We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) in cooperation with the U.S. Army Corps of Engineers along Bull Creek, Haskell Creek, and the Los Angeles River (Sepulveda Dam project area) in Los Angeles County, California, in 2018. Four vireo surveys were conducted between April 27 and July 18, 2018, and three flycatcher surveys were conducted between May 24 and July 18, 2018. We found 14 territorial male vireos, 7 of which were confirmed as paired. Sixty-four percent of vireos were detected along the Los Angeles River, 21 percent along Haskell Creek, and 14 percent along Bull Creek. Eighty-six percent of vireos were detected in habitat characterized as mixed willow, and all vireos were detected in habitat with greater than 50 percent native plant cover. No flycatchers were observed in the survey area in 2018.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1105","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Pottinger, R.E., and Kus, B.E., 2019, Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Sepulveda Dam Basin, Los Angeles County, California—2018 data summary: U.S. Geological Survey Data Series 1105, 10 p., https://doi.org/10.3133/ds1105. ","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-103359","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":362053,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1105/coverthb.jpg"},{"id":362054,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1105/ds1105.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1105"}],"country":"United States","state":"California","county":"Los Angles County","otherGeospatial":"Sepulveda Dam Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.49387884140015,\n 34.16423284168825\n ],\n [\n -118.47091913223267,\n 34.16423284168825\n ],\n [\n -118.47091913223267,\n 34.1809029051214\n ],\n [\n -118.49387884140015,\n 34.1809029051214\n ],\n [\n -118.49387884140015,\n 34.16423284168825\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Consistency in stratigraphic nomenclature enables communication among scientists both regionally and globally, thus requiring the North American Stratigraphic Code, as presented by the North American Commission on Stratigraphic Nomenclature, to follow international convention. The ratification of three subseries of the Holocene by the InternationalUnion of Geological Sciences (IUGS) in June 2018 warrants the integration of subseries among formal chronostratigraphic ranks in the Code. The purpose ofmaking subseries a formal rank is that it aligns the Code with the International StratigraphicGuide, and establishes the option of using the prefixes super- and sub- for other chronostratigraphic and geochronologic ranks. This is in accordance with the guiding principle of the Code to make it as consistent as possible with international usage and to foster innovations to meet the expanding and changing needs of earth scientists.
","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Aubry, M., Fluegeman, R.H., Edwards, L.E., Pratt, B.R., and Brett, C.E., 2019, North American Commission on Stratigraphic Nomenclature Note 69 – Application for addition of subseries/subepoch to the North American Stratigraphic Code: Stratigraphy, v. 15, no. 4, p. 261-263.","productDescription":"3 p.","startPage":"261","endPage":"263","ipdsId":"IP-104235","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":362045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":362023,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/stratigraphy/issue-345/article-2113"}],"volume":"15","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aubry, Marie-Pierre","contributorId":174332,"corporation":false,"usgs":false,"family":"Aubry","given":"Marie-Pierre","email":"","affiliations":[{"id":27421,"text":"Department of Earth and Planetary Sciences Rutgers University 610 Taylor Road Piscataway NJ 08854-8066, USA","active":true,"usgs":false}],"preferred":false,"id":759216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fluegeman, Richard H.","contributorId":139942,"corporation":false,"usgs":false,"family":"Fluegeman","given":"Richard","email":"","middleInitial":"H.","affiliations":[{"id":13322,"text":"Ball State University","active":true,"usgs":false}],"preferred":false,"id":759217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":759215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Brian R.","contributorId":214140,"corporation":false,"usgs":false,"family":"Pratt","given":"Brian","email":"","middleInitial":"R.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":759218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brett, Carlton E.","contributorId":214141,"corporation":false,"usgs":false,"family":"Brett","given":"Carlton","email":"","middleInitial":"E.","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":759219,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202590,"text":"70202590 - 2019 - Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA","interactions":[],"lastModifiedDate":"2019-03-13T15:20:06","indexId":"70202590","displayToPublicDate":"2019-03-13T15:20:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA","docAbstract":"The enrichment factor (EF) is a widely used metric for determining how much the presence of an element in a sampling media has increased relative to average natural abundance because of human activity. Calculation of an EF requires the selection of both a background composition and a reference element, choices that can strongly influence the result of the calculation. Here, it is shown how carefully applied, classical principal component analysis (PCA) examined via biplots can guide the selections of background compositions and reference elements. Elemental data were treated using the centered log ratio (CLR) transformation, and multiple subsets of major and trace elements were examined to gain different perspectives. The methodology was applied to a dataset of elemental soil concentrations from around breccia pipe uranium mines in Arizona, U.S.A., with most samples collected via incremental sampling methodology. Storage of ore at the surface creates the potential for wind dispersal of ore-derived material. Uranium was found to be the best individual tracer of dispersal of ore-derived material to nearby soils, with EF values up to 75. Sulfur, As, Mo, and Cu were also enriched but to lesser degrees. The results demonstrate several practical benefits of a PCA in these situations: (1) the ability to identify one or more elements best suited to distinguish a specific source of enrichment from background composition; (2) understanding how background compositions vary within and between sites; (3) identification of samples containing enriched or anthropogenic materials based upon their integrated, multi-element composition. Calculating the most representative EF values is useful for numerical assessment of enrichment, whether anthropogenic or natural. As shown here, however, the PCA and biplot method provide a visual approach that integrates information from all elements for a given subset of data in a manner that yields geochemical insights beyond the power of the EF.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2019.01.122","usgsCitation":"Bern, C.R., Walton-Day, K., and Naftz, D.L., 2019, Improved enrichment factor calculations through principal component analysis: Examples from soils near breccia pipe uranium mines, Arizona, USA: Environmental Pollution, v. 248, p. 90-100, https://doi.org/10.1016/j.envpol.2019.01.122.","productDescription":"11 p.","startPage":"90","endPage":"100","ipdsId":"IP-102119","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":467818,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2019.01.122","text":"Publisher Index Page"},{"id":437543,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KTLXL8","text":"USGS data release","linkHelpText":"Surface Materials Data from Breccia-Pipe Uranium Mine and Reference Sites, Arizona, USA"},{"id":362042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.04907226562499,\n 35.5\n ],\n [\n -111,\n 35.5\n ],\n [\n -111,\n 37\n ],\n [\n -114.04907226562499,\n 37\n ],\n [\n -114.04907226562499,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"248","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bern, Carleton R. 0000-0002-8980-1781 cbern@usgs.gov","orcid":"https://orcid.org/0000-0002-8980-1781","contributorId":201152,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton","email":"cbern@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759222,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202253,"text":"ofr20191014 - 2019 - Assessment of skin and liver neoplasms in white sucker (Catostomus commersonii) collected in the Sheboygan River Area of Concern, Wisconsin, in 2017","interactions":[],"lastModifiedDate":"2024-03-04T19:11:14.877436","indexId":"ofr20191014","displayToPublicDate":"2019-03-13T14:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1014","displayTitle":"Assessment of Skin and Liver Neoplasms in White Sucker (Catostomus commersonii) Collected at the Sheboygan River Area of Concern, Wisconsin, in 2017","title":"Assessment of skin and liver neoplasms in white sucker (Catostomus commersonii) collected in the Sheboygan River Area of Concern, Wisconsin, in 2017","docAbstract":"Two hundred adult white sucker (Catostomus commersonii), age 3 years and older, were collected from the lower Sheboygan River Area of Concern in 2017, during the spring spawning run. Fish were euthanized, weighed, and measured, and any visible abnormalities were documented. Pieces of raised skin lesions as well as five to eight pieces of liver were removed and preserved for histopathological analyses. Skin and liver neoplasm prevalence was determined for assessment of the Fish Tumors or Other Deformities Beneficial Use Impairment. Although 45.5 percent of the suckers had raised skin lesions, the prevalence of skin neoplasms, either papilloma or squamous cell carcinoma, was 29.5 percent. This observation was similar to the prevalence (32.6 percent) of skin neoplasms in 2012; however, the percentage of squamous cell carcinoma was higher in 2017 (9.5 percent) than in 2012 (2.1 percent). The prevalence of liver neoplasms in 2017 (8.5 percent) was similar to that in 2012 (8.3 percent).