Re-examination of previously published dissolved iron time-series data from Ocean Station Papa in the central Gulf of Alaska (GoA) reveals 33-70% increases in the dissolved iron inventories occurring between September and February of successive years, implying a source of Fe to this region during autumn or early winter. Because I can virtually rule out many possible iron sources at this time of year, I suggest Alaskan glacial dust is the likely iron source. Large plumes of such dust are known to be generated regularly in the autumn by anomalous offshore winds and channelled through mountain gaps, simultaneously from several locations spanning ∼1000 km of the northern Gulf of Alaska coastline. Large dust flux events occur when below-freezing, low-humidity air temperatures persist for many days during the autumn. I suggest that existing state-of-the-art global dust models fail to reproduce this Alaskan dust flux because the model spatial resolution is too coarse to resolve the high winds through the narrow mountain gaps that generate the dust. Future work that could help to confirm this Fe source to the central GoA includes time-series profiles of iron concentrations, and ancillary information from sensor-equipped profiling floats. If this mechanism of Fe supply to the central GoA were confirmed, it would imply this Alaskan dust is transported ≥ 1100 km from the coast, more than twice as far as has been visually documented from satellite observations.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JG006323","usgsCitation":"Crusius, J., 2021, Dissolved Fe supply to the central Gulf of Alaska is inferred to be derived from Alaskan glacial dust that is not resolved by dust transport models: JGR-Biogeosciences, v. 126, e2021JG006323, 13 p., https://doi.org/10.1029/2021JG006323.","productDescription":"e2021JG006323, 13 p.","ipdsId":"IP-102176","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":385832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.28125,\n 51.39920565355378\n ],\n [\n -131.1328125,\n 51.39920565355378\n ],\n [\n -131.1328125,\n 59.5343180010956\n ],\n [\n -153.28125,\n 59.5343180010956\n ],\n [\n -153.28125,\n 51.39920565355378\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationDate":"2021-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":816240,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220247,"text":"ofr20211003 - 2021 - Sediment characteristics of northwestern Wisconsin’s Nemadji River, 1973–2016","interactions":[],"lastModifiedDate":"2021-05-19T11:51:06.797744","indexId":"ofr20211003","displayToPublicDate":"2021-05-18T16:16:58","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1003","displayTitle":"Sediment Characteristics of Northwestern Wisconsin’s Nemadji River, 1973–2016","title":"Sediment characteristics of northwestern Wisconsin’s Nemadji River, 1973–2016","docAbstract":"In 2015–16, a comparison study of stream sediment collection techniques was done for a U.S. Geological Survey streamgage on the Nemadji River near South Superior, Wisconsin (U.S. Geological Survey station number 04024430) to provide an adjustment factor for comparing suspended-sediment rating curves for two historical periods 1973–86 and 2006–16. During 1973–1986, the U.S. Geological Survey used the equal-width-increment technique to collect suspended-sediment concentration data (EWI SSC). The Wisconsin Department of Natural Resources and Minnesota Pollution Control Agency collected grab samples for total suspended solids (grab TSS) concentration starting in 2006 and continuing beyond 2016. In addition to the comparison study of suspended-sediment concentrations, bedload and bed material samples were collected in 2015–16, and the modified Einstein procedure was run to further characterize total sediment loads. The 2015–16 study indicated that the EWI SSC and grab TSS concentrations were different, but not as much as expected, especially on the high end where grab TSS concentrations were sometimes higher than EWI SSC concentrations, possibly due to a combination of a high percentage of fines in suspension and higher concentrations in the center of the channel than the margins. The 2015–16 measured bedload made up a small percentage of total sediment load, and bedload and streambed particle sizes are 90 to 100 percent sand sized or smaller. The relative proportion of measured bedload to total load decreased with increased streamflow, and for streamflows greater than 1,800 cubic feet per second, the suspended load made up 98 percent of the total load. Calculated 2015–16 instantaneous total sediment loads from the modified Einstein procedure were up to 70 percent of the measured loads for flows less than 1,000 cubic feet per second and near or more than 100 percent for flows greater than 1,000 cubic feet per second. The sediment rating curve developed for the 2006–16 adjusted grab TSS data had a similar slope but a lower intercept than its 1973–86 EWI SSC counterpart, indicating that for a given streamflow, suspended-sediment concentrations were lower for 2006–16 compared to 1973–86. The negative offset equates to estimates of annual suspended-sediment loads in 2006–16 being on average 87 percent of the 1973–86 loads. Over the period 2009–16, annual suspended-sediment loads ranged from a low of about 21,000 tons per year in 2015 to a high of 167,000 tons per year in 2012 with a mean of 85,000 tons per year. However, reductions in suspended-sediment concentrations are likely obscured by large loads during years with flooding.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211003","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Fitzpatrick, F.A., 2021, Sediment characteristics of northwestern Wisconsin’s Nemadji River, 1973–2016: U.S. Geological Survey Open-File Report 2021–1003, 27 p., https://doi.org/10.3133/ofr20211003.","productDescription":"Report: viii, 27 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-085024","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385361,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FX0X6Y","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Selected sediment data and results from regression models, modified Einstein Procedure, and loads estimation for the Nemadji River, 1973–2016"},{"id":385360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1003/ofr20211003.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1003"},{"id":385359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1003/coverthb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","otherGeospatial":"Nemadji River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.55157470703125,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.38672781370433\n ],\n [\n -92.01599121093749,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.65697731621612\n ],\n [\n -92.55157470703125,\n 46.38672781370433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Waterborne contaminants were monitored in 69 tributaries of the Laurentian Great Lakes in 2010 and 2014 using semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS). A risk-based screening approach was used to prioritize chemicals and chemical mixtures, identify sites at greatest risk for biological impacts, and identify potential hazards to monitor at those sites. Analyses included 185 chemicals (143 detected) including polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, fire retardants, pharmaceuticals, and fragrances. Hazard quotients were calculated by dividing detected concentrations by biological effect concentrations reported in the ECOTOX Knowledgebase (toxicity quotients) or ToxCast database (exposure–activity ratios [EARs]). Mixture effects were estimated by summation of EAR values for chemicals that influence ToxCast assays with common gene targets. Nineteen chemicals—atrazine, N,N-diethyltoluamide, di(2-ethylhexyl)phthalate, dl-menthol, galaxolide, p-tert-octylphenol, 3 organochlorine pesticides, 3 PAHs, 4 pharmaceuticals, and 3 phosphate flame retardants—had toxicity quotients >0.1 or EARs for individual chemicals >10–3 at 10% or more of the sites monitored. An additional 4 chemicals (tributyl phosphate, triethyl citrate, benz[a]anthracene, and benzo[b]fluoranthene) were present in mixtures with EARs >10–3. To evaluate potential apical effects and biological endpoints to monitor in exposed wildlife, in vitro bioactivity data were compared to adverse outcome pathway gene ontology information. Endpoints and effects associated with endocrine disruption, alterations in xenobiotic metabolism, and potentially neuronal development would be relevant to monitor at the priority sites. The EAR threshold exceedance for many chemical classes was correlated with urban land cover and wastewater effluent influence, whereas herbicides and fire retardants were also correlated to agricultural land cover. Environ Toxicol Chem 2021;40:2165–2182. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Increasing the resilience of coastal communities while decreasing the risk to them are key to the continued inhabitance and sustainability of these areas. Low-lying coral reef-lined islands are experiencing storm wave-driven flood events that currently strike with little to no warning. These events are occurring more frequently and with increasing severity. There is a need along the world’s coral reef-lined coasts for a tool that can forecast the timing and severity of wave-driven flooding events. Without this tool, coastal communities are vulnerable to:
loss of life from drowning • loss of, and damage to, property and infrastructure • decreasing viability of communities via loss of, and damage to crops, fishing (via decreased water quality and wave-damaged reefs), and freshwater resources • reduction of livable land due to increased erosion and salt intrusion. The currently available tools were developed for sandy shorelines and do not accurately predict wave-driven flooding on reef-lined coasts, leaving inhabitants without accurate and timely warnings. In addition, the flood models that do exist for reef-lined coasts have only been implemented on a small number of areas throughout the world because running these models is costly and requires a high level of computing power. Using these existing models and techniques to generate high-resolution forecasts for wave-driven flooding for all reef-lined coasts would cost approximately US$1 billion. To remedy this issue, an international team associated with the GEO Blue Planet initiative is working to develop a wave-driven flood-forecasting early-warning system (EWS) for coral reef-lined coasts known as WaveFoRCE. The system aims to provide all nations and people living on a coral reef-lined coast anywhere in the world with an up to 7.5-day forecast of storm wave-driven flood events.
