The ontogenetic diet shift to piscivory can be energetically beneficial for fish growth and allows larger, more energetically profitable prey to be consumed. A shift to piscivory may be easier for longer individuals within a cohort due to larger gape size, and an early shift is likely advantageous, potentially leading to increased growth rates and survival. Such length-dependent ontogenetic diet shifts may explain the intracohort variability in length that is common for age-0 walleye (Sander vitreus). The objectives of this study were to describe seasonal intracohort variability in length, identify the timing of the shift to piscivory and determine if the onset of piscivory was length-dependent in age-0 walleye. Walleye initially fed on zooplankton, but shifted to piscivory during July of 2010 and June of 2011. The onset of piscivory in age-0 walleye was associated with length-dependent differences during both years, in which longer individuals within the cohort became piscivorous earlier than shorter individuals within the same cohort. Intracohort variability in length was detected and increased postontogenetic diet shift. Age-0 walleye that experience a growth advantage could benefit from increased survival and feeding opportunities.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2018.1529637","usgsCitation":"Uphoff, C.S., Schoenebeck, C.W., Koupal, K., Pope, K.L., and Hoback, W., 2019, Age-0 walleye Sander vitreus display length-dependent diet shift to piscivory: Journal of Freshwater Ecology, v. 34, no. 1, p. 27-36, https://doi.org/10.1080/02705060.2018.1529637.","productDescription":"10 p.","startPage":"27","endPage":"36","ipdsId":"IP-069781","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467981,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2018.1529637","text":"Publisher Index Page"},{"id":394881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Harlan County Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.41047668457031,\n 40.01499435375046\n ],\n [\n -99.20036315917969,\n 40.01499435375046\n ],\n [\n -99.20036315917969,\n 40.116414757817246\n ],\n [\n -99.41047668457031,\n 40.116414757817246\n ],\n [\n -99.41047668457031,\n 40.01499435375046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Uphoff, C. S.","contributorId":272193,"corporation":false,"usgs":false,"family":"Uphoff","given":"C.","email":"","middleInitial":"S.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":831695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenebeck, C. W.","contributorId":272194,"corporation":false,"usgs":false,"family":"Schoenebeck","given":"C.","email":"","middleInitial":"W.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":831696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koupal, K. D.","contributorId":272195,"corporation":false,"usgs":false,"family":"Koupal","given":"K. D.","affiliations":[{"id":56368,"text":"Nebraska Game and Parks","active":true,"usgs":false}],"preferred":false,"id":831697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":831698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoback, W. W.","contributorId":272196,"corporation":false,"usgs":false,"family":"Hoback","given":"W. W.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":831699,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204097,"text":"70204097 - 2019 - Changes in the active, dead, and dormant microbial community structure across a Pleistocene permafrost chronosequence","interactions":[],"lastModifiedDate":"2019-07-05T14:57:57","indexId":"70204097","displayToPublicDate":"2019-01-25T16:26:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Changes in the active, dead, and dormant microbial community structure across a Pleistocene permafrost chronosequence","docAbstract":"Permafrost hosts a community of microorganisms that survive and reproduce for millennia despite extreme environmental conditions such as water stress, subzero temperatures, high salinity, and low nutrient availability. Many studies focused on permafrost microbial community composition use DNA-based methods such as metagenomic and 16S rRNA gene sequencing. However, these methods do not distinguish between active, dead, and dormant cells. This is of particular concern in ancient permafrost where constant subzero temperatures preserve DNA from dead organisms and dormancy may be a common survival strategy. To circumvent this we applied: (i) live/dead differential staining coupled with microscopy, (ii) endospore enrichment, and (iii) selective depletion of DNA from dead cells to permafrost microbial communities across a Pleistocene permafrost chronosequence (19 thousand years (K), 27K, and 33K). Cell counts and analysis of 16S rRNA gene amplicons from live, dead, and dormant cells revealed how communities differ between these pools, how they are influenced by soil physicochemical properties, and whether they change over geologic time. We found evidence that cells capable of forming endospores are not necessarily dormant and that members of class Bacilli were more likely to form endospores in response to long-term stressors associated with permafrost environmental conditions than members of Clostridia, which were more likely to persist as vegetative cells in our older samples. We also found that removing exogenous ‘relic’ DNA preserved within permafrost did not significantly alter microbial community composition. These results link the live, dead, and dormant microbial communities to physicochemical characteristics and provides insights into the survival of microbial communities in ancient permafrost.","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/AEM.02646-18","usgsCitation":"Burkert, A., Douglas, T.A., Waldrop, M., and Mackelprang, R., 2019, Changes in the active, dead, and dormant microbial community structure across a Pleistocene permafrost chronosequence: Applied and Environmental Microbiology, v. 85, no. 7, e02646-18: 52 p., https://doi.org/10.1128/AEM.02646-18.","productDescription":"e02646-18: 52 p.","ipdsId":"IP-101909","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/aem.02646-18","text":"Publisher Index Page"},{"id":365297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"85","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burkert, Alexander","contributorId":201933,"corporation":false,"usgs":false,"family":"Burkert","given":"Alexander","email":"","affiliations":[{"id":36305,"text":"CSU Northridge","active":true,"usgs":false}],"preferred":false,"id":765487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, Thomas A. 0000-0003-1314-1905","orcid":"https://orcid.org/0000-0003-1314-1905","contributorId":64553,"corporation":false,"usgs":false,"family":"Douglas","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":33087,"text":"Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":true,"id":765488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216780,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mackelprang, Rachel","contributorId":200882,"corporation":false,"usgs":false,"family":"Mackelprang","given":"Rachel","email":"","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":765489,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215866,"text":"70215866 - 2019 - The 12 November 2017 Mw 7.3 Ezgeleh–Sarpolzahab (Iran) earthquake and active tectonics of the Lurestan arc","interactions":[],"lastModifiedDate":"2020-10-30T17:04:17.439383","indexId":"70215866","displayToPublicDate":"2019-01-25T11:49:46","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The 12 November 2017 Mw 7.3 Ezgeleh–Sarpolzahab (Iran) earthquake and active tectonics of the Lurestan arc","docAbstract":"The 12 November 2017 Mw 7.3 Ezgeleh‐Sarpolzahab earthquake is the largest instrumentally recorded earthquake in the Zagros Simply Folded Belt by a factor of ∼10 in seismic moment. Exploiting local, regional, and teleseismic data and synthetic aperture radar interferometry imagery, we characterize the rupture, its aftershock sequence, background seismicity, and regional tectonics. The mainshock ruptured slowly (∼2 