Keys to Clay-colored Sparrow (Spizella pallida) management include providing grasslands with a shrub or forb component or shrub-dominated edge habitat, which includes dense grass and moderately high litter cover, and avoiding disturbances that completely eliminate woody vegetation. Clay-colored Sparrows have been reported to use habitats with 20–186 centimeters (cm) average vegetation height, 3–50 cm visual obstruction reading, 15–74 percent grass cover, 5–23 percent forb cover, less than 30 percent shrub cover, 1–20 percent bare ground, 10–63 percent litter cover, and less than or equal to 5 cm litter depth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/pp1842Z","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Nenneman, M.P., and Euliss, B.R., 2023, The effects of management practices on grassland birds—Clay-colored Sparrow (Spizella pallida), chap. Z of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 27 p., https://doi.org/10.3133/pp1842Z.","productDescription":"v, 27 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097128","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":412290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/z/coverthb.jpg"},{"id":412291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/z/pp1842z.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842Z"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Acoustic communication in the form of songs is a learned behavior in oscine that can be passed down from one generation to the next through cultural transmission. Over time songs can change when populations become isolated from one another, creating dialects that are distinct to a population. Habitat fragmentation is an isolating mechanism that can influence differences in songs between populations when there is little to no connectivity between fragments and fragment size can influence diversity of song traits. We characterized and analyzed songs of the ‘ōma‘o (Myadestes obscurus) in a naturally fragmented forest to determine how landscape variables influenced song differences between populations. We chose five fragments of different sizes and isolation to record songs of the ‘ōma‘o. We performed a correlation test to evaluate whether there was a relationship between fragment size and total syllables, and between unique syllables and degree of isolation. We also conducted a Mantel test to determine if geographic distance had an influence on song similarity. Our results indicated that songs from larger fragments tended to have higher syllable diversity, but neither connectivity nor distance was related to the number of unique or shared syllables found within a fragment, respectively. Overall, the results indicated that ‘ōma‘o songs are highly variable at the individual level and that there may be little to no syllable sharing within and among populations.
","language":"English","publisher":"University of Hawaii Press","doi":"10.2984/76.3.6","usgsCitation":"Fernandez, N., Paxton, K.L., Paxton, E.H., Pack, A.A., and Hart, P.J., 2023, Landscape configuration influences Oma‘o (Myadestes obscurus) song diversity: Pacific Science, v. 76, p. 325-335, https://doi.org/10.2984/76.3.6.","productDescription":"11 p.","startPage":"325","endPage":"335","ipdsId":"IP-132856","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":420014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawai'i, Mauna Loa, Waiakea Forest Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.40,\n 19.70\n ],\n [\n -155.40,\n 19.60\n ],\n [\n -155.30,\n 19.60\n ],\n [\n -155.30,\n 19.70\n ],\n [\n -155.40,\n 19.70\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"76","edition":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fernandez, Nicole","contributorId":328627,"corporation":false,"usgs":false,"family":"Fernandez","given":"Nicole","email":"","affiliations":[{"id":37485,"text":"University of Hawai‘i - Hilo","active":true,"usgs":false}],"preferred":false,"id":880811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paxton, Kristina L. 0000-0003-2321-5090","orcid":"https://orcid.org/0000-0003-2321-5090","contributorId":41917,"corporation":false,"usgs":false,"family":"Paxton","given":"Kristina","email":"","middleInitial":"L.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":880812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":880813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pack, Adam A.","contributorId":204176,"corporation":false,"usgs":false,"family":"Pack","given":"Adam","email":"","middleInitial":"A.","affiliations":[{"id":36870,"text":"University of Hawai‘i Hilo","active":true,"usgs":false}],"preferred":false,"id":880814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":880815,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240951,"text":"70240951 - 2023 - Genetic diversity, structure, and effective population size of an endangered, endemic hoary bat, ʻōpeʻapeʻa, across the Hawaiian Islands","interactions":[],"lastModifiedDate":"2023-03-02T13:16:02.493245","indexId":"70240951","displayToPublicDate":"2023-01-25T07:13:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13441,"text":"Peer J","active":true,"publicationSubtype":{"id":10}},"title":"Genetic diversity, structure, and effective population size of an endangered, endemic hoary bat, ʻōpeʻapeʻa, across the Hawaiian Islands","docAbstract":"Island bat species are disproportionately at risk of extinction, and Hawaiʻi’s only native terrestrial land mammal, the Hawaiian hoary bat (Lasiurus semotus) locally known as ʻōpeʻapeʻa, is no exception. To effectively manage this bat species with an archipelago-wide distribution, it is important to determine the population size on each island and connectivity between islands. We used 18 nuclear microsatellite loci and one mitochondrial gene from 339 individuals collected from 1988–2020 to evaluate genetic diversity, population structure and estimate effective population size on the Islands of Hawaiʻi, Maui, Oʻahu, and Kauaʻi. Genetic differentiation occurred between Hawaiʻi and Maui, both of which were differentiated from Oʻahu and Kauaʻi. The population on Maui presents the greatest per-island genetic diversity, consistent with their hypothesized status as the original founding population. A signature of isolation by distance was detected between islands, with contemporary migration analyses indicating limited gene flow in recent generations, and male-biased sex dispersal within Maui. Historical and long-term estimates of genetic effective population sizes were generally larger than contemporary estimates, although estimates of contemporary genetic effective population size lacked upper bounds in confidence intervals for Hawaiʻi and Kauaʻi. Contemporary genetic effective population sizes were smaller on Oʻahu and Maui. We also detected evidence of past bottlenecks on all islands with the exception of Hawaiʻi. Our study provides population-level estimates for the genetic diversity and geographic structure of ‘ōpeʻapeʻa, that could be used by agencies tasked with wildlife conservation in Hawaiʻi.
Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible. For example, if predictions are conditional on assumptions about how the future will unfold (e.g. possible interventions), these assumptions may never materialize, precluding any direct comparison between predictions and observations. Here, we summarize literature on aggregating probabilistic predictions, illustrate various methods for infectious disease predictions via simulation, and present a strategy for choosing an aggregation method when empirical validation cannot be used. We focus on the linear opinion pool (LOP) and Vincent average, common methods that make different assumptions about between-prediction uncertainty. We contend that assumptions of the aggregation method should align with a hypothesis about how uncertainty is expressed within and between predictions from different sources. The LOP assumes that between-prediction uncertainty is meaningful and should be retained, while the Vincent average assumes that between-prediction uncertainty is akin to sampling error and should not be preserved. We provide an R package for implementation. Given the rising importance of multi-model infectious disease hubs, our work provides useful guidance on aggregation and a deeper understanding of the benefits and risks of different approaches.
The use of moving boat ADCPs (Acoustic Doppler Current Profilers) for discharge measurements requires identification of the sources and magnitude of uncertainty to ensure accurate measurements. Recently, a tool known as QUant was developed to estimate the contribution to the uncertainty estimates for each transect of moving-boat ADCP discharge measurements, by varying different sampling configurations parameters through the use of Monte Carlo simulations. QUant is not only useful for estimating ADCP discharge measurement uncertainty, but also for identifying contributions of the various sources of uncertainty.
However, the software requires long computational times, and the method to estimate the uncertainty of multiple-transect measurements does not consider the correlation of the variables between transects. Therefore, improvements in QUant are needed to optimize its application for practical purposes by hydrographers immediately after discharge measurements.