","largerWorkType":{"id":25,"text":"Newsletter"},"largerWorkTitle":"Environment Coastal & Offshore (ECO)","language":"English","publisher":"United Nations","usgsCitation":"Skirving, W., Storlazzi, C.D., and Smail, E.A., 2021, Wave-driven flood-forecasting on reef-lined coasts early warning system (WaveFoRCE), p. 144-147.","productDescription":"4 p.","startPage":"144","endPage":"147","ipdsId":"IP-127710","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386977,"type":{"id":15,"text":"Index Page"},"url":"https://www.oceandecade.org/news/128/ECO-Magazine--special-digital-issue-on-the-Ocean-Decade-May-2021"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skirving, William","contributorId":224303,"corporation":false,"usgs":false,"family":"Skirving","given":"William","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":818745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smail, Emily A","contributorId":217219,"corporation":false,"usgs":false,"family":"Smail","given":"Emily","email":"","middleInitial":"A","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":818747,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70220611,"text":"70220611 - 2021 - Pilot-scale expanded assessment of inorganic and organic tapwater exposures and predicted effects in Puerto Rico, USA","interactions":[],"lastModifiedDate":"2021-06-01T17:49:41.562885","indexId":"70220611","displayToPublicDate":"2021-05-18T06:57:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"Pilot-scale expanded assessment of inorganic and organic tapwater exposures and predicted effects in Puerto Rico, USA","docAbstract":"A pilot-scale expanded target assessment of mixtures of inorganic and organic contaminants in point-of-consumption drinking water (tapwater, TW) was conducted in Puerto Rico (PR) to continue to inform TW exposures and corresponding estimations of cumulative human-health risks across the US. In August 2018, a spatial synoptic pilot assessment of than 524 organic, 37 inorganic, and select microbiological contaminant indicators was conducted in 14 locations (7 home; 7 commercial) across PR. A follow-up 3-day temporal assessment of TW variability was conducted in December 2018 at two of the synoptic locations (1 home, 1 commercial) and included daily pre- and post-flush samples. Concentrations of regulated and unregulated TW contaminants were used to calculate cumulative in vitro bioactivity ratios and Hazard Indices (HI) based on existing human-health benchmarks. Synoptic results confirmed that human exposures to inorganic and organic contaminant mixtures, which are rarely monitored together in drinking water at the point of consumption, occurred across PR and consisted of elevated concentrations of inorganic contaminants (e.g., lead, copper), disinfection byproducts (DBP), and to a lesser extent per/polyfluoroalkyl substances (PFAS) and phthalates. Exceedances of human-health benchmarks in every synoptic TW sample support further investigation of the potential cumulative risk to vulnerable populations in PR and emphasize the importance of continued broad characterization of drinking-water exposures at the tap with analytical capabilities that better represent the complexity of both inorganic and organic contaminant mixtures known to occur in ambient source waters. Such health-based monitoring data are essential to support public engagement in source water sustainability and treatment and to inform consumer point-of-use treatment decision making in PR and throughout the US.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.147721","usgsCitation":"Bradley, P., Padilla, I.Y., Romanok, K., Smalling, K., Focazio, M.J., Breitmeyer, S.E., Cardon, M.C., Conley, J.M., Evans, N., Givens, C.E., Gray, J., Gray, L., Hartig, P.C., Hladik, M.L., Higgins, C.P., Iwanowicz, L., Lane, R.F., Loftin, K.A., McCleskey, R., McDonough, C.A., Medlock-Kakaley, E., Meppelink, S.M., Weis, C.P., and Wilson, V.S., 2021, Pilot-scale expanded assessment of inorganic and organic tapwater exposures and predicted effects in Puerto Rico, USA: Environment International, v. 788, 147721, 14 p., https://doi.org/10.1016/j.scitotenv.2021.147721.","productDescription":"147721, 14 p.","ipdsId":"IP-110491","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":452219,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://europepmc.org/pmc/articles/PMC8504685","text":"Publisher Index Page"},{"id":436359,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EQS5CS","text":"USGS data release","linkHelpText":"Target-Chemical Concentration Results of Mixed-Organic/Inorganic Chemical Exposures in Puerto Rico Tapwater, 2017 to 2018"},{"id":385835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.3681640625,\n 17.727758609852284\n ],\n [\n -65.5224609375,\n 17.727758609852284\n ],\n [\n -65.5224609375,\n 18.625424540701264\n ],\n [\n -67.3681640625,\n 18.625424540701264\n ],\n [\n -67.3681640625,\n 17.727758609852284\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"788","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":221226,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816175,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Padilla, Ingrid Y. 0000-0001-8460-1679","orcid":"https://orcid.org/0000-0001-8460-1679","contributorId":258259,"corporation":false,"usgs":false,"family":"Padilla","given":"Ingrid","email":"","middleInitial":"Y.","affiliations":[{"id":52264,"text":"University of Puerto Rico-Mayaguez","active":true,"usgs":false}],"preferred":false,"id":816178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanok, Kristin M. 0000-0002-8472-8765","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":221227,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smalling, Kelly 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":221234,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true}],"preferred":true,"id":816179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Breitmeyer, Sara E. 0000-0003-0609-1559 sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":816180,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cardon, Mary C.","contributorId":190792,"corporation":false,"usgs":false,"family":"Cardon","given":"Mary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":816181,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Conley, Justin M.","contributorId":184086,"corporation":false,"usgs":false,"family":"Conley","given":"Justin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":816182,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Evans, Nicola","contributorId":184087,"corporation":false,"usgs":false,"family":"Evans","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":816183,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Givens, Carrie E. 0000-0003-2543-9610","orcid":"https://orcid.org/0000-0003-2543-9610","contributorId":247691,"corporation":false,"usgs":true,"family":"Givens","given":"Carrie","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816184,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":202726,"corporation":false,"usgs":true,"family":"Gray","given":"James L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":816185,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gray, L. 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Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. Blaine","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":816192,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"McDonough, Carrie A. 0000-0001-5152-8495","orcid":"https://orcid.org/0000-0001-5152-8495","contributorId":205664,"corporation":false,"usgs":false,"family":"McDonough","given":"Carrie","email":"","middleInitial":"A.