Salmon populations spawning in the Lake Ozette watershed of northwestern Washington were once sufficiently abundant to support traditional Tribal fisheries, and were later harvested by settlers. However, in 1974 and 1975, the sockeye salmon (Oncorhynchus nerka) harvest decreased to 0 from a high of more than 17,500 in 1949, thus stimulating research into the causes of decrease, which resulted in eventual listing of the population as threatened under the Endangered Species Act in 1999. The listing status was upheld in 2005 and 2014 following 5-year reviews. Meanwhile, research results were compiled in a limiting factors analysis (LFA) and a recovery plan was developed. Although there has been some improvement in sockeye abundance since listing, the numbers remain too low to allow harvest and it is not yet clear which of the many potential limiting factors are most consequential.
As part of the LFA process, a population model was developed to determine values of life-history parameters that would enable the population to survive for 100 years. The model was based on the best available data, but data are limited for the Lake Ozette system. Results informed the qualitative assessment of the importance of limiting factors used to develop the recovery plan for Lake Ozette sockeye. The model was built in Microsoft Excel® and is difficult to use. The purpose of the model described herein is to synthesize the results of the LFA in a form that can be manipulated by resource managers and the public to create scenarios, test hypotheses, and observe sensitivities of results to changes in parameters. The goal is to provide a tool that enables research, monitoring and management to be focused on the most impactful elements and processes, including identifying the information gaps that are most critical to fill.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191031","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Woodward, A., Haggerty, M., and Crain, P., 2019, Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide: U.S. Geological Survey Open-File Report 2019-1031, 79 p., https://doi.org/10.3133/ofr20191031.","productDescription":"viii, 79 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-101934","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362633,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1031/coverthb.jpg"},{"id":362634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1031/ofr20191031.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1031"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Ozette","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.68074798583986,\n 48.033560004128255\n ],\n [\n -124.59320068359374,\n 48.033560004128255\n ],\n [\n -124.59320068359374,\n 48.15509285476017\n ],\n [\n -124.68074798583986,\n 48.15509285476017\n ],\n [\n -124.68074798583986,\n 48.033560004128255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Environmental stochasticity encountered during migration can have negative consequences for individuals and population demographics through direct reductions in survival or cross-seasonal impacts. We took advantage of substantial interannual variation in spring migration conditions over a 4 year field study to examine physiological and dietary variation among two species of migrant ducks. We collected female Lesser Scaup (Aythya affinis (Eyton, 1838)) and Blue-winged Teal (Spatula discors (Linnaeus, 1766)) during spring migration and measured lipid and protein reserves, an index of recent lipid metabolism based on concentrations of lipid metabolites in plasma, and diets. We documented systematic interannual variation among these metrics in both species, contrasting primarily the warmest, earliest spring and the coldest, latest spring. Lesser Scaup had reduced lipid and protein reserves and consumed less energy-rich prey during the coldest and latest spring but showed no interannual variation in the index of lipid metabolism. Blue-winged Teal similarly had reduced protein reserves in the cold, late spring but maintained constant lipid reserves among years, likely facilitated by increased consumption of energy-rich seeds reflected in diets and lipid metabolism. Our results reveal impacts of environmental stochasticity on migrants and suggest that recruitment may be impacted by variable conditions encountered during migration during extreme weather events.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2018-0075","usgsCitation":"Janke, A.K., Anteau, M.J., and Stafford, J.D., 2019, Extreme climatic variability during migration invokes physiological and dietary plasticity among spring migrating ducks: Canadian Journal of Zoology, v. 97, no. 4, p. 340-351, https://doi.org/10.1139/cjz-2018-0075.","productDescription":"12 p.","startPage":"340","endPage":"351","ipdsId":"IP-097607","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467746,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/94294","text":"External Repository"},{"id":395459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.51391601562499,\n 45.94351068030587\n ],\n [\n -100.32714843749999,\n 45.66780526567164\n ],\n [\n -100.546875,\n 45.590978249451936\n ],\n [\n -100.32714843749999,\n 45.44471679159555\n ],\n [\n -100.316162109375,\n 45.29034662473613\n ],\n [\n -100.37109375,\n 45.02695045318546\n ],\n [\n -100.546875,\n 44.762336674810996\n ],\n [\n -100.6787109375,\n 44.824708282300236\n ],\n [\n -100.634765625,\n 44.55916341529182\n ],\n [\n -100.37109375,\n 44.36313311380771\n ],\n [\n -99.920654296875,\n 44.268804788566165\n ],\n [\n -99.95361328125,\n 44.15856343854312\n ],\n [\n -99.60205078124999,\n 44.12702800650004\n ],\n [\n -99.36035156249999,\n 43.99281450048989\n ],\n [\n -99.481201171875,\n 43.691707903073805\n ],\n [\n -99.404296875,\n 43.6599240747891\n ],\n [\n -99.31640625,\n 43.50075243569041\n ],\n [\n -98.72314453125,\n 43.08493742707592\n ],\n [\n -98.5693359375,\n 43.08493742707592\n ],\n [\n -98.54736328125,\n 42.99661231842139\n ],\n [\n -98.009033203125,\n 42.771211138625894\n ],\n [\n -97.8662109375,\n 42.83569550641452\n ],\n [\n -97.294921875,\n 42.867912483915305\n ],\n [\n -97.18505859374999,\n 42.79540065303723\n ],\n [\n -96.734619140625,\n 42.62587560259137\n ],\n [\n -96.602783203125,\n 42.48830197960227\n ],\n [\n -96.45996093749999,\n 42.47209690919285\n ],\n [\n -96.61376953125,\n 42.74701217318067\n ],\n [\n -96.448974609375,\n 43.07691312608711\n ],\n [\n -96.48193359375,\n 43.205175817237304\n ],\n [\n -96.558837890625,\n 43.213183300738876\n ],\n [\n -96.591796875,\n 43.27720532212024\n ],\n [\n -96.51489257812499,\n 43.30119623257966\n ],\n [\n -96.51489257812499,\n 43.37311218382002\n ],\n [\n -96.602783203125,\n 43.43696596521823\n ],\n [\n -96.602783203125,\n 43.50075243569041\n ],\n [\n -96.448974609375,\n 43.50075243569041\n ],\n [\n -96.448974609375,\n 45.29034662473613\n ],\n [\n -96.50390625,\n 45.359865333959746\n ],\n [\n -96.712646484375,\n 45.44471679159555\n ],\n [\n -96.78955078125,\n 45.54483149242463\n ],\n [\n -96.83349609375,\n 45.62940492064501\n ],\n [\n -96.591796875,\n 45.79050946752472\n ],\n [\n -96.558837890625,\n 45.9511496866914\n ],\n [\n -100.51391601562499,\n 45.94351068030587\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":833116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":833117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Joshua D. 0000-0001-7590-8708 jstafford@usgs.gov","orcid":"https://orcid.org/0000-0001-7590-8708","contributorId":267260,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833115,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203433,"text":"70203433 - 2019 - Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem","interactions":[],"lastModifiedDate":"2019-05-14T11:56:23","indexId":"70203433","displayToPublicDate":"2019-04-01T11:56:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem","docAbstract":"Grizzly bear (Ursus arctos) conflicts with humans, including livestock depredation on public\nland grazing allotments, have increased during the last several decades within the Greater Yellowstone Ecosystem (GYE) in the western United States as the grizzly bear population has grown in number and occupied range. Minimizing conflicts and improving conservation efficacy requires information on the relationships between livestock depredations, allotment management, grizzly bear habitat conditions, and their interactions. We used generalized linear mixed models to evaluate spatio-temporal relationships between grizzly bear depredation of livestock and the characteristics of 316 United States Department of Agriculture Forest Service and National Park Service grazing allotments in the GYE during 1992–2014. We evaluated relationships at 2 spatial extents, representing daily and annual grizzly bear activity areas. During the study period, more grazing allotments became occupied by grizzly bears and most livestock depredations were associated with these areas of population expansion. Number of livestock (beta = 1.15 +/- 0.19 [SE]) and grizzly bear density index (beta = 1.13 +/- 0.10) had the greatest effects on the number of livestock depredation events relative to other allotment attributes. Estimated number of depredation events increased by approximately 20% when cow-calf pairs increased by 100 pairs and grizzly bear density index increased by 1 bear/196 km2 (the average annual home-range size of a female grizzly bear in the GYE). Additionally, grazing allotment size was positively related to the number of depredation events (beta = 0.56 +/- 0.16), whereas the presence of bull cattle or horses was associated with an approximately 50% reduction in depredations (beta = -0.71 +/- 0.37). Livestock depredation events were greater for allotments with lower road density (beta = -0.89 +/- 0.28), less rugged terrain (beta = -0.57 +/- 0.25), higher vegetative primary productivity (beta = 0.33 +/- 0.16), and more whitebark pine coverage (beta = 0.30 +/- 0.15). Relationships between depredations and grizzly bear habitat conditions varied across spatial extents. As the grizzly bear population continues to expand, natural resource managers and livestock producers could focus efforts on allotments with a higher density of grizzly bears, fewer roads, and quality grizzly bear habitat, including higher vegetative productivity, when developing cooperative management plans and preventative measures to reduce the likelihood of depredation. The perspectives gained from our analysis provide context for long-term, landscape-level planning to accommodate livestock production on public lands while meeting conservation goals for grizzly bears.","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21618","usgsCitation":"Wells, S.L., McNew, L.B., Tyers, D.B., van Manen, F.T., and Thompson, D.J., 2019, Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem: Journal of Wildlife Management, v. 83, no. 3, p. 556-566, https://doi.org/10.1002/jwmg.21618.","productDescription":"11 p.","startPage":"556","endPage":"566","ipdsId":"IP-096436","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.21618","text":"Publisher Index Page"},{"id":363764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.32421875,\n 43.54854811091286\n ],\n [\n -109.0283203125,\n 43.54854811091286\n ],\n [\n -109.0283203125,\n 45.36758436884978\n ],\n [\n -112.32421875,\n 45.36758436884978\n ],\n [\n -112.32421875,\n 43.54854811091286\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Smith L.","contributorId":215575,"corporation":false,"usgs":false,"family":"Wells","given":"Smith","email":"","middleInitial":"L.","affiliations":[{"id":39286,"text":"Montana State University, Department of Animal and Range Sciences","active":true,"usgs":false}],"preferred":false,"id":762689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McNew, Lance B.","contributorId":190322,"corporation":false,"usgs":false,"family":"McNew","given":"Lance","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":762690,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tyers, Daniel B.","contributorId":124587,"corporation":false,"usgs":false,"family":"Tyers","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":5129,"text":"U.S. Forest Service, 2327 University Way, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":762691,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":762688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thompson, Daniel J.","contributorId":149795,"corporation":false,"usgs":false,"family":"Thompson","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":5116,"text":"Large Carnivore Section, Wyoming Game & Fish Department, 260 Buena Vista, Lander, WY 82520, USA","active":true,"usgs":false}],"preferred":false,"id":762692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203387,"text":"70203387 - 2019 - Earth history and the passerine superradiation","interactions":[],"lastModifiedDate":"2019-06-25T11:36:54","indexId":"70203387","displayToPublicDate":"2019-04-01T11:32:27","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":"Earth history and the passerine superradiation","docAbstract":"Avian diversification has been influenced by global climate change, plate tectonic movements, and mass extinction events. However, the impact of these factors on the diversification of the hyperdiverse perching birds (passerines) is unclear because family level relationships are unresolved and the timing of splitting events among lineages is uncertain. We analyzed DNA data from 4060 nuclear loci and 137 passerine families using concatenation and coalescent approaches to infer a comprehensive phylogenetic hypothesis that clarifies relationships among all passerine families. Then, we calibrated this phylogeny using 13 fossils to examine the effects of different events in Earth history on the timing and rate of passerine diversification. Our analyses reconcile passerine diversification with the fossil and geological records, suggest that passerines originated on the Australian landmass ~47 Ma, and show that subsequent dispersal and diversification of passerines was affected by a number of climatological and geological events, such as Oligocene glaciation and inundation of the New Zealand landmass. Although passerine diversification rates fluctuated throughout the Cenozoic, we find no link between the rate of passerine diversification and Cenozoic global temperature, and our analyses show that the increases in passerine diversification we observe are disconnected from the colonization of new continents. Taken together, these results suggest more complex mechanisms than temperature change or ecological opportunity have controlled macroscale patterns of passerine speciation.","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.1813206116","collaboration":"Carl Oliveros et al","usgsCitation":"Oliveros, C.H., Field, D.J., Ksepka, D.T., Barker, F., Aleixo, A., Andersen, M., Alstrom, P., Benz, B.W., Braun, E.L., Braun, M., Bravo, G., Brumfield, R., Chesser, T., Claramunt, S., Cracraft, J., Andrés M. Cuervo, Derryberry, E.P., Glenn, T.C., Harvey, M.G., Hosner, P.A., Joseph, L., Kimball, R., Mack, A.L., Miskelly, C.M., A. Townsend Peterson, Mark B. Robbins, Frederick H. Sheldon, Luís Fábio Silveira, Smith, B.T., Noor D. White, Moyle, R.G., and Faircloth, B.C., 2019, Earth history and the passerine superradiation: PNAS, v. 116, no. 16, p. 7916-7925, https://doi.org/10.1073/pnas.1813206116.","productDescription":"12 p.","startPage":"7916","endPage":"7925","ipdsId":"IP-103538","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467748,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1813206116","text":"Publisher Index Page"},{"id":365012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","issue":"16","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oliveros, Carl H","contributorId":215463,"corporation":false,"usgs":false,"family":"Oliveros","given":"Carl","email":"","middleInitial":"H","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":762447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Field, Daniel J","contributorId":215464,"corporation":false,"usgs":false,"family":"Field","given":"Daniel","email":"","middleInitial":"J","affiliations":[{"id":39255,"text":"Univ. of Bath","active":true,"usgs":false}],"preferred":false,"id":762448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ksepka, Daniel T","contributorId":215465,"corporation":false,"usgs":false,"family":"Ksepka","given":"Daniel","email":"","middleInitial":"T","affiliations":[{"id":39256,"text":"Bruce Museum","active":true,"usgs":false}],"preferred":false,"id":762449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barker, F Keith","contributorId":215466,"corporation":false,"usgs":false,"family":"Barker","given":"F Keith","affiliations":[{"id":27811,"text":"Univ. of Minnesota","active":true,"usgs":false}],"preferred":false,"id":762450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aleixo, Alexandre","contributorId":215467,"corporation":false,"usgs":false,"family":"Aleixo","given":"Alexandre","email":"","affiliations":[{"id":39257,"text":"Goeldi Museum","active":true,"usgs":false}],"preferred":false,"id":762451,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andersen, Michael J","contributorId":215468,"corporation":false,"usgs":false,"family":"Andersen","given":"Michael J","affiliations":[{"id":39258,"text":"Univ New Mexico","active":true,"usgs":false}],"preferred":false,"id":762452,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alstrom, Per","contributorId":215469,"corporation":false,"usgs":false,"family":"Alstrom","given":"Per","email":"","affiliations":[{"id":33333,"text":"Uppsala Univ.","active":true,"usgs":false}],"preferred":false,"id":762453,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Benz, Brett W","contributorId":215470,"corporation":false,"usgs":false,"family":"Benz","given":"Brett","email":"","middleInitial":"W","affiliations":[{"id":6989,"text":"American Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":762454,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Braun, Edward L","contributorId":215471,"corporation":false,"usgs":false,"family":"Braun","given":"Edward","email":"","middleInitial":"L","affiliations":[{"id":17943,"text":"Univ of Florida","active":true,"usgs":false}],"preferred":false,"id":762455,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Braun, Michael J","contributorId":215472,"corporation":false,"usgs":false,"family":"Braun","given":"Michael J","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":762456,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bravo, Gustavo A","contributorId":215473,"corporation":false,"usgs":false,"family":"Bravo","given":"Gustavo A","affiliations":[{"id":16810,"text":"Harvard Univ.","active":true,"usgs":false}],"preferred":false,"id":762457,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brumfield, Robb T","contributorId":215474,"corporation":false,"usgs":false,"family":"Brumfield","given":"Robb T","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":762458,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chesser, Terry 0000-0003-4389-7092 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Townsend Peterson","contributorId":215486,"corporation":false,"usgs":false,"family":"A. Townsend Peterson","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":762470,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Mark B. Robbins","contributorId":215487,"corporation":false,"usgs":false,"family":"Mark B. Robbins","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":762471,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Frederick H. Sheldon","contributorId":215488,"corporation":false,"usgs":false,"family":"Frederick H. 