This work presents four approaches for optimizing the performance of QUant to estimate the contribution to the uncertainty of different selected variables on ADCP discharge measurements and describes a new method of estimating multi-transect uncertainty with the QUant model that considers the correlation of errors in selected variables between transects. The approaches for optimization and the new multi-transect uncertainty method are evaluated using a dataset of 38 field measurements from a variety of riverine settings.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.flowmeasinst.2023.102311","usgsCitation":"Diaz Lozada, J.M., Garcia, C.M., Oberg, K., Over, T.M., and Flores Nieto, F., 2023, Improvements to estimate ADCP uncertainty sources for discharge measurements: Flow Measurement and Instrumentation, v. 90, 102311, 12 p., https://doi.org/10.1016/j.flowmeasinst.2023.102311.","productDescription":"102311, 12 p.","ipdsId":"IP-122869","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Diaz Lozada, Jose M. 0000-0002-6735-0916","orcid":"https://orcid.org/0000-0002-6735-0916","contributorId":287571,"corporation":false,"usgs":false,"family":"Diaz Lozada","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":61615,"text":"Institute for Advanced Studies for Engineering and Technology (IDIT CONICET/UNC) – FCEFyN, National University of Córdoba","active":true,"usgs":false}],"preferred":false,"id":878354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Carlos M. 0000-0002-4091-6756","orcid":"https://orcid.org/0000-0002-4091-6756","contributorId":287572,"corporation":false,"usgs":false,"family":"Garcia","given":"Carlos","email":"","middleInitial":"M.","affiliations":[{"id":61615,"text":"Institute for Advanced Studies for Engineering and Technology (IDIT CONICET/UNC) – FCEFyN, National University of Córdoba","active":true,"usgs":false}],"preferred":false,"id":878355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oberg, Kevin 0000-0002-7024-3361 kaoberg@usgs.gov","orcid":"https://orcid.org/0000-0002-7024-3361","contributorId":175229,"corporation":false,"usgs":true,"family":"Oberg","given":"Kevin","email":"kaoberg@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":878356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flores Nieto, Federico","contributorId":316794,"corporation":false,"usgs":false,"family":"Flores Nieto","given":"Federico","email":"","affiliations":[{"id":68697,"text":"Universidad Nacional de Córdoba, Argentina","active":true,"usgs":false}],"preferred":false,"id":878358,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239820,"text":"sir20225121 - 2023 - Survey of fish communities in tributaries to the Mohawk River, New York, 2019","interactions":[],"lastModifiedDate":"2026-02-23T20:44:15.554802","indexId":"sir20225121","displayToPublicDate":"2023-01-24T09:40:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5121","displayTitle":"Survey of Fish Communities in Tributaries to the Mohawk River, New York, 2019","title":"Survey of fish communities in tributaries to the Mohawk River, New York, 2019","docAbstract":"Fish communities of the Mohawk River and associated sections of the New York State Canal System have been well documented but little information is available regarding the status of fish communities in the extensive network of tributaries that feed the Mohawk River. This lack of information is problematic because changes in species distributions or general ecosystem health may go unnoticed in the absence of baseline data. The need for baseline information has been made particularly urgent by the recent establishment of a high-profile invasive fish species in the mainstem of the Mohawk River, the round goby (Neogobius melanostomus). Round goby can adversely affect aquatic ecosystems in numerous ways and are able to colonize streams in addition to large rivers and lakes. This potential threat to the aquatic ecosystem, therefore, has created an urgent need to quantify the distribution and abundance of fish species inhabiting tributaries to the Mohawk River before round goby can begin colonizing these habitats. In response, the U.S. Geological Survey and the Mohawk River Basin Program of the New York State Department of Environmental Conservation initiated a study in 2019 to collect quantitative information on fish communities and stream habitats in tributaries to the Mohawk River that could be used in the future to determine the effects of round goby on local fish assemblages and identify substrate and other habitat characteristics that facilitate or inhibit colonization by round goby.
Fish communities were surveyed at 20 sites on tributaries to the Mohawk River during summer 2019, using three-pass depletion backpack electrofishing surveys. The resulting data were used to produce quantitative estimates of fish population density and biomass for all species at each site. A total of 11,794 individual fish and 37 species were captured during the 20 surveys. Longnose dace (Rhinichthys cataractae), white sucker (Catostomus commersonii), blacknose dace (Rhinichthys atratulus), fantail darter (Etheostoma flabellare), and creek chub (Semotilus atromaculatus) were the most frequently encountered species, occurring at 18, 18, 17, 17, and 16 of the 20 sites, respectively. Six darter species, small bottom-dwelling fish that are highly vulnerable to displacement by round goby, were captured during the surveys, and at least one darter species was captured at all but one of the sites. Round goby were only captured at one site, Ninemile Creek near Rome, New York, where they occurred at a low density. Overall, the results indicated that round goby had not extensively colonized tributaries to the Mohawk River as of 2019, and the suite of data collected in this project should serve as a valuable baseline for future assessments of the effects of round goby and other stressors on aquatic ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225121","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"George, S.D., Winterhalter, D.R., and Baldigo, B.P., 2023, Survey of fish communities in tributaries to the Mohawk River, New York, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5121, 37 p., https://doi.org/10.3133/sir20225121.","productDescription":"Report: vii, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135887","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":412151,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225121/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5121"},{"id":412152,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5121/sir20225121.XML"},{"id":412153,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5121/images/"},{"id":412131,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5121/coverthb.jpg"},{"id":412132,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5121/sir20225121.pdf","text":"Report","size":"5.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5121"},{"id":412133,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZRRG3T","text":"USGS data release","linkHelpText":"Fish community and substrate data from tributaries to the Mohawk River"},{"id":500464,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114280.