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191014","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources","usgsCitation":"Blazer, V.S., Walsh, H.L., Braham, R.P., and Mazik, P.M., 2019, Assessment of skin and liver neoplasms in white sucker (Catostomus commersonii) collected in the Sheboygan River Area of Concern, Wisconsin, in 2017: U.S. Geological Survey Open-File Report 2019–1014, 18 p., https://doi.org/10.3133/ofr20191014.","productDescription":"vi, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103639","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":361922,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1014/ofr20191014.pdf","text":"Report","size":"4.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1014"},{"id":361921,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1014/coverthb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Lower Sheboygan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.82230377197266,\n 43.71801614233635\n ],\n [\n -87.69132614135742,\n 43.71801614233635\n ],\n [\n -87.69132614135742,\n 43.7596885685863\n ],\n [\n -87.82230377197266,\n 43.7596885685863\n ],\n [\n -87.82230377197266,\n 43.71801614233635\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The putative respiratory selenite [Se(IV)] reductase (Srr) from Bacillus selenitireducens MLS10 has been identified through a polyphasic approach involving genomics, proteomics, and enzymology. Nondenaturing gel assays were used to identify Srr in cell fractions, and the active band was shown to contain a single protein of 80 kDa. The protein was identified through liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a homolog of the catalytic subunit of polysulfide reductase (PsrA). It was found to be encoded as part of an operon that contains six genes that we designated srrE, srrA, srrB, srrC, srrD, and srrF. SrrA is the catalytic subunit (80 kDa), with a twin-arginine translocation (TAT) leader sequence indicative of a periplasmic protein and one putative 4Fe-4S binding site. SrrB is a small subunit (17 kDa) with four putative 4Fe-4S binding sites, SrrC (43 kDa) is an anchoring subunit, and SrrD (24 kDa) is a chaperon protein. Both SrrE (38 kDa) and SrrF (45 kDa) were annotated as rhodanese domain-containing proteins. Phylogenetic analysis revealed that SrrA belonged to the PsrA/PhsA clade but that it did not define a distinct subgroup, based on the putative homologs that were subsequently identified from other known selenite-respiring bacteria (e.g., Desulfurispirillum indicum and Pyrobaculum aerophilum). The enzyme appeared to be specific for Se(IV), showing no activity with selenate, arsenate, or thiosulfate, with a Km of 145 ± 53 μM, a Vmax of 23 ± 2.5 μM min−1, and a kcat of 23 ± 2.68 s−1. These results further our understanding of the mechanisms of selenium biotransformation and its biogeochemical cycle.
","language":"English","publisher":"American Chemical Society","doi":"10.1128/JB.00614-18","usgsCitation":"Wells, M.L., McGarry, J., Gaye, M.M., Basu, P., Oremland, R.S., and Stolz, J.F., 2019, Respiratory selenite reductase from Bacillus selenitireducens strain MLS10: Journal of Bacteriology, v. 201, no. 7, e00614-18, 13 p., https://doi.org/10.1128/JB.00614-18.","productDescription":"e00614-18, 13 p.","ipdsId":"IP-102359","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467819,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1128/jb.00614-18","text":"External Repository"},{"id":379726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"201","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Michael L.","contributorId":194318,"corporation":false,"usgs":false,"family":"Wells","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":802929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGarry, Jennifer","contributorId":243983,"corporation":false,"usgs":false,"family":"McGarry","given":"Jennifer","email":"","affiliations":[{"id":48783,"text":"Purdue","active":true,"usgs":false}],"preferred":false,"id":802930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaye, Maissa M","contributorId":243984,"corporation":false,"usgs":false,"family":"Gaye","given":"Maissa","email":"","middleInitial":"M","affiliations":[{"id":48783,"text":"Purdue","active":true,"usgs":false}],"preferred":false,"id":802931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Basu, Partha","contributorId":189834,"corporation":false,"usgs":false,"family":"Basu","given":"Partha","email":"","affiliations":[],"preferred":false,"id":802932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":802933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stolz, John F.","contributorId":179305,"corporation":false,"usgs":false,"family":"Stolz","given":"John","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":802934,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70203101,"text":"70203101 - 2019 - Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland","interactions":[],"lastModifiedDate":"2019-04-22T11:18:36","indexId":"70203101","displayToPublicDate":"2019-03-13T11:18:17","publicationYear":"2019","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":"Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland","docAbstract":"With warmer springs, herbivores migrating to Arctic breeding grounds may experience phenological mismatches between their energy demands and the availability of high quality forage. However, the timing of high quality forage relative to the timing of grazing is often unknown. In coastal western Alaska, approximately one million migratory geese arrive each spring to breed where foliar %N and C:N ratios are linked to gosling survival and population growth. We conducted a three-year experiment where we manipulated the start of the growing season using warming chambers and grazing times using captive Pacific black brant (Branta bernicla nigricans) to examine how the timing of these events influences the quality of an important forage species. Our results suggest that grazing timing plays a much greater role than an advanced growing season in determining forage quality. Both top models included grazing timing, and suggested that compared to typical grazing timing, early grazing significantly reduced foliar %C by 6% and C:N ratios by 16%, while late goose grazing significantly reduced foliar %N by 15% and increased foliar C:N ratios by 21%. While the second-ranking top model included the effect of season, the advanced growing season only reduced %N by 4%, increased %C by <1%, and increased C:N ratios by 5% compared to an ambient growing season. In summary, in years where geese arrive early, they will consume higher quality forage when they arrive and throughout the season, while in years that geese arrive late they will consume lower quality forage when they arrive and for the remainder of the season. When the growing season starts has only a minor influence on this pattern. Our findings suggest that cues determining migration and arrival times to breeding areas are important factors influencing forage quality for geese in western Alaska.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0213037","usgsCitation":"Beard, K.H., Choi, R.T., Leffer, A.J., Carlson, L., Kelsey, K.C., Schmutz, J.A., and Welker, J., 2019, Migratory goose arrival time plays a larger role in influencing forage quality than advancing springs in an Arctic coastal wetland: PLoS ONE, v. 14, no. 3, 21 p., https://doi.org/10.1371/journal.pone.0213037.","productDescription":"21 p.","ipdsId":"IP-103582","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":467820,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0213037","text":"Publisher Index Page"},{"id":363103,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.4705810546875,\n 60.66510605284197\n ],\n [\n -165.25634765625,\n 59.78128682109904\n ],\n [\n -162.916259765625,\n 59.678835236960765\n ],\n [\n -162.916259765625,\n 61.65598732543086\n ],\n [\n -166.34948730468747,\n 61.65598732543086\n ],\n [\n -165.4705810546875,\n 60.66510605284197\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Beard, Karen H.","contributorId":205934,"corporation":false,"usgs":false,"family":"Beard","given":"Karen","email":"","middleInitial":"H.