Daily mean discharge values were estimated for May 20–September 30 for 1976–82 and 2006–18 for the U.S. Geological Survey North Fork Fortymile River and Middle Fork Fortymile River streamgage sites in Alaska. A relation between study streamgage discharge and discharge for an index streamgage on the main-stem Fortymile River for a concurrent period in 2019 was developed using the maintenance of variance extension type 3 (MOVE.3) record extension technique. The relation for North Fork Fortymile River discharges incorporated a 1-day-earlier offset to index streamgage discharges. No offset was applied to the index streamgage discharges for use with the Middle Fork Fortymile River discharges. The developed MOVE.3 regressions were used to estimate daily mean discharges at the study streamgage sites during the study season for the longer period of record of the index streamgage. The modified Nash-Sutcliffe efficiency coefficients for the estimated records were 0.38 and 0.63 for the North Fork Fortymile River and Middle Fork Fortymile River streamgages, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205003","collaboration":"Prepared in cooperation with U.S. Bureau of Land Management","usgsCitation":"Curran, J.H., 2020, Extending seasonal discharge records for streamgage sites on the North Fork Fortymile and Middle Fork Fortymile Rivers, Alaska, through water year 2019: U.S. Geological Survey Scientific Investigations Report 2020–5003, 11 p., https://doi.org/10.3133/sir20205003.","productDescription":"Report: iv, 11 p.; 1 Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-114440","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":399626,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109660.htm"},{"id":371893,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5003/sir20205003.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5033"},{"id":371892,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5003/coverthb.jpg"},{"id":371894,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5003/sir20205003_appendix1.csv","text":"Appendix 1","size":"137 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5033 Appendix 1"}],"country":"United States","state":"Alaska","otherGeospatial":"North Fork Fortymile River, Middle Fork Fortymile River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -144.3333,\n 63.1667\n ],\n [\n -141,\n 63.1667\n ],\n [\n -141,\n 64.75\n ],\n [\n -144.3333,\n 64.75\n ],\n [\n -144.3333,\n 63.1667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
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4210 University Drive
Anchorage, Alaska 99508
Unconventional oil and gas (UOG) extractions has produced large economic benefits. However, prudent management of UOG wastes necessitates a thorough understanding of the complex composition, fate, and potential impacts of wastewater releases. UOG production results in large volumes of wastewater. Despite limited re-use of the wastewater, the majority needs to be disposed of, usually by underground injection. The wastewater contains myriad organic, inorganic, and radioactive substances from hydraulic fracturing and production activities or from the (typically shale) formation. Many substances in this wastewater are either proprietary, or are known or potential toxicants. Limited toxicological studies of these mixtures suggest that some of the components are highly toxic. Thus, any releases of untreated wastewater may represent a threat to environmental integrity and human health.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"A handbook of environmental toxicology: Human disorders and ecotoxicology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CAB International Publishers","usgsCitation":"Crosby, L., and Orem, W.H., 2020, Review of studies of composition, toxicology and human health impacts of wastewater from unconventional oil and gas development from shale, chap. 23 of A handbook of environmental toxicology: Human disorders and ecotoxicology, p. 334-350.","productDescription":"17 p.","startPage":"334","endPage":"350","ipdsId":"IP-097385","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":372969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crosby, Lynn M.","contributorId":220626,"corporation":false,"usgs":false,"family":"Crosby","given":"Lynn M.","affiliations":[{"id":40194,"text":"(former USGS)","active":true,"usgs":false}],"preferred":false,"id":775339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":775338,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208347,"text":"70208347 - 2020 - Identification of management thresholds of urban development in support of aquatic biodiversity conservation","interactions":[],"lastModifiedDate":"2020-02-05T16:32:15","indexId":"70208347","displayToPublicDate":"2020-01-31T16:25:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Identification of management thresholds of urban development in support of aquatic biodiversity conservation","docAbstract":"Urbanization degrades stream ecosystems and causes loss of bodiversity. Using benthic macroinvertebrates as a surragate for overall aquatic diversity, we conducted a series of analytical approaches to derive management thresholds of urban development designed to link ecological responses to the primary management goal of protecting aquatic diversity in streams within the Delaware Water Gap National Recreation Area (USA). We were particularly interested in identifying urban thresholds that represent the early phases of biological impact to support cost-effect management and mitigation interventions. We used taxa-specific modeling approaches within a spatially-explicit framework to develop sensitive thresholds that anticipate and demark the onset of taxa loss and provide a foundation for investigating alternative mechanisms driving biological change. We identified an early-warning threshold of 1.5% urban development in the contributing watershed where 15% of the 107 taxa evaluated exhibited significant declines in abundance but prior to any evidence of extirpation, and an extirpation threshold of 6% urban development where nearly 3% of taxa are likely to be lost locally. These thresholds of urban development are substantially lower than response thresholds typically reported based upon traditional modeling approaches that rely on spatially-implicit summaries of land cover and univariate metrics or composite indices. An analysis of ecological and functional trait composition of taxa determined to be sensitive suggests that reduced storage of benthic organic matter caused by flashier hydrographs may be the primary mechanism driving biological changes observed at relatively low levels of urbanization. Although the extent to which stream communities respond to stressor gradients in a non-linear fashion continues to be debated, we show that threshold approaches can be applied in support of aquatic resource management irrespective of whether or not stress-response functions are non-linear.