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White","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":762475,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Moyle, Robert G.","contributorId":215492,"corporation":false,"usgs":false,"family":"Moyle","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":762476,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Faircloth, Brant C.","contributorId":215493,"corporation":false,"usgs":false,"family":"Faircloth","given":"Brant","email":"","middleInitial":"C.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":762477,"contributorType":{"id":1,"text":"Authors"},"rank":32}]}} ,{"id":70074783,"text":"sim2932B - 2019 - Geologic map of the central-southeast flank of Mauna Loa Volcano, Island of Hawaii, Hawaii","interactions":[],"lastModifiedDate":"2024-05-23T22:02:49.901846","indexId":"sim2932B","displayToPublicDate":"2019-04-01T11:26:46","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2932-B","displayTitle":"Geologic Map of the Central-Southeast Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii","title":"Geologic map of the central-southeast flank of Mauna Loa Volcano, Island of Hawaii, Hawaii","docAbstract":"Mauna Loa, the largest volcano on Earth, has erupted 33 times since written descriptions became available in 1832. Some eruptions began with only brief seismic unrest, while others followed several months to a year of increased seismicity. Once underway, its eruptions can produce lava flows that may reach the sea in less than 24 hours, severing roads and utilities. For example, lava flows erupted from the Southwest Rift Zone (SWRZ) in 1950 advanced at an average rate of 9.3 km per hour, and all three lobes reached the ocean within approximately 24 hours (Finch and Macdonald, 1953). Near the eruptive vents, the flows must have traveled even faster. In terms of eruption frequency, pre-eruption warning, and rapid flow emplacement, Mauna Loa poses an enormous volcanic-hazard threat to the Island of Hawai‘i. Volcanic hazards on Mauna Loa may be anticipated, and risk substantially mitigated, by documenting the past activity to refine our knowledge of the hazards and by alerting the public and local government officials of our findings and their implications for hazards assessments and risk.
From the geologic record, we may deduce several generalized facts about the geologic history of the Northeast Rift Zone (NERZ). The middle to uppermost segments of the rift zone were more active in the past 4,000 years than the lower portion of the rift zone. This may be due to buttressing of the lower east rift zone by Mauna Kea and Kīlauea volcanoes. The historical flows that erupted on the north side of the rift zone advanced toward Hilo. This flank of the volcano may be more vulnerable to inundation. Lockwood (1990) noted that the vents of historical activity are migrating to the south. The volcano appears to have a self-regulating mechanism that evenly distributes long-term activity across its flanks. The geologic record also supports this notion; the time prior to the historical period (Age Group 1, pre-A.D. 1832 to 1,000 yrs B.P.; orange units) is dominated by activity on the south side of the NERZ.
Although most Mauna Loa eruptions begin in the summit area at the 12,000-ft elevation (Lockwood and Lipman, 1987), the central-southeast flank has not been the source of any activity. All flows originated from the summit or the upper reaches of the Northeast Rift Zone (NERZ) or the Southwest Rift Zone (SWRZ). The NERZ was the source of eight flank eruptions since 1843. The NERZ extends from the 13,680-ft-high summit towards Hilo (population ~60,000; second-largest city in State of Hawaii). The northern portion of the map area is built entirely on flows erupted from the NERZ. The SWRZ extends from the summit towards Kalae (South Point) at sea level. The southern portion of the map area is built entirely on flows erupted from the SWRZ.
The map area extends from the 10,350-ft elevation on Mauna Loa’s east flank toward the Hawaii Volcanoes National Park and the town of Volcano (population approx. 2,000) in the northeast. At the south boundary of the map area is the town of Pāhala (population approx. 900). This map includes areas adjacent to and downslope of the NERZ and regions east of and directly downslope of Moku‘āweoweo, Mauna Loa’s summit caldera.
The map encompasses 506 km2 of the southeast flank (fig. 1) of Mauna Loa from 10,350-ft elevation to sea level. The map of the central-southeast flank of Mauna Loa shows the distribution and relations of volcanic and surficial sedimentary deposits separated into 15 age groups ranging from a period greater than 50,000 yr B.P. to A.D. 1984. It incorporates previously reported work published in generalized small-scale maps (Lockwood and Lipman, 1987; Lockwood, 1995; Wolfe and Morris, 1996).
This map is the second in a series of five maps that will cover Mauna Loa volcano. See SIM 2932-A at https://doi.org/10.3133/sim2932A.
NOTE: Map sheet 1 contains lines and type with overprint. This feature may be turned on or off in the Adobe Acrobat page display preferences.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim2932B","usgsCitation":"Trusdell, F.A., and Lockwood, J.P., 2019, Geologic map of the central-southeast flank of Mauna Loa volcano, Island of Hawai‘i, Hawaii: U.S. Geological Survey Scientific Investigations Map 2932–B, scale 1:50,000, 2 sheets, pamphlet 23 p., https://doi.org/10.3133/sim2932B.","productDescription":"Pamphlet: iii, 23 p.; 2 Sheets: 33.94 x 39.27 inches and 39.59 x 29.91 inches; Chemical data table; Metadata; Read Me; Geospatial data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-011879","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":429220,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932E","text":"Scientific Investigations Map 2932-E","linkHelpText":"- Geologic Map of the Northwest Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":374330,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932C","text":"Scientific Investigations Map 2932-C","linkHelpText":"- Geologic Map of the Southern Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":362610,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932A","text":"Scientific Investigations Map 2932-A","linkHelpText":"- Geologic Map of the Northeast Flank of Mauna Loa Volcano, Island of Hawai'i, Hawaii"},{"id":362608,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_chemical_data_table.xlsx","text":"Chemical data table","size":"25 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":362607,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_sheet2.pdf","text":"Sheet 2","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":362606,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_sheet1.pdf","text":"Sheet 1","size":"7.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":362605,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_pamphlet.pdf","text":"Pamphlet","size":"700 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":362604,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_METADATA.zip","size":"400 KB","linkFileType":{"id":6,"text":"zip"}},{"id":362603,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_DATABASE.zip","text":"Geospatial data","size":"6.5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":362590,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/2932/b/sim2932b_readme.docx","size":"2 KB docx"},{"id":362543,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/2932/b/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.5,\n 19.125\n ],\n [\n -155.125,\n 19.125\n ],\n [\n -155.125,\n 19.5\n ],\n [\n -155.5,\n 19.5\n ],\n [\n -155.5,\n 19.125\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact HVO
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U.S. Geological Survey
The combination of life-history traits that makes some turtle species vulnerable to population declines also limits their ability to recover even after threats have been addressed. Because juvenile turtle survival is typically lower than adult survival, head-starting, the process of rearing juveniles through one of their most vulnerable periods, may be a useful recovery tool. We evaluated short-term, outdoor head-starting in Mojave Desert Tortoises (Gopherus agassizii) by comparing growth and survival among three treatments: (1) juveniles reared in outdoor predator-resistant enclosures and receiving low (LOW) or (2) high levels of rain supplementation (HIGH); and (3) free-ranging animals released 0-18 mo after hatching (FIELD). Juveniles from the HIGH treatment had higher annual growth (12.7 mm midline carapace length [MCL] per year) than juveniles from the LOW or FIELD treatments (10.7 mm). Annual growth also varied among years, presumably due to variation in rainfall. Annual survival was high (0.94 ± 0.01) for both LOW and HIGH treatments; MCL at hatching had a weak positive effect on survival probability (effect size: 0.42 ± 0.35). Annual survival of FIELD animals averaged 0.48 ± 0.09. There was no effect of size at release (40.8-61.5 mm MCL) on post-release survival of FIELD animals, suggesting that the greatest benefit of short-term outdoor head-starting is increasing survival during the head-start period. Although releasing at larger sizes (100 mm MCL) has been recommended, slow growth in tortoises would require extended outdoor head-starting periods. Indoor rearing, which has been successfully implemented with other turtle species, may increase growth rates of juvenile Desert Tortoises and warrants future study as a conservation technique.