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Mohawk River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.48132611302138,\n 43.63870971245336\n ],\n [\n -75.61112592880968,\n 43.63870971245336\n ],\n [\n -75.61112592880968,\n 42.00327529599426\n ],\n [\n -73.48132611302138,\n 42.00327529599426\n ],\n [\n -73.48132611302138,\n 43.63870971245336\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Flood frequency characteristics and estimated flood discharges for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed at 299 streamgaged locations in Wisconsin. The State was divided into four flood frequency regions using a cluster analysis to produce regions which are homogeneous with respect to physical basin characteristics. Regression equations relating flood discharges to basin characteristics within each region were developed and can be used to estimate flood discharges at ungaged locations in Wisconsin. Basin characteristics included in the final regression equations include drainage area, saturated hydraulic conductivity, percent forest, percent herbaceous upland, percent open water, and the maximum 24-hour precipitation with a 10-year recurrence interval. The standard error of prediction for regression equations ranges between 40 and 71 percent, and the pseudo coefficient of determination ranges between 0.8 and 0.95. Nonmonotonic trends in the annual peak flow time series in the southwest part of the State are producing bias in some flood discharge estimates at streamgages with shorter (less than 20 years) periods of record. This bias increases the uncertainty in regression equations in this flood frequency region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/sir20225118","collaboration":"Prepared in cooperation with Wisconsin Department of Transportation","usgsCitation":"Levin, S.B., and Sanocki, C.A., 2023, Estimating flood magnitude and frequency for unregulated streams in Wisconsin: U.S. Geological Survey Scientific Investigations Report 2022–5118, 25 p., https://doi.org/10.3133/sir20225118. [Supersedes Scientific Investigations Report 2016–5140.]","productDescription":"Report: v, 25 p.; 2 Data Releases","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-136903","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":500462,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114282.htm","linkFileType":{"id":5,"text":"html"}},{"id":412139,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9JVO8QV","text":"USGS data release","linkHelpText":"Model archive—Regional regression models for estimating flood frequency characteristics of unregulated streams in Wisconsin"},{"id":412138,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BDHH6D","text":"USGS data release","linkHelpText":"PeakFQ inputs and outputs for 299 streamgages in Wisconsin through water year 2020"},{"id":412137,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5118/images"},{"id":412134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5118/coverthb.jpg"},{"id":412135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5118/sir20225118.pdf","text":"Report","size":"7.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5118"},{"id":412136,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5118/sir20225118.XML"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-90.403306,47.026693],[-90.411972,47.014958],[-90.425351,47.007526],[-90.464079,46.994636],[-90.465465,47.002593],[-90.457688,47.012484],[-90.4553,47.02375],[-90.455502,47.051331],[-90.449572,47.064965],[-90.438734,47.072557],[-90.417272,47.07757],[-90.395367,47.077175],[-90.393342,47.066204],[-90.403306,47.026693]]],[[[-90.730883,46.873096],[-90.677989,46.897527],[-90.667776,46.890037],[-90.675239,46.881029],[-90.718547,46.864531],[-90.745356,46.83566],[-90.756052,46.830595],[-90.760991,46.838277],[-90.749816,46.861806],[-90.730883,46.873096]]],[[[-90.764857,46.946524],[-90.741417,46.9636],[-90.71511,46.957332],[-90.694487,46.93671],[-90.689302,46.918563],[-90.737107,46.914712],[-90.764857,46.946524]]],[[[-90.568938,46.847391],[-90.58505,46.839789],[-90.613569,46.837958],[-90.673838,46.819684],[-90.683356,46.813275],[-90.685753,46.805003],[-90.652916,46.797755],[-90.65892,46.7885],[-90.696465,46.78204],[-90.716456,46.785418],[-90.7625,46.755547],[-90.787751,46.753301],[-90.783086,46.772939],[-90.790965,46.781373],[-90.790231,46.786103],[-90.733231,46.800183],[-90.720932,46.815897],[-90.656946,46.843476],[-90.622048,46.872872],[-90.602619,46.872715],[-90.568938,46.847391]]],[[[-90.572383,46.958835],[-90.528182,46.968396],[-90.508157,46.956836],[-90.524018,46.935714],[-90.539947,46.92785],[-90.543852,46.918289],[-90.549104,46.915461],[-90.569169,46.920309],[-90.637124,46.906724],[-90.64412,46.908373],[-90.654796,46.919249],[-90.634507,46.942944],[-90.572383,46.958835]]],[[[-87.335299,45.211327],[-87.331962,45.199251],[-87.33622,45.173174],[-87.327284,45.157363],[-87.376777,45.177298],[-87.375403,45.199296],[-87.335299,45.211327]]],[[[-90.962901,46.962028],[-90.980316,46.971578],[-90.98222,46.985417],[-90.949383,46.991208],[-90.939866,47.001321],[-90.928563,47.000726],[-90.923764,46.987928],[-90.932132,46.962655],[-90.962901,46.962028]]],[[[-90.757147,47.03372],[-90.688544,47.043347],[-90.643623,47.041177],[-90.608824,47.007558],[-90.560936,47.037013],[-90.544875,47.017383],[-90.552867,46.999686],[-90.609715,46.991208],[-90.634105,46.970983],[-90.671581,46.948973],[-90.712032,46.98526],[-90.767985,47.002327],[-90.776921,47.024324],[-90.757147,47.03372]]],[[[-87.405658,44.860098],[-87.384821,44.865532],[-87.385396,44.889964],[-87.406199,44.90449],[-87.393752,44.933751],[-87.374805,44.956631],[-87.360288,44.987643],[-87.322117,45.034201],[-87.264877,45.081361],[-87.257449,45.121644],[-87.240813,45.137559],[-87.242924,45.149377],[-87.238426,45.166492],[-87.224065,45.174551],[-87.21437,45.165735],[-87.195876,45.163201],[-87.17517,45.173],[-87.163169,45.185331],[-87.13303,45.192843],[-87.119972,45.191103],[-87.122708,45.221786],[-87.109541,45.255397],[-87.078316,45.265723],[-87.071035,45.280355],[-87.057627,45.292838],[-87.0517,45.285888],[-87.043895,45.284767],[-87.017036,45.299254],[-86.994112,45.298061],[-86.97778,45.290684],[-86.970355,45.278455],[-86.984938,45.259036],[-86.983066,45.250764],[-86.973287,45.246381],[-86.985973,45.215872],[-87.002806,45.211773],[-87.00754,45.222127],[-87.032521,45.222274],[-87.040909,45.211535],[-87.045242,45.158798],[-87.030225,45.147382],[-87.03292,45.141963],[-87.045748,45.134987],[-87.054282,45.120074],[-87.049346,45.110122],[-87.048213,45.089124],[-87.057415,45.087472],[-87.064864,45.078427],[-87.079552,45.070783],[-87.081866,45.059103],[-87.090849,45.055465],[-87.121156,45.058311],[-87.139384,45.012565],[-87.163477,45.004913],[-87.189134,44.969078],[-87.188399,44.94856],[-87.17524,44.939753],[-87.1717,44.931476],[-87.204238,44.916819],[-87.215808,44.906744],[-87.217171,44.898013],[-87.206285,44.885928],[-87.204815,44.877199],[-87.267061,44.847025],[-87.282561,44.814729],[-87.304824,44.804603],[-87.313363,44.794237],[-87.320397,44.784963],[-87.319903,44.769672],[-87.353789,44.701915],[-87.401629,44.631191],[-87.437751,44.604559],[-87.467089,44.553557],[-87.483696,44.511354],[-87.490024,44.477224],[-87.498662,44.460686],[-87.506362,44.423804],[-87.517965,44.394356],[-87.517597,44.375696],[-87.533583,44.351111],[-87.545382,44.321385],[-87.541382,44.294018],[-87.508457,44.229755],[-87.507419,44.210803],[-87.512903,44.192808],[-87.51966,44.17987],[-87.53994,44.15969],[-87.563181,44.144195],[-87.603572,44.13039],[-87.6458,44.105222],[-87.654935,44.082552],[-87.656062,44.051919],[-87.683361,44.020139],[-87.695053,43.990715],[-87.69892,43.965936],[-87.71817,43.939498],[-87.735436,43.882219],[-87.728698,43.852524],[-87.726408,43.810454],[-87.700251,43.76735],[-87.702985,43.749695],[-87.709885,43.735795],[-87.702685,43.687596],[-87.789105,43.564844],[-87.797608,43.52731],[-87.793239,43.492783],[-87.807799,43.461136],[-87.855608,43.405441],[-87.872504,43.380178],[-87.882392,43.352099],[-87.889207,43.307652],[-87.901847,43.284117],[-87.911787,43.250406],[-87.896286,43.197108],[-87.881085,43.170609],[-87.900285,43.13731],[-87.900496,43.126],[-87.893185,43.114011],[-87.876084,43.099011],[-87.866487,43.074419],[-87.870184,43.064412],[-87.894813,43.042497],[-87.898184,43.030689],[-87.896157,43.017486],[-87.887789,43.000715],[-87.857182,42.978015],[-87.845181,42.962015],[-87.842786,42.944865],[-87.847745,42.889595],[-87.824,42.836649],[-87.766675,42.784896],[-87.781949,42.74857],[-87.778824,42.728432],[-87.783489,42.705164],[-87.802377,42.676651],[-87.814674,42.64402],[-87.819407,42.617327],[-87.819374,42.60662],[-87.810873,42.58732],[-87.812273,42.52982],[-87.800477,42.49192],[-88.115285,42.496219],[-88.786681,42.491983],[-89.690088,42.505191],[-90.640927,42.508302],[-90.636727,42.518702],[-90.645627,42.5441],[-90.654127,42.5499],[-90.661527,42.567999],[-90.685487,42.589614],[-90.693999,42.614509],[-90.709204,42.636078],[-90.769495,42.651443],[-90.88743,42.67247],[-90.921155,42.685406],[-90.949213,42.685573],[-90.977735,42.696816],[-91.000128,42.716189],[-91.026786,42.724228],[-91.035418,42.73734],[-91.053733,42.738238],[-91.056297,42.747341],[-91.065783,42.753387],[-91.060261,42.761847],[-91.069549,42.769628],[-91.078097,42.806526],[-91.078665,42.827678],[-91.09406,42.830813],[-91.091402,42.84986],[-91.097656,42.859871],[-91.100565,42.883078],[-91.115512,42.894672],[-91.14556,42.90798],[-91.144315,42.926592],[-91.149784,42.940244],[-91.14655,42.963345],[-91.156562,42