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":761171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Choi, Ryan T.","contributorId":205936,"corporation":false,"usgs":false,"family":"Choi","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":761172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leffer, A. Joshua","contributorId":214925,"corporation":false,"usgs":false,"family":"Leffer","given":"A.","email":"","middleInitial":"Joshua","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":761174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Lindsay","contributorId":214924,"corporation":false,"usgs":false,"family":"Carlson","given":"Lindsay","email":"","affiliations":[{"id":39139,"text":"Utah State University and the Ecology Center","active":true,"usgs":false}],"preferred":false,"id":761173,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelsey, Katharine C.","contributorId":195397,"corporation":false,"usgs":false,"family":"Kelsey","given":"Katharine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":761175,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":761170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Welker, Jeffrey","contributorId":214926,"corporation":false,"usgs":false,"family":"Welker","given":"Jeffrey","affiliations":[{"id":37194,"text":"University of Alaska Anchorage","active":true,"usgs":false}],"preferred":false,"id":761176,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228343,"text":"70228343 - 2019 - Antipredator response diminishes during periods of resource deficit for a large herbivore","interactions":[],"lastModifiedDate":"2022-02-09T17:21:24.143256","indexId":"70228343","displayToPublicDate":"2019-03-13T11:12:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Antipredator response diminishes during periods of resource deficit for a large herbivore","docAbstract":"The starvation-predation hypothesis predicts that, during resource shortages, prey forego antipredator behavior and forage as much as possible to avoid starvation, even when risk of predation is high. We tested this hypothesis using GPS locations collected simultaneously from moose (Alces alces) and wolves (Canis lupus) in the Greater Yellowstone Ecosystem of North America. We assessed shifts in the speed, displacement, and habitat selection of moose 24 hours following encounter with wolves (0–1500 m distance). We examined whether the strength of antipredator behaviors would weaken as winter progressed and the nutritional condition of moose declined. Moose responded to wolf encounters by increasing their rate of movement in early winter, but only within 500 m distance. Importantly, these responses attenuated as winter progressed. Moose did not avoid their preferred foraging habitat (riparian areas) following encounters with wolves at any distance, and instead they more strongly selected riparian areas, especially in early winter. Our findings support theoretical predictions that resource deficits should dampen prey antipredator behavior, and suggest that nutritional condition of prey may buffer against run-away risk effects in food webs involving large mammalian predators and prey.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2618","usgsCitation":"Oates, B.A., Merkle, J., Kauffman, M., Dewey, S., Jimenez, M., Vartanian, J., Becker, S., and Goheen, J., 2019, Antipredator response diminishes during periods of resource deficit for a large herbivore: Ecology, v. 100, no. 4, e02618, 8 p., https://doi.org/10.1002/ecy.2618.","productDescription":"e02618, 8 p.","ipdsId":"IP-098231","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bridger-Teton National Forest, Grand Teton National Park,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.9674072265625,\n 42.85985981506279\n ],\n [\n -110.2972412109375,\n 42.85985981506279\n ],\n [\n -110.2972412109375,\n 43.95328204198018\n ],\n [\n -110.9674072265625,\n 43.95328204198018\n ],\n [\n -110.9674072265625,\n 42.85985981506279\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Oates, Brendan A.","contributorId":275241,"corporation":false,"usgs":false,"family":"Oates","given":"Brendan","email":"","middleInitial":"A.","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":833868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkle, J.A.","contributorId":275242,"corporation":false,"usgs":false,"family":"Merkle","given":"J.A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dewey, S.R.","contributorId":275243,"corporation":false,"usgs":false,"family":"Dewey","given":"S.R.","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":833871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jimenez, M.D.","contributorId":275244,"corporation":false,"usgs":false,"family":"Jimenez","given":"M.D.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vartanian, J.M.","contributorId":275245,"corporation":false,"usgs":false,"family":"Vartanian","given":"J.M.","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Becker, S.A.","contributorId":275246,"corporation":false,"usgs":false,"family":"Becker","given":"S.A.","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833874,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goheen, J.R.","contributorId":275247,"corporation":false,"usgs":false,"family":"Goheen","given":"J.R.","email":"","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":833875,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227949,"text":"70227949 - 2019 - Winter precipitation and summer temperature predict lake water quality at macroscales","interactions":[],"lastModifiedDate":"2022-02-02T16:04:07.07506","indexId":"70227949","displayToPublicDate":"2019-03-13T09:52:13","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Winter precipitation and summer temperature predict lake water quality at macroscales","docAbstract":"Climate change can have strong effects on aquatic ecosystems, including disrupting nutrient cycling and mediating processes that affect primary production. Past studies have been conducted mostly on individual or small groups of ecosystems, making it challenging to predict how future climate change will affect water quality at broad scales. We used a subcontinental-scale database to address three objectives: (1) identify which climate metrics best predict lake water quality, (2) examine whether climate influences different nutrient and productivity measures similarly, and (3) quantify the potential effects of a changing climate on lakes. We used climate data to predict lake water quality in ~11,000 north temperate lakes across 17 U.S. states. We developed a novel machine learning method that jointly models different measures of water quality using 48 climate metrics and accounts for properties inherent in macroscale data (e.g., spatial autocorrelation). Our results suggest that climate metrics related to winter precipitation and summer temperature were strong predictors of lake nutrients and productivity. However, we found variation in the magnitude and direction of the relationship between climate and water quality. We predict that a likely future climate change scenario of warmer summer temperatures will lead to increased nutrient concentrations and algal biomass across lakes (median ~3%–9% increase), whereas increased winter precipitation will have highly variable effects. Our results emphasize the importance of heterogeneity in the response of individual ecosystems to climate and are a caution to extrapolating relationships across space.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023088","usgsCitation":"Collins, S.M., Yuan, S., Tan, P.N., Oliver, S.K., Lapierre, J.F., Cheruvelil, K., Fergus, C., Skaff, N.K., Stachelek, J., Wagner, T., and Soranno, P., 2019, Winter precipitation and summer temperature predict lake water quality at macroscales: Water Resources Research, v. 55, no. 4, p. 2708-2721, https://doi.org/10.1029/2018WR023088.","productDescription":"14 p.","startPage":"2708","endPage":"2721","ipdsId":"IP-095436","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","noUsgsAuthors":false,"publicationDate":"2019-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, S. M.","contributorId":273184,"corporation":false,"usgs":false,"family":"Collins","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":832670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yuan, S.","contributorId":273185,"corporation":false,"usgs":false,"family":"Yuan","given":"S.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":832671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tan, P. N.","contributorId":273186,"corporation":false,"usgs":false,"family":"Tan","given":"P.","email":"","middleInitial":"N.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":832672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, S. K.","contributorId":273187,"corporation":false,"usgs":false,"family":"Oliver","given":"S.","email":"","middleInitial":"K.