Occupancy models are widely applied to estimate species distributions, but few methods exist for model checking. Thorough model assessments can uncover inadequacies and allow for deeper ecological insight by exploring structure in the observed data not accounted for by a model. We introduce occupancy model residual definitions that utilize the posterior distribution of the partially latent occupancy states. Residual‐based assessments are valuable because they can target specific assumptions and identify ways to improve a model, such as adding spatial correlation or meaningful covariates. Our approach defines separate residuals for occupancy and detection, and we use simulation to examine whether missing structure for modeling detection probabilities can be distinguished from that for occupancy probabilities. In many scenarios, our residual diagnostics were able to successfully separate inadequacies at the different model levels, but we describe other situations when this may not be the case. Applying Moran's I residual diagnostics to assess models for silver‐haired (Lasionycteris noctivagans) and little brown (Myotis lucifugus) bats only provided evidence of residual spatial correlation among detections. Targeting specific model assumptions using carefully chosen residual diagnostics is valuable for any analysis, and we remove previous barriers for occupancy analyses — lack of examples and practical advice.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.2703","usgsCitation":"Wright, W., Irvine, K., and Higgs, M.D., 2019, Identifying occupancy model inadequacies: Can residuals separately assess detection and presence?: Ecology, v. 100, no. 6, e02703, https://doi.org/10.1002/ecy.2703.","productDescription":"e02703","ipdsId":"IP-088414","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":467749,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ecy.2703","text":"External Repository"},{"id":362650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"100","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Wilson 0000-0003-4276-3850","orcid":"https://orcid.org/0000-0003-4276-3850","contributorId":214592,"corporation":false,"usgs":true,"family":"Wright","given":"Wilson","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":760332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":214591,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":760331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgs, Megan D.","contributorId":127365,"corporation":false,"usgs":false,"family":"Higgs","given":"Megan","email":"","middleInitial":"D.","affiliations":[{"id":6916,"text":"Department of Mathematical Sciences, Montana State University, Bozeman, USA","active":true,"usgs":false}],"preferred":false,"id":760333,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219176,"text":"70219176 - 2019 - Status of pelagic prey fishes in Lake Michigan, 2018","interactions":[],"lastModifiedDate":"2021-04-16T12:21:47.47692","indexId":"70219176","displayToPublicDate":"2019-04-01T10:39:36","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Status of pelagic prey fishes in Lake Michigan, 2018","docAbstract":"Acoustic surveys were conducted in late summer/early fall during the years 2004-2018 to estimate pelagic prey fish biomass in Lake Michigan. Midwater trawling during the surveys as well as acoustic target strength provided a measure of species and size composition of the fish community for use in scaling acoustic data and providing species-specific abundance estimates. The 2018 survey consisted of 33 acoustic transects 648 km total (403 miles) and 52 midwater trawl tows. Bottom depth at sampling sites ranged from 5 to 245 m (16-804 ft). Mean prey fish biomass density was 8.5 kg/ha, which was 1.9 times higher than in 2017 and 2.4 times the long-term (15 years) mean. The numeric density of the 2018 alewife year-class was 52% of the time series average and 1.8 times the 2017 density. The 2018 cohort was 7% of total alewife biomass (5.2 kg/ha). In 2018 alewife comprised 61% of total prey fish biomass, while rainbow smelt and bloater were 2% and 37% of total biomass, respectively. Small bloater were extremely rare in 2018 and were only caught near Frankfort, Michigan. Their density (< 1 fish/ha) in 2018 was the lowest observed in the 2004-2018 period. Biomass density of rainbow smelt and bloater remain well below observed in the 1980s-1990s. Cisco are infrequently caught in this survey, including the past two years. In 2018 three adult fish were caught (> 400 mm), with two in Grand Traverse Bay and one south of Manistique, Michigan. 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through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15481603.2018.1517445","usgsCitation":"Wylie, B.K., Pastick, N.J., Picotte, J.J., and Deering, C., 2019, Geospatial data mining for digital raster mapping: GIScience and Remote Sensing, v. 56, no. 3, p. 406-429, https://doi.org/10.1080/15481603.2018.1517445.","productDescription":"14 p.","startPage":"406","endPage":"429","ipdsId":"IP-094736","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499974,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/7c16e86b33fd456cb54a7bd63a3e2985","text":"External Repository"},{"id":358204,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f76e4b0fc368eb53837","contributors":{"authors":[{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":747499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":747500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":747501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Deering, Carol 0000-0003-3565-6264 cdeering@usgs.gov","orcid":"https://orcid.org/0000-0003-3565-6264","contributorId":3001,"corporation":false,"usgs":true,"family":"Deering","given":"Carol","email":"cdeering@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":747502,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70257348,"text":"70257348 - 2019 - Yellowstone convenes science information sharing panel on aquatic invasive species","interactions":[],"lastModifiedDate":"2024-08-15T15:26:35.711851","indexId":"70257348","displayToPublicDate":"2019-04-01T10:23:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3802,"text":"Yellowstone Science","active":true,"publicationSubtype":{"id":10}},"title":"Yellowstone convenes science information sharing panel on aquatic invasive species","docAbstract":"Yellowstone National Park (YNP) supports one of the most significant aquatic ecosystems in the U.S. Headwater streams and rivers emerge from the park and join to become three of America’s most important waterways and ultimately flow into the Pacific and Atlantic oceans: the Yellowstone River, the Missouri River and the Snake River. At the heart of YNP lies Yellowstone Lake – the largest alpine body of water in North America. The park encompasses about 2.25 million acres, five percent of which is covered by water, including more than 220 lakes and 2,650 miles of streams.","language":"English","publisher":"U.S. National Park Service","usgsCitation":"Sepulveda, A., 2019, Yellowstone convenes science information sharing panel on aquatic invasive species: Yellowstone Science, v. 27, no. 1.","productDescription":"1 p.","startPage":"95","ipdsId":"IP-102610","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":432771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":432711,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/articles/news-and-notes-27_1.htm"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.15282532013835,\n 45.12511425934483\n ],\n [\n -111.15282532013835,\n 44.10736308163101\n ],\n [\n -109.84635449345764,\n 44.10736308163101\n ],\n [\n -109.84635449345764,\n 45.12511425934483\n ],\n [\n -111.15282532013835,\n 45.12511425934483\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Adam 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":4187,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":910045,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203004,"text":"70203004 - 2019 - Diverse late‐stage crystallization and storage conditions in melt domains from the Youngest Toba Tuff revealed by age and compositional heterogeneity in the last increment of accessory phase growth","interactions":[],"lastModifiedDate":"2019-08-15T11:55:37","indexId":"70203004","displayToPublicDate":"2019-04-01T10:18:21","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1336,"text":"Contributions to Mineralogy and Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Diverse late‐stage crystallization and storage conditions in melt domains from the Youngest Toba Tuff revealed by age and compositional heterogeneity in the last increment of accessory phase growth","docAbstract":"The chemical record contained within the nal increment of growth on crystals is utilized to reveal the dynamics and time- scales of magma assembly and storage before eruption of the cataclysmic 2800 km3 Youngest Toba Tu (YTT), Indonesia. In situ U–Th disequilibrium dates and trace element concentrations were obtained via secondary ionization mass spectrometry (SIMS) on unsectioned and unpolished faces of individual zircon and allanite crystals. The six high-silica (> 73 wt% SiO2) pumices from which crystals were derived are among the more evolved and lower crystallinity (< 25 wt%) pumices from the YTT eruption, and likely represent the melt-dominated portion of the magma system. Discrete SIMS measurement cycles were coupled with statistical treatments to detect zircon and allanite surface zoning domains at the ~ 1 μm scale. Coupled r-MELTS and accessory phase saturation modeling indicates that at the granite ternary minimum or ‘eutectoid’ conditions that de ne this portion of the YTT, zircon and allanite crystallization is dependent on and proportionate to major phase crystallization, and is more limited than at pre-eutectoid conditions. A lower proportion of near-eruption zircon surface ages in the comparatively cool and wet YTT relative to other hotter and drier voluminous silicic eruptions could