While microbiome research is a rapidly expanding field of study, relatively little is known of the microbiomes associated with Foraminifera. This preliminary study investigated microbes associated with four species of Foraminifera, representing two taxonomic orders, which host three kinds of algal endosymbionts. A major objective was to explore potential influences on the microbiome composition, including phylogenetic relatedness among the host species, similarities in algal symbionts hosted, and environmental conditions from which the specimens were collected. Samples examined from two locations along the middle Florida Keys reef tract included 45 foraminiferal specimens and four environmental samples. Bacterial DNA extraction from individual specimens was followed by amplification and amplicon sequencing of the V4 variable region of the 16S rRNA gene; results were obtained from 21 specimens.
The Order Miliolida, Family Soritidae, was represented by 5–8 specimens of each of three species: Archaias angulatus and Cyclorbiculina compressa, which both host chlorophyte symbionts, and Sorites orbiculus, which hosts dinoflagellate symbionts. Three Ar. angulatus specimens from which the microbiome was successfully sequenced shared 177 OTUs. Six C. compressa specimens successfully sequenced shared 58 OTUs, of which 31 were also shared by the three specimens of Ar. angulatus. Four successfully sequenced S. orbiculus specimens shared 717 unique OTUs. The 13 soritid specimens shared 26 OTUs, 23 of which represented Proteobacteria, predominantly of the bacterial family Rhodobacteraceae.
The fourth foraminiferal species, Amphistegina gibbosa (Order Rotaliida) hosts diatom endosymbionts. Bacterial DNA extraction was attempted on 16 Am. gibbosa, including both normal-appearing and partly-bleached specimens. Only six OTUs, four of which represented Proteobacteria, were found in all eight specimens successfully sequenced. The partly bleached specimens shared nearly twice as many unique microbial OTUs (32) as the normal-appearing specimens (19). All Am. gibbosa specimens shared only four microbial OTUs with the soritid species, three of which may have been contaminants, indicating minimal commonality between the microbiomes of Am. gibbosa and the soritid taxa.
","language":"English","publisher":"Cushman Foundation for Foraminiferal Research","doi":"10.2113/gsjfr.49.2.178","usgsCitation":"Martin, M.M., Kellogg, C.A., and Hallock, P., 2019, Microbial associations of four species of algal symbiont-bearing Foraminifers from the Florida Reef Tract, USA: Journal of Foraminiferal Research, v. 49, no. 2, p. 178-190, https://doi.org/10.2113/gsjfr.49.2.178.","productDescription":"13 p.","startPage":"178","endPage":"190","ipdsId":"IP-097807","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":363561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.04290771484374,\n 24.492147541216028\n ],\n [\n -80.15625,\n 24.492147541216028\n ],\n [\n -80.15625,\n 25.535006795752302\n ],\n [\n -83.04290771484374,\n 25.535006795752302\n ],\n [\n -83.04290771484374,\n 24.492147541216028\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Makenna M.","contributorId":215415,"corporation":false,"usgs":false,"family":"Martin","given":"Makenna","email":"","middleInitial":"M.","affiliations":[{"id":39241,"text":"College of Marine Science, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":762267,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":762266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hallock, Pamela 0000-0002-1813-0482","orcid":"https://orcid.org/0000-0002-1813-0482","contributorId":215416,"corporation":false,"usgs":false,"family":"Hallock","given":"Pamela","email":"","affiliations":[{"id":39241,"text":"College of Marine Science, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":762268,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202948,"text":"70202948 - 2019 - The contribution of road-based citizen science to the conservation of pond-breeding amphibians","interactions":[],"lastModifiedDate":"2019-04-08T15:24:14","indexId":"70202948","displayToPublicDate":"2019-04-01T12:15:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The contribution of road-based citizen science to the conservation of pond-breeding amphibians","docAbstract":"Roadside amphibian citizen science (CS) programmes bring together volunteers focused on collecting scientific data while working to mitigate population declines by reducing road mortality of pond‐breeding amphibians. Despite the international popularity of these movement‐based, roadside conservation efforts (i.e. “big nights,” “bucket brigades” and “toad patrols”), direct benefits to conservation have rarely been quantified or evaluated.
As a case study, we used a population simulation approach to evaluate how volunteer intensity, frequency and distribution influence three conservation outcomes (minimum population size, population growth rate and years to extinction) of the spotted salamander (Ambystoma maculatum), often a focal pond‐breeding amphibian of CS and conservation programmes in the United States.
Sensitivity analysis supported the expectation that spotted salamander populations were primarily recruitment‐driven. Thus, conservation outcomes were highest when volunteers focused on metamorph outmigration as opposed to adult in‐migration—contrary to the typical timing of such volunteer events.
