr is necessary to fully understand the implications of this behavior to lake charr ecology, population dynamics, and management in the Great Lakes.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-018-0714-6","usgsCitation":"Riley, S., Binder, T., Taaja R. Tucker, and Krueger, C.C., 2019, Evidence of repeated long-distance movements by lake charr Salvelinus namaycush in Lake Huron: Environmental Biology of Fishes, v. 101, no. 4, p. 531-545, https://doi.org/10.1007/s10641-018-0714-6.","productDescription":"15 p.","startPage":"531","endPage":"545","ipdsId":"IP-087084","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":365490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.7705078125,\n 42.85180609584705\n ],\n [\n -79.5849609375,\n 42.85180609584705\n ],\n [\n -79.5849609375,\n 46.430285240839964\n ],\n [\n -84.7705078125,\n 46.430285240839964\n ],\n [\n -84.7705078125,\n 42.85180609584705\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"101","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Riley, Stephen 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":169479,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binder, Tom","contributorId":166711,"corporation":false,"usgs":false,"family":"Binder","given":"Tom","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":765966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taaja R. Tucker","contributorId":169481,"corporation":false,"usgs":false,"family":"Taaja R. Tucker","affiliations":[{"id":25527,"text":"CSS-Dynamac","active":true,"usgs":false}],"preferred":false,"id":765967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krueger, Charles C.","contributorId":169487,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":765968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204367,"text":"70204367 - 2019 - Seasonal trophic variation of yellow perch exceeds spatial variation in a large lake basin","interactions":[],"lastModifiedDate":"2019-12-22T14:50:00","indexId":"70204367","displayToPublicDate":"2018-02-10T12:35:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal trophic variation of yellow perch exceeds spatial variation in a large lake basin","docAbstract":"Trophic structuring of complex food webs may vary at multiple spatial and temporal scales, both in terms of direct trophic connections and underlying energy pathways that support production. In large freshwater systems, the prey and primary producers that support individual higher-order consumers may vary across seasons and habitats due to differences in food availability, predator consumption patterns, seasonal succession of organisms at lower trophic levels, and heterogeneous nutrient inputs. We examined spatial and temporal variation in stomach contents, fatty acids, and stable isotopes of yellow perch (Perca flavescens) across seasons and across sites spanning approximately 200 km in Lake Erie's Central Basin (LECB). Stomach contents provided a short-term index of trophic patterns, while biochemical markers (fatty acids and stable isotopes) provided a more temporally integrated description of underlying energy pathways and trophic links. We found limited spatial variation of biochemical indicators and documented seasonal variation for all three trophic indicators, especially fatty acid profiles. Differences in stomach contents were driven by relative chironomid consumption, the most abundant prey resource, while fatty acid profiles were predominantly influenced by seasonal fluctuations in C22:6n-3 (DHA). Seasonal trends were evident in δ13C and δ15N; however, they varied within a narrow range of values. Our findings suggest that adult yellow perch in LECB showed little differentiation in resource use across space in 2014, but their diets and biochemical compositions varied seasonally.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2018.01.007","usgsCitation":"Hrycik, A.R., Collingsworth, P.D., Rogers, M.W., Guffey, S.C., and Hook, T.O., 2019, Seasonal trophic variation of yellow perch exceeds spatial variation in a large lake basin: Journal of Great Lakes Research, v. 44, no. 2, p. 299-310, https://doi.org/10.1016/j.jglr.2018.01.007.","productDescription":"12 p.","startPage":"299","endPage":"310","ipdsId":"IP-082056","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":365800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.69384765625,\n 41.80407814427234\n ],\n [\n -83.408203125,\n 41.343824581185686\n ],\n [\n -82.77099609375,\n 41.21172151054787\n ],\n [\n -81.7822265625,\n 41.1455697310095\n ],\n [\n -80.068359375,\n 41.95131994679697\n ],\n [\n -78.837890625,\n 42.65012181368022\n ],\n [\n -78.68408203124999,\n 43.03677585761058\n ],\n [\n -80.771484375,\n 42.85985981506279\n ],\n [\n -83.03466796874999,\n 42.17968819665961\n ],\n [\n -83.69384765625,\n 41.80407814427234\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hrycik, Allison R. 0000-0002-0870-3398","orcid":"https://orcid.org/0000-0002-0870-3398","contributorId":217379,"corporation":false,"usgs":false,"family":"Hrycik","given":"Allison","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":766675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collingsworth, Paris D.","contributorId":145526,"corporation":false,"usgs":false,"family":"Collingsworth","given":"Paris","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":766676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":766551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guffey, Samuel C.","contributorId":217380,"corporation":false,"usgs":false,"family":"Guffey","given":"Samuel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":766677,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hook, Tomas O.","contributorId":150480,"corporation":false,"usgs":false,"family":"Hook","given":"Tomas","email":"","middleInitial":"O.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":766678,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215340,"text":"70215340 - 2019 - Construction of probabilistic event trees for eruption forecasting at Sinabung volcano, Indonesia 2013–14","interactions":[],"lastModifiedDate":"2020-10-15T19:27:16.575269","indexId":"70215340","displayToPublicDate":"2018-02-08T13:57:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Construction of probabilistic event trees for eruption forecasting at Sinabung volcano, Indonesia 2013–14","docAbstract":"Eruptions of Sinabung volcano, Indonesia have been ongoing since 2013. Since that time, the character of eruptions has changed, from phreatic to phreatomagmatic to magmatic explosive eruptions, and from production of a lava dome that collapsed to a subsequent thick lava flow that slowly ceased to be active, and later, to a new lava dome. As the eruption progressed, event trees were constructed to forecast eruptive behavior six times, with forecast windows that ranged from 2 weeks to 1 year: November 7–10, December 12–14, and December 27, 2013; and January 9–10, May 13, and October 7, 2014. These event trees were successful in helping to frame the forecast scenarios, to collate current monitoring information, and to document outstanding questions and unknowns. The highest probability forecasts closely matched outcomes of eruption size (including extrusion of the first dome), production of pyroclastic density currents, and pyroclastic density current runout distances. Events assigned low probabilities also occurred, including total collapse of the lava dome in January 2014 and production of a small blast pyroclastic density current in February 2014.