.978226],[-91.15749,42.991475],[-91.174692,43.038713],[-91.179457,43.067427],[-91.175193,43.103771],[-91.177932,43.128875],[-91.175253,43.134665],[-91.1562,43.142945],[-91.1462,43.152405],[-91.12217,43.197255],[-91.066398,43.239293],[-91.059684,43.248566],[-91.058644,43.257679],[-91.072649,43.262129],[-91.07371,43.274746],[-91.107237,43.313645],[-91.137343,43.329757],[-91.181115,43.345926],[-91.201847,43.349103],[-91.21477,43.365874],[-91.19767,43.395334],[-91.203144,43.419805],[-91.22875,43.445537],[-91.233367,43.455168],[-91.216035,43.481142],[-91.217353,43.512474],[-91.232941,43.523967],[-91.243183,43.540309],[-91.24382,43.54913],[-91.232812,43.564842],[-91.231865,43.581822],[-91.268748,43.615348],[-91.268457,43.627352],[-91.262397,43.64176],[-91.270767,43.65308],[-91.273252,43.666623],[-91.268455,43.709824],[-91.255932,43.729849],[-91.255431,43.744876],[-91.243955,43.773046],[-91.262436,43.792166],[-91.277695,43.837741],[-91.284138,43.847065],[-91.310991,43.867381],[-91.320605,43.888491],[-91.338141,43.897664],[-91.346271,43.910074],[-91.356741,43.916564],[-91.366642,43.937463],[-91.385785,43.954239],[-91.406011,43.963929],[-91.43738,43.999962],[-91.463515,44.009041],[-91.478498,44.00803],[-91.507121,44.01898],[-91.580019,44.026925],[-91.59207,44.031372],[-91.610487,44.04931],[-91.638115,44.063285],[-91.647873,44.064109],[-91.667006,44.086964],[-91.68153,44.0974],[-91.707491,44.103906],[-91.710597,44.12048],[-91.721552,44.130342],[-91.751747,44.134786],[-91.774486,44.147539],[-91.808064,44.159262],[-91.817302,44.164235],[-91.829167,44.17835],[-91.875158,44.200575],[-91.877429,44.212921],[-91.892698,44.231105],[-91.88704,44.251772],[-91.896008,44.262871],[-91.895652,44.273008],[-91.924613,44.291815],[-91.913534,44.311392],[-91.918625,44.322671],[-91.92559,44.333548],[-91.941311,44.340978],[-91.9636,44.362112],[-92.038147,44.388731],[-92.056486,44.402729],[-92.078605,44.404869],[-92.111085,44.413948],[-92.124513,44.422115],[-92.195378,44.433792],[-92.232472,44.445434],[-92.291005,44.485464],[-92.302215,44.500298],[-92.302466,44.516487],[-92.314071,44.538014],[-92.336114,44.554004],[-92.361518,44.558935],[-92.399281,44.558292],[-92.431101,44.565786],[-92.455105,44.561886],[-92.481001,44.568276],[-92.493808,44.566063],[-92.518358,44.575183],[-92.54806,44.567792],[-92.55151,44.571607],[-92.549777,44.58113],[-92.569434,44.603539],[-92.577148,44.605054],[-92.584711,44.599861],[-92.601516,44.612052],[-92.621456,44.615017],[-92.619779,44.634195],[-92.632105,44.649027],[-92.660988,44.660884],[-92.700948,44.693751],[-92.737259,44.717155],[-92.787906,44.737432],[-92.807317,44.750364],[-92.805287,44.768361],[-92.785206,44.792303],[-92.78043,44.812589],[-92.766102,44.834966],[-92.76909,44.861997],[-92.764133,44.875905],[-92.773946,44.889997],[-92.774571,44.898084],[-92.758701,44.908979],[-92.750645,44.937299],[-92.754603,44.955767],[-92.769445,44.97215],[-92.771231,45.001378],[-92.76206,45.02432],[-92.770362,45.033803],[-92.793282,45.047178],[-92.803079,45.060978],[-92.800851,45.069477],[-92.791528,45.079647],[-92.746749,45.107051],[-92.739528,45.116515],[-92.745694,45.123112],[-92.757707,45.155466],[-92.752542,45.171772],[-92.764872,45.182812],[-92.767408,45.190166],[-92.763908,45.204866],[-92.751708,45.218666],[-92.760249,45.2496],[-92.751659,45.26591],[-92.760615,45.278827],[-92.761013,45.289028],[-92.737122,45.300459],[-92.709968,45.321302],[-92.698967,45.336374],[-92.703705,45.35633],[-92.679193,45.37271],[-92.669505,45.389111],[-92.650422,45.398507],[-92.646602,45.441635],[-92.652698,45.454527],[-92.680234,45.464344],[-92.702224,45.493046],[-92.726677,45.514462],[-92.726082,45.541112],[-92.770223,45.566939],[-92.785741,45.567888],[-92.823309,45.560934],[-92.871082,45.567581],[-92.883749,45.575483],[-92.886442,45.598679],[-92.882529,45.610216],[-92.888035,45.624959],[-92.887929,45.639006],[-92.875488,45.689014],[-92.870145,45.696757],[-92.869193,45.717568],[-92.809837,45.744172],[-92.784621,45.764196],[-92.776496,45.790014],[-92.757815,45.806574],[-92.765146,45.830183],[-92.739991,45.846283],[-92.734039,45.868108],[-92.712503,45.891705],[-92.676607,45.90637],[-92.676807,45.91093],[-92.659549,45.922937],[-92.639116,45.924555],[-92.640115,45.932478],[-92.636316,45.934634],[-92.614314,45.934529],[-92.60246,45.940815],[-92.551933,45.951651],[-92.549806,45.967986],[-92.527052,45.983245],[-92.469354,45.973811],[-92.46126,45.979427],[-92.464512,45.985038],[-92.453373,45.992913],[-92.442259,46.016177],[-92.428555,46.024241],[-92.410649,46.027259],[-92.372717,46.014198],[-92.35176,46.015685],[-92.344244,46.02743],[-92.343604,46.040917],[-92.332912,46.062697],[-92.294033,46.074377],[-92.292192,46.666042],[-92.287392,46.667342],[-92.286192,46.660342],[-92.274392,46.657441],[-92.270592,46.650741],[-92.256592,46.658741],[-92.242493,46.649241],[-92.228492,46.652941],[-92.216392,46.649841],[-92.207092,46.651941],[-92.202292,46.655041],[-92.204092,46.666941],[-92.176091,46.686341],[-92.183091,46.695241],[-92.198491,46.696141],[-92.205192,46.698341],[-92.205692,46.702541],[-92.189091,46.717541],[-92.167291,46.719941],[-92.146291,46.71594],[-92.141291,46.72524],[-92.14329,46.73464],[-92.13789,46.73954],[-92.108777,46.749105],[-92.08949,46.74924],[-92.03399,46.708939],[-92.020289,46.704039],[-92.007989,46.705039],[-91.961889,46.682539],[-91.942988,46.679939],[-91.886963,46.690211],[-91.820027,46.690176],[-91.790473,46.694624],[-91.74965,46.709129],[-91.646146,46.734575],[-91.590684,46.754331],[-91.511077,46.757453],[-91.489125,46.766997],[-91.44957,46.773252],[-91.411799,46.78964],[-91.369387,46.793745],[-91.33825,46.817704],[-91.315061,46.826729],[-91.256873,46.836833],[-91.226796,46.86361],[-91.207524,46.865835],[-91.200107,46.854017],[-91.178292,46.844259],[-91.168297,46.844727],[-91.140301,46.873105],[-91.133337,46.870341],[-91.134977,46.859023],[-91.107323,46.857469],[-91.096565,46.86153],[-91.090916,46.88267],[-91.080951,46.883609],[-91.069331,46.878772],[-91.052991,46.881325],[-91.03989,46.88923],[-91.034518,46.903053],[-91.019141,46.911502],[-90.995149,46.917577],[-90.968419,46.94391],[-90.92204,46.931372],[-90.914044,46.933346],[-90.908654,46.941221],[-90.880358,46.957661],[-90.855874,46.962232],[-90.838814,46.957728],[-90.786595,46.927019],[-90.75563,46.899247],[-90.751151,46.887863],[-90.77017,46.876296],[-90.798545,46.823922],[-90.825696,46.803858],[-90.835008,46.790366],[-90.854916,46.788952],[-90.863542,46.780565],[-90.859724,46.774433],[-90.862333,46.768135],[-90.885021,46.756341],[-90.870396,46.723293],[-90.853225,46.70028],[-90.853644,46.694464],[-90.870079,46.679449],[-90.914619,46.659054],[-90.924487,46.625417],[-90.93831,46.608768],[-90.951418,46.600774],[-90.942101,46.588573],[-90.906058,46.58343],[-90.873154,46.601223],[-90.794775,46.624941],[-90.770192,46.636127],[-90.755381,46.646225],[-90.756495,46.664591],[-90.74809,46.669817],[-90.73726,46.692267],[-90.627885,46.623839],[-90.558141,46.586384],[-90.538346,46.581182],[-90.505909,46.589614],[-90.437596,46.561492],[-90.418136,46.566094],[-90.39332,46.532615],[-90.369964,46.540549],[-90.350121,46.537337],[-90.344338,46.552087],[-90.331887,46.553278],[-90.326686,46.54615],[-90.320428,46.546287],[-90.310859,46.539365],[-90.316983,46.517319],[-90.285707,46.518846],[-90.277131,46.524487],[-90.272599,46.521127],[-90.274721,46.515416],[-90.270684,46.508237],[-90.263018,46.502777],[-90.231587,46.509842],[-90.230324,46.501732],[-90.216594,46.501759],[-90.204009,46.478175],[-90.188996,46.469015],[-90.193294,46.463143],[-90.180336,46.456746],[-90.17786,46.440548],[-90.166919,46.439851],[-90.158603,46.422656],[-90.157851,46.409291],[-90.144359,46.390255],[-90.13225,46.381249],[-90.133871,46.371828],[-90.116844,46.355153],[-90.12138,46.338131],[-89.09163,46.138505],[-88.85027,46.040274],[-88.837991,46.030176],[-88.811948,46.021609],[-88.79646,46.023605],[-88.80067,46.030036],[-88.796182,46.033712],[-88.779221,46.031869],[-88.783891,46.020934],[-88.779915,46.015436],[-88.765208,46.022086],[-88.756295,46.020173],[-88.746422,46.025798],[-88.730675,46.026535],[-88.721125,46.022013],[-88.718397,46.013284],[-88.704687,46.018154],[-88.679132,46.013538],[-88.661312,45.988819],[-88.6375,45.98496],[-88.616405,45.9877],[-88.611466,46.003332],[-88.60144,46.017599],[-88.59386,46.015132],[-88.589755,46.005602],[-88.565485,46.015708],[-88.550756,46.012896],[-88.541078,46.013763],[-88.533825,46.020915