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":816193,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Medlock-Kakaley, Elizabeth 0000-0001-5543-9262","orcid":"https://orcid.org/0000-0001-5543-9262","contributorId":248523,"corporation":false,"usgs":false,"family":"Medlock-Kakaley","given":"Elizabeth","email":"","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":816194,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Meppelink, Shannon M. 0000-0003-1294-7878","orcid":"https://orcid.org/0000-0003-1294-7878","contributorId":205653,"corporation":false,"usgs":true,"family":"Meppelink","given":"Shannon","email":"","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816195,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Weis, Christopher P. 0000-0002-7678-1080","orcid":"https://orcid.org/0000-0002-7678-1080","contributorId":205667,"corporation":false,"usgs":false,"family":"Weis","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":37136,"text":"NIH/NIEHS","active":true,"usgs":false}],"preferred":false,"id":816196,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Wilson, Vickie S. 0000-0003-1661-8481","orcid":"https://orcid.org/0000-0003-1661-8481","contributorId":184092,"corporation":false,"usgs":false,"family":"Wilson","given":"Vickie","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":816197,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70220501,"text":"70220501 - 2021 - Northern Madtom use of artificial reefs in the St. Clair–Detroit River System","interactions":[],"lastModifiedDate":"2021-10-18T14:02:12.325767","indexId":"70220501","displayToPublicDate":"2021-05-17T15:55:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Northern Madtom use of artificial reefs in the St. Clair–Detroit River System","docAbstract":"The St. Clair and Detroit rivers historically supported abundant fish populations. However, like many river systems, these rivers have been greatly altered through the creation of navigation channels and other anthropogenic disturbances, resulting in the loss of fish and wildlife habitat and declines in native fish populations. To ameliorate this environmental degradation, artificial fish spawning reefs were constructed in the St. Clair and Detroit rivers. One native species to potentially benefit from artificial reefs is the Northern Madtom Noturus stigmosus, a small ictalurid that is listed as endangered in the state of Michigan and the province of Ontario. Between 2016 and 2018, artificial reefs and nearby control sites were sampled in the St. Clair and Detroit rivers to compare the number of Northern Madtoms. In total, 171 Northern Madtoms were captured in 1,848 minnow traps with one of four bait types: cheese, dog food, worms, or control (no bait). Baited minnow traps successfully captured Northern Madtoms in the fast-flowing, deep water of the St. Clair–Detroit River system, and catch rates were significantly higher when traps were baited with worms. The number of Northern Madtoms captured was lower in the Detroit River than in the St. Clair River and increased with increasing water temperature and turbidity. Artificial reefs constructed in the St. Clair–Detroit River system are providing habitat for Northern Madtoms; however, use did not differ between reef sites and nearby control sites. This work provides insight regarding sampling strategies to target Northern Madtoms in large-river systems and highlights the importance of incorporating a temporal sampling strategy into survey design.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10614","usgsCitation":"Johnson, J., Chiotti, J., Briggs, A.S., Boase, J., Hessenauer, J., and Roseman, E., 2021, Northern Madtom use of artificial reefs in the St. Clair–Detroit River System: North American Journal of Fisheries Management, v. 41, no. S1, p. S42-S53, https://doi.org/10.1002/nafm.10614.","productDescription":"12 p.","startPage":"S42","endPage":"S53","ipdsId":"IP-119659","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":452226,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10614","text":"Publisher Index Page"},{"id":386094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"Detroit River, St Clair River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.07861328125,\n 42.037054301883806\n ],\n [\n -82.94677734375,\n 42.28950073090457\n ],\n [\n -82.4359130859375,\n 42.27730877423709\n ],\n [\n -82.3590087890625,\n 42.532844281713125\n ],\n [\n -82.4853515625,\n 42.56926437219384\n ],\n [\n -82.353515625,\n 43.01669737169671\n ],\n [\n -82.4359130859375,\n 43.04881979669318\n ],\n [\n -82.5677490234375,\n 42.70665956351041\n ],\n [\n -82.7764892578125,\n 42.73894375124377\n ],\n [\n -82.9742431640625,\n 42.55712670332118\n ],\n [\n -82.9742431640625,\n 42.382894009614034\n ],\n [\n -83.177490234375,\n 42.3016903282445\n ],\n [\n -83.2928466796875,\n 42.08191667830631\n ],\n [\n -83.22143554687499,\n 41.97582726102573\n ],\n [\n -83.07861328125,\n 42.037054301883806\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"S1","noUsgsAuthors":false,"publicationDate":"2021-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Jennifer","contributorId":258148,"corporation":false,"usgs":false,"family":"Johnson","given":"Jennifer","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chiotti, Justin A.","contributorId":26629,"corporation":false,"usgs":false,"family":"Chiotti","given":"Justin A.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Andrew S 0000-0002-0268-9310","orcid":"https://orcid.org/0000-0002-0268-9310","contributorId":215596,"corporation":false,"usgs":false,"family":"Briggs","given":"Andrew","email":"","middleInitial":"S","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boase, James C.","contributorId":38077,"corporation":false,"usgs":false,"family":"Boase","given":"James C.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":815842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hessenauer, Jan-Michael","contributorId":257795,"corporation":false,"usgs":false,"family":"Hessenauer","given":"Jan-Michael","email":"","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":815843,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":815844,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221150,"text":"70221150 - 2021 - Aeolian sediments in paleowetland deposits of the Las Vegas Formation","interactions":[],"lastModifiedDate":"2022-01-06T17:13:04.657899","indexId":"70221150","displayToPublicDate":"2021-05-17T08:21:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Aeolian sediments in paleowetland deposits of the Las Vegas Formation","docAbstract":"The Las Vegas Formation (LVF) is a well-characterized sequence of groundwater discharge (GWD) deposits exposed in and around the Las Vegas Valley in southern Nevada. Nearly monolithologic bedrock surrounds the valley, which provides an excellent opportunity to test the hypothesis that GWD deposits include an aeolian component. Mineralogical data indicate that the LVF sediments are dominated by carbonate minerals, similar to the local bedrock, but silicate minerals are also present. The median particle size is ~35 μm, consistent with modern dust in the region, and magnetic properties contrast strongly with local bedrock, implying an extralocal origin. By combining geochemical data from the LVF sediments and modern dust, we found that an average of ~25% of the LVF deposits were introduced by aeolian processes. The remainder consists primarily of authigenic groundwater carbonate as well as minor amounts of alluvial material and soil carbonate. Our data also show that the aeolian sediments accumulated in spring ecosystems in the Las Vegas Valley in a manner that was independent of both time and the specific hydrologic environment. These results have broad implications for investigations of GWD deposits located elsewhere in the southwestern U.S. and worldwide.