Accurate assessment of abundance forms a central challenge in population ecology and wildlife management. Many statistical techniques have been developed to estimate population sizes because populations change over time and space and to correct for the bias resulting from animals that are present in a study area but not observed. The mobility of individuals makes it difficult to design sampling procedures that account for movement into and out of areas with fixed jurisdictional boundaries. Aerial surveys are the gold standard used to obtain data of large mobile species in geographic regions with harsh terrain, but these surveys can be prohibitively expensive and dangerous. Estimating abundance with ground‐based census methods have practical advantages, but it can be difficult to simultaneously account for temporary emigration and observer error to avoid biased results. Contemporary research in population ecology increasingly relies on telemetry observations of the states and locations of individuals to gain insight on vital rates, animal movements, and population abundance. Analytical models that use observations of movements to improve estimates of abundance have not been developed. Here we build upon existing multi‐state mark–recapture methods using a hierarchical N‐mixture model with multiple sources of data, including telemetry data on locations of individuals, to improve estimates of population sizes. We used a state‐space approach to model animal movements to approximate the number of marked animals present within the study area at any observation period, thereby accounting for a frequently changing number of marked individuals. We illustrate the approach using data on a population of elk (Cervus elaphus nelsoni) in Northern Colorado, USA. We demonstrate substantial improvement compared to existing abundance estimation methods and corroborate our results from the ground based surveys with estimates from aerial surveys during the same seasons. We develop a hierarchical Bayesian N‐mixture model using multiple sources of data on abundance, movement and survival to estimate the population size of a mobile species that uses remote conservation areas. The model improves accuracy of inference relative to previous methods for estimating abundance of open populations.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1692","usgsCitation":"Ketz, A.C., Johnson, T.L., Monello, R.J., Mack, J.A., George, J.L., Hooten, M., Kraft, B.R., Wild, M.A., and Hobbs, N.T., 2019, Estimating abundance of an open population with an N-mixture model using auxiliary data on animal movements: Ecological Applications, v. 28, no. 3, p. 816-825, https://doi.org/10.1002/eap.1692.","productDescription":"10 p.","startPage":"816","endPage":"825","ipdsId":"IP-082132","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":365802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Ketz, Alison C.","contributorId":217310,"corporation":false,"usgs":false,"family":"Ketz","given":"Alison","email":"","middleInitial":"C.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":766559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Therese L.","contributorId":217311,"corporation":false,"usgs":false,"family":"Johnson","given":"Therese","email":"","middleInitial":"L.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":766560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monello, Ryan J.","contributorId":217312,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":766561,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mack, John A.","contributorId":217313,"corporation":false,"usgs":false,"family":"Mack","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":766562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"George, Janet L.","contributorId":217314,"corporation":false,"usgs":false,"family":"George","given":"Janet","email":"","middleInitial":"L.","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":766563,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":766558,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kraft, Benjamin R.","contributorId":217315,"corporation":false,"usgs":false,"family":"Kraft","given":"Benjamin","email":"","middleInitial":"R.","affiliations":[{"id":36246,"text":"CPW","active":true,"usgs":false}],"preferred":false,"id":766564,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wild, Margaret A.","contributorId":217316,"corporation":false,"usgs":false,"family":"Wild","given":"Margaret","email":"","middleInitial":"A.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":766565,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hobbs, N. Thompson","contributorId":217317,"corporation":false,"usgs":false,"family":"Hobbs","given":"N.","email":"","middleInitial":"Thompson","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":766566,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70212305,"text":"70212305 - 2019 - Bright carbonate surfaces on Ceres as remnants of salt-rich water fountains","interactions":[],"lastModifiedDate":"2020-08-14T15:10:21.219148","indexId":"70212305","displayToPublicDate":"2018-02-02T10:07:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Bright carbonate surfaces on Ceres as remnants of salt-rich water fountains","docAbstract":"Vinalia and Cerealia Faculae are bright and salt-rich localized areas in Occator crater on Ceres. The predominance of the near-infrared signature of sodium carbonate on these surfaces suggests their original material was a brine. Here we analyze Dawn Framing Camera's images and characterize the surfaces as composed of a central structure, either a possible depression (Vinalia) or a central dome (Cerealia), and a discontinuous mantling. We consider three materials enabling the ascent and formation of the faculae: ice ascent with sublimation and carbonate particle lofting, pure gas emission entraining carbonate particles, and brine extrusion. We find that a mechanism explaining the entire range of morphologies, topographies, as well as the common composition of the deposits is brine fountaining. This process consists of briny liquid extrusion, followed by flash freezing of carbonate and ice particles, particle fallback, and sublimation. Subsequent increase in briny liquid viscosity leads to doming. Dawn observations did not detect currently active water plumes, indicating the frequency of such extrusions is longer than