The diversification of modern birds has been shaped by a number of radiations. Rapid diversification events make reconstructing the evolutionary relationships among taxa challenging due to the convoluted effects of incomplete lineage sorting (ILS) and introgression. Phylogenomic data sets have the potential to detect patterns of phylogenetic incongruence, and to address their causes. However, the footprints of ILS and introgression on sequence data can vary between different phylogenomic markers at different phylogenetic scales depending on factors such as their evolutionary rates or their selection pressures. We show that combining phylogenomic markers that evolve at different rates, such as paired-end double-digest restriction site-associated DNA (PE-ddRAD) and ultraconserved elements (UCEs), allows a comprehensive exploration of the causes of phylogenetic discordance associated with short internodes at different timescales. We used thousands of UCE and PE-ddRAD markers to produce the first well-resolved phylogeny of shearwaters, a group of medium-sized pelagic seabirds that are among the most phylogenetically controversial and endangered bird groups. We found that phylogenomic conflict was mainly derived from high levels of ILS due to rapid speciation events. We also documented a case of introgression, despite the high philopatry of shearwaters to their breeding sites, which typically limits gene flow. We integrated state-of-the-art concatenated and coalescent-based approaches to expand on previous comparisons of UCE and RAD-Seq data sets for phylogenetics, divergence time estimation, and inference of introgression, and we propose a strategy to optimize RAD-Seq data for phylogenetic analyses. Our results highlight the usefulness of combining phylogenomic markers evolving at different rates to understand the causes of phylogenetic discordance at different timescales.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/sysbio/syaa101","usgsCitation":"Ferrer Obiol, J., James, H.F., Chesser, R., Bretagnolle, V., Gonzalez-Solis, J., Rozas, J., Riutort, M., and Welch, A., 2021, Integrating sequence capture and restriction-site associated DNA sequencing to resolve recent radiations of pelagic seabirds: Systematic Biology, v. 70, no. 5, p. 976-996, https://doi.org/10.1093/sysbio/syaa101.","productDescription":"21 p.","startPage":"976","endPage":"996","ipdsId":"IP-120576","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":453551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/sysbio/syaa101","text":"Publisher Index Page"},{"id":383696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Ferrer Obiol, Joan","contributorId":252895,"corporation":false,"usgs":false,"family":"Ferrer Obiol","given":"Joan","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"James, Helen F.","contributorId":54414,"corporation":false,"usgs":false,"family":"James","given":"Helen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":811078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chesser, R. Terry 0000-0003-4389-7092 tchesser@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":894,"corporation":false,"usgs":true,"family":"Chesser","given":"R. Terry","email":"tchesser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":811079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bretagnolle, Vincent","contributorId":213757,"corporation":false,"usgs":false,"family":"Bretagnolle","given":"Vincent","email":"","affiliations":[{"id":38848,"text":"CNRS & Université de La Rochelle","active":true,"usgs":false}],"preferred":false,"id":811080,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gonzalez-Solis, Jacob 0000-0002-8691-9397","orcid":"https://orcid.org/0000-0002-8691-9397","contributorId":252896,"corporation":false,"usgs":false,"family":"Gonzalez-Solis","given":"Jacob","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rozas, Julio","contributorId":252897,"corporation":false,"usgs":false,"family":"Rozas","given":"Julio","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811082,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Riutort, Marta","contributorId":252898,"corporation":false,"usgs":false,"family":"Riutort","given":"Marta","email":"","affiliations":[{"id":50463,"text":"Univ. of Barcelona","active":true,"usgs":false}],"preferred":false,"id":811083,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Welch, Andreanna J.","contributorId":79313,"corporation":false,"usgs":false,"family":"Welch","given":"Andreanna J.","affiliations":[],"preferred":false,"id":811084,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228532,"text":"70228532 - 2021 - Reduced recruitment of Chinook salmon in a leveed bar-built estuary","interactions":[],"lastModifiedDate":"2022-02-14T21:09:09.622847","indexId":"70228532","displayToPublicDate":"2021-02-05T16:08:48","publicationYear":"2021","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":"Reduced recruitment of Chinook salmon in a leveed bar-built estuary","docAbstract":"Estuaries are commonly touted as nurseries for salmonids, providing numerous advantages for smolts prior to ocean entry. In bar-built estuaries, sandbars form at the mouth of rivers during periods of low stream flow, closing access to the ocean and preventing outmigration. We evaluated how summer residency in a leveed bar-built estuary affects the growth, survival, and recruitment of a Chinook salmon (Oncorhynchus tshawytscha) population. We performed a mark–recapture study on outmigrants to determine juvenile estuary abundance, growth, and survival. We used returning adult scales and otoliths to determine the relative proportion of summer estuary residents in spawning adults. Juveniles in the estuary grew less after mouth closure, and ultimately summer estuary residents had lower smolt-to-adult survival and contributed disproportionately less to the spawning population than juveniles that reared in the ocean their first summer. Mouth closure may lower food availability and deteriorate estuary conditions by reducing marine prey influx and estuary circulation. This research demonstrates the complexity of estuary dynamics and function as salmonid nurseries, particularly when considering the extensive modification of estuaries.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2020-0122","usgsCitation":"Chen, E., and Henderson, M., 2021, Reduced recruitment of Chinook salmon in a leveed bar-built estuary: Canadian Journal of Fisheries and Aquatic Sciences, v. 78, p. 894-904, https://doi.org/10.1139/cjfas-2020-0122.","productDescription":"11 p.","startPage":"894","endPage":"904","ipdsId":"IP-117728","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501015,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/106026","text":"External Repository"},{"id":395942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Humboldt County","otherGeospatial":"Redwood Creek","volume":"78","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Emily K.","contributorId":276069,"corporation":false,"usgs":false,"family":"Chen","given":"Emily K.","affiliations":[{"id":27855,"text":"HSU","active":true,"usgs":false}],"preferred":false,"id":834527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henderson, Mark J. 0000-0002-2861-8668 mhenderson@usgs.gov","orcid":"https://orcid.org/0000-0002-2861-8668","contributorId":198609,"corporation":false,"usgs":true,"family":"Henderson","given":"Mark J.","email":"mhenderson@usgs.gov","affiliations":[],"preferred":false,"id":834526,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218770,"text":"70218770 - 2021 - Ground‐penetrating radar, electromagnetic induction, terrain, and vegetation observations coupled with machine learning to map permafrost distribution at Twelvemile Lake, Alaska","interactions":[],"lastModifiedDate":"2021-08-17T16:09:40.432278","indexId":"70218770","displayToPublicDate":"2021-02-05T08:03:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3032,"text":"Permafrost and Periglacial Processes","active":true,"publicationSubtype":{"id":10}},"title":"Ground‐penetrating radar, electromagnetic induction, terrain, and vegetation observations coupled with machine learning to map permafrost distribution at Twelvemile Lake, Alaska","docAbstract":"We collected ground‐penetrating radar (GPR) and frequency‐domain electromagnetic induction (FDEM) profiles in 2011 and 2012 to identify the extent of permafrost relative to surface biomass and solar insolation around Twelvemile Lake near Fort Yukon, Alaska. We compared a Landsat‐derived biomass estimate and modeled solar insolation from a digital elevation model to the geophysical measurements. We show correspondence between vegetation type and biomass relative to permafrost extent and seasonal freeze–thaw. Thicker permafrost (≥25 m) was covered by greater biomass, and seasonal thaw depths in these regions were minimal (1 m). Shallow (1–3 m depth) and thin (20–50 cm) newly forming permafrost or frozen layers from the previous winter occurred below northward oriented slopes with thin biomass cover. South‐facing slopes exhibited permafrost when there was enough biomass to shield incoming solar energy. We developed an artificial neural network to predict permafrost extent across the broader region by mapping GPR‐observed instances of permafrost to FDEM, biomass, and terrain observations with 90.2% accuracy. We identified a strong linear correlation (r = −0.77) between permafrost probability and seasonal thaw depth, indicating that our models may also be used to explore thaw patterns and variability in active layer thickness. This study highlights the combined influence of biomass and terrain on the presence of permafrost and the value of evaluating such parameters via remote sensing to predict permafrost spatial or temporal variability. Incorporating diverse geophysical datasets with in‐situ validation into machine learning models demonstrates a useful approach to upscale estimated permafrost extent across large Arctic expanses.