Recent studies have shown the oxygen isotopic composition (δ18O) of modern terrestrial gastropod shells is determined largely by the δ18O of precipitation. This implies that fossil shells could be used to reconstruct the δ18O of paleo-precipitation as long as the isotopic system, including the hydrologic pathways of the local watershed and the gastropod systematics, is well understood. In this study, we measured the δ18O values of 456 individual gastropod shells collected from paleowetland deposits in the San Pedro Valley, Arizona that range in age from ca. 29.1 to 9.8 ka. Isotopic differences of up to 2‰ were identified among the four taxa analyzed (Succineidae, Pupilla hebes, Gastrocopta tappaniana, and Vallonia gracilicosta), with Succineidae shells yielding the highest values and V. gracilicosta shells exhibiting the lowest values. We used these data to construct a composite isotopic record that incorporates these taxonomic offsets, and found shell δ18O values increased by ~4‰ between the last glacial maximum and early Holocene, which is similar to the magnitude, direction, and rate of isotopic change recorded by speleothems in the region. These results suggest the terrestrial gastropods analyzed here may be used as a proxy for past climate in a manner that is complementary to speleothems, but potentially with much greater spatial coverage.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2021.18","usgsCitation":"Rech, J.A., Pigati, J.S., Springer, K.B., Bosch, S., Nekola, J.C., and Yanes, Y., 2021, Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest: Quaternary Research, v. 104, p. 43-53, https://doi.org/10.1017/qua.2021.18.","productDescription":"11 p.","startPage":"43","endPage":"53","onlineOnly":"N","ipdsId":"IP-122769","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":436362,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EISWFZ","text":"USGS data release","linkHelpText":"Data release for Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest"},{"id":385834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, Nevada, New Mexico, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.1904296875,\n 42.032974332441405\n ],\n [\n -119.92675781249999,\n 39.16414104768742\n ],\n [\n -114.9169921875,\n 35.35321610123823\n ],\n [\n -114.9609375,\n 32.731840896865684\n ],\n [\n -111.005859375,\n 31.240985378021307\n ],\n [\n -108.19335937499999,\n 31.466153715024294\n ],\n [\n -108.1494140625,\n 31.80289258670676\n ],\n [\n -106.34765625,\n 31.728167146023935\n ],\n [\n -103.1396484375,\n 31.952162238024975\n ],\n [\n -103.095703125,\n 36.94989178681327\n ],\n [\n -102.041015625,\n 36.98500309285596\n ],\n [\n -102.0849609375,\n 41.0130657870063\n ],\n [\n -110.9619140625,\n 40.91351257612758\n ],\n [\n -110.9619140625,\n 42.00032514831621\n ],\n [\n -120.1904296875,\n 42.032974332441405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"104","noUsgsAuthors":false,"publicationDate":"2021-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Rech, Jason A.","contributorId":117323,"corporation":false,"usgs":false,"family":"Rech","given":"Jason","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":816199,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":816200,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":816201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bosch, Stephanie","contributorId":258260,"corporation":false,"usgs":false,"family":"Bosch","given":"Stephanie","email":"","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":816202,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nekola, Jeffrey C.","contributorId":26214,"corporation":false,"usgs":false,"family":"Nekola","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":816203,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yanes, Yurena","contributorId":197219,"corporation":false,"usgs":false,"family":"Yanes","given":"Yurena","email":"","affiliations":[],"preferred":false,"id":816204,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70222934,"text":"70222934 - 2021 - A U.S.-China EcoPartnership study of disturbed wetland vegetation in West Dongting Lake, China","interactions":[],"lastModifiedDate":"2021-09-14T16:10:27.356423","indexId":"70222934","displayToPublicDate":"2021-05-16T09:15:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9138,"text":"Environmental Progress and Sustainable Energy","active":true,"publicationSubtype":{"id":10}},"title":"A U.S.-China EcoPartnership study of disturbed wetland vegetation in West Dongting Lake, China","docAbstract":"West Dongting Lake in China is important for human livelihoods and habitat of migratory waterfowl and other wildlife. The waterway re-engineering and agriculture intensification have contributed to changes in hydrology, sediment, and vegetation on the floodplain. This paper describes an EcoPartnership program conducted by the U.S. Geological Survey, Wetland and Aquatic Research Center, and Beijing Forestry University. It focused on the development of a wetland ecosystem network in West Dongting Lake with technical support from the U.S. partner using a number of related studies to examine wetland vegetation dynamics from upstream to downstream along the tributaries. The results of U.S. studies showed that the regeneration potential of species might be altered by changes in climate and local environment, and seed bank depletion by germination may be a major conservation threat in a future with recurring droughts in swamps of the southeastern United States. In the monsoonal wetlands of West Dongting Lake, the soil seed bank could be used as a seed source for revegetation after hydrologic restoration with the introduction of certain foundational species and the removal of poplar plantations. Also, West Dongting Lake is at high ecological risk of mercury pollution. Wetland ecosystem monitoring may allow managers to use the information to predict effects of climate change, water level and flow changes on sedimentation, and to manage for desired vegetation to support waterfowl and ecosystem services. The cooperation of two countries through the EcoPartnership program is now well established and poised for extensive research projects in the future.
","language":"English","publisher":"American Institute of Chemical Engineers","doi":"10.1002/ep.13673","usgsCitation":"Lei, T., and Middleton, B., 2021, A U.S.-China EcoPartnership study of disturbed wetland vegetation in West Dongting Lake, China: Environmental Progress and Sustainable Energy, v. 40, no. 5, e13673, 6 p., https://doi.org/10.1002/ep.13673.","productDescription":"e13673, 6 p.","ipdsId":"IP-119570","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":387811,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"West Dongting Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 111.93695068359375,\n 28.71829174815013\n ],\n [\n 112.33245849609375,\n 28.71829174815013\n ],\n [\n 112.33245849609375,\n 29.1281717828162\n ],\n [\n 111.93695068359375,\n 29.1281717828162\n ],\n [\n 111.93695068359375,\n 28.71829174815013\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Lei, Ting","contributorId":245022,"corporation":false,"usgs":false,"family":"Lei","given":"Ting","affiliations":[{"id":40912,"text":"Beijing Forestry","active":true,"usgs":false}],"preferred":false,"id":820871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":820872,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222409,"text":"70222409 - 2021 - Calcium concentrations in the lower Columbia River, USA, are generally sufficient to support invasive bivalve spread","interactions":[],"lastModifiedDate":"2021-07-27T11:49:09.678999","indexId":"70222409","displayToPublicDate":"2021-05-16T06:45:18","publicationYear":"2021","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}},"title":"Calcium concentrations in the lower Columbia River, USA, are generally sufficient to support invasive bivalve spread","docAbstract":"Dissolved calcium concentration [Ca2+] is thought to be a major factor limiting the establishment and thus the spread of invasive bivalves such as zebra (Dreissena polymorpha) and quagga (Dreissena bugensis) mussels. We measured [Ca2+] in 168 water samples collected along ~100 river-km of the lower Columbia River, USA, between June 2018 and March 2020. We found [Ca2+] to range from 13 to 18 mg L−1 during summer/fall and 5 to 22 mg L−1 during the winter/spring. Previous research indicates that [Ca2+] < 12 mg L−1 are likely to limit the establishment and spread of invasive bivalves. Thus, our results indicate that there is sufficient Ca2+ in most locations in the lower Columbia River to support the establishment of invasive dreissenid mussels, which could join the already widespread and abundant Asian clam (Corbicula fluminea) as the newest invader to an already heavily invaded Columbia River ecosystem. These new data provide important measurements from a heretofore undersampled region of the Columbia River and have important implications for the spread of invasive bivalves and, by extension, the conservation and management of native species and ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3804","usgsCitation":"Bollens, S.M., Harrison, J., Kramer, M.G., Rollwagen-Bollens, G., Counihan, T., Robb-Chavez, S.B., and Nolan, S.T., 2021, Calcium concentrations in the lower Columbia River, USA, are generally sufficient to support invasive bivalve spread: River Research and Applications, v. 37, no. 6, p. 889-894, https://doi.org/10.1002/rra.3804.","productDescription":"6 p.","startPage":"889","endPage":"894","ipdsId":"IP-126009","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":387455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington, Oregon","otherGeospatial":"southern Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.96972656249999,\n 45.336701909968134\n ],\n [\n -117.8173828125,\n 45.336701909968134\n ],\n [\n -117.8173828125,\n 46.9502622421856\n ],\n [\n -123.96972656249999,\n 