],[-88.514601,46.019926],[-88.507188,46.0183],[-88.498108,45.99636],[-88.492495,45.992157],[-88.476002,45.992826],[-88.470855,46.001004],[-88.458658,45.999391],[-88.450325,45.990181],[-88.439733,45.990456],[-88.416914,45.975323],[-88.388847,45.982675],[-88.380183,45.991654],[-88.330137,45.965951],[-88.330296,45.956625],[-88.326953,45.955071],[-88.316894,45.960969],[-88.292381,45.951115],[-88.250133,45.963147],[-88.246307,45.962983],[-88.242518,45.950363],[-88.23314,45.947405],[-88.201852,45.945173],[-88.202116,45.949836],[-88.191991,45.95274],[-88.170096,45.93947],[-88.146352,45.935314],[-88.121864,45.92075],[-88.104686,45.922121],[-88.096496,45.917273],[-88.095354,45.913895],[-88.105677,45.904387],[-88.101814,45.883504],[-88.095841,45.880042],[-88.083965,45.881186],[-88.073944,45.875593],[-88.075146,45.864832],[-88.081641,45.865087],[-88.13611,45.819029],[-88.129461,45.809288],[-88.105355,45.800104],[-88.103247,45.791361],[-88.072091,45.780261],[-88.050634,45.780972],[-88.040221,45.789236],[-87.991447,45.795393],[-87.98087,45.776977],[-87.989829,45.772945],[-87.96697,45.764021],[-87.963452,45.75822],[-87.905873,45.759364],[-87.896032,45.752285],[-87.875813,45.753888],[-87.864141,45.745697],[-87.86432,45.737139],[-87.85548,45.726943],[-87.805867,45.706841],[-87.809181,45.700337],[-87.782226,45.683053],[-87.780737,45.675458],[-87.823164,45.662732],[-87.824102,45.647138],[-87.810194,45.638732],[-87.79588,45.618846],[-87.780845,45.614599],[-87.777199,45.588499],[-87.787534,45.581376],[-87.790874,45.564096],[-87.806104,45.562863],[-87.829346,45.568776],[-87.833591,45.562529],[-87.80339,45.538272],[-87.802267,45.514233],[-87.792769,45.499967],[-87.812971,45.4661],[-87.861697,45.434473],[-87.860432,45.423504],[-87.849322,45.403872],[-87.859131,45.398967],[-87.859418,45.388227],[-87.875424,45.379373],[-87.871789,45.373557],[-87.884855,45.362792],[-87.888052,45.354697],[-87.881114,45.351278],[-87.86856,45.360537],[-87.860871,45.351192],[-87.850418,45.347492],[-87.848368,45.340676],[-87.832612,45.352249],[-87.790324,45.353444],[-87.783076,45.349725],[-87.754104,45.349442],[-87.751626,45.354169],[-87.738352,45.358243],[-87.718891,45.377462],[-87.693956,45.389893],[-87.675017,45.382454],[-87.674403,45.378065],[-87.657349,45.368752],[-87.656632,45.358617],[-87.648476,45.352243],[-87.648126,45.339396],[-87.662029,45.326434],[-87.663666,45.318257],[-87.687498,45.298055],[-87.698248,45.281512],[-87.69878,45.26942],[-87.709137,45.260341],[-87.711339,45.239965],[-87.724156,45.233236],[-87.721935,45.228444],[-87.726952,45.218949],[-87.726198,45.209391],[-87.741732,45.198201],[-87.736509,45.173389],[-87.683902,45.144135],[-87.675816,45.135059],[-87.678511,45.131204],[-87.672447,45.121294],[-87.661296,45.112566],[-87.661211,45.108279],[-87.631535,45.106224],[-87.59188,45.094689],[-87.587147,45.089495],[-87.587992,45.085271],[-87.601849,45.082297],[-87.610395,45.075617],[-87.625748,45.045157],[-87.624693,45.014176],[-87.630298,44.976865],[-87.661964,44.973035],[-87.696492,44.974233],[-87.766115,44.965351],[-87.817551,44.951986],[-87.837647,44.933091],[-87.844299,44.918524],[-87.827751,44.891229],[-87.832764,44.880939],[-87.852789,44.86486],[-87.865898,44.840988],[-87.878218,44.839016],[-87.899787,44.828051],[-87.941453,44.75608],[-87.964714,44.74357],[-87.983065,44.72073],[-87.990081,44.669791],[-88.002085,44.664035],[-88.009766,44.637081],[-87.998836,44.609523],[-88.001943,44.603909],[-88.012395,44.602438],[-88.027103,44.578992],[-88.039092,44.574324],[-88.042261,44.567344],[-88.005518,44.539216],[-87.970702,44.530292],[-87.943801,44.529693],[-87.929001,44.535993],[-87.901206,44.568887],[-87.899368,44.573043],[-87.903689,44.581317],[-87.901179,44.584545],[-87.867941,44.607606],[-87.809076,44.636189],[-87.77516,44.639281],[-87.756048,44.649117],[-87.748409,44.667122],[-87.71978,44.693246],[-87.720312,44.725073],[-87.610063,44.838384],[-87.581635,44.851638],[-87.550288,44.85129],[-87.530999,44.857437],[-87.515142,44.869596],[-87.502431,44.864619],[-87.478489,44.863572],[-87.437084,44.892718],[-87.421007,44.887869],[-87.419951,44.87594],[-87.405658,44.860098]]],[[[-86.880572,45.331467],[-86.895055,45.329035],[-86.899488,45.322588],[-86.896667,45.307275],[-86.899891,45.295185],[-86.925681,45.3242],[-86.95499,45.34128],[-86.956192,45.351179],[-86.946297,45.35869],[-86.95497,45.383194],[-86.943041,45.41525],[-86.934724,45.421123],[-86.928045,45.411273],[-86.917686,45.40789],[-86.892893,45.40898],[-86.877502,45.413981],[-86.862174,45.412151],[-86.853145,45.405547],[-86.830353,45.410852],[-86.828731,45.428461],[-86.810055,45.422619],[-86.805415,45.407324],[-86.824383,45.406135],[-86.841432,45.389601],[-86.853103,45.370861],[-86.863367,45.365],[-86.869031,45.333244],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Wisconsin\",\"nation\":\"USA \"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive
Madison, WI 53726
Lake Powell is a large water storage reservoir in the arid southwestern United States. Here, we present a 58-yr limnology dataset that captures water quality parameters from reservoir filling to present day (temperature, salinity, major ions, total suspended solids), as well as a 38-yr record of Secchi depth, and a ~ 30-yr record of nutrients, phytoplankton, and zooplankton assemblages. The dataset includes 5208 unique site visits spanning 258 unique sites of which 9 have been consistently visited. It also spans the establishment of an invasive bivalve (Dreissena bugensis, i.e. Quagga mussel) which was first detected in 2012. Given the general lack of long-term data from lakes or reservoirs in arid regions, this dataset represents a unique contribution to regional, continental, and global-scale limnology studies. As the hot drought in the desert southwest continues, we expect this dataset will inform water management decision-making for this largest reservoir in the Upper Colorado River Basin.
A suite of complementary techniques was used to examine germanium (Ge), a byproduct critical element, and co-substituent trace elements in ZnS and mine wastes from four mineral districts where germanium is, or has been, produced within the United States. This contribution establishes a comprehensive workflow for characterizing Ge and other trace elements, which captures the full heterogeneity of samples through extensive pre-characterization. This process proceeded from optical microscopy, to scanning electron microscopy and cathodoluminescence (CL) imaging, to electron microprobe analysis, prior to synchrotron-based investigations. Utilizing non-destructive techniques enabled reanalysis, which proved essential for verifying observations and validating unexpected results. In cases where the Fe content was <0.3 wt% in ZnS, cathodoluminescence imaging proved to be an efficient means to qualitatively identify trace element zonation that could then be further explored by other micro-focused techniques. Micro-focused X-ray diffraction was used to map the distribution of the non-cubic ZnS polymorph, whereas micro-focused X-ray fluorescence (μ-XRF) phase mapping distinguished between Ge4+ hosted in primary ZnS and a weathering product, hemimorphite [Zn4Si2O7(OH)2·H2O]. Microprobe data and μ-XRF maps identified spatial relationships among trace elements in ZnS and implied substitutional mechanisms, which were further explored using Ge and copper (Cu) X-ray absorption near-edge spectroscopy (XANES). Both oxidation states of Ge (4+ and 2+) were identified in ZnS along with, almost exclusively, monovalent Cu. However, the relative abundance of Ge oxidation states varied among mineral districts and, sometimes, within samples. Further, bulk XANES measurements typically agreed with micro-focused XANES (μ-XANES) spectra, but unique micro-environments were detected, highlighting the importance of complementary bulk and micro-focused measurements. Some Ge μ-XANES utilized a high energy resolution fluorescence detector, which improved spectral resolution and spectral signal-to-noise ratio. This detector opens new opportunities for exploring byproduct critical elements in complex matrices. Overall, the non-destructive workflow employed here can be extended to other byproduct critical elements to more fully understand fundamental ore enrichment processes, which have practical implications for critical element exploration, resource quantification, and extraction.