km/s), unilaterally southward, for ∼40 km along an oblique (dextral‐thrust) fault that dips ∼14°E beneath the northwestern Lurestan arc. Slip is confined to basement depths of ∼12–18 km, resolvably beneath the sedimentary cover which is ∼8 km thick in this area. The gentle dip angle and basement location allow for a broad slip area, explaining the large magnitude relative to earthquakes in the main Fars arc of the Zagros, where shallower, steeper faults are limited in rupture extent by weak sedimentary layers. Early aftershocks concentrate around the southern and western edges of the mainshock slip area and therefore cluster in the direction of rupture propagation, implying a contribution from dynamic triggering. A cluster of events ∼100 km to the south near Mandali (Iraq) reactivated the ∼50° dipping Zagros Foredeep Fault. The basement fault responsible for the Ezgeleh‐Sarpolzahab earthquake probably accounts for the ∼1 km elevation contrast between the Lurestan arc and the Kirkuk embayment but is distinct from sections of the Mountain Front Fault that define frontal escarpments elsewhere in the Zagros. It may be related to a seismic interface underlying the central and southern Lurestan arc, and a key concern is whether or not the more extensive regional structure is also seismogenic.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB016221","usgsCitation":"Nissen, E., Ghods, A., Karasozen, E., Elliott, J.R., Barnhart, W., Bergman, E.A., Hayes, G.P., Jamal-Reyhani, M., Nemati, M., Tan, F., Abdulnaby, W., Benz, H.M., Shahvar, M.P., Talebian, M., and Chen, L., 2019, The 12 November 2017 Mw 7.3 Ezgeleh–Sarpolzahab (Iran) earthquake and active tectonics of the Lurestan arc: Journal of Geophysical Research: Solid Earth, v. 124, no. 2, p. 2124-2152, https://doi.org/10.1029/2018JB016221.","productDescription":"29 p.","startPage":"2124","endPage":"2152","ipdsId":"IP-101802","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb016221","text":"Publisher Index 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Mohammadreza","contributorId":244226,"corporation":false,"usgs":false,"family":"Jamal-Reyhani","given":"Mohammadreza","email":"","affiliations":[{"id":48866,"text":"Institute for Advanced Studies in Basic Sciences","active":true,"usgs":false}],"preferred":false,"id":803537,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nemati, Majid","contributorId":244227,"corporation":false,"usgs":false,"family":"Nemati","given":"Majid","email":"","affiliations":[{"id":48867,"text":"Shahid Bahonar University of Kerman,","active":true,"usgs":false}],"preferred":false,"id":803538,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tan, Fengzhou 0000-0003-1989-7017","orcid":"https://orcid.org/0000-0003-1989-7017","contributorId":244228,"corporation":false,"usgs":false,"family":"Tan","given":"Fengzhou","email":"","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":803539,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Abdulnaby, Wathiq","contributorId":244229,"corporation":false,"usgs":false,"family":"Abdulnaby","given":"Wathiq","email":"","affiliations":[{"id":48868,"text":"University of Basra","active":true,"usgs":false}],"preferred":false,"id":803540,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":803541,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Shahvar, Mohammad P.","contributorId":244230,"corporation":false,"usgs":false,"family":"Shahvar","given":"Mohammad","email":"","middleInitial":"P.","affiliations":[{"id":48869,"text":"Building and Housing Research Network","active":true,"usgs":false}],"preferred":false,"id":803542,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Talebian, Morteza","contributorId":244231,"corporation":false,"usgs":false,"family":"Talebian","given":"Morteza","email":"","affiliations":[{"id":48870,"text":"Geological Survey of Iran","active":true,"usgs":false}],"preferred":false,"id":803543,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Chen, Ling 0000-0001-7170-5954","orcid":"https://orcid.org/0000-0001-7170-5954","contributorId":244232,"corporation":false,"usgs":false,"family":"Chen","given":"Ling","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":803544,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70203484,"text":"70203484 - 2019 - The 2018 rift eruption and summit collapse of Kilauea Volcano","interactions":[],"lastModifiedDate":"2021-10-26T15:58:24.187026","indexId":"70203484","displayToPublicDate":"2019-01-25T09:27:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 rift eruption and summit collapse of Kilauea Volcano","docAbstract":"In 2018, Kīlauea Volcano experienced its largest lower East Rift Zone (LERZ) eruption and caldera collapse in at least 200 years. After collapse of the Pu'u 'Ō'ō vent on 30 April, magma propagated downrift. Eruptive fissures opened in the LERZ on 3 May, eventually extending ~6.8 km. A 4 May earthquake (M6.9) produced ~5 m of fault slip. Lava erupted at rates exceeding 100 m3/s, eventually covering 35.5 km2. The summit magma system partially drained, producing minor explosions and near-daily collapses releasing energy equivalent to M4.7-M5.4 earthquakes. Activity declined rapidly on 4 August. Summit collapse and lava flow volume estimates are roughly equivalent--about 0.8 km3. Careful historical observation and monitoring of Kīlauea enabled successful forecasting of hazardous events.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aav7046","usgsCitation":"Neal, C.A., Brantley, S., Antolik, L., Babb, J., Burgess, M.K., Cappos, M., Chang, J., Conway, S., Desmither, L.G., Dotray, P., Elias, T., Fukunaga, P., Fuke, S., Johanson, I.A., Kamibayashi, K., Kauahikaua, J.P., Lee, R., Pekalib, S., Miklius, A., Shiro, B., Swanson, D., Nadeau, P.A., Zoeller, M.H., Okubo, P., Parcheta, C., Patrick, M.R., Tollett, W., Trusdell, F., Younger, E.F., Montgomery-Brown, E.K., Anderson, K.R., Poland, M.P., Ball, J.L., Bard, J., Coombs, M.L., Dietterich, H., Kern, C., Thelen, W., Cervelli, P., Orr, T.R., Houghton, B.F., Gansecki, C., Hazlett, R., Lundgren, P., Diefenbach, A., Lerner, A., Waite, G., Kelly, P.J., Clor, L., Werner, C., Mulliken, K., Fisher, G.B., and Damby, D., 2019, The 2018 rift eruption and summit collapse of Kilauea Volcano: Science, v. 363, no. 6425, p. 367-374, https://doi.org/10.1126/science.aav7046.","productDescription":"8 p.","startPage":"367","endPage":"374","ipdsId":"IP-100772","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":364001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.31646728515625,\n 19.263507501734075\n ],\n [\n -155.03562927246094,\n 19.263507501734075\n ],\n [\n -155.03562927246094,\n 19.46432633709043\n ],\n [\n -155.31646728515625,\n 19.46432633709043\n ],\n [\n -155.31646728515625,\n 19.263507501734075\n ]\n ]\n ]\n }\n }\n 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genomics era","interactions":[],"lastModifiedDate":"2021-08-12T12:55:41.045881","indexId":"70223138","displayToPublicDate":"2019-01-25T07:52:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"The future is now: Amplicon sequencing and sequence capture usher in the conservation genomics era","docAbstract":"The genomics revolution has initiated a new era of population genetics where genome-wide data are frequently used to understand complex patterns of population structure and selection. However, the application of genomic tools to inform management and conservation has been somewhat rare outside a few well studied species. Fortunately, two recently developed approaches, amplicon sequencing and sequence capture, have the potential to significantly advance the field of conservation genomics. Here, amplicon sequencing refers to highly multiplexed PCR followed by high-throughput sequencing (e.g., GTseq), and sequence capture refers to using capture probes to isolate loci from reduced-representation libraries (e.g., Rapture). Both approaches allow sequencing of thousands of individuals at relatively low costs, do not require any specialized equipment for library preparation, and generate data that can be analyzed without sophisticated computational infrastructure. Here, we discuss the advantages and disadvantages of each method and provide a decision framework for geneticists who are looking to integrate these methods into their research programme. While it will always be important to consider the specifics of the biological question and system, we believe that amplicon sequencing is best suited for projects aiming to genotype <500 loci on many individuals (>1,500) or for species where continued monitoring is anticipated (e.g., long-term pedigrees). Sequence capture, on the other hand, is best applied to projects including fewer individuals or where >500 loci are required. Both of these techniques should smooth the transition from traditional genetic techniques to genomics, helping to usher in the conservation genomics era.