46.9502622421856\n ],\n [\n -123.96972656249999,\n 45.336701909968134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Bollens, Stephen M. 0000-0001-9214-9037","orcid":"https://orcid.org/0000-0001-9214-9037","contributorId":148958,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":819945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, John A.","contributorId":261389,"corporation":false,"usgs":false,"family":"Harrison","given":"John A.","affiliations":[{"id":52831,"text":"Washington State University - Vancouver, School of the Environment","active":true,"usgs":false}],"preferred":false,"id":819946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kramer, Marc G.","contributorId":261390,"corporation":false,"usgs":false,"family":"Kramer","given":"Marc","email":"","middleInitial":"G.","affiliations":[{"id":52831,"text":"Washington State University - Vancouver, School of the Environment","active":true,"usgs":false}],"preferred":false,"id":819947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rollwagen-Bollens, Gretchen","contributorId":190162,"corporation":false,"usgs":false,"family":"Rollwagen-Bollens","given":"Gretchen","email":"","affiliations":[],"preferred":false,"id":819948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Counihan, Timothy D. 0000-0003-4967-6514","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":207532,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":819949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robb-Chavez, Salvador B.","contributorId":261391,"corporation":false,"usgs":false,"family":"Robb-Chavez","given":"Salvador","email":"","middleInitial":"B.","affiliations":[{"id":52831,"text":"Washington State University - Vancouver, School of the Environment","active":true,"usgs":false}],"preferred":false,"id":819950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nolan, Sean T.","contributorId":261392,"corporation":false,"usgs":false,"family":"Nolan","given":"Sean","email":"","middleInitial":"T.","affiliations":[{"id":52831,"text":"Washington State University - Vancouver, School of the Environment","active":true,"usgs":false}],"preferred":false,"id":819951,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223781,"text":"70223781 - 2021 - Surface water with more natural temperatures promotes physiological and endocrine changes in landlocked Atlantic salmon smolts","interactions":[],"lastModifiedDate":"2021-09-08T20:28:54.694355","indexId":"70223781","displayToPublicDate":"2021-05-14T15:03:27","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Surface water with more natural temperatures promotes physiological and endocrine changes in landlocked Atlantic salmon smolts","docAbstract":"Hatchery salmonid smolts are often reared using groundwater with elevated temperatures to maximize growth. Previous work has shown that rearing hatchery smolts in surface water with a more natural thermal regime resulted in increased return rates of adult landlocked Atlantic salmon (Salmo salar). We evaluated whether landlocked Atlantic salmon reared in surface water with a natural temperature regime have altered physiological smolt characteristics compared with fish reared in groundwater with elevated winter temperatures. Hatchery fish were sampled three consecutive years from January to May. Additional fish were released as smolts, recaptured, and compared with fry-stocked smolts. Surface water smolts had earlier peaks of plasma T4, lower T3 levels, later peak cortisol, and lower gill Na+/K+-ATPase activity as compared with groundwater smolts. After release and recapture, surface water fish had elevated plasma T4 and gill Na+/K+-ATPase activity compared with groundwater fish, but less than stream-reared fish. Elevated plasma T4 in surface water fish in the hatchery and after release may have promoted imprinting and other aspects of smolt development, contributing to the higher adult return rates of a cohort reared in surface water.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0295","usgsCitation":"Regish, A.M., Ardren, W.R., Staats, N.R., Bouchard, H., Withers, J.L., Castro-Santos, T.R., and McCormick, S.D., 2021, Surface water with more natural temperatures promotes physiological and endocrine changes in landlocked Atlantic salmon smolts: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, no. 6, p. 775-786, https://doi.org/10.1139/cjfas-2020-0295.","productDescription":"12 p.","startPage":"775","endPage":"786","ipdsId":"IP-122416","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":388973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","city":"Newark, Pittsford","otherGeospatial":"Vermont Department of Fish and Wildlife Bald Hill Fish Culture Station","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.9937515258789,\n 44.67158278684375\n ],\n [\n -71.87255859375,\n 44.67158278684375\n ],\n [\n -71.87255859375,\n 44.746245565030684\n ],\n [\n -71.9937515258789,\n 44.746245565030684\n ],\n [\n -71.9937515258789,\n 44.67158278684375\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.06062698364258,\n 43.70256765579351\n ],\n [\n -72.99985885620117,\n 43.70256765579351\n ],\n [\n -72.99985885620117,\n 43.72682433969664\n ],\n [\n -73.06062698364258,\n 43.72682433969664\n ],\n [\n -73.06062698364258,\n 43.70256765579351\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"78","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Ardren, William R.","contributorId":184180,"corporation":false,"usgs":false,"family":"Ardren","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":822780,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Greenberg, Larry","contributorId":265472,"corporation":false,"usgs":false,"family":"Greenberg","given":"Larry","email":"","affiliations":[],"preferred":false,"id":822781,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ardren, William R.","contributorId":184180,"corporation":false,"usgs":false,"family":"Ardren","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":822660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staats, Nicholas R","contributorId":265362,"corporation":false,"usgs":false,"family":"Staats","given":"Nicholas","email":"","middleInitial":"R","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":822661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bouchard, Henry","contributorId":265365,"corporation":false,"usgs":false,"family":"Bouchard","given":"Henry","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":822662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Withers, Jonah L.","contributorId":265471,"corporation":false,"usgs":false,"family":"Withers","given":"Jonah","email":"","middleInitial":"L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":822779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822664,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":822665,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70220664,"text":"70220664 - 2021 - Expansion of intertidal mussel beds following disease-driven reduction of a keystone predator","interactions":[],"lastModifiedDate":"2021-05-24T13:24:03.077478","indexId":"70220664","displayToPublicDate":"2021-05-14T08:20:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2664,"text":"Marine Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Expansion of intertidal mussel beds following disease-driven reduction of a keystone predator","docAbstract":"Disease shapes community composition by removing species with strong interactions. To test whether the absence of keystone predation due to disease produced changes to the species composition of rocky intertidal communities, we leverage a natural experiment involving mass mortality of the keystone predator Pisaster ochraceus from Sea Star Wasting Syndrome. Over four years, we measured dimensions of mussel beds, sizes of Mytilus californianus, mussel recruitment, and species composition on vertical rock walls at six rocky intertidal sites on the central California coast. We also assessed the relationship between changes in mussel cover and changes in sea star density across 33 sites along the North American Pacific coast using data from long-term monitoring. After four years, the lower boundary of the central California mussel beds shifted downward toward the water 18.7 ± 15.8 cm (SD) on the rock and 11.7 ± 11.0 cm in elevation, while the upper boundary remained unchanged. In central California, downward expansion and total area of the mussel bed were positively correlated with mussel recruitment but were not correlated with pre-disease sea star density or biomass. At a multi-region scale, changes in mussel percent cover were positively correlated with pre-disease sea star densities but not change in densities. Species composition of primary substrate holders and epibionts below the mussel bed remained similar across years. Extirpation of the community below the bed did not occur. Instead, this community became limited to a smaller spatial extent while the mussel bed expanded.