The precise location of the seismic source of 1755 CE Great Lisbon earthquake is still uncertain. The aim of this work is to use an onland sedimentary record in southern Portugal to test and validate seismic sources for the earthquake. To achieve this, tsunami deposit thicknesses from over 150 cores collected at Salgados in southern Portugal were compared to the results of a tsunami sediment transport model (Delft3D-FLOW) that simulates tsunami propagation, inundation, erosion, and deposition. Five different hypothetical seismic sources were modeled with varying bed roughness coefficients to assess how well they reproduced observed patterns of tsunami deposit thicknesses and dune. Modeled and observed historical tsunami arrival times were also used to test different earthquake sources. Based on these comparisons, three modeled earthquake sources were able to reproduce the observed data, suggesting they should be regarded as somewhat more likely sources for the 1755 earthquake in contrast to four other modeled sources. The fault closest to shore (Marquês de Pombal) yielded the best correlations between model and observations.
Chemical-contaminant mixtures are widely reported in large stream reaches in urban/agriculture-developed watersheds, but mixture compositions and aggregate biological effects are less well understood in corresponding smaller headwaters, which comprise most of stream length, riparian connectivity, and spatial biodiversity. During 2014–2017, the U.S. Geological Survey (USGS) measured 389 unique organic analytes (pharmaceutical, pesticide, organic wastewater indicators) in 305 headwater streams within four contiguous United States (US) regions. Potential aquatic biological effects were evaluated for estimated maximum and median exposure conditions using multiple lines of evidence, including occurrence/concentrations of designed-bioactive pesticides and pharmaceuticals and cumulative risk screening based on vertebrate-centric ToxCast™ exposure-response data and on invertebrate and nonvascular plant aquatic life benchmarks. Mixed-contaminant exposures were ubiquitous and varied, with 78% (304) of analytes detected at least once and cumulative maximum concentrations up to more than 156,000 ng/L. Designed bioactives represented 83% of detected analytes. Contaminant summary metrics correlated strong-positive (rho (ρ): 0.569–0.719) to multiple watershed-development metrics, only weak-positive to point-source discharges (ρ: 0.225–353), and moderate- to strong-negative with multiple instream invertebrate metrics (ρ: −0.373 to −0.652). Risk screening indicated common exposures with high probability of vertebrate-centric molecular effects and of acute toxicity to invertebrates, respectively. The results confirm exposures to broad and diverse contaminant mixtures and provide convincing multiple lines of evidence that chemical contaminants contribute substantially to adverse multi-stressor effects in headwater-stream communities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.145062","usgsCitation":"Bradley, P., Journey, C., Romanok, K., Breitmeyer, S.E., Button, D.T., Carlisle, D.M., Huffman, B., Mahler, B., Nowell, L.H., Qi, S.L., Smalling, K., Waite, I.R., and Van Metre, P.C., 2021, Multi-region assessment of chemical mixture exposures and predicted cumulative effects in USA wadeable urban/agriculture-gradient streams: Science of the Total Environment, v. 773, 145062, 12 p., https://doi.org/10.1016/j.scitotenv.2021.145062.","productDescription":"145062, 12 p.","ipdsId":"IP-122523","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science 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sbreitmeyer@usgs.gov","orcid":"https://orcid.org/0000-0003-0609-1559","contributorId":172622,"corporation":false,"usgs":true,"family":"Breitmeyer","given":"Sara","email":"sbreitmeyer@usgs.gov","middleInitial":"E.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":810480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Button, Daniel T. 0000-0002-7479-884X dtbutton@usgs.gov","orcid":"https://orcid.org/0000-0002-7479-884X","contributorId":2084,"corporation":false,"usgs":true,"family":"Button","given":"Daniel","email":"dtbutton@usgs.gov","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science 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bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":810484,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment 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Center","active":true,"usgs":true}],"preferred":true,"id":810487,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810488,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810489,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70228589,"text":"70228589 - 2021 - Urbanization’s influence on the distribution of mange in a carnivore revealed with multistate occupancy models","interactions":[],"lastModifiedDate":"2022-02-14T14:51:52.531783","indexId":"70228589","displayToPublicDate":"2021-02-04T08:43:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Urbanization’s influence on the distribution of mange in a carnivore revealed with multistate occupancy models","docAbstract":"Increasing urbanization and use of urban areas by synanthropic wildlife has increased human and domestic animal exposure to zoonotic diseases and exacerbated epizootics within wildlife populations. Consequently, there is a need to improve wildlife disease surveillance programs to rapidly detect outbreaks and refine inferences regarding spatiotemporal disease dynamics. Multistate occupancy models can address potential shortcomings in surveillance programs by accounting for imperfect detection and the misclassification of disease states. We used these models to explore the relationship between urbanization, slope, and the spatial distribution of sarcoptic mange in coyotes (Canis latrans) inhabiting Fort Irwin, California, USA. We deployed remote cameras across 180 sites within the desert surrounding the populated garrison and classified sites by mange presence or absence depending on whether a symptomatic or asymptomatic coyote was photographed. Coyotes selected flatter sites closer to the urban area with a high probability of use (0.845, 95% credible interval (CRI): 0.728, 0.944); site use decreased as the distance to urban areas increased (standardized
The U.S. Geological Survey (USGS) completed hydrologic and hydraulic analyses for selected reaches of the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan, in cooperation with the city of Lansing. The study comprised a 3.1-mile reach of the Grand River, a 30.3-mile reach of the Red Cedar River, and a 12.0-mile reach of Sycamore Creek. The information produced from the study can be used to update and expand an existing Federal Emergency Management Agency Flood Insurance Study for Ingham County, Mich.
Historical streamflow data from USGS streamgages on Grand River at Lansing, Mich. (station number 04113000); Red Cedar River at East Lansing, Mich. (station number 04112500); Red Cedar River near Williamston, Mich. (station number 04111379); and Sycamore Creek at Holt Road near Holt, Mich. (station number 04112850) were used to estimate instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities (AEPs) and a “1-percent plus” AEP.
The Hydrologic Engineering Center’s River Analysis System step-backwater model was used to determine water-surface elevation profiles for the 10-, 4-, 2-, 1-, and 0.2-percent AEP floods, the 1-percent plus AEP flood, and a regulatory floodway for each stream reach. The hydraulic models were calibrated based on stage-streamflow ratings at USGS streamgages. Flood-inundation boundaries for the 1- and 0.2-percent annual exceedance probability floods and regulatory floodway were created for each stream.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205144","collaboration":"Prepared in cooperation with the city of Lansing, Michigan","usgsCitation":"Whitehead, M.T., and Ostheimer, C.J., 2021, Hydrologic and hydraulic analyses of the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan: U.S. Geological Survey Scientific Investigations Report 2020–5144, \n17 p., https://doi.org/10.3133/sir2020–5144.","productDescription":"Report: iv, 17 p.; Data Realease","onlineOnly":"Y","ipdsId":"IP-118378","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":382823,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5144/coverthb.jpg"},{"id":382824,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5144/sir20205144.pdf","text":"Report","size":"3.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5144"},{"id":382825,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91CQ755","text":"USGS data release","linkHelpText":"Geospatial datasets and hydraulic models for the Grand River, Red Cedar River, and Sycamore Creek near Lansing, Michigan"}],"country":"United States","state":"Michigan","otherGeospatial":"Grand River, Red Cedar River, Sycamore Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.57550048828125,\n 42.48526384858916\n ],\n [\n -83.9959716796875,\n 42.48526384858916\n ],\n [\n -83.9959716796875,\n 42.76465818533266\n ],\n [\n -84.57550048828125,\n 42.76465818533266\n ],\n [\n -84.57550048828125,\n 42.48526384858916\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Science Center
U.S. Geological Survey
6460 Busch Blvd., Suite 100
Columbus, OH 43229
The factors that set range limits for animal populations can inform management plans aimed at maintaining regional biodiversity. We examine abiotic and biotic drivers of the distribution of finescale dace (Chrosomus neogaeus) in two Great Plains basins to identify limiting factors for a threatened freshwater fish population at the edge of their range.
Great Plains, Nebraska, South Dakota and Wyoming, USA.
We investigated abiotic and biotic factors influencing the contemporary distribution of finescale dace in the Belle Fourche and Niobrara River basins with Random Forests classification models using fish surveys from multiple agencies spanning 2008–2019 and GIS-derived environmental data.