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2020.106124","usgsCitation":"Snyder, C.D., and Young, J.A., 2020, Identification of management thresholds of urban development in support of aquatic biodiversity conservation: Ecological Indicators, v. 112, 106124, 14 p., https://doi.org/10.1016/j.ecolind.2020.106124.","productDescription":"106124, 14 p.","ipdsId":"IP-112218","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457919,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2020.106124","text":"Publisher Index Page"},{"id":437132,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MI9BOO","text":"USGS data release","linkHelpText":"Benthic macroinvertebrates abundance data for the study of urbanization effects in the Delaware Water Gap National Recreation Area, (2006)"},{"id":372098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, Pennsylvania","otherGeospatial":"Delaware Water Gap National Recreation Area","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 40.92804010533237\n ],\n [\n -74.77706909179688,\n 40.92804010533237\n ],\n [\n -74.77706909179688,\n 41.47771800887871\n ],\n [\n -75.157470703125,\n 41.47771800887871\n ],\n [\n -75.157470703125,\n 40.92804010533237\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"112","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":781527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":781528,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208237,"text":"70208237 - 2020 - Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","interactions":[],"lastModifiedDate":"2020-06-04T16:51:39.984534","indexId":"70208237","displayToPublicDate":"2020-01-31T16:07:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1822,"text":"Geostandards and Geoanalytical Research","active":true,"publicationSubtype":{"id":10}},"title":"Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance","docAbstract":"Waters co-produced during petroleum extraction are the largest waste stream from oil and gas development. Reuse or disposal of these waters is difficult due to their high salinities and the sheer volumes generated. Produced waters may also contain valuable mineral commodities. While an understanding of produced water trace element composition is required for evaluating the associated resource and waste potential of these materials, measuring trace elements in brines is challenging due to the dilution requirements of typical methods. Alternatively, inductively coupled plasma-optical emission spectrometry (ICP-OES) has shown promise as being capable of direct measurements of trace elements within produced waters with minimal dilution. Here we evaluate direct ICP-OES trace element quantification in produced waters for 17 trace elements (As, Al, Ba, Be, Cd, Cr, Co, Cu, Hg, Mo, Ni, Pb, Rb, Sb, U, V, and Zn) within 15 produced waters from five U.S. continuous reservoirs. The ICP-OES results are compared against trace element levels determined using inductively coupled plasma-mass spectrometry from the same samples. Our results demonstrate the potential for direct analysis of high salinity waters using ICP-OES with minimal dilution and provide trace element concentrations in waters from several important U.S. petroleum-generating reservoirs where available data is sparse.","language":"English","publisher":"Wiley","doi":"10.1111/GGR.12316","usgsCitation":"Jubb, A., Engle, M., Chenault, J., Blondes, M., Danforth, C.G., Doolan, C., Gallegos, T., Mueller, D., and Shelton, J., 2020, Direct trace element determination in oil and gas produced waters with inductively coupled plasma - Optical emission spectrometry (ICP-OES): Advantages of high salinity tolerance: Geostandards and Geoanalytical Research, v. 44, no. 2, p. 385-397, https://doi.org/10.1111/GGR.12316.","productDescription":"13 p.","startPage":"385","endPage":"397","ipdsId":"IP-111055","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":457922,"rank":0,"type":{"id":40,"text":"Open 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40.74725696280421\n ],\n [\n -81.8701171875,\n 39.33429742980725\n ],\n [\n -80.5517578125,\n 38.20365531807149\n ],\n [\n -78.79394531249999,\n 38.89103282648846\n ],\n [\n -76.37695312499999,\n 42.261049162113856\n ],\n [\n -74.970703125,\n 43.100982876188546\n ],\n [\n -73.6962890625,\n 43.03677585761058\n ],\n [\n -73.6083984375,\n 44.08758502824516\n ],\n [\n -75.849609375,\n 43.644025847699496\n ],\n [\n -79.6728515625,\n 42.261049162113856\n ],\n [\n -82.1337890625,\n 41.31082388091818\n ],\n [\n -82.3974609375,\n 40.74725696280421\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"44","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engle, Mark 0000-0001-5258-7374","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":222085,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chenault, Jessica 0000-0002-5974-0762","orcid":"https://orcid.org/0000-0002-5974-0762","contributorId":222078,"corporation":false,"usgs":true,"family":"Chenault","given":"Jessica","email":"","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blondes, Madalyn 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":222079,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":781119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Danforth, Cloelle G.","contributorId":222080,"corporation":false,"usgs":false,"family":"Danforth","given":"Cloelle","email":"","middleInitial":"G.","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":781219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Doolan, Colin 0000-0002-7595-7566 cdoolan@usgs.gov","orcid":"https://orcid.org/0000-0002-7595-7566","contributorId":222081,"corporation":false,"usgs":true,"family":"Doolan","given":"Colin","email":"cdoolan@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science 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River Suckers associated with cyanobacteria blooms in mesocosms in Upper Klamath Lake, Oregon","docAbstract":"Unsustainably high mortality within the first 2 years of life prevents endangered Lost River Suckers Deltistes luxatus in Upper Klamath Lake, Oregon, from recruiting to spawning populations. Massive blooms of the cyanobacterium Aphanizomenon flos‐aquae and their subsequent death and decay in the lake (bloom‐crashes) are associated with high pH, low percent oxygen