years.","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2018.01.022","usgsCitation":"Ruesch, O., Quick, L., Landis, M.E., Sori, M., Cadek, O., Broz, P., Otto, K., Bland, M.T., Byrne, S., Castillo-Rogez, J., Hiesinger, H., Jaumann, R., Krohn, K., McFadden, L., Nathues, A., Neesemann, A., Preusker, F., Roatsch, T., Schenk, P., Scully, J.E., Sykes, M., Williams, D., Raymond, C., and Russell., C., 2019, Bright carbonate surfaces on Ceres as remnants of salt-rich water fountains: Icarus, v. 320, p. 39-48, https://doi.org/10.1016/j.icarus.2018.01.022.","productDescription":"10 p.","startPage":"39","endPage":"48","ipdsId":"IP-090459","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":377525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ceres","volume":"320","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruesch, Ottavian","contributorId":238472,"corporation":false,"usgs":false,"family":"Ruesch","given":"Ottavian","email":"","affiliations":[{"id":47713,"text":"NASA Goddard Space Flight Center / ESTEC, ESA","active":true,"usgs":false}],"preferred":false,"id":796256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quick, Lynnae","contributorId":238473,"corporation":false,"usgs":false,"family":"Quick","given":"Lynnae","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":796257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landis, Margaret Evelyn 0000-0001-7321-2272","orcid":"https://orcid.org/0000-0001-7321-2272","contributorId":238475,"corporation":false,"usgs":false,"family":"Landis","given":"Margaret","email":"","middleInitial":"Evelyn","affiliations":[],"preferred":false,"id":796258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sori, M.M.","contributorId":238476,"corporation":false,"usgs":false,"family":"Sori","given":"M.M.","email":"","affiliations":[],"preferred":false,"id":796259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cadek, O.","contributorId":238478,"corporation":false,"usgs":false,"family":"Cadek","given":"O.","email":"","affiliations":[],"preferred":false,"id":796260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Broz, P.","contributorId":238479,"corporation":false,"usgs":false,"family":"Broz","given":"P.","email":"","affiliations":[],"preferred":false,"id":796261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Otto, K.A.","contributorId":238480,"corporation":false,"usgs":false,"family":"Otto","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":796262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":796263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Byrne, S.","contributorId":238482,"corporation":false,"usgs":false,"family":"Byrne","given":"S.","affiliations":[],"preferred":false,"id":796264,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Castillo-Rogez, J.C.","contributorId":238484,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":796265,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hiesinger, H.","contributorId":238485,"corporation":false,"usgs":false,"family":"Hiesinger","given":"H.","affiliations":[],"preferred":false,"id":796266,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaumann, R.","contributorId":238487,"corporation":false,"usgs":false,"family":"Jaumann","given":"R.","affiliations":[],"preferred":false,"id":796267,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Krohn, K.","contributorId":238488,"corporation":false,"usgs":false,"family":"Krohn","given":"K.","email":"","affiliations":[],"preferred":false,"id":796268,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McFadden, L.A.","contributorId":238489,"corporation":false,"usgs":false,"family":"McFadden","given":"L.A.","affiliations":[],"preferred":false,"id":796269,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Nathues, A.","contributorId":238491,"corporation":false,"usgs":false,"family":"Nathues","given":"A.","affiliations":[],"preferred":false,"id":796270,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Neesemann, A.","contributorId":177383,"corporation":false,"usgs":false,"family":"Neesemann","given":"A.","email":"","affiliations":[],"preferred":false,"id":796271,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Preusker, F.","contributorId":238492,"corporation":false,"usgs":false,"family":"Preusker","given":"F.","affiliations":[],"preferred":false,"id":796272,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Roatsch, T.","contributorId":238493,"corporation":false,"usgs":false,"family":"Roatsch","given":"T.","affiliations":[],"preferred":false,"id":796273,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schenk, P.M.","contributorId":238495,"corporation":false,"usgs":false,"family":"Schenk","given":"P.M.","affiliations":[],"preferred":false,"id":796274,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Scully, J. E. C.","contributorId":238497,"corporation":false,"usgs":false,"family":"Scully","given":"J.","middleInitial":"E. C.","affiliations":[],"preferred":false,"id":796275,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Sykes, M.V.","contributorId":238498,"corporation":false,"usgs":false,"family":"Sykes","given":"M.V.","email":"","affiliations":[],"preferred":false,"id":796276,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Williams, D.A.","contributorId":98048,"corporation":false,"usgs":false,"family":"Williams","given":"D.A.","email":"","affiliations":[{"id":7114,"text":"Arizona State Unviersity","active":true,"usgs":false}],"preferred":false,"id":796277,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Raymond, C.A.","contributorId":50301,"corporation":false,"usgs":false,"family":"Raymond","given":"C.A.","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":796278,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Russell., C.T.","contributorId":238501,"corporation":false,"usgs":false,"family":"Russell.","given":"C.T.","email":"","affiliations":[],"preferred":false,"id":796279,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70204674,"text":"70204674 - 2019 - Phenotypic plasticity and climate change: Can polar bears respond to longer Arctic summers with an adaptive fast?","interactions":[],"lastModifiedDate":"2019-08-13T07:07:15","indexId":"70204674","displayToPublicDate":"2018-02-01T12:47:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Phenotypic plasticity and climate change: Can polar bears respond to longer Arctic summers with an adaptive fast?","docAbstract":"Plasticity in the physiological and behavioural responses of animals to prolonged food shortages may determine the persistence of species under climate warming. This is particularly applicable for species that can “adaptively fast” by conserving protein to protect organ function while catabolizing endogenous tissues. Some