In both basins, finescale dace occurrence exhibited a nonlinear response to mean August water temperature. Abiotic covariates, including streamflow, water temperature and channel slope, were important limiting factors in the final model fit with Belle Fourche River basin surveys (n = 131). In contrast, a biotic covariate, native minnow richness, was the most important predictor of finescale dace occurrence in the Niobrara River basin model (n = 27). In the Niobrara River, native minnow richness was lower at sites with non-native northern pike (Esox lucius).
Basin-specific analyses revealed context dependencies for species–environment relationships, which can inform targeted restoration actions. Similar relationships between water temperature and finescale dace occurrence across both basins suggest summer thermal habitat as a regional limiting factor. The importance of biotic interactions in the Niobrara River highlights an emergent threat from invasive predators to a distinct assemblage of native prairie fishes.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13227","usgsCitation":"Booher, E., and Walters, A.W., 2021, Biotic and abiotic determinants of finescale dace distribution at the southern edge of their range: Diversity and Distributions, v. 27, no. 4, p. 696-709, https://doi.org/10.1111/ddi.13227.","productDescription":"14 p.","startPage":"696","endPage":"709","ipdsId":"IP-119393","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453583,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13227","text":"Publisher Index Page"},{"id":396435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska, South Dakota, Wyoming","otherGeospatial":"Belle Fourche River, Niobara River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.8,\n 42.132858175814626\n ],\n [\n -102.80731201171875,\n 42.132858175814626\n ],\n [\n -102.80731201171875,\n 42.7\n ],\n [\n -104.8,\n 42.7\n ],\n [\n -104.8,\n 42.132858175814626\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.94140625,\n 44.44358514592119\n ],\n [\n -103.53240966796875,\n 44.44358514592119\n ],\n [\n -103.53240966796875,\n 45\n ],\n [\n -104.94140625,\n 45\n ],\n [\n -104.94140625,\n 44.44358514592119\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Booher, Evan C. J.","contributorId":280044,"corporation":false,"usgs":false,"family":"Booher","given":"Evan C. J.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":835937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":835936,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218286,"text":"70218286 - 2021 - Multi‐constrained catchment scale optimization of groundwater abstraction using linear programming","interactions":[],"lastModifiedDate":"2021-08-03T13:34:47.019013","indexId":"70218286","displayToPublicDate":"2021-02-03T06:42:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Multi‐constrained catchment scale optimization of groundwater abstraction using linear programming","docAbstract":"Due to increasing water demands globally, freshwater ecosystems are under constant pressure. Groundwater resources, as the main source of accessible freshwater, are crucially important for irrigation worldwide. Over‐abstraction of groundwater leads to declines in groundwater levels; consequently, the groundwater inflow to streams decreases. The reduction in base flow and alteration of the stream flow regime can potentially have an adverse impact on groundwater‐dependent ecosystems. A spatially distributed, coupled groundwater‐surface water model can simulate the impacts of groundwater abstraction on aquatic ecosystems. A constrained optimization algorithm and a simulation model in combination can provide an objective tool for the water practitioner to evaluate the interplay between economic benefits of groundwater abstractions and requirements to environmental flow. In this study, a holistic catchment‐scale groundwater abstraction optimization framework has been developed that allows for a spatially explicit optimization of groundwater abstraction, while fulfilling a pre‐defined maximum allowed reduction of stream flow (base flow (Q95) or median flow (Q50)) as constraint criteria for 1484 stream locations across the catchment. A balanced K‐Means clustering method was implemented to reduce the computational burden of the optimization. The model parameters and observation uncertainties calculated based on Bayesian linear theory allow for a risk assessment on the optimized groundwater abstraction values. The results from different optimization scenarios indicated that using the linear programming optimization algorithm in conjunction with integrated models provides valuable information for guiding the water practitioners in designing an effective groundwater abstraction plan with the consideration of environmental flow criteria important for the ecological status of the entire system.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.13083","usgsCitation":"Danapour, M., Fienen, M., Hojberg, A.L., Jensen, K.H., and Stisen, S., 2021, Multi‐constrained catchment scale optimization of groundwater abstraction using linear programming: Groundwater, v. 59, no. 4, p. 503-516, https://doi.org/10.1111/gwat.13083.","productDescription":"14 p.","startPage":"503","endPage":"516","ipdsId":"IP-124860","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":383584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Danapour, Mehrdis 0000-0003-1877-0233","orcid":"https://orcid.org/0000-0003-1877-0233","contributorId":251915,"corporation":false,"usgs":false,"family":"Danapour","given":"Mehrdis","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":810824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hojberg, Anker Lajer","contributorId":251916,"corporation":false,"usgs":false,"family":"Hojberg","given":"Anker","email":"","middleInitial":"Lajer","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":810826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jensen, Karsten Hogh","contributorId":251917,"corporation":false,"usgs":false,"family":"Jensen","given":"Karsten","email":"","middleInitial":"Hogh","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":810827,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stisen, Simon","contributorId":251920,"corporation":false,"usgs":false,"family":"Stisen","given":"Simon","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":810828,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70218008,"text":"70218008 - 2021 - Body condition of wintering Pacific greater white-fronted geese","interactions":[],"lastModifiedDate":"2021-03-19T20:55:49.752814","indexId":"70218008","displayToPublicDate":"2021-02-02T13:22:52","publicationYear":"2021","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":"Body condition of wintering Pacific greater white-fronted geese","docAbstract":"Extreme changes to key waterfowl habitats in the Klamath Basin (KB) on the Oregon–California border and the Sacramento Valley (SV) in California, USA, have occurred since 1980. The spatial distribution of Pacific greater white‐fronted geese (Anser albifrons sponsa; geese) has likewise changed among these areas and population size has grown from 79,000 to >600,000 geese during the same period. To assess the effects of landscape changes and spatial‐temporal distribution of geese, we collected Pacific greater white‐fronted geese during winters of 2009–2010 and 2010–2011 in the KB and SV and compared their body condition to geese collected during 1979–1980 and 1980–1981. We modeled body and lipid mass to assess body condition for each sex independently and examined the influence of collection day, year, and region. Body condition of geese varied throughout the winter and within years in a nonlinear fashion. We detected an increase in body condition in both sexes during December and January in the SV, which corresponds with improved habitat conditions and increases seen in other species in the region. Body condition upon arrival in fall migration varied by year for females and by year and region for males. Males and females arrived in poorer body condition during 2010–2011 than all other study years and males in the KB during 2010–2011 had extremely low lipid mass, reflecting poor regional habitat conditions induced by drought. Body condition of females varied over spring, by year, and by region and regional effects were evident for males. Body condition was significantly higher for geese in the SV than in the KB during spring. Our results suggest that Pacific greater white‐fronted geese have adapted to a changing landscape and have adjusted historical spatial use patterns to take advantage of more favorable conditions in the SV between 1979 and 2010.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21997","usgsCitation":"Skalos, D., Eadie, J.M., Yparraguirre, D., Weaver, M.L., Oldenburger, S.L., Ely, C.R., Yee, J.L., and Fleskes, J., 2021, Body condition of wintering Pacific greater white-fronted geese: Journal of Wildlife Management, v. 85, no. 3, p. 484-497, https://doi.org/10.1002/jwmg.21997.","productDescription":"14 p.","startPage":"484","endPage":"497","ipdsId":"IP-116418","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":383221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath Basin, Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.44262695312501,\n 37.80544394934271\n ],\n [\n -120.794677734375,\n 37.80544394934271\n ],\n [\n -120.794677734375,\n 39.444677580473424\n ],\n [\n -122.44262695312501,\n 39.444677580473424\n ],\n [\n -122.44262695312501,\n 37.80544394934271\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.431640625,\n 41.51680395810118\n ],\n [\n -121.06933593749999,\n 41.51680395810118\n ],\n [\n -121.06933593749999,\n 42.52069952914966\n ],\n [\n -122.431640625,\n 42.52069952914966\n ],\n [\n -122.431640625,\n 41.51680395810118\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Skalos, Daniel A.","contributorId":250668,"corporation":false,"usgs":false,"family":"Skalos","given":"Daniel A.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":810205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eadie, John M.","contributorId":65219,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":7082,"text":"University of California - Davis","active":true,"usgs":false}],"preferred":false,"id":810206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yparraguirre, Daniel R.","contributorId":250671,"corporation":false,"usgs":false,"family":"Yparraguirre","given":"Daniel R.