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marenvres.2021.105363","usgsCitation":"Moritsch, M.M., 2021, Expansion of intertidal mussel beds following disease-driven reduction of a keystone predator: Marine Environmental Research, v. 169, 105363, 10 p., https://doi.org/10.1016/j.marenvres.2021.105363.","productDescription":"105363, 10 p.","ipdsId":"IP-126316","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":452258,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marenvres.2021.105363","text":"Publisher Index Page"},{"id":385892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"California, Oregon","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -129.990234375,\n 50.064191736659104\n ],\n [\n -125.33203125,\n 47.754097979680026\n ],\n [\n -120.76171875,\n 49.095452162534826\n ],\n [\n -128.232421875,\n 55.677584411089526\n ],\n [\n -134.912109375,\n 55.27911529201561\n ],\n [\n -129.990234375,\n 50.064191736659104\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.15625000000001,\n 42.09822241118974\n ],\n [\n -123.31054687499999,\n 42.09822241118974\n ],\n [\n -123.31054687499999,\n 46.49839225859763\n ],\n [\n -125.15625000000001,\n 46.49839225859763\n ],\n [\n -125.15625000000001,\n 42.09822241118974\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.3984375,\n 41.83682786072714\n ],\n [\n -125.15625000000001,\n 41.83682786072714\n ],\n [\n -125.5078125,\n 39.977120098439634\n ],\n [\n -122.87109375,\n 35.67514743608467\n ],\n [\n -118.65234374999999,\n 32.32427558887655\n ],\n [\n -116.27929687499999,\n 32.39851580247402\n ],\n [\n -116.71874999999999,\n 34.08906131584994\n ],\n [\n -121.9921875,\n 37.78808138412046\n ],\n [\n -123.3984375,\n 41.83682786072714\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"169","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moritsch, Monica Mei Jeen 0000-0002-3890-1264","orcid":"https://orcid.org/0000-0002-3890-1264","contributorId":225210,"corporation":false,"usgs":true,"family":"Moritsch","given":"Monica","email":"","middleInitial":"Mei Jeen","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":816354,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220865,"text":"70220865 - 2021 - Heat flux from a vapor-dominated hydrothermal field beneath Yellowstone Lake","interactions":[],"lastModifiedDate":"2021-05-26T12:24:30.798807","indexId":"70220865","displayToPublicDate":"2021-05-14T07:13:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Heat flux from a vapor-dominated hydrothermal field beneath Yellowstone Lake","docAbstract":"We report results from 149 heat flux measurements made over n ∼2-year interval at sites in and around a vapor-dominated geothermal field located at water depths of ∼100–120 m in Yellowstone Lake, Wyoming. Measurements of both in situ temperature and thermal conductivity as a function of depth were made with a 1 m probe via a remotely operated vehicle, and are combined to compute the vertical conductive heat flux. Inside the ∼55.5 × 103 m2 bathymetric depression demarcating the vapor-dominated field, the median conductive flux is 13 W m−2, with a conductive output of 0.72 MW. Outside the thermal field, the median conductive flux is 3.5 W m−2. We observed 49 active vents inside the thermal field, with an estimated mass discharge rate of 56 kg s−1, a median exit-fluid temperature of 132°C, and a total heat output of 29 MW. We find evidence for relatively weak secondary convection with a total output of 0.09 MW in thermal area lake floor sediments. Our data indicate that vapor beneath the thermal field is trapped by a low-permeability cap at a temperature of ∼189°C and a depth of ∼15 m below the lake floor. The thermal output of the Deep Hole is among the highest of any vapor-dominated field in Yellowstone, due in part to the high boiling temperatures associated with the elevated lake floor pressures.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB021098","usgsCitation":"Favorito, J.E., Harris, R.N., Sohn, R.A., Hurwitz, S., and Luttrell, K., 2021, Heat flux from a vapor-dominated hydrothermal field beneath Yellowstone Lake: Journal of Geophysical Research, v. 126, no. 5, e2020JB021098, 20 p., https://doi.org/10.1029/2020JB021098.","productDescription":"e2020JB021098, 20 p.","ipdsId":"IP-125194","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":452262,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2020jb021098","text":"External Repository"},{"id":385976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.62957763671875,\n 44.25306865928177\n ],\n [\n -110.1434326171875,\n 44.25306865928177\n ],\n [\n -110.1434326171875,\n 44.65888542068506\n ],\n [\n -110.62957763671875,\n 44.65888542068506\n ],\n [\n -110.62957763671875,\n 44.25306865928177\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-05-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Favorito, Julia E.","contributorId":258789,"corporation":false,"usgs":false,"family":"Favorito","given":"Julia","email":"","middleInitial":"E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":816503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Robert N. 0000-0002-4641-1425","orcid":"https://orcid.org/0000-0002-4641-1425","contributorId":258790,"corporation":false,"usgs":false,"family":"Harris","given":"Robert","email":"","middleInitial":"N.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":816504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sohn, Robert A. 0000-0002-9050-8603","orcid":"https://orcid.org/0000-0002-9050-8603","contributorId":258792,"corporation":false,"usgs":false,"family":"Sohn","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":816505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":816506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luttrell, Karen 0000-0003-1405-1207","orcid":"https://orcid.org/0000-0003-1405-1207","contributorId":258797,"corporation":false,"usgs":false,"family":"Luttrell","given":"Karen","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":816507,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220492,"text":"70220492 - 2021 - Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas","interactions":[],"lastModifiedDate":"2021-05-17T12:47:37.844807","indexId":"70220492","displayToPublicDate":"2021-05-13T07:39:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas","docAbstract":"Ostracoda (bivalved Crustacea) comprise a significant part of the benthic meiofauna in the Pacific-Arctic region, including more than 50 species, many with identifiable ecological tolerances. These species hold potential as useful indicators of past and future ecosystem changes. In this study, we examined benthic ostracodes from nearly 300 surface sediment samples, >34,000 specimens, from three regions—the northern Bering, Chukchi and Beaufort Seas—to establish species’ ecology and distribution. Samples were collected during various sampling programs from 1970 through 2018 on the continental shelves at 20 to ~100m water depth. Ordination analyses using species’ relative frequencies identified six species, Normanicythere leioderma, Sarsicytheridea bradii, Paracyprideis pseudopunctillata, Semicytherura complanata, Schizocythere ikeyai, and Munseyella mananensis, as having diagnostic habitat ranges in bottom water temperatures, salinities, sediment substrates and/or food sources. Species relative abundances and distributions can be used to infer past bottom environmental conditions in sediment archives for paleo-reconstructions and to characterize potential changes in Pacific-Arctic ecosystems in future sampling studies. Statistical analyses further showed ostracode assemblages grouped by the summer water masses influencing the area. Offshore-to-nearshore transects of samples across different water masses showed that complex water mass characteristics, such as bottom temperature, productivity, as well as sediment texture, influenced the relative frequencies of ostracode species over small spatial scales. On the larger biogeographic scale, synoptic ordination analyses showed dominant species—N. leioderma (Bering Sea), P. pseudopunctillata (offshore Chukchi and Beaufort Seas), and S. bradii (all regions)—remained fairly constant over recent decades. However, during 2013–2018, northern Pacific species M. mananensis and S. ikeyai increased in abundance by small but significant proportions in the Chukchi Sea region compared to earlier years. It is yet unclear if these assemblage changes signify a meiofaunal response to changing water mass properties and if this trend will continue in the future. Our new ecological data on ostracode species and biogeography suggest these hypotheses can be tested with future benthic monitoring efforts.
Algal and cyanobacterial blooms can foul water systems, inhibit recreation, and produce cyanotoxins, which can be toxic to humans, domestic animals, and wildlife. Blooms that recur yearly present a special challenge, in that chronic effects of most cyanotoxins are unknown. To better understand cyanotoxin timing, possible environmental triggers, and inter-relations among taxa and toxins in bloom communities, recurring cyanobacterial blooms were investigated at three recreational sites in Kabetogama Lake in Voyageurs National Park from 2016-2019. Results indicated that peak neurotoxin concentrations occurred before peak microcystin concentrations and that toxin-forming cyanobacteria were present before visible blooms, which is a serious human health concern. Two cyanotoxin mixture models (MIX) and two microcystin (MC) models were developed using near-real-time environmental variables and additional comprehensive variables based on laboratory analyses. Comprehensive models explained more variability than the environmental models and neither MIX model was a better fit than the MC models. However, the MIX models produced no false negatives, indicating that all observations above human-health regulatory guidelines were simulated by the MIX models. The results show that a model based on a cyanotoxin mixture is more protective of human health than a model based on microcystin alone. In 2019, 7 of 19 toxins were detected in various mixtures. The potential toxin producing cyanobacteria, Microcystis, was significantly correlated with microcystin-YR, while Pseudanabaena sp. and Synechococcus sp. were negatively correlated to several toxins. Jaccard and Sorenson indices indicated strong same-day similarities among the three bloom communities. Nitrogen-fixing cyanobacteria were present at every site, and when combined with internal loading of phosphorus, might explain similarities among sites, and why seasonal differences, even in samples from the same site, were stronger. Information from this dissertation adds to the body of work on recurring blooms and under-studied toxins and toxin mixtures, providing a better understanding of future research options for freshwater cyanotoxins in and outside of Voyageurs National Park.