saturation, high total ammonia concentrations, and spikes in the cyanotoxin microcystin. Poor water quality within the lake is considered the most likely cause of juvenile sucker mortality, but mechanisms causing the high mortality are not known. We introduced PIT‐tagged age‐1 Lost River suckers into three continuously monitored mesocosms in Upper Klamath Lake to determine the timing of juvenile sucker mortality relative to pH, temperature, and dissolved oxygen. Mortality was inferred from a lack of movement detected on remote PIT tag detection equipment within each mesocosm. Mortality was compared among mesocosms and an indoor tank‐held control group. We fitted time‐varying Cox hazard models to test hypotheses about short‐term and chronic effects of single and co‐occurring water quality parameters on the daily hazard rate. Presumed healthy or moribund fish that were collected pre‐season, mid‐season, or at the end of the study were examined macroscopically and histologically to generate inferences about the causes of mortality. Models did not indicate a plausible association between water quality variables and mortality. Hypoxia preceded periods of higher mortality at two of three sites but did not co‐occur with mortality. Hatchery‐reared Lost River Suckers confined to mesocosms may not represent the behavior of wild fish, and it is unclear whether the same factors affect the mortality of wild age‐0 suckers.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10227","usgsCitation":"Burdick, S.M., Hereford, D.M., Conway, C.M., Banet, N.V., Powers, R., Martin, B.A., and Elliott, D.G., 2020, Mortality of endangered juvenile Lost River Suckers associated with cyanobacteria blooms in mesocosms in Upper Klamath Lake, Oregon: Transactions of the American Fisheries Society, v. 149, no. 3, p. 245-265, https://doi.org/10.1002/tafs.10227.","productDescription":"21 p.","startPage":"245","endPage":"265","ipdsId":"IP-111701","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":377390,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.13226318359375,\n 42.200038266046754\n ],\n [\n -121.74774169921875,\n 42.200038266046754\n ],\n [\n -121.74774169921875,\n 42.60768474453004\n ],\n [\n -122.13226318359375,\n 42.60768474453004\n ],\n [\n -122.13226318359375,\n 42.200038266046754\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"149","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-05-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":795812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hereford, Danielle M 0000-0001-8993-6144","orcid":"https://orcid.org/0000-0001-8993-6144","contributorId":238014,"corporation":false,"usgs":false,"family":"Hereford","given":"Danielle","email":"","middleInitial":"M","affiliations":[{"id":47681,"text":"U. 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Understanding the epidemiology of FP has been hampered by a lack of robust serological assays to monitor exposure to ChHV5. This is due in part to an inability to efficiently culture the virus in vitro for neutralization assays. Here, we expressed two glycoproteins (FUS4 and FUS8) from ChHV5 using baculovirus. These proteins were immobilized on enzyme-linked immunosorbent assay plates in their native form and assayed for reactivity to two types of antibodies, full-length 7S IgY and 5.7S IgY, which has a truncated Fc region. Turtles from Florida were uniformly seropositive to ChHV5 regardless of tumor status. In contrast, in turtles from Hawaii, we detected strong antibody reactivity mainly in tumored animals, with a lower antibody response being seen in nontumored animals, including those from areas where FP is enzootic. Turtles from Hawaii actively shedding ChHV5 were more seropositive than nonshedders. In trying to account for differences in the serological responses to ChHV5 between green turtles from Hawaii and green turtles from Florida, we rejected the cross-reactivity of antibodies to other herpesviruses, differences in viral epitopes, or differences in procedure as likely explanations. Rather, behavioral or other differences between green turtles from Hawaii and green turtles from Florida might have led to the emergence of biologically different viral strains. While the strains from turtles in Florida apparently spread independently of tumors, the transmission of the Hawaiian subtype relies heavily on tumor formation.
","language":"English","publisher":"ASM Journals","doi":"10.1128/JVI.01658-19","usgsCitation":"Work, T.M., Dagenais, J., Willimann, A., Balazs, G., Mansfield, K., and Ackermann, M., 2020, Differences in antibody responses against Chelonid Alphaherpesvirus 5 (ChHV5) suggest differences in virus biology in ChHV5-seropositive green turtles from Hawaii and ChHV5-seropositive green turtles from Florida: Journal of Virology, v. 94, no. 4, e01658-19, 15 p., https://doi.org/10.1128/JVI.01658-19.","productDescription":"e01658-19, 15 p.","ipdsId":"IP-113540","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":457924,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6997749","text":"External Repository"},{"id":418309,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418308,"rank":1,"type":{"id":30,"text":"Data 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\"}}]}","volume":"94","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":875866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dagenais, Julie 0000-0001-5560-9946 jdagenais@usgs.gov","orcid":"https://orcid.org/0000-0001-5560-9946","contributorId":5955,"corporation":false,"usgs":true,"family":"Dagenais","given":"Julie","email":"jdagenais@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":875867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willimann, Anna","contributorId":310753,"corporation":false,"usgs":false,"family":"Willimann","given":"Anna","email":"","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":875868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Balazs, George","contributorId":310754,"corporation":false,"usgs":false,"family":"Balazs","given":"George","affiliations":[{"id":67262,"text":"Golden Honu Services","active":true,"usgs":false}],"preferred":false,"id":875869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mansfield, Kate","contributorId":310755,"corporation":false,"usgs":false,"family":"Mansfield","given":"Kate","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":875870,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ackermann, Mathias","contributorId":310756,"corporation":false,"usgs":false,"family":"Ackermann","given":"Mathias","affiliations":[{"id":27368,"text":"University of