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":810207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weaver, Melanie L.","contributorId":250673,"corporation":false,"usgs":false,"family":"Weaver","given":"Melanie","email":"","middleInitial":"L.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":810208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oldenburger, Shaun L.","contributorId":177598,"corporation":false,"usgs":false,"family":"Oldenburger","given":"Shaun","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":810209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":810210,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":810211,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fleskes, Joseph P. 0000-0001-5388-6675","orcid":"https://orcid.org/0000-0001-5388-6675","contributorId":210345,"corporation":false,"usgs":false,"family":"Fleskes","given":"Joseph P.","affiliations":[],"preferred":false,"id":810212,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218835,"text":"70218835 - 2021 - Effect of nanoparticle size and natural organic matter composition on the bioavailability of polyvinylpyrrolidone- coated platinum nanoparticles to a model freshwater invertebrate","interactions":[],"lastModifiedDate":"2021-03-17T12:31:19.360902","indexId":"70218835","displayToPublicDate":"2021-02-02T07:27:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6491,"text":"Environ. Sci. Technol.","active":true,"publicationSubtype":{"id":10}},"title":"Effect of nanoparticle size and natural organic matter composition on the bioavailability of polyvinylpyrrolidone- coated platinum nanoparticles to a model freshwater invertebrate","docAbstract":"The bioavailability of dissolved Pt(IV) and polyvinylpyrrolidone-coated platinum nanoparticles (PtNPs) of five different nominal hydrodynamic diameters (20, 30, 50, 75, and 95 nm) was characterized in laboratory experiments using the model freshwater snail Lymnaea stagnalis. Dissolved Pt(IV) and all nanoparticle sizes were bioavailable to L. stagnalis. Platinum bioavailability, inferred from conditional uptake rate constants, was greater for nanoparticulate than dissolved forms and increased with increasing nanoparticle hydrodynamic diameter. The effect of natural organic matter (NOM) composition on PtNP bioavailability was evaluated using six NOM samples at two nanoparticle sizes (20 and 95 nm). NOM suppressed the bioavailability of 95 nm PtNPs in all cases, and DOM reduced sulfur content exhibited a positive correlation with 95 nm PtNP bioavailability. The bioavailability of 20 nm PtNPs was only suppressed by NOM with a low reduced sulfur content. The physiological elimination of Pt accumulated after dissolved Pt(IV) exposure was slow and constant. In contrast, the elimination of Pt accumulated after PtNP exposures exhibited a triphasic pattern likely involving in vivo PtNP dissolution. This work highlights the importance of PtNP size and interfacial interactions with NOM on Pt bioavailability and suggests that in vivo PtNP transformations could yield unexpectedly higher adverse effects to organisms than dissolved exposure alone.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c05985","usgsCitation":"Sikder, M., Croteau, M.N., Poulin, B., and Baalousha, M., 2021, Effect of nanoparticle size and natural organic matter composition on the bioavailability of polyvinylpyrrolidone- coated platinum nanoparticles to a model freshwater invertebrate: Environ. Sci. Technol., v. 55, no. 4, p. 2452-2461, https://doi.org/10.1021/acs.est.0c05985.","productDescription":"10 p.","startPage":"2452","endPage":"2461","ipdsId":"IP-121039","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":436523,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G18URX","text":"USGS data release","linkHelpText":"Laboratory data to assess the effect of nanoparticle size and natural organic matter composition on the bioavailability of platinum nanoparticles to a model freshwater invertebrate species"},{"id":384450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Sikder, Mithun 0000-0002-6295-0939","orcid":"https://orcid.org/0000-0002-6295-0939","contributorId":255449,"corporation":false,"usgs":false,"family":"Sikder","given":"Mithun","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":812372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":812373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":812374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baalousha, Mohammed 0000-0001-7491-4954","orcid":"https://orcid.org/0000-0001-7491-4954","contributorId":255450,"corporation":false,"usgs":false,"family":"Baalousha","given":"Mohammed","email":"","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":812375,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228521,"text":"70228521 - 2021 - In-situ monitoring of infiltration-induced instability of I-70 embankment west of the Eisenhower-Johnson Memorial Tunnels, phase III","interactions":[],"lastModifiedDate":"2022-02-14T16:58:12.573395","indexId":"70228521","displayToPublicDate":"2021-02-01T14:43:21","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":10112,"text":"Colorado Department of Transportation Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"2021-08","title":"In-situ monitoring of infiltration-induced instability of I-70 embankment west of the Eisenhower-Johnson Memorial Tunnels, phase III","docAbstract":"A new methodology that uses recent advances in unsaturated soil mechanics and hydrology was developed and tested. The approach consists of using soil suction and moisture content field information in the prediction of the likelihood of landslide movement. The testing ground was an active landslide on I-70 west of the Eisenhower/Johnson Memorial Tunnels. A joint effort between Colorado School of Mines, CDOT, and USGS performed detailed site characterization, set up and calibrated a hydro-mechanical model of the site based on seven years of field data, and performed a stability analysis of the slope. Results indicate that consecutive years of high or low infiltration have a compounding effect so that the slope stability is influenced by the preceding years. Additionally, a new drainage system is proposed based on analysis of the current horizontal drains.
","language":"English","publisher":"Colorado Department of Transportation","usgsCitation":"Wayllace, A., Lu, N., and Mirus, B., 2021, In-situ monitoring of infiltration-induced instability of I-70 embankment west of the Eisenhower-Johnson Memorial Tunnels, phase III: Colorado Department of Transportation Report 2021-08, 84 p.","productDescription":"84 p.","ipdsId":"IP-126891","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":395894,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395834,"type":{"id":11,"text":"Document"},"url":"https://www.codot.gov/programs/research/pdfs/2021/in-situ-monitoring-of-infiltration-induced-instability-of-i-70-embankment-west-of-the-eisenhower-johnson-memorial-tunnels-phase-iii.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Straight Creek slide location","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.96334934234619,\n 39.67218123730546\n ],\n [\n -105.95322132110596,\n 39.67218123730546\n ],\n [\n -105.95322132110596,\n 39.678853450286766\n ],\n [\n -105.96334934234619,\n 39.678853450286766\n ],\n [\n -105.96334934234619,\n 39.67218123730546\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wayllace, Alexandra","contributorId":203213,"corporation":false,"usgs":false,"family":"Wayllace","given":"Alexandra","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":834488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Ning","contributorId":267914,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":834489,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":267912,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":834490,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70230771,"text":"70230771 - 2021 - Fluid-earthquake and earthquake-earthquake interactions in southern Kansas, USA","interactions":[],"lastModifiedDate":"2022-04-26T15:36:02.791587","indexId":"70230771","displayToPublicDate":"2021-02-01T10:28:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Fluid-earthquake and earthquake-earthquake interactions in southern Kansas, USA","docAbstract":"An increase in injection activity associated with energy production in southern Kansas starting in 2013 has been linked to the occurrence of more than 130,000 earthquakes (M −1.5 to 4.9) between 2014 and 2017. Studies suggest that the dramatic increase in seismicity rate is related to wastewater injection into the highly permeable Arbuckle formation. Most of the seismicity is located in the underlying crystalline basement, for which hydrological properties and specific fault geometries are unknown. Additionally, some earthquake clusters occurred relatively far (tens of kilometers) from the main injection wells. Therefore, the effect of pore pressure diffusion may be insufficient to explain the relation between the volume of injected fluids and the spatiotemporal evolution of seismicity. Combining physical models (static stress and poroelasticity) and a statistical cluster analysis applied to a high-resolution relocated catalog, we analyze the evolution of seismicity in southern Kansas. We find that pore pressure changes (Δp) and Coulomb stress changes (ΔCFS) due to fluid diffusion smaller than 0.1 MPa are enough to initiate seismic sequences, which then evolve depending on their distance from the major injection wells. However, we find that earthquake sequences have different seismogenic responses to Δp and ΔCFS in terms of triggering threshold. In regions located close to disposal wells (Harper area) our cluster analysis suggests that both earthquake interactions and fluid diffusion control the evolution of seismicity. On the other hand, at greater distances (Milan area), where clustering behavior suggests greater earthquake interactions, we find that coseismic ΔCFS are larger than Δp.