The microscopic alga Picocystis sp. strain ML is responsible for recurrent algal blooms in Mono Lake, CA. This organism was characterized by only very little molecular data, despite its prominence as a primary producer in saline environments. Here, we report the draft genome sequence for Picocystis sp. strain ML based on long-read sequencing.
","largerWorkTitle":"Microbiology Resource Announcements","language":"English","publisher":"ASM Journals","doi":"10.1128/MRA.01353-18","usgsCitation":"Junkins, E.N., Stamps, B.W., Corsetti, F., Oremland, R., Spear, J.R., and Stevenson, B.S., 2019, Draft genome sequence of Picocystis strain ML cultivated from Mono Lake, California, in Microbiology Resource Announcements, 3 p., https://doi.org/10.1128/MRA.01353-18.","productDescription":"3 p.","ipdsId":"IP-101960","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/mra.01353-18","text":"Publisher Index Page"},{"id":425937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mono Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.17915239667829,\n 38.09589581962763\n ],\n [\n -119.17915239667829,\n 37.91351094828286\n ],\n [\n -118.86238694901873,\n 37.91351094828286\n ],\n [\n -118.86238694901873,\n 38.09589581962763\n ],\n [\n -119.17915239667829,\n 38.09589581962763\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Junkins, Emily N","contributorId":294487,"corporation":false,"usgs":false,"family":"Junkins","given":"Emily","email":"","middleInitial":"N","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":848133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamps, Blake W.","contributorId":176485,"corporation":false,"usgs":false,"family":"Stamps","given":"Blake","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":848134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corsetti, Frank A","contributorId":293642,"corporation":false,"usgs":false,"family":"Corsetti","given":"Frank A","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":848135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oremland, Ronald S. 0000-0001-7382-0147","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":257598,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":848136,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spear, John R.","contributorId":176847,"corporation":false,"usgs":false,"family":"Spear","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":848137,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stevenson, Bradley S.","contributorId":176491,"corporation":false,"usgs":false,"family":"Stevenson","given":"Bradley","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":848138,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215990,"text":"70215990 - 2019 - Simulating detection-censored movement records for home range analysis planning","interactions":[],"lastModifiedDate":"2020-11-03T13:55:55.524376","indexId":"70215990","displayToPublicDate":"2019-01-24T07:49:30","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Simulating detection-censored movement records for home range analysis planning","docAbstract":"Home range estimation is an important analytical method; yet best practices for addressing the effects of spatial variation in detection probability on home range estimates remains elusive. We introduce the R package “DiagnoseHR,” simulation tools for assessing how variation in detection probability arising from landscape, animal behavior, and methodological processes affects home range inference. We demonstrate the utility of simulation methods for home range analysis planning by comparing bias arising from three home range estimation methods under multiple detection scenarios. We simulated correlated random walks in three landscapes that varied in detection probability and constructed home ranges from locations filtered through a range of sampling protocols. Home range estimates were less biased by reduced detection probability when sampling effort was increased, but the effects of sampling day distribution were marginal. Like others, we found that kernel density estimates were the least affected by variation in detection probability, while minimum convex polygons were most affected. Our results illustrate the value of quantifying uncertainty in home range estimates and suggest that field biologists working in conditions with low-detection may wish to weight sample-size greater than concerns about temporal autocorrelation when designing sampling protocols.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.10.017","usgsCitation":"Wszola, L.S., Simonsen, V., Corral, L., Chizinski, C.J., and Fontaine, J.J., 2019, Simulating detection-censored movement records for home range analysis planning, v. 392, p. 268-278, https://doi.org/10.1016/j.ecolmodel.2018.10.017.","productDescription":"11 p.","startPage":"268","endPage":"278","ipdsId":"IP-096329","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":380070,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wszola, L. S.","contributorId":244291,"corporation":false,"usgs":false,"family":"Wszola","given":"L.","email":"","middleInitial":"S.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonsen, V.L.","contributorId":244292,"corporation":false,"usgs":false,"family":"Simonsen","given":"V.L.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803697,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corral, L.","contributorId":244293,"corporation":false,"usgs":false,"family":"Corral","given":"L.","email":"","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803698,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chizinski, C. J.","contributorId":243358,"corporation":false,"usgs":false,"family":"Chizinski","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":803699,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fontaine, Joseph J. 0000-0002-7639-9156 jfontaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-9156","contributorId":3820,"corporation":false,"usgs":true,"family":"Fontaine","given":"Joseph","email":"jfontaine@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":803700,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203104,"text":"70203104 - 2019 - Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?","interactions":[],"lastModifiedDate":"2023-03-24T16:35:52.034587","indexId":"70203104","displayToPublicDate":"2019-01-23T11:03:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5259,"text":"SOIL","active":true,"publicationSubtype":{"id":10}},"title":"Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?","docAbstract":"Ecosystem shifts related to climate change are anticipated for the next decades to centuries based on a number of conceptual and experimentally derived models of plant structure and function. Belowground, the potential responses of soil systems are less well known. We used geochemical steady state models, soil density fractionation, and soil radiocarbon data to constrain changes in soil carbon based on measurements from detrital (free light), aggregate-bound (occluded) and complexed or chemically bound (mineral associated) carbon pools and for bulk soil. We explored a space-for-time sequence of soils along a cold-to-warm climatic gradient from Alaskan Black Spruce forest soil with permafrost (Gelisols; 50 cm Mean Annual Temperature −1.5 ºC), Alaskan White Spruce forest soil lacking permafrost (Inceptisols; 50 cm MAT +3 ºC ), and Iowa Grassland soil lacking permafrost (Mollisols; 50 cm MAT +9 ºC) developed on similar geologic substrates (wind-blown loess deposits). These temperature ranges were also representative of temperatures at 50 cm soil depth from model output by the Community Land Model for the years 2014, 2100, and 2300 for Interior Alaska. Fitting an exponential equation to depth trends in soil C down to 2 m depths, we found that depth distributions of organic C were related mainly to depths of rooting and changes in bulk density. Using output from the geochemical steady state model, the direction and magnitude of the C loss or gain upon ecosystem shift was dictated by the C stocks of initial and final ecosystems. Radiocarbon measurements specific to each soil fraction (free light, occluded, and mineral associated) allowed us to constrain the timing of the potential loss or gain of C in each fraction driven by climatic shifts. Thawing from the Gelisol to Inceptisol in loess parent materials from present day to year 2100 resulted in small net gains to soil C, reflecting the net balance between loss of detrital and gain into occluded and mineral associated C. Greater warming and shifts from Inceptisol to Mollisol analogous to predicted warming from circa 2100 to 2300 resulted in net C losses from both occluded and mineral associated C, although small gains to the free light C fraction occurred throughout the depth profile. Gains to occluded and mineral associated C post- thaw likely reflect aggregate formation and physical protection of C as well as formation of organo-mineral compounds that accompany microbial processing. Greater warming and shifts from Inceptisol to Mollisol, which are analogous to predicted warming circa 2100 to 2300, resulted in net C losses from both occluded and mineral associated C resulting from enhanced decomposition, small gains to the free light C fraction occurred throughout the transition to Mollisol reflecting deeper rooting of the tallgrass prairie system.","language":"English","publisher":"European Geosciences Union (EGU)","doi":"10.5194/soil-2018-41","usgsCitation":"Harden, J.W., O’Donnell, J., Heckman, K., Sulman, B., Koven, C., Ping, C., and Michaelson, G., 2019, Beneath the arctic greening: Will soils lose or gain carbon or perhaps a little of both?: SOIL, 22 p., https://doi.org/10.5194/soil-2018-41.","productDescription":"22 p.","ipdsId":"IP-103776","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467986,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5194/soil-2018-41","text":"External Repository"},{"id":363102,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":761184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, J.A.","contributorId":214930,"corporation":false,"usgs":false,"family":"O’Donnell","given":"J.A.","email":"","affiliations":[{"id":39140,"text":"Arctic Network, National Park Service, Anchorage, Alaska","active":true,"usgs":false}],"preferred":false,"id":761185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heckman, K.A.","contributorId":197919,"corporation":false,"usgs":false,"family":"Heckman","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":761186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sulman, B.N.","contributorId":214931,"corporation":false,"usgs":false,"family":"Sulman","given":"B.N.","email":"","affiliations":[{"id":37400,"text":"Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee","active":true,"usgs":false}],"preferred":false,"id":761187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koven, C.D.","contributorId":199628,"corporation":false,"usgs":false,"family":"Koven","given":"C.D.","email":"","affiliations":[],"preferred":false,"id":761188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ping, C.L.","contributorId":199629,"corporation":false,"usgs":false,"family":"Ping","given":"C.L.","affiliations":[],"preferred":false,"id":761189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Michaelson, G.J.","contributorId":199630,"corporation":false,"usgs":false,"family":"Michaelson","given":"G.J.","email":"","affiliations":[],"preferred":false,"id":761190,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223135,"text":"70223135 - 2019 - Factors influencing fish mercury concentrations in Iowa rivers","interactions":[],"lastModifiedDate":"2021-08-12T13:04:48.413743","indexId":"70223135","displayToPublicDate":"2019-01-21T08:02:15","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing fish mercury concentrations in Iowa rivers","docAbstract":"Fish mercury concentrations have received considerable attention due to human health implications. Fish mercury concentrations are variable within and among systems due to a suite of biotic and abiotic influences that vary among regions and are difficult to predict. Understanding factors associated with variability in fish mercury concentrations would help guide consumption advisories. Mercury concentrations in channel catfish (Ictalurus punctatus, n = 205), flathead catfish (Pylodictis olivaris, n = 123), northern pike (Esox lucius, n = 60), smallmouth bass (Micropterus dolomieu, n = 176), and walleye (Sander vitreus, n = 176) were assessed in ten Iowa rivers and relationships with land use, water chemistry, and fish characteristics were explored. Mercury concentrations were generally low (mean among all species = 0.17 mg/kg, n = 740) but higher in flathead catfish, northern pike, smallmouth bass, and walleye than channel catfish and were positively related to fish length, age, trophic position, and δ13C signatures. Phosphorus, sulfate, and percent open water and grassland were negatively related to fish mercury concentrations, whereas water hardness, nitrogen-ammonia, Human Threat Index, and percent wetland and forest were positively related to fish mercury concentrations. Fish collected from the Paleozoic Plateau ecoregion in northeast Iowa had higher mercury concentrations than other ecoregions in Iowa. Combined, these factors explained 70% of the variation in fish mercury concentrations. This study provides a comprehensive analysis of abiotic and biotic factors influencing fish mercury concentrations in lotic ecosystems at the individual and system scale that will help guide fish consumption advisories.
The forthcoming Surface Water and Ocean Topography (SWOT) satellite mission will provide global measurements of the free surface of large rivers, providing new opportunities for remote sensing‐derived estimates of river discharge in gaged and ungaged basins. SWOT discharge algorithms have been developed and benchmarked using synthetic data but remain untested on real‐world swath altimetry observations. We present the first discharge estimates from AirSWOT, a SWOT‐like airborne Ka‐band radar, using 6 days of measurements over a 40‐km segment of the Willamette River in Oregon, USA. The three evaluated discharge algorithms estimated discharge with normalized root‐mean‐square errors of 10–31% when compared with in situ gage data but were sensitive to an initial estimate of mean annual discharge. Our results show that these discharge algorithms provide reliable discharge estimates on remotely sensed data at SWOT‐like spatial scales while highlighting the need for further algorithm sensitivity tests.