re ect the in u- ence of eutectoid storage conditions on magmatic responses to remobilization-related magmatic recharge.","language":"English","publisher":"Springer","doi":"10.1007/s00410-019-1566-6","usgsCitation":"Tierney, C.R., Reid, M.R., Vazquez, J.A., and Chesner, C.A., 2019, Diverse late‐stage crystallization and storage conditions in melt domains from the Youngest Toba Tuff revealed by age and compositional heterogeneity in the last increment of accessory phase growth: Contributions to Mineralogy and Petrology, v. 174, 31, 21 p., https://doi.org/10.1007/s00410-019-1566-6.","productDescription":"31, 21 p.","ipdsId":"IP-106418","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":362910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Youngest Toba Tuff","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 98.41827392578125,\n 2.2324061399778894\n ],\n [\n 99.30816650390625,\n 2.2324061399778894\n ],\n [\n 99.30816650390625,\n 2.981441678317486\n ],\n [\n 98.41827392578125,\n 2.981441678317486\n ],\n [\n 98.41827392578125,\n 2.2324061399778894\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"174","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Tierney, Casey R.","contributorId":214772,"corporation":false,"usgs":false,"family":"Tierney","given":"Casey","email":"","middleInitial":"R.","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":760745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, Mary R.","contributorId":192856,"corporation":false,"usgs":false,"family":"Reid","given":"Mary","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":760746,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":760744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chesner, Craig A.","contributorId":214773,"corporation":false,"usgs":false,"family":"Chesner","given":"Craig","email":"","middleInitial":"A.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":760747,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240305,"text":"70240305 - 2019 - Repatriated desert bighorn sheep population on the Nevada National Security Site","interactions":[],"lastModifiedDate":"2023-02-03T15:50:43.147464","indexId":"70240305","displayToPublicDate":"2019-04-01T09:29:58","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Repatriated desert bighorn sheep population on the Nevada National Security Site","docAbstract":"Ecological studies have been conducted on the Nevada National Security Site (NNSS) since the 1960s. Desert bighorn sheep (Ovis canadensis nelsoni) were considered rare visitors on the NNSS, with only 9 recorded observations between 1963 and 2009, all of which were males. Females and young were not documented definitively until winter 2011, when several were killed by a radiomarked female mountain lion (Puma concolor). Following these observations, we initiated a study of desert bighorn sheep on the NNSS to better understand their movements/interactions with other populations, prevalence of disease, population size, origin, radionuclide burdens and potential radiological dose to humans that may consume harvested animals away from the NNSS. We captured and radiomarked 6 sheep (2 females, 4 males) in November 2015, and 15 (7 females, 8 males) in November 2016. We sampled blood for genetic and disease testing and collected nasal swabs for respiratory disease testing. Sheep from the NNSS spent most of their time around Shoshone Mountain, Fortymile Canyon, and Yucca Mountain but also moved to Bare Mountain, Thirsty Canyon, and Black Mountain. Females greatly expanded their core and overall home ranges during spring, whereas males expanded their home ranges during summer. Of 18 sheep sampled for disease, 12 showed an immune response to Mycoplasma ovipneumoniae, and 5 had the bacteria present. Genetic testing revealed that the ancestry of NNSS sheep is from the Bare Mountain (1991-1995, within 24 km of our study area), Specter Range (1990-1995, within 32 km of our study area), and Stonewall Mountain (1975-1983, within 72 km of our study area) reintroduced populations. Radionuclide burden in NNSS sheep was minimal with no significant difference from sheep captured on the Nevada Test and Training Range and northern Nevada. One marked adult male was legally harvested off the NNSS north of Bare Mountain. This recently colonized reproducing population of sheep on the NNSS warrants further monitoring, protection, and inclusion in resource management plans.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Desert Bighorn Council transactions 2019: A compilation of papers presented at the 55th meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"55th Meeting","conferenceDate":"April 17-19, 2019","conferenceLocation":"Mesquite, Nevada, United States","language":"English","publisher":"Desert Bighorn Council","usgsCitation":"Hall, D., Longshore, K., Lowrey, C., Wehausen, J.D., WIlson-Henjum, G., and Cummings, P., 2019, Repatriated desert bighorn sheep population on the Nevada National Security Site, in Desert Bighorn Council transactions 2019: A compilation of papers presented at the 55th meeting, v. 55, Mesquite, Nevada, United States, April 17-19, 2019, p. 32-53.","productDescription":"22 p.","startPage":"32","endPage":"53","ipdsId":"IP-120326","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":412679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412667,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.desertbighorncouncil.com/transactions/download-past-dbc-transactions/"}],"country":"United States","state":"Nevada","otherGeospatial":"Nevada National Security Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.9584341778068,\n 37.512200103774404\n ],\n [\n -116.9584341778068,\n 36.68193488883483\n ],\n [\n -115.51098544733807,\n 36.68193488883483\n ],\n [\n -115.51098544733807,\n 37.512200103774404\n ],\n [\n -116.9584341778068,\n 37.512200103774404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"55","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":863366,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Hall, Derek","contributorId":302024,"corporation":false,"usgs":false,"family":"Hall","given":"Derek","email":"","affiliations":[{"id":65398,"text":"Mission Support and Test Services, LLC","active":true,"usgs":false}],"preferred":false,"id":863319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowrey, Chris 0000-0001-5084-7275","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":216375,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wehausen, John D.","contributorId":198149,"corporation":false,"usgs":false,"family":"Wehausen","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":863322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"WIlson-Henjum, Grete","contributorId":302025,"corporation":false,"usgs":false,"family":"WIlson-Henjum","given":"Grete","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":863323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cummings, Patrick","contributorId":174650,"corporation":false,"usgs":false,"family":"Cummings","given":"Patrick","email":"","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":863324,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70206865,"text":"70206865 - 2019 - Largemouth bass natural history","interactions":[],"lastModifiedDate":"2019-11-27T09:23:35","indexId":"70206865","displayToPublicDate":"2019-04-01T09:23:03","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Largemouth bass natural history","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Largemouth bass aquaculture","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"5M Publishing","publisherLocation":"Sheffield, UK","isbn":"9781789180480","usgsCitation":"Miranda, L.E., 2019, Largemouth bass natural history, chap. of Largemouth bass aquaculture.","ipdsId":"IP-090185","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":369702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369701,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.5mbooks.com/largemouth-bass-aquaculture.html"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":776100,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203005,"text":"70203005 - 2019 - Upper mantle earth structure in Africa from full-wave ambient noise tomography","interactions":[],"lastModifiedDate":"2019-04-11T11:37:56","indexId":"70203005","displayToPublicDate":"2019-04-01T09:20:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Upper mantle earth structure in Africa from full-wave ambient noise tomography","docAbstract":"Our understanding of the tectonic development of the African continent and the interplay between its geological provinces is hindered by unevenly distributed seismic instrumentation. In order to better understand the continent, we used long-period ambient noise full waveform tomography on data collected from 186 broadband seismic stations throughout Africa and surrounding regions to better image the upper mantle structure. We extracted empirical Green’s functions from ambient seismic noise using a frequency-time normalization method and retrieved coherent signal at periods of 7-340 seconds. We simulated wave propagation through a heterogeneous Earth using a spherical finite-difference approach to obtain synthetic waveforms, measured the misfit as phase delay between the data and synthetics, calculated numerical sensitivity kernels using the scattering integral approach, and iteratively inverted for structure. The resulting images of isotropic, shear wavespeed for the continent reveal segmented, low-velocity upper mantle beneath the highly magmatic northern and eastern sections of the East African Rift System (EARS). In the southern and western sections, high-velocity upper mantle dominates, and distinct, low-velocity anomalies are restricted to regions of current volcanism. At deeper depths, the southern and western EARS transitions to low-velocities. In addition to the EARS, several low-velocity anomalies are scattered through the shallow upper mantle beneath Angola and North Africa, and some of these low-velocity anomalies may be connected to a deeper feature. Distinct upper mantle high-velocity anomalies are imaged throughout the continent and suggest multiple cratonic roots within the Congo region, and possible cratonic roots within the Sahara Metacraton.