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020384","usgsCitation":"Verdecchia, A., Cochran, E.S., and Harrington, R.M., 2021, Fluid-earthquake and earthquake-earthquake interactions in southern Kansas, USA: JGR Solid Earth, v. 126, e2020JB020384, 17 p., https://doi.org/10.1029/2020JB020384.","productDescription":"e2020JB020384, 17 p.","ipdsId":"IP-124580","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":453604,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jb020384","text":"Publisher Index Page"},{"id":399674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.3,\n 36.75\n ],\n [\n -97.2,\n 36.75\n ],\n [\n -97.2,\n 37.5\n ],\n [\n -98.3,\n 37.5\n ],\n [\n -98.3,\n 36.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","noUsgsAuthors":false,"publicationDate":"2021-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Verdecchia, A.","contributorId":221418,"corporation":false,"usgs":false,"family":"Verdecchia","given":"A.","affiliations":[{"id":40369,"text":"Institute of Geology, Mineralogy and Geophysics, Ruhr-University Bochum, Bochum, Germany; Department of Earth and Environmental Sciences, Ludwig-Maximilians University, Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":841338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":841339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrington, R. M","contributorId":156299,"corporation":false,"usgs":false,"family":"Harrington","given":"R.","email":"","middleInitial":"M","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":841340,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70229038,"text":"70229038 - 2021 - Sex-specific behaviors of hunted mule deer during rifle season","interactions":[],"lastModifiedDate":"2022-02-28T16:31:15.834673","indexId":"70229038","displayToPublicDate":"2021-02-01T10:19:26","publicationYear":"2021","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":"Sex-specific behaviors of hunted mule deer during rifle season","docAbstract":"Animal populations face increased threats to mobility and access to critical habitat from a variety of human disturbances including roads, residential development, agriculture, and energy development. Disturbance from human hunting is known to alter habitat use in ungulates, but recent work suggests that hunting may also trigger the onset of migration. Whether this holds true across ungulate species and hunting systems warrants further empirical testing. We used global positioning system location data from mule deer (Odocoileus hemionus) in south-central Wyoming, USA, to evaluate the sex-specific effects of hunting on habitat selection and migratory behavior from 2016 to 2018. We modeled habitat selection before and during hunting season using a step selection function, and we used time-to-event models to evaluate if hunting triggered migration. We found habitat selection and migration timing to be sex specific. Males responded to hunting season by selecting security habitat away from motorized routes, whereas females used habitat through hunting season that retained higher forage quality. Weather, as indexed by temperature and precipitation (i.e., snowfall), influenced migration timing for males and females. Migration timing in males was influenced by migration distance, where individuals traveling >50 km tended to migrate earlier than individuals moving <50 km. For deer that survived to rifle season, hunting was less influential on migration timing than environmental factors. Rifle season increased the likelihood of migration by 2% in females and <0.01% in males compared to outside rifle season. Our findings suggest that roadless areas on mule deer summer ranges and within migration corridors reduce the effects of hunting disturbance. Consequently, managers may consider limiting the use of motorized vehicles as a method for reducing effects on migration from hunting disturbance.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21988","usgsCitation":"Rodgers, P.A., Sawyer, H., Mong, T.W., Stephens, S., and Kauffman, M., 2021, Sex-specific behaviors of hunted mule deer during rifle season: Journal of Wildlife Management, v. 85, no. 2, p. 215-227, https://doi.org/10.1002/jwmg.21988.","productDescription":"13 p.","startPage":"215","endPage":"227","ipdsId":"IP-123653","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.885498046875,\n 39.35129035526705\n ],\n [\n -105.325927734375,\n 39.35129035526705\n ],\n [\n -105.325927734375,\n 42.67435857693381\n ],\n [\n -108.885498046875,\n 42.67435857693381\n ],\n [\n -108.885498046875,\n 39.35129035526705\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-12-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Rodgers, Patrick A.","contributorId":286877,"corporation":false,"usgs":false,"family":"Rodgers","given":"Patrick","email":"","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":836491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":836338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mong, Tony W.","contributorId":243064,"corporation":false,"usgs":false,"family":"Mong","given":"Tony","email":"","middleInitial":"W.","affiliations":[{"id":48630,"text":"wy gF","active":true,"usgs":false}],"preferred":false,"id":836339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephens, Sam","contributorId":286876,"corporation":false,"usgs":false,"family":"Stephens","given":"Sam","email":"","affiliations":[{"id":34137,"text":"Wyoming Fish and Game Department","active":true,"usgs":false}],"preferred":false,"id":836340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":836337,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236572,"text":"70236572 - 2021 - Sea state from single optical images: A methodology to derive wind-generated ocean waves from cameras, drones and satellites","interactions":[],"lastModifiedDate":"2022-09-12T14:24:33.012692","indexId":"70236572","displayToPublicDate":"2021-02-01T09:09:21","publicationYear":"2021","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":"Sea state from single optical images: A methodology to derive wind-generated ocean waves from cameras, drones and satellites","docAbstract":"Sea state is a key variable in ocean and coastal dynamics. The sea state is either sparsely\nmeasured by wave buoys and satellites or modelled over large scales. Only a few attempts have been devoted to sea state measurements covering a large domain; in particular its estimation from optical images. With optical technologies becoming omnipresent, optical images offer incomparable spatial resolution from diverse sensors such as shore-based cameras, airborne drones (unmanned aerial vehicles/UAVs), or satellites. Here, we present a standalone methodology to derive the water surface elevation anomaly induced by wind-generated ocean waves from optical imagery. The methodology was tested on drone and satellite images and compared against ground truth. The results show a clear dependence on the relative azimuth view angle in relation to the wave crest. A simple correction is proposed to overcome this bias. Overall, the presented methodology offers a practical way of estimating ocean waves for a wide range of applications.","language":"English","publisher":"MDPI","doi":"10.3390/rs13040679","usgsCitation":"Almar, R., Bergsma, E.W., Catalan, P.A., Cienfuegos, R., Suarez, L., Lucero, F., Lerma, A.N., Desmazes, F., Perugini, E., Palmsten, M.L., and Chickadel, C., 2021, Sea state from single optical images: A methodology to derive wind-generated ocean waves from cameras, drones and satellites: Remote Sensing, v. 13, no. 4, 679, 8 p., https://doi.org/10.3390/rs13040679.","productDescription":"679, 8 p.","ipdsId":"IP-126573","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":453613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13040679","text":"Publisher Index Page"},{"id":406532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Almar, Rafael","contributorId":296397,"corporation":false,"usgs":false,"family":"Almar","given":"Rafael","email":"","affiliations":[{"id":64029,"text":"LEGOS (CNRS/IRD/CNES/Université de Toulouse), Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":851414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergsma, Erwin W. 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Interactions among these drivers can lead to complex and non-linear changes in island morphology and transitions between migrational, erosional, or progradational states. This study seeks to constrain the morphologic consequences of barrier islands migrating across complex antecedent topography in response to rising sea level. The stratigraphy of four barrier-backbarrier systems along the U.S. Mid-Atlantic coast informs idealized geometries of diverse antecedent substrate. These outcomes are integrated into a cross-shore morphodynamic model of barrier-island migration to quantify the influence of this antecedent geology on barrier-retreat behavior. Additionally, this study explores the future response of specific barrier islands to various rates of sea-level rise over multi-decadal to millennial timescales. The results show antecedent substrate slope plays a central role in barrier morphodynamic behaviour. In particular, migration across a subaqueous backbarrier ridge (e.g., coastal barrier or dune deposits from earlier sea-level highstands) can cause a succession of phase changes in a modern island. For example, the case studies illustrate the steep slopes and decreased backbarrier accommodation associated with antecedent highs greater than 3 m in profile can greatly reduce island migration rates, effectively “pinning” the island in place, even with sea-level rise rates up to 6 mm yr-1. However, once the island migrates over the high, backbarrier accommodation increases, leading to enhanced overwash fluxes, more rapid landward migration, and possible drowning. Additionally, the results indicate that antecedent substrate may slow barrier-island migration by providing sediment through both shoreface and inlet processes. The field and modelling insights from this study are presented as a conceptual model of the relative influence of various antecedent features on barrier-island dynamics along sandy, siliciclastic coasts.","language":"English","publisher":"Wiley","doi":"10.1111/sed.12798","usgsCitation":"Shawler, J.L., Ciarletta, D.J., Connell, J.E., Boggs, B.Q., Lorenzo-Trueba, J., and Hein, C.J., 2021, Relative influence of antecedent topography and sea-level rise on barrier-island migration: Sedimentology, v. 68, no. 2, p. 