Ursids, including polar bears (Ursus maritimus), adaptively fast during winter hibernation—and it has been suggested that polar bears also employ this strategy during summer. We captured 57 adult female polar bears in the Southern Beaufort Sea (SBS) during summer 2008 and 2009 and measured blood variables that indicate feeding, regular fasting, and adaptive fasting. We also assessed tissue δ13C and δ15N to infer diet, and body condition via mass and length. We found that bears on shore maintained lipid and protein stores by scavenging on bowhead whale (Balaena mysticetus) carcasses from human harvest, while those that followed the retreating sea ice beyond the continental shelf were food deprived. They had low ratios of blood urea to creatinine (U:C), normally associated with adaptive fasting. However, they also exhibited low albumin and glucose (indicative of protein loss) and elevated alanine aminotransferase and ghrelin (which fall during adaptive fasting). Thus, the ~ 70% of the SBS subpopulation that spends summer on the ice experiences more of a regular, rather than adaptive, fast. This fast will lengthen as summer ice declines. The resulting protein loss prior to winter could be a mechanism driving the reported correlation between summer ice and polar bear reproduction and survival in the SBS.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-017-4023-0","usgsCitation":"Whiteman, J.P., Harlow, H.J., Durner, G.M., Regher, E.V., Amstrup, S.C., and Ben-David, M., 2019, Phenotypic plasticity and climate change: Can polar bears respond to longer Arctic summers with an adaptive fast?: Oecologia, v. 186, no. 2, p. 369-381, https://doi.org/10.1007/s00442-017-4023-0.","productDescription":"13 p.","startPage":"369","endPage":"381","ipdsId":"IP-073266","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":366390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"186","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Whiteman, John P.","contributorId":194427,"corporation":false,"usgs":false,"family":"Whiteman","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":768025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harlow, Henry J.","contributorId":195844,"corporation":false,"usgs":false,"family":"Harlow","given":"Henry","email":"","middleInitial":"J.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":768026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":768024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Regher, Eric V","contributorId":140838,"corporation":false,"usgs":false,"family":"Regher","given":"Eric","email":"","middleInitial":"V","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":768027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":768028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ben-David, Merav","contributorId":190901,"corporation":false,"usgs":false,"family":"Ben-David","given":"Merav","email":"","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":768029,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194829,"text":"sir20185003 - 2019 - Hydrogeologic controls and geochemical indicators of groundwater movement in the Niles Cone and southern East Bay Plain groundwater subbasins, Alameda County, California","interactions":[],"lastModifiedDate":"2019-02-04T09:40:36","indexId":"sir20185003","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2019","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":"2018-5003","title":"Hydrogeologic controls and geochemical indicators of groundwater movement in the Niles Cone and southern East Bay Plain groundwater subbasins, Alameda County, California","docAbstract":"Beginning in the 1970s, Alameda County Water District began infiltrating imported water through ponds in repurposed gravel quarries at the Quarry Lakes Regional Park, in the Niles Cone groundwater subbasin, to recharge groundwater and to minimize intrusion of saline, San Francisco Bay water into freshwater aquifers. Hydraulic connection between distinct aquifers underlying Quarry Lakes allows water to recharge the upper aquifer system to depths of 400 feet below land surface, and the Deep aquifer to depths of more than 650 feet. Previous studies of the Niles Cone and southern East Bay Plain groundwater subbasins suggested that these two subbasins may be hydraulically connected. Characterization of storage capacities and hydraulic properties of the complex aquifers and the structural and stratigraphic controls on groundwater movement aids in optimal storage and recovery of recharged water and provides information on the ability of aquifers shared by different water management agencies to fulfill competing storage and extraction demands. The movement of recharge water through the Niles Cone groundwater subbasin from Quarry Lakes and the possible hydraulic connection between the Niles Cone and the southern East Bay Plain groundwater subbasins were investigated using interferometric synthetic aperture radar (InSAR), water-chemistry, and isotopic data, including tritium/helium-3, helium-4, and carbon-14 age-dating techniques.
InSAR data collected during refilling of the Quarry Lakes recharge ponds show corresponding ground-surface displacement. Maximum uplift was about 0.8 inches, reasonable for elastic expansion of sedimentary materials experiencing an increase in hydraulic head that resulted from pond refilling. Sodium concentrations increase while calcium and magnesium concentrations in groundwater decrease along groundwater flowpaths from the Niles Cone groundwater subbasin through the Deep aquifer to the northwest toward the southern East Bay Plain groundwater subbasin. Residual effects of pre-1970s intrusion of saline water from San Francisco Bay, including high chloride concentrations in groundwater, are evident in parts of the Niles Cone subbasin. Noble gas recharge temperatures indicate two primary recharge sources (Quarry Lakes and Alameda Creek) in the Niles Cone groundwater subbasin. Although recharge at Quarry Lakes affects hydraulic heads as far as the transition zone between the Niles Cone and East Bay Plain groundwater subbasins (about 5 miles), the effect of recharged water on water quality is only apparent in wells near (less than 2 miles) recharge sources. Groundwater chemistry from upper aquifer system wells near Quarry Lakes showed an evaporated signal (less negative oxygen and hydrogen isotopic values) relative to surrounding groundwater and a tritium concentration (2 tritium units) consistent with recently recharged water from a surface-water impoundment.