Zurich","active":true,"usgs":false}],"preferred":false,"id":875871,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217164,"text":"70217164 - 2020 - Predictive relations between acid-base chemistry and fish assemblages in streams of the Adirondack Mountains","interactions":[],"lastModifiedDate":"2021-01-08T17:30:33.449604","indexId":"70217164","displayToPublicDate":"2020-01-31T11:26:17","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5590,"text":"NYSERDA Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"20-04","title":"Predictive relations between acid-base chemistry and fish assemblages in streams of the Adirondack Mountains","docAbstract":"Surface waters across much of New York State’s Adirondack Mountains were acidified in the late 20th century but began to recover following the 1990 Title IV Amendments to the Clean Air Act. Previous assessments of acidification recovery in the Adirondacks have generally been based on surface water chemistry data and inferred relationships to fish and other aquatic biota. Little data, however, has been available to characterize biological impacts and predict recovery of fish assemblages in streams of the region. Here, we use quantitative fish surveys combined with chemistry data from 48 headwater streams sampled during summer 2014–2016 to develop logistic (probability) models that characterize the status of contemporary fish assemblages and predict how different N and S deposition loads may affect future fish assemblages. Statistical models for inorganic aluminum (Ali) and richness ≥1 species; and for acid neutralizing capacity (ANC) and total density >400 fish/0.1 ha, total biomass >1500 g/0.1 ha, brook trout Salvelinus fontinalis density >0 or >200 fish/0.1 ha, and brook trout biomass >1000 g/0.1 ha were suitable for evaluating community and population responses to changes in acid-base chemistry. Predictions of fish-assemblage responses using several of these models demonstrated that anticipated changes in national (U.S.) secondary standards for atmospheric emissions of NOx and SOx to achieve target N and S deposition loads are likely to alter the acid-base chemistry and the probabilities of observing various levels of brook trout population and fish-community metrics in streams across the region and elsewhere.
The 2016–2017 shallow submarine eruption of Bogoslof volcano produced numerous infrasound signals over 9 months that were recorded on six Alaska Volcano Observatory (AVO) arrays at ranges of 59 to over 800 km from the volcano. The lack of geophysical monitoring near Bogoslof and the repeated production of volcanic clouds to flight levels made monitoring by remote infrasound critical during the eruption; for the first time, AVO relied extensively on automated infrasound detections from regional arrays to dispatch timely notifications of the ongoing activity. Most of the 70 eruptive events were detected on at least one array, but no array detected all of the events mainly because atmospheric conditions were highly variable during the eruption. Acoustic propagation modeling helps explain some of the variation in array detections but also highlights limitations in regional propagation models. To our knowledge, this is the first example of well-recorded infrasound from an explosive eruption occurring in shallow seawater, providing extensive insights into eruption dynamics in this unique environment. The dominance of low-frequency infrasound (0.1–1 Hz) is attributed to eruptions occurring beneath tens of meters of seawater. Higher-frequency infrasound signals were mostly limited to eruptions where the vent was isolated from major interaction with seawater or in several cases where a lava dome grew above sea level.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1355-0","usgsCitation":"Lyons, J.J., Iezzi, A., Fee, D., Schwaiger, H., Wech, A., and Haney, M.M., 2020, Infrasound generated by the 2016-2017 shallow submarine eruption of Bogoslof volcano, Alaska: Bulletin of Volcanology, v. 82, 19, 14 p., https://doi.org/10.1007/s00445-019-1355-0.","productDescription":"19, 14 p.","ipdsId":"IP-112505","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":383363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -178.63769531249997,\n 48.86471476180277\n ],\n [\n -155.0390625,\n 48.86471476180277\n ],\n [\n -155.0390625,\n 61.39671887310411\n ],\n [\n -178.63769531249997,\n 61.39671887310411\n ],\n [\n -178.63769531249997,\n 48.86471476180277\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":810600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":810601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fee, David","contributorId":199660,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[],"preferred":false,"id":810602,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwaiger, Hans 0000-0001-7397-8833","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":214983,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wech, Aaron 0000-0003-4983-1991","orcid":"https://orcid.org/0000-0003-4983-1991","contributorId":202561,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810604,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":810605,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208223,"text":"70208223 - 2020 - Progress in natural capital accounting for ecosystems","interactions":[],"lastModifiedDate":"2020-01-31T10:13:43","indexId":"70208223","displayToPublicDate":"2020-01-31T09:56:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Progress in natural capital accounting for ecosystems","docAbstract":"Reversing the ongoing degradation of the planet's ecosystems requires timely and detailed monitoring of ecosystem change and uses. Yet, the System of National Accounts (SNA), first developed in response to the economic crisis of the 1930s and used by statistical offices worldwide to record economic activity (for example, production, consumption, and asset accumulation), does not make explicit either inputs from the environment to the economy or the cost of environmental degradation (1, 2). Experimental Ecosystem Accounting (EEA), part of the System of Environmental-Economic Accounting (SEEA), has been developed to monitor and report on ecosystem change and use, using the same accounting approach, concepts, and classifications as the SNA (3). The EEA is part of the statistical community's response to move SNA measurement “beyond gross domestic product (GDP).” With the first generation of ecosystem accounts now published in 24 countries, and with a push to finalize a United Nations (UN) statistical standard for ecosystem accounting by 2021, we highlight key advances, challenges, and opportunities.
