{"pageNumber":"335","pageRowStart":"8350","pageSize":"25","recordCount":40783,"records":[{"id":70203314,"text":"70203314 - 2019 - Methane emissions from groundwater pumping in the USA","interactions":[],"lastModifiedDate":"2019-08-15T12:05:17","indexId":"70203314","displayToPublicDate":"2019-03-25T09:33:16","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5831,"text":"Climate and Atmospheric Science","active":true,"publicationSubtype":{"id":10}},"title":"Methane emissions from groundwater pumping in the USA","docAbstract":"Atmospheric methane accumulation contributes to climate change, hence quantifying methane emissions is essential to assess and model the impacts. Here we estimate methane emissions from groundwater pumping in the Los Angeles Basin (LAB), north-eastern Pennsylvania, and the Principal aquifers of the USA using the average concentrations of methane in groundwater and annual groundwater pumping volumes. High average methane concentrations, 44.1 mg/L, and extensive groundwater pumping, ~3.1 x 1011 L/a in the LAB, result in the annual emission of ~2.9 x 10-3 Tg of microbial methane. Ethane emissions in the LAB were 3.5 x 10-6 Tg/a. Lower methane emissions estimated for NE Pennsylvania, ~3.0 x 10-8 Tg/a, reflect lower methane concentrations and groundwater pumping, 0.7 mg/L and 4.67 x 107 L/a, respectively. Methane concentrations and groundwater withdrawals, 1.06 x 1014 L, across the USA enabled the estimation of the total emissions of methane from Principal aquifers (92% of total pumping) of 0.044 Tg/a in the year 2000, which represents a small percentage (~0.2%) of the total annual US methane emissions, but a previously unquantified flux in the global methane budget. Globally, groundwater-pumping methane emissions were estimated to be 0.53 Tg/a, 0.2% of global methane emissions, by adopting a global estimate for groundwater extraction, and an average methane concentration in older groundwater of 0.44 mg/L.","language":"English","publisher":"Nature","doi":"10.1038/s41612-019-0068-6","usgsCitation":"Kulongoski, J.T., and McMahon, P.B., 2019, Methane emissions from groundwater pumping in the USA: Climate and Atmospheric Science, v. 2, p. 1-8, https://doi.org/10.1038/s41612-019-0068-6.","productDescription":"11, 8 p.","startPage":"1","endPage":"8","ipdsId":"IP-094126","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":467779,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41612-019-0068-6","text":"Publisher Index 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kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":762103,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197235,"text":"70197235 - 2019 - Prediction of unprecedented biological shifts in the global ocean","interactions":[],"lastModifiedDate":"2019-08-13T14:41:55","indexId":"70197235","displayToPublicDate":"2019-03-25T00:00:00","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Prediction of unprecedented biological shifts in the global ocean","docAbstract":"

Impermanence is an ecological principle1 but there are times when changes occur nonlinearly as abrupt community shifts (ACSs) that transform the ecosystem state and the goods and services it provides2. Here, we present a model based on niche theory3 to explain and predict ACSs at the global scale. We test our model using 14 multi-decadal time series of marine metazoans from zooplankton to fish, spanning all latitudes and the shelf to the open ocean. Predicted and observed fluctuations correspond, with both identifying ACSs at the end of the 1980s4,5,6,7 and 1990s5,8. We show that these ACSs coincide with changes in climate that alter local thermal regimes, which in turn interact with the thermal niche of species to trigger long-term and sometimes abrupt shifts at the community level. A large-scale ACS is predicted after 2014—unprecedented in magnitude and extent—coinciding with a strong El Niño event and major shifts in Northern Hemisphere climate. Our results underline the sensitivity of the Arctic Ocean, where unprecedented melting may reorganize biological communities5,9, and suggest an increase in the size and consequences of ACS events in a warming world.

","language":"English","publisher":"Nature","doi":"10.1038/s41558-019-0420-1","usgsCitation":"Beaugrand, G., Conversi, A., Atkinson, A., Cloern, J., Chiba, S., Fonda-Umani, S., Kirby, R., Greene, C., Goberville, E., Otto, S., Reid, P., Stemmann, L., and Edwards, M., 2019, Prediction of unprecedented biological shifts in the global ocean: Nature Climate Change, v. 9, p. 237-243, https://doi.org/10.1038/s41558-019-0420-1.","productDescription":"7 p.","startPage":"237","endPage":"243","ipdsId":"IP-085095","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":467781,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hal.sorbonne-universite.fr/hal-02189417","text":"External Repository"},{"id":354481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Beaugrand, G.","contributorId":205183,"corporation":false,"usgs":false,"family":"Beaugrand","given":"G.","email":"","affiliations":[{"id":37043,"text":"Centre National de la Recherche Scientifique, Laboratoire d’Océanologie et de Géosciences’ UMR LOG CNRS 8187, Station Marine, Université des Sciences et Technologies de Lille 1 - Lille 1 BP 80, 62930 Wimereux, France","active":true,"usgs":false}],"preferred":false,"id":736310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conversi, A.","contributorId":205184,"corporation":false,"usgs":false,"family":"Conversi","given":"A.","email":"","affiliations":[{"id":37044,"text":"Marine Institute, Plymouth University, Plymouth, PL4 8AA, UK","active":true,"usgs":false}],"preferred":false,"id":736311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, A.","contributorId":205185,"corporation":false,"usgs":false,"family":"Atkinson","given":"A.","email":"","affiliations":[{"id":37045,"text":"Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL13DH, UK","active":true,"usgs":false}],"preferred":false,"id":736312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cloern, James","contributorId":26181,"corporation":false,"usgs":true,"family":"Cloern","given":"James","affiliations":[],"preferred":false,"id":736309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiba, S.","contributorId":205186,"corporation":false,"usgs":false,"family":"Chiba","given":"S.","email":"","affiliations":[{"id":37046,"text":"RCGC, JAMSTEC, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, 236-0001 Japan","active":true,"usgs":false}],"preferred":false,"id":736313,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fonda-Umani, S.","contributorId":205187,"corporation":false,"usgs":false,"family":"Fonda-Umani","given":"S.","email":"","affiliations":[{"id":37047,"text":"Department of Life Sciences, University of Trieste, v. Giorgieri, 10, 34127 Trieste, Italy","active":true,"usgs":false}],"preferred":false,"id":736314,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kirby, R.R.","contributorId":205188,"corporation":false,"usgs":false,"family":"Kirby","given":"R.R.","email":"","affiliations":[{"id":37048,"text":"Marine Biological Association, The Laboratory, Citadel Hill, The Hoe, Plymouth, PL1 2PB, UK","active":true,"usgs":false}],"preferred":false,"id":736315,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Greene, C.H.","contributorId":205189,"corporation":false,"usgs":false,"family":"Greene","given":"C.H.","email":"","affiliations":[{"id":37049,"text":"Ocean Resources and Ecosystems Program, Cornell University, Ithaca, NY 14853-1504, USA","active":true,"usgs":false}],"preferred":false,"id":736316,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goberville, E.","contributorId":205191,"corporation":false,"usgs":false,"family":"Goberville","given":"E.","email":"","affiliations":[{"id":37043,"text":"Centre National de la Recherche Scientifique, Laboratoire d’Océanologie et de Géosciences’ UMR LOG CNRS 8187, Station Marine, Université des Sciences et Technologies de Lille 1 - Lille 1 BP 80, 62930 Wimereux, France","active":true,"usgs":false}],"preferred":false,"id":736318,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Otto, S.A.","contributorId":205192,"corporation":false,"usgs":false,"family":"Otto","given":"S.A.","email":"","affiliations":[{"id":37051,"text":"Stockholm Resilience Centre, Stockholm University, Kräftriket 2B,SE-106 91 Stockholm, Sweden","active":true,"usgs":false}],"preferred":false,"id":736319,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Reid, P.C.","contributorId":205193,"corporation":false,"usgs":false,"family":"Reid","given":"P.C.","email":"","affiliations":[{"id":37052,"text":"SAHFOS, Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, The Hoe, Plymouth PL1 2PB, UK","active":true,"usgs":false}],"preferred":false,"id":736320,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stemmann, L.","contributorId":205194,"corporation":false,"usgs":false,"family":"Stemmann","given":"L.","email":"","affiliations":[{"id":37053,"text":"Sorbonne Universités, UPMC Univ Paris 06, UMR 7093, LOV, Observatoire océanologique, F-06230, Villefranche/mer, France","active":true,"usgs":false}],"preferred":false,"id":736321,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Edwards, M.","contributorId":205196,"corporation":false,"usgs":false,"family":"Edwards","given":"M.","affiliations":[{"id":37052,"text":"SAHFOS, Sir Alister Hardy Foundation for Ocean Science, The Laboratory, Citadel Hill, The Hoe, Plymouth PL1 2PB, UK","active":true,"usgs":false}],"preferred":false,"id":736323,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70202868,"text":"70202868 - 2019 - Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine","interactions":[],"lastModifiedDate":"2020-01-03T09:36:40","indexId":"70202868","displayToPublicDate":"2019-03-23T13:29:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine","docAbstract":"

Methods to detect and monitor the spread of invasive grasses are critical to avoid ecosystem transformations and large economic costs. The rapid spread of non‐native buffelgrass(Pennisetum ciliare) has intensified fire risk and is replacing fire intolerant native vegetation in the Sonoran Desert of the southwestern US. Coarse‐resolution satellite imagery has had limited success in detecting small patches of buffelgrass, whereas ground‐based and aerial survey methods are often cost prohibitive. To improve detection, we trained 2 m resolution DigitalGlobe WorldView‐2 satellite imagery with 12 cm resolution unmanned aerial vehicle (UAV) imagery and classified buffelgrass on Google Earth Engine, a cloud computing platform, using Random Forest (RF) models in Saguaro National Park, Arizona, USA. Our classification models had an average overall accuracy of 93% and producer's accuracies of 94–96% for buffelgrass, although user's accuracies were low. We detected a 2.92 km2 area of buffelgrass in the eastern Rincon Mountain District (1.07% of the total area) and a 0.46 km2 area (0.46% of the total area) in the western Tucson Mountain District of Saguaro National Park. Buffelgrass cover was significantly greater in the Sonoran Paloverde‐Mixed Cacti Desert Scrub vegetation type, on poorly developed Entisols and Inceptisol soils and on south‐facing topographic aspects compared to other areas. Our results demonstrate that high‐resolution imagery improve on previous attempts to detect and classify buffelgrass and indicate potential areas where the invasive grass might spread. The methods demonstrated in this study could be employed by land managers as a low‐cost strategy to identify priority areas for control efforts and continued monitoring.