Almost every volunteer strategy resulted in increased conservation outcomes compared to a no‐volunteer strategy. Specifically, volunteer frequency during metamorph migration increased outcomes more than the same increases in volunteer effort during adult migration. Small population sizes resulted in a negligible effect of volunteer intensity. Volunteers during the first adult in‐migration had a relatively small effect compared to most other strategies.
Synthesis and applications. Although citizen science (CS)‐focused conservation actions could directly benefit declining populations, additional conservation measures are needed to halt or reverse local amphibian declines. This study demonstrates a need to evaluate the effectiveness of focusing CS mitigation efforts on the metamorph stage, as opposed to the adult stage. This may be challenging, compared to other management actions such as road‐crossing infrastructure. Current amphibian CS programmes will be challenged to balance implementing evidence‐based conservation measures on the most limiting life stage, while retaining social and community benefits for volunteers.
In 2017, we investigated a mortality event of muskrat (Ondatra zibethicus) in Northwest Ohio, USA, and determined the causes of death to be from Tyzzer's disease due to Clostridium piliforme and Klebsiella pneumoniae septicemia. The gross presentation resembled tularemia, which highlighted the importance of a complete diagnostic investigation.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-11-267","usgsCitation":"Grear, D.A., Lankton, J.S., Zaleski, S., Witt, M., and Lorch, J.M., 2019, Mortality due to Tyzzer's disease of muskrats in northern Ohio, USA: Journal of Wildlife Diseases, v. 55, no. 4, p. 982-985, https://doi.org/10.7589/2018-11-267.","productDescription":"4 p.","startPage":"982","endPage":"985","ipdsId":"IP-105259","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":460419,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/2018-11-267","text":"Publisher Index Page"},{"id":362833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.08736801147461,\n 41.51693249137831\n ],\n [\n -82.9742431640625,\n 41.51693249137831\n ],\n [\n -82.9742431640625,\n 41.57975468033126\n ],\n [\n -83.08736801147461,\n 41.57975468033126\n ],\n [\n -83.08736801147461,\n 41.51693249137831\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"4","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":760561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":760562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zaleski, Sara","contributorId":214687,"corporation":false,"usgs":false,"family":"Zaleski","given":"Sara","email":"","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":760563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Witt, Mark","contributorId":214690,"corporation":false,"usgs":false,"family":"Witt","given":"Mark","email":"","affiliations":[],"preferred":false,"id":760564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":760565,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203428,"text":"70203428 - 2019 - Offshore landslide hazard curves from mapped landslide size distributions","interactions":[],"lastModifiedDate":"2019-06-18T12:05:49","indexId":"70203428","displayToPublicDate":"2019-04-01T12:06:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Offshore landslide hazard curves from mapped landslide size distributions","docAbstract":"We present a method to calculate landslide hazard curves along offshore margins based on size distributions of submarine landslides. The method analyzes ten different continental margins, that were mapped by high-resolution multibeam sonar with landslide scar areas measured by a consistent GIS procedure. Statistical tests of several different probability distribution models indicate that the lognormal model is most appropriate for these siliciclastic environments, consistent with an earlier study of the U.S. Atlantic margin [Chaytor et al., 2009]. Parameter estimation is performed using the maximum likelihood technique and confidence intervals are determined using likelihood profiles. Pairwise comparison of size distributions for the ten margins indicates that the U.S. Atlantic and Queen Charlotte margins are different than most other margins. These margins represent end members, with the U.S. Atlantic margin having the highest mean scar area and the Queen Charlotte margin, the lowest. We demonstrate that empirical, offshore landslide hazard curves can be developed from the landslide size distributions, if the duration of mapped landslide activity is known. This study indicates that the shape parameter of the size distribution is similar among all ten margins and thus the shape of the hazard curves is also similar. Significant differences in hazard curves among the margins are therefore related to differences in mean sizes and, potentially, differences in the duration of landslide activity.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JB017236","usgsCitation":"Geist, E.L., and ten Brink, U., 2019, Offshore landslide hazard curves from mapped landslide size distributions: Journal of Geophysical Research B: Solid Earth, v. 124, no. 4, p. 3320-3334, https://doi.org/10.1029/2018JB017236.","productDescription":"15 p.","startPage":"3320","endPage":"3334","ipdsId":"IP-103389","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":460421,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/24319","text":"External Repository"},{"id":363766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"124","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":762670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":762671,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204926,"text":"70204926 - 2019 - Pheno forecasts predict seasonal activity of pest and invasive species to support decision making","interactions":[],"lastModifiedDate":"2019-08-23T12:06:45","indexId":"70204926","displayToPublicDate":"2019-04-01T12:03:54","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Pheno forecasts predict seasonal activity of pest and invasive species to support decision making","docAbstract":"The USA National Phenology Network’s Pheno Forecast maps indicate the status of insect pest or invasive plant life cycle stages in real time across the contiguous United States. This information can guide when to monitor or to undertake management activities. These