","language":"English","publisher":"AAAS","doi":"10.1126/science.aaz8901","usgsCitation":"Hein, L., Bagstad, K.J., Obst, C., Edens, B., Schenau, S., Castillo, G., Soulard, F., Brown, C., Driver, A., Bordt, M., Steurer, A., Harris, R., and Capparros, A., 2020, Progress in natural capital accounting for ecosystems: Science, v. 6477, no. 367, p. 514-515, https://doi.org/10.1126/science.aaz8901.","productDescription":"2 p.","startPage":"514","endPage":"515","ipdsId":"IP-108491","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":371803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6477","issue":"367","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hein, Lars","contributorId":176849,"corporation":false,"usgs":false,"family":"Hein","given":"Lars","email":"","affiliations":[],"preferred":false,"id":781013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":781012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obst, Carl","contributorId":176851,"corporation":false,"usgs":false,"family":"Obst","given":"Carl","email":"","affiliations":[],"preferred":false,"id":781014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edens, Bram","contributorId":176850,"corporation":false,"usgs":false,"family":"Edens","given":"Bram","email":"","affiliations":[],"preferred":false,"id":781015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenau, Sjoerd","contributorId":222041,"corporation":false,"usgs":false,"family":"Schenau","given":"Sjoerd","email":"","affiliations":[{"id":27734,"text":"Statistics Netherlands","active":true,"usgs":false}],"preferred":false,"id":781016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Castillo, Gem","contributorId":222042,"corporation":false,"usgs":false,"family":"Castillo","given":"Gem","email":"","affiliations":[{"id":40481,"text":"Resources, Environment and Economics Center for Studies, Philippines","active":true,"usgs":false}],"preferred":false,"id":781017,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Soulard, Francois","contributorId":211874,"corporation":false,"usgs":false,"family":"Soulard","given":"Francois","email":"","affiliations":[{"id":38339,"text":"Statistics Canada","active":true,"usgs":false}],"preferred":false,"id":781018,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Claire","contributorId":222043,"corporation":false,"usgs":false,"family":"Brown","given":"Claire","email":"","affiliations":[{"id":40482,"text":"UNEP-World Conservation Monitoring Centre","active":true,"usgs":false}],"preferred":false,"id":781019,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Driver, Amanda","contributorId":222044,"corporation":false,"usgs":false,"family":"Driver","given":"Amanda","email":"","affiliations":[{"id":40483,"text":"South African National Biodiversity Institute","active":true,"usgs":false}],"preferred":false,"id":781020,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bordt, Michael 0000-0001-5634-2294","orcid":"https://orcid.org/0000-0001-5634-2294","contributorId":222045,"corporation":false,"usgs":false,"family":"Bordt","given":"Michael","email":"","affiliations":[{"id":40484,"text":"UN Economic and Social Commission for Asia and the Pacific","active":true,"usgs":false}],"preferred":false,"id":781021,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Steurer, Anton","contributorId":222046,"corporation":false,"usgs":false,"family":"Steurer","given":"Anton","email":"","affiliations":[{"id":40485,"text":"Statistical Office of the European Union","active":true,"usgs":false}],"preferred":false,"id":781022,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Harris, Rocky","contributorId":222065,"corporation":false,"usgs":false,"family":"Harris","given":"Rocky","email":"","affiliations":[],"preferred":false,"id":781094,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Capparros, Alejandro","contributorId":222047,"corporation":false,"usgs":false,"family":"Capparros","given":"Alejandro","email":"","affiliations":[{"id":34335,"text":"Spanish National Research Council","active":true,"usgs":false}],"preferred":false,"id":781023,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70208466,"text":"70208466 - 2020 - Expert bioblitzes facilitate non-native fish tracking and interagency partnerships","interactions":[],"lastModifiedDate":"2020-03-11T15:32:23","indexId":"70208466","displayToPublicDate":"2020-01-31T09:40:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Expert bioblitzes facilitate non-native fish tracking and interagency partnerships","docAbstract":"Documenting the distribution and composition of non-native species populations can be challenging, especially when species cross jurisdictional boundaries that require interagency coordination. Herein I report the development of three tools that have been used in Florida over the past seven years to assist with tracking of non-native fishes: 1) an overarching organization to increase coordination and communication amongst stakeholders (Florida Non-Native Fish Action Alliance); 2) regularly-scheduled expert bioblitzes (Fish Slams); and 3) symposia (Fish Chats). Ten Fish Slams were held since 2012, which have included nearly 100 individuals from 20 organizations. Participants have sampled nearly 200 unique sites, capturing 36 non-native fish taxa. These activities have generated over 600 records for the U.S. Geological Survey’s Nonindigenous Aquatic Species database. Many specimens collected during Fish Slams are deposited into natural history museums or used by researchers. Informal interactions amongst colleagues working together in the field, at check-in meetings at the end of the day, and during more structured Fish Chat symposia allow members of various organizations to become acquainted, build trust, and share information and technology, which may then lead to professional collaborations. While this program is focused on non-native fish species in south Florida, I also discuss how the expert bioblitz may be adapted to suit other taxonomic groups and a variety of conservation needs.","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2020.11.1.10","usgsCitation":"Schofield, P.J., 2020, Expert bioblitzes facilitate non-native fish tracking and interagency partnerships: Management of Biological Invasions, v. 11, no. 1, p. 139-154, https://doi.org/10.3391/mbi.2020.11.1.10.","productDescription":"16 