","language":"English","publisher":"Zoological Society of London","doi":"10.1002/rse2.116","usgsCitation":"Elkind, K., Sankey, T.T., Munson, S.M., and Aslan, C.E., 2019, Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine: Remote Sensing in Ecology and Conservation, v. 5, no. 4, p. 318-331, https://doi.org/10.1002/rse2.116.","productDescription":"14 p.","startPage":"318","endPage":"331","ipdsId":"IP-099999","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":467782,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.116","text":"Publisher Index Page"},{"id":362657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Rincon Mountain District ,Tucson Mountain 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\"}}]}","volume":"5","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Elkind, Kaitlyn","contributorId":214593,"corporation":false,"usgs":false,"family":"Elkind","given":"Kaitlyn","email":"","affiliations":[{"id":39080,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":760341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":760342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":760340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aslan, Clare E.","contributorId":214594,"corporation":false,"usgs":false,"family":"Aslan","given":"Clare","email":"","middleInitial":"E.","affiliations":[{"id":39081,"text":"Landscape Conservation Initiative, Northern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":760343,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228865,"text":"70228865 - 2019 - Plague management of prairie dog colonies: Degree and duration of deltamethrin flea control","interactions":[],"lastModifiedDate":"2022-02-23T16:25:30.616899","indexId":"70228865","displayToPublicDate":"2019-03-23T10:20:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2489,"text":"Journal of Vector Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Plague management of prairie dog colonies: Degree and duration of deltamethrin flea control","docAbstract":"

Plague is a flea-borne disease of mammalian hosts. On the grasslands of western North America, plague stifles populations of Cynomys spp. prairie dogs (PDs). To manage plague, PD burrows are treated with 0.05% deltamethrin dust that can suppress flea numbers and plague transmission. Here, we evaluate the degree and duration of deltamethrin flea control with three PD species at six sites across four U.S. states. Data were simultaneously collected at paired plots. Burrows from one randomly assigned member of each pair were treated with deltamethrin; non-treated plots served as experimental baselines. Flea control was strong ≤two months after treatment, remained moderate one year later, and was statistically detectable for up to two years at some sites. Flea abundance was lower in plots with higher rates of deltamethrin application. After burrow treatments, flea abundance increased over time, reaching >one per PD within 255 to 352 days. Nevertheless, annual treatments of burrows with deltamethrin provided PDs with substantial protection against plague. Even so, deltamethrin should be further evaluated and combined with other tools under an integrated approach to plague management. Integrated plague management should help to conserve PDs and species that associate with them, including the endangered black-footed ferret (Mustela nigripes).

","language":"English","publisher":"Wiley","doi":"10.1111/jvec.12327","usgsCitation":"Eads, D.A., and Biggins, D.E., 2019, Plague management of prairie dog colonies: Degree and duration of deltamethrin flea control: Journal of Vector Ecology, v. 44, no. 1, p. 40-47, https://doi.org/10.1111/jvec.12327.","productDescription":"8 p.","startPage":"40","endPage":"47","ipdsId":"IP-103576","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467783,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jvec.12327","text":"Publisher Index Page"},{"id":437529,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AWK322","text":"USGS data release","linkHelpText":"Data on the Degree and Duration of Deltamethrin Flea Control on Prairie Dog Colonies in Montana, South Dakota, and Utah, USA"},{"id":396352,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, South Dakota, 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\"}}]}","volume":"44","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-05-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Eads, David Austin 0000-0002-4247-017X","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":279909,"corporation":false,"usgs":false,"family":"Eads","given":"David","email":"","middleInitial":"Austin","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835726,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202752,"text":"70202752 - 2019 - Regeneration of Metrosideros polymorpha forests in Hawaii after landscape‐level canopy dieback","interactions":[],"lastModifiedDate":"2019-03-25T08:24:25","indexId":"70202752","displayToPublicDate":"2019-03-22T15:47:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Regeneration of Metrosideros polymorpha forests in Hawaii after landscape‐level canopy dieback","title":"Regeneration of Metrosideros polymorpha forests in Hawaii after landscape‐level canopy dieback","docAbstract":"

Questions

(a) Have Metrosideros polymorpha trees become re‐established in Hawaiian forests previously impacted by canopy dieback in the 1970s? (b) Has canopy dieback expanded since the 1970s? (c) Can spatial patterns from this dieback be correlated with habitat factors to model future dieback in this area?

Study Site

An 83,603 ha study area on the eastern slopes of Mauna Loa and Mauna Kea volcanoes on the island of Hawaii, USA.

Methods

We analyzed very‐high‐resolution imagery to assess status of Metrosideros polymorphaforests across the eastern side of the island of Hawaii. We generated 1,170 virtual vegetation plots with a 100‐m radius; 541 plots in areas mapped in 1977 with trees dead or mostly defoliated (dieback), and 629 plots in adjacent wet forest habitat, previously mapped as non‐dieback condition. In each plot we estimated the frequency of M. polymorpha trees that were dead or mostly defoliated, and the frequency of trees with healthy crowns. These results were combined with habitat data to produce a spatial model depicting probability of canopy dieback within the study area.

Results

Seventy‐nine percent of plots mapped in 1977 in dieback condition recovered their canopy and were now considered in non‐dieback condition. Ninety‐one percent of plots in previous non‐dieback areas were found to still have a healthy M. polymorpha canopy in 2015. A spatial model allowed us to identify areas within the study area with high, medium, and low probability of experiencing this same type of canopy dieback in the future.

Conclusions

Most former dieback areas mapped within the study area in 1977 now show recovery of the tree canopy through growth of new cohorts of young M. polymorpha trees. This suggests these forest communities are resilient to this type of canopy loss and tree death so long as other factors do not disrupt the natural regeneration process.

","language":"English","publisher":"Wiley","doi":"10.1111/jvs.12704","usgsCitation":"Mertelmeyer, L., Jacobi, J.D., Mueller-Dombois, D., Brinck, K.W., and Boehmer, H.J., 2019, Regeneration of Metrosideros polymorpha forests in Hawaii after landscape‐level canopy dieback: Journal of Vegetation Science, v. 30, no. 1, p. 146-155, https://doi.org/10.1111/jvs.12704.","productDescription":"10 p.","startPage":"146","endPage":"155","ipdsId":"IP-099401","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":437530,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97OSO15","text":"USGS data release","linkHelpText":"Hawaii Island Regeneration of Metrosideros polymorpha forests since landscape-level canopy dieback in the 1970s"},{"id":362292,"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 -155.38238525390625,\n 19.452348936859018\n ],\n [\n -155.08987426757812,\n 19.452348936859018\n ],\n [\n -155.08987426757812,\n 20.06754094648767\n ],\n [\n -155.38238525390625,\n 20.06754094648767\n ],\n [\n -155.38238525390625,\n 19.452348936859018\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Mertelmeyer, Linda","contributorId":214407,"corporation":false,"usgs":false,"family":"Mertelmeyer","given":"Linda","email":"","affiliations":[{"id":39035,"text":"Technical University of Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":759816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":759815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mueller-Dombois, Dieter","contributorId":214408,"corporation":false,"usgs":false,"family":"Mueller-Dombois","given":"Dieter","email":"","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":759817,"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":759818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehmer, Hans Juergen","contributorId":207895,"corporation":false,"usgs":false,"family":"Boehmer","given":"Hans","email":"","middleInitial":"Juergen","affiliations":[{"id":37652,"text":"School of Geography, University of the South Pacific, Suva, Fiji","active":true,"usgs":false}],"preferred":false,"id":759819,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202746,"text":"70202746 - 2019 - Confronting uncertainty: Contributions of the wildlife profession to the broader scientific community","interactions":[],"lastModifiedDate":"2019-03-25T08:26:33","indexId":"70202746","displayToPublicDate":"2019-03-22T15:32:37","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":"Confronting uncertainty: Contributions of the wildlife profession to the broader scientific community","docAbstract":"

Most wildlife professionals are engaged in 1 or both of 2 basic endeavors: science and management. These endeavors are a focus of many other disciplines, leading to widespread sharing of general methodologies. Wildlife professionals have appropriately borrowed and assimilated many methods developed primarily in other disciplines but have also led the development of one class of quantitative methods, those that confront and incorporate uncertainty. Uncertainty arises in counts of focal entities, for which wildlife professionals have developed effective methods to deal with the common problems of nondetection and misclassification. These methods have been borrowed by disciplines as varied as paleobiology, medicine, human epidemiology, industrial quality control, military target acquisition, remote sensing, and human census. Uncertainty also arises in the modeling of those counts, specifically the observation and ecological processes that generated them. Wildlife professionals recognized the fundamental importance of model selection and rapidly assimilated methods for selecting the most appropriate model for a given data set. These methods for dealing with uncertainty inherent to counting and modeling are critical to the conduct of science and management. Wildlife professionals have developed additional methods for incorporating uncertainty in the accumulation of knowledge and the development of optimal decisions in an environment of learning. In some cases, professionals in other disciplines are using methods developed and popularized in the wildlife profession, but there is much potential for greater use. In this essay, I describe these areas of wildlife leadership, document their assimilation by other disciplines, and emphasize the potential for more interdisciplinary use of these methods. 