639-669, https://doi.org/10.1111/sed.12798.","productDescription":"31 p.","startPage":"639","endPage":"669","ipdsId":"IP-118839","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":406531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New Jersey, Virginia","otherGeospatial":"Assateague Island, Brigantine Island, Cedar Island, Edwin B. Forsythe National Wildlife Refuge, Little Beach Island, Parramore Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.45331573486328,\n 39.42452501272267\n ],\n [\n -74.29092407226562,\n 39.42452501272267\n ],\n [\n -74.29092407226562,\n 39.504305605954634\n ],\n [\n -74.45331573486328,\n 39.504305605954634\n ],\n [\n -74.45331573486328,\n 39.42452501272267\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.25875091552734,\n 38.19421209045785\n ],\n [\n -75.13206481933594,\n 38.19421209045785\n ],\n [\n -75.13206481933594,\n 38.241955275979336\n ],\n [\n -75.25875091552734,\n 38.241955275979336\n ],\n [\n -75.25875091552734,\n 38.19421209045785\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.69236755371094,\n 37.60253625794439\n ],\n [\n -75.58422088623047,\n 37.60253625794439\n ],\n [\n -75.58422088623047,\n 37.67213612088675\n ],\n [\n -75.69236755371094,\n 37.67213612088675\n ],\n [\n -75.69236755371094,\n 37.60253625794439\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.73322296142578,\n 37.51217686964284\n ],\n [\n -75.58868408203125,\n 37.51217686964284\n ],\n [\n -75.58868408203125,\n 37.599816190326464\n ],\n [\n -75.73322296142578,\n 37.599816190326464\n ],\n [\n -75.73322296142578,\n 37.51217686964284\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"68","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Shawler, Justin L.","contributorId":256701,"corporation":false,"usgs":false,"family":"Shawler","given":"Justin","email":"","middleInitial":"L.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":851438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":851439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connell, Jennifer E.","contributorId":296407,"corporation":false,"usgs":false,"family":"Connell","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":851440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boggs, Bianca Q.","contributorId":296408,"corporation":false,"usgs":false,"family":"Boggs","given":"Bianca","email":"","middleInitial":"Q.","affiliations":[{"id":57314,"text":"William & Mary","active":true,"usgs":false}],"preferred":false,"id":851441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lorenzo-Trueba, Jorge 0000-0002-7082-7762","orcid":"https://orcid.org/0000-0002-7082-7762","contributorId":203269,"corporation":false,"usgs":false,"family":"Lorenzo-Trueba","given":"Jorge","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":851442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hein, Christopher J.","contributorId":256702,"corporation":false,"usgs":false,"family":"Hein","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":851443,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70229121,"text":"70229121 - 2021 - Learning augmented methods for matching: Improving invasive species management and urban mobility","interactions":[],"lastModifiedDate":"2022-03-01T14:43:16.295732","indexId":"70229121","displayToPublicDate":"2021-02-01T08:24:39","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Learning augmented methods for matching: Improving invasive species management and urban mobility","docAbstract":"With the success of machine learning, integrating learned models into real-world systems has become a critical chal- lenge. Naively applying predictions to combinatorial opti- mization problems can incur high costs, which has motivated researchers to consider learning augmented algorithms that can make use of faulty or incomplete predictions. Inspired by two matching problems in computational sustainability where data are abundant, we consider the learning augmented min weight matching problem where some nodes are revealed\n \nonline while others are known a priori, e.g., by being pre- dicted by machine learning. We develop an algorithm that is able to make use of this extra information and provably im- proves upon pessimistic online algorithms. We evaluate our algorithm on two settings from computational sustainability\n– the coordination of opportunistic citizen scientists for inva- sive species management and the matching between taxis and riders under uncertain trip duration predictions. In both cases, we perform extensive experiments on real-world datasets and find that our method outperforms baselines, showing how learning augmented algorithms can reliably improve solu- tions for problems in computational sustainability","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the AAAI conference on artificial intelligence","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"AAAI conference on artificial intelligence","conferenceDate":"February 2-9, 2021","conferenceLocation":"Online","language":"English","publisher":"Association for the Advancement of Artificial Intelligence","usgsCitation":"Bjorck, J., Shi, Q., Brown-Lima, C., Dean, J., Fuller, A.K., and Gomes, C., 2021, Learning augmented methods for matching: Improving invasive species management and urban mobility, in Proceedings of the AAAI conference on artificial intelligence, v. 35, no. 17, Online, February 2-9, 2021, p. 14702-14710.","productDescription":"9 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York\",\"nation\":\"USA \"}}]}","volume":"35","issue":"17","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bjorck, Johan","contributorId":287218,"corporation":false,"usgs":false,"family":"Bjorck","given":"Johan","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Qinru","contributorId":269685,"corporation":false,"usgs":false,"family":"Shi","given":"Qinru","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836570,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown-Lima, Carrie","contributorId":236893,"corporation":false,"usgs":false,"family":"Brown-Lima","given":"Carrie","email":"","affiliations":[],"preferred":false,"id":836572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dean, Jennifer","contributorId":287223,"corporation":false,"usgs":false,"family":"Dean","given":"Jennifer","email":"","affiliations":[{"id":61506,"text":"New York Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":836571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gomes, Carla","contributorId":274582,"corporation":false,"usgs":false,"family":"Gomes","given":"Carla","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836574,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230071,"text":"70230071 - 2021 - Applications of bistatic radar to volcano topography – A review of 10 years of TanDEM-X","interactions":[],"lastModifiedDate":"2022-03-28T13:24:28.710009","indexId":"70230071","displayToPublicDate":"2021-02-01T08:20:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Applications of bistatic radar to volcano topography – A review of 10 years of TanDEM-X","docAbstract":"The TanDEM-X satellite mission has revolutionized DEM generation from spaceborne synthetic aperture radar. In addition to the primary objective of generating a consistent digital elevation model with global coverage and unprecedented accuracy, the mission has acquired time series of topographic data over several volcanoes, providing an excellent opportunity to test the use of this innovative dataset for volcano monitoring and research. In this article, we review the utilization of the single-pass TanDEM-X data for studying various kinds of volcanic activity, such as basaltic lava flows, the formation and destruction of lava domes and related pyroclastic density currents, and subsurface magma withdrawal and intrusion. We then consider the uses of these data for hazard assessment and forecasting. Our goal is to highlight the importance of timely and repeated topographic information in volcanology, and to suggest the development of future spaceborne bistatic synthetic aperture radar satellite missions, such as ESA's Earth Explorer 10 candidate mission, “Harmony.”
","language":"English","publisher":"Institute of Electrical and Electronics Engineers (IEEE)","doi":"10.1109/JSTARS.2021.3055653","usgsCitation":"Kubanek, J., Poland, M., and Biggs, J., 2021, Applications of bistatic radar to volcano topography – A review of 10 years of TanDEM-X: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 14, p. 3282-3302, https://doi.org/10.1109/JSTARS.2021.3055653.","productDescription":"21 p.","startPage":"3282","endPage":"3302","ipdsId":"IP-122045","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1109/jstars.2021.3055653","text":"Publisher Index Page"},{"id":397687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kubanek, Julia","contributorId":289336,"corporation":false,"usgs":false,"family":"Kubanek","given":"Julia","email":"","affiliations":[{"id":62103,"text":"ESTEC, European Space Agency","active":true,"usgs":false}],"preferred":false,"id":838944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":838946,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70218814,"text":"70218814 - 2021 - Extrinsically reinforced hybrid speciation within Holarctic ermine (Mustela spp.) produces an insular endemic","interactions":[],"lastModifiedDate":"2021-03-15T13:04:34.193849","indexId":"70218814","displayToPublicDate":"2021-02-01T07:59:31","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Extrinsically reinforced hybrid speciation within Holarctic ermine (Mustela spp.) produces an insular endemic","docAbstract":"Refugial isolation during glaciation is an established driver of speciation; however, the opposing role of interglacial population expansion, secondary contact, and gene flow on the diversification process remains less understood. The consequences of glacial cycling on diversity are complex and especially so for archipelago species, which experience dramatic fluctuations in connectivity in response to both lower sea levels during glacial events and increased fragmentation during glacial recession. We test whether extended refugial isolation has led to the divergence of genetically and morphologically distinct species within Holarctic ermine (Mustela erminea), a small cosmopolitan carnivore species that harbours 34 extant subspecies, 14 of which are insular endemics.