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GC007804","usgsCitation":"Emry, E.L., Shen, Y., Nyblade, A.A., Flinders, A.F., and Bao, X., 2019, Upper mantle earth structure in Africa from full-wave ambient noise tomography: Geochemistry, Geophysics, Geosystems, v. 20, no. 1, p. 120-147, https://doi.org/10.1029/2018GC007804.","productDescription":"28 p.","startPage":"120","endPage":"147","ipdsId":"IP-102538","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":460423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gc007804","text":"Publisher Index Page"},{"id":362907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -15.820312499999988,\n 26.43122806450644\n ],\n [\n -19.335937499999986,\n 17.644022027872712\n ],\n [\n -15.468749999999986,\n 5.9657536710655235\n ],\n [\n -2.1093749999999862,\n 1.0546279422758869\n ],\n [\n 7.3828125,\n 2.4601811810210052\n ],\n [\n 11.6015625,\n -10.833305983642491\n ],\n [\n 10.8984375,\n -19.31114335506464\n ],\n [\n 13.7109375,\n -27.371767300523032\n ],\n [\n 16.875,\n -34.30714385628803\n ],\n [\n 22.8515625,\n -36.87962060502676\n ],\n [\n 52.03125,\n -27.68352808378776\n ],\n [\n 51.328125,\n 2.8113711933311403\n ],\n [\n 51.67968749999999,\n 12.211180191503997\n ],\n [\n 43.06640625,\n 12.554563528593656\n ],\n [\n 42.01171875,\n 15.623036831528264\n ],\n [\n 36.035156250000014,\n 25.799891182088334\n ],\n [\n 33.046875000000014,\n 31.503629305773003\n ],\n [\n 21.445312500000014,\n 33.43144133557529\n ],\n [\n 19.33593750000001,\n 30.751277776257812\n ],\n [\n 10.371093750000012,\n 37.857507156252\n ],\n [\n -8.78906249999999,\n 35.17380831799956\n ],\n [\n -15.820312499999988,\n 26.43122806450644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Emry, Erica L.","contributorId":214774,"corporation":false,"usgs":false,"family":"Emry","given":"Erica","email":"","middleInitial":"L.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":760749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shen, Yang","contributorId":206754,"corporation":false,"usgs":false,"family":"Shen","given":"Yang","affiliations":[{"id":37391,"text":"University of Rhode Island, Graduate School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":760750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nyblade, Andrew A.","contributorId":214775,"corporation":false,"usgs":false,"family":"Nyblade","given":"Andrew","email":"","middleInitial":"A.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":760751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flinders, Ashton F. 0000-0003-2483-4635 aflinders@usgs.gov","orcid":"https://orcid.org/0000-0003-2483-4635","contributorId":196960,"corporation":false,"usgs":true,"family":"Flinders","given":"Ashton","email":"aflinders@usgs.gov","middleInitial":"F.","affiliations":[{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":760748,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bao, Xueyang","contributorId":214776,"corporation":false,"usgs":false,"family":"Bao","given":"Xueyang","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":760752,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204103,"text":"70204103 - 2019 - Exploring ends of eras in the eastern Mojave Desert: The road log","interactions":[],"lastModifiedDate":"2019-07-09T09:17:31","indexId":"70204103","displayToPublicDate":"2019-04-01T09:13:22","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring ends of eras in the eastern Mojave Desert: The road log","docAbstract":"No abstract available.
","language":"English","publisher":"Desert Symposium Inc.","usgsCitation":"Miller, D., Spaulding, G., Reynolds, R., Calzia, J., Wells, M., Fleck, R.J., and Baltzer, S., 2019, Exploring ends of eras in the eastern Mojave Desert: The road log, p. 7-48.","productDescription":"42 p.","startPage":"7","endPage":"48","ipdsId":"IP-106551","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":365357,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365306,"type":{"id":11,"text":"Document"},"url":"https://www.desertsymposium.org/DS 2019 Ends of Eras for web 4-12 b.pdf"}],"country":"United States","otherGeospatial":"Mojave Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.9789,34.1607 ], [ -117.9789,37.5219 ], [ -114.7254,37.5219 ], [ -114.7254,34.1607 ], [ -117.9789,34.1607 ] ] ] } } ] }","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spaulding, G.A.","contributorId":216784,"corporation":false,"usgs":false,"family":"Spaulding","given":"G.A.","email":"","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":765522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, R.E.","contributorId":205013,"corporation":false,"usgs":false,"family":"Reynolds","given":"R.E.","email":"","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":765523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calzia, James","contributorId":216787,"corporation":false,"usgs":true,"family":"Calzia","given":"James","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wells, M.E.","contributorId":216785,"corporation":false,"usgs":false,"family":"Wells","given":"M.E.","email":"","affiliations":[{"id":39515,"text":"UNLV","active":true,"usgs":false}],"preferred":false,"id":765524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765527,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Baltzer, S.","contributorId":216786,"corporation":false,"usgs":false,"family":"Baltzer","given":"S.","email":"","affiliations":[],"preferred":false,"id":765525,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203198,"text":"70203198 - 2019 - Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps","interactions":[],"lastModifiedDate":"2019-04-29T08:57:06","indexId":"70203198","displayToPublicDate":"2019-04-01T08:56:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps","docAbstract":"Monitoring ichthyoplankton is useful for identifying reproductive fronts and spawning locations of bigheaded carps (Hypophthalmichthys spp.). Unfortunately, sorting and identifying ichthyoplankton to monitor for bigheaded carp reproduction is time consuming and expensive. Traditional methods require frequent egg-larvae sampling, sorting of all samples to obtain presumptively identified bigheaded carp, and genetic validation of presumptively identified eggs. Quantitative PCR (qPCR) has the potential to streamline this process by identifying samples that likely do or do not contain a target species. Our objective was to develop a genetic screening tool using qPCR with the duplex assays SCTM4/5 and BHTM1/2 to prioritize samples that have a higher likelihood of containing bigheaded carp eggs or larvae. We used tandem ichthyoplankton samples collected for monitoring bigheaded carps in the Upper Mississippi, Illinois, and St. Croix rivers to evaluate the effectiveness of qPCR as a screening tool. Samples with > 10,000 copies of DNA had 100% occurrence of bigheaded carp eggs or larvae in the traditionally sorted samples, whereas samples with < 10 copies of DNA had 0% occurrence of ichthyoplankton from these invasive species. We used a logistic regression model to calculate the probability of finding bigheaded carp eggs or larvae based upon the number of DNA copies; 406 copies corresponded with a 50% probability of having bigheaded carp ichthyoplankton present in a sample. These data can be used to inform management actions (i.e., control, containment) for these invasive fishes, and this tool could be adapted for monitoring for reproduction of other aquatic invasive species.","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1887-9","usgsCitation":"Fritts, A.K., Knights, B.C., Larson, J.H., Amberg, J., Merkes, C.M., Tajjioui, T., Butler, S.E., Diana, M.J., Wahl, D.H., Weber, M.J., and Waters, J.D., 2019, Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps: Biological Invasions, v. 21, no. 4, p. 1143-1153, https://doi.org/10.1007/s10530-018-1887-9.","productDescription":"11 p.","startPage":"1143","endPage":"1153","ipdsId":"IP-100744","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":467750,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tajjioui, Tariq 0000-0002-0113-0451","orcid":"https://orcid.org/0000-0002-0113-0451","contributorId":215091,"corporation":false,"usgs":true,"family":"Tajjioui","given":"Tariq","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":761606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Butler, Steven E.","contributorId":206527,"corporation":false,"usgs":false,"family":"Butler","given":"Steven","email":"","middleInitial":"E.","affiliations":[{"id":37336,"text":"Illinois 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0000-0003-0430-3087","orcid":"https://orcid.org/0000-0003-0430-3087","contributorId":210835,"corporation":false,"usgs":false,"family":"Weber","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":761610,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Waters, John D.","contributorId":215092,"corporation":false,"usgs":false,"family":"Waters","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":6964,"text":"Minnesota Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":761611,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70206560,"text":"70206560 - 2019 - A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns","interactions":[],"lastModifiedDate":"2019-11-08T08:55:07","indexId":"70206560","displayToPublicDate":"2019-04-01T08:50:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5841,"text":"Applied Sciences","onlineIssn":"2076-3417","active":true,"publicationSubtype":{"id":10}},"title":"A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns","docAbstract":"Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r2) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was <20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.