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GL080771","usgsCitation":"Tuozzolo, S., Lind, G.D., Overstreet, B., Mangano, J.F., Fonstad, M.A., Hagemann, M., Frasson, R., Larnier, K., Garambois, P., Monnier, J., and Durand, M., 2019, Estimating river discharge with swath altimetry: A proof of concept using AirSWOT observations: Geophysical Research Letters, v. 46, no. 3, p. 1459-1466, https://doi.org/10.1029/2018GL080771.","productDescription":"8 p.","startPage":"1459","endPage":"1466","ipdsId":"IP-103081","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":499858,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/528a9d5c4cdf4081a5ffc133acacf87b","text":"External Repository"},{"id":379940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40966796874999,\n 43.82263823180498\n ],\n [\n -122.80517578125,\n 44.008620115415354\n ],\n [\n -122.991943359375,\n 44.07574700247845\n ],\n [\n -123.02490234375,\n 43.937461690316646\n ],\n [\n -122.47009277343749,\n 43.64800079902171\n ],\n [\n -122.40966796874999,\n 43.82263823180498\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Tuozzolo, Stephen","contributorId":244142,"corporation":false,"usgs":false,"family":"Tuozzolo","given":"Stephen","email":"","affiliations":[{"id":48856,"text":"Byrd Polar and Climate Research Center, Ohio State University","active":true,"usgs":false}],"preferred":false,"id":803406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lind, Greg D. 0000-0001-5385-2117 glind@usgs.gov","orcid":"https://orcid.org/0000-0001-5385-2117","contributorId":5514,"corporation":false,"usgs":true,"family":"Lind","given":"Greg","email":"glind@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overstreet, Brandon 0000-0001-7845-6671 boverstreet@usgs.gov","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":169201,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"boverstreet@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mangano, Joseph F. 0000-0003-4213-8406 jmangano@usgs.gov","orcid":"https://orcid.org/0000-0003-4213-8406","contributorId":4722,"corporation":false,"usgs":true,"family":"Mangano","given":"Joseph","email":"jmangano@usgs.gov","middleInitial":"F.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fonstad, Mark A","contributorId":169202,"corporation":false,"usgs":false,"family":"Fonstad","given":"Mark","email":"","middleInitial":"A","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":803410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hagemann, M.","contributorId":244143,"corporation":false,"usgs":false,"family":"Hagemann","given":"M.","email":"","affiliations":[{"id":48857,"text":"Byrd Polar and Climate Research Center, Ohio State University, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":803411,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frasson, R.P.M.","contributorId":244144,"corporation":false,"usgs":false,"family":"Frasson","given":"R.P.M.","affiliations":[{"id":48857,"text":"Byrd Polar and Climate Research Center, Ohio State University, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":803412,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Larnier, K","contributorId":244145,"corporation":false,"usgs":false,"family":"Larnier","given":"K","affiliations":[{"id":48858,"text":"CS corporation, Business Unit Espace, Toulouse, France; 5Institut de Mathématiques de Toulouse (IMT), France; INSA Strasbourg, France; INSA Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":803413,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Garambois, P.-A.","contributorId":244146,"corporation":false,"usgs":false,"family":"Garambois","given":"P.-A.","affiliations":[{"id":48859,"text":"INSA Strasbourg, France; ICUBE, Strasbourg, France","active":true,"usgs":false}],"preferred":false,"id":803414,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Monnier, J.","contributorId":244147,"corporation":false,"usgs":false,"family":"Monnier","given":"J.","email":"","affiliations":[{"id":48860,"text":"Institut de Mathématiques de Toulouse (IMT), France; INSA Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":803415,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Durand, M.","contributorId":244148,"corporation":false,"usgs":false,"family":"Durand","given":"M.","email":"","affiliations":[{"id":48857,"text":"Byrd Polar and Climate Research Center, Ohio State University, Columbus, Ohio, USA","active":true,"usgs":false}],"preferred":false,"id":803416,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70223291,"text":"70223291 - 2019 - Does incorporating gear selectivity during macroscale investigations of fish growth reduce size-selective sampling bias in parameter estimates?","interactions":[],"lastModifiedDate":"2021-08-20T13:30:36.240789","indexId":"70223291","displayToPublicDate":"2019-01-19T08:28:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6455,"text":"Canadian Journal Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Does incorporating gear selectivity during macroscale investigations of fish growth reduce size-selective sampling bias in parameter estimates?","docAbstract":"Permafrost thaw alters subsurface flow in boreal regions that in turn influences the magnitude, seasonality, and chemical composition of streamflow. Prediction of these changes is challenged by incomplete knowledge of timing, flowpath depth, and amount of groundwater discharge to streams in response to thaw. One important phenomenon that may affect flow and transport through boreal hillslopes is development of lateral perennial thaw zones (PTZs), the existence of which is here supported by geophysical observations and cryohydrogeologic modeling. Model results link thaw to enhanced and seasonally-extended baseflow, which have implications for mobilization of soluble constituents. Results demonstrate the sensitivity of PTZ development to organic layer thickness and near-surface factors that mediate heat exchange at the atmosphere/ground-surface interface. Study findings suggest that PTZs serve as a detectable precursor to accelerated permafrost degradation. This study provides important contextual insight on a fundamental thermo-hydrologic process that can enhance terrestrial-to-aquatic transfer of permafrost carbon, nitrogen, and mercury previously sequestered in thawing watersheds.
","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/aaf0cc","usgsCitation":"Walvoord, M.A., Voss, C., Ebel, B., and Minsley, B.J., 2019, Development of perennial thaw zones in boreal hillslopes enhances potential mobilization of permafrost carbon: Environmental Research Letters, v. 14, no. 1, p. 1-11, https://doi.org/10.1088/1748-9326/aaf0cc.","productDescription":"Article 015003; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-098066","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467989,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aaf0cc","text":"Publisher Index Page"},{"id":437601,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HWCOBP","text":"USGS data release","linkHelpText":"Model Archive for coupled energy and fluid flow simulations generalized to boreal hillslopes"},{"id":360760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"14","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-17","publicationStatus":"PW","scienceBaseUri":"5c5022c3e4b0708288f7e800","contributors":{"authors":[{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Clifford I. 0000-0001-5923-2752","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":211844,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":755033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":755034,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228357,"text":"70228357 - 2019 - The influence of depth and velocity on age-0 Scaphirhynchus sturgeon prey consumption: Implications for aquatic habitat restoration","interactions":[],"lastModifiedDate":"2022-02-09T17:50:05.198217","indexId":"70228357","displayToPublicDate":"2019-01-17T11:44:42","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The influence of depth and velocity on age-0 Scaphirhynchus sturgeon prey consumption: Implications for aquatic habitat restoration","title":"The influence of depth and velocity on age-0 Scaphirhynchus sturgeon prey consumption: Implications for aquatic habitat restoration","docAbstract":"After the pallid sturgeon (Scaphirhynchus albus) was listed as endangered in 1990, a variety of management actions focusing on early life history needs have been implemented to aid species recovery. Given the scarcity of age-0 pallid sturgeon, managers and scientists have relied on sympatric congeners to evaluate the effectiveness of management actions in the short term; however, increased understanding of habitat requirements for age-0 Scaphirhynchus sturgeon is still needed to appropriately focus management efforts. Recently, a lack of food-producing and foraging habitats were proposed as potential limiting factors for pallid sturgeon, and the purpose of this study was to evaluate the current definition of these habitats at multiple spatial scales using data from age-0 Scaphirhynchus sturgeon (shovelnose sturgeon [Scaphirhynchus platyrhynchus] or hybrid [shovelnose sturgeon x pallid sturgeon]). Results showed the water depths and velocities that currently define age-0 pallid sturgeon foraging habitat had little effect on age-0 Scaphirhynchus sturgeon prey consumption. Similar results occurred when evaluating the relationship between prey consumption and food-producing habitat present 10, 20, and 30 days before capture. Assuming that individuals captured during this study were a valid surrogate, these results suggest that increasing foraging and food-producing habitat as defined by the current depth and velocity criteria is unlikely to result in the desired benefits of increased growth and survival of age-0 pallid sturgeon.