Holarctic.
We use genetic sequences (complete mitochondrial genomes, four nuclear genes) from >100 ermine (stoats) and geometric morphometric data for >200 individuals (27 of the 34 extant subspecies) from across their Holarctic range to provide an integrative perspective on diversification and endemism across this complex landscape. Multiple species delimitation methods (iBPP, bPTP) assessed congruence between morphometric and genetic data.
Our results support the recognition of at least three species within the M. erminea complex, coincident with three of four genetic clades, tied to diversification in separate glacial refugia. We found substantial geographic variation within each species, with geometric morphometric results largely consistent with historical infraspecific taxonomy.
Phylogeographic structure mirrors patterns of diversification in other Holarctic species, with a major Nearctic‐Palearctic split, but with greater intraspecific morphological diversity. Recognition of insular endemic species M. haidarum is consistent with a deep history of refugial persistence and highlights the urgency of mindful management of island populations along North America's North Pacific Coast. Significant environmental modification (e.g. industrial‐scale logging, mining) has been proposed for a number of these islands, which may elevate the risk of extinction of insular palaeoendemics.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13234","usgsCitation":"Colella, J.P., Frederick, L., Talbot, S.L., and Cook, J., 2021, Extrinsically reinforced hybrid speciation within Holarctic ermine (Mustela spp.) produces an insular endemic: Diversity and Distributions, v. 27, no. 4, p. 747-762, https://doi.org/10.1111/ddi.13234.","productDescription":"16 p.","startPage":"747","endPage":"762","ipdsId":"IP-106752","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":487317,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13234","text":"Publisher Index Page"},{"id":436524,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97INKCG","text":"USGS data release","linkHelpText":"Sequence Information from the Mitogenome and Four Nuclear Genes from Holarctic Ermine (Mustela spp.)"},{"id":384376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Colella, Jocelyn P.","contributorId":190332,"corporation":false,"usgs":false,"family":"Colella","given":"Jocelyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":812151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frederick, Lindsey","contributorId":255345,"corporation":false,"usgs":false,"family":"Frederick","given":"Lindsey","email":"","affiliations":[{"id":18859,"text":"Department of Biology and Museum of Southwestern Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":812152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":812153,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Joe","contributorId":255346,"corporation":false,"usgs":false,"family":"Cook","given":"Joe","email":"","affiliations":[{"id":18859,"text":"Department of Biology and Museum of Southwestern Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":812154,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222491,"text":"70222491 - 2021 - Time since burning and rainfall characteristics impact post-fire debris flow initiation and magnitude","interactions":[],"lastModifiedDate":"2021-07-30T13:00:46.620849","indexId":"70222491","displayToPublicDate":"2021-02-01T07:58:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9124,"text":"Environmental Engineering and Geology","active":true,"publicationSubtype":{"id":10}},"title":"Time since burning and rainfall characteristics impact post-fire debris flow initiation and magnitude","docAbstract":"The extreme heat from wildfire alters soil properties and incinerates vegetation, leading to changes in infiltration capacity, ground cover, soil erodibility, and rainfall interception. These changes promote elevated rates of runoff and sediment transport that increase the likelihood of runoff-generated debris flows. Debris flows are most common in the year immediately following wildfire, but temporal changes in the likelihood and magnitude of debris flows following wildfire are not well constrained. In this study, we combine measurements of soil-hydraulic properties with vegetation survey data and numerical modeling to understand how debris-flow threats are likely to change in steep, burned watersheds during the first 3 years of recovery. We focus on documenting recovery following the 2016 Fish Fire in the San Gabriel Mountains, California, and demonstrate how a numerical model can be used to predict temporal changes in debris-flow properties and initiation thresholds. Numerical modeling suggests that the 15-minute intensity-duration (ID) threshold for debris flows in post-fire year 1 can vary from 15 to 30 mm/hr, depending on how rainfall is temporally distributed within a storm. Simulations further demonstrate that expected debris-flow volumes would be reduced by more than a factor of three following 1 year of recovery and that the 15-minute rainfall ID threshold would increase from 15 to 30 mm/hr to greater than 60 mm/hr by post-fire year 3. These results provide constraints on debris-flow thresholds within the San Gabriel Mountains and highlight the importance of considering local rainfall characteristics when using numerical models to assess debris-flow and flood potential.
Endocrine-disrupting compounds (EDCs), specifically estrogenic endocrine-disrupting compounds, vary in concentration and composition in surface waters under the influence of different landscape sources and landcover gradients. Estrogenic activity in surface waters may lead to adverse effects in aquatic species at both individual and population levels, often observed through the presence of intersex and vitellogenin induction in male fish. In the Chesapeake Bay Watershed, located on the mid-Atlantic coast of the USA, intersex has been observed in several sub-watersheds where previous studies have identified specific landscape sources of EDCs in tandem with observed fish health effects. Previous work in the Potomac River Watershed (PRW), the largest basin within the Chesapeake Bay Watershed, was leveraged to build random forest regression models to predict estrogenic activity at unsampled reaches in both the Potomac River and larger Chesapeake Bay Watersheds (CBW). Model outputs including important variables, partial dependence plots, and predicted values of estrogenic activity at unsampled reaches provide insight into drivers of estrogenic activity at different seasons and scales. Using the US Environmental Protection Agency effects-based threshold of 1.0 ng/L 17 β-estradiol equivalents, catchments predicted to exceed this value were categorized as at risk for adverse effects from exposure to estrogenic compounds and evaluated relative to healthy watersheds and recreation access locations throughout the PRW. Results show immediate catchment scale models are more reliable than upstream models, and the best predictive variables differ by season and scale. A small percentage of healthy watersheds (< 13%) and public access sites were classified as at risk using the “Total” (annual) model in the CBW. This study is the first Potomac River Watershed assessment of estrogenic activity, providing a new foundation for future risk assessment and management design efforts, with additional context provided for the entire Chesapeake Bay Watershed.
As permafrost thaws in the Arctic, new subsurface pathways open for the transport of groundwater, energy, and solutes. We identify different ways that these subsurface changes are driving observed surface consequences, including the potential for increased contaminant transport, modification to water resources, and enhanced rates of infrastructure (e.g. buildings and roads) damage. Further, as permafrost thaws it allows groundwater to transport carbon, nutrients, and other dissolved constituents from terrestrial to aquatic environments via progressively deeper subsurface flow paths. Cryohydrogeology, the study of groundwater in cold regions, should be included in northern research initiatives to account for this hidden catalyst of environmental and societal change.