","language":"English","publisher":"MDPI","doi":"10.3390/app9071368","usgsCitation":"Wilkinson, J.W., Boxall, A., and Kolpin, D., 2019, A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns: Applied Sciences, v. 9, no. 7, 1368, 14 p., https://doi.org/10.3390/app9071368.","productDescription":"1368, 14 p.","ipdsId":"IP-106171","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/app9071368","text":"Publisher Index Page"},{"id":369080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilkinson, John W.","contributorId":147014,"corporation":false,"usgs":false,"family":"Wilkinson","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":774939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boxall, Alistair","contributorId":152697,"corporation":false,"usgs":false,"family":"Boxall","given":"Alistair","affiliations":[],"preferred":false,"id":774940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana 0000-0002-3529-6506","orcid":"https://orcid.org/0000-0002-3529-6506","contributorId":220448,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774938,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70210142,"text":"70210142 - 2019 - Increased nesting success of Hawaii Elepaio in response to the removal of invasive black rats","interactions":[],"lastModifiedDate":"2020-05-15T13:45:50.949288","indexId":"70210142","displayToPublicDate":"2019-04-01T08:39:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Increased nesting success of Hawaii Elepaio in response to the removal of invasive black rats","docAbstract":"In Hawaii and other oceanic islands with few native land mammals, black rats (Rattus rattus) are among the most damaging invasive vertebrate species to native forest bird populations and habitats, due to their arboreal behavior and generalist foraging habits and habitat use. We evaluated the nesting response of Hawaii Elepaio (Chasiempis sandwichensis; Monarchidae), a generalist insectivore, to the removal of black rats using rodenticide in a before-after-control-impact study in high- and low-elevation mesic montane habitat recovering from long-term damage from introduced ungulates and weeds. We monitored nesting success and rat abundance during 2015–2016 before applying rodenticide bait in 2017 to remove rats from two 700 × 700 m treatment plots that were paired with 2 nontreatment plots of the same size. Rat abundance was reduced by 90% during treatment, with combined variables treatment and elevation best explaining the change using GLM methods and AIC model selection. The daily survival rate (DSR) of nests (n = 191) was greater on treated plots after rodenticide application (mean ± SE = 0.980 ± 0.004 treatment; 0.964 ± 0.004 nontreatment), modeled nest success increased from 29% to 50%, and apparent nest success (number of successful nests per total nests) increased from 37% to 52%. The most informative model for predicting DSR included the effect of treatment. Predation by rats was documented at 3 of 16 nests using video surveillance, and we observed additional evidence of rat predation during in-person nest monitoring. Rats targeted adults on the nest and sometimes removed intact eggs, leaving little trace of their activity. Our results demonstrate that reducing rat predation can immediately improve the nesting success of even a common bird species in habitat with a long history of forest restoration. Sustained predator control may be critical to accelerating the recovery of native forest bird communities.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duz003","collaboration":"","usgsCitation":"Banko, P.C., Jaenecke, K., Peck, R., and Brinck, K.W., 2019, Increased nesting success of Hawaii Elepaio in response to the removal of invasive black rats: Condor, v. 121, no. 2, duz003, 12 p., https://doi.org/10.1093/condor/duz003.","productDescription":"duz003, 12 p.","ipdsId":"IP-080105","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":467752,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duz003","text":"Publisher Index Page"},{"id":437519,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93TOM58","text":"USGS data release","linkHelpText":"Hawaii Volcanoes National Park Elepaio nest monitoring and black rat mark recapture data 2015-2017"},{"id":374869,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.46728515625,\n 18.87510275035649\n ],\n [\n -154.75341796875,\n 18.87510275035649\n ],\n [\n -154.75341796875,\n 20.365227537412434\n ],\n [\n -156.46728515625,\n 20.365227537412434\n ],\n [\n -156.46728515625,\n 18.87510275035649\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":789282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaenecke, Kelly 0000-0002-7124-4788","orcid":"https://orcid.org/0000-0002-7124-4788","contributorId":211063,"corporation":false,"usgs":false,"family":"Jaenecke","given":"Kelly","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":789283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peck, Robert W. 0000-0002-8739-9493","orcid":"https://orcid.org/0000-0002-8739-9493","contributorId":193088,"corporation":false,"usgs":false,"family":"Peck","given":"Robert W.","affiliations":[],"preferred":false,"id":789284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":150936,"corporation":false,"usgs":false,"family":"Brinck","given":"Kevin","email":"kbrinck@usgs.gov","middleInitial":"W.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":789285,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70203203,"text":"70203203 - 2019 - Consequences of ignoring spatial variation in population trend when conducting a power analysis","interactions":[],"lastModifiedDate":"2019-04-29T08:39:06","indexId":"70203203","displayToPublicDate":"2019-04-01T08:38:43","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of ignoring spatial variation in population trend when conducting a power analysis","docAbstract":"Long-term, large-scale monitoring programs are becoming increasingly common to document status and trends of wild populations. A successful program for monitoring population trend hinges on the ability to detect the trend of interest. Power analyses are useful for quantifying the sample size needed for trend detection, given expected variation in the population. Four components of variation (within-year variation at a given site, interannual variation within a site, variation among sites in the interannual variation, and variation among sites in mean abundance or density) are commonly considered in power analyses for population trend, but a fifth is not: variation among sites in the local trend. Spatial variation in trend is expected to reduce statistical power, but the magnitude of this reduction has not been fully explored. We used computer simulations to evaluate the consequences of ignoring spatial variation in trend under a variety of sampling designs and wide ranges of other components of variation. The effect of spatial variation in trend on power was minor when other input parameters took extreme values that made the trend either very difficult or very easy to detect. However, at moderate values of the other parameters, spatial variation in trend had a strong effect, reducing statistical power by up to 60%. In some cases, ignoring spatial variation in trend resulted in an 80% probability of a Type I error (falsely detecting a trend in a stable population). Spatial variation in trend is therefore an important consideration when designing a long-term monitoring program for many species, especially those affected by local conditions at sites that are repeatedly surveyed. If variation in trend is ignored, as in most previous power analyses, the recommended sampling design will likely be insufficient to detect the trend of interest and lead to potentially false conclusions of a stable population.","language":"English","publisher":"Wiley-Blackwell","doi":"10.1111/ecog.04093","usgsCitation":"Weiser, E.L., Diffendorfer, J., Lopez-Hoffman, L., Semmens, D.J., and Thogmartin, W.E., 2019, Consequences of ignoring spatial variation in population trend when conducting a power analysis: Ecography, v. 42, no. 4, p. 836-844, https://doi.org/10.1111/ecog.04093.","productDescription":"9 p.","startPage":"836","endPage":"844","ipdsId":"IP-091066","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437520,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SFUH2K","text":"USGS data release","linkHelpText":"Power analysis code"},{"id":363285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":213770,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":761631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":761632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez-Hoffman, Laura","contributorId":149127,"corporation":false,"usgs":false,"family":"Lopez-Hoffman","given":"Laura","affiliations":[{"id":17654,"text":"School of Natural Resources & the Environment and Udall Center for Studies in Public Policy, The University of Arizona, Tucson","active":true,"usgs":false}],"preferred":false,"id":761633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":761634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":761635,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204642,"text":"70204642 - 2019 - Lead in piscivorous raptors during breeding season in the Chesapeake Bay region of Maryland and Virginia, USA","interactions":[],"lastModifiedDate":"2019-08-12T11:43:39","indexId":"70204642","displayToPublicDate":"2019-04-01T08:32:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Lead in piscivorous raptors during breeding season in the Chesapeake Bay region of Maryland and Virginia, USA","docAbstract":"Sources of lead exposure of many bird species are poorly understood. We analyzed blood lead concentrations from osprey (n = 244; Pandion haliaetus) and bald eagles (n = 68; Haliaeetus leucocephalus) and documented potential sources of lead they may encounter. Adult bald eagles had higher blood lead concentrations than did adult osprey. However, blood lead concentrations of nestlings were similar for both species. Although 62% of osprey had detectable lead concentrations (x ̅ = 1.99 µg/dL ± 4.02; mean; ± SD), there was no difference in the detection frequency or lead concentrations between osprey adults and nestlings. Likewise, we found no differences in the detection frequency or lead concentrations in osprey adults and nestlings from high and low salinity areas. Of the bald eagle samples tested, 55% had detectable lead levels (x ̅ = 6.23 µg/dL ± 10.74). Adult bald eagles had more detectable and higher lead concentrations than did nestlings or pre-adults. Among environmental samples, paint had the highest lead concentrations, followed by sediment, blue catfish (Ictalurus furcatus), and gizzard shad (Dorosoma cepedianum). There was no correlation between blood lead concentrations of osprey adults and their offspring. Our work indicates that, in the Chesapeake Bay region, there are multiple sources by which piscivorous raptors may be exposed to lead.