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21630","usgsCitation":"Nichols, J.D., 2019, Confronting uncertainty: Contributions of the wildlife profession to the broader scientific community: Journal of Wildlife Management, v. 83, no. 3, p. 519-533, https://doi.org/10.1002/jwmg.21630.","productDescription":"15 p.","startPage":"519","endPage":"533","ipdsId":"IP-101830","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":362289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"83","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759785,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70202751,"text":"70202751 - 2019 - North-south dipole in winter hydroclimate in the western United States during the last deglaciation","interactions":[],"lastModifiedDate":"2019-03-25T08:35:00","indexId":"70202751","displayToPublicDate":"2019-03-22T15:27:07","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"North-south dipole in winter hydroclimate in the western United States during the last deglaciation","docAbstract":"

During the termination of the last glacial period the western U.S. experienced exceptionally wet conditions, driven by changes in location and strength of the mid-latitude winter storm track. The distribution of modern winter precipitation is frequently characterized by a north-south wet/dry dipole pattern, controlled by interaction of the storm track with ocean-atmosphere conditions over the Pacific and Atlantic Oceans. Here we show that a dipole pattern of similar geographic extent persisted and switched sign during millennial-scale abrupt climate changes of the last deglaciation, based on a new lake level reconstruction for pluvial Lake Chewaucan (northwestern U.S.), and a compilation of regional paleoclimate records. This suggests the dipole pattern is robust, and one mode may be favored for centuries, thereby creating persistent contrasting wet/dry conditions across the western U.S. The TraCE-21k climate model simulation shows an equatorward enhancement of winter storm track activity in the northeastern Pacific, favoring wet conditions in southwestern U.S. during the second half of Heinrich Stadial 1 (16.1–14.6 ka) and consistent with paleoclimate evidence. During the Bølling/Allerød (14.6–12.8 ka), the northeastern Pacific storm track contracted poleward, consistent with wetter conditions concentrated poleward toward the northwest U.S.

","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-41197-y","usgsCitation":"Hudson, A.M., Hatchett, B.J., Quade, J., Boyle, D.P., Bassett, S.D., Ali, G., and De los Santos, M.G., 2019, North-south dipole in winter hydroclimate in the western United States during the last deglaciation: Scientific Reports, v. 9, p. 1-12, https://doi.org/10.1038/s41598-019-41197-y.","productDescription":"Article number: 4826, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-097821","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":467785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-41197-y","text":"Publisher Index Page"},{"id":362287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":759808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hatchett, Benjamin J. 0000-0003-1066-3601","orcid":"https://orcid.org/0000-0003-1066-3601","contributorId":214405,"corporation":false,"usgs":false,"family":"Hatchett","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":39033,"text":"Division of Atmospheric Sciences, Desert Research Institute, Reno, Nevada, USA","active":true,"usgs":false}],"preferred":false,"id":759809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quade, Jay","contributorId":22108,"corporation":false,"usgs":false,"family":"Quade","given":"Jay","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":759810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boyle, Douglas P.","contributorId":195421,"corporation":false,"usgs":false,"family":"Boyle","given":"Douglas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":759811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bassett, Scott D.","contributorId":214406,"corporation":false,"usgs":false,"family":"Bassett","given":"Scott","email":"","middleInitial":"D.","affiliations":[{"id":39034,"text":"Department of Geography, University of Nevada-Reno, Reno, Nevada, USA","active":true,"usgs":false}],"preferred":false,"id":759812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ali, Guleed","contributorId":195420,"corporation":false,"usgs":false,"family":"Ali","given":"Guleed","email":"","affiliations":[],"preferred":false,"id":759813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"De los Santos, Marie G.","contributorId":195424,"corporation":false,"usgs":false,"family":"De los Santos","given":"Marie","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":759814,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70203927,"text":"70203927 - 2019 - Aquatic macroinvertebrate community responses to wetland mitigation in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2019-06-21T11:29:27","indexId":"70203927","displayToPublicDate":"2019-03-22T11:17:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Aquatic macroinvertebrate community responses to wetland mitigation in the Greater Yellowstone Ecosystem","docAbstract":"

1. Wetlands are critical components of freshwater biodiversity and provide ecosystem services, but human activities have resulted in large-scale loss of these habitats across the globe. To offset this loss, mitigation wetlands are frequently constructed, but their ability to replicate the functions of natural wetlands remains uncertain. Further, monitoring of mitigation wetlands is limited and often focused exclusively on vegetation and physical characteristics.

2. Wetland fauna are assumed to be present if suitable habitat restoration is achieved, but this assumption is rarely tested. We used the macroinvertebrate community as a proxy for wetland function to compare created mitigation wetlands, natural wetlands impacted but not destroyed by road construction activity, and unimpacted reference wetlands along a highway corridor in the Greater Yellowstone Ecosystem. Unlike most other studies of invertebrate communities in created wetlands which have occurred in warm climates, our study area has a cold temperate climate with short growing seasons.

3. We estimated macroinvertebrate taxonomic richness and used linear models to test for effects of wetland design features (wetland age, isolation, depth, vegetation, size, and pH) on invertebrate richness. We also used non-metric multidimensional scaling to examine differences in community composition among wetland types and used indicator species analysis to determine which taxa were causing observed differences.

4. Taxonomic richness of macroinvertebrates was lower in created wetlands than impacted or reference wetlands, whereas richness was similar in impacted and reference wetlands. Wetland age was positively correlated with taxonomic richness. The amount of aquatic vegetation in wetlands had the greatest influence on taxonomic richness, so that recently created wetlands with little vegetation had the simplest invertebrate communities. Community composition of invertebrates in created wetlands also differed from community composition in reference and impacted wetlands. Most notably, created wetlands lacked some passive dispersers that were common in other wetland types, although we found no relationship between taxonomic richness and wetland isolation.

5. Overall, constructed wetlands had diminished and altered macroinvertebrate communities relative to reference and impacted wetlands, suggesting that longer times may be required for wetland mitigation projects in cold temperate climates to attain full functionality.

","language":"English","publisher":"Wiley","doi":"10.1111/fwb.13276","usgsCitation":"SWARTZ, L.K., Hossack, B.R., Muths, E.L., Newell, R.L., and Lowe, W.H., 2019, Aquatic macroinvertebrate community responses to wetland mitigation in the Greater Yellowstone Ecosystem: Freshwater Biology, v. 64, p. 942-953, https://doi.org/10.1111/fwb.13276.","productDescription":"12 p.","startPage":"942","endPage":"953","ipdsId":"IP-098009","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":364893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Togwotee Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.50735473632812,\n 43.875128129336716\n ],\n [\n -110.52520751953125,\n 43.79092385423618\n ],\n [\n -109.62570190429688,\n 43.48082639482503\n ],\n [\n -109.53643798828125,\n 43.574421623084234\n ],\n [\n -110.14480590820312,\n 43.875128129336716\n ],\n [\n -110.48126220703125,\n 43.916691089303114\n ],\n [\n -110.49774169921875,\n 43.916691089303114\n ],\n [\n -110.50735473632812,\n 43.875128129336716\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"64","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"SWARTZ, LEAH K. 0000-0003-2315-8727","orcid":"https://orcid.org/0000-0003-2315-8727","contributorId":216428,"corporation":false,"usgs":false,"family":"SWARTZ","given":"LEAH","email":"","middleInitial":"K.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":764741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":764740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":764742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Newell, Robert L.","contributorId":146452,"corporation":false,"usgs":false,"family":"Newell","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":16698,"text":"Wilderness Research Institute, 790 East Beckwith Avenue, Missoul","active":true,"usgs":false}],"preferred":false,"id":764743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowe, Winsor H.","contributorId":146455,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","email":"","middleInitial":"H.","affiliations":[{"id":5084,"text":"Division of Biological Sciences, University of Montana, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":764744,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202736,"text":"70202736 - 2019 - UAV-based measurements of spatio-temporal concentration distributions of fluorescent tracers in open channel flows","interactions":[],"lastModifiedDate":"2019-03-25T08:41:22","indexId":"70202736","displayToPublicDate":"2019-03-22T10:54:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"UAV-based measurements of spatio-temporal concentration distributions of fluorescent tracers in open channel flows","docAbstract":"

A new method of unmanned aerial vehicle (UAV)-based tracer tests using RGB (red, green, blue) images was developed in order to acquire the spatio-temporal concentration distribution of tracer clouds in open channel flows. Tracer tests using Rhodamine WT were conducted to collect the RGB images using a commercial digital camera mounted on a UAV, and the concentration of Rhodamine WT using in-situ fluorometric probes. The correlation analysis showed that the in-situmeasured concentrations of Rhodamine WT were strongly correlated with the digital number (DN) of the RGB images, even though the response of DN to the concentration was spatially heterogeneous. The empirical relationship between the DN values and the Rhodamine WT concentration data was estimated using artificial neural network (ANN) models. The trained ANN models, which consider the effect of water depth and river bed, accurately retrieved the detailed spatio-temporal concentration distributions of all study areas that had an R2 higher than 0.9. The acquired spatio-temporal concentration distributions by the proposed method based on the UAV images gave general as well as detailed views of the tracer cloud moving dynamically in open channel flows that cannot be easily observed using conventional in-situ measurements.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2019.03.007","usgsCitation":"Baek, D., Seo, I.W., Kim, J.S., and Nelson, J.M., 2019, UAV-based measurements of spatio-temporal concentration distributions of fluorescent tracers in open channel flows: Advances in Water Resources, v. 127, p. 76-88, https://doi.org/10.1016/j.advwatres.2019.03.007.","productDescription":"13 p.","startPage":"76","endPage":"88","ipdsId":"IP-102149","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":362275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baek, Donghae","contributorId":214366,"corporation":false,"usgs":false,"family":"Baek","given":"Donghae","email":"","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":759728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Seo, Il Won","contributorId":214367,"corporation":false,"usgs":false,"family":"Seo","given":"Il","email":"","middleInitial":"Won","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":759729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Jun Song","contributorId":214368,"corporation":false,"usgs":false,"family":"Kim","given":"Jun","email":"","middleInitial":"Song","affiliations":[{"id":37780,"text":"Seoul National University","active":true,"usgs":false}],"preferred":false,"id":759730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":759727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202742,"text":"70202742 - 2019 - Scale‐dependent effects of isolation on seasonal patch colonisation by two Neotropical freshwater fishes","interactions":[],"lastModifiedDate":"2019-03-25T08:48:53","indexId":"70202742","displayToPublicDate":"2019-03-22T10:50:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Scale‐dependent effects of isolation on seasonal patch colonisation by two Neotropical freshwater fishes","docAbstract":"