","language":"English","publisher":"North Dakota State University","usgsCitation":"Christensen, V., 2021, Freshwater cyanotoxin mixtures in recurring cyanobacterial blooms in Voyageurs National Park, 221 p.","productDescription":"221 p.","ipdsId":"IP-128041","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":409293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":409284,"type":{"id":15,"text":"Index Page"},"url":"https://www.proquest.com/docview/2547519599","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","otherGeospatial":"Kabetogama Lake, Voyageurs National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.7287375311439,\n 48.44384887858732\n ],\n [\n -92.74528481592849,\n 48.46823569471036\n ],\n [\n -92.85651934142741,\n 48.45238559671293\n ],\n [\n -92.80320031267578,\n 48.47311165228035\n ],\n [\n -92.9355785909554,\n 48.46823569471036\n ],\n [\n -93.01371854688433,\n 48.52184546050012\n ],\n [\n -93.05508675884663,\n 48.53280411143439\n ],\n [\n -93.11300225559437,\n 48.51271143988237\n ],\n [\n -93.11759872359,\n 48.48469017375146\n ],\n [\n -93.06703757563596,\n 48.47494001557638\n ],\n [\n -93.06060252044176,\n 48.44628808733975\n ],\n [\n -93.02199218927704,\n 48.431041110668644\n ],\n [\n -92.98062397731476,\n 48.41151830276564\n ],\n [\n -92.95120658214137,\n 48.426161111635196\n ],\n [\n -92.92822424216214,\n 48.42189072806485\n ],\n [\n -92.9034033149849,\n 48.43226103720582\n ],\n [\n -92.86755086461727,\n 48.42189072806485\n ],\n [\n -92.80871607427095,\n 48.410908094197964\n ],\n [\n -92.78113726629607,\n 48.40480560576938\n ],\n [\n -92.7287375311439,\n 48.44384887858732\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Christensen, Victoria 0000-0003-4166-7461","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":220548,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":856888,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220886,"text":"70220886 - 2021 - Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","interactions":[],"lastModifiedDate":"2021-06-30T19:00:04.291567","indexId":"70220886","displayToPublicDate":"2021-05-12T07:16:05","publicationYear":"2021","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":"Exploring the factors controlling the error characteristics of the Surface Water and Ocean Topography mission discharge estimates","docAbstract":"The Surface Water and Ocean Topography (SWOT) satellite mission will measure river width, water surface elevation, and slope for rivers wider than 50-100 m. SWOT observations will enable estimation of river discharge by using simple flow laws such as the Manning-Strickler equation, complementing in-situ streamgages. Several discharge inversion algorithms designed to compute unobserved flow law parameters (e.g. friction coefficient, bathymetry) have been proposed, but to date, a systematic assessment of factors controlling algorithm performance has not been conducted. Here, we assess the performance of the five algorithms that are expected to be used in the construction of the SWOT product. To perform this assessment, we used synthetic SWOT observations created with hydraulic model output corrupted with SWOT-like error. Prior information provided to the algorithms was purposefully limited to an estimate of mean annual flow (MAF), designed to produce a “worst case” benchmark. Prior MAF error was an important control on algorithm performance, but discharge estimates produced by the algorithms are less biased than the MAF; thus, the discharge algorithms improve on the prior. We show for the first time that accuracy and frequency of remote sensing observations are less important than prior bias, hydraulic variability among reaches, and flow law accuracy in governing discharge algorithm performance. The discharge errors and error sensitivities reported herein are a bounding benchmark, representing worst possible expected errors and error sensitivities. This study lays the groundwork to develop predictive power of algorithm performance, and thus map the global distribution of worst-case SWOT discharge accuracy.
Hurricanes are extreme storms that affect coastal communities, but the linkages between hurricane forcing and ocean dynamics remain poorly understood. Here, we present full water column observations at unprecedented resolution from the southwest Puerto Rico insular shelf and slope during Hurricane María, representing a rare set of high-frequency, subsurface, oceanographic observations collected along an island margin during a hurricane. The shelf geometry and orientation relative to the storm acted to stabilize and strengthen stratification. This maintained elevated sea-surface temperatures (SSTs) throughout the storm and led to an estimated 65% greater potential hurricane intensity contribution at this site before eye passage. Coastal cooling did not occur until 11 hours after the eye passage. Our findings present a new framework for how hurricane interaction with insular island margins may generate baroclinic processes that maintain elevated SSTs, thus potentially providing increased energy for the storm.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.abf1552","usgsCitation":"Cheriton, O.M., Storlazzi, C.D., Rosenberger, K.J., Sherman, C.E., and Schmidt, W., 2021, Rapid observations of ocean dynamics and stratification along a steep island coast during Hurricane María: Science Advances, v. 7, no. 20, eabf1552, 10 p., https://doi.org/10.1126/sciadv.abf1552.","productDescription":"eabf1552, 10 p.","ipdsId":"IP-111341","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":452294,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.abf1552","text":"Publisher Index Page"},{"id":386110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"southwestern Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.0880126953125,\n 17.90556881196468\n ],\n [\n -66.7474365234375,\n 17.90556881196468\n ],\n [\n -66.7474365234375,\n 18.109308155101445\n ],\n [\n -67.0880126953125,\n 18.109308155101445\n ],\n [\n -67.0880126953125,\n 17.90556881196468\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":816758,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherman, Clark E. 0000-0003-0758-7900","orcid":"https://orcid.org/0000-0003-0758-7900","contributorId":259180,"corporation":false,"usgs":false,"family":"Sherman","given":"Clark","middleInitial":"E.","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":816759,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, Wilford 0000-0003-3564-4159","orcid":"https://orcid.org/0000-0003-3564-4159","contributorId":259182,"corporation":false,"usgs":false,"family":"Schmidt","given":"Wilford","email":"","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":816760,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220401,"text":"ofr20211022 - 2021 - Evaporation from Lake Mead and Lake Mohave, Nevada and Arizona, 2010–2019","interactions":[],"lastModifiedDate":"2021-05-12T11:48:04.655661","indexId":"ofr20211022","displayToPublicDate":"2021-05-11T15:05:25","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1022","displayTitle":"Evaporation from Lake Mead and Lake Mohave, Nevada and Arizona, 2010–2019","title":"Evaporation from Lake Mead and Lake Mohave, Nevada and Arizona, 2010–2019","docAbstract":"Evaporation-rate estimates at Lake Mead and Lake Mohave, Nevada and Arizona, were based on eddy covariance and available energy measurements from March 2010 through April 2019 at Lake Mead and May 2013 through April 2019 at Lake Mohave. The continuous data needed to compute monthly evaporation were collected from floating-platform and land-based measurement stations located at each reservoir. Collected data include latent- and sensible-heat fluxes, net radiation, air temperature, wind speed, humidity, and water-temperature profiles. Data collection, analysis methods, and monthly evaporation results for Lake Mead through February 2012 were documented in a U.S. Geological Survey (USGS) Scientific-Investigations Report, 2013–5229. Monthly evaporation and associated datasets for both reservoirs through April 2015 were published in a USGS Data Release (https://doi.org/10.5066/F79C6VG3). Average annual evaporation at Lake Mead was 1,896 millimeters (mm), which is a 10 percent difference from the 1,718 mm average annual evaporation at Lake Mohave; this was primarily due to differences in available energy. Average annual available energy at Lake Mead was 139 watts per square meter (W/m2), which is an 18 percent difference from the 116 W/m2 average annual available energy at Lake Mohave. Differences in available energy are driven by differences in advected heat between Lake Mead and Lake Mohave; advected heat at Lake Mohave is lower due to colder inflows and warmer outflows. Lake Mead monthly evaporation estimates for this study compare reasonably well to the Bureau of Reclamation’s 24-Month Study (24MS) evaporation coefficients, which are based on pioneering studies from the 1950s. Temporal trends in this study indicate that the effects of heat storage at Lake Mead were underestimated in the 24MS, particularly during the fall months when energy was released from the lake. Mean monthly evaporation rates at Lake Mead were greater than Lake Mohave from June through November during the study period. The seasonal pattern of evaporation at Lake Mohave in this study indicates that the effects of available energy were underestimated in the 24MS coefficients for this reservoir, and that evaporation was substantially overestimated from spring through summer
during the study period of 2013 through 2019.
Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Long-distance migrations influence the dynamics of hostpathogen interactions and understanding the role of migratory waterfowl in the spread of the highly pathogenic avian influenza viruses (HPAIV) is important. While wild geese have been associated with outbreak events, disease ecology of closely related species has not been studied to the same extent. The swan goose (Anser cygnoides) and the bar-headed goose (Anser indicus) are congeneric species with distinctly different HPAIV infection records; the former with few and the latter with numerous records. We compared movements of these species, as well as the more distantly related whooper swan (Cygnus cygnus) through their annual migratory cycle to better understand exposure to HPAIV events and how this compares within and between congeneric and noncongeneric species. In spite of their record of fewer infections, swan geese were more likely to come in contact with disease outbreaks than bar-headed geese. We propose two possible explanations: i) frequent prolonged contact with domestic ducks increases innate immunity in swan geese, and/or ii) the stress of high-elevation migration reduces immunity of bar-headed geese. Continued efforts to improve our understanding of species-level pathogen response is critical to assessing disease transmission risk.
Little information exists on the habitat use and feeding ecology of insectivorous bats in arid ecosystems, especially at and near uranium mines in northern Arizona, within the Grand Canyon watershed. In 2015–2016, we conducted mist-netting, nightly acoustic monitoring (>1 year), and diet analyses of bats, as well as insect sampling, at 2 uranium mines (Pinenut and Arizona 1) with water containment ponds. Because of physical barriers and limited general access to areas within the mine yard, mist-netting was limited to outside of the perimeter fence and away from the containment ponds. Mist-netting also occurred at 2 nearby sites that served as proxies to the mines. Bats captured directly at the mines included one pregnant Antrozous pallidus and 3 adult male Parastrellus hesperus. At the proxy sites, we captured 45 individuals identified as A. pallidus, Corynorhinus townsendii, Eptesicus fuscus, Euderma maculatum, Lasionycteris noctivagans, Myotis californicus, Myotis ciliolabrum, P. hesperus, and Tadarida brasiliensis. The nightly and seasonal presence of bats, as shown through acoustic recordings at each mine, coincided with the seasonal migratory and hibernation behaviors of the bat species. Statistical comparisons of acoustic recordings with precipitation data collected over one year show that seasonal monsoon rains generally had a negative effect on the nightly activity and presence of bats. Diets of P. hesperus from both mines were comprised mostly of coleopterans but also included smaller volumes of Hymenoptera, Hemiptera, Lepidoptera, Diptera, and Neuroptera. The diet of A. pallidus was comprised solely of Coleoptera. Diets of bat species from the proxy sites were characteristic of their known feeding ecology, which ranged from the consumption of soft-bodied insects (e.g., moths) by C. townsendii to the consumption of hard-bodied insects (e.g., beetles) by E. fuscus. Ultimately, the increased knowledge of the natural history of bats through multiple methods of data collection allows for a better understanding of complex arid ecosystems. It also provides resources needed for the management of habitat associated with alternative energy, such as uranium mining.
Biological communities, including periphyton, are continuously affected by chemical, physical, and other biological factors, and the health of these communities can reflect the overall health of the aquatic system. A diverse community is more robust, and communities with lower richness and evenness often indicate a degraded community dominated by few taxa tolerant to the degraded conditions, which makes the community more susceptible to ecological changes. Water-quality nutrient samples were collected at sites in the Lower Grand River during 2010 through 2018 and periphyton sample collections began in 2011 to describe the periphyton community and overall ecological health. Nutrient sample concentrations were generally elevated at these sites, which can lead to eutrophication, excessive plant and algae growth, drinking-water taste and odor problems, low dissolved-oxygen concentrations, and harmful algal blooms. Concentrations of total nitrogen were greater than acceptable as described by the U.S. Environmental Protection Agency, and total phosphorus concentrations were greater than reference concentrations. Periphyton communities were dominated by taxa that are tolerant to or indicative of elevated nutrient concentrations; and nuisance algae, or harmful algal bloom producers, were identified at all sites, except one. The presence of these producers indicates that harmful algal blooms may have high potential during optimal conditions at these sites. Chlorophyll concentrations that exceed 100 milligrams per square meter are considered nuisance and were determined in 11 percent of the samples and at every site during September 2012. Samples were collected during low-flow conditions when nutrient concentrations are generally lower than during high-flow and runoff conditions. Elevated nutrient concentrations during low-flow conditions indicate nutrient concentrations are likely elevated throughout most of the year. Agriculture is the primary land use within the Lower Grand River and is likely a primary source of nutrients and sediments. Conservation practices intended to reduce nutrient loss from agriculture fields have increased because of the Mississippi River Basin Healthy Watersheds Initiative and will potentially increase the ecological, chemical, and physical health of these waterways.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215012","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Krempa, H.M., 2021, Periphyton biomass and community compositions as indicators of water quality in the Lower Grand River hydrologic unit, Missouri and Iowa, 2011–18: U.S. Geological Survey Scientific Investigations Report 2021–5012, 51 p., https://doi.org/10.3133/sir20215012.","productDescription":"Report: vi, 51 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-117668","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385478,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5012/coverthb.jpg"},{"id":385479,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5012/sir20215012.pdf","text":"Report","size":"2.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5012"},{"id":385480,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BYF1EN","text":"USGS data release","description":"USGs Data Release","linkHelpText":"Periphyton community data within the Lower Grand River hydrologic unit code 10280103, Missouri and Iowa, 2011–2018"},{"id":385481,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Iowa, Missouri","otherGeospatial":"Lower Grand River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.4716796875,\n 40.97989806962013\n ],\n [\n -94.10888671875,\n 41.36031866306708\n ],\n [\n -94.72412109375,\n 40.83043687764923\n ],\n [\n -94.833984375,\n 40.027614437486655\n ],\n [\n -94.41650390625,\n 39.232253141714885\n ],\n [\n -93.6474609375,\n 38.94232097947902\n ],\n [\n -92.83447265624999,\n 39.16414104768742\n ],\n [\n -92.8125,\n 39.757879992021756\n ],\n [\n -92.94433593749999,\n 40.74725696280421\n ],\n [\n -93.4716796875,\n 40.97989806962013\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
No abstract available.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14226","usgsCitation":"Rosenberry, D., Engesgaard, P., and Hatch, C.E., 2021, Hydraulic conductivity can no longer be considered a fixed property when quantifying flow between groundwater and surface water: Hydrological Processes, v. 35, no. 6, e14226, 7 p., https://doi.org/10.1002/hyp.14226.","productDescription":"e14226, 7 p.","ipdsId":"IP-128235","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":386567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":257638,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":817782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engesgaard, Peter 0000-0002-5925-8757","orcid":"https://orcid.org/0000-0002-5925-8757","contributorId":260357,"corporation":false,"usgs":false,"family":"Engesgaard","given":"Peter","email":"","affiliations":[{"id":12672,"text":"University of Copenhagen","active":true,"usgs":false}],"preferred":false,"id":817783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hatch, Christine E. 0000-0002-4996-1617","orcid":"https://orcid.org/0000-0002-4996-1617","contributorId":260358,"corporation":false,"usgs":false,"family":"Hatch","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":817784,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}