This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency's Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses (n = 84) submitted as part of the U.S. Environmental Protection Agency's fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016 through 2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117377","usgsCitation":"Coffer, M., Schaeffer, B., Foreman, K., Porteous, A., Loftin, K.A., Stumpf, R., Werdell, J., Urquhart, E., Albert, R., and Darling, J., 2021, Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States: Water Research, v. 201, no. 1, 117377, 13 p., https://doi.org/10.1016/j.watres.2021.117377.","productDescription":"117377, 13 p.","ipdsId":"IP-129698","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":451757,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2021.117377","text":"Publisher Index Page"},{"id":387133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"201","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coffer, Megan","contributorId":260848,"corporation":false,"usgs":false,"family":"Coffer","given":"Megan","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaeffer, Blake A.","contributorId":260849,"corporation":false,"usgs":false,"family":"Schaeffer","given":"Blake A.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foreman, Katherine","contributorId":260850,"corporation":false,"usgs":false,"family":"Foreman","given":"Katherine","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Porteous, Alex","contributorId":260851,"corporation":false,"usgs":false,"family":"Porteous","given":"Alex","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":221964,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":818970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stumpf, Richard","contributorId":260852,"corporation":false,"usgs":false,"family":"Stumpf","given":"Richard","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":818971,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Werdell, Jeremy","contributorId":260853,"corporation":false,"usgs":false,"family":"Werdell","given":"Jeremy","email":"","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":818972,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Urquhart, Erin","contributorId":260854,"corporation":false,"usgs":false,"family":"Urquhart","given":"Erin","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":818973,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Albert, Ryan","contributorId":260855,"corporation":false,"usgs":false,"family":"Albert","given":"Ryan","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818974,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Darling, John","contributorId":260856,"corporation":false,"usgs":false,"family":"Darling","given":"John","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":818975,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70221576,"text":"sir20215059 - 2021 - Borehole analysis, single-well aquifer testing, and water quality for the Burnpit well, Mount Rushmore National Memorial, South Dakota","interactions":[],"lastModifiedDate":"2021-06-25T11:51:29.973079","indexId":"sir20215059","displayToPublicDate":"2021-06-24T10:38:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5059","displayTitle":"Borehole Analysis, Single-Well Aquifer Testing, and Water Quality for the Burnpit Well, Mount Rushmore National Memorial, South Dakota","title":"Borehole analysis, single-well aquifer testing, and water quality for the Burnpit well, Mount Rushmore National Memorial, South Dakota","docAbstract":"Mount Rushmore National Memorial (hereafter referred to as “the memorial”), in western South Dakota, is maintained by the National Park Service (NPS) and includes 1,278 acres of land in the east-central part of the Black Hills. An ongoing challenge for NPS managers at the memorial is providing water from sustainable and reliable sources for operations, staff, and the increasing number of visitors. In 2020, the U.S. Geological Survey (USGS) and NPS completed a hydrological study of the Burnpit well (well 5), a 580-foot-deep open hole groundwater well completed in metamorphic (crystalline) rock at the memorial. The purpose of this study was to estimate the geological and hydraulic properties of the aquifer supplying the well and to determine the water quality of the groundwater from the well. The study provides NPS staff and managers background information for assessing future uses for the well. Methods for data collection and analysis for the study included borehole and video camera analysis in 2020, aquifer testing by the NPS in 2009 and the USGS in 2020, and water-quality sampling in 2020.
Borehole camera video generally matched the lithology recorded in the well log. Fractures recorded in the well log and observed with the borehole camera, including more than 20 less prominent fractures and rough sidewall areas, indicated a fractured aquifer. The fractures are the primary conduits for groundwater flow through the rock and into the well.
Transmissivity was estimated for the upper and lower water-level drawdown zones at the Burnpit well with data from the NPS and USGS using the Theis and Cooper-Jacob methods. Transmissivity for the NPS test using the Theis method was 9.0 and 11 feet squared per day (ft2/d) for the upper and lower drawdown zones, respectively. Using the Cooper-Jacob method, the transmissivity was 22 and 14 ft2/d for the upper and lower drawdown zones of the aquifer, respectively. Transmissivity estimates from data from the USGS test were similar. The Theis method, applied to the upper and lower drawdown zones of the aquifer, produced transmissivity estimates of 7.7 and 10 ft2/d, and the Cooper-Jacob method produced estimates of 9.7 and 12 ft2/d, respectively.
Storativity (specific yield) estimated using the Theis method for the NPS aquifer-test data was 0.85 and 0.92 for the upper and lower drawdown zones of the aquifer, respectively. The Cooper-Jacob method applied to the NPS aquifer-test data produced storativity estimates of 0.11 and 0.50 for the upper and lower drawdown zones, respectively. The Theis method applied to the USGS aquifer-test data estimated storativity values of 0.77 and 1.0 for the upper and lower drawdown zones, respectively. The Cooper-Jacob method estimated storativity of 0.50 and 0.60 for the upper and lower drawdown zones of the USGS aquifer test, respectively. The estimated storativity values from the NPS and USGS aquifer tests for the upper and lower drawdown zones were higher than expected for limestones and schists.
The hypothetical equilibrium drawdown for the Burnpit well was estimated after the NPS test in 2009 at no more, and possibly less, than 35 gallons per minute. The NPS noted that the sustainable yield likely was overestimated because the water level did not stabilize during the NPS aquifer test. The specific capacity for the NPS aquifer test in 2009 was 0.16 gallon per minute per foot ([gal/min]/ft) of drawdown at 3 hours, and the specific capacity for the USGS aquifer test in 2020 was 0.13 (gal/min)/ft of drawdown at 3 hours. The rate of water-level recovery after pumping ceased was 0.017 and 0.013 (gal/min)/ft for the NPS and USGS aquifer tests, respectively. The water-level recovery rate was nearly an order of magnitude less than the specific capacity estimated during pumping, indicating that water levels in the Burnpit well may not recover quickly enough during pumping to provide for a continuous source of water.
Water-quality samples were collected at the Burnpit well on June 24 and July 23, 2020, and analyzed for field-measured properties, major ions, metals, nutrients, and perchlorate. Iron, zinc, and lithium concentrations for unfiltered samples in the well were at least three times greater than the mean filtered sample concentrations reported for crystalline aquifers in the Black Hills. Manganese concentrations were less than the mean concentration for crystalline aquifers but exceeded the U.S. Environmental Protection Agency (EPA) secondary drinking-water standards. The iron concentration from the June 24 sample was about 11 times greater than the EPA secondary drinking-water standards and mean concentrations from crystalline aquifers in the Black Hills. Arsenic concentrations in Burnpit well samples collected in 2020 were greater than the EPA primary drinking-water standard and the mean concentration for crystalline aquifers in the Black Hills. Arsenic occurs naturally in the rock of crystalline aquifers, and concentrations from samples in the Black Hills commonly exceed the EPA primary drinking-water standard of 10 micrograms per liter. High concentrations of arsenic, iron, and manganese metals in the Burnpit well make groundwater from the well in its natural state unusable as a drinking-water source, and water treatment would be necessary to reduce the trace element concentrations to less than the EPA primary and secondary drinking-water standards. However, if the memorial has immediate nonpotable water requirements, such as for construction and fire suppression, groundwater from the Burnpit well could provide water without causing additional stress to current (2021) drinking-water sources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215059","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Eldridge, W.G., Hoogestraat, G.K., and Rice, S.E., 2021, Borehole analysis, single-well aquifer testing, and water quality for the Burnpit well, Mount Rushmore National Memorial, South Dakota: U.S. Geological Survey Scientific Investigations Report 2021–5059, 29 p., https://doi.org/10.3133/sir20215059.","productDescription":"Report: vii, 29 p.; Data Release; Dataset","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-126498","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":386673,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98OZQN9","text":"USGS data release","description":"USGS data release","linkHelpText":"Borehole video and aquifer test data for the Burnpit well, Mount Rushmore National Memorial, South Dakota, 2020"},{"id":386672,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5059/sir20215059.pdf","text":"Report","size":"2.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5059"},{"id":386674,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS dataset","linkHelpText":"— USGS water data for the Nation"},{"id":386671,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5059/coverthb.jpg"}],"country":"United States","state":"South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.0625,\n 43.40903821777055\n ],\n [\n -103.2440185546875,\n 43.40903821777055\n ],\n [\n -103.2440185546875,\n 44.52392653654213\n ],\n [\n -104.0625,\n 44.52392653654213\n ],\n [\n -104.0625,\n 43.40903821777055\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
Amphibian larvae are commonly used as indicators of aquatic ecosystem health because they are susceptible to contaminants. However, there is limited information on how species characteristics and trophic position influence contaminant loads in larval amphibians. Importantly, there remains a need to understand whether grazers (frogs and toads [anurans]) and predators (salamanders) provide comparable information on contaminant accumulation or if they are each indicative of unique environmental processes and risks. To better understand the role of trophic position in contaminant accumulation, we analyzed composite tissues for 10 metals from larvae of multiple co-occurring anuran and salamander species from 20 wetlands across the United States. We examined how metal concentrations varied with body size (anurans and salamanders) and developmental stage (anurans) and how the digestive tract (gut) influenced observed metal concentrations. Across all wetlands, metal concentrations were greater in anurans than salamanders for all metals tested except mercury (Hg), selenium (Se), and zinc (Zn). Concentrations of individual metals in anurans decreased with increasing weight and developmental stage. In salamanders, metal concentrations were less correlated with weight, indicating diet played a role in contaminant accumulation. Based on batches of similarly sized whole-body larvae compared to larvae with their digestive tracts removed, our results indicated that tissue type strongly affected perceived concentrations, especially for anurans (gut represented an estimated 46–97% of all metals except Se and Zn). This suggests the reliability of results based on whole-body sampling could be biased by metal, larval size, and development. Overall, our data shows that metal concentrations differs between anurans and salamanders, which suggests that metal accumulation is unique to feeding behavior and potentially trophic position. To truly characterize exposure risk in wetlands, species of different life histories, sizes and developmental stages should be included in biomonitoring efforts.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2021.117638","usgsCitation":"Smalling, K., Oja, E.B., Cleveland, D.M., Davenport, J.D., Eagles-Smith, C., Campbell Grant, E.H., Kleeman, P.M., Halstead, B., Stemp, K.M., Tornabene, B., Bunnell, Z.J., and Hossack, B., 2021, Metal accumulation varies with life history, size, and development of larval amphibians: Environmental Pollution, v. 287, 117638, 10 p., https://doi.org/10.1016/j.envpol.2021.117638.","productDescription":"117638, 10 p.","ipdsId":"IP-127103","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":489089,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2021.117638","text":"Publisher Index Page"},{"id":436291,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q3LM78","text":"USGS data release","linkHelpText":"Metal concentrations in sediment and amphibian tissues from wetlands sampled across the United States"},{"id":387228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"287","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oja, Emily Bea 0000-0002-8621-9665","orcid":"https://orcid.org/0000-0002-8621-9665","contributorId":261164,"corporation":false,"usgs":true,"family":"Oja","given":"Emily","email":"","middleInitial":"Bea","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819407,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":819408,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davenport, Jon D 0000-0002-9911-2779","orcid":"https://orcid.org/0000-0002-9911-2779","contributorId":261166,"corporation":false,"usgs":false,"family":"Davenport","given":"Jon","email":"","middleInitial":"D","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":819409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":819410,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819411,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819412,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research 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0000-0001-6142-8703","orcid":"https://orcid.org/0000-0001-6142-8703","contributorId":261172,"corporation":false,"usgs":true,"family":"Bunnell","given":"Zachary","email":"","middleInitial":"J","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819416,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819417,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70221581,"text":"70221581 - 2021 - Sources and risk factors for nitrate and microbial contamination of private household wells in the fractured dolomite aquifer of northeastern Wisconsin","interactions":[],"lastModifiedDate":"2021-06-24T14:54:40.481459","indexId":"70221581","displayToPublicDate":"2021-06-23T09:52:05","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1542,"text":"Environmental Health Perspectives","active":true,"publicationSubtype":{"id":10}},"title":"Sources and risk factors for nitrate and microbial contamination of private household wells in the fractured dolomite aquifer of northeastern Wisconsin","docAbstract":"Groundwater quality in the Silurian dolomite aquifer in northeastern Wisconsin, USA, has become contentious as dairy farms and exurban development expand.