Deterministic watershed models (DWMs) are used in nearly all hydrologic planning, design, and management activities, yet they cannot generate streamflow ensembles needed for hydrologic risk management (HRM). The stochastic component of DWMs is often ignored in practice, leading to a systematic bias in extreme events. Since traditional stochastic streamflow models used in HRM struggle to account for anthropogenic change, there is a need to convert DWMs into stochastic watershed models (SWMs) to generate ensembles for use in HRM. A DWM can be converted to an SWM using a post-processing (pp) approach to add error to the DWM predictions. Many pp methods advanced in the area of flood forecasting are useful in HRM and for correcting extreme event biases. Selecting a suitable error model for pp is challenging due to nonnormality, skewness, heteroscedasticity, and autocorrelation. We develop a parsimonious pp method based on an autoregressive (AR) model of the logarithm of the ratio of the observations and simulations, which leads to AR model residuals that are approximately symmetric and independent. We document the value of pp for improving flood and low flow frequency analysis and we reintroduce the concepts of verification and validation of stochastic streamflow ensembles to ensure that the SWM can reproduce both statistics it was and was not designed to reproduce, respectively. These concepts are illustrated on a Massachusetts basin using the USGS Precipitation Runoff Modeling System, with an additional analysis indicating the approach may be applicable to 1,225 other sites across the United States.
Wastewater injection has induced earthquakes in Northeastern Colorado since 2014. We apply ambient noise correlation techniques to determine temporal changes in seismic velocities in the region. We find no clear correlation between seismic velocity fluctuations and either injection volumes or seismicity patterns. We do observe apparent annual variations in velocity that may be associated with hydrologic loading or thermoelastic strain. In addition, we model uniform and vertically localized velocity perturbations, and measure the velocity change with 1D synthetic seismograms. Our results indicate that our methods underestimate the known velocity change, especially at shorter station distances and when variations are restricted to a horizontal layer. If injection does cause measurable velocity changes, its effect is likely diluted in cross correlations due to its localized spatial extent around injection wells.
The U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, collected borehole geophysical data and completed simple aquifer tests to estimate the thickness and hydraulic properties of surficial deposits. The purpose of data collection was to create generalized contour maps of Pierre Shale elevation and surficial deposit thickness within and near Ellsworth Air Force Base (study area). Natural gamma and electromagnetic induction data were collected to refine or determine surficial deposit thickness at selected wells. Additionally, data from previous geophysical studies and driller logs were compiled and combined with results from natural gamma and electromagnetic induction data to provide a more spatially complete image of the subsurface. Borehole nuclear magnetic resonance (bNMR) data were collected to estimate hydraulic conductivity and water content of surficial deposits overlying Pierre Shale. Simple aquifer tests using water slugs (slug tests) were completed to estimate hydraulic conductivity of surficial deposits, and results were compared to hydraulic conductivity estimates from bNMR data. All data used to construct maps and estimate hydraulic properties are provided in an accompanying U.S. Geological Survey data release (available at https://doi.org/10.5066/P9FLR79F).
Generalized contour maps were constructed using results from 26 borehole geophysical logs, 35 geophysical transects from previous studies, and 304 wells with driller logs. Pierre Shale elevation generally followed land-surface topography, sloping from high elevations in the north to lower elevations in the south. Topographic highs of Pierre Shale, where present, could act as groundwater divides that potentially affect groundwater flow direction. Surficial deposit thickness varied spatially and ranged from 0 to 86 feet. Surficial deposits generally were thickest in higher elevation areas near ephemeral streams in the northern part of the study area. Hydraulic conductivity estimated from bNMR results using two analytical methods ranged from 0.1 to 2,314 feet per day, whereas hydraulic conductivity estimated from slug tests ranged from 0.001 to 193 feet per day. Hydraulic conductivity estimates from slug tests were plotted with surficial deposit thickness contours instead of bNMR estimates because bNMR estimates were determined to overestimate hydraulic conductivity. Hydraulic conductivity values generally were greater in the southwestern part of study area than the northeastern part.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3502","collaboration":"Prepared in cooperation with the U.S. Air Force Civil Engineer Center","usgsCitation":"Medler, C.J., Eldridge, W.G., Anderson, T.M., and Phillips, S.N., 2023, Maps of elevation of top of Pierre Shale and surficial deposit thickness with hydraulic properties from borehole geophysics and aquifers tests within and near Ellsworth Air Force Base, South Dakota, 2020–21: U.S. Geological Survey Scientific Investigations Map 3502, 25-p. pamphlet, 2 sheets, https://doi.org/10.3133/sim3502.","productDescription":"Report: vii, 25 p.; 2 Sheets: 36.00 x 36.00 inches; 2 Data Releases; Dataset","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-138395","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":500208,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114281.htm","linkFileType":{"id":5,"text":"html"}},{"id":412159,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3502/images"},{"id":412158,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3502/sim3502.XML"},{"id":412155,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3502/sim3502.pdf","text":"Pamphlet","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3502"},{"id":412250,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3502/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"}},{"id":412161,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XSJH17","text":"USGS data release","linkHelpText":"Electrical resistivity tomography (ERT) and horizontal-to-vertical spectral ratio (HVSR) data collected within and near Ellsworth Air Force Base, South Dakota, from 2014 to 2019"},{"id":412157,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3502/sim3502_sheet02.pdf","text":"Sheet 2","size":"7.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3502, sheet 2","linkHelpText":"—Map showing contours of depth to Pierre Shale, hydraulic conductivity, and groundwater velocity of surficial deposits"},{"id":412156,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3502/sim3502_sheet01.pdf","text":"Sheet 1","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3502, sheet 1","linkHelpText":"—Map showing elevation contours of the top of Pierre Shale from well logs and electrical resistivity tomography data"},{"id":412162,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":412154,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3502/coverthb.jpg"},{"id":412160,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FLR79F","text":"USGS data release","linkHelpText":"Datasets used to create maps of Pierre Shale elevation and surficial deposit thickness within and near Ellsworth Air Force Base, South Dakota, 2021"}],"country":"United States","state":"South Dakota","otherGeospatial":"Ellsworth Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.17044722999105,\n 44.19638858668296\n ],\n [\n -103.17044722999105,\n 44.0880305228894\n ],\n [\n -103.00984038772282,\n 44.0880305228894\n ],\n [\n -103.00984038772282,\n 44.19638858668296\n ],\n [\n -103.17044722999105,\n 44.19638858668296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Knowledge of the breeding ecology of Endangered Nordmann’s Greenshank Tringa guttifer is necessary to develop a comprehensive species-specific conservation plan. We found nine greenshank nests in Schaste Bay, Russian Far East during the summers of 2019–2021. These are the first nests found in over 40 years and the only discovered to date on mainland Russia. In contrast to previous nest descriptions, we found greenshanks do not exclusively nest in trees, but also place nests on the ground at the base of mature or sapling larches. Our results indicate greenshanks may be larch obligates during the breeding season, and protecting coastal larch forest ecosystems near bogs, meadows, and mudflats throughout the Russian Far East may be critical to the species’ conservation.
Detailed geologic maps are the basis of most earth science investigations and can be used for natural hazard mitigation, resource identification and exploration, infrastructure planning, and more. As a part of the U.S. Geological Survey (USGS) congressionally mandated National Cooperative Geologic Mapping Program (NCGMP), the EDMAP program (referred to as EDMAP) is a partnership between the USGS and participating colleges and universities that provides mentorship and training opportunities for earth science students nationwide. EDMAP supports graduate students and upper-level undergraduate students—under the guidance of a faculty member who serves as a “principal investigator”—for the training of students to become geologic mappers. Between 1996 and 2021, EDMAP funded geologic mapping educational experiences and training for 1,373 students at more than 170 universities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233002","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Shelton, J.L., Swezey, C.S., and Marketti, M., 2023, The EDMAP Program: Training the next generation of geologic mappers: U.S. Geological Survey Fact Sheet 2023–3002, 4 p., https://doi.org/10.3133/fs20233002.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-131886","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":64806,"text":"National Cooperative Geologic Mapping","active":true,"usgs":true}],"links":[{"id":411786,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3002"},{"id":411784,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3002/coverthb.jpg"},{"id":411787,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3002/fs20233002.XML"},{"id":411788,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3002/images/"},{"id":411785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3002/fs20233002.pdf","text":"Report","size":"1.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3002"}],"contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 908
Reston, VA 20192
Geomagnetically induced currents (GICs) result from the interaction of the time variation of ground magnetic field during a geomagnetic disturbance with the Earth's deep electrical resistivity structure. In this study, we simulate induced GICs in a hypothetical representation of a low-latitude power transmission network located mainly over the large Paleozoic Paraná basin (PB) in southern Brazil. Two intense geomagnetic storms in June and December 2015 are chosen and geoelectric fields are calculated by convolving a three-dimensional (3-D) Earth resistivity model with recorded geomagnetic variations. The dB/dt proxy often used to characterize GIC activity fails during the June storm mainly due to the relationship of the instantaneous geoelectric field to previous magnetic field values. Precise resistances of network components are unknown, so assumptions are made for calculating GIC flows from the derived geoelectric field. The largest GICs are modeled in regions of low conductance in the 3-D resistivity model, concentrated in an isolated substation at the northern edge of the network and in a cluster of substations in its central part where the east-west (E-W) oriented transmission lines coincide with the orientation of the instantaneous geoelectric field. The maximum magnitude of the modeled GIC was obtained during the main phase of the June storm, modeled at a northern substation, while the lowest magnitudes were found over prominent crustal anomalies along the PB axis and bordering the continental margin. The simulation results will be used to prospect the optimal substations for installation of GIC monitoring equipment.