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4376","usgsCitation":"Slabe, V.A., Anderson, J.T., Cooper, J., Brown, B., Ortiz, P., Buchweitz, J., McRuer, D., and Katzner, T., 2019, Lead in piscivorous raptors during breeding season in the Chesapeake Bay region of Maryland and Virginia, USA: Environmental Toxicology and Chemistry, v. 38, no. 4, p. 862-871, https://doi.org/10.1002/etc.4376.","productDescription":"10 p.","startPage":"862","endPage":"871","ipdsId":"IP-102514","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366362,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.32177734375,\n 36.89719446989036\n ],\n [\n -75.16845703124999,\n 36.89719446989036\n ],\n [\n -75.16845703124999,\n 39.52099229357195\n ],\n [\n -77.32177734375,\n 39.52099229357195\n ],\n [\n -77.32177734375,\n 36.89719446989036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Slabe, Vincent A.","contributorId":213764,"corporation":false,"usgs":false,"family":"Slabe","given":"Vincent","email":"","middleInitial":"A.","affiliations":[{"id":38849,"text":"West VA University","active":true,"usgs":false}],"preferred":false,"id":767881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":767882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cooper, Jeff","contributorId":199741,"corporation":false,"usgs":false,"family":"Cooper","given":"Jeff","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":767883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Bracken","contributorId":217945,"corporation":false,"usgs":false,"family":"Brown","given":"Bracken","email":"","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":767884,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ortiz, Patricia 0000-0003-3067-7904","orcid":"https://orcid.org/0000-0003-3067-7904","contributorId":217946,"corporation":false,"usgs":true,"family":"Ortiz","given":"Patricia","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767885,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Buchweitz, John","contributorId":217947,"corporation":false,"usgs":false,"family":"Buchweitz","given":"John","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":767886,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McRuer, Dave","contributorId":217948,"corporation":false,"usgs":false,"family":"McRuer","given":"Dave","affiliations":[{"id":37079,"text":"Wildlife Center of Virginia","active":true,"usgs":false}],"preferred":false,"id":767887,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767880,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203136,"text":"70203136 - 2019 - AVO-G2S: A modified, open-source Ground-to-Space atmospheric specification for infrasound modeling","interactions":[],"lastModifiedDate":"2019-04-24T08:16:39","indexId":"70203136","displayToPublicDate":"2019-04-01T08:16:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"AVO-G2S: A modified, open-source Ground-to-Space atmospheric specification for infrasound modeling","docAbstract":"To facilitate infrasound propagation studies, we present AVO-G2S, an open-source, Ground-to-Space model which provides temperature and wind specifications from the surface to an altitude of 225 km. This model provides a means of smoothly characterizing atmospheric conditions using multiple numerical weather prediction forecast and reanalysis products, along with upper-atmospheric empirical models. Regional atmospheric reconstructions only require a limited domain and can utilize high-resolution numerical weather prediction forecasts typically provided\non a projected grid. The use of a projected grid allows for faster spectral transform libraries to be\nemployed. The AVO-G2S software can also provide global reconstructions that rely on global\nnumerical weather prediction products and spherical harmonic decompositions. AVO-G2S is inspired by a global Ground-to-Space model developed by the Naval Research Laboratory, and relies on their empirical descriptions of upper-atmospheric conditions. Alaska Volcano Observatory has implemented this model for near-real-time infrasound monitoring of volcanic eruptions and historical research projects.","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2018.12.013","usgsCitation":"Schwaiger, H., Iezzi, A., and Fee, D., 2019, AVO-G2S: A modified, open-source Ground-to-Space atmospheric specification for infrasound modeling: Computers & Geosciences, v. 125, p. 90-97, https://doi.org/10.1016/j.cageo.2018.12.013.","productDescription":"8 p.","startPage":"90","endPage":"97","ipdsId":"IP-091624","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.cageo.2018.12.013","text":"Publisher Index Page"},{"id":363165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schwaiger, Hans 0000-0001-7397-8833","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":214983,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":761353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":761354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fee, David","contributorId":199660,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[],"preferred":false,"id":761355,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204653,"text":"70204653 - 2019 - Assessing seasonal changes in microgravity at Yellowstone caldera","interactions":[],"lastModifiedDate":"2019-08-09T10:45:59","indexId":"70204653","displayToPublicDate":"2019-04-01T07:51:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessing seasonal changes in microgravity at Yellowstone caldera","docAbstract":"Microgravity time series at active volcanoes can provide an indication of mass change related to subsurface magmatic processes, but uncertainty is often introduced by hydrologic variations and other noise sources that cannot easily be isolated. We empirically assessed seasonality and noise by conducting four surveys over the course of May-October 2017 at Yellowstone caldera, Wyoming. Yellowstone experiences frequent changes in the rates and styles of seismicity and surface deformation, but the mechanisms of these changes are poorly understood because the characteristics of the driving fluids are not clear. Past gravity data from the caldera have yielded ambiguous results, possibly due to hydrologic noise. Given the strong visually observable changes in surface water and snow conditions over the course of our surveys, we expected to see significant variations in gravity. The net change in gravity, however, was less than 20 µGal at most sites, and there was no strong correlation with river and lake levels or snow conditions. Seasonal changes in gravity are therefore small compared to those that would be expected from magmatic activity, although they may be on the same order as those associated with Yellowstone’s hydrothermal system. We did find that noise levels in gravity data were highly dependent on site characteristics, with bedrock sites away from trees yielding the lowest levels of noise, and thin concrete pads in forested areas the highest. These results can be used to plan future surveys at Yellowstone and to reinterpret past data, and they provide guidance in terms of best practices for repeat gravity work on volcanoes worldwide.","language":"English","publisher":"Wiley","doi":"10.1029/2018JB017061","usgsCitation":"Poland, M.P., and de Zeeuw-van Dalfsen, E., 2019, Assessing seasonal changes in microgravity at Yellowstone caldera: Journal of Geophysical Research, v. 124, no. 4, p. 4174-4188, https://doi.org/10.1029/2018JB017061.","productDescription":"15 p.","startPage":"4174","endPage":"4188","ipdsId":"IP-103468","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jb017061","text":"Publisher Index Page"},{"id":366351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.28051757812499,\n 43.79488907226601\n ],\n [\n -109.3304443359375,\n 43.79488907226601\n ],\n [\n -109.3304443359375,\n 45.14717913418674\n ],\n [\n -111.28051757812499,\n 45.14717913418674\n ],\n [\n -111.28051757812499,\n 43.79488907226601\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"124","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":767930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":767931,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70203230,"text":"70203230 - 2019 - Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2019-05-02T08:07:59","indexId":"70203230","displayToPublicDate":"2019-04-01T07:46:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region","docAbstract":"Understanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota.