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":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","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":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","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":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","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}]}} ,{"id":70215991,"text":"70215991 - 2019 - Space use, forays, and habitat selection in California Spotted Owls (Strix occidentalis occidentalis): New insights from high resolution GPS tracking","interactions":[],"lastModifiedDate":"2020-11-02T16:02:27.176921","indexId":"70215991","displayToPublicDate":"2019-01-15T09:52:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Space use, forays, and habitat selection in California Spotted Owls (Strix occidentalis occidentalis): New insights from high resolution GPS tracking","docAbstract":"Our current understanding of the relationship between imperiled species and forest management can benefit from global positioning system (GPS) technologies. Fauna of lateseral stage forests have historically been difficult to detect and track in rugged terrain, leading to challenges in movement characterization and conservation. We investigated movement of California Spotted Owls (Strix occidentalis occidentalis) using automated GPS loggers affixed to 15 owls in the northern Sierra Nevada, California. We used >17,000 locations from individual owls to characterize homerange size, movement distances, and roosting and foraging habitat selection at four spatio-temporal scales (landscape, home range, foray, nightly) during the breeding season (April–August). Additionally, we assessed owl use of Protected Activity Centers (PACs), which are designated by the U.S.D.A. Forest Service to protect nesting and roosting habitat. Our results corroborated some previous findings about habitat requirements of California Spotted Owls, while also revealing new nuances in space use and habitat selection. Roosting and foraging owls selected stands with high canopy cover and large trees at multiple spatio-temporal scales, with foraging owls showing strongest selection at the largest (landscape) scale investigated. Although owls selected for PACs while foraging and roosting, PACs protected less than one quarter of foraging space use (volume of use) and fewer than half of observed roosts during the breeding season. Female owl home ranges were double the size of male home ranges, and distances travelled from the nest by females were 1.3 times greater than distances travelled by males, with non-breeding females travelling farthest and visiting up to six PACs during a single breeding season. Foraying behavior of this sort has not been documented previously in California Spotted Owls. Our findings support protection of later seral stage forest attributes for roosting and foraging California Spotted Owls. Given their selection for later seral forest attributes, strongest evidence of foraging habitat selection at the landscape scale, long distances travelled by owls and limited habitat protection afforded by PACs, habitat connectivity across the landscape is likely an important component for owl conservation, and distribution of current protected areas may be inadequate for this wide-ranging species.
The Atastra Creek siliceous hot spring deposit, or sinter, occurs in the Paramount-Bald Peak alteration zone, due north of the Bodie precious metals mining district in the Miocene Bodie Hills volcanic field, California and Nevada, U.S.A. Distinctive features include its geomorphically intact geyser vent mounds, the presence of growth-fault-stepped sinter terraces that developed westward along a NNW trending fault, and atypical Hg, Sb and As concentrations. High-temperature (>75 °C), subaerial, proximal apron sinter occurs in two settings – (1) radiating botryoidal geyserite in vent mounds and (2) bedded geyserite (columnar, nodular, size-sorted geyser eggs) intercalated with mid- to low-temperature (<60 °C), middle to distal apron terrace sinter. The active geyser vent mounds migrated from south to north across the apron terrace through time. A newly recognized, visually striking type of sinter – termed silica infiltrate herein – formed directly beneath the subaerial geyserite deposits. It is characterized by mainly parallel, thin, irregular beds of white silica with narrow borders of dark blue-gray silica, as well as swirly to globular white silica, all chaotically linked together by silica ‘necks’ and ‘bridges’. The silica infiltrate permeates the pre-existing sinter, and is interpreted to represent super-heated fluid injections into the immediately overlying geyser vent mounds and pools. The adjacent sinter sheets preserve fluid-flow directions of warm-water channels that traversed the discharge apron, including microbial streamer fabric and wavy laminated sinter with flattened bubbles. More distal sinter textures are recorded by rimmed terracettes with mammillated and palisade microbial fabrics and rare, warm pool-related stromatolites. However, plants are absent, probably due to the high metalloids, in particular As. Post-depositional events include an inferred hydrothermal eruption breccia and an interpreted drop in the water table accompanied by incursion of steam acid condensate, as evidenced by pervasive hydrothermal alteration of the Atastra Creek deposits. Hence, the well-exposed sedimentary facies distributions, well-preserved geomorphology, and stratigraphic and structural relationships together allow an unusually complete, paleoenvironmental reconstruction of the Atastra Creek paleohydrothermal deposit.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2018.12.006","usgsCitation":"Campbell, K.A., Guido, D.M., John, D.A., Vikre, P., Rhys, D., and Hamilton, A., 2019, The Miocene Atastra Creek sinter (Bodie Hills volcanic field, California and Nevada): 4D evolution of a geomorphically intact siliceous hot spring deposit: Journal of Volcanology and Geothermal Research, v. 370, p. 65-81, https://doi.org/10.1016/j.jvolgeores.2018.12.006.","productDescription":"17 p.","startPage":"65","endPage":"81","ipdsId":"IP-102174","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":502590,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11336/104267","text":"External Repository"},{"id":426119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"370","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell, Kathleen A. 0000-0002-4815-2519","orcid":"https://orcid.org/0000-0002-4815-2519","contributorId":334434,"corporation":false,"usgs":false,"family":"Campbell","given":"Kathleen","email":"","middleInitial":"A.","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":895630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guido, Diego M. 0000-0003-4696-5644","orcid":"https://orcid.org/0000-0003-4696-5644","contributorId":334435,"corporation":false,"usgs":false,"family":"Guido","given":"Diego","email":"","middleInitial":"M.","affiliations":[{"id":80146,"text":"Universidad Nacional de La Plata, La Plata, Argentina","active":true,"usgs":false}],"preferred":false,"id":895631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vikre, Peter 0000-0001-7895-5972","orcid":"https://orcid.org/0000-0001-7895-5972","contributorId":203922,"corporation":false,"usgs":true,"family":"Vikre","given":"Peter","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895633,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rhys, David","contributorId":334437,"corporation":false,"usgs":false,"family":"Rhys","given":"David","email":"","affiliations":[{"id":12586,"text":"Consultant","active":true,"usgs":false}],"preferred":false,"id":895634,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, Ayrton","contributorId":334438,"corporation":false,"usgs":false,"family":"Hamilton","given":"Ayrton","email":"","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":895635,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263892,"text":"70263892 - 2019 - An investigation of seismicity induced by hydraulic fracturing in the Sichuan basin of China based on data from a temporary seismic network","interactions":[],"lastModifiedDate":"2025-02-27T15:35:39.361512","indexId":"70263892","displayToPublicDate":"2019-01-15T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"An investigation of seismicity induced by hydraulic fracturing in the Sichuan basin of China based on data from a temporary seismic network","docAbstract":"Hydraulic fracturing has been inferred to trigger the majority of injection‐induced seismicity in the Zhaotong and Changning shale gas field, Sichuan basin of China, in contrast to the Midwestern United States, where massive wastewater disposal has been the dominant triggering mechanism. More than 15,000 earthquakes, with magnitudes ranging up to Mw 4.7, were recorded by a temporary network in the Sichuan basin for three years, with a completeness magnitude of ML 1.1. A catalog of earthquakes relocated with code tomoDD, combined with comprehensive injection data during an eight day period, shows that the earthquakes were highly correlated spatiotemporally with hydraulic fracturing activities mostly from a single well pad. Three ML≥4.0 events occurred during hydraulic fracturing operations from 12 to 19 January 2017, followed by the fourth and largest event, with moment magnitude (Mw) 4.7, on 28 January. The hypocenters of the four largest events were located in dolomite of Cambrian age, between a shale gas reservoir and the top of the crystalline basement rocks. This was found to be similar to 60% of the smaller earthquakes in this cluster, at depths from 2.5 to 4.0 km.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180310","usgsCitation":"Meng, L., McGarr, A.F., Zhou, L., and Zang, Y., 2019, An investigation of seismicity induced by hydraulic fracturing in the Sichuan basin of China based on data from a temporary seismic network: Bulletin of the Seismological Society of America, v. 109, no. 1, p. 348-357, https://doi.org/10.1785/0120180310.","productDescription":"10 p.","startPage":"348","endPage":"357","ipdsId":"IP-101593","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Sichuan 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Lingyuan 0000-0001-7267-7625","orcid":"https://orcid.org/0000-0001-7267-7625","contributorId":351561,"corporation":false,"usgs":true,"family":"Meng","given":"Lingyuan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGarr, Arthur F. 0000-0001-9769-4093 mcgarr@usgs.gov","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":3178,"corporation":false,"usgs":true,"family":"McGarr","given":"Arthur","email":"mcgarr@usgs.gov","middleInitial":"F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":928926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Longquan","contributorId":351562,"corporation":false,"usgs":false,"family":"Zhou","given":"Longquan","affiliations":[{"id":84008,"text":"China Earthquake Networks 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conflicts with expectations from fishery-independent surveys","docAbstract":"Stock assessments of Walleyes Sander vitreus in Lake Erie rely on a combination of suspended and bottom overnight gill‐net surveys to provide population and demographic information. However, the assumption that Walleyes undertake diel vertical migrations and become available to the suspended gill nets at night has never been validated. To understand how vertical habitat use affects the availability of Walleyes to fishery‐independent surveys, we compared individual behaviors observed by means of acoustic depth telemetry tags (20 individuals; 2013–2016) with catches in paired suspended and bottom gill‐net sets (273 paired sets; 2013–2016) used by management agencies. In contrast to our expectations and observations in other lakes, the mean depths for Walleyes most often occurred in the lower one‐half to one‐third of the water column, and at lake depths <25 m the fish tended to be close to the bottom. The relationship between fish and lake depth was dependent on year and season. At lake depths >15 m, Walleyes were found at shallower depths during stratified periods (i.e., summer) than during unstratified periods (autumn). They were also found at shallower depths in 2015 and 2016 than in 2013 and 2014. In paired autumn gill‐net surveys, (1) the overall proportion of Walleye catch was nearly equal in suspended and bottom gill nets and (2) the proportion of the catch in suspended gill nets declined with fish length. The pattern of decline was dependent on how deep the suspended net was fished and the year in which the data were collected. These results provide evidence that the suspended gill‐net surveys currently being used to assess Walleye demographics in Lake Erie are biased toward the capture small Walleyes, while bottom nets are biased toward the capture of large ones. Future telemetry investigations will be needed to understand whether these biases reflect differences in the depth of habitat between small and large Walleyes.","language":"English","doi":"10.1002/tafs.10150","usgsCitation":"Ann Marie Gorman, Kraus, R.T., Gutowsky, L., Vandergoot, C., Yingming Zhao, Knight, C., Faust, M., Hayden, T., and Charles Krueger, 2019, Vertical habitat use of adult Walleye conflicts with expectations from fishery-independent surveys: Transactions of the American Fisheries Society, v. 148, no. 3, p. 592-604, https://doi.org/10.1002/tafs.10150.","productDescription":"13 p.","startPage":"592","endPage":"604","ipdsId":"IP-097146","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":467995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10150","text":"Publisher Index Page"},{"id":362144,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","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 -84.19921875,\n 41.27780646738183\n ],\n [\n -78.75,\n 41.27780646738183\n ],\n [\n -78.75,\n 43.068887774169625\n ],\n [\n -84.19921875,\n 43.068887774169625\n ],\n [\n -84.19921875,\n 41.27780646738183\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"148","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ann Marie Gorman","contributorId":214228,"corporation":false,"usgs":false,"family":"Ann Marie Gorman","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759401,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":759400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutowsky, Lee","contributorId":214229,"corporation":false,"usgs":false,"family":"Gutowsky","given":"Lee","email":"","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":759402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":759403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yingming Zhao","contributorId":140825,"corporation":false,"usgs":false,"family":"Yingming Zhao","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knight, Carey","contributorId":214230,"corporation":false,"usgs":false,"family":"Knight","given":"Carey","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Faust, Matt","contributorId":214231,"corporation":false,"usgs":false,"family":"Faust","given":"Matt","email":"","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":759406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hayden, Todd","contributorId":214232,"corporation":false,"usgs":false,"family":"Hayden","given":"Todd","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":759407,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Charles Krueger","contributorId":203268,"corporation":false,"usgs":false,"family":"Charles Krueger","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":759408,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70205059,"text":"70205059 - 2019 - Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends","interactions":[],"lastModifiedDate":"2019-08-29T09:01:06","indexId":"70205059","displayToPublicDate":"2019-01-14T08:59:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5038,"text":"International Journal of Climate Change: Impacts and Responses","seriesDoiName":"10.18848/1835-7156/CGP","printIssn":"1835-7156","active":true,"publicationSubtype":{"id":10}},"title":"Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends","docAbstract":"Droughts in Tanzania pose challenges to agriculture, water resources, and hydropower production, all of which impact livelihoods. Tanzania experienced below average precipitation during 1999-2014 during two important seasons: December to February (DJF) in the south and during March to June (MAMJ) in the northeast. We explore DJF and MAMJ precipitation in the areas with drying trends and examine their relationships with anomalous sea surface temperatures (SST) in the Indo-Pacific and corresponding circulation patterns. It is found that at seasonal time scales, precipitation in DJF and MAMJ trend areas appears inversely related to diabatic forcing in the equatorial Pacific. The dominant influence for droughts in DJF is from eastern Pacific SST while for droughts in MAMJ it is from West Pacific SST. A bivariate regression model with West Pacific and Niño3.4 region SST as predictors is found to recreate multidecadal DJF variability after the 1950s and the extreme drying in MAMJ during the 2000s. The regression model coefficients also indicate differential eastern vs. western Pacific forcing for DJF vs. MAMJ. Thus we suggest that recent La Niña-like conditions, characterized by an enhanced Pacific SST gradient due to cooling in the eastern Pacific and warming in the western Pacific, played a substantial role in Tanzania’s recent multi-season drying trends. SST change scenarios (difference between 2023-2037 and 2000-2014 means) based on CMIP5 projections and observed trends illustrate the uncertainty about future precipitation outcomes and also the potential implications of contrasting linkages to eastern vs. western Pacific SSTs. These scenarios are mainly optimistic for the DJF southern Tanzania trend area, because it appears dominated by Niño3.4 cooling at both seasonal and decadal time scales. Conversely, our scenarios are quite pessimistic for the MAMJ northeastern Tanzania trend area, because we find a dominant negative influence of warming West Pacific SST.","language":"English","publisher":"Wiley","doi":"10.1002/joc.6003","usgsCitation":"Harrison, L., Funk, C., McNally, A., Shukla, S., and Husak, G., 2019, Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends: International Journal of Climate Change: Impacts and Responses, v. 39, no. 6, p. 3057-3075, https://doi.org/10.1002/joc.6003.","productDescription":"19 p.","startPage":"3057","endPage":"3075","ipdsId":"IP-101903","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/joc.6003","text":"Publisher Index Page"},{"id":367045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367039,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1002/joc.6003"}],"country":"Tanzania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[33.90371,-0.95],[34.07262,-1.05982],[37.69869,-3.09699],[37.7669,-3.67712],[39.20222,-4.67677],[38.74054,-5.90895],[38.79977,-6.47566],[39.44,-6.84],[39.47,-7.1],[39.19469,-7.7039],[39.25203,-8.00781],[39.18652,-8.48551],[39.53574,-9.11237],[39.9496,-10.0984],[40.31659,-10.3171],[39.521,-10.89688],[38.42756,-11.2852],[37.82764,-11.26879],[37.47129,-11.56876],[36.77515,-11.59454],[36.51408,-11.72094],[35.3124,-11.43915],[34.55999,-11.52002],[34.28,-10.16],[33.94084,-9.69367],[33.73972,-9.41715],[32.75938,-9.2306],[32.19186,-8.93036],[31.55635,-8.76205],[31.15775,-8.59458],[30.74,-8.34],[30.2,-7.08],[29.62,-6.52],[29.41999,-5.94],[29.51999,-5.41998],[29.34,-4.49998],[29.75351,-4.45239],[30.11632,-4.09012],[30.50554,-3.56858],[30.75224,-3.35931],[30.74301,-3.03431],[30.52766,-2.80762],[30.46967,-2.41383],[30.75831,-2.28725],[30.81613,-1.69891],[30.4191,-1.13466],[30.76986,-1.01455],[31.86617,-1.02736],[33.90371,-0.95]]]},\"properties\":{\"name\":\"United Republic of Tanzania\"}}]}","volume":"39","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Laura","contributorId":192382,"corporation":false,"usgs":false,"family":"Harrison","given":"Laura","email":"","affiliations":[],"preferred":false,"id":769796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":769795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNally, Amy","contributorId":145810,"corporation":false,"usgs":false,"family":"McNally","given":"Amy","email":"","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shukla, Shraddhanand","contributorId":145841,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16255,"text":"Climate Hazards Group University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":769798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Husak, Gregory","contributorId":145811,"corporation":false,"usgs":false,"family":"Husak","given":"Gregory","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":769799,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}