Masting describes the spatiotemporal variability in seed production by a population of plants. Both abiotic and biotic factors drive masting, but the importance of these factors can vary among individuals and populations. To better understand how a changing climate, altered disturbance regimes, or novel management strategies might affect future seed production, we quantified the joint influence of multiple factors on annual cone production in a widespread conifer species, Rocky Mountain ponderosa pine (Pinus ponderosa var. scopulorum). We reconstructed individual-level annual cone production across climatic gradients using the cone abscission scar method, and explored the causes and drivers of masting in this species. Site-level responses between weather and masting were highly variable, notably differing in the strength of their response to either summer or spring weather. In addition, the relationship to summer precipitation during cone initiation, a primary driver of annual seed production in this species, was strongest at hotter and drier sites. Additionally, we found that masting was strongly influenced by tree- and stand-level factors such as diameter, age, and local neighborhood density, all of which were associated with the mean, interannual variability, and between-tree synchrony of cone production at the individual-level. Larger and older trees produced more cones, more frequently, and with less synchrony than smaller and younger trees. Open grown trees experiencing lower levels of neighborhood competition also produced more cones with less interannual variability, but with higher between-tree synchrony. Because tree- and stand-level traits appear to regulate seed production more strongly than climate or weather in this species, management interventions targeting these factors could be powerful tools to manage future tree recruitment. Thus, current efforts to reduce stand density and conserve large trees in some ponderosa pine forests may enhance tree-level seed production and reduce variability in seed crops among years.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2023.120794","usgsCitation":"Wion, A., Pearse, I., Rodman, K.C., Veblen, T.T., and Redmond, M., 2023, Masting is shaped by tree-level attributes and stand structure, more than climate, in a Rocky Mountain conifer species: Forest Ecology and Management, v. 531, 120794, 11 p., https://doi.org/10.1016/j.foreco.2023.120794.","productDescription":"120794, 11 p.","ipdsId":"IP-144420","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":502516,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":416439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.90275843175954,\n 45.00494791264421\n ],\n [\n -113.03797988217684,\n 45.00494791264421\n ],\n [\n -113.03797988217684,\n 35.165989564592365\n ],\n [\n -102.90275843175954,\n 35.165989564592365\n ],\n [\n -102.90275843175954,\n 45.00494791264421\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"531","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wion, Andreas","contributorId":225092,"corporation":false,"usgs":false,"family":"Wion","given":"Andreas","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":870737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":211154,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":870738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodman, Kyle C.","contributorId":268842,"corporation":false,"usgs":false,"family":"Rodman","given":"Kyle","email":"","middleInitial":"C.","affiliations":[{"id":49843,"text":"U Wisconsin","active":true,"usgs":false}],"preferred":false,"id":870739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veblen, Thomas T.","contributorId":192285,"corporation":false,"usgs":false,"family":"Veblen","given":"Thomas","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":870740,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Redmond, Miranda D.","contributorId":225094,"corporation":false,"usgs":false,"family":"Redmond","given":"Miranda","middleInitial":"D.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":870741,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241055,"text":"70241055 - 2023 - Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides","interactions":[],"lastModifiedDate":"2023-03-08T13:17:43.875878","indexId":"70241055","displayToPublicDate":"2023-01-23T07:11:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides","docAbstract":"The invasion of nonnative grasses threatens biodiversity and ecosystem function globally through competition with native plant species and increases to wildfire frequency and intensity. Management actions to reduce buffelgrass [Pennisetum ciliare (L.) Link], an invasive warm-season perennial bunchgrass, are widely implemented, with chemical and mechanical treatments extending over two decades within Saguaro National Park in the Sonoran Desert of North America. We assessed how the effectiveness of treatments to reduce P. ciliare cover spanning from 2011 to 2020 were influenced by stage of invasion, treatment type and intensity, and environmental conditions. An increase in treatment effectiveness was largely explained by high initial cover of P. ciliare, an indicator of a late invasion stage and associated with high treatment intensity. Treatments had potential to be effective in patches as small as 0.3-m2 P. ciliare canopy per 400-m−2 area (<0.001% canopy cover) across treatment types and environmental gradients. Chemical treatments had higher or equal effectiveness compared with mechanical treatments, and greater reductions in P. ciliare were associated with shorter average years of treatment interruptions, or gaps, and to a lesser degree, total years of treatment. In many cases, P. ciliare was reduced with as little as 2 yr of treatment, but more than 3 average years of treatment gap could result in reduced treatment effectiveness. There was generally higher treatment effectiveness on shallow slopes, north- and east-facing aspects, and on higher elevations within one district of the park. Our findings highlight that resource-intensive treatments in all but the smallest patches of P. ciliare have largely been effective. Further opportunities for improvement include more frequent surveillance, limiting treatment gaps to ≤3 yr in areas of low P. ciliare cover, and comparison of treated with untreated areas.
Phragmites australis (common reed) has a cosmopolitan distribution and has been suggested as a model organism for the study of invasive plant species. In North America, the non-native subspecies (ssp. australis) is widely distributed across the contiguous 48 states in the United States and large parts of Canada. Even though millions of dollars are spent annually on Phragmites management, insufficient knowledge of P. australis impeded the efficiency of management. To solve this problem, transcriptomic information generated from multiple types of tissue could be a valuable resource for future studies. Here, we constructed forty-nine P. australis transcriptomes assemblies via different assembly tools and multiple parameter settings. The optimal transcriptome assembly for functional annotation and downstream analyses was selected among these transcriptome assemblies by comprehensive assessments. For a total of 422,589 transcripts assembled in this transcriptome assembly, 319,046 transcripts (75.5%) have at least one functional annotation. Within the transcriptome assembly, we further identified 1,495 transcripts showing tissue-specific expression pattern, 10,828 putative transcription factors, and 72,165 candidates for simple sequence repeats markers. The identification and analyses of predicted transcripts related to herbicide- and salinity-resistant genes were shown as two applications of the transcriptomic information to facilitate further research on P. australis. Transcriptome assembly and selection would be important for the transcriptome annotation. With this optimal transcriptome assembly and all relative information from downstream analyses, we have helped to establish foundations for future studies on the mechanisms underlying the invasiveness of non-native P. australis subspecies.
No abstract available.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3971","usgsCitation":"Condon, L.A., Shinneman, D.J., Rosentreter, R., and Coates, P.S., 2023, Could biological soil crusts act as natural fire fuel breaks in the sagebrush steppe?: Ecology, v. 104, no. 4, e3971, 6 p., https://doi.org/10.1002/ecy.3971.","productDescription":"e3971, 6 p.","ipdsId":"IP-139552","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":444734,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3971","text":"Publisher Index Page"},{"id":435492,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P943JB43","text":"USGS data release","linkHelpText":"Fire Response Effects, Biocrust, and Vascular Plant Abundance Following Wildfire near Boise, Idaho (October 2021)"},{"id":413525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865273,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":865274,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosentreter, Roger","contributorId":257441,"corporation":false,"usgs":false,"family":"Rosentreter","given":"Roger","affiliations":[{"id":52018,"text":"Biology Department, Boise State University, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":865275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865276,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239769,"text":"70239769 - 2023 - A global perspective on bacterial diversity in the terrestrial deep subsurface","interactions":[],"lastModifiedDate":"2023-01-19T12:49:23.155276","indexId":"70239769","displayToPublicDate":"2023-01-23T06:42:49","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13275,"text":"Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"A global perspective on bacterial diversity in the terrestrial deep subsurface","docAbstract":"While recent efforts to catalogue Earth’s microbial diversity have focused upon surface and marine habitats, 12–20 % of Earth’s biomass is suggested to exist in the terrestrial deep subsurface, compared to ~1.8 % in the deep subseafloor. Metagenomic studies of the terrestrial deep subsurface have yielded a trove of divergent and functionally important microbiomes from a range of localities. However, a wider perspective of microbial diversity and its relationship to environmental conditions within the terrestrial deep subsurface is still required. Our meta-analysis reveals that terrestrial deep subsurface microbiota are dominated by Betaproteobacteria, Gammaproteobacteria and Firmicutes, probably as a function of the diverse metabolic strategies of these taxa. Evidence was also found for a common small consortium of prevalent Betaproteobacteria and Gammaproteobacteria operational taxonomic units across the localities. This implies a core terrestrial deep subsurface community, irrespective of aquifer lithology, depth and other variables, that may play an important role in colonizing and sustaining microbial habitats in the deep terrestrial subsurface. An in silico contamination-aware approach to analysing this dataset underscores the importance of downstream methods for assuring that robust conclusions can be reached from deep subsurface-derived sequencing data. Understanding the global panorama of microbial diversity and ecological dynamics in the deep terrestrial subsurface provides a first step towards understanding the role of microbes in global subsurface element and nutrient cycling.