We investigated private household wells in the region, determining the extent, sources, and risk factors of nitrate and microbial contamination.
Total coliforms, Escherichia coli, and nitrate were evaluated by synoptic sampling during groundwater recharge and no-recharge periods. Additional seasonal sampling measured genetic markers of human and bovine fecal-associated microbes and enteric zoonotic pathogens. We constructed multivariable regression models of detection probability (log-binomial) and concentration (gamma) for each contaminant to identify risk factors related to land use, precipitation, hydrogeology, and well construction.
Total coliforms and nitrate were strongly associated with depth-to-bedrock at well sites and nearby agricultural land use, but not septic systems. Both human wastewater and cattle manure contributed to well contamination. Rotavirus group A, Cryptosporidium, and Salmonella were the most frequently detected pathogens. Wells positive for human fecal markers were associated with depth-to-groundwater and number of septic system drainfield within
These findings may inform policies to minimize contamination of the Silurian dolomite aquifer, a major water supply for the U.S. and Canadian Great Lakes region.
","language":"English","publisher":"Environmental health Perspectives","doi":"10.1289/EHP7813","usgsCitation":"Borchardt, M.A., Stokdyk, J.P., Kieke, B.A., Muldoon, M.A., Spencer, S.K., Firnstahl, A.D., Bonness, D., Hunt, R., and Burch, T., 2021, Sources and risk factors for nitrate and microbial contamination of private household wells in the fractured dolomite aquifer of northeastern Wisconsin: Environmental Health Perspectives, v. 129, no. 6, 067004, 18 p., https://doi.org/10.1289/EHP7813.","productDescription":"067004, 18 p.","ipdsId":"IP-120190","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":451762,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1289/ehp7813","text":"Publisher Index Page"},{"id":386701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Kewaunee County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-87.3761,44.6754],[-87.3774,44.674],[-87.381,44.6636],[-87.3858,44.6545],[-87.3911,44.6473],[-87.3944,44.6442],[-87.3966,44.6378],[-87.4045,44.6302],[-87.4085,44.6257],[-87.4137,44.6235],[-87.4223,44.6145],[-87.4263,44.61],[-87.4341,44.6056],[-87.442,44.6011],[-87.4428,44.5934],[-87.4468,44.5893],[-87.4502,44.5816],[-87.4544,44.5721],[-87.4604,44.5622],[-87.4664,44.555],[-87.4738,44.5455],[-87.476,44.5369],[-87.4761,44.5305],[-87.4796,44.5223],[-87.4851,44.5106],[-87.488,44.4974],[-87.4959,44.4706],[-87.5046,44.4575],[-87.5041,44.4534],[-87.5062,44.4457],[-87.5064,44.4375],[-87.5074,44.4279],[-87.5121,44.4188],[-87.5163,44.408],[-87.5191,44.3998],[-87.5212,44.3907],[-87.5209,44.3816],[-87.5218,44.3734],[-87.5232,44.3688],[-87.5279,44.3602],[-87.5351,44.3521],[-87.5386,44.3422],[-87.5368,44.338],[-87.5408,44.3331],[-87.5454,44.3277],[-87.6445,44.3273],[-87.7665,44.3271],[-87.7655,44.4146],[-87.7646,44.5017],[-87.7643,44.5888],[-87.7628,44.6477],[-87.7582,44.6522],[-87.7555,44.6558],[-87.7547,44.6608],[-87.7507,44.6667],[-87.7435,44.673],[-87.7389,44.6775],[-87.6413,44.6757],[-87.5193,44.6753],[-87.4384,44.6754],[-87.3973,44.6753],[-87.3761,44.6754]]]},\"properties\":{\"name\":\"Kewaunee\",\"state\":\"WI\"}}]}","volume":"129","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":818173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kieke, Burney A","contributorId":195802,"corporation":false,"usgs":false,"family":"Kieke","given":"Burney","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":818175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muldoon, Maureen A.","contributorId":198974,"corporation":false,"usgs":false,"family":"Muldoon","given":"Maureen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":818176,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spencer, Susan K.","contributorId":181738,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":818177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bonness, Davina","contributorId":260613,"corporation":false,"usgs":false,"family":"Bonness","given":"Davina","email":"","affiliations":[{"id":52618,"text":"Kewaunee County","active":true,"usgs":false}],"preferred":false,"id":818179,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818180,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burch, Tucker R.","contributorId":195801,"corporation":false,"usgs":false,"family":"Burch","given":"Tucker R.","affiliations":[],"preferred":false,"id":818181,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70221582,"text":"70221582 - 2021 - Quantitative microbial risk assessment for contaminated private wells in the fractured dolomite aquifer of Kewaunee County, Wisconsin","interactions":[],"lastModifiedDate":"2021-06-24T14:50:56.03881","indexId":"70221582","displayToPublicDate":"2021-06-23T09:46:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1542,"text":"Environmental Health Perspectives","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative microbial risk assessment for contaminated private wells in the fractured dolomite aquifer of Kewaunee County, Wisconsin","docAbstract":"Private wells are an important source of drinking water in Kewaunee County, Wisconsin. Due to the region’s fractured dolomite aquifer, these wells are vulnerable to contamination by human and zoonotic gastrointestinal pathogens originating from land-applied cattle manure and private septic systems.
We determined the magnitude of the health burden associated with contamination of private wells in Kewaunee County by feces-borne gastrointestinal pathogens.
This study used data from a year-long countywide pathogen occurrence study as inputs into a quantitative microbial risk assessment (QMRA) to predict the total cases of acute gastrointestinal illness (AGI) caused by private well contamination in the county. Microbial source tracking was used to associate predicted cases of illness with bovine, human, or unknown fecal sources.
Results suggest that private well contamination could be responsible for as many as 301 AGI cases per year in Kewaunee County, and that 230 and 12 cases per year were associated with a bovine and human fecal source, respectively. Furthermore, Cryptosporidium parvum was predicted to cause 190 cases per year, the most out of all 8 pathogens included in the QMRA.
This study has important implications for land use and water resource management in Kewaunee County and informs the public health impacts of consuming drinking water produced in other similarly vulnerable hydrogeological settings.