","language":"English","publisher":"Copernicus","doi":"10.5194/tc-15-479-2021","usgsCitation":"McKenzie, J.M., Kurylyk, B.L., Walvoord, M.A., Bense, V.F., Fortier, D., Spence, C., and Grenier, C., 2021, Invited perspective: What lies beneath a changing Arctic?: The Cryosphere, v. 15, p. 479-484, https://doi.org/10.5194/tc-15-479-2021.","productDescription":"6 p.","startPage":"479","endPage":"484","ipdsId":"IP-099776","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":453634,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-15-479-2021","text":"Publisher Index Page"},{"id":382873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","noUsgsAuthors":false,"publicationDate":"2021-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":809556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":809557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":809558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bense, Victor F.","contributorId":248636,"corporation":false,"usgs":false,"family":"Bense","given":"Victor","email":"","middleInitial":"F.","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":809559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fortier, Daniel","contributorId":194641,"corporation":false,"usgs":false,"family":"Fortier","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":809560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spence, Chris","contributorId":248637,"corporation":false,"usgs":false,"family":"Spence","given":"Chris","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":809561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grenier, Christophe","contributorId":248640,"corporation":false,"usgs":false,"family":"Grenier","given":"Christophe","email":"","affiliations":[{"id":49963,"text":"Université Paris-Saclay","active":true,"usgs":false}],"preferred":false,"id":809562,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70218232,"text":"70218232 - 2021 - Biological and chemical recovery of acidified Catskill Mountain streams in response to the Clean Air Act Amendments of 1990","interactions":[],"lastModifiedDate":"2021-02-19T17:52:29.548291","indexId":"70218232","displayToPublicDate":"2021-01-31T11:47:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Biological and chemical recovery of acidified Catskill Mountain streams in response to the Clean Air Act Amendments of 1990","docAbstract":"Decades of acidic deposition have adversely affected aquatic and terrestrial ecosystems in acid-sensitive watersheds in parts of the eastern United States. The national Acid Rain Program (Title IV of the 1990 Clean Air Act Amendments - CAAA) helped reduce emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) and resulted in sharp decreases in the acidity of atmospheric deposition. The decrease in acidic deposition produced a steady decline in the acidity of streams in many poorly buffered waters across the western Adirondacks and parts of the Catskill Mountains of New York. Until recently, however, there has been little evidence of biological recovery in most acid-sensitive streams in both regions. Long-term deposition and stream-chemistry records and fish-community data from quantitative surveys done during 1991–93 and again during 2012–19 at 13 sites in the upper Neversink River and its tributaries were evaluated to determine if chemical and biological recovery were evident in this Catskill Mountain watershed and if they could be linked to regional declines in acidic deposition. Between 1991 and 2019, large decreases in sulfate and nitrate deposition in the basin mirrored declines in total nationwide SO2 and NOx emissions. There were corresponding decreases in sulfate and nitrate concentrations in deposition at a National Trends Network station at Frost Valley (NY68) and coincident declines in sulfate concentrations at four long-term monitoring sites in the Neversink River watershed. Mean acid neutralizing capacity and pH increased and inorganic aluminum (Ali) concentrations from routine summertime samples decreased significantly at most moderately to severely acidified sites between the two study periods. Richness, density, and biomass of fish communities increased at most sites, while the density and biomass of brook trout Salvelinus fontinalis populations increased at fewer sites that were undergoing chemical recovery. Although recovery is far from complete, trends in deposition chemistry, water quality, and fish assemblages in streams of the upper Neversink watershed indicate that the 1990 CAAA is having positive impacts on aquatic ecosystems in the Catskill Mountain region, New York.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2021.118235","usgsCitation":"Baldigo, B.P., George, S.D., Winterhalter, D., and McHale, M., 2021, Biological and chemical recovery of acidified Catskill Mountain streams in response to the Clean Air Act Amendments of 1990: Atmospheric Environment, v. 249, 118235, 18 p., https://doi.org/10.1016/j.atmosenv.2021.118235.","productDescription":"118235, 18 p.","ipdsId":"IP-121887","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":453636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2021.118235","text":"Publisher Index Page"},{"id":383377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Neversink watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.63973999023438,\n 41.81175536180908\n ],\n [\n -74.53399658203125,\n 41.873139978873574\n ],\n [\n -74.4275665283203,\n 41.937019660425264\n ],\n [\n -74.33967590332031,\n 41.963064211132306\n ],\n [\n -74.28680419921875,\n 42.039094188385945\n ],\n [\n -74.34104919433594,\n 42.10382653879911\n ],\n [\n -74.40696716308594,\n 42.11859868281563\n ],\n [\n -74.45571899414062,\n 42.08395512413707\n ],\n [\n -74.62806701660156,\n 41.95080927751363\n ],\n [\n -74.70291137695312,\n 41.86700416724044\n ],\n [\n -74.67750549316406,\n 41.81021999190292\n ],\n [\n -74.63973999023438,\n 41.81175536180908\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"249","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winterhalter, Dylan R. 0000-0003-1774-8034","orcid":"https://orcid.org/0000-0003-1774-8034","contributorId":251765,"corporation":false,"usgs":true,"family":"Winterhalter","given":"Dylan R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810547,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810548,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221208,"text":"70221208 - 2021 - Beware of spatial autocorrelation when applying machine learning algorithms to borehole geophysical logs","interactions":[],"lastModifiedDate":"2021-06-07T12:36:39.054303","indexId":"70221208","displayToPublicDate":"2021-01-31T07:34:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Beware of spatial autocorrelation when applying machine learning algorithms to borehole geophysical logs","docAbstract":"Although many of the algorithms now considered to be machine learning algorithms (MLAs) have existed for nearly a century (e.g., Rosenblatt 1958), interest in MLAs has recently increased exponentially for solving data-driven problems across a variety of fields due to the expanded availability of large, complex datasets that may be difficult to interrogate using other methods, increases in computing power, and a growing library of easily implemented machine learning tools. While MLAs are often similar to statistical methods, there are key differences in the approach to problem solving. Namely, statistical methods are more concerned with generating informative models from “long” data (i.e., many more observations than explanatory variables), whereas MLAs are typically concerned with generating accurate predictions from “wide” data (i.e., a large number of variables with relatively fewer observations, Bzdok et al. 2018). In hydrogeologic studies, such wide datasets may be available from boreholes, where various types of geophysical, geochemical, and lithological information may exist. Borehole datasets are therefore a tempting target for MLAs to reveal hidden relations among gathered data and parameters of interest (e.g., contaminant concentration), and as a method of parameter reduction (e.g., reduce costs by collecting fewer datasets).
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.13081","usgsCitation":"Terry, N., Johnson, C., Day-Lewis, F., Parker, B.L., and Slater, L., 2021, Beware of spatial autocorrelation when applying machine learning algorithms to borehole geophysical logs: Groundwater, v. 59, no. 3, p. 315-319, https://doi.org/10.1111/gwat.13081.","productDescription":"5 p.","startPage":"315","endPage":"319","ipdsId":"IP-124633","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":436525,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TN8EC4","text":"USGS data release","linkHelpText":"Selected borehole geophysical logs from three contaminant sites in California, Wisconsin, and New Jersey"},{"id":386259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":817055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":817056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":817057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Beth L.","contributorId":209230,"corporation":false,"usgs":false,"family":"Parker","given":"Beth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":817058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Slater, Lee D. 0000-0003-0292-746X","orcid":"https://orcid.org/0000-0003-0292-746X","contributorId":192555,"corporation":false,"usgs":false,"family":"Slater","given":"Lee D.","affiliations":[],"preferred":false,"id":817059,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249479,"text":"70249479 - 2021 - Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","interactions":[],"lastModifiedDate":"2023-10-10T14:16:37.55892","indexId":"70249479","displayToPublicDate":"2021-01-30T09:10:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting","docAbstract":"Cleveland and Tana are remote volcanoes located in the central Aleutian volcanic arc on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband seismometers on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize seismicity beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of earthquake hypocenters, magnitudes, focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8 km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional seismic velocity model, are consistent with a shallow body of magma that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7 km northeast of Cleveland's summit at depths of 5 to 10 km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence magmatism and account for the multiple closely spaced volcanic centers in this region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107182","usgsCitation":"Power, J., Roman, D., Lyons, J.J., Haney, M.M., Rasmussen, D.J., Plank, T., Nicolaysen, K., Izbekov, P., Werner, C., and Kaufman, A., 2021, Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting: Journal of Volcanology and Geothermal Research, v. 412, 107182, 18 p., https://doi.org/10.1016/j.jvolgeores.2021.107182.","productDescription":"107182, 18 p.","ipdsId":"IP-121823","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453641,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107182","text":"Publisher Index Page"},{"id":421816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chuginadak Island, Cleveland Volcano, Tana Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -169.65098413866693,\n 52.904805932105404\n ],\n [\n -169.83106863712771,\n 52.8971644246661\n ],\n [\n -170.01036155537554,\n 52.86086066337441\n ],\n [\n -170.01669419707966,\n 52.78767701983992\n ],\n [\n -169.66364942207514,\n 52.76373370379605\n ],\n [\n -169.65098413866693,\n 52.904805932105404\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Power, John 0000-0002-7233-4398","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":215240,"corporation":false,"usgs":true,"family":"Power","given":"John","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":885874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885875,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":885876,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rasmussen, Daniel J.","contributorId":237828,"corporation":false,"usgs":false,"family":"Rasmussen","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Plank, Terry","contributorId":237829,"corporation":false,"usgs":false,"family":"Plank","given":"Terry","affiliations":[{"id":47619,"text":"Lamont-Doherty Earth Observatory, Columbia University, New York, NY 10027","active":true,"usgs":false}],"preferred":false,"id":885878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nicolaysen, K. 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