Uncorrected carbon-14 activities measured in water sampled from wells in the Niles Cone groundwater subbasin range from 16 to 100 percent modern carbon (pmC). The geochemical reaction modeling software NETPATH was used to interpret carbon-14 ages along a flowpath from Quarry Lakes toward the East Bay Plain groundwater subbasin. Model results indicate that changes in groundwater chemistry are controlled by cation exchange on clay minerals and weathering of primary silicate minerals. Old groundwater (lower carbon-14 activities) is characterized by high dissolved silica and pH. Interpreted carbon-14 ages ranged from 830 to more than 7,000 years before present and are less than helium-4 ages that range from 2,000 to greater than 11,000 years before present. The average horizontal groundwater velocity along the studied flowpath, as calculated using interpreted carbon-14 ages, through the Deep aquifer of the Niles Cone groundwater subbasin is between 3 and 12 feet per year. The groundwater velocity decreases near the boundary of the transition zone to the southern East Bay Plain groundwater subbasin to about 0.5 feet per year. These changes may result from water recharged from different sources converging in flowpaths north of the transition zone, or a boundary to flow between the Niles Cone and southern East Bay Plain groundwater subbasins, likely owing to changes in lithology caused by depositional patterns.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185003","collaboration":"Prepared in cooperation with the East Bay Municipal Utility District, City of Hayward, and Alameda County Water District","usgsCitation":"Teague, Nick, Izbicki, John, Borchers, Jim, Kulongoski, Justin, and Jurgens, Bryant, 2018, Hydrogeologic controls and geochemical indicators of groundwater movement in the Niles Cone and southern East Bay Plain groundwater subbasins, Alameda County, California (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Report 2018–5003, 62 p., https://doi.org/10.3133/sir20185003.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-043410","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":360934,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5003/versionHist.txt"},{"id":351228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5003/coverthb.jpg"},{"id":351229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5003/sir20185003_v1.1.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5003"}],"country":"United States","state":"California","county":"Alameda County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3333,\n 37.5\n ],\n [\n -121.9167,\n 37.5\n ],\n [\n -121.9167,\n 37.8333\n ],\n [\n -122.3333,\n 37.8333\n ],\n [\n -122.3333,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Ver. 1.0: February 2018; Ver. 1.1: February 2019","contact":"Director,
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
We investigated the direct and indirect influence of tides on net ecosystem exchange (NEE) of carbon dioxide (CO2) in a temperate brackish tidal marsh. NEE displayed a tidally driven pattern with obvious characteristics at the multiday scale, with greater net CO2uptake during spring tides than neap tides. Based on the relative mutual information between NEE and biophysical variables, this was driven by a combination of higher water table depth (WTD), cooler air temperature, and lower vapor pressure deficit (VPD) during spring tides relative to neap tides, as the fortnightly tidal cycle not only influenced water levels but also strongly modulated water and air temperature and VPD. Tides also influenced NEE at shorter timescales, with a reduction in nighttime fluxes during growing season spring tides when the higher of the two semidiurnal tides caused inundation at the site. WTD significantly influenced ecosystem respiration (Reco), with lower Reco during spring tides than neap tides. While WTD did not appear to affect ecosystem photosynthesis (gross ecosystem production, GPP) directly, the impact of tides on temperature and VPD influenced GPP, with higher daily light‐use efficiency and photosynthetic activity during spring tides than neap tides when temperature and VPD were lower. The strong direct and indirect influence of tides on NEE across the diel and multiday timescales has important implications for modeling NEE in tidal wetlands and can help inform the timing and frequency of chamber measurements as annual or seasonal net CO2 uptake may be underestimated if measurements are only taken during nonflooded periods.