","language":"English","doi":"10.1289/EHP7815","usgsCitation":"Burch, T., Stokdyk, J.P., Spencer, S.K., Kieke, B.A., Firnstahl, A.D., Muldoon, M.A., and Borchardt, M.A., 2021, Quantitative microbial risk assessment for contaminated private wells in the fractured dolomite aquifer of Kewaunee County, Wisconsin: Environmental Health Perspectives, v. 129, no. 6, 067003, 9 p., https://doi.org/10.1289/EHP7815.","productDescription":"067003, 9 p.","ipdsId":"IP-120047","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":451765,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1289/ehp7815","text":"Publisher Index Page"},{"id":386700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Kewaunee County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-87.3761,44.6754],[-87.3774,44.674],[-87.381,44.6636],[-87.3858,44.6545],[-87.3911,44.6473],[-87.3944,44.6442],[-87.3966,44.6378],[-87.4045,44.6302],[-87.4085,44.6257],[-87.4137,44.6235],[-87.4223,44.6145],[-87.4263,44.61],[-87.4341,44.6056],[-87.442,44.6011],[-87.4428,44.5934],[-87.4468,44.5893],[-87.4502,44.5816],[-87.4544,44.5721],[-87.4604,44.5622],[-87.4664,44.555],[-87.4738,44.5455],[-87.476,44.5369],[-87.4761,44.5305],[-87.4796,44.5223],[-87.4851,44.5106],[-87.488,44.4974],[-87.4959,44.4706],[-87.5046,44.4575],[-87.5041,44.4534],[-87.5062,44.4457],[-87.5064,44.4375],[-87.5074,44.4279],[-87.5121,44.4188],[-87.5163,44.408],[-87.5191,44.3998],[-87.5212,44.3907],[-87.5209,44.3816],[-87.5218,44.3734],[-87.5232,44.3688],[-87.5279,44.3602],[-87.5351,44.3521],[-87.5386,44.3422],[-87.5368,44.338],[-87.5408,44.3331],[-87.5454,44.3277],[-87.6445,44.3273],[-87.7665,44.3271],[-87.7655,44.4146],[-87.7646,44.5017],[-87.7643,44.5888],[-87.7628,44.6477],[-87.7582,44.6522],[-87.7555,44.6558],[-87.7547,44.6608],[-87.7507,44.6667],[-87.7435,44.673],[-87.7389,44.6775],[-87.6413,44.6757],[-87.5193,44.6753],[-87.4384,44.6754],[-87.3973,44.6753],[-87.3761,44.6754]]]},\"properties\":{\"name\":\"Kewaunee\",\"state\":\"WI\"}}]}","volume":"129","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Burch, Tucker R.","contributorId":195801,"corporation":false,"usgs":false,"family":"Burch","given":"Tucker R.","affiliations":[],"preferred":false,"id":818182,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stokdyk, Joel P. 0000-0003-2887-6277 jstokdyk@usgs.gov","orcid":"https://orcid.org/0000-0003-2887-6277","contributorId":193848,"corporation":false,"usgs":true,"family":"Stokdyk","given":"Joel","email":"jstokdyk@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818183,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":818184,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kieke, Burney A","contributorId":195802,"corporation":false,"usgs":false,"family":"Kieke","given":"Burney","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":818185,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Firnstahl, Aaron D. 0000-0003-2686-7596 afirnstahl@usgs.gov","orcid":"https://orcid.org/0000-0003-2686-7596","contributorId":168296,"corporation":false,"usgs":true,"family":"Firnstahl","given":"Aaron","email":"afirnstahl@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818186,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muldoon, Maureen A.","contributorId":198974,"corporation":false,"usgs":false,"family":"Muldoon","given":"Maureen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":818187,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":210973,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":818188,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221563,"text":"ds1139 - 2021 - Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2020","interactions":[],"lastModifiedDate":"2021-06-25T11:54:48.413365","indexId":"ds1139","displayToPublicDate":"2021-06-23T08:51:05","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1139","displayTitle":"Water-Level Data for the Albuquerque Basin and Adjacent Areas, Central New Mexico, Period of Record Through September 30, 2020","title":"Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2020","docAbstract":"The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water in areas within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of 2020, the network consisted of 120 wells and piezometers. A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers screened at different depths. The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels from the wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at the sites through water year 2020 (October 1, 2019, through September 30, 2020). Water levels that were collected from discontinued wells in previous water years were published in previous USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1139","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Jurney, E.R., and Bell, M.T., 2021, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2020: U.S. Geological Survey Data Series 1139, 40 p., https://doi.org/10.3133/ds1139.","productDescription":"iv, 40 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-128111","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":386657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1139/coverthb.jpg"},{"id":386658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1139/ds1139.pdf","text":"Report","size":"6.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":386659,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/ds/1139/images"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.3583984375,\n 34.261756524459805\n ],\n [\n -106.14990234375,\n 34.261756524459805\n ],\n [\n -106.14990234375,\n 35.65729624809628\n ],\n [\n -107.3583984375,\n 35.65729624809628\n ],\n [\n -107.3583984375,\n 34.261756524459805\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Between 2012 and 2016, California suffered one of the most severe droughts on record. During this period Sequoiadendron giganteum (giant sequoias) in the Sequoia and Kings Canyon National Parks (SEKI), California, USA experienced canopy water content (CWC) loss, unprecedented foliage senescence, and, in a few cases, death. We present an assessment of the vulnerability of giant sequoia populations to droughts that is currently lacking and needed for management. We used a temporal trend of remotely sensed CWC obtained between 2015 and 2017, and recently georeferenced giant sequoia crowns to quantify the vulnerability of 7,408 individuals in 10 groves in the northern portion of SEKI. CWC is sensitive to changes in liquid water in tree canopies; therefore, it is a useful metric for quantifying the response of sequoia trees to drought. Temporal trends indicated that 9% of giant sequoias had a significant decline or consistently low CWC, suggesting these trees were likely operating at low photosynthetic capacity and potentially at high risk to drought stress. We also found that 20% of the giant sequoias had an increase or consistently high level of CWC, indicating these trees were at low risk to drought stress. These vulnerability categories were used in a random forest model with a combination of topographic, fire-related, and climate variables to generate high-resolution vulnerability risk maps. These maps show that higher risk is associated with lower elevation and higher climate water deficit. We also found that sequoias at higher elevations but located near meadows had higher vulnerability risk. These results and the vulnerability maps can identify vulnerable sequoias that may be difficult to save or locations of refugia to be protected, and thus may aid forest managers in preparation for future droughts.
Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS-980
Denver, CO 80225-0046
Groundwater is an important source of drinking water in California. Water-borne diseases caused by microbial contamination are a growing concern. The MI test, a membrane filtration method for the chromogenic/fluorogenic detection of total coliforms and Escherichia coli, was used for samples collected January to April 2014 from 42 domestic wells in the southeastern San Joaquin Valley. The wells were sampled as part of the Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP), a cooperative study between the U.S. Geological Survey and the California State Water Resources Control Board. Polymerase chain reaction analysis and sequencing of deoxyribonucleic acid (DNA) were used for 34 target and nontarget colonies that grew on the MI media from samples collected from 13 of the domestic wells to identify what genera of bacteria could exist in groundwater used by domestic wells. Gene sequences obtained using the Sanger method were entered into the basic local alignment search tool (BLAST) database, and 17 genera of bacteria were identified. Of these, 13 genera contain species that are human pathogens or opportunistic human pathogens. All the genera that include human pathogens are naturally present in soil, plants, or water; one of the pathogens also can be found in fecal matter. Six of the human pathogens were from non-target colony growth on the MI media. Target and non-target microbial growth on MI media are indicators of the possible presence of pathogenic bacteria even if the bacteria naturally are from soil rather than from a fecal source.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215030","collaboration":"Prepared in cooperation with California State Water Resources Control BoardDirector,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Mississippi Alluvial Plain hosts one of the most prolific shallow aquifer systems in the United States but is experiencing chronic groundwater decline. The Reelfoot rift and New Madrid seismic zone underlie the region and represent an important and poorly understood seismic hazard. Despite its societal and economic importance, the shallow subsurface architecture has not been mapped with the spatial resolution needed for effective management. Here, we present airborne electromagnetic, magnetic, and radiometric observations, measured over more than 43,000 flight-line-kilometers, which collectively provide a system-scale snapshot of the entire region. We develop detailed maps of aquifer connectivity and shallow geologic structure, infer relationships between structure and groundwater age, and identify previously unseen paleochannels and shallow fault structures. This dataset demonstrates how regional-scale airborne geophysics can close a scale gap in Earth observation by providing observational data at suitable scales and resolutions to improve our understanding of subsurface structures.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s43247-021-00200-z","usgsCitation":"Minsley, B.J., Rigby, J.R., James, S.R., Burton, B.L., Knierim, K.J., Pace, M., Bedrosian, P.A., and Kress, W., 2021, Airborne geophysical surveys of the lower Mississippi Valley demonstrate system-scale mapping of subsurface architecture: Communications Earth & Environment, v. 2, 131, 14 p., https://doi.org/10.1038/s43247-021-00200-z.","productDescription":"131, 14 p.","ipdsId":"IP-126061","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":451779,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-021-00200-z","text":"Publisher Index Page"},{"id":387124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.47265625,\n 37.405073750176925\n ],\n [\n -91.40625,\n 34.45221847282654\n ],\n [\n -91.7578125,\n 31.653381399664\n ],\n [\n -91.7138671875,\n 30.600093873550072\n ],\n [\n -90.17578124999999,\n 31.615965936476076\n ],\n [\n -89.12109375,\n 35.137879119634185\n ],\n [\n -88.41796875,\n 37.020098201368114\n ],\n [\n -89.47265625,\n 37.405073750176925\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationDate":"2021-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 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States","interactions":[],"lastModifiedDate":"2022-02-14T17:30:20.604864","indexId":"70228607","displayToPublicDate":"2021-06-22T11:19:50","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Hydrology of annual winter water level drawdown regimes in recreational lakes of Massachusetts, United States","docAbstract":"Annual winter water level drawdown (WD) is a common lake management strategy to maintain recreational value by controlling nuisance macrophytes and preventing ice damage to shoreline infrastructure in lakes of the northeastern United States. The state of Massachusetts provides general guidelines for lake managers to implement and practice WDs. However, WD management reporting is not required and as such empirical water level records are scarce, making it difficult to assess guideline adherence and link these management actions to littoral habitat conditions. We monitored water levels bihourly in 18 lakes with ongoing WD regimes and 3 non-drawdown lakes over 3–4 yr. Our results show an interlake drawdown magnitude gradient of 0.07–2.66 m with intralake consistency across years. Corresponding WD magnitudes generated exposure of 1.3–37.6% for entire lakebeds and 9.2–71.1% for littoral zones. WD durations averaged 171 d and ranged widely from 5 to 246 d. Longer recession and refill phase durations and faster recession rates were moderately to strongly correlated with drawdown magnitudes. WDs were predominantly initiated prior to the state of Massachusetts 1 November starting guideline (83.1%) and refilled to summer reference levels after the recommended date of 1 April (70.6%). To minimize ecological impacts while still meeting recreational goals, WD performance guidelines may require a more fine-scale approach that integrates local hydrogeomorphic features and the presence of WD-sensitive littoral biotic assemblages. However, climate change model projections of warmer and wetter winters in the Northeast indicate increasing uncertainty for WD as an effective and worthwhile macrophyte control tool.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2021.1927268","usgsCitation":"Carmignani, J., Roy, A.H., Stolarski, J., and Richards, T., 2021, Hydrology of annual winter water level drawdown regimes in recreational lakes of Massachusetts, United States: Lake and Reservoir Management, v. 37, no. 4, p. 339-359, https://doi.org/10.1080/10402381.2021.1927268.","productDescription":"21 p.","startPage":"339","endPage":"359","ipdsId":"IP-117681","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":451781,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/10402381.2021.1927268","text":"Publisher Index Page"},{"id":395898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Carmignani, Jason R.","contributorId":276347,"corporation":false,"usgs":false,"family":"Carmignani","given":"Jason R.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":834779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stolarski, Jason","contributorId":276348,"corporation":false,"usgs":false,"family":"Stolarski","given":"Jason","email":"","affiliations":[{"id":51525,"text":"Massachusetts Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":834780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Todd","contributorId":276349,"corporation":false,"usgs":false,"family":"Richards","given":"Todd","affiliations":[{"id":51525,"text":"Massachusetts Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":834781,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221400,"text":"ds1137 - 2021 - Survey of fish assemblages in the upper Neversink River and upper Rondout Creek, New York, 2017–19","interactions":[],"lastModifiedDate":"2021-06-23T12:09:25.791588","indexId":"ds1137","displayToPublicDate":"2021-06-22T11:05:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1137","displayTitle":"Survey of Fish Assemblages in the Upper Neversink River and Upper Rondout Creek, New York, 2017–19","title":"Survey of fish assemblages in the upper Neversink River and upper Rondout Creek, New York, 2017–19","docAbstract":"Streams in the Catskill Mountains region of New York provide many important ecological and economic services, including recreational angling and serving as a drinking water supply to New York City. Many streams in this region were adversely affected by acid deposition during the late 20th century, impairing water quality and aquatic ecosystems. More recently, the level of acid deposition has declined while changes in climate have become more pronounced. As a result, biological and chemical data are needed to determine the current condition of stream ecosystems in the Catskill Mountains region. The U.S. Geological Survey, in cooperation with the Rondout Neversink Stream Program, surveyed fish communities and water chemistry annually between 2017 and 2019 at 23 sites in the upper Neversink River and upper Rondout Creek watersheds to compile a contemporary baseline dataset and assess potential biological recovery from reduced acidification.