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":832673,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lapierre, J. F.","contributorId":273188,"corporation":false,"usgs":false,"family":"Lapierre","given":"J.","email":"","middleInitial":"F.","affiliations":[{"id":41192,"text":"Université de Montreal","active":true,"usgs":false}],"preferred":false,"id":832674,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cheruvelil, K. S.","contributorId":273189,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"K. S.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":832675,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fergus, C. E.","contributorId":273190,"corporation":false,"usgs":false,"family":"Fergus","given":"C. E.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":832676,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Skaff, N. K.","contributorId":273191,"corporation":false,"usgs":false,"family":"Skaff","given":"N.","email":"","middleInitial":"K.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":832677,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stachelek, J.","contributorId":273193,"corporation":false,"usgs":false,"family":"Stachelek","given":"J.","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":832678,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832679,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Soranno, P. A.","contributorId":273195,"corporation":false,"usgs":false,"family":"Soranno","given":"P. A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":832680,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70228045,"text":"70228045 - 2019 - Behavior of adult and young grassland songbirds at fledging","interactions":[],"lastModifiedDate":"2022-02-03T15:52:54.250301","indexId":"70228045","displayToPublicDate":"2019-03-13T09:46:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"title":"Behavior of adult and young grassland songbirds at fledging","docAbstract":"The behavior of adults and young at the time of fledging is one of the least understood aspects of the breeding ecology of birds. Current hypotheses propose that fledging occurs either as a result of parent-offspring conflict or nestling choice. We used video recordings to monitor the behavior of nestling and adult grassland songbirds at the time of fledging. We observed 525 nestlings from 166 nests of 15 bird species nesting in grasslands of Alberta, Canada, and Wisconsin, USA. Overall, 78% of nestlings used terrestrial locomotion for fledging and 22% used wing-assisted locomotion. Species varied in propensity for using wing-assisted locomotion when fledging, with nestling Grasshopper Sparrows (Ammodramus savannarum) and Henslow's Sparrows (Centronyx henslowii) often doing so (47% of fledgings) and nestling Song Sparrows (Melospiza melodia), Common Yellowthroats (Geothlypis trichas), and Chestnut-collared Longspurs (Calcarius ornatus) rarely doing so (3.5% of fledgings). For 390 fledging events at 127 nests, camera placement allowed adults near nests to be observed. Of these, most young fledged (81.5%) when no adult was present at nests. Of 72 fledging events that occurred when an adult was either at or approaching a nest, 49 (68.1%) involved feeding. Of those 49 fledgings, 30 (62.1%) occurred when one or more nestlings jumped or ran from nests to be fed as an adult approached nests. The low probability of nestlings fledging while an adult was at nests, and the tendency of young to jump or run from nests when adults did approach nests with food minimize opportunities for parents to withhold food to motivate nestlings to fledge. These results suggest that the nestling choice hypothesis best explains fledging by nestlings of ground-nesting grassland songbirds, and fledging results in families shifting from being place-based to being mobile and spatially dispersed.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12289","usgsCitation":"Ribic, C., Rugg, D., Koper, N., Ellison, K., and Ng, C.S., 2019, Behavior of adult and young grassland songbirds at fledging: Journal of Field Ornithology, v. 90, no. 2, p. 143-153, https://doi.org/10.1111/jofo.12289.","productDescription":"11 p.","startPage":"143","endPage":"153","ipdsId":"IP-099894","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Wisconsin","otherGeospatial":"Brooks, Mount Horeb","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.77323532104492,\n 43.01004492519582\n ],\n [\n -89.72929000854492,\n 43.01004492519582\n ],\n [\n -89.72929000854492,\n 43.04116715093847\n ],\n [\n -89.77323532104492,\n 43.04116715093847\n ],\n [\n -89.77323532104492,\n 43.01004492519582\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112,\n 50.55\n ],\n [\n -111.85,\n 50.55\n ],\n [\n -111.85,\n 50.58\n ],\n [\n -112,\n 50.58\n ],\n [\n -112,\n 50.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"90","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":832959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rugg, David J.","contributorId":274388,"corporation":false,"usgs":false,"family":"Rugg","given":"David J.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":832960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koper, Nicola","contributorId":274389,"corporation":false,"usgs":false,"family":"Koper","given":"Nicola","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":832961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellison, Kevin","contributorId":274390,"corporation":false,"usgs":false,"family":"Ellison","given":"Kevin","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":832962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ng, Christoph S.","contributorId":274391,"corporation":false,"usgs":false,"family":"Ng","given":"Christoph","email":"","middleInitial":"S.","affiliations":[{"id":16603,"text":"University of Manitoba","active":true,"usgs":false}],"preferred":false,"id":832963,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210073,"text":"70210073 - 2019 - Recreational impacts to wildlife: Managing visitors and resources to protect wildlife","interactions":[],"lastModifiedDate":"2020-05-13T14:45:18.84393","indexId":"70210073","displayToPublicDate":"2019-03-13T09:44:24","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Recreational impacts to wildlife: Managing visitors and resources to protect wildlife","docAbstract":"Publication Abstract: Visitor use management is essential for maximizing benefits for visitors while achieving and maintaining desired resource conditions and visitor experiences on federally managed lands and waters. Visitor capacity, a component of visitor use management, is defined as the maximum amounts and types of visitor use that an area can accommodate while achieving and maintaining the desired resource conditions and visitor experiences that are consistent with the purposes for which the area was established. This visitor capacity guidebook, in combination with the “Visitor Use Management Framework” (the framework), provides managers with processes to collaboratively develop long-term strategies to manage the amounts and types of visitor use to protect resources, improve access, connect visitors to key experiences, and achieve desired conditions. The purpose of this guidebook is to provide cohesive guidance on identifying and implementing visitor capacity on federally managed lands and waters. Similar to the framework, the sliding scale of analysis is discussed throughout this guidebook to ensure the investment of time, money, and other resources for a project is commensurate with the complexity of the project and the consequences of the decision. Overall, this guidebook is meant to expand on the framework and guide a professional and consistent approach to identifying and implementing visitor capacity.\n\nPaper Abstract: Most protected natural areas, including parks, forests, and wildlife refuges, are managed under a dual mandate to preserve predominantly natural settings and processes while also accommodating recreational visitation. Visitor activities can have deleterious impacts to protected area vegetation, soil, water, wildlife, and cultural resources. The term impact denotes undesirable visitor-related effects to natural resources and/or wildlife. This paper reviews the management of recreation impacts to wildlife, including discussions of influential factors, impact indicators, and the range of management responses. This information is provided to assist recreation and land managers in avoiding or minimizing visitor impact to wildlife, particularly related to decision-making within the new Visitor Use Management (VUM) framework. Such decision-making requires a thorough understanding of the different types of wildlife impact and the use-related, environmental, and managerial factors that influence them.","language":"English","publisher":"National Park Service","collaboration":"Department of Interior, US National Park Service","usgsCitation":"Marion, J.L., 2019, Recreational impacts to wildlife: Managing visitors and resources to protect wildlife, 18 p.","productDescription":"18 p.","ipdsId":"IP-096635","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":374756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":374739,"type":{"id":15,"text":"Index Page"},"url":"https://visitorusemanagement.nps.gov/Content/documents/Contributing%20Paper_Impacts%20to%20Wildlife_Visitor%20Capacity_Edition%201.