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3395","usgsCitation":"Gemeinhardt, T.R., Gosch, N.J., Civiello, A., Chrisman, N., Shaughnessy, H., Brown, T.L., Long, J.M., and Bonneau, J.L., 2019, The influence of depth and velocity on age-0 Scaphirhynchus sturgeon prey consumption: Implications for aquatic habitat restoration: River Research and Applications, v. 35, no. 3, p. 205-215, https://doi.org/10.1002/rra.3395.","productDescription":"11 p.","startPage":"205","endPage":"215","ipdsId":"IP-098842","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"lower Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.76806640624999,\n 37.92686760148135\n ],\n [\n -90.164794921875,\n 37.92686760148135\n ],\n [\n -90.164794921875,\n 39.52099229357195\n ],\n [\n -94.76806640624999,\n 39.52099229357195\n ],\n [\n -94.76806640624999,\n 37.92686760148135\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gemeinhardt, T. R.","contributorId":275284,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T.","email":"","middleInitial":"R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gosch, N. J. C.","contributorId":272518,"corporation":false,"usgs":false,"family":"Gosch","given":"N.","email":"","middleInitial":"J. C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Civiello, A. P.","contributorId":272519,"corporation":false,"usgs":false,"family":"Civiello","given":"A. P.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chrisman, N.","contributorId":275285,"corporation":false,"usgs":false,"family":"Chrisman","given":"N.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shaughnessy, H.","contributorId":275286,"corporation":false,"usgs":false,"family":"Shaughnessy","given":"H.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833931,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, T. L.","contributorId":275287,"corporation":false,"usgs":false,"family":"Brown","given":"T.","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833932,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":833933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bonneau, J. L.","contributorId":275288,"corporation":false,"usgs":false,"family":"Bonneau","given":"J.","email":"","middleInitial":"L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":833934,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216037,"text":"70216037 - 2019 - Temporal variability in nitrate – discharge relationships in large rivers as revealed by high frequency data","interactions":[],"lastModifiedDate":"2020-11-03T17:07:07.577689","indexId":"70216037","displayToPublicDate":"2019-01-17T11:03:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Temporal variability in nitrate – discharge relationships in large rivers as revealed by high frequency data","docAbstract":"Little is known about temporal variability in nitrate concentration responses to changes in discharge on intraannual time scales in large rivers. To investigate this knowledge gap, we used a six‐year data set of daily surface water nitrate concentration and discharge averaged from near‐continuous monitoring at U.S. Geological Survey gaging stations on the Connecticut, Potomac, and Mississippi Rivers, three large rivers that contribute substantial nutrient pollution to important estuaries. Interannually, a comparison of nitrate concentration‐discharge (c‐Q) relationships between a traditional discrete grab sample data set and the near‐continuous data set revealed differing c‐Q slopes, which suggests that sample frequency can impact how we ultimately characterize hydrologic systems. Intraannually, we conducted correlation analyses over 30‐day windows to isolate the strength and direction of monthly c‐Q relationships. Monthly c‐Q slopes in the Potomac were positive (enrichment/mobilization response) in summer and fall and negative (dilution response) and weakly chemostatic (nonsignificant near‐zero c‐Q slope) in winter and spring, respectively. The Connecticut displayed a dilution response year‐round, except summer when it was weakly chemostatic. Mississippi c‐Q slopes were weakly chemostatic in all seasons and showed inconsistent responses to discharge fluctuations. The c‐Q dynamics in the Potomac and Connecticut were correlated (R > 0.3) to river temperature, flow percentile, and calendar day. Minimal correlation in the Mississippi suggests that the large basin area coupled with spatiotemporally variable anthropogenic forcings from substantial land use development created stochastic short‐term c‐Q relationships. Additional work using high‐frequency sensors across large river networks can improve our understanding of spatial source input dynamics in these natural‐human coupled systems.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023478","usgsCitation":"Zimmer, M., Pellerin, B., Burns, D., and Petrochenkov, G.P., 2019, Temporal variability in nitrate – discharge relationships in large rivers as revealed by high frequency data: Water Resources Research, v. 55, no. 2, p. 973-989, https://doi.org/10.1029/2018WR023478.","productDescription":"17 p.","startPage":"973","endPage":"989","ipdsId":"IP-092633","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":467990,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/82eeaf2c310645d18b234ef435a83b9c","text":"Publisher Index Page"},{"id":380080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmer, Margaret 0000-0001-8287-1923","orcid":"https://orcid.org/0000-0001-8287-1923","contributorId":225158,"corporation":false,"usgs":false,"family":"Zimmer","given":"Margaret","affiliations":[{"id":41054,"text":"Earth and Planetary Sciences, University of California, Santa Cruz, CA, 95064, USA","active":true,"usgs":false}],"preferred":false,"id":803845,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pellerin, Brian A. 0000-0003-3712-7884","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":204324,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian A.