The resulting data indicated that brook trout (Salvelinus fontinalis) were present at every study site, although slimy sculpin (Cottus cognatus) was the most abundant species at most sites. Stream pH ranged from 4.8 to 7.0 across all sites and generally increased from upstream to downstream. Similarly, the number of species present and the ratio of brown trout (Salmo trutta) to brook trout increased at sites in each subwatershed from upstream to downstream.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1137","collaboration":"Prepared in cooperation with the Rondout Neversink Stream Program","usgsCitation":"Winterhalter, D.R., George, S.D., and Baldigo, B.P., 2021, Survey of fish assemblages in the upper Neversink River and upper Rondout Creek, 2017–19: U.S. Geological Survey Data Series 1137, 55 p., https://doi.org/10.3133/ds1137.","productDescription":"Report: viii, 55 p.; Data Release","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-1118329","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":386501,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1137/ds1137_2pg_spread.pdf","text":"Report (2-page spread)","size":"4.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1137 (2-page spread)","linkHelpText":"- To be printed on tabloid paper"},{"id":386500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1137/ds1137.pdf","text":"Report","size":"3.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1137"},{"id":386499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1137/coverthb2.jpg"},{"id":386502,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4V25","text":"USGS data release","linkHelpText":"Adirondack and Catskill stream-fish survey dataset (ver. 3.0, November 2020)"}],"country":"United States","state":"New York","otherGeospatial":"Upper Neversink River, Upper Rondout Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.157470703125,\n 41.66060124302088\n ],\n [\n -73.7841796875,\n 41.66060124302088\n ],\n [\n -73.7841796875,\n 42.40317854182803\n ],\n [\n -75.157470703125,\n 42.40317854182803\n ],\n [\n -75.157470703125,\n 41.66060124302088\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Rising global temperatures are expected to decrease the precipitation amount that falls as snow, causing greater risk of water scarcity, groundwater overdraft, and fire in areas that rely on mountain snowpack for their water supply. Streamflow in large river basins varies with the amount, timing, and type of precipitation, evapotranspiration, and drainage properties of watersheds; however, these controls vary in time and space making it difficult to identify the areas contributing most to flow and when. In this study, we separate the evaporative influences from source values of water isotopes from the Snake River Basin in the western United States (US) to relate source area to flow dynamics. We developed isoscapes (δ2H and δ18O) for the basin and found that isotopic composition of surface water in small watersheds is primarily controlled by longitude, latitude, and elevation. To examine temporal variability in source contributions to flow, we present a six-year record of Snake River water isotopes from King Hill, Idaho after removing evaporative influences. During periods of low flow, source water values were isotopically lighter indicating a larger contribution to flow from surface waters in the highest elevation, eastern portion of the basin. River evaporation increases were evident during summer likely reflecting climate, changing water availability, and management strategies within the basin. Our findings present a potential tool for identifying critical portions of basins contributing to river flow as climate fluctuations alter flow dynamics. This tool can be applied in other continental-interior basins where evaporation may obscure source water isotopic signatures.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020WR029157","usgsCitation":"Windler, G., Brooks, J.R., Johnson, H.M., Comeleo, R., Coulombe, R., and Bowen, G.J., 2021, Climate impacts on source contributions and evaporation to flow in the Snake River Basin using surface water isoscapes (δ2H and δ18O): Water Resources Research, v. 57, no. 7, e2020WR029157, 15 p., https://doi.org/10.1029/2020WR029157.","productDescription":"e2020WR029157, 15 p.","ipdsId":"IP-122721","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":451798,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8328002","text":"External Repository"},{"id":386865,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Oregon, Wyoming","otherGeospatial":"Snake River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.73999023437499,\n 42.16340342422401\n ],\n [\n -109.742431640625,\n 42.16340342422401\n ],\n [\n -109.742431640625,\n 45.78284835197676\n ],\n [\n -119.73999023437499,\n 45.78284835197676\n ],\n [\n -119.73999023437499,\n 42.16340342422401\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Windler, Grace","contributorId":260666,"corporation":false,"usgs":false,"family":"Windler","given":"Grace","email":"","affiliations":[{"id":52636,"text":"Department of Geosciences, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":818451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, J. Renee","contributorId":176587,"corporation":false,"usgs":false,"family":"Brooks","given":"J.","email":"","middleInitial":"Renee","affiliations":[],"preferred":false,"id":818452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Henry M. 0000-0002-7571-4994 hjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":869,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"hjohnson@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Comeleo, Randy","contributorId":217974,"corporation":false,"usgs":false,"family":"Comeleo","given":"Randy","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":818454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coulombe, Rob","contributorId":260667,"corporation":false,"usgs":false,"family":"Coulombe","given":"Rob","email":"","affiliations":[{"id":52638,"text":"Pacific Ecological Systems Division, Center for Public Health and Environmental Assessment Office of Research and Development, U.S. Environmental Protection Agency, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":818455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowen, Gabriel J.","contributorId":138889,"corporation":false,"usgs":false,"family":"Bowen","given":"Gabriel","email":"","middleInitial":"J.","affiliations":[{"id":12566,"text":"Department of Geology and Geophysics, Unviersity of Utah","active":true,"usgs":false}],"preferred":false,"id":818456,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70221489,"text":"cir1479 - 2021 - The North American Breeding Bird Survey in Mexico, 2008 to 2018—A status report","interactions":[],"lastModifiedDate":"2021-06-21T17:42:27.497155","indexId":"cir1479","displayToPublicDate":"2021-06-21T08:55:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1479","displayTitle":"The North American Breeding Bird Survey in Mexico, 2008 to 2018—A Status Report","title":"The North American Breeding Bird Survey in Mexico, 2008 to 2018—A status report","docAbstract":"Collection of avian population data has repeatedly been identified as a high priority for bird conservation in Mexico. To meet this need, in 2008 the North American Breeding Bird Survey (BBS), a volunteer-based survey, was expanded to include northern Mexico. The BBS in Mexico (Mexican BBS) is managed by the North American Bird Conservation Initiative (NABCI), Mexico’s National Coordination Office inside the Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO).
During 2008–18, 252 surveys were conducted along 68 routes in Mexico, with geographic coverage varying from year to year. Of these 68 routes, 36 were surveyed three or more times. Thirty-one observers conducted the surveys, and 21 of these observers conducted two or more surveys. Just two observers conducted more than one-third of the 252 surveys, and both observers were paid to conduct the surveys. The low availability of local observers who are qualified, willing, and able to volunteer their services to conduct BBS surveys may prove to be the biggest obstacle to the success of the Mexican BBS program, especially in the context of Mexico’s ongoing safety and security concerns.
Apart from the amount of data collected, many surveys did not adhere to pre-established quality-control requirements, and this would result in the exclusion of a large percentage of the data from potential trend analyses. Only 31 percent of the surveys met all the quality-control criteria. Additional observer training may help resolve this issue. Of greater concern is the selection of region-specific sampling date windows during which the surveys are conducted. Observers consistently conducted surveys outside the preliminarily prescribed sampling date window, reflecting the need to re-evaluate the regional appropriateness of this date window.
Regardless of the quality of the data, the quantity of data available from 2008 to 2018 is insufficient for trend analysis using methods typically employed by U.S. Geological Survey BBS analysts. Reaching minimum sample size thresholds for statistical analysis will require a substantial increase in effort. During 2008–18, no strata (defined as the intersection of State and Bird Conservation Region boundaries) reached the suggested minimum of 14 sampled routes, and most routes were not run consistently.