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marion, Jeffrey L. 0000-0003-2226-689X jeff_marion@usgs.gov","orcid":"https://orcid.org/0000-0003-2226-689X","contributorId":3614,"corporation":false,"usgs":true,"family":"Marion","given":"Jeffrey","email":"jeff_marion@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":788989,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202395,"text":"gip188 - 2019 - Harmful algal blooms","interactions":[],"lastModifiedDate":"2019-03-13T16:12:57","indexId":"gip188","displayToPublicDate":"2019-03-13T09:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"188","displayTitle":"Harmful Algal Blooms","title":"Harmful algal blooms","docAbstract":"This postcard provides details about \"Cyanobacterial Harmful Algal Blooms and U.S. Geological Survey Science Capabilities, \"Open File Report 2016-1174, where you can find details about how U.S. Geological Survey (USGS) scientists use traditional methods and emerging technologies in collaboration with numerous partners to lead a diverse range of studies addressing harmful algal bloom (HAB) issues in water bodies throughout the United States. Cutting-edge USGS research in HABs has advanced scientific understanding and led to practical applications that help protect ecological and human health.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip188","collaboration":" ","usgsCitation":"U.S. Geological Survey, 2019, Harmful algal blooms: U.S. Geological Survey General Information Product 188, 2 p., https://doi.org/10.3133/gip188.","productDescription":"Postcard: 8.5 x 5.5 inches","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-104836","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":361806,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0188/gip188.pdf","text":"Report","size":"344 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 188"},{"id":361805,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0188/coverthb3.jpg"},{"id":361807,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0188/gip188_highres.pdf","text":"Report","size":"1.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 188","linkHelpText":"- High Resolution"},{"id":361808,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161174","text":"Open-File Report 2016-1174","linkHelpText":"- Cyanobacterial Harmful Algal Blooms and U.S. Geological Survey Science Capabilities"},{"id":361811,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/gip185","text":"General Information Product 185","linkHelpText":"- Water Resources Science of the U.S. Geological Survey in New York"}],"contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180
Digital flood-inundation maps for a 16.4-mile reach of the Yellow River in Gwinnett County, Georgia, from 0.5 mile upstream from River Drive to Centerville Highway (Georgia State Route 124) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at two U.S. Geological Survey (USGS) streamgages in the mapped area. The maps for the 9.0-mile reach from 0.5 mile upstream from River Drive to Stone Mountain Highway (U.S. Route 78) are referenced to the streamgage Yellow River near Snellville, Ga. (station 02206500), and the maps for the 7.4-mile reach from Stone Mountain Highway to Centerville Highway are referenced to the streamgage Yellow River at Ga. 124, near Lithonia, Ga. (02207120). Real-time stage information from these streamgages can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgages Yellow River near Snellville, Ga. (02206500), and Yellow River at Ga. 124, near Lithonia, Ga. (02207120), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation.
A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineering Center's River Analysis System (HEC–RAS) software for the Yellow River and was used to compute flood profiles for a 16.4-mile reach of the Yellow River. The hydraulic model was then used to simulate 16 water-surface profiles at 1.0-foot (ft) intervals at the Yellow River near Snellville streamgage and 17 water-surface profiles at 1.0-ft intervals at the Yellow River near Lithonia streamgage. At the Yellow River near Snellville streamgage, the profiles ranged from a stage of 18.0 ft, which is 819.1 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 33.0 ft, which is 834.1 ft above NAVD 88. At the Yellow River near Lithonia streamgage, the profiles ranged from the National Weather Service action stage of 13.0 ft, which is 732.5 ft above NAVD 88, to a stage of 29.0 ft, which is 748.5 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 5.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage for both streamgages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195009","collaboration":"Prepared in cooperation with Gwinnett County, Georgia","usgsCitation":"Musser, J.W., 2019, Flood-inundation maps for the Yellow River from River Drive to Centerville Highway, Gwinnett County, Georgia: U.S. Geological Survey Scientific Investigations Report 2019–5009, 15 p., https://doi.org/10.3133/sir20195009.","productDescription":"Report: vi, 15 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-100804","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":361975,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KKB3H2","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation and flood depth for the Yellow River in Gwinnett County, Georgia based on water-surface elevation at the U.S. Geological Survey streamgages Yellow River, near Snellville, Georgia (02206500) and Yellow River at Ga. 124, near Lithonia, Georgia (02207120)"},{"id":361973,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5009/coverthb.jpg"},{"id":361974,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5009/sir20195009.pdf","text":"Report","size":"1.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5009"}],"country":"United States","state":"Georgia","county":"Gwinnett County","otherGeospatial":"Yellow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.1667,\n 33.75\n ],\n [\n -84,\n 33.75\n ],\n [\n -84,\n 33.9167\n ],\n [\n -84.1667,\n 33.9167\n ],\n [\n -84.1667,\n 33.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 2.6 billion barrels of oil and 123.9 trillion cubic feet of gas in the Tindouf Basin Province of North Africa.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193006","usgsCitation":"Brownfield, M.E., Schenk, C.J., Mercier, T.J., Woodall, C.A., Le, P.A., Tennyson, M.E., Finn, T.M., Gaswirth, S.B., Pitman, J.K., Marra, K.R., Leathers-Miller, H.M., and Drake, R.M., II, 2019, Assessment of undiscovered oil and gas resources in the Tindouf Basin Province, North Africa, 2018: U.S. Geological Survey Fact Sheet 2019–3006, 2 p., https://doi.org/10.3133/fs20193006.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-102826","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":361945,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3006/fs20193006.pdf","text":"Report","size":"476 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3006"},{"id":361944,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3006/coverthb.jpg"}],"otherGeospatial":"Tindouf Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -13,\n 25\n ],\n [\n 0,\n 25\n ],\n [\n 0,\n 30\n ],\n [\n -13,\n 30\n ],\n [\n -13,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
We studied some of the relationships between federally listed fall Chinook Salmon, Oncorhynchus tshawytscha, endemic Sand Roller, Percopsis transmontana, and non-native Smallmouth Bass, Micropterus dolomieu, in Lower Granite Reservoir on the Snake River. Because of its recent reappearance and population increase, the Sand Rollers could be filling the role of a “native invader” in the reservoir food web. We speculated that Sand Rollers could either negatively affect fall Chinook Salmon by potentially competing with them for resources in shoreline habitats or, alternatively, benefit the salmon by providing a buffer against Smallmouth Bass predation. Nighttime beach seining showed that habitat use by fall Chinook Salmon and Sand Rollers overlapped completely in spring when both species were present along shorelines. Diet data from stomach samples also showed high overlap, but data on stable isotopes of 13C and 15N suggested that each species could be obtaining much of their dietary energy from different reservoir locations. Although habitat and diet overlap are evidence of competition, diel and spatial partitioning of resource use between fall Chinook Salmon and Sand Rollers may act to reduce potential competition. Analyses of Smallmouth Bass diets showed that fall Chinook Salmon and Sand Rollers comprised the majority of prey fish consumed by bass. Across years, as Smallmouth Bass increased their consumption of Sand Rollers (range 0.219 to 0.392 fish smallmouth-1 day-1), they decreased their consumption of fall Chinook Salmon (range 0.114 to 0.050 fish smallmouth-1 day-1). The greatest effect Sand Rollers may have on fall Chinook Salmon in Lower Granite Reservoir is to serve as a buffer against Smallmouth Bass predation.