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":803846,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803847,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petrochenkov, Gregory Paul 0000-0001-9247-821X","orcid":"https://orcid.org/0000-0001-9247-821X","contributorId":244356,"corporation":false,"usgs":true,"family":"Petrochenkov","given":"Gregory","email":"","middleInitial":"Paul","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":803848,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223290,"text":"70223290 - 2019 - Temperature–not flow–predicts native fish reproduction with Implications for climate change","interactions":[],"lastModifiedDate":"2021-08-20T14:10:26.124351","indexId":"70223290","displayToPublicDate":"2019-01-17T09:05:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Temperature–not flow–predicts native fish reproduction with Implications for climate change","docAbstract":"Habitat alterations and introduction of nonnative fishes reduced the distributions of the Flannelmouth Sucker Catostomus latipinnis, Bluehead Sucker C. discobolus, and Roundtail Chub Gila robusta to less than 50% of their historical ranges. Climate change models generally predict decreased streamflows and increased water temperatures that may further affect these species. Understanding the effects of flow and water temperature on their life histories should lead to better assessments of climate change impacts on extant populations and more informed management for species conservation. Basinwide larval fish sampling and hatch dates derived from otolith daily increment counts showed that water temperature was the dominant environmental factor cueing reproduction in the upper White River basin, Colorado. Reproduction for all three species began in spring, occurring first at warmer, lower-elevation, downstream locations and progressing upriver to higher elevations as water temperatures increased. Warmer water temperatures in tributaries initiated earlier reproductive activity compared to adjacent cooler main-stem habitat. Presence of larvae in samples and estimated hatch dates demonstrated a distinct, predictable upstream progression of reproduction associated with warming water and clear upstream limits to reproduction for all three species. Larval presence and hatching dates revealed earlier reproductive activity in 2012 than in 2013, driven by lower flow and earlier stream warming. A regression model predicted stream temperature during fish spawning seasons under different climate change scenarios and showed expanded upstream limits of thermally suitable reproductive habitat and earlier reproduction for our study species. The long-term implications of climate change are unknown, but managers should strive to perpetuate the valuable and relatively pristine native fish community in the upper White River drainage as a vestige of those that formerly existed throughout the Colorado River basin.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10151","usgsCitation":"Fraser, G., Bestgen, K., Winkelman, D.L., and Thompson, K.G., 2019, Temperature–not flow–predicts native fish reproduction with Implications for climate change: Transactions of the American Fisheries Society, v. 148, no. 3, p. 509-527, https://doi.org/10.1002/tafs.10151.","productDescription":"19 p.","startPage":"509","endPage":"527","ipdsId":"IP-101495","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":467991,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10151","text":"Publisher Index Page"},{"id":388233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"White River headwaters","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.951416015625,\n 39.78532331459258\n ],\n [\n -107.193603515625,\n 39.78532331459258\n ],\n [\n -107.193603515625,\n 40.233411907115055\n ],\n [\n -108.951416015625,\n 40.233411907115055\n ],\n [\n -108.951416015625,\n 39.78532331459258\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Fraser, Gregory S.","contributorId":264508,"corporation":false,"usgs":false,"family":"Fraser","given":"Gregory S.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":821623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bestgen, Kevin R.","contributorId":264509,"corporation":false,"usgs":false,"family":"Bestgen","given":"Kevin R.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":821624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Kevin G.","contributorId":264512,"corporation":false,"usgs":false,"family":"Thompson","given":"Kevin","email":"","middleInitial":"G.","affiliations":[{"id":54484,"text":"co pw","active":true,"usgs":false}],"preferred":false,"id":821625,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203149,"text":"70203149 - 2019 - Sediment oxygen demand: A review of in situ methods","interactions":[],"lastModifiedDate":"2019-04-24T08:49:15","indexId":"70203149","displayToPublicDate":"2019-01-17T08:47:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Sediment oxygen demand: A review of in situ methods","docAbstract":"Sediment oxygen demand (SOD) plays a fundamental role in biological and chemical processes within the benthic layer of a water body. Land use, including agricultural land use, can affect SOD. However, a wide variety of approaches have been used for in situ SOD chamber construction and data collection, and modelers frequently use SOD values from the literature, without consideration of the differences in methods. Here, we review existing literature on SOD chambers (32 papers, 1974–2016), compare the differences between in situ and laboratory methods, evaluate the effects of in situ chamber mixing, and discuss common challenges associated with deployment. A cohesive in situ sealed chamber design for use with a multiparameter water-quality instrument is presented as an effort toward standardizing SOD methodology, an important consideration that may facilitate integration of SOD data sets among multiple research efforts.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2018.06.0251","usgsCitation":"Coenen, E., Christensen, V.G., Bartsch, L., Kreiling, R.M., and Richardson, W.B., 2019, Sediment oxygen demand: A review of in situ methods: Journal of Environmental Quality, v. 48, no. 2, p. 403-411, https://doi.org/10.2134/jeq2018.06.0251.","productDescription":"9 p.","startPage":"403","endPage":"411","ipdsId":"IP-091254","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":363167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coenen, Erin N. 0000-0003-2470-3854","orcid":"https://orcid.org/0000-0003-2470-3854","contributorId":211159,"corporation":false,"usgs":true,"family":"Coenen","given":"Erin N.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":761395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartsch, Lynn 0000-0002-1483-4845 lbartsch@usgs.gov","orcid":"https://orcid.org/0000-0002-1483-4845","contributorId":214995,"corporation":false,"usgs":true,"family":"Bartsch","given":"Lynn","email":"lbartsch@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kreiling, Rebecca M. 0000-0002-9295-4156","orcid":"https://orcid.org/0000-0002-9295-4156","contributorId":202193,"corporation":false,"usgs":true,"family":"Kreiling","given":"Rebecca","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":761398,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201965,"text":"70201965 - 2019 - The 4.2 ka event, ENSO, and coral reef development","interactions":[],"lastModifiedDate":"2019-02-04T16:03:19","indexId":"70201965","displayToPublicDate":"2019-01-16T16:03:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"The 4.2 ka event, ENSO, and coral reef development","docAbstract":"Variability of sea-surface temperature related to shifts in the mode of the El Niño–Southern Oscillation (ENSO) has been implicated as a possible forcing mechanism for the global-scale changes in tropical and subtropical precipitation known as the 4.2 ka event. We review records of coral reef development and paleoceanography from the tropical eastern Pacific (TEP) to evaluate the potential impact of the 4.2 ka event on coral reefs. Our goal is to identify the regional climatic and oceanographic drivers of a 2500-year shutdown of vertical reef accretion in the TEP after 4.2 ka. The 2500-year hiatus represents ∼40 % of the Holocene history of reefs in the TEP and appears to have been tied to increased variability of ENSO. When ENSO variability abated approximately 1.7–1.6 ka, coral populations recovered and vertical accretion of reef framework resumed apace. There is some evidence that the 4.2 ka event suppressed coral growth and reef accretion elsewhere in the Pacific Ocean as well. Although the ultimate causality behind the global 4.2 ka event remains elusive, correlations between shifts in ENSO variability and the impacts of the 4.2 ka event suggest that ENSO could have played a role in climatic changes at that time, at least in the tropical and subtropical Pacific. We outline a framework for testing hypotheses of where and under what conditions ENSO may be expected to have impacted coral reef environments around 4.2 ka. Although most studies of the 4.2 ka event have focused on terrestrial environments, we suggest that understanding the event in marine systems may prove to be the key to deciphering its ultimate cause.