p.","startPage":"139","endPage":"154","ipdsId":"IP-109058","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457927,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.3391/mbi.2020.11.1.10","text":"Publisher Index Page"},{"id":372225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.7822265625,\n 25.08062377244484\n ],\n [\n -80.013427734375,\n 25.08062377244484\n ],\n [\n -80.013427734375,\n 26.59343927024179\n ],\n [\n -81.7822265625,\n 26.59343927024179\n ],\n [\n -81.7822265625,\n 25.08062377244484\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schofield, Pamela J. 0000-0002-8752-2797 pschofield@usgs.gov","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":168659,"corporation":false,"usgs":true,"family":"Schofield","given":"Pamela","email":"pschofield@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":782015,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70208591,"text":"70208591 - 2020 - Applications of correlative light and electron microscopy (CLEM) to organic matter in the North American shale petroleum systems","interactions":[],"lastModifiedDate":"2020-02-20T09:12:46","indexId":"70208591","displayToPublicDate":"2020-01-31T09:12:37","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Applications of correlative light and electron microscopy (CLEM) to organic matter in the North American shale petroleum systems","docAbstract":"Scanning electron microscopy (SEM) has revolutionized our understanding of shale petroleum systems through microstructural characterization of dispersed organic matter (OM). However, due to the low atomic weight of carbon, all OM appears black in SEM (BSE image) regardless of differences in thermal maturity or OM type (kerogen types or solid bitumen). Traditional petrographic identification of OM uses optical microscopy, where reflectance (%Ro), form, relief and fluorescence can be used to discern OM types and thermal maturation stage. Unfortunately, most SEM studies of shale OM do not employ correlative optical techniques, leading to misidentifications or to the conclusion that all OM (i.e., kerogen and solid bitumen) is the same. To improve the accuracy of SEM identifications of dispersed OM in shale, this study used correlative light and electron microscopy (CLEM) to create optical and SEM images of OM in the same fields of view (500x magnification) under white light, blue light, secondary electron, and backscatter electron conditions. Samples (n=8) of varying thermal maturities and typical of the North American shale petroleum systems were used, including the Green River Mahogany Zone, Bakken Formation, Ohio Shale, Eagle Ford Formation, Barnett Formation, Haynesville Formation and Woodford Shale. The CLEM image sets demonstrate the importance of correlative microscopy by showing how easily OM can be misidentified when viewed by SEM alone. Without CLEM techniques, petrographic data from SEM such as observations of organic nano-porosity may be misinterpreted, resulting in false or ambiguous results and impairing an improved understanding of organic diagenesis and catagenesis.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Mudstone diagenesis: Research perspectives for shale hydrocarbon reservoirs, seals, and source rocks","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"AAPG","isbn":"9180891814252","usgsCitation":"Valentine, B.J., and Hackley, P.C., 2020, Applications of correlative light and electron microscopy (CLEM) to organic matter in the North American shale petroleum systems, chap. 1 of Mudstone diagenesis: Research perspectives for shale hydrocarbon reservoirs, seals, and source rocks, p. 1-18.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-093317","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":372446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":372421,"type":{"id":15,"text":"Index Page"},"url":"https://store.aapg.org/detail.aspx?id=1310"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":782638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":782677,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70226997,"text":"70226997 - 2020 - Ecosystem-specific growth responses to climate pattern by a temperate freshwater fish","interactions":[],"lastModifiedDate":"2021-12-27T14:45:19.675432","indexId":"70226997","displayToPublicDate":"2020-01-31T08:42:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem-specific growth responses to climate pattern by a temperate freshwater fish","docAbstract":"Somatic growth patterns among animal populations are maintained through complex processes that vary among ecosystems. Changes in growth patterns may be concomitant with changes in climate; however, understanding how growth will manifest among ecosystems is limited. Information embedded within fish hard-parts (i.e., otoliths, spines, vertebrae) can account for variation in growth patterns resulting from changing climate conditions. Channel catfish Ictalurus punctatus is a freshwater fish species widely distributed across North America with limited information regarding climate influences on growth and differences in climate-growth relations among ecological systems. We assessed growth (total length) response to changing climate conditions for channel catfish among three waterbody types—pit lakes, irrigation and power-generation reservoirs, and flood-control reservoirs in Nebraska, USA. We used linear mixed-effect models and an information theoretic approach to assess the relative strengths among competing hypotheses. The most supported linear mixed-effect model of channel catfish growth was a function of fish age and an interaction between waterbody type and growing-degree-day (GDD). A positive trend existed in GDD from 1990 through 2008 whereby the predicted increase in GDD among waterbody types ranged from 182 GDD to 189 GDD. The predicted change in channel catfish growth resulting from increased GDD ranged from 1% to 39% among waterbody types. Channel catfish population rate functions, thus, may not respond similarly to climate conditions across ecosystem types. Changes in climate variables may contribute to system-specific responses in population dynamics for channel catfish as well as other similar freshwater species. The establishment of relations between climate and growth variables for a freshwater generalist with a plastic diet and broad temperature tolerance serves as an indication of the breadth of responses possible for freshwater fishes under global changes in climate conditions.