maps, available at 2.5 km spatial resolution, are updated daily and are available six days into the future. Pheno Forecast maps are now available for 12 insect pest species and for one invasive grass species.","language":"English","publisher":"University of Arizona","collaboration":"University of Arizona","usgsCitation":"Crimmins, T.M., Gerst, K.L., Posthumus, E.E., Rosemartin, A., and Weltzin, J., 2019, Pheno forecasts predict seasonal activity of pest and invasive species to support decision making, 2 p.","productDescription":"2 p.","ipdsId":"IP-108796","costCenters":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":366864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366841,"type":{"id":15,"text":"Index Page"},"url":"https://www.usanpn.org/files/npn/reports/USA-NPN_PhenoForecast_InfoSheet_v2_2019.pdf"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crimmins, Theresa M.","contributorId":178236,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerst, Katharine L.","contributorId":175227,"corporation":false,"usgs":false,"family":"Gerst","given":"Katharine","email":"","middleInitial":"L.","affiliations":[{"id":27543,"text":"National Phenology Network, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":769051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Posthumus, Erin E. 0000-0003-3855-2380","orcid":"https://orcid.org/0000-0003-3855-2380","contributorId":204418,"corporation":false,"usgs":false,"family":"Posthumus","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":40537,"text":"USA National Phenology Network, National Coordinating Office; University of Arizona, School of Natural Resources and the Environment","active":true,"usgs":false}],"preferred":false,"id":769052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosemartin, Alyssa","contributorId":175226,"corporation":false,"usgs":false,"family":"Rosemartin","given":"Alyssa","affiliations":[],"preferred":false,"id":769053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weltzin, Jake 0000-0001-8641-6645 jweltzin@usgs.gov","orcid":"https://orcid.org/0000-0001-8641-6645","contributorId":196323,"corporation":false,"usgs":true,"family":"Weltzin","given":"Jake","email":"jweltzin@usgs.gov","affiliations":[{"id":433,"text":"National Phenology Network","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":769049,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202797,"text":"ofr20191031 - 2019 - Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide","interactions":[],"lastModifiedDate":"2019-04-05T14:49:39","indexId":"ofr20191031","displayToPublicDate":"2019-04-01T12:03:46","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1031","displayTitle":"Life-History Model for Sockeye Salmon (Oncorhynchus nerka) at Lake Ozette, Northwestern Washington—Users’ Guide","title":"Life-history model for sockeye salmon (Oncorhynchus nerka) at Lake Ozette, northwestern Washington—Users' guide","docAbstract":"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.
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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 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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. These results indicate that cisco density is very low at the lake level.","conferenceTitle":"Great Lakes Fishery Commission, Lake Michigan Committee Meeting","conferenceDate":"March 25, 2019","conferenceLocation":"Ypsilanti, MI","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Warner, D., Phillips, K., Turschak, B., Hanson, D., and Smith, J., 2019, Status of pelagic prey fishes in Lake Michigan, 2018, Great Lakes Fishery Commission, Lake Michigan Committee Meeting, Ypsilanti, MI, March 25, 2019, 15 p.","productDescription":"15 p.","ipdsId":"IP-106761","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":385127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":385126,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/lake-michigan-committee.php"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n 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Center","active":true,"usgs":true}],"preferred":true,"id":813136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Kristy","contributorId":256722,"corporation":false,"usgs":false,"family":"Phillips","given":"Kristy","affiliations":[],"preferred":false,"id":813137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turschak, Ben","contributorId":257454,"corporation":false,"usgs":false,"family":"Turschak","given":"Ben","email":"","affiliations":[],"preferred":false,"id":814304,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Dale","contributorId":190498,"corporation":false,"usgs":false,"family":"Hanson","given":"Dale","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":814305,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Jason","contributorId":215444,"corporation":false,"usgs":false,"family":"Smith","given":"Jason","affiliations":[{"id":39249,"text":"Little Traverse Band of Odawa Indians","active":true,"usgs":false}],"preferred":false,"id":814306,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199964,"text":"70199964 - 2019 - Geospatial data mining for digital raster mapping","interactions":[],"lastModifiedDate":"2024-05-17T15:09:45.727773","indexId":"70199964","displayToPublicDate":"2019-04-01T10:38:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Geospatial data mining for digital raster mapping","docAbstract":"We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters 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":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}],"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":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"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":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":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","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":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":153,"text":"California Volcano Observatory","active":false,"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":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, 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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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.
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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}]}} ]}