","language":"English","publisher":"EGU","doi":"10.5194/cp-15-105-2019","usgsCitation":"Toth, L., and Aronson, R.B., 2019, The 4.2 ka event, ENSO, and coral reef development: Climate of the Past, v. 15, p. 105-119, https://doi.org/10.5194/cp-15-105-2019.","productDescription":"15 p.","startPage":"105","endPage":"119","ipdsId":"IP-100232","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-15-105-2019","text":"Publisher Index Page"},{"id":360988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":756357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":756358,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215986,"text":"70215986 - 2019 - Fire legacies in eastern ponderosa pine forests","interactions":[],"lastModifiedDate":"2020-11-03T13:59:00.469885","indexId":"70215986","displayToPublicDate":"2019-01-16T07:49:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Fire legacies in eastern ponderosa pine forests","docAbstract":"Disturbance legacies structure communities and ecological memory, but due to increasing changes in disturbance regimes, it is becoming more difficult to characterize disturbance legacies or determine how long they persist. We sought to quantify the characteristics and persistence of material legacies (e.g., biotic residuals of disturbance) that arise from variation in fire severity in an eastern ponderosa pine forest in North America. We compared forest stand structure and understory woody plant and bird community composition and species richness across unburned, low‐, moderate‐, and high‐severity burn patches in a 27‐year‐old mixed‐severity wildfire that had received minimal post‐fire management. We identified distinct tree densities (high: 14.3 ± 7.4 trees per ha, moderate: 22.3 ± 12.6, low: 135.3 ± 57.1, unburned: 907.9 ± 246.2) and coarse woody debris cover (high: 8.5 ± 1.6% cover per 30 m transect, moderate: 4.3 ± 0.7, low: 2.3 ± 0.6, unburned: 1.0 ± 0.4) among burn severities. Understory woody plant communities differed between high‐severity patches, moderate‐ and low‐severity patches, and unburned patches (all p < 0.05). Bird communities differed between high‐ and moderate‐severity patches, low‐severity patches, and unburned patches (all p < 0.05). Bird species richness varied across burn severities: low‐severity patches had the highest (5.29 ± 1.44) and high‐severity patches had the lowest (2.87 ± 0.72). Understory woody plant richness was highest in unburned (5.93 ± 1.10) and high‐severity (5.07 ± 1.17) patches, and it was lower in moderate‐ (3.43 ± 1.17) and low‐severity (3.43 ± 1.06) patches. We show material fire legacies persisted decades after the mixed‐severity wildfire in eastern ponderosa forest, fostering distinct structures, communities, and species in burned versus unburned patches and across fire severities. At a patch scale, eastern and western ponderosa system responses to mixed‐severity fires were consistent.
The South Pacific Convergence Zone (SPCZ) is the Southern Hemisphere’s largest precipitation feature supplying freshwater to 11 million people. Despite its significance, little is known about the location and intensity of SPCZ precipitation prior to instrumental records, hindering attempts to predict precipitation changes in a warming world. Here we use sedimentary molecular fossils to establish a tool for extending the historical record of precipitation. Freshwater lake sediments and water samples were collected from 30 lakes that span a 4.6 mm d−1 range in precipitation rates from the Global Precipitation Climatology Project (GPCP). δ2Hlakewater values from 29 lakes ranged from −29 to +23‰ and were inversely correlated (r = −0.51, p < 0.001) with precipitation rates, likely due to the combination of the amount of precipitation plus evaporation. δ2H values of the dinoflagellate sterol dinosterol in surficial sediments from 21 lakes ranged from −316‰ in the Solomon Islands to −245‰ in French Polynesia. These δ2Hdinosterolvalues were significantly correlated (r = 0.71, p < 0.001) with δ2Hlakewaterand inversely correlated (r = −0.77, p < 0.001) with mean annual precipitation rates with a sensitivity of −12.1 ± 2.6‰ (mm d−1)−1. Fractionation between dinosterol and lake water (εdinosterol/lakewater) decreased at the driest lake sites (r = − 0.70, p < 0.001). The empirical relationship between δ2Hdinosterol and GPCP rainfall, although indirect, provides a means of quantitatively reconstructing past precipitation in the SPCZ region with an uncertainty of less than 3.1 mm d−1, which compares favorably to the 1.5 mm d−1 uncertainty for the satellite-gauge based GPCP precipitation data.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2018.10.028","usgsCitation":"Maloney, A.E., Nelson, D.B., Richey, J.N., Prebble, M., Sear, D.A., Hassall, J.D., Langdon, P.G., Croudace, I.W., Zawadzki, A., and Sachs, J.P., 2019, Reconstructing precipitation in the tropical South Pacific from dinosterol 2H/1H ratios in lake sediment: Geochimica et Cosmochimica Acta, v. 245, p. 190-206, https://doi.org/10.1016/j.gca.2018.10.028.","productDescription":"17 p.","startPage":"190","endPage":"206","ipdsId":"IP-101195","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467994,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2018.10.028","text":"Publisher Index Page"},{"id":361167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"245","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maloney, Ashley E.","contributorId":213177,"corporation":false,"usgs":false,"family":"Maloney","given":"Ashley","email":"","middleInitial":"E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":757044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Daniel B.","contributorId":213178,"corporation":false,"usgs":false,"family":"Nelson","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":38710,"text":"University of Basel","active":true,"usgs":false}],"preferred":false,"id":757045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prebble, Matthew","contributorId":213179,"corporation":false,"usgs":false,"family":"Prebble","given":"Matthew","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":757046,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sear, David A.","contributorId":213180,"corporation":false,"usgs":false,"family":"Sear","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":757047,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hassall, Jonathan D.","contributorId":213181,"corporation":false,"usgs":false,"family":"Hassall","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":757048,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Langdon, Peter G.","contributorId":213182,"corporation":false,"usgs":false,"family":"Langdon","given":"Peter","email":"","middleInitial":"G.","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":757049,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Croudace, Ian W.","contributorId":213183,"corporation":false,"usgs":false,"family":"Croudace","given":"Ian","email":"","middleInitial":"W.","affiliations":[{"id":37955,"text":"University of Southampton","active":true,"usgs":false}],"preferred":false,"id":757050,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zawadzki, Atun","contributorId":213184,"corporation":false,"usgs":false,"family":"Zawadzki","given":"Atun","email":"","affiliations":[{"id":38711,"text":"Australian Nuclear Science an Technology Organization","active":true,"usgs":false}],"preferred":false,"id":757051,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sachs, Julian P.","contributorId":174047,"corporation":false,"usgs":false,"family":"Sachs","given":"Julian","email":"","middleInitial":"P.","affiliations":[{"id":27348,"text":"School of Oceanography, University of Washington, Seattle, WA 98195, USA","active":true,"usgs":false}],"preferred":false,"id":757052,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ]}