","language":"English","publisher":"Society for Northwestern Vertebrate Biology","doi":"10.1898/NWN18-13","usgsCitation":"Hemingway, R.J., Tiffan, K.F., Erhardt, J.M., Rhodes, T., and Bickford, B.K., 2019, Fall Chinook salmon (Oncorhynchus tshawytscha), sand roller (Percopsis transmontana), and smallmouth bass (Micropterus dolomieu) interactions in a Snake River reservoir: A tale of three species: Northwestern Naturalist, v. 100, no. 1, p. 26-36, https://doi.org/10.1898/NWN18-13.","productDescription":"11 p.","startPage":"26","endPage":"36","ipdsId":"IP-097818","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":362014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.25021362304689,\n 46.29476444388206\n ],\n [\n -116.9769287109375,\n 46.29476444388206\n ],\n [\n -116.9769287109375,\n 46.4752265177719\n ],\n [\n -117.25021362304689,\n 46.4752265177719\n ],\n [\n -117.25021362304689,\n 46.29476444388206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"100","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hemingway, Rulon J. 0000-0001-8143-0325 rhemingway@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-0325","contributorId":194697,"corporation":false,"usgs":true,"family":"Hemingway","given":"Rulon","email":"rhemingway@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":759198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":759199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erhardt, John M. 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":5380,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":759200,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rhodes, Tobyn N. 0000-0002-4023-4827","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":210057,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":759201,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bickford, Brad K. 0000-0003-3756-6588 bbickford@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6588","contributorId":140889,"corporation":false,"usgs":true,"family":"Bickford","given":"Brad","email":"bbickford@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":759202,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202445,"text":"sir20195002 - 2019 - Contemporary environmental assessment using a viability analysis in a large river system to inform restoration and adaptive management decisions","interactions":[],"lastModifiedDate":"2019-03-13T16:05:04","indexId":"sir20195002","displayToPublicDate":"2019-03-12T15:18:28","publicationYear":"2019","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":"2019-5002","displayTitle":"Contemporary Environmental Assessment Using a Viability Analysis in a Large River System to Inform Restoration and Adaptive Management Decisions","title":"Contemporary environmental assessment using a viability analysis in a large river system to inform restoration and adaptive management decisions","docAbstract":"As large-scale restoration plans for degraded aquatic habitats evolve, it is essential that multiorganizational collaborations have a common vision to achieve consensus on restoration goals. Development of restoration targets and postrestoration monitoring strategies can be focused using a viability analysis framework that supports an adaptive management process. Viability analysis is a robust and accommodating framework, adaptable to any restoration monitoring program and, through the determination of common desired endpoints, can aid consensus building and collaboration across jurisdictional boundaries. In the St. Clair-Detroit River System, which is the Great Lakes connecting channel between southern Lake Huron and western Lake Erie, a viability analysis framework was used to evaluate environmental parameters associated with fisheries and aquatic restoration efforts and to gauge the overall health of the aquatic environment. Steps to derive the viability analysis were as follows: (1) establishing meaningful baseline metrics, (2) identifying information deficiencies, and (3) placing the context of current conditions into a usable format for managers and practitioners. Most geographic segments were designated in overall fair condition, and the conservation targets were designated in either good or fair condition, based on available assessed indicators. Many indicators were unable to be assessed or assigned condition status, which identified research and monitoring data gaps. Metrics associated with native migratory fishes, Lake St. Clair, and islands are generally in better condition than metrics associated with the coastal terrestrial systems, aerial migrants, and coastal wetlands. These results were not unexpected given the highly urbanized landscape of the St. Clair-Detroit River System. Resource managers in the corridor can use these results to identify knowledge gaps, research and restoration priorities, and to assess progress towards meeting restoration goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195002","usgsCitation":"DeBruyne, R.L., Roseman, E.F., Ross, J.E., Newman, K.R., and Strach, R.M., 2019, Contemporary environmental assessment using a viability analysis in a large river system to inform restoration and adaptive management decisions: U.S. Geological Survey Scientific Investigations Report 2019–5002, 59 p., https://doi.org/10.3133/sir20195002.","productDescription":"xi, 59 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-071170","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":362006,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5002/sir20195002.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5002"},{"id":362005,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5002/coverthb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"St. Clair-Detroit River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.5,\n 42\n ],\n [\n -82,\n 42\n ],\n [\n -82,\n 43\n ],\n [\n -83.5,\n 43\n ],\n [\n -83.5,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Great Lakes Science Center
U.S. Geological Survey
1451 Green Road
Ann Arbor, Michigan 48105
The Upper Cretaceous Eagle Ford Group displays significant lateral and vertical geochemical variability. Much of the work on the Eagle Ford Group has been focused southwest of the San Marcos arch. To more fully characterize the Eagle Ford across the entire region, a thermally immature drill core was acquired north of the San Marcos arch that recovered the Pepper Shale and the Eagle Ford Group. Molecular and isotopic analyses of rock extracts were combined with bulk organic and inorganic geochemistry and mineralogy to track the variability in organic matter source and depositional environment, as well as to identify drivers of organic enrichment.
The Pepper Shale received significant terrigenous organic matter in its distal deltaic or prodeltaic setting compared to the more distally deposited Eagle Ford Group that primarily hosts marine organic matter. The upper Eagle Ford contains two chemofacies. The older upper Eagle Ford chemofacies has similar mineralogy and organic matter to the underlying lower Eagle Ford, and both intervals display good to excellent source rock potential. In contrast, the younger upper Eagle Ford chemofacies has a different sterane assemblage, a larger terrigenous component, and a higher clay mineral abundance. However, anoxic to euxinic depositional conditions distinguish the lower Eagle Ford from the upper Eagle Ford, which was deposited under oxic to dysoxic conditions. Redox chemistry and organic matter source are two important variables that determine source rock quality, but they did not change in parallel during Eagle Ford deposition. Differences in organic facies explain the Tmax variability, and depositional redox conditions governed organic-richness in the Eagle Ford Group in central Texas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2019.02.007","usgsCitation":"French, K.L., Birdwell, J.E., and Whidden, K.J., 2019, Geochemistry of a thermally immature Eagle Ford Group drill core in central Texas: Organic Geochemistry, v. 131, p. 19-33, https://doi.org/10.1016/j.orggeochem.2019.02.007.","productDescription":"15 p.","startPage":"19","endPage":"33","ipdsId":"IP-099901","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":467821,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.orggeochem.2019.02.007","text":"Publisher Index Page"},{"id":437544,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95QUX1H","text":"USGS data release","linkHelpText":"Geochemistry data for the USGS Gulf Coast #1 West Woodway core - A thermally immature core of the Eagle Ford Group in central Texas"},{"id":362003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","volume":"131","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":false,"id":759161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":759162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":759163,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202576,"text":"70202576 - 2019 - Towards determining spatial methane distribution on Arctic permafrost bluffs with an unmanned aerial system","interactions":[],"lastModifiedDate":"2019-03-12T10:23:33","indexId":"70202576","displayToPublicDate":"2019-03-12T10:23:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5814,"text":"SN Applied Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Towards determining spatial methane distribution on Arctic permafrost bluffs with an unmanned aerial system","docAbstract":"Arctic permafrost stores vast amounts of methane (CH4) in subsurface reservoirs. Thawing permafrost creates areas for this potent greenhouse gas to be released to the atmosphere. Identifying ‘hot spots’ of methane flux on a local scale has been limited by the spatial scales of traditional ground-based or satellite-based methane-sampling methods. Here we present a reliable and an easily replicable design using only off-the-shelf, cost-effective methane sensor components and an Unmanned Aerial System (UAS). Our results demonstrate the high efficiency of the design and the advantages of this methodology for environmental methane studies that are subjected to the high spatial variability of methane levels. On Barter Island, NE Alaska, we noted spikes in CH4 concentrations coincident with topographic features or anomalies. Such spikes may be attributed to enhanced land/air transfer and may reveal zones of high methane production and/or minimal oxidation in areas of thermoerosional gullies along thawing coastal zones. Thermoerosional gullies represent hotspots that release significantly higher levels of methane than the surrounding areas, thus suggesting that point sampling is inadequate in characterizing methane releases and that increasing rates of permafrost thaw may result in increasing point sources of high CH4 emissions.
","language":"English","publisher":"Springer","doi":"10.1007/s42452-019-0242-9","usgsCitation":"Oberle, F.K., Gibbs, A.E., Richmond, B.M., Erikson, L.H., Waldrop, M.P., and Swarzenski, P.W., 2019, Towards determining spatial methane distribution on Arctic permafrost bluffs with an unmanned aerial system: SN Applied Sciences, v. 1, p. 1-9, https://doi.org/10.1007/s42452-019-0242-9.","productDescription":"Article 236; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-098329","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460441,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s42452-019-0242-9","text":"Publisher Index Page"},{"id":362001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Oberle, Ferdinand K. J. 0000-0001-8871-3619 foberle@usgs.gov","orcid":"https://orcid.org/0000-0001-8871-3619","contributorId":195642,"corporation":false,"usgs":true,"family":"Oberle","given":"Ferdinand","email":"foberle@usgs.gov","middleInitial":"K. J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":759172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":759173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":759174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":759175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waldrop, Mark P. 0000-0003-1829-7140 mwaldrop@usgs.gov","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":1599,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","email":"mwaldrop@usgs.gov","middleInitial":"P.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":759176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":189823,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":759177,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202577,"text":"70202577 - 2019 - Long‐term plant community trajectories suggest divergent responses of native and non‐native perennials and annuals to vegetation removal and seeding treatments","interactions":[],"lastModifiedDate":"2019-07-23T13:12:42","indexId":"70202577","displayToPublicDate":"2019-03-12T10:19:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Long‐term plant community trajectories suggest divergent responses of native and non‐native perennials and annuals to vegetation removal and seeding treatments","docAbstract":"Land managers frequently apply vegetation removal and seeding treatments to restore ecosystem function following woody plant encroachment, invasive species spread, and wildfire. However, the long‐term outcome of these treatments is unclear due to a lack of widespread monitoring. We quantified how vegetation removal (via wildfire or management) with or without seeding and environmental conditions related to plant community composition change over time in 491 sites across the intermountain western United States. Most community metrics took over 10 years to reach baseline conditions posttreatment, with the slowest recovery observed for native perennial cover. Total cover was initially higher in sites with seeding after vegetation removal than sites with vegetation removal alone, but increased faster in sites with vegetation removal only. Seeding after vegetation removal was associated with rapidly increasing non‐native perennial cover and decreasing non‐native annual cover. Native perennial cover increased in vegetation removal sites irrespective of seeding and was suppressed by increasing non‐native perennial cover. Seeding was associated with higher non‐native richness across the monitoring period as well as initially higher, then declining, total and native species richness. Several cover and richness recovery metrics were positively associated with mean annual precipitation and negatively associated with mean annual temperature, whereas relationships with weather extremes depended on the lag time and season. Our results suggest that key plant groups, such as native perennials and non‐native annuals, respond to restoration treatments at divergent timescales and with different sensitivities to climate and weather variation.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12928","usgsCitation":"Copeland, S., Munson, S.M., Bradford, J.B., Butterfield, B.J., and Gunnell, K.L., 2019, Long‐term plant community trajectories suggest divergent responses of native and non‐native perennials and annuals to vegetation removal and seeding treatments: Restoration Ecology, v. 27, no. 4, p. 821-831, https://doi.org/10.1111/rec.12928.","productDescription":"11 p.","startPage":"821","endPage":"831","ipdsId":"IP-102402","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":362000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"27","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":759178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":759179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":759180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":759181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gunnell, Kevin L. 0000-0003-4157-7140","orcid":"https://orcid.org/0000-0003-4157-7140","contributorId":214119,"corporation":false,"usgs":false,"family":"Gunnell","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":38982,"text":"Great Basin Research Center, Utah Division of Wildlife Resources, Ephraim, UT","active":true,"usgs":false}],"preferred":false,"id":759182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202579,"text":"70202579 - 2019 - Diversity and abundance of wild bees in an agriculturally dominated landscape of eastern Colorado","interactions":[],"lastModifiedDate":"2019-03-12T10:17:15","indexId":"70202579","displayToPublicDate":"2019-03-12T10:17:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2356,"text":"Journal of Insect Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Diversity and abundance of wild bees in an agriculturally dominated landscape of eastern Colorado","docAbstract":"Agricultural intensification has resulted in loss of natural and semi-natural habitats impacting several important ecosystem services. One group of organisms that has suffered greatly are the bees and hence pollination, the supporting ecosystem service they complete. The United States Department of Agriculture (USDA) Conservation Reserve Program (CRP) has implemented conservation practices designed to improve habitat for pollinators in agroecosystems by paying to recover environmentally sensitive agricultural land from production, and restoring them by planting native grass mixes, pollinator-friendly legumes and wildflowers. Our study, aimed at demonstrating the efficacy of this practice, measured diversity and abundance of wild bee genera in the agricultural landscape of eastern semiarid regions of Colorado, USA, where CRP practices were implemented. Over our 3-year study, we obtained a total of 16,207 bees belonging to 51 genera. We found inconsistent differences in number of bee genera and abundance of bees in CRP fields supplemented with wildflowers compared to those with conventional grass seed mix. However, we observed only a 40–80% overlap in bee genera between fields supplemented with wildflowers and those with grass seed mixes indicating that diversity was enhanced by having both habitats. With the caveat that 3 years is a very short period to see appreciable changes, our results suggest that recovering environmentally sensitive land can strengthen pollinator populations in landscapes dominated by agricultural activities. In addition, periodic evaluation and maintenance of these recovered lands will further support the efforts towards revitalization of ecosystem services in these areas.