","language":"English","publisher":"Wiley","doi":"10.1002/2017JG004048","usgsCitation":"Knox, S., Windham-Myers, L., Frank Anderson, Sturtevant, C., and Bergamaschi, B.A., 2019, Direct and indirect effects of tides on ecosystem-scale CO2 exchange in a brackish tidal marsh in Northern California: Journal of Geophysical Research: Biogeosciences, v. 123, no. 3, p. 787-806, https://doi.org/10.1002/2017JG004048.","productDescription":"20 p.","startPage":"787","endPage":"806","ipdsId":"IP-094185","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":365630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay National Estuarine Research Reserve, Suisun Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.2235870361328,\n 38.065932950547484\n ],\n [\n -122.22427368164064,\n 38.05944549633448\n ],\n [\n -122.1906280517578,\n 38.053498158026564\n ],\n [\n -122.17758178710939,\n 38.03619406237626\n ],\n [\n -122.15217590332031,\n 38.02267239225365\n ],\n [\n -122.13294982910156,\n 38.028622234587964\n ],\n [\n -122.11509704589845,\n 38.038357297980816\n ],\n [\n -122.09587097167967,\n 38.04322434446539\n ],\n [\n -122.08694458007812,\n 38.04755033643351\n ],\n [\n -122.0684051513672,\n 38.05403884511629\n ],\n [\n -122.04574584960938,\n 38.05566088242076\n ],\n [\n -122.02583312988281,\n 38.058364198044636\n ],\n [\n -121.99493408203125,\n 38.05403884511629\n ],\n [\n -121.96609497070312,\n 38.04755033643351\n ],\n [\n -121.94892883300781,\n 38.050794662666895\n ],\n [\n -121.93450927734375,\n 38.05457952821193\n ],\n [\n -121.9207763671875,\n 38.059986139487975\n ],\n [\n -121.91734313964844,\n 38.07025760046315\n ],\n [\n -121.91116333007811,\n 38.067554724225275\n ],\n [\n -121.90910339355467,\n 38.077284611299554\n ],\n [\n -121.91665649414062,\n 38.08268954483802\n ],\n [\n -121.9379425048828,\n 38.07944663265489\n ],\n [\n -121.95236206054688,\n 38.077284611299554\n ],\n [\n -121.96060180664062,\n 38.07674409597339\n ],\n [\n -121.97158813476561,\n 38.07458199472\n ],\n [\n -121.97845458984375,\n 38.07998712800633\n ],\n [\n -122.00042724609374,\n 38.08647276060778\n ],\n [\n -122.02308654785156,\n 38.09674050228651\n ],\n [\n -122.00111389160155,\n 38.10268432504872\n ],\n [\n -121.98875427246092,\n 38.11024849111732\n ],\n [\n -121.9921875,\n 38.131856078273124\n ],\n [\n -122.00935363769531,\n 38.1399572748485\n ],\n [\n -122.03407287597655,\n 38.13725697591337\n ],\n [\n -122.06085205078125,\n 38.135096664819784\n ],\n [\n -122.06634521484374,\n 38.12159327165922\n ],\n [\n -122.06634521484374,\n 38.109708219514644\n ],\n [\n -122.11990356445312,\n 38.05944549633448\n ],\n [\n -122.13020324707033,\n 38.04538737239996\n ],\n [\n -122.135009765625,\n 38.04268357749736\n ],\n [\n -122.15011596679688,\n 38.04322434446539\n ],\n [\n -122.16110229492186,\n 38.043765107439675\n ],\n [\n -122.17071533203125,\n 38.05403884511629\n ],\n [\n -122.17483520507811,\n 38.05944549633448\n ],\n [\n -122.1844482421875,\n 38.065932950547484\n ],\n [\n -122.18994140624999,\n 38.069176461951876\n ],\n [\n -122.1954345703125,\n 38.06052677864718\n ],\n [\n -122.20573425292967,\n 38.06809530746208\n ],\n [\n -122.2235870361328,\n 38.065932950547484\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Knox, Sara 0000-0003-2255-5835","orcid":"https://orcid.org/0000-0003-2255-5835","contributorId":216996,"corporation":false,"usgs":false,"family":"Knox","given":"Sara","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":766227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Windham-Myers, Lisamarie 0000-0003-0281-9581 lwindham-myers@usgs.gov","orcid":"https://orcid.org/0000-0003-0281-9581","contributorId":2449,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - 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2019 - Isotopic evidence that nitrogen enrichment intensifies nitrogen losses to the atmosphere from subtropical mangroves","interactions":[],"lastModifiedDate":"2019-08-15T11:54:06","indexId":"70202922","displayToPublicDate":"2018-01-08T11:31:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1478,"text":"Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Isotopic evidence that nitrogen enrichment intensifies nitrogen losses to the atmosphere from subtropical mangroves","docAbstract":"Nitrogen (N) enrichment can have large effects on mangroves’ capacity to provide critical ecosystem services by affecting fundamental functions such as N cycling and primary productivity. However, our understanding of excess N input effects on N cycling in mangroves remains quite limited. To advance our understanding of how N enrichment via water or air pollution affects mangroves, we evaluated whether increasing N inputs would decrease biological N fixation (BNF), but intensify N dynamics and N losses to the atmosphere in these systems. We measured N concentrations in sediment and vegetation, rates of BNF in sediment and litter, and net sediment ammonification and nitrification rates. We also evaluated long-term integrated N dynamics and N losses to the atmosphere using the natural abundance of N stable isotopes (δ15N) in the sediment–plant system and in estuarine water. We performed these analyses at non-N-enriched and N-enriched (that is, polluted) fringe and basin mangroves in southeastern Brazil. The δ15N in the sediment–plant system was higher at N-enriched than non-N-enriched fringe sites, indicating increased N losses to the atmosphere from N-enriched sites. However, N concentrations in sediment and vegetation were similar or lower at N-enriched relative to non-N-enriched sites. BNF and net ammonification and nitrification rates were also similar between N-enriched and non-N-enriched sites. Excess N inputs intensified N losses to the atmosphere from mangroves, but N pools, BNF, and net ammonification and nitrification rates were not affected by N enrichment, likely because excess N was quickly lost from the system by direct denitrification and volatilization.