This report provides information needed for an evaluation of the merits of continuing to invest in the Mexican BBS program in its current form. Such an evaluation should consider the likelihood of achieving the primary project goal of producing reliable long-term population trend estimates, a projected timeline for meeting this goal, and include an assessment of the potential value of any additional data products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1479","usgsCitation":"U.S. Geological Survey and Mexican National Commission for the Knowledge and Use of Biodiversity, 2021, The North American Breeding Bird Survey in Mexico, 2008 to 2018—A Status Report: U.S. Geological Survey Circular 1479, 33 p., https://doi.org/10.3133/cir1479.","productDescription":"Report: v, 33 p.; Data Release","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120948","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":436297,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L4KBDC","text":"USGS data release","linkHelpText":"The North American Breeding Bird Survey in Mexico, 2008-2018 - unprocessed data"},{"id":386569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1479/cir1479.pdf","text":"Report","size":"14.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1479"},{"id":386568,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1479/coverthb.jpg"},{"id":386570,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.doi.org/10.5066/P9L4KBDC","text":"USGS data release","linkHelpText":"The North American Breeding Bird Survey in Mexico, 2008–2018—unprocessed data"}],"country":"Mexico","state":"Baja California, Baja California Sur, Chihuahua, Coahuila, Nuevo Leon, Sonora, Tamaulipas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.09423828125,\n 26.303264239389534\n ],\n [\n -108.336181640625,\n 27.049341619870376\n ],\n [\n -108.17138671875,\n 26.83387451505858\n ],\n [\n -107.808837890625,\n 26.185018250078308\n ],\n [\n -106.61132812499999,\n 25.54244147012483\n ],\n [\n -106.051025390625,\n 26.814266197561462\n ],\n [\n -104.501953125,\n 26.322960198925365\n ],\n [\n -104.21630859375,\n 26.775039386999605\n ],\n [\n -103.370361328125,\n 26.56887654795065\n ],\n [\n -103.436279296875,\n 25.3241665257384\n ],\n [\n -102.908935546875,\n 24.716895455859337\n ],\n [\n -102.469482421875,\n 25.06569718553588\n ],\n [\n -101.898193359375,\n 24.986058021167594\n ],\n [\n -100.74462890625,\n 24.5271348225978\n ],\n [\n -100.404052734375,\n 23.200960808078566\n ],\n [\n -100.1953125,\n 23.271627053918277\n ],\n [\n -100.08544921874999,\n 22.806567100271522\n ],\n [\n -99.42626953125,\n 22.664709810176827\n ],\n [\n -98.909912109375,\n 22.31958944283391\n ],\n [\n -98.63525390624999,\n 22.370396344320053\n ],\n [\n -98.184814453125,\n 22.451648819126202\n ],\n [\n -97.7947998046875,\n 22.17214491738176\n ],\n [\n -97.7288818359375,\n 24.307053283225915\n ],\n [\n -97.38830566406249,\n 25.18505888358067\n ],\n [\n -97.1246337890625,\n 25.962983554822678\n ],\n [\n -97.37182617187499,\n 25.86416657624641\n ],\n [\n -97.7398681640625,\n 26.03704188651584\n ],\n [\n -98.2342529296875,\n 26.046912801683984\n ],\n [\n -99.085693359375,\n 26.441065564038418\n ],\n [\n -99.50866699218749,\n 27.36201054924028\n ],\n [\n -99.51416015625,\n 27.581329075043357\n ],\n [\n -100.579833984375,\n 28.7965462417692\n ],\n [\n -101.4532470703125,\n 29.76437737516313\n ],\n [\n -102.32666015625,\n 29.854937397596693\n ],\n [\n -102.623291015625,\n 29.72145191669099\n ],\n [\n -103.216552734375,\n 28.98411731593083\n ],\n [\n -104.249267578125,\n 29.501768632523262\n ],\n [\n -104.5513916015625,\n 29.625996273660785\n ],\n [\n -104.6832275390625,\n 30.178373310707887\n ],\n [\n -105.0018310546875,\n 30.680439786468128\n ],\n [\n -106.46301269531249,\n 31.765537409484374\n ],\n [\n -106.5673828125,\n 31.770207631866715\n ],\n [\n -108.1988525390625,\n 31.774877618507386\n ],\n [\n -108.204345703125,\n 31.320794146937374\n ],\n [\n -111.0443115234375,\n 31.325486676506983\n ],\n [\n -114.466552734375,\n 32.37996146435729\n ],\n [\n -114.81811523437501,\n 32.509761735919426\n ],\n [\n -114.71923828124999,\n 32.72721987021932\n ],\n [\n -117.13623046874999,\n 32.54218257955074\n ],\n [\n -117.10876464843749,\n 32.29177633471201\n ],\n [\n -116.73522949218751,\n 31.81689688674699\n ],\n [\n -116.75170898437501,\n 31.63467554954133\n ],\n [\n -116.53198242187499,\n 31.245681880715527\n ],\n [\n -115.64208984374999,\n 29.616445727622548\n ],\n [\n -115.6640625,\n 27.737022779516813\n ],\n [\n -113.25256347656249,\n 26.115985925333536\n ],\n [\n -111.68701171875,\n 23.83560098662095\n ],\n [\n -109.8687744140625,\n 22.71032284205226\n ],\n [\n -109.2041015625,\n 23.427968862308678\n ],\n [\n -110.54443359375,\n 25.27450351782018\n ],\n [\n -109.434814453125,\n 26.367263860129366\n ],\n [\n -109.09423828125,\n 26.303264239389534\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Road
Laurel, MD
Altered flow regimes can contribute to dissociation between life history strategies and environmental conditions, leading to reduced persistence reported for many wildlife populations inhabiting regulated rivers. The Oregon spotted frog (Rana pretiosa) is a threatened species occurring in floodplains, ponds, and wetlands in the Pacific Northwest with a core range in Oregon, USA. All life stages of R. pretiosa are reliant on aquatic habitats, and inundation patterns across the phenological timeline can have implications for population success. We conducted capture–mark–recapture (CMR) sampling of adult and subadult R. pretiosa at three sites along the Deschutes River downstream from two dams that regulate flows. We related the seasonal extent of inundated habitat at each site to monthly survival probabilities using a robust design CMR model. We also developed matrix projection models to simulate population dynamics into the future under current river flows. Monthly survival was strongly associated with the extent and variability of inundated habitat, suggesting some within-season fluctuations at higher water levels could be beneficial. Seasonal survival was lowest in the winter for all three sites, owing to limited water availability and the greater number of months within this season relative to other seasons. Population growth for the two river-connected sites was most strongly linked to adult survival, whereas population growth at the river-disconnected site was most strongly tied to survival in juvenile stages. This research identifies population effects of seasonally limited water and highlights conservation potential of enhancing survival of particularly influential life stages.
Peatlands within the northern permafrost region cover approximately 2 million km2 and are characterized by organic soils that can be several meters thick, and a fine-scale mosaic of permafrost and non-permafrost landforms interspersed by shallow ponds and lakes. Ongoing permafrost thaw is transforming these peatlands, causing abrupt changes to their morphology, hydrology, ecology, and biogeochemistry. In this review we show how changes to individual peatlands depend on both their Holocene developmental history and their location within current permafrost zones. Permafrost thaw in peatlands often leads to land surface collapse between 0.5 and 5 m, the so-called thermokarst. Thermokarst in peatlands can lead to the development of ice-wedge troughs, waterlogged thermokarst bogs and fens, and the initiation, expansion, and drainage of thermokarst lakes. Permafrost thaw in peatlands can thus completely alter vegetation composition and shift patterns of landscape inundation and hydrological connectivity. These changes in turn have implications for magnitude and timing of runoff, downstream water quality, habitat suitability for birds and larger mammals, traditional land-use, and the exchange of greenhouse gases with the atmosphere. Ongoing permafrost thaw is largely irreversible at relevant human time-scales, and peatland thermokarst has been accelerating over the last few decades. Complete permafrost loss is expected this century for peatlands in relatively warmer permafrost zones, and all peatlands in the northern permafrost region will be profoundly transformed by permafrost thaw.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecosystem collapse and climate change","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-71330-0_3","usgsCitation":"Olefeldt, D., Hefferman, L., Jones, M.C., Sannel, A.B., Treat, C.C., and Turetsky, M.R., 2021, Permafrost thaw in northern peatlands: Rapid changes in ecosystem and landscape functions, chap. of Ecosystem collapse and climate change, p. 27-67, https://doi.org/10.1007/978-3-030-71330-0_3.","productDescription":"41 p.","startPage":"27","endPage":"67","ipdsId":"IP-112928","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":386702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":818208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hefferman, Liam","contributorId":260626,"corporation":false,"usgs":false,"family":"Hefferman","given":"Liam","email":"","affiliations":[],"preferred":false,"id":818223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Miriam C. 0000-0002-6650-7619","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":257239,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":818209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sannel, A. Britta","contributorId":260622,"corporation":false,"usgs":false,"family":"Sannel","given":"A.","email":"","middleInitial":"Britta","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":818210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Treat, Claire C.","contributorId":150798,"corporation":false,"usgs":false,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":818211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":818212,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217621,"text":"70217621 - 2021 - Extreme events trigger terrestrial and marine ecosystem collapses: A tale of two regions","interactions":[],"lastModifiedDate":"2021-09-21T15:52:23.755967","indexId":"70217621","displayToPublicDate":"2021-06-19T10:48:11","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"8","title":"Extreme events trigger terrestrial and marine ecosystem collapses: A tale of two regions","docAbstract":"We outline the multiple, cross-scale, and complex consequences of terrestrial and marine ecosystem heatwaves in two regions on opposite sides of the planet: the southwestern USA and southwestern Australia, both encompassing Global Biodiversity Hotspots, and where ecosystem collapses or features of it have occurred in the past two decades. We highlight ecosystem shifts that have clearly demonstrated a substantial change from a baseline state over time, although not necessarily across their entire distribution, with evidence of collapse at local scales. Responses to temperature extremes, such as heatwaves, encompass processes at all scales, including population level (e.g. altered demography such as survival, recruitment, and fecundity, together resulting in structural changes), community level (e.g. species compositional shifts), and ecosystem level (e.g. carbon loss), as well as physical properties altered by vegetation loss (e.g. microclimate, fire behaviour on land). These changes impact all trophic levels with foundational species losses (such as seagrasses, kelp, and trees), flowing through to vertebrates (such as sea turtles, penguins, and cockatoos). Where extensive collapse has occurred, shifts in microclimate could affect important biosphere-to-atmosphere feedbacks including fluxes of energy, carbon, and water. Such extensive changes usually do not occur in isolation and frequently interact with other disturbance processes such as fire, storms, pathogen and pest outbreaks, and anthropogenic stressors. Interactions may alter the likelihood, extent, or severity of subsequent disturbances (linked disturbances) as well as condition the ecological response and recovery (compound disturbances). In addition, if ecosystem collapse is extensive enough (e.g. tree die-off), those changes also can impact climate and ecosystems elsewhere via ecoclimate teleconnections. Increasing rates of climatic extremes will drive a host of direct and indirect feedbacks certain to produce large-scale shifts in ecological functioning at unprecedented rates. Understanding how, why, and where these shifts will occur will be critical for effective ecosystem management and climate change mitigation.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ecosystem collapse and climate change","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Ruthrof, K.X., Fontaine, J.B., Breshears, D.D., Field, J.P., and Allen, C.D., 2021, Extreme events trigger terrestrial and marine ecosystem collapses: A tale of two regions, chap. 8 of Ecosystem collapse and climate change, p. 187-217.","productDescription":"31 p.","startPage":"187","endPage":"217","ipdsId":"IP-114954","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":389550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruthrof, Katinka X.","contributorId":203622,"corporation":false,"usgs":false,"family":"Ruthrof","given":"Katinka","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":808922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fontaine, Joseph B.","contributorId":168610,"corporation":false,"usgs":false,"family":"Fontaine","given":"Joseph","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":808923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":808924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Field, Jason P.","contributorId":216389,"corporation":false,"usgs":false,"family":"Field","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":808925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":808926,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221546,"text":"70221546 - 2021 - Comparison of historical water temperature measurements with landsat analysis ready data provisional surface temperature estimates for the Yukon River in Alaska","interactions":[],"lastModifiedDate":"2021-06-23T12:24:25.466012","indexId":"70221546","displayToPublicDate":"2021-06-19T07:08:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of historical water temperature measurements with landsat analysis ready data provisional surface temperature estimates for the Yukon River in Alaska","docAbstract":"Water temperature is a key element of freshwater ecological systems and a critical element within natural resource monitoring programs. In the absence of in situ measurements, remote sensing platforms can indirectly measure water temperature over time and space. The Earth Resources Observation and Science (EROS) Center has processed archived Landsat imagery into analysis ready data (ARD), including Level-2 Provisional Surface Temperature (pST) estimates derived from the Landsat 4–5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Thermal Infrared Sensor (TIRS). We compared in situ measurements of water temperature within the Yukon River in Alaska with 52 instances of pST estimates between June 2014 and September 2020. Agreement was good with an RMSE of 2.25 °C and only a slight negative bias in the estimated mean daily water temperature of −0.47 °C. For the 52 dates compared, the average daily water temperature measured by the USGS streamgage was 11.3 °C with a standard deviation of 5.7 °C. The average daily pST estimate was 10.8 °C with a standard deviation of 6.1 °C. At least in the case of large unstratified rivers in Alaska, ARD pST can be used to infer water temperature in the absence of or in tandem with ground-based water temperature monitoring campaigns.
","language":"English","publisher":"MDPI","doi":"10.3390/rs13122394","usgsCitation":"Baughman, C., and Conaway, J., 2021, Comparison of historical water temperature measurements with landsat analysis ready data provisional surface temperature estimates for the Yukon River in Alaska: Remote Sensing, v. 13, no. 12, 2394, 45 p., https://doi.org/10.3390/rs13122394.","productDescription":"2394, 45 p.","ipdsId":"IP-127623","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":451818,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13122394","text":"Publisher Index Page"},{"id":436300,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MCNPGK","text":"USGS data release","linkHelpText":"Historical Landsat-Derived Water Surface Temperature for Three Large Alaska Rivers 1984-2022"},{"id":386643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164.53125,\n 61.48075950007598\n ],\n [\n -158.81835937499997,\n 61.48075950007598\n ],\n [\n -158.81835937499997,\n 63.35212928507874\n ],\n [\n -164.53125,\n 63.35212928507874\n ],\n [\n -164.53125,\n 61.48075950007598\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-06-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Baughman, Carson 0000-0002-9423-9324 cbaughman@usgs.gov","orcid":"https://orcid.org/0000-0002-9423-9324","contributorId":169657,"corporation":false,"usgs":true,"family":"Baughman","given":"Carson","email":"cbaughman@usgs.gov","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":818015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conaway, Jeff 0000-0002-3036-592X","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":214226,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeff","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":818016,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221855,"text":"70221855 - 2021 - Sediment transport, turbidity, and dissolved oxygen responses to annual streambed drawdowns for downstream fish passage in a flood control reservoir","interactions":[],"lastModifiedDate":"2021-07-12T17:40:19.227133","indexId":"70221855","displayToPublicDate":"2021-06-18T12:39:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Sediment transport, turbidity, and dissolved oxygen responses to annual streambed drawdowns for downstream fish passage in a flood control reservoir","docAbstract":"Sediment transport, turbidity, and dissolved oxygen were evaluated during six consecutive water years (2013–2018) of drawdowns of a flood control reservoir in the upper Willamette Valley, Oregon, USA. The drawdowns were conducted to allow volitional passage of endangered juvenile chinook salmon through the dam's regulating outlets by lowering the reservoir elevation to a point where the historical streambed was exposed and transported water and sediment through the reservoir dam. Sediment loads during the drawdown were highest in the first year of monitoring, with a computed value of 40,200 metric tons over a 5-day drawdown, followed by 5 years of lower sediment loads and lower sediment transport rates, suggesting that much of the stored sediment within the reservoir thalweg was transported out of the reservoir in the early years of the consecutive drawdowns. Suspended sediment concentrations (SSC) computed using turbidity and streamflow data resulted in maximum SSC at the onset of the drawdowns, with the highest computed values occurring during the water year 2017 drawdown at 17,500 mg/L (turbidity = 2,990 FNU), and average drawdown SSC values ranging from 654 to 3,950 mg/L for the six years of monitoring. Computed SSC were on the lower range of concentrations that could be harmful to out-migrating juvenile salmon published in other studies. High amounts of particulate organic matter and sand-sized material in drawdown SSC samples affected relations between turbidity and SSC, requiring the use of multiple surrogate regression models over short time frames. Dissolved oxygen minimum values were recorded in two of the monitoring years, with a minimum value of 0.71 and 3.4 mg/L recorded at the onset of the drawdowns in water years 2016 and 2018, respectively. Dissolved oxygen values below 4 mg/L lasted for 1 h, suggesting a rapidly expressed chemical oxygen demand. The response of suspended sediment loads and SSC highlight the site-specific nature of reservoir drawdowns, and the need for evaluation of expected sediment responses for drawdowns being considered at other locations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2021.113068","usgsCitation":"Schenk, L.N., and Bragg, H.M., 2021, Sediment transport, turbidity, and dissolved oxygen responses to annual streambed drawdowns for downstream fish passage in a flood control reservoir: Journal of Environmental Management, v. 295, 113068, 11 p., https://doi.org/10.1016/j.jenvman.2021.113068.","productDescription":"113068, 11 p.","ipdsId":"IP-119744","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":387132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Fall Creek Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.69325256347656,\n 43.923862711777446\n ],\n [\n -122.73548126220703,\n 43.9429004110983\n ],\n [\n -122.69565582275389,\n 43.95130472827632\n ],\n [\n -122.65342712402344,\n 43.97305156068593\n ],\n [\n -122.66578674316406,\n 43.97972228837853\n ],\n [\n -122.71076202392577,\n 43.96069638244953\n ],\n [\n -122.75333404541016,\n 43.959460723283826\n ],\n [\n -122.76226043701173,\n 43.958472177448414\n ],\n [\n -122.76191711425781,\n 43.93820336335502\n ],\n [\n -122.7509307861328,\n 43.93721446391471\n ],\n [\n -122.73616790771484,\n 43.93251696697599\n ],\n [\n -122.70767211914064,\n 43.92336814487696\n ],\n [\n -122.69256591796876,\n 43.92287357386489\n ],\n [\n -122.69325256347656,\n 43.923862711777446\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"295","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bragg, Heather M. 0000-0002-0013-4573 hmbragg@usgs.gov","orcid":"https://orcid.org/0000-0002-0013-4573","contributorId":239645,"corporation":false,"usgs":true,"family":"Bragg","given":"Heather","email":"hmbragg@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":819010,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70232408,"text":"70232408 - 2021 - Egg retention of high-latitude sockeye salmon (Oncorhynchus nerka) in the Pilgrim River, Alaska, during the Pacific marine heatwave of 2014–2016","interactions":[],"lastModifiedDate":"2022-06-30T17:06:48.667022","indexId":"70232408","displayToPublicDate":"2021-06-18T11:59:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Egg retention of high-latitude sockeye salmon (Oncorhynchus nerka) in the Pilgrim River, Alaska, during the Pacific marine heatwave of 2014–2016","title":"Egg retention of high-latitude sockeye salmon (Oncorhynchus nerka) in the Pilgrim River, Alaska, during the Pacific marine heatwave of 2014–2016","docAbstract":"Ocean and freshwater conditions can influence spawning success of Pacific salmon (Oncorhynchus spp.) by governing the energy content of fish at the start of and during the spawning migration. Ocean conditions determine the energy stores of fish at the freshwater entry, while freshwater conditions determine how quickly stored energy is depleted as individuals migrate to spawning grounds in natal rivers and lakes. We assessed the occurrence of sockeye salmon (Oncorhynchus nerka) egg retention (failure to deposit eggs) in a high-latitude (~ 65°N) watershed that has a large, inter-annual variation in the number of returning adults. We also explored relationships between ocean and freshwater conditions with egg retention of female sockeye salmon. The proportion of females with egg retention (> 50 eggs) varied by threefold (12 to 36%) across years (2013 to 2020) and was related to ocean conditions represented by the North Pacific Index (NPI). Egg retention was more common in years with low NPI values (a stronger Aleutian Low) in association with the Pacific marine heatwave of 2014–2016 that disrupted food webs. This initial study contains the first empirical data observing the influence of ocean conditions on egg retention for any Pacific salmon population. The lack of any relationship between egg retention and freshwater temperatures was consistent with water temperatures primarily occurring below thresholds associated with heat stress related mortality (< 18 °C). Understanding the amount of egg retention and how environmental drivers influence egg retention within Pacific salmon populations provides insights for managers assessing the number of successful spawners and helps refine escapement-based management efforts.
","language":"English","publisher":"Springer","doi":"10.1007/s00300-021-02902-8","usgsCitation":"Carey, M.P., von Biela, V.R., Dunker, A., Keith, K.D., Schelske, M., Lean, C., and Zimmerman, C.E., 2021, Egg retention of high-latitude sockeye salmon (Oncorhynchus nerka) in the Pilgrim River, Alaska, during the Pacific marine heatwave of 2014–2016: Polar Biology, v. 44, p. 1643-1654, https://doi.org/10.1007/s00300-021-02902-8.","productDescription":"12 p.","startPage":"1643","endPage":"1654","ipdsId":"IP-120209","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":402767,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Pilgrim River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -167,\n 64.5\n ],\n [\n -165,\n 64.5\n ],\n [\n -165,\n 65.25\n ],\n [\n -167,\n 65.25\n ],\n [\n -167,\n 64.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","noUsgsAuthors":false,"publicationDate":"2021-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":845449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"von Biela, Vanessa R. 0000-0002-7139-5981 vvonbiela@usgs.gov","orcid":"https://orcid.org/0000-0002-7139-5981","contributorId":3104,"corporation":false,"usgs":true,"family":"von Biela","given":"Vanessa","email":"vvonbiela@usgs.gov","middleInitial":"R.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":845450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunker, Ashley","contributorId":292682,"corporation":false,"usgs":false,"family":"Dunker","given":"Ashley","email":"","affiliations":[{"id":33645,"text":"Norton Sound Fisheries Research & Development","active":true,"usgs":false}],"preferred":false,"id":845451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith, Kevin D.","contributorId":192846,"corporation":false,"usgs":false,"family":"Keith","given":"Kevin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":845452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schelske, Merlyn","contributorId":192847,"corporation":false,"usgs":false,"family":"Schelske","given":"Merlyn","email":"","affiliations":[],"preferred":false,"id":845453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lean, Charlie","contributorId":221506,"corporation":false,"usgs":false,"family":"Lean","given":"Charlie","affiliations":[{"id":33645,"text":"Norton Sound Fisheries Research & Development","active":true,"usgs":false}],"preferred":false,"id":845454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":845455,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70221701,"text":"70221701 - 2021 - New geochemical tools for investigating resource and energy functions at deep-sea cold seeps using amino-acid δ15N in chemosymbiotic mussels (Bathymodiolus childressi)","interactions":[],"lastModifiedDate":"2021-11-01T15:36:01.701983","indexId":"70221701","displayToPublicDate":"2021-06-18T10:07:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1751,"text":"Geobiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"New geochemical tools for investigating resource and energy functions at deep-sea cold seeps using amino acid δ15N in chemosymbiotic mussels (Bathymodiolus childressi)","title":"New geochemical tools for investigating resource and energy functions at deep-sea cold seeps using amino-acid δ15N in chemosymbiotic mussels (Bathymodiolus childressi)","docAbstract":"In order to reconstruct the ecosystem structure of chemosynthetic environments in the fossil record, geochemical proxies must be developed. Here, we present a suite of novel compound-specific isotope parameters for tracing chemosynthetic production with a focus on understanding nitrogen dynamics in deep-sea cold seep environments. We examined the chemosymbiotic bivalve Bathymodiolus childressi from three geographically distinct seep sites on the NE Atlantic Margin and compared isotope data to non-chemosynthetic littoral mussels to test whether water depth, seep activity, and/or mussel bed size are linked to differences in chemosynthetic production. The bulk isotope analysis of carbon (δ13C) and nitrogen (δ15N), and δ15N values of individual amino acids (δ15NAA) in both gill and muscle tissues, as well as δ15NAA-derived parameters including trophic level (TL), baseline δ15N value (δ15NPhe), and a microbial resynthesis index (ΣV), were used to investigate specific geochemical signatures of chemosynthesis. Our results show that δ15NAA values provide a number of new proxies for relative reliance on chemosynthesis, including TL, ∑V, and both δ15N values and molar percentages (Gly/Glu mol% index) of specific AA. Together, these parameters suggested that relative chemoautotrophy is linked to both degree of venting from seeps and mussel bed size. Finally, we tested a Bayesian mixing model using diagnostic AA δ15N values, showing that percent contribution of chemoautotrophic versus heterotrophic production to seep mussel nutrition can be directly estimated from δ15NAA values. Our results demonstrate that δ15NAA analysis can provide a new set of geochemical tools to better understand mixotrophic ecosystem function and energetics, and suggest extension to the study of ancient chemosynthetic environments in the fossil record.
","language":"English","publisher":"Wiley","doi":"10.1111/gbi.12458","usgsCitation":"Vokhshoori, N., McCarthy, M., Close, H., Demopoulos, A., and Prouty, N.G., 2021, New geochemical tools for investigating resource and energy functions at deep-sea cold seeps using amino-acid δ15N in chemosymbiotic mussels (Bathymodiolus childressi): Geobiology, v. 19, no. 6, p. 601-617, https://doi.org/10.1111/gbi.12458.","productDescription":"17 p.","startPage":"601","endPage":"617","ipdsId":"IP-121092","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":386867,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Vokhshoori, Natasha","contributorId":260681,"corporation":false,"usgs":false,"family":"Vokhshoori","given":"Natasha","email":"","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":818469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Matt","contributorId":260682,"corporation":false,"usgs":false,"family":"McCarthy","given":"Matt","email":"","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":818470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Close, Hilary","contributorId":199931,"corporation":false,"usgs":false,"family":"Close","given":"Hilary","affiliations":[],"preferred":false,"id":818471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222192,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":818472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818473,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221695,"text":"70221695 - 2021 - Nutrient limitation of algae and macrophytes in streams: Integrating laboratory bioassays, field experiments, and field data","interactions":[],"lastModifiedDate":"2021-06-29T14:31:23.162807","indexId":"70221695","displayToPublicDate":"2021-06-18T09:13:25","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":"Nutrient limitation of algae and macrophytes in streams: Integrating laboratory bioassays, field experiments, and field data","docAbstract":"Successful eutrophication control strategies need to address the limiting nutrient. We conducted a battery of laboratory and in situ nutrient-limitation tests with waters collected from 9 streams in an agricultural region of the upper Snake River basin, Idaho, USA. Laboratory tests used the green alga Raphidocelis subcapitata, the macrophyte Lemna minor (duckweed) with native epiphytes, and in situ nutrient-limitation tests of periphyton were conducted with nutrient-diffusing substrates (NDS). In the duckweed/epiphyte test, P saturation occurred when concentrations reached about 100 μg/L. Chlorophyll a in epiphytic periphyton was stimulated at low P additions and by about 100 μg/L P, epiphytic periphyton chlorophyll a appeared to be P saturated. Both duckweed and epiphyte response patterns with total N were weaker but suggested a growth stimulation threshold for duckweed when total N concentrations exceeded about 300 μg/L and approached saturation at the highest N concentration tested, 1300 μg/L. Nutrient uptake by epiphytes and macrophytes removed up to 70 and 90% of the N and P, respectively. The green algae and the NDS nutrient-limitation test results were mostly congruent; N and P co-limitation was the most frequent result for both test series. Across all tests, when N:P molar ratios >30 (mass ratios >14), algae or macrophyte growth was P limited; N limitation was observed at N:P molar ratios up to 23 (mass ratios up to 10). A comparison of ambient periphyton chlorophyll a concentrations with chlorophyll a accrued on control artificial substrates in N-limited streams, suggests that total N concentrations associated with a periphyton chlorophyll a benchmark for desirable or undesirable conditions for recreation would be about 600 to 1000 μg/L total N, respectively. For P-limited streams, the corresponding benchmark concentrations were about 50 to 90 μg/L total P, respectively. Our approach of integrating controlled experiments and matched biomonitoring field surveys was cost effective and more informative than either approach alone.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0252904","usgsCitation":"Mebane, C.A., Ray, A.M., and Marcarelli, A.M., 2021, Nutrient limitation of algae and macrophytes in streams: Integrating laboratory bioassays, field experiments, and field data: PLoS ONE, v. 16, no. 6, e0252904, 27 p., https://doi.org/10.1371/journal.pone.0252904.","productDescription":"e0252904, 27 p.","ipdsId":"IP-127847","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":451823,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0252904","text":"Publisher Index Page"},{"id":386850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Cottonwood Creek, Stalker Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.98040771484375,\n 42.176126260952934\n ],\n [\n -113.76480102539062,\n 42.176126260952934\n ],\n [\n -113.76480102539062,\n 42.33063116562984\n ],\n [\n -113.98040771484375,\n 42.33063116562984\n ],\n [\n -113.98040771484375,\n 42.176126260952934\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.16468620300293,\n 43.311127198613335\n ],\n [\n -114.15696144104004,\n 43.320744323395154\n ],\n [\n -114.16399955749512,\n 43.32218051659263\n ],\n [\n -114.17404174804688,\n 43.31118965238512\n ],\n [\n -114.18365478515625,\n 43.316560436671395\n ],\n [\n -114.19017791748047,\n 43.32823713177707\n ],\n [\n -114.20339584350586,\n 43.34365692013493\n ],\n [\n -114.21223640441895,\n 43.33966188522517\n ],\n [\n -114.20125007629395,\n 43.328986361785745\n ],\n [\n -114.18837547302246,\n 43.313625299426235\n ],\n [\n -114.18022155761719,\n 43.307005107782196\n ],\n [\n -114.17326927185059,\n 43.306755275110774\n ],\n [\n -114.16468620300293,\n 43.311127198613335\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":818449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marcarelli, Amy