","language":"English","publisher":"Springer","doi":"10.1007/s10841-019-00125-1","usgsCitation":"Arathi, H.S., Vandever, M.W., and Cade, B.S., 2019, Diversity and abundance of wild bees in an agriculturally dominated landscape of eastern Colorado: Journal of Insect Conservation, v. 23, no. 1, p. 187-197, https://doi.org/10.1007/s10841-019-00125-1.","productDescription":"11 p.","startPage":"187","endPage":"197","ipdsId":"IP-085946","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":361999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","volume":"23","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Arathi, H. S.","contributorId":214123,"corporation":false,"usgs":false,"family":"Arathi","given":"H.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":759187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":759186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cade, Brian S. 0000-0001-9623-9849 cadeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9623-9849","contributorId":1278,"corporation":false,"usgs":true,"family":"Cade","given":"Brian","email":"cadeb@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":759188,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209288,"text":"70209288 - 2019 - Widespread global peatland establishment and persistence over the last 130,000 y","interactions":[],"lastModifiedDate":"2020-03-31T13:18:33","indexId":"70209288","displayToPublicDate":"2019-03-12T09:13:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Widespread global peatland establishment and persistence over the last 130,000 y","docAbstract":"Glacial−interglacial variations in CO2 and methane in polar ice cores have been attributed, in part, to changes in global wetland extent, but the wetland distribution before the Last Glacial Maximum (LGM, 21 ka to 18 ka) remains virtually unknown. We present a study of global peatland extent and carbon (C) stocks through the last glacial cycle (130 ka to present) using a newly compiled database of 1,063 detailed stratigraphic records of peat deposits buried by mineral sediments, as well as a global peatland model. Quantitative agreement between modeling and observations shows extensive peat accumulation before the LGM in northern latitudes (>40°N), particularly during warmer periods including the last interglacial (130 ka to 116 ka, MIS 5e) and the interstadial (57 ka to 29 ka, MIS 3). During cooling periods of glacial advance and permafrost formation, the burial of northern peatlands by glaciers and mineral sediments decreased active peatland extent, thickness, and modeled C stocks by 70 to 90% from warmer times. Tropical peatland extent and C stocks show little temporal variation throughout the study period. While the increased burial of northern peats was correlated with cooling periods, the burial of tropical peat was predominately driven by changes in sea level and regional hydrology. Peat burial by mineral sediments represents a mechanism for long-term terrestrial C storage in the Earth system. These results show that northern peatlands accumulate significant C stocks during warmer times, indicating their potential for C sequestration during the warming Anthropocene.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1813305116","usgsCitation":"Treat, C.C., Kleinen, T., Broothaerts , N., Dalton, A.S., Dommain, R., Douglas, T.A., Drexler, J.Z., Finkelstein, S., Grosse, G., Hope, G., Hutchings, J., Jones, M.C., Kuhry, P., Lacourse, T., Lahteenoja, O., Loisel, J., Notebaert, B., Payne, R., Peteet, D.M., Sannel, A.B., Stelling, J.M., Strauss, J., Swindles, G.T., Talbot, J., Tarnocai, C., Verstraeten, G., Williams , C., Xia, Z., Yu, Z., Valiranta, M., Hattestrand, M., Alexanderson, H., and Brovkin, V., 2019, Widespread global peatland establishment and persistence over the last 130,000 y: PNAS, v. 116, no. 11, p. 4822-4827, https://doi.org/10.1073/pnas.1813305116.","productDescription":"6 p.","startPage":"4822","endPage":"4827","ipdsId":"IP-091584","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":467822,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1813305116","text":"Publisher Index Page"},{"id":373582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","issue":"11","noUsgsAuthors":false,"publicationDate":"2019-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Treat, Claire C.","contributorId":96606,"corporation":false,"usgs":true,"family":"Treat","given":"Claire","email":"","middleInitial":"C.","affiliations":[{"id":25501,"text":"University of Eastern Finland","active":true,"usgs":false}],"preferred":false,"id":785865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleinen, Thomas 0000-0001-9550-5164","orcid":"https://orcid.org/0000-0001-9550-5164","contributorId":50427,"corporation":false,"usgs":true,"family":"Kleinen","given":"Thomas","email":"","affiliations":[{"id":32387,"text":"Max Planck Institute for Meteorology, Hamburg, Germany","active":true,"usgs":false}],"preferred":false,"id":785866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Broothaerts , Nils ","contributorId":223665,"corporation":false,"usgs":true,"family":"Broothaerts ","given":"Nils ","affiliations":[],"preferred":false,"id":785867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalton, April S.","contributorId":223666,"corporation":false,"usgs":true,"family":"Dalton","given":"April","email":"","middleInitial":"S.","affiliations":[{"id":13300,"text":"3Department of Earth Sciences, University of Toronto, Toronto, Ontario M5S 3B1, Canada.","active":true,"usgs":false}],"preferred":false,"id":785868,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dommain, Rene","contributorId":220666,"corporation":false,"usgs":false,"family":"Dommain","given":"Rene","email":"","affiliations":[{"id":40220,"text":"University of Potsdam, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":785869,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douglas, Thomas A. 0000-0003-1314-1905","orcid":"https://orcid.org/0000-0003-1314-1905","contributorId":64553,"corporation":false,"usgs":false,"family":"Douglas","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":33087,"text":"Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":true,"id":785870,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - 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The 6th International Swan Symposium (6th ISS), was held at the Estonian University of Life Sciences in Tartu, Estonia, in October 2018. The symposium brought together 101 delegates from 17 countries, with presentations on a range of topics on Cygnus and Coscoroba species, including monitoring, habitat and resource use, demography, movements and migration, and threats and conservation. The proceedings of the 6th ISS in this special issue of Wildfowl include select papers on swan research presented at the 6th ISS, covering a wide range of species, systems and issues. This paper presents a synthesis of the 6th ISS and an overview of current trends and future directions in swan research. Despite progress on many topics, southern hemisphere swan species continue to receive less attention than their northern hemisphere counterparts, whilst facing many of the same pressures. It is clear that, given the challenges facing swan researchers in the twenty-first century, international cooperation will continue to be vital. Swans are highly mobile animals and many populations undertake migrations spanning thousands of kilometres, and crucially do not recognise human geographic and political borders. Such international collaborations will be particularly important in coordinating future monitoring and conservation activities. The IUCN-SSC/Wetlands International Swan Specialist Group (SSG) will continue to facilitate international collaborations and communication among the global network of swan researchers, through its activities, website and annual newsletter. Given the substantial challenges and knowledge gaps documented here, there is no doubt that swan researchers will continue to benefit from regular symposia to share information and develop collaborations towards understanding and addressing emerging conservation issues. As such, we recommend holding International Swan Symposia every 4–5 years.
Lakeshore areas provide important habitat for aquatic invertebrates in shallow lakes. However, these zones are prone to anthropogenic disturbances that include shoreline development, urbanization, nutrient inputs, agricultural and(or) recreational use. Among recreational uses, public access sites are often developed to accommodate boaters and facilitate lake access via boat ramps. Although the ‘foot print’ associated with boat ramp structures can be relatively small compared to total shoreline coverage, little is known about the relative effects of boating activity on littoral zones and macroinvertebrate communities. In this study, we assess the relative impact of boating-related activities on aquatic macroinvertebrate communities at high-use (primary) and low-use (secondary) boat ramps on five glacial lakes of eastern South Dakota. Macroinvertebrate assemblages were dominated by few taxa that included Chironomidae, Corixidae, Caenidae, and Amphipoda. Moreover, boat ramp use did not influence abundance or diversity of aquatic macroinvertebrates. Habitat, specifically substrate composition, was also similar between primary and secondary boat ramps despite more intense use associated with primary boat ramps. Our results support related findings that aquatic invertebrate assemblages in the Prairie Pothole Region are structured by regional environmental variability (climate, habitat, and water quality) resulting in communities with characteristically low diversity and tolerant taxa. This may explain why small-scale disturbance associated with boating activity has no discernable effect on macroinvertebrate assemblages in glacial lakes of the Prairie Pothole Region.