We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL—the AM4 atmosphere model, MOM6 ocean code, LM4 land model, and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0° (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1° to 0.25°. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM4 models but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM4 models.
A prototype system to explore Linked Data that semantically integrates geospatial data in various formats from different publication sources with data from The National Map of the U.S. Geological Survey is presented. The focus is on accessing advanced feature descriptions for data from The National Map with data coreferenced from other sources. The prototype uses Geoserver to access The National Map data, which are converted to Resource Description Framework triples using Karma and stored in the Marmotta triplestore. Marmotta uses a Postgres relational database as a backend for the project and queries to the Marmotta triplestore are converted to structured query language and executed by Postgres. Triples retrieved are linked with same_as relationships to external data sources. The links to these sources provide additional attributes and relationships of the data from The National Map. Visualization of the results is provided using Leaflet and workflows for all parts of the system are defined. A use case for the system is provided to access structures and names information from The National Map for the Washington, D.C., area and link these to Geonames data, with visualization of the graphical and tabular results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195148","usgsCitation":"Wagner, M., Varanka, D.E., and Usery, E.L., 2020, A system design for implementing advanced feature descriptions for a map knowledge base: U.S. Geological Survey Scientific Investigations Report 2019–5148, 25 p., https://doi.org/10.3133/sir20195148. ","productDescription":"viii, 25 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-111001","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":371735,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5148/coverthb.jpg"},{"id":371736,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5148/sir20195148.pdf","text":"Report","size":"3.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5148"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Estimating the number of breeding pairs in a mixed-species waterbird colony is difficult because colonial waterbirds are vulnerable to human intrusion and their colonies are often in remote areas with limited access. We investigated methods to estimate the number of nests of waterbirds at a large, mixed-species colony at Chase Lake National Wildlife Refuge in south-central North Dakota. The primary goals of this study were to evaluate survey methods for shrub- and ground-nesting colonial waterbirds at Chase Lake National Wildlife Refuge and to develop protocols for estimating abundance of the different species. The specific objectives were (1) to assess visible-nest counts for ciconiiform species from the perimeter of nesting areas (hereafter, perimeter counts) and observational surveys from fixed points outside the colony to count flights of adult ciconiiforms in and out of the colony (hereafter, flightline surveys) as alternatives to within-colony counts of ciconiiform nests, and (2) to assess semiautomated, pixel-based image-analysis techniques to estimate abundance of American White Pelicans (Pelecanus erythrorhynchos) as an alternative to traditional manual counts from aerial photographs.
For shrub-nesting ciconiiform species, observers counted 2,259 and 1,759 active ciconiiform nests in 2012 and 2013, respectively, during within-colony counts of ciconiiform nests. Results from within-colony counts of ciconiiform nests indicated a positive relation between the number of nests and the area of the shrub subcolony for the three most common ciconiiform species and all ciconiiform species combined. The perimeter nest counts of ciconiiform nests at Chase Lake represented only 18.8 percent of the total active ciconiiform nests counted in 11 subcolonies in 2012, which was well below the recommended target of 50 percent. Although we found a positive relationship between the number of nests counted during perimeter counts and the number of nests counted during within-colony counts for the three most common ciconiiform species and all ciconiiform species combined, perimeter counts at Chase Lake were hampered by disturbance to nesting birds. Thus, we discontinued the perimeter counts before they were completed. We did not develop predictive models from these perimeter counts in 2012 because these models could be misleading due to inconsistent application of the survey methods, which likely would have provided inaccurate perimeter counts. The extent of this issue is unknown. Flightline surveys at Chase Lake documented patterns of ciconiiform activity that were unknown for this region. For the common ciconiiform species, the number of flights to and from the South Island at Chase Lake were greatest in the morning (7:00−12:00 central daylight time [CDT]) and least in the afternoon (12:00−17:00), and least early in the breeding season (May 29–June 20, 2013) and greatest later in the breeding season (June 24–August 1, 2013). Flightline surveys are an index but lacked comparability with within-colony nest counts because the two methods provide measures of different things (that is, adult activity away from the colony as compared to the number of nests within the colony). The overall proportions of flights generally reflected the proportions of the within-colony nest counts for the four most common species: Black-crowned Night-Heron (Nycticorax nycticorax), Cattle Egret (Bubulcus ibis), Great Egret (Ardea alba), and Snowy Egret (Egretta thula). Flightline surveys at Chase Lake indicated apparent variation related to the time of day and season, as well as a variation in detection of inbound and outbound adult ciconiiforms. For ciconiiforms at Chase Lake, the most appropriate combination of survey approaches will depend on the need for annual estimates of nest abundance of ciconiiform species, balanced with the financial, personnel, and logistical constraints associated with the survey methods.