M 0000-0002-4175-9211","orcid":"https://orcid.org/0000-0002-4175-9211","contributorId":257363,"corporation":false,"usgs":false,"family":"Marcarelli","given":"Amy","email":"","middleInitial":"M","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":818450,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221662,"text":"70221662 - 2021 - Land-based sediment sources and transport to southwest Puerto Rico coral reefs after Hurricane Maria, May 2017 to June 2018","interactions":[],"lastModifiedDate":"2021-06-28T13:22:06.601915","indexId":"70221662","displayToPublicDate":"2021-06-18T08:16:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Land-based sediment sources and transport to southwest Puerto Rico coral reefs after Hurricane Maria, May 2017 to June 2018","docAbstract":"The effects of runoff from land on nearshore ecosystems, including coral reef communities, are influenced by both sediment supply and removal by coastal processes. Integrated studies across the land-sea interface describing sources and transport of terrestrial sediment and its nearshore fate allow reef protection initiatives to target key onshore and offshore areas. Geochemical signatures in the fine fraction of terrestrial sediment from watersheds in southwest Puerto Rico were determined by multivariate principal component analysis and used to identify terrestrial sources of sediment runoff to nearshore coral reefs. Sediment settling out of suspension at reefs was collected at approximately 2 month-long intervals in bottom-mounted sediment traps from May 2017 to June 2018, a period that included Hurricanes Irma and Maria. Bulk sediment accumulation rates in traps exceeded a 10 mg/cm2/d threshold found to stress corals at 5 of 7 reef sites throughout the 13 month-long study. Geochemical signatures showed that watersheds 10s km to the east were a predominant, year-round source of fine sediment to reefs offshore of Guánica Bay and could have introduced sediment-bound contaminants due to a higher degree of industrialization and urbanization than the local watershed. Sediment runoff from the local watershed appeared to be constrained to a narrow band close to shore. During the 2.5 months after Hurricanes Irma and Maria, bulk sediment accumulation rates increased substantially and fine sediment geochemical signatures were indicative of predominantly distal sources, except outside of the mouth of Guánica Bay, which was strongly impacted by local runoff. Mass wasting, sediment runoff, and coastal turbidity persisted for months after Hurricane Maria and could account for the appearance of a small fraction of geochemical variance from a distal sediment source that appeared in reef traps 4 months post-hurricane and persisted through the end of the study 9 months post-hurricane. Sediment geochemical sourcing in temporally resolved records from sediment traps showed how landscape-scale changes after a major hurricane affected both near-term and long-term sediment delivery to reef communities. In addition, the importance of fine sediment advection from distal sources indicates that successful reduction of land-based pressures on nearshore ecosystems will require cross-jurisdictional strategies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2021.107476","usgsCitation":"Takesue, R.K., Sherman, C.E., Reyes, A.O., Cheriton, O.M., Ramirez, N.I., Viqueira Rios, R., and Storlazzi, C.D., 2021, Land-based sediment sources and transport to southwest Puerto Rico coral reefs after Hurricane Maria, May 2017 to June 2018: Estuarine, Coastal and Shelf Science, v. 259, 107476, 12 p., https://doi.org/10.1016/j.ecss.2021.107476.","productDescription":"107476, 12 p.","ipdsId":"IP-113468","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2021.107476","text":"Publisher Index Page"},{"id":386790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.16354370117188,\n 17.770920015568638\n ],\n [\n -66.1761474609375,\n 17.770920015568638\n ],\n [\n -66.1761474609375,\n 18.135411517108345\n ],\n [\n -67.16354370117188,\n 18.135411517108345\n ],\n [\n -67.16354370117188,\n 17.770920015568638\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"259","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Takesue, Renee K. 0000-0003-1205-0825 rtakesue@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0825","contributorId":2159,"corporation":false,"usgs":true,"family":"Takesue","given":"Renee","email":"rtakesue@usgs.gov","middleInitial":"K.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":818370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":818371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reyes, Aaron O.","contributorId":260655,"corporation":false,"usgs":false,"family":"Reyes","given":"Aaron","email":"","middleInitial":"O.","affiliations":[{"id":52630,"text":"Westfield State University","active":true,"usgs":false}],"preferred":false,"id":818372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":818373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramirez, Natalia I.","contributorId":260656,"corporation":false,"usgs":false,"family":"Ramirez","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":52631,"text":"University of Puerto Rico at Mayaguez","active":true,"usgs":false}],"preferred":false,"id":818374,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Viqueira Rios, Roberto","contributorId":260657,"corporation":false,"usgs":false,"family":"Viqueira Rios","given":"Roberto","email":"","affiliations":[{"id":52632,"text":"Protectores de Cuencas, Inc.","active":true,"usgs":false}],"preferred":false,"id":818375,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":818376,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230947,"text":"70230947 - 2021 - Regional occurrence of aqueous tungsten and relations with antimony, arsenic and molybdenum concentrations (Sardinia, Italy)","interactions":[],"lastModifiedDate":"2022-04-29T12:18:41.756084","indexId":"70230947","displayToPublicDate":"2021-06-18T07:15:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Regional occurrence of aqueous tungsten and relations with antimony, arsenic and molybdenum concentrations (Sardinia, Italy)","docAbstract":"Tungsten (W) is rarely found in natural waters, yet it can be introduced into the food chain and cause potentially toxic effects. Uptake of W by plants and vegetables, or trace presence of W in drinking water are possible vectors for ingestion of W by humans. The latter is recognized as a possible cause of lymphatic leukemia. Increased uses of W might result in a degradation of water resources, with attendant adverse effects on biota and human health. Therefore, this study was aimed at investigating regional occurrence and speciation of W in aquatic systems in Sardinia, Italy, factors affecting W mobility and possible relations with other oxyanion-forming trace elements such as Sb, As and Mo. Although our results are specifically from Sardinia, the implications are broader and should prompt future studies in other areas with known high W concentrations.
A total of 350 sample sites are reported here, including surface waters, groundwaters, mine drainages, thermal waters and local seawater. The waters were analyzed for major and trace components, including W, Sb, As and Mo. The waters showed a variety of major chemical compositions and W concentrations. High concentrations of W were found in some mine waters and drainages from slag heaps, with W, Sb and As up to 140, 5000 and 800 μg L−1, respectively. The highest concentrations of W occurred under slightly alkaline pH and oxygenated conditions, and were likely due to the dissolution of scheelite [CaWO4] hosted in materials with which the water came into contact. High W concentrations also were observed in thermal waters, under alkaline pH and reducing conditions, and sometimes coincided with relatively high concentrations either of As or Mo.
Previous studies of W geochemistry have focused on WO42− as the major dissolved form of W. For this study, we have augmented the thermodynamic database in PHREEQC to include possible formation of many other W-bearing complexes gleaned from the literature. The results of the speciation calculations with the newly added complexation reactions shows that the neutral species CaWO4° and MgWO4° are particularly dominant in most W-bearing waters and lead to undersaturation with respect to scheelite and other W-bearing minerals.
Assessing W contamination in water systems and establishing W limits in drinking water may prevent potential adverse effects of W on human and ecosystem health.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2021.106846","usgsCitation":"Cidu, R., Biddau, R., Frau, F., Wanty, R., and Naitza, S., 2021, Regional occurrence of aqueous tungsten and relations with antimony, arsenic and molybdenum concentrations (Sardinia, Italy): Journal of Geochemical Exploration, v. 229, 106846, 16 p., https://doi.org/10.1016/j.gexplo.2021.106846.","productDescription":"106846, 16 p.","ipdsId":"IP-127822","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":399886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","otherGeospatial":"Sardinia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 7.943115234375001,\n 38.865374851611634\n ],\n [\n 9.920654296875,\n 38.865374851611634\n ],\n [\n 9.920654296875,\n 41.31082388091818\n ],\n [\n 7.943115234375001,\n 41.31082388091818\n ],\n [\n 7.943115234375001,\n 38.865374851611634\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"229","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cidu, Rosa","contributorId":290729,"corporation":false,"usgs":false,"family":"Cidu","given":"Rosa","affiliations":[{"id":16820,"text":"University of Cagliari","active":true,"usgs":false}],"preferred":false,"id":841689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biddau, Riccardo","contributorId":290730,"corporation":false,"usgs":false,"family":"Biddau","given":"Riccardo","affiliations":[{"id":16820,"text":"University of Cagliari","active":true,"usgs":false}],"preferred":false,"id":841690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frau, Franco","contributorId":290731,"corporation":false,"usgs":false,"family":"Frau","given":"Franco","affiliations":[{"id":16820,"text":"University of Cagliari","active":true,"usgs":false}],"preferred":false,"id":841691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wanty, Richard 0000-0002-2063-6423","orcid":"https://orcid.org/0000-0002-2063-6423","contributorId":209899,"corporation":false,"usgs":true,"family":"Wanty","given":"Richard","affiliations":[],"preferred":true,"id":841692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Naitza, Stefano","contributorId":290732,"corporation":false,"usgs":false,"family":"Naitza","given":"Stefano","email":"","affiliations":[{"id":16820,"text":"University of Cagliari","active":true,"usgs":false}],"preferred":false,"id":841693,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}