The metapopulation paradigm has been central to improve the conservation and management of natural populations. However, despite the large number of studies on metapopulation dynamics, the overall support for the relationships on which the paradigm is based has not been strong. Here, we studied the occupancy dynamics of two Neotropical fishes (i.e., Pimelodella gracilis and Leporinus friderici) to investigate two fundamental premises of the metapopulation paradigm, that is, that isolation and area/habitat quality affect colonisation and extinction probabilities in predictable ways. In order to do this, we used a modification of occupancy models that allows modelling the probability of a site's occupancy as a function of the occupancy of its neighbourhood. We found a weak positive effect of neighbourhood occupancy on P. gracilis colonisation, which is consistent with the propagule rain metapopulation, that is, colonists arriving from outside the studied system. However, we found a strong negative neighbourhood effect on extinction probability, suggesting that declining populations from stream sections are rescued from extinction by neighbouring patches. In contrast, the effect of neighbourhood occupancy on the metapopulation dynamics of L. friderici was in the opposite direction, affecting positively colonisation but not affecting extinction rates, which is consistent with the classical metapopulation model. In addition, the occupancy dynamics of both species were affected by water velocity. To our knowledge, this is the first study to link directly dispersal to local population dynamics in Neotropical fishes, and one of the few studies doing inferences on spatial population dynamics based on direct estimates of neighbourhood occupancy.

","language":"English","publisher":"Wiley","doi":"10.1111/eff.12452","usgsCitation":"Penha, J., Hakamada, K.Y., Hines, J.E., and Nichols, J.D., 2019, Scale‐dependent effects of isolation on seasonal patch colonisation by two Neotropical freshwater fishes: Ecology of Freshwater Fish, v. 28, no. 2, p. 274-284, https://doi.org/10.1111/eff.12452.","productDescription":"11 p.","startPage":"274","endPage":"284","ipdsId":"IP-096324","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":362273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Penha, Jerry","contributorId":214384,"corporation":false,"usgs":false,"family":"Penha","given":"Jerry","email":"","affiliations":[{"id":39029,"text":"Instituto de Biociências, Universidade Federal de Mato Grosso, Brazil","active":true,"usgs":false}],"preferred":false,"id":759761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hakamada, Karlo Y. P.","contributorId":214390,"corporation":false,"usgs":false,"family":"Hakamada","given":"Karlo","email":"","middleInitial":"Y. P.","affiliations":[],"preferred":false,"id":759768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759762,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215994,"text":"70215994 - 2019 - A re-examination of the three most prominent Holocene tephra deposits in western Canada: Bridge River, Mount St. Helens Yn and Mazama","interactions":[],"lastModifiedDate":"2020-11-02T15:39:49.210587","indexId":"70215994","displayToPublicDate":"2019-03-22T09:34:48","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"A re-examination of the three most prominent Holocene tephra deposits in western Canada: Bridge River, Mount St. Helens Yn and Mazama","docAbstract":"

Volcanic ash deposits (tephra) in western Canada are instrumental in providing independent chronologic control for many archaeological and paleoenvironmental sites. In Alberta, tephra are a key chronologic tool in a region where radiocarbon dates are often unreliable because of the prevalence of carbonate-rich bedrock and other “old carbon” sources, such as coal. However, many studies using tephra for age control, particularly archaeological projects, identify tephra simply through field characteristics or light microscopy. In both Alberta and British Columbia, many radiocarbon dates that were used to date key tephra deposits were bulk conventional ages on peat and lake sediments, which are not always reliable. These factors have led to uncertainty in the age and number of Bridge River and Mount St. Helens (MSH) set Y tephra present in the region and incomplete distribution maps. New major-element geochemical analyses from archaeological and sedimentary sites across south-central Alberta, complemented by new analyses of tephra from British Columbia and Saskatchewan, refine the distribution of the Bridge River, MSH Yn and Mazama tephra. New geochemical data, radiocarbon dates, and a detailed overview of proximal MSH set Y stratigraphy and geochemistry show that only one MSH layer, Yn, is present in this region, rather than two MSH set Y tephra as previously suggested. Additionally, re-assessment of age data combined with new geochemical analyses confirm that there is also only one Bridge River tephra. A Bayesian modelled age estimate is determined for MSH Yn based on new AMS dates on the tephra and vetted existing conventional ages, providing a revised age estimate for MSH Yn of 3805–3535 cal BP (mean of 3660 cal BP).

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2019.03.017","usgsCitation":"Jensen, B.J., Beaudoin, A.B., Clynne, M.A., Harvey, J., and Vallance, J.W., 2019, A re-examination of the three most prominent Holocene tephra deposits in western Canada: Bridge River, Mount St. Helens Yn and Mazama: Quaternary International, v. 500, p. 83-95, https://doi.org/10.1016/j.quaint.2019.03.017.","productDescription":"13 p.","startPage":"83","endPage":"95","ipdsId":"IP-104318","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":380028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.24414062499999,\n 39.70718665682654\n ],\n [\n -107.314453125,\n 39.70718665682654\n ],\n [\n -107.314453125,\n 52.908902047770255\n ],\n [\n -125.24414062499999,\n 52.908902047770255\n ],\n [\n -125.24414062499999,\n 39.70718665682654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"500","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jensen, Britta J.L. 0000-0001-9134-7170","orcid":"https://orcid.org/0000-0001-9134-7170","contributorId":244298,"corporation":false,"usgs":false,"family":"Jensen","given":"Britta","email":"","middleInitial":"J.L.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":803715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaudoin, Alwynne B.","contributorId":244299,"corporation":false,"usgs":false,"family":"Beaudoin","given":"Alwynne","email":"","middleInitial":"B.","affiliations":[{"id":48883,"text":"Royal Alberta Museum","active":true,"usgs":false}],"preferred":false,"id":803716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":803717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harvey, Jordan","contributorId":244300,"corporation":false,"usgs":false,"family":"Harvey","given":"Jordan","email":"","affiliations":[{"id":48883,"text":"Royal Alberta Museum","active":true,"usgs":false}],"preferred":false,"id":803718,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallance, James W. 0000-0002-3083-5469 jvallance@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5469","contributorId":547,"corporation":false,"usgs":true,"family":"Vallance","given":"James","email":"jvallance@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":803719,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222523,"text":"70222523 - 2019 - Snowmelt-triggered earthquake swarms at the margin of Long Valley Caldera, California","interactions":[],"lastModifiedDate":"2021-08-03T13:08:55.847945","indexId":"70222523","displayToPublicDate":"2019-03-22T08:02:54","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Snowmelt-triggered earthquake swarms at the margin of Long Valley Caldera, California","docAbstract":"

Fluids are well known to influence earthquakes, yet rarely are earthquakes convincingly linked to precipitation. Weak modulation or limited data often leads to ambiguous interpretations. In contrast, here we find that shallow seismicity in the Sierra Nevada range near Long Valley Caldera is strongly modulated by snowmelt. Over 33 years, shallow seismicity rates were ~37 times higher during very wet periods versus very dry periods. Relative earthquake relocations from a swarm in 2017 reveal downward migration from ~1- to 3-km depth along a steeply inclined plane. Steeply dipping strata may provide high-permeability pathways and faulting plane. Here we combine the correlated seismicity and hydrologic time series with the propagation observed in the relatively relocated earthquakes. From this combined evidence, we infer that pressure diffusion from groundwater recharge dramatically accelerated shallow seismicity rates, causing seismic swarms unrelated to volcanic processes.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019GL082254","usgsCitation":"Montgomery-Brown, E.K., Shelly, D.R., and Hsieh, P.A., 2019, Snowmelt-triggered earthquake swarms at the margin of Long Valley Caldera, California: Geophysical Research Letters, v. 46, no. 7, p. 3698-3705, https://doi.org/10.1029/2019GL082254.","productDescription":"7 p.","startPage":"3698","endPage":"3705","ipdsId":"IP-096033","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":387655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Long Valley Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.970703125,\n 35.24561909420681\n ],\n [\n -115.7080078125,\n 35.24561909420681\n ],\n [\n -115.7080078125,\n 38.238180119798635\n ],\n [\n -119.970703125,\n 38.238180119798635\n ],\n [\n -119.970703125,\n 35.24561909420681\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"7","noUsgsAuthors":false,"publicationDate":"2019-04-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Montgomery-Brown, Emily K. 0000-0001-6787-2055","orcid":"https://orcid.org/0000-0001-6787-2055","contributorId":214074,"corporation":false,"usgs":true,"family":"Montgomery-Brown","given":"Emily","email":"","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":820459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":820460,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202730,"text":"70202730 - 2019 - Stream metabolism increases with drainage area and peaks asynchronously across a stream network","interactions":[],"lastModifiedDate":"2019-03-26T08:16:07","indexId":"70202730","displayToPublicDate":"2019-03-21T16:36:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Stream metabolism increases with drainage area and peaks asynchronously across a stream network","docAbstract":"

Quantifying the spatial and temporal dynamics of stream metabolism across stream networks is key to understanding carbon cycling and stream food web ecology. To better understand intra-annual temporal patterns of gross primary production (GPP) and ecosystem respiration (ER) and their variability across space, we continuously measured dissolved oxygen and modeled stream metabolism for an entire year at ten sites across a temperate river network in Washington State, USA. We expected GPP and ER to increase with stream size and peak during summer and autumn months due to warmer temperatures and higher light availability. We found that GPP and ER increased with drainage area and that only four sites adhered to our expectations of summer peaks in GPP and autumn peaks in ER while the rest either peaked in winter, spring or remained relatively constant. Our results suggest the spatial arrangement and temporal patterns of discharge, temperature, light and nutrients within watersheds may result in asynchronies in GPP and ER, despite similar regional climatic conditions. These findings shed light on how temporal dynamics of stream metabolism can shift across a river network, which likely influence the dynamics of carbon cycling and stream food webs at larger scales.

","language":"English","publisher":"Springer","doi":"10.1007/s00027-018-0606-z","usgsCitation":"Mejia, F.H., Fremier, A.K., Benjamin, J.R., Bellmore, J., Grimm, A.Z., Watson, G., and Newsom, M., 2019, Stream metabolism increases with drainage area and peaks asynchronously across a stream network: Aquatic Sciences, v. 81, p. 1-17, https://doi.org/10.1007/s00027-018-0606-z.","productDescription":"Article 9, 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-086489","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":362255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.38818359375,\n 48.11476663187632\n ],\n [\n -119.79080200195311,\n 48.11476663187632\n ],\n [\n -119.79080200195311,\n 48.539341045937974\n ],\n [\n -120.38818359375,\n 48.539341045937974\n ],\n [\n -120.38818359375,\n 48.11476663187632\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Mejia, Francine H. 0000-0003-4447-231X","orcid":"https://orcid.org/0000-0003-4447-231X","contributorId":214345,"corporation":false,"usgs":true,"family":"Mejia","given":"Francine","email":"","middleInitial":"H.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":759692,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fremier, Alexander K.","contributorId":214346,"corporation":false,"usgs":false,"family":"Fremier","given":"Alexander","email":"","middleInitial":"K.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":759693,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":759694,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bellmore, J. Ryan jbellmore@usgs.gov","contributorId":4527,"corporation":false,"usgs":true,"family":"Bellmore","given":"J. Ryan","email":"jbellmore@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":759695,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grimm, Adrianne Z.","contributorId":214347,"corporation":false,"usgs":false,"family":"Grimm","given":"Adrianne","email":"","middleInitial":"Z.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":759696,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watson, Grace A.","contributorId":214348,"corporation":false,"usgs":false,"family":"Watson","given":"Grace A.","affiliations":[{"id":39012,"text":"Methow Salmon Recovery Foundation","active":true,"usgs":false}],"preferred":false,"id":759697,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Newsom, Michael","contributorId":178562,"corporation":false,"usgs":false,"family":"Newsom","given":"Michael","affiliations":[],"preferred":false,"id":759698,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202725,"text":"70202725 - 2019 - Evidence for non-steady-state carbon emissions from snow-scoured alpine tundra","interactions":[],"lastModifiedDate":"2019-03-21T14:47:38","indexId":"70202725","displayToPublicDate":"2019-03-21T14:11:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for non-steady-state carbon emissions from snow-scoured alpine tundra","docAbstract":"

High-latitude warming is capable of accelerating permafrost degradation and the decomposition of previously frozen carbon. The existence of an analogous high-altitude feedback, however, has yet to be directly evaluated. We address this knowledge gap by coupling a radiocarbon-based model to 7 years (2008–2014) of continuous eddy covariance data from a snow-scoured alpine tundra meadow in Colorado, USA, where solifluction lobes are associated with discontinuous permafrost. On average, the ecosystem was a net annual source of 232 ± 54 g C m−2 (mean ± 1 standard deviation) to the atmosphere, and respiration of relatively radiocarbon-depleted (i.e., older) substrate contributes to carbon emissions during the winter. Given that alpine soils with permafrost occupy 3.6 × 106 km2 land area and are estimated to contain 66.3 Pg of soil organic carbon (4.5% of the global pool), this scenario has global implications for the mountain carbon balance and corresponding resource allocation to lower elevations.

","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41467-019-09149-2","usgsCitation":"Knowles, J.F., Blanken, P.D., Lawrence, C., and Williams, M.W., 2019, Evidence for non-steady-state carbon emissions from snow-scoured alpine tundra: Nature Communications, v. 10, Article number: 1306; 9 p., https://doi.org/10.1038/s41467-019-09149-2.","productDescription":"Article number: 1306; 9 p.","ipdsId":"IP-101783","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":460433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-019-09149-2","text":"Publisher Index Page"},{"id":362250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Niwot Ridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.62410354614256,\n 40.052322006146916\n ],\n [\n -105.56985855102538,\n 40.052322006146916\n ],\n [\n -105.56985855102538,\n 40.07045271464657\n ],\n [\n -105.62410354614256,\n 40.07045271464657\n ],\n [\n -105.62410354614256,\n 40.052322006146916\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Knowles, John F.","contributorId":203853,"corporation":false,"usgs":false,"family":"Knowles","given":"John","email":"","middleInitial":"F.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":759656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blanken, Peter D.","contributorId":189305,"corporation":false,"usgs":false,"family":"Blanken","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":759657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Corey 0000-0002-2179-2436","orcid":"https://orcid.org/0000-0002-2179-2436","contributorId":214331,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":759655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Mark W.","contributorId":214082,"corporation":false,"usgs":false,"family":"Williams","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":38977,"text":"University of Colorado at Boulder","active":true,"usgs":false}],"preferred":false,"id":759658,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204977,"text":"70204977 - 2019 - A cautionary tale of topography and tilt from Kilauea Caldera","interactions":[],"lastModifiedDate":"2019-08-28T09:18:23","indexId":"70204977","displayToPublicDate":"2019-03-21T13:52:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"A cautionary tale of topography and tilt from Kilauea Caldera","docAbstract":"We conduct finite element analysis to investigate the effect of sharp topography on surface ground deformation caused by pressure changes in a magma reservoir. Tilt data express the horizontal gradient of vertical displacement and therefore can emphasize small variations in deformation that go unnoticed using other methods. We find that the vertical displacement profile at a surface with a cliff can be thought of as the superposition of the deformation from shallow and deeper sources. This combination can create a small peak in vertical displacement that acts as a pseudo‐source, creating a reversal of the deformation gradient and therefore anomalous tilt magnitude and a rotation of up to 180°. We apply these models to Kīlauea Caldera and find that surface geometry creates a tilt rotation of ∼10°, partially explaining anomalous tilt that has been observed. Our analysis highlights the importance of considering topography when assessing tilt measurements at active volcanoes.","language":"English","publisher":"Wiley","doi":"10.1029/2018GL081757","usgsCitation":"Johnson, J.A., Poland, M.P., Anderson, K.R., and Biggs, J., 2019, A cautionary tale of topography and tilt from Kilauea Caldera: Geophysical Research Letters, v. 46, no. 8, p. 4221-4229, https://doi.org/10.1029/2018GL081757.","productDescription":"9 p.","startPage":"4221","endPage":"4229","ipdsId":"IP-104361","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467789,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2018gl081757","text":"External Repository"},{"id":366969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Caldera","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3360366821289,\n 19.34969555223576\n ],\n [\n -155.20179748535153,\n 19.34969555223576\n ],\n [\n -155.20179748535153,\n 19.449111649832837\n ],\n [\n -155.3360366821289,\n 19.449111649832837\n ],\n [\n -155.3360366821289,\n 19.34969555223576\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"46","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Jessica A.","contributorId":149712,"corporation":false,"usgs":false,"family":"Johnson","given":"Jessica","email":"","middleInitial":"A.","affiliations":[{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":769381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":769380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":769382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biggs, Juliet","contributorId":206389,"corporation":false,"usgs":false,"family":"Biggs","given":"Juliet","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":769383,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202793,"text":"70202793 - 2019 - Relative abundance and molecular evolution of Lake Sinai Virus (Sinaivirus) clades","interactions":[],"lastModifiedDate":"2019-03-28T10:36:45","indexId":"70202793","displayToPublicDate":"2019-03-21T11:08:33","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Relative abundance and molecular evolution of Lake Sinai Virus (Sinaivirus) clades","docAbstract":"

Lake Sinai Viruses (Sinaivirus) are commonly detected in honey bees (Apis mellifera) but no disease phenotypes or fitness consequences have yet been demonstrated. This viral group is genetically diverse, lacks obvious geographic structure, and multiple lineages can co-infect individual bees. While phylogenetic analyses have been performed, the molecular evolution of LSV has not been studied extensively. Here, I use LSV isolates from GenBank as well as contigs assembled from honey bee Sequence Read Archive (SRA) accessions to better understand the evolutionary history of these viruses. For each ORF, substitution rate variation, codon usage, and tests of positive selection were evaluated. Outlier regions of high or low diversity were sought with sliding window analysis and the role of recombination in creating LSV diversity was explored. Phylogenetic analysis consistently identified two large clusters of sequences that correspond to the current LSV1 and LSV2 nomenclature, however lineages sister to LSV1 were the most frequently detected in honey bee SRA accessions. Different expression levels among ORFs suggested the occurrence of subgenomic transcripts. ORF1 and RNA-dependent RNA polymerase had higher evolutionary rates than the capsid and ORF4. A hypervariable region of the ORF1 protein-coding sequence was identified that had reduced selective constraint, but a site-based model of positive selection was not significantly more likely than a neutral model for any ORF. The only significant recombination signals detected between LSV1 and LSV2 initiated within this hypervariable region, but assumptions of the test (single-frame coding and independence of substitution rate by site) were violated. LSV codon usage differed strikingly from that of honey bees and other common honey-bee viruses, suggesting LSV is not strongly co-evolved with that host. LSV codon usage was significantly correlated with that of Varroa destructor, however, despite the relatively weak codon bias exhibited by the latter. While codon usage between the LSV1 and LSV2 clusters was similar for three ORFs, ORF4 codon usage was uncorrelated between these clades, implying rapid divergence of codon use for this ORF only. Phylogenetic placement and relative abundance of LSV isolates reconstructed from SRA accessions suggest that detection biases may be over-representing LSV1 and LSV2 in public databases relative to their sister lineages.

","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.6305","usgsCitation":"Cornman, R.S., 2019, Relative abundance and molecular evolution of Lake Sinai Virus (Sinaivirus) clades: PeerJ, v. 7, e6305; 19 p., https://doi.org/10.7717/peerj.6305.","productDescription":"e6305; 19 p.","ipdsId":"IP-102658","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":467792,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.6305","text":"Publisher Index Page"},{"id":437533,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F4YR6P","text":"USGS data release","linkHelpText":"Metagenomic detection and reconstruction of Lake Sinai Virus from honey bee sequence data"},{"id":362332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":760027,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70227919,"text":"70227919 - 2019 - Validating the performance of occupancy models for estimating habitat use and predicting the distribution of highly-mobile species: A case study using the American black bear","interactions":[],"lastModifiedDate":"2022-02-02T16:21:43.226849","indexId":"70227919","displayToPublicDate":"2019-03-21T10:04:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Validating the performance of occupancy models for estimating habitat use and predicting the distribution of highly-mobile species: A case study using the American black bear","docAbstract":"

Occupancy models have become a valuable tool for estimating wildlife-habitat relationships and for predicting species distributions. Highly-mobile species often violate the assumption that sampling units are geographically closed shifting the probability of occupancy to be interpreted as the probability of use. We used occupancy models, in conjunction with noninvasive sampling, to estimate habitat use and predict the distribution of a highly-mobile carnivore, the American black bear (Ursus americanus) in New Mexico, USA. The top model indicated that black bears use areas with higher primary productivity and fewer roads. The predictive performance of such models is rarely validated with independent data, so we validated our model predictions with 2-independent datasets. We first assessed the correlation between predicted and observed habitat use for 28 telemetry-collared bears in the Jemez Mountains. Predicted habitat use was positively correlated with observed use for all 3 years (2012: ρ = 0.81; 2013: ρ = 0.87; 2014: ρ = 0.90). We then predicted the probability of use within a cell where a bear mortality was documented using 2043 mortality locations from sport harvest, depredation, and vehicle collisions. The probability of habitat use at a mortality location was also positively correlated with observed use by the species (2012: ρ = 0.74; 2013: ρ = 0.89; 2014: ρ = 0.93). Our validation procedure supports the notion that occupancy models can be an effective tool for estimating habitat use and predicting the distribution of highly-mobile species when the assumption of geographic closure has been violated. Our findings may be of interest to studies that are estimating habitat use for highly-mobile species that are secretive or rare, difficult to capture, or expensive to monitor with other more intensive methods.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.03.010","usgsCitation":"Gould, M.J., Gould, W., Cain, J.W., and Roemer, G.W., 2019, Validating the performance of occupancy models for estimating habitat use and predicting the distribution of highly-mobile species: A case study using the American black bear: Biological Conservation, v. 234, p. 28-36, https://doi.org/10.1016/j.biocon.2019.03.010.","productDescription":"9 p.","startPage":"28","endPage":"36","ipdsId":"IP-099292","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Sangre de Cristo, Sacramento, and Jemez Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.479248046875,\n 32.37996146435729\n ],\n [\n -104.83154296875,\n 32.37996146435729\n ],\n [\n -104.83154296875,\n 36.712467243386264\n ],\n [\n -107.479248046875,\n 36.712467243386264\n ],\n [\n -107.479248046875,\n 32.37996146435729\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"234","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gould, Matthew J.","contributorId":201504,"corporation":false,"usgs":false,"family":"Gould","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":832573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gould, William R.","contributorId":244516,"corporation":false,"usgs":false,"family":"Gould","given":"William R.","affiliations":[{"id":27575,"text":"NMSU","active":true,"usgs":false}],"preferred":false,"id":832574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":832575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roemer, Gary W.","contributorId":273109,"corporation":false,"usgs":false,"family":"Roemer","given":"Gary","email":"","middleInitial":"W.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":832576,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216029,"text":"70216029 - 2019 - Quantitative coseismic and precipitation-induced landslide risk mapping for the country of Lebanon","interactions":[],"lastModifiedDate":"2020-11-05T13:01:03.14155","indexId":"70216029","displayToPublicDate":"2019-03-21T07:44:33","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Quantitative coseismic and precipitation-induced landslide risk mapping for the country of Lebanon","docAbstract":"

Quantitative landslide risk assessment is a key step in creating appropriate land use policies. The forced migration of those displaced by recent events in Syria has highlighted the need for studies to guide humanitarian aid and resettlement policies. In 2011, armed conflict in the region precipitated the largest refugee crisis in a generation. Over 1.5 million displaced Syrians now reside in Lebanon, rapidly changing the population distribution in geomorphically-active areas of the country. We use a multi-step process to quantitatively assess the landslide risk profile of Lebanon throughout the ongoing Syrian conflict. First, mode-specific geotechnical models are utilized to assess the individual hazard contributions of a suite of triggering scenarios and types of landslides appropriate to the varied terrain of Lebanon. Second, vulnerability estimates and population data from the United Nations High Commissioner for Refugees (UNHCR) are combined to produce scenario-specific risk. Finally, risk data is aggregated to create a comprehensive landslide risk profile for Syrian refugees in Lebanon and compared to that of the pre-conflict Lebanese population.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geo-Congress 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Eighth International Conference on Case Histories in Geotechnical Engineering","conferenceDate":"March 24–27, 2019","conferenceLocation":"Philadelphia, Pennsylvania","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/9780784482155.013","usgsCitation":"Pollock, W., Wartman, J., Abou-Jaoude, G., and Grant, A.R., 2019, Quantitative coseismic and precipitation-induced landslide risk mapping for the country of Lebanon, in Geo-Congress 2019, Philadelphia, Pennsylvania, March 24–27, 2019, https://doi.org/10.1061/9780784482155.013.","ipdsId":"IP-101086","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":380122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Lebanon","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[35.8211,33.27743],[35.5528,33.26427],[35.46071,33.08904],[35.12605,33.0909],[35.48221,33.90545],[35.97959,34.61006],[35.9984,34.64491],[36.44819,34.59394],[36.61175,34.20179],[36.06646,33.82491],[35.8211,33.27743]]]},\"properties\":{\"name\":\"Lebanon\"}}]}","noUsgsAuthors":false,"publicationDate":"2019-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollock, William","contributorId":244344,"corporation":false,"usgs":false,"family":"Pollock","given":"William","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":803816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wartman, Joseph 0000-0001-7659-7198","orcid":"https://orcid.org/0000-0001-7659-7198","contributorId":241918,"corporation":false,"usgs":false,"family":"Wartman","given":"Joseph","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":803817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abou-Jaoude, Grace 0000-0003-1992-1611","orcid":"https://orcid.org/0000-0003-1992-1611","contributorId":244345,"corporation":false,"usgs":false,"family":"Abou-Jaoude","given":"Grace","email":"","affiliations":[{"id":48898,"text":"Lebanese American University","active":true,"usgs":false}],"preferred":false,"id":803818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grant, Alex R. 0000-0002-5096-4305","orcid":"https://orcid.org/0000-0002-5096-4305","contributorId":219066,"corporation":false,"usgs":true,"family":"Grant","given":"Alex","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":803819,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204353,"text":"70204353 - 2019 - Relatedness within and among Myotis septentrionalis colonies at a local scale","interactions":[],"lastModifiedDate":"2019-07-19T07:42:19","indexId":"70204353","displayToPublicDate":"2019-03-21T07:40:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Relatedness within and among Myotis septentrionalis colonies at a local scale","docAbstract":"Abstract: We assessed parentage within and among maternity colonies of the northern long-eared bat (Myotis septentrionalis Troessart 1897) in north-central Kentucky from 2011–2013 to better understand colony social structure, formation, and membership dynamics. We intensively sampled colonies in close and remote (> 10 km) spatial proximity both before and after targeted day-roost removal. Colonies were not necessarily comprised of closely related individuals, but natal philopatry was common. Adjacent colonies often contained maternally related individuals, indicating that some pups did disperse, albeit not far from their natal home range. Lack of apparent overlap among maternity colonies, along with no observed individual movements between colonies, suggests that colonies may be relatively closed once established in the maternity season. Whereas some young on site had been sired by males collected on site that by chance had dispersed to the same summering grounds, most had not, as would be expected since the species mates in the fall swarms near hibernacula. The number of parentages that we inferred among colonies, however, suggests that outside the maternity season, social groups may be relatively flexible and open, with individuals moving among groups close to their natal area. Analysis of microsatellite DNA data showed a low FST (= 0.011) and best fit to a model of one multilocus genotypic cluster across the study area. We observed high turnover in colony membership between years in all colonies, regardless of roost removal treatment. Our results suggest that female northern long-eared bats exhibit fidelity to a general geographic area rather than individual colonies between years, and indicate presence of a complex and dynamic social-genetic structure. Greater understanding of colony dynamics, including formation, dissolution, and dispersal patterns, may contribute to conservation and management of this threatened species.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjz-2018-0229","usgsCitation":"Ford, W., Olivera-Hyde, M., Alexander Silvis, Eric M. 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Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":766483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olivera-Hyde, Miluska","contributorId":217270,"corporation":false,"usgs":false,"family":"Olivera-Hyde","given":"Miluska","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":766484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander Silvis","contributorId":199527,"corporation":false,"usgs":false,"family":"Alexander Silvis","affiliations":[],"preferred":false,"id":766485,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eric M. Hallerman","contributorId":217271,"corporation":false,"usgs":false,"family":"Eric M. Hallerman","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":766486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Britzke, Eric R.","contributorId":171586,"corporation":false,"usgs":false,"family":"Britzke","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":26924,"text":"USArmy Engineer Research and Development Center, Vicksburg, MS","active":true,"usgs":false}],"preferred":false,"id":766487,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202709,"text":"70202709 - 2019 - Defining the limits of spectrally based bathymetric mapping on a large river","interactions":[],"lastModifiedDate":"2019-03-20T14:45:46","indexId":"70202709","displayToPublicDate":"2019-03-20T14:45:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Defining the limits of spectrally based bathymetric mapping on a large river","docAbstract":"

Remote sensing has emerged as a powerful method of characterizing river systems but is subject to several important limitations. This study focused on defining the limits of spectrally based mapping in a large river. We used multibeam echosounder (MBES) surveys and hyperspectral images from a deep, clear-flowing channel to develop techniques for inferring the maximum detectable depth, dmax\">dmax , directly from an image and identifying optically deep areas that exceed dmax\">dmax . Optimal Band Ratio Analysis (OBRA) of progressively truncated subsets of the calibration data provided an estimate of dmax\">dmax by indicating when depth retrieval performance began to deteriorate due to the presence of depths greater than the sensor could detect. We then partitioned the calibration data into shallow and optically deep ( d&gt;dmax\">d>dmax ) classes and fit a logistic regression model to estimate the probability of optically deep water, Pr(OD)\">Pr(OD) . Applying a Pr(OD)\">Pr(OD) threshold value allowed us to delineate optically deep areas and thus only attempt depth retrieval in relatively shallow locations. For the Kootenai River, dmax\">dmax reached as high as 9.5 m at one site, with accurate depth retrieval ( R2=0.94\">R2=0.94 ) in areas with d&lt;dmax\">d<dmax . As a first step toward scaling up from short reaches to long river segments, we evaluated the portability of depth-reflectance relations calibrated at one site to other sites along the river. This analysis highlighted the importance of calibration data spanning a broad range of depths. Due to the inherent limitations of passive optical depth retrieval in large rivers, a hybrid field- and remote sensing-based approach would be required to obtain complete bathymetric coverage.

","language":"English","publisher":"MDPI","doi":"10.3390/rs11060665","usgsCitation":"Legleiter, C.J., and Fosness, R.L., 2019, Defining the limits of spectrally based bathymetric mapping on a large river: Remote Sensing, v. 11, no. 6, p. 1-29, https://doi.org/10.3390/rs11060665.","productDescription":"Article 665; 29 p.","startPage":"1","endPage":"29","ipdsId":"IP-104066","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467796,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11060665","text":"Publisher Index Page"},{"id":437535,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K54WDL","text":"USGS data release","linkHelpText":"Hyperspectral image data and multibeam echosounder surveys used for bathymetric mapping of the Kootenai River in northern Idaho, September 26-27, 2017"},{"id":362210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","volume":"11","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":759601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759602,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70202094,"text":"sir20195005 - 2019 - Regression models for estimating sediment and nutrient concentrations and loads at the Kankakee River, Shelby, Indiana, December 2015 through May 2018","interactions":[],"lastModifiedDate":"2019-03-21T09:42:58","indexId":"sir20195005","displayToPublicDate":"2019-03-20T14:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5005","displayTitle":"Regression Models for Estimating Sediment and Nutrient Concentrations and Loads at the Kankakee River, Shelby, Indiana, December 2015 through May 2018","title":"Regression models for estimating sediment and nutrient concentrations and loads at the Kankakee River, Shelby, Indiana, December 2015 through May 2018","docAbstract":"

The Kankakee River in northern Indiana flows through the area once known as the Grand Marsh. Beginning in the 1860s, anthropogenic changes to the river within Indiana resulted in downstream flooding and additional transport of sediment and nutrients. In 2015, the U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, upgraded the gaging station Kankakee River at Shelby, Indiana, to include the collection of water-quality data. By relating continuously monitored water-quality data to discrete data collected from December 2015 through May 2018, linear regression was used to develop models for estimating concentrations of suspended sediment, total nitrogen, and total phosphorus. Developed regression models indicated a strong correlation between turbidity and specific conductance with suspended-sediment concentration (adjusted coefficient of determination equals 0.92, predicted residual error sum of squares equals 0.151), nitrate plus nitrite and specific conductance with total nitrogen (adjusted coefficient of determination equals 0.95, predicted residual error sum of squares equals 0.0248), and turbidity with total phosphorus (adjusted coefficient of determination equals 0.89, predicted residual error sum of squares equals 0.0103).

Daily loads of suspended sediment, total nitrogen, and total phosphorus were computed as the product of daily mean regression model concentrations and daily mean streamflow. Rloadest models were used to compute daily loads of each constituent during gaps in regression model loads. For 2016 and 2017, the estimated annual suspended-sediment loads were 105,000 and 91,000 tons; estimated total nitrogen loads were 8,690 and 8,890 tons; and estimated total phosphorus loads were 265 and 236 tons, respectively.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195005","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Lathrop, T.R., Bunch, A.R., and Downhour, M.S., 2019, Regression models for estimating sediment and nutrient concentrations and loads at the Kankakee River, Shelby, Indiana, December 2015 through May 2018: U.S. Geological Survey Scientific Investigation Report 2019–5005, 13 p., https://doi.org/10.3133/sir20195005.","productDescription":"Report: v, 13 p.; 2 Data Releases","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-101520","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":362192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5005/coverthb.jpg"},{"id":362193,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5005/sir20195005.pdf","text":"Report","size":"1.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5005"},{"id":362194,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PE9PTD","text":"USGS data release","description":"USGS data release","linkHelpText":"Data and rloadest models for suspended sediment, total nitrogen, and total phosphorus for Kankakee River at Shelby, Indiana, January 5, 2016 to May 31, 2018"},{"id":362195,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90EKU6X","text":"USGS data release","description":"USGS data release","linkHelpText":"Data and Surrogate Models for Suspended Sediment, Total Nitrogen, and Total Phosphorus for the Kankakee River at Shelby, Indiana, January 5, 2016 to May 31, 2018"}],"country":"United States","state":"Indiana","city":"Shelby","otherGeospatial":"Kankakee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.81396484375,\n 41.34897943069752\n ],\n [\n -86.08337402343749,\n 41.34588656996287\n ],\n [\n -86.08337402343749,\n 41.76721469421018\n ],\n [\n -86.81259155273438,\n 41.76823896512856\n ],\n [\n -86.81396484375,\n 41.34897943069752\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2019-03-20","noUsgsAuthors":false,"publicationDate":"2019-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Lathrop, Timothy R. 0000-0002-3568-1286 trlathro@usgs.gov","orcid":"https://orcid.org/0000-0002-3568-1286","contributorId":213061,"corporation":false,"usgs":true,"family":"Lathrop","given":"Timothy","email":"trlathro@usgs.gov","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":756861,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunch, Aubrey R. 0000-0002-2453-3624 aurbunch@usgs.gov","orcid":"https://orcid.org/0000-0002-2453-3624","contributorId":4351,"corporation":false,"usgs":true,"family":"Bunch","given":"Aubrey","email":"aurbunch@usgs.gov","middleInitial":"R.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":756863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Downhour, Myles S. 0000-0001-6677-412X","orcid":"https://orcid.org/0000-0001-6677-412X","contributorId":213062,"corporation":false,"usgs":true,"family":"Downhour","given":"Myles S.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":756862,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202705,"text":"70202705 - 2019 - State-space analysis of power to detect regional brook trout population trends over time","interactions":[],"lastModifiedDate":"2019-10-28T09:48:18","indexId":"70202705","displayToPublicDate":"2019-03-20T14:42:05","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"State-space analysis of power to detect regional brook trout population trends over time","docAbstract":"

Threats to aquatic biodiversity are expressed at broad spatial scales, but identifying regional trends in abundance is challenging owing to variable sampling designs, and temporal and spatial variation in abundance. We compiled a regional dataset of brook trout Salvelinus fontinalis counts across their southern range representing 326 sites from eight states between 1982-2014, and conducted a statistical power analysis using Bayesian state-space models to evaluate the ability to detect temporal trends by characterizing posterior distributions with three approaches. A combination of monitoring periods, number of sites and electrofishing passes, decline magnitude and different revisit patterns were tested. Power increased with monitoring periods and decline magnitude. Trends in adults were better detected than young-of-the-year fish, which showed greater inter-annual variation in abundance. The addition of weather covariates to account for the temporal variation increased power only slightly. Single- and three-pass electrofishing methods were similar in power. Finally, power was higher for sampling designs with more frequent revisits over the duration of the monitoring program. Our results provide guidance for broad-scale monitoring designs for temporal trend detection.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0241","usgsCitation":"Pregler, K.C., Hanks, R.D., Childress, E., Hitt, N.P., Hocking, D.J., Letcher, B., and Kanno, Y., 2019, State-space analysis of power to detect regional brook trout population trends over time: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 11, p. 2145-2155, https://doi.org/10.1139/cjfas-2018-0241.","productDescription":"11 p.","startPage":"2145","endPage":"2155","ipdsId":"IP-098679","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":362209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"11","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pregler, Kasey C.","contributorId":149616,"corporation":false,"usgs":false,"family":"Pregler","given":"Kasey","email":"","middleInitial":"C.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":759565,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, R. Daniel","contributorId":214286,"corporation":false,"usgs":false,"family":"Hanks","given":"R.","email":"","middleInitial":"Daniel","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":759566,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Childress, Evan S.","contributorId":214287,"corporation":false,"usgs":false,"family":"Childress","given":"Evan S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":759567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hocking, Daniel J.","contributorId":214288,"corporation":false,"usgs":false,"family":"Hocking","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":39006,"text":"Frostburg State University","active":true,"usgs":false}],"preferred":false,"id":759568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Letcher, Benjamin H. 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":167313,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":759569,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kanno, Yoichiro","contributorId":210653,"corporation":false,"usgs":false,"family":"Kanno","given":"Yoichiro","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":759570,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202439,"text":"tm7C22 - 2019 - User’s manual for the Draper climate-distribution software suite with data‑evaluation tools","interactions":[],"lastModifiedDate":"2019-07-26T12:05:14","indexId":"tm7C22","displayToPublicDate":"2019-03-20T11:25:22","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C22","displayTitle":"User’s Manual for the Draper Climate-Distribution Software Suite with Data-Evaluation Tools","title":"User’s manual for the Draper climate-distribution software suite with data‑evaluation tools","docAbstract":"

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiring distributed inputs of climate data beyond what is available from observations collected at climate stations. To prepare inputs required for model-mapping units across the study area, climate data (temperature and precipitation) are distributed by combining data from gridded surfaces of mean-monthly climate-data values with (often) widely spaced daily point observations. Examples of climate-data files used to develop PRMS-formatted input files for the Merced River Basin Precipitation-Runoff Modeling System (PRMS) are included in this manual.

The Draper Climate-Distribution Software Suite (Draper Suite) consists of the Draper climate-distribution program (Draper) and several supporting pre- and post-processing applications. Draper combines spatially distributed input in the form of monthly averaged values for precipitation, maximum temperature, and minimum temperature with daily observed data from climate stations to estimate distributed climate-data values at predefined locations across a study area (typically a drainage basin) on a daily time step. Alternative methods are used when station data are limited or missing for a particular day. Draper uses a set of required and optional input and output files with defined formats and naming conventions. A shell application also is available to manage multiple runs of the Draper application.

Other applications in the Draper Suite include (1) a tool to find and interactively remove outliers in the input data, (2) a tool to check and enforce a minimum daily temperature range, and (3) a tool to view output diagnostic information as time-series graphs. These tools can be used iteratively to evaluate and improve the results from Draper as part of a workflow involving physically based environmental models, such as the Precipitation-Runoff Modeling System (PRMS).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C22","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Donovan, J.M., and Koczot, K.M., 2019, User’s manual for the Draper climate-distribution software suite with data‑evaluation tools: U.S. Geological Survey Techniques and Methods 7-C22, 55 p., https://doi.org/10.3133/tm7C22. ","productDescription":"viii, 55 p","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-086388","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":362190,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c22/coverthb.jpg"},{"id":362191,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c22/tm7c22.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C22"},{"id":365983,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://code.usgs.gov/cawsc/draper","text":"Source code and executables","linkHelpText":"- Users are required to create an account to access the distribution"}],"contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2019-03-20","noUsgsAuthors":false,"publicationDate":"2019-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Donovan, John M. 0000-0002-7957-5397 jmd@usgs.gov","orcid":"https://orcid.org/0000-0002-7957-5397","contributorId":1255,"corporation":false,"usgs":true,"family":"Donovan","given":"John","email":"jmd@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koczot, Kathryn M. 0000-0001-5728-9798 kmkoczot@usgs.gov","orcid":"https://orcid.org/0000-0001-5728-9798","contributorId":2039,"corporation":false,"usgs":true,"family":"Koczot","given":"Kathryn","email":"kmkoczot@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758539,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216766,"text":"70216766 - 2019 - Estimating the energy expenditure of free‐ranging polar bears using tri‐axial accelerometers: A validation with doubly labeled water","interactions":[],"lastModifiedDate":"2020-12-04T22:03:41.306725","indexId":"70216766","displayToPublicDate":"2019-03-19T15:59:38","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the energy expenditure of free‐ranging polar bears using tri‐axial accelerometers: A validation with doubly labeled water","docAbstract":"

Measures of energy expenditure can be used to inform animal conservation and management, but methods for measuring the energy expenditure of free‐ranging animals have a variety of limitations. Advancements in biologging technologies have enabled the use of dynamic body acceleration derived from accelerometers as a proxy for energy expenditure. Although dynamic body acceleration has been shown to strongly correlate with oxygen consumption in captive animals, it has been validated in only a few studies on free‐ranging animals. Here, we use relationships between oxygen consumption and overall dynamic body acceleration in resting and walking polar bears Ursus maritimus and published values for the costs of swimming in polar bears to estimate the total energy expenditure of 6 free‐ranging polar bears that were primarily using the sea ice of the Beaufort Sea. Energetic models based on accelerometry were compared to models of energy expenditure on the same individuals derived from doubly labeled water methods. Accelerometer‐based estimates of energy expenditure on average predicted total energy expenditure to be 30% less than estimates derived from doubly labeled water. Nevertheless, accelerometer‐based measures of energy expenditure strongly correlated (r2 = 0.70) with measures derived from doubly labeled water. Our findings highlight the strengths and limitations in dynamic body acceleration as a measure of total energy expenditure while also further supporting its use as a proxy for instantaneous, detailed energy expenditure in free‐ranging animals.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.5053","usgsCitation":"Pagano, A.M., and Williams, T.M., 2019, Estimating the energy expenditure of free‐ranging polar bears using tri‐axial accelerometers: A validation with doubly labeled water: Ecology and Evolution, v. 9, no. 7, p. 4210-4219, https://doi.org/10.1002/ece3.5053.","productDescription":"10 p.","startPage":"4210","endPage":"4219","ipdsId":"IP-101615","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":467799,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.5053","text":"Publisher Index Page"},{"id":381005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Northwest Territories, Yukon","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -127.35351562499999,\n 70.19999407534661\n ],\n [\n -125.859375,\n 72.97118902284586\n ],\n [\n -157.58789062499997,\n 73.17589717422607\n ],\n [\n -156.62109374999997,\n 71.30079291637452\n ],\n [\n -148.798828125,\n 70.25945200030638\n ],\n [\n -145.1953125,\n 70.05059634999759\n ],\n [\n -139.5703125,\n 69.47296854140573\n ],\n [\n -135.703125,\n 68.65655498475735\n ],\n [\n -127.35351562499999,\n 70.19999407534661\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"7","noUsgsAuthors":false,"publicationDate":"2019-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":806132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Terrie M.","contributorId":191735,"corporation":false,"usgs":false,"family":"Williams","given":"Terrie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":806133,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217076,"text":"70217076 - 2019 - Characteristics and spatial variability of wind noise on near-surface broadband seismometers","interactions":[],"lastModifiedDate":"2021-01-04T17:25:38.395765","indexId":"70217076","displayToPublicDate":"2019-03-19T11:18:03","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Characteristics and spatial variability of wind noise on near-surface broadband seismometers","docAbstract":"

By coupling with the ground, wind causes ground motion that appears on seismic records as noise across a wide bandwidth. This wind-generated noise can drown out important features such as small earthquakes and prevent observation of normal modes from large earthquakes. Because the wind field is heterogeneous at local scales due to structures, diurnal heating, and topography, wind-induced seismic noise may be different on seismometers installed just meters apart. We have investigated the spatial variability of wind-induced noise using two weather sensors separated by approximately ~100 m and co-located with one deep borehole and four near-surface broadband seismometers. We found that at longer periods (>5 s), increasing wind speed causes increases in noise on the horizontal components of seismometers. While this has been previously observed, we also measured a γ2-coherence of less than 0.2 between the wind speed, wind direction, and the pressure recorded by our weather stations. We further observed a loss of coherence between the vertical components of our seismometers from 8 s to 20 s period. The amplitude of the drop-in coherence appears to depend on the substrate surrounding the seismometer. Based on two previously-developed theoretical models, we found that the local material surrounding the sensor could be amplifying the wind-generated noise. We also investigated the frequency dependence of wind-induced noise and found that the dominant source of high-frequency seismic noise at some sites could be anthropogenic rather than induced by wind. Additionally, we estimated the linear relationship between the root mean squares (RMS) of wind speed and RMS seismic velocity for all sensors, finding substantial variability between different installments. A more detailed understanding of the complex processes by which wind-induced noise is generated can inform the installation of sensors and the development of methods for mitigation of these effects, thus improving the overall quality of seismic data.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120180227","usgsCitation":"Dybing, S., Ringler, A.T., Wilson, D.C., and Anthony, R.E., 2019, Characteristics and spatial variability of wind noise on near-surface broadband seismometers: Bulletin of the Seismological Society of America, v. 109, no. 3, p. 1082-1098, https://doi.org/10.1785/0120180227.","productDescription":"17 p.","startPage":"1082","endPage":"1098","ipdsId":"IP-103523","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":381855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","city":"Alburquerque","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.84478759765624,\n 34.95799531086792\n ],\n [\n -106.46575927734375,\n 34.95799531086792\n ],\n [\n -106.46575927734375,\n 35.240011164750456\n ],\n [\n -106.84478759765624,\n 35.240011164750456\n ],\n [\n -106.84478759765624,\n 34.95799531086792\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"109","issue":"3","noUsgsAuthors":false,"publicationDate":"2019-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Dybing, S. N.","contributorId":246021,"corporation":false,"usgs":false,"family":"Dybing","given":"S. N.","affiliations":[{"id":35028,"text":"Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":807510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":3946,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807513,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}