","language":"English","publisher":"Springer","doi":"10.1007/s10021-018-0327-0","usgsCitation":"Reis, C.R., Reed, S.C., Oliveira, R.S., and Nardoto, G.B., 2019, Isotopic evidence that nitrogen enrichment intensifies nitrogen losses to the atmosphere from subtropical mangroves: Ecosystems, v. 22, no. 5, p. 1126-1144, https://doi.org/10.1007/s10021-018-0327-0.","productDescription":"19 p.","startPage":"1126","endPage":"1144","ipdsId":"IP-102196","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":362799,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","state":"São Paulo","otherGeospatial":"Estuarine Lagunar Complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -47.471923828125,\n -24.705043861733333\n ],\n 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]\n ]\n }\n }\n ]\n}","volume":"22","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Reis, Carla Roberta Goncalves","contributorId":214647,"corporation":false,"usgs":false,"family":"Reis","given":"Carla","email":"","middleInitial":"Roberta Goncalves","affiliations":[{"id":39103,"text":"Programa de Pós-Graduação em Ecologia, Instituto de Ciências Biológicas, Campus Darcy Ribeiro, Universidade de Brasília, 70910-900, Brasília, Distrito Federal, Brazil","active":true,"usgs":false}],"preferred":false,"id":760483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":760482,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oliveira, Rafael Silva","contributorId":214648,"corporation":false,"usgs":false,"family":"Oliveira","given":"Rafael","email":"","middleInitial":"Silva","affiliations":[{"id":39104,"text":"Departamento de Biologia Vegetal, Rua Monteiro Lobato 255, Cidade Universitária Zeferino Vaz, Universidade Estadual de Campinas, 13083-862, Barão Geraldo, Campinas, São Paulo, Brazil","active":true,"usgs":false}],"preferred":false,"id":760484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nardoto, Gabriela Bielefeld","contributorId":214649,"corporation":false,"usgs":false,"family":"Nardoto","given":"Gabriela","email":"","middleInitial":"Bielefeld","affiliations":[{"id":39103,"text":"Programa de Pós-Graduação em Ecologia, Instituto de Ciências Biológicas, Campus Darcy Ribeiro, Universidade de Brasília, 70910-900, Brasília, Distrito Federal, Brazil","active":true,"usgs":false}],"preferred":false,"id":760485,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204760,"text":"70204760 - 2019 - Understanding the genetic characteristics of Wild Brook Trout populations in North Carolina thanks to the guidance of Dr. Tim King","interactions":[],"lastModifiedDate":"2019-09-03T08:16:10","indexId":"70204760","displayToPublicDate":"2017-12-31T12:46:33","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Understanding the genetic characteristics of Wild Brook Trout populations in North Carolina thanks to the guidance of Dr. Tim King","docAbstract":"We genotyped 7,588 brook trout representing 406 collections from across the State of North Carolina (Figure 1) at 12 microsatellite loci (King et al. 2012). The vast majority of
collections appeared to represent single populations, based on general conformance to HardyWeinberg equilibrium and limited evidence for linkage-disequilibrium. Allelic diversity was low to moderate relative to Brook Trout Salvelinus fontinalis populations endemic to higher latitudes. Effective population sizes varied widely among populations, but were often very small and indicate that many populations are at risk of losing diversity through genetic drift. Remarkable levels of genetic differentiation exist among populations, which suggests that little, if any, gene flow occurs among most populations. Analysis of molecular variance (AMOVA) revealed that a substantial portion of the observed genetic variation was attributed to differences among patches (44.8%), and there was some variation (11.2%) even among collections within a single patch. These results, taken in conjunction with high levels of genetic differentiation among populations, suggest that the fundamental unit of management for Brook Trout should be the
population. Interestingly, despite extensive stocking across the state, the vast majority of wild populations show limited evidence of introgression by northern origin hatchery strains. These results represent a valuable baseline for management and restoration efforts, and can be used to (a) select suitable donor streams for translocation efforts, (b) identify streams with low effective population sizes that may be vulnerable to extirpation, and (c) target stocking efforts into watersheds where extensive introgression has already occurred. All data associated with this manuscript has been publicly released (Kazyak et al. 2017).
Of the 24 species in the Auk (or Alcidae) family of seabirds living in the northern hemisphere, 22 reside within the North Pacific Ocean. These “penguins of the north” use their small wings to “fly” underwater, some to more than 200 meters, where they catch and eat a variety of small fish and invertebrates. In terms of sheer numbers (>65 million) and food consumption, the Auks dominate seabird communities on our continental shelves and they serve as indicators of the health of our ocean. If Auk populations are not all thriving, then we should be concerned about the status of the oceans, plankton and fish that normally sustain them. A few Auk “tribes” genera) are abundant and widespread (such as Uria murres and Aethia auklets), and some are rare and isolated such as Synthliboramphus murrelets, including the Japanese “Crested” Murrelet). Only 8 species of Auk breed in Japan, including species that have either widespread or isolated populations in the North Pacific. During the past century, most of these Auks have declined dramatically in Japan from many causes, including the introduction of predatory rats and cats to breeding islands, bycatch in fishing nets, alteration of food supplies by fishing and climate change, oil spills, and destruction of seabird nesting habitats. Widespread species such as the Common Murre and Tufted Puffin were once common in Japan but now breed in low numbers at only a few locations. Probably common in the past, small numbers of the widespread Ancient Murrelet were recently re-discovered breeding at Teuri Island, which is also home to the world’s largest colony of Rhinoceros Auklet, another widespread species. Though common throughout the North Pacific, Pigeon Guillemots, breed only in the southern Kuril Islands. Their population status is unknown, but they were never considered common in Japan. In contrast, Spectacled Guillemots are an example of an uncommon and isolated population of Auk. They nest along coasts of the Sea of Okhotsk and Sea of Japan, and populations have declined in recent decades. The Long-billed Murrelet has a similar distribution to Spectacled Guillemot, and once bred in Hokkaido, but populations appear to have been extirpated. The Japanese Murrelet has a very small world population, and breeds at only a few locations in southern Japan and the Republic of Korea. The international community of research and conservation biologists is greatly concerned about the ability of this species—probably the rarest of all Auks in the world— to maintain its population size. Owing to its small size and high metabolic demand, this species is especially vulnerable to any stress that increases its food requirements such as changing fish stocks, disturbance on feeding or wintering grounds, or changing ocean climate. Immediate management actions are needed to preserve Japanese Murrelets and other Auks in Japan, by such means as eradicating rats and cats on breeding islands, altering fishing gear to minimize bycatch, and reducing human disturbance to nesting habitats. More research and monitoring of Auk populations in Japan is needed to track population trends, and further identify factors responsible for declines. Interaction between governments and biologists at regional and international levels will be mutually beneficial as we all strive to conserve precious resources and biodiversity in the northwest Pacific, and particularly the Japanese islands.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Status and Monitoring of Rare and Threatened Japanese Crested Murrelet","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Marine Bird Restoration Group","usgsCitation":"Piatt, J.F., Nelson, S., and Carter, H.R., 2019, Monitoring and conservation of Japanese Murrelets and related seabirds in Japan, in Status and Monitoring of Rare and Threatened Japanese Crested Murrelet, p. 33-42.","startPage":"33","endPage":"42","ipdsId":"IP-090741","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":365028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365027,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://marinebird-restorationgroup.jimdo.com/app/download/11136230791/4_p33-42_Piatt.pdf?t=1510725322"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":761700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, S Kim","contributorId":205442,"corporation":false,"usgs":false,"family":"Nelson","given":"S Kim","affiliations":[{"id":37105,"text":"Oregon State Unversity","active":true,"usgs":false}],"preferred":false,"id":765061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Harry R.","contributorId":216125,"corporation":false,"usgs":false,"family":"Carter","given":"Harry","email":"","middleInitial":"R.","affiliations":[{"id":39369,"text":"Carter Biological Consulting","active":true,"usgs":false}],"preferred":false,"id":765062,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227758,"text":"70227758 - 2019 - Remaining populations of an upland stream fish persist in refugia defined by habitat features at multiple scales","interactions":[],"lastModifiedDate":"2022-01-28T13:29:15.856931","indexId":"70227758","displayToPublicDate":"2017-12-07T07:27:14","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Remaining populations of an upland stream fish persist in refugia defined by habitat features at multiple scales","docAbstract":"Conserving stream biota could require strategies that preserve habitats conveying resistance to ecological impacts of changing land use and climate. Retrospective analyses of species’ responses to anthropogenic disturbances can inform such strategies. We developed a hierarchical framework to contrast environmental conditions underlying persistence versus extirpation of an imperilled stream fish, Candy Darter (Etheostoma osburni), over decades of changing land use. The decline of E. osburni may broadly represent the challenge of conserving sensitive freshwater species in intensively used upland environments.
New River drainage, Appalachian Mountains, USA.
We surveyed fish and habitat in historically occupied sites to identify population refugia, and used multivariate and spatial analyses to address three questions: (a) what are the environmental correlates of refugia? (b) are the pathways by which land use impacts instream habitat constrained by catchment- and/or segment-scale features? and (c) are E. osburni distributional dynamics spatially structured and explained by fine sediment and warm stream temperatures?
We confirmed a recently localized distribution similar to other upland species, marked by at least seven extirpations from streams throughout E. osburni's southern range. Catchment-scale features primarily constrained land use and finer-scale habitat, leading to either extirpations or population-supporting refugia defined by features at multiple scales. Refugium habitats contained cooler temperatures and less fine sediment. Rare mismatches between persistence and habitat suitability were explained by network location, suggesting unmeasured environmental gradients and/or dispersal contributed to distributional dynamics.
We provided insight at multiple spatial scales into how aquatic species’ distributions become fragmented and localized. Our results demonstrate that natural landscape heterogeneity imparts spatially variable resistance of sensitive species to intensive land uses. By recognizing the scale-specific features that buffer populations from extirpation, conservation strategies could be tailored to protect naturally occurring refugium habitats and focus restoration in systems where such habitats are broadly lacking.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12866","usgsCitation":"Dunn, C., and Angermeier, P.L., 2019, Remaining populations of an upland stream fish persist in refugia defined by habitat features at multiple scales: Diversity and Distributions, v. 25, no. 3, p. 385-399, https://doi.org/10.1111/ddi.12866.","productDescription":"15 p.","startPage":"385","endPage":"399","ipdsId":"IP-090855","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468135,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12866","text":"Publisher Index Page"},{"id":395042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.123046875,\n 37.28279464911045\n ],\n [\n -78.20068359374999,\n 37.28279464911045\n ],\n [\n -78.20068359374999,\n 39.757879992021756\n ],\n [\n -81.123046875,\n 39.757879992021756\n ],\n [\n -81.123046875,\n 37.28279464911045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"3","noUsgsAuthors":false,"publicationDate":"2018-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Dunn, Corey G.","contributorId":272531,"corporation":false,"usgs":false,"family":"Dunn","given":"Corey G.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":832056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832055,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190431,"text":"sir20175093 - 2019 - Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam","interactions":[],"lastModifiedDate":"2019-12-30T14:46:50","indexId":"sir20175093","displayToPublicDate":"2017-12-01T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5093","title":"Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam","docAbstract":"In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model.
Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River.
The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume.
In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas.
The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175093","collaboration":"Prepared in cooperation with the U.S. Department of Defense Strategic Environmental Research and Development Program (SERDP)","usgsCitation":"Rosa, S.N., and Hay, L.E., 2019, Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Report 2017–5093, 64 p., https://doi.org/10.3133/sir20175093.","productDescription":"Report: viii, 64 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-081743","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":349631,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5093/coverthb2.jpg"},{"id":349632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5093/sir20175093.pdf","text":"Report","size":"22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5093 v1.1"},{"id":361066,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2017/5093/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2017-5093 Version History"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.6240234375,\n 13.230587802102518\n ],\n [\n 144.96047973632812,\n 13.230587802102518\n ],\n [\n 144.96047973632812,\n 13.652659349024093\n ],\n [\n 144.6240234375,\n 13.652659349024093\n ],\n [\n 144.6240234375,\n 13.230587802102518\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 2017; Version 1.1: February 2019","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818