For ground-nesting American White Pelicans, the results from this study indicated that digital-image processing using remote-sensing software provides an accurate estimate of the number of American White Pelican nests. Estimates of the number of pelican nests from digital-image processing, using two commercially available remote-sensing software packages, produced nest estimates that were comparable to those of traditional manual counts from aerial photographs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201008","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Igl, L.D., Bartos, A.J., Woodward, R.O., Scherr, P., and Sovada, M.A, 2020, Evaluation of survey methods for colonial waterbirds at Chase Lake National Wildlife Refuge, North Dakota: U.S. Geological Survey Open-File Report 2020–1008, 44 p., https://doi.org/10.3133/ofr20201008. ","productDescription":"Report: viii, 44 p.; Data Release","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-112516","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":371775,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1008/ofr20201008.pdf","text":"Report","size":"7.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1008"},{"id":371774,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1008/coverthb.jpg"},{"id":371776,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90NK31K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Evaluation of Survey Methods for Colonial Waterbirds at Chase Lake National Wildlife Refuge, North Dakota, data release"}],"country":"United States","state":"North Dakota ","otherGeospatial":"Chase Lake National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.481105,46.983794 ], [ -99.481105,47.030693 ], [ -99.417191,47.030693 ], [ -99.417191,46.983794 ], [ -99.481105,46.983794 ] ] ] } } ] }","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401
Since the 1990s, increased chloride concentrations of water pumped from wells (much of which is used for drinking water) and the effects of withdrawals on groundwater-dependent ecosystems have led to concerns over groundwater availability on the island of Molokaʻi, Hawaiʻi. An improved understanding of the hydrologic effects of proposed groundwater withdrawals is needed to ensure effective management of the groundwater resources of Molokaʻi, plan for possible growth, and accommodate cultural, social, and economic concerns. To address the information needs of managers and community stakeholders on Molokaʻi, the U.S. Geological Survey developed a numerical groundwater model capable of simulating salinity change and reduction in groundwater discharge in coastal areas of central and southern Molokaʻi. Estimates of groundwater recharge needed as input to the numerical groundwater model were made using a daily water budget for each decade during 1940−2012 (the period 2000−12 spanned 13 years) and the most current available data, including the distributions of monthly rainfall and potential evapotranspiration. Total island recharge during the decadal periods ranged from a low of about 189 Mgal/d during the 1970s to a high of 278 Mgal/d during the 1960s. These recharge estimates were used to develop an island-wide numerical groundwater model with simplifying assumptions (sharp interface between freshwater and saltwater; two-dimensional flow). The island-wide model provided estimates of groundwater inflows to the main area of interest simulated with a three-dimensional numerical groundwater model. Simulated withdrawal scenarios were selected in consultation with water managers and stakeholders and consisted of: (1) a baseline scenario using average recharge (1978−2007 rainfall and 2010 land cover) and average 2016−17 withdrawals; (2) a scenario using average recharge and withdrawals from existing wells at pending (as of January 2019) water-use permit rates; (3) six scenarios using average recharge and selected withdrawals from existing and proposed wells; and (4) a scenario using reduced recharge and selected withdrawals from existing and proposed wells. Results of the simulated withdrawal scenarios indicate that wells may be capable of producing groundwater with chloride concentrations below 250 mg/L at withdrawal rates exceeding average 2016−17 rates. However, the quality of water withdrawn from production wells is dependent on the rate and distribution of the withdrawals. For all nonbaseline scenarios, simulated groundwater discharge to the nearshore environment is reduced relative to the baseline scenario. Areas of discharge reduction may correspond to areas used for cultural or subsistence purposes. The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the hydrologic effects of additional groundwater withdrawals in central Molokaʻi. The model has several limitations, including its nonuniqueness and inability to account for local-scale heterogeneities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195150","collaboration":"Prepared in cooperation with the State of Hawai‘i Department of Hawaiian Home Lands, State of Hawai‘i Office of Hawaiian Affairs, and County of Maui Department of Water Supply","usgsCitation":"Oki, D.S., Engott, J.A., and Rotzoll, K., 2020, Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2019–5150, 95 p., https://doi.org/10.3133/sir20195150.","productDescription":"Report: ix, 95 p.; Data Release","numberOfPages":"95","onlineOnly":"Y","ipdsId":"IP-032683","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":399622,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109628.htm"},{"id":371721,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRQASS","linkHelpText":"Central Molokaʻi, Hawaiʻi, SUTRA model"},{"id":371719,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5150/coverthb.jpg"},{"id":371720,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5150/sir20195150.pdf","text":"Report","size":"40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5150"}],"country":"United States","state":"Hawaii","otherGeospatial":"Moloka‘i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.77352905273438,\n 21.179289725795993\n ],\n [\n -156.8572998046875,\n 21.163922551671376\n ],\n [\n -156.92184448242188,\n 21.167764494849468\n ],\n [\n -156.97265625,\n 21.211299542246586\n ],\n [\n -156.99737548828125,\n 21.189533621502626\n ],\n [\n -157.1429443359375,\n 21.199776807250093\n ],\n [\n -157.21298217773435,\n 21.220261047755002\n ],\n [\n -157.25830078125,\n 21.218980865996457\n ],\n [\n -157.25555419921875,\n 21.17672864097083\n ],\n [\n -157.2967529296875,\n 21.14599216495789\n ],\n [\n -157.30499267578125,\n 21.097313035028538\n ],\n [\n -157.18826293945312,\n 21.090906697412837\n ],\n [\n -157.08801269531247,\n 21.103719096296263\n ],\n [\n -157.03582763671875,\n 21.090906697412837\n ],\n [\n -156.90811157226562,\n 21.051181240269393\n ],\n [\n -156.84906005859375,\n 21.047336278183312\n ],\n [\n -156.77215576171875,\n 21.08450008351735\n ],\n [\n -156.70074462890625,\n 21.15879980561845\n ],\n [\n -156.77352905273438,\n 21.179289725795993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818