","language":"English","publisher":"Microbiology Society","doi":"10.1099/mic.0.001172","usgsCitation":"Soares, A., Edwards, A.L., Bagnoud, A., Bradley, J., Barnhart, E.P., Bomberger Brown, M., Budwill, K., Caffrey, S.M., Fields, M., Gralnick., J., Kadnikov, V., Momper, L., Osburn, M., Mu, A., Moreau, J., Moser, D., Purkamo, L., Rassner, S.M., Sheik, C.S., Lollar, B.S., Toner, B., Voordouw, G., Wouters, K., and Mitchell, A.C., 2023, A global perspective on bacterial diversity in the terrestrial deep subsurface: Microbiology, v. 169, no. 1, 001172, 10 p., https://doi.org/10.1099/mic.0.001172.","productDescription":"001172, 10 p.","ipdsId":"IP-106711","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":444736,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1099/mic.0.001172","text":"External Repository"},{"id":412067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"169","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Soares, A.","contributorId":301036,"corporation":false,"usgs":false,"family":"Soares","given":"A.","email":"","affiliations":[{"id":65275,"text":"1. Department of Geography and Earth Sciences (DGES), Aberystwyth University (AU), Wales, UK","active":true,"usgs":false}],"preferred":false,"id":861819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, A. L.","contributorId":43551,"corporation":false,"usgs":false,"family":"Edwards","given":"A.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":861820,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagnoud, A.","contributorId":301037,"corporation":false,"usgs":false,"family":"Bagnoud","given":"A.","email":"","affiliations":[{"id":65276,"text":"Institut de Génie Thermique (IGT), Haute École d'Ingénierie et de Gestion du Canton de Vaud (HEIG-VD), Yverdon-les-Bains, Switzerland","active":true,"usgs":false}],"preferred":false,"id":861822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bradley, J.","contributorId":301038,"corporation":false,"usgs":false,"family":"Bradley","given":"J.","affiliations":[{"id":65277,"text":"6. School of Geography, Queen Mary University of London, London, UK.","active":true,"usgs":false}],"preferred":false,"id":861823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":203225,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861824,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bomberger Brown, M.","contributorId":169602,"corporation":false,"usgs":false,"family":"Bomberger Brown","given":"M.","email":"","affiliations":[{"id":25563,"text":"School of Natural Resources, University of Nebraska, Lincoln, NE 68583","active":true,"usgs":false}],"preferred":false,"id":861825,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Budwill, K.","contributorId":301039,"corporation":false,"usgs":false,"family":"Budwill","given":"K.","email":"","affiliations":[{"id":17795,"text":"Alberta Innovates, Canada","active":true,"usgs":false}],"preferred":false,"id":861826,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Caffrey, S. M.","contributorId":301040,"corporation":false,"usgs":false,"family":"Caffrey","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":65278,"text":"University of Toronto, Canada (UT)","active":true,"usgs":false}],"preferred":false,"id":861827,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fields, M.","contributorId":301041,"corporation":false,"usgs":false,"family":"Fields","given":"M.","email":"","affiliations":[{"id":65279,"text":"Center for Biofilm Engineering (CBE), Montana State University (MSU), USA","active":true,"usgs":false}],"preferred":false,"id":861828,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gralnick., J.","contributorId":301042,"corporation":false,"usgs":false,"family":"Gralnick.","given":"J.","email":"","affiliations":[{"id":65280,"text":"Department of Plant and Microbial Biology, UM, USA","active":true,"usgs":false}],"preferred":false,"id":861829,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kadnikov, V.","contributorId":301043,"corporation":false,"usgs":false,"family":"Kadnikov","given":"V.","email":"","affiliations":[{"id":65281,"text":"14. Faculty of Biology, Moscow State University (MoSU), Russia","active":true,"usgs":false}],"preferred":false,"id":861830,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Momper, L.","contributorId":301044,"corporation":false,"usgs":false,"family":"Momper","given":"L.","email":"","affiliations":[{"id":65282,"text":"16. Department of Earth, Atmospheric and Planetary Sciences (DEAPS), The Massachusetts Institute of Technology (MIT), United States of America (USA)","active":true,"usgs":false}],"preferred":false,"id":861831,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Osburn, M.","contributorId":301045,"corporation":false,"usgs":false,"family":"Osburn","given":"M.","email":"","affiliations":[{"id":65283,"text":"Department of Earth and Planetary Sciences (DEPS), Northwestern University (NWU), USA","active":true,"usgs":false}],"preferred":false,"id":861832,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Mu, A.","contributorId":301073,"corporation":false,"usgs":false,"family":"Mu","given":"A.","email":"","affiliations":[],"preferred":false,"id":861833,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Moreau, J.W.","contributorId":301046,"corporation":false,"usgs":false,"family":"Moreau","given":"J.W.","affiliations":[{"id":65284,"text":"21. School of Earth Sciences, The University of Melbourne (UM), Parkville, Australia","active":true,"usgs":false}],"preferred":false,"id":861834,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Moser, D.","contributorId":301047,"corporation":false,"usgs":false,"family":"Moser","given":"D.","email":"","affiliations":[{"id":65285,"text":"Division of Hydrologic Sciences, Desert Research Institute (DRI), Las Vegas, NV, USA","active":true,"usgs":false}],"preferred":false,"id":861835,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Purkamo, L.","contributorId":301048,"corporation":false,"usgs":false,"family":"Purkamo","given":"L.","email":"","affiliations":[{"id":65286,"text":"VTT Technical Research Centre of Finland, Finland","active":true,"usgs":false}],"preferred":false,"id":861836,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Rassner, S. M.","contributorId":301049,"corporation":false,"usgs":false,"family":"Rassner","given":"S.","email":"","middleInitial":"M.","affiliations":[{"id":65287,"text":"Department of Geography and Earth Sciences (DGES), Aberystwyth University (AU), Wales, UK","active":true,"usgs":false}],"preferred":false,"id":861837,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Sheik, C. S.","contributorId":301050,"corporation":false,"usgs":false,"family":"Sheik","given":"C.","email":"","middleInitial":"S.","affiliations":[{"id":65288,"text":"Large Lakes Observatory, University of Minnesota – Duluth (UMD)","active":true,"usgs":false}],"preferred":false,"id":861838,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Lollar, B. Sherwood","contributorId":106719,"corporation":false,"usgs":true,"family":"Lollar","given":"B.","email":"","middleInitial":"Sherwood","affiliations":[],"preferred":false,"id":861905,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Toner, B. M.","contributorId":301051,"corporation":false,"usgs":false,"family":"Toner","given":"B. M.","affiliations":[{"id":65289,"text":"Department of Soil, Water & Climate, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":861839,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Voordouw, G.","contributorId":301052,"corporation":false,"usgs":false,"family":"Voordouw","given":"G.","email":"","affiliations":[{"id":65291,"text":"Department of Biological Sciences, University of Calgary, Canada","active":true,"usgs":false}],"preferred":false,"id":861840,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Wouters, K.","contributorId":301053,"corporation":false,"usgs":false,"family":"Wouters","given":"K.","email":"","affiliations":[{"id":65292,"text":"Institute for Environment, Health and Safety (EHS), Belgian Nuclear Research Centre SCK•CEN, Mol, Belgium","active":true,"usgs":false}],"preferred":false,"id":861841,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Mitchell, A. C.","contributorId":301054,"corporation":false,"usgs":false,"family":"Mitchell","given":"A.","email":"","middleInitial":"C.","affiliations":[{"id":65287,"text":"Department of Geography and Earth Sciences (DGES), Aberystwyth University (AU), Wales, UK","active":true,"usgs":false}],"preferred":false,"id":861842,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70239922,"text":"70239922 - 2023 - Nitrogen-15 NMR study on the incorporation of nitrogen into aquatic NOM upon chloramination","interactions":[],"lastModifiedDate":"2023-01-25T12:42:43.226364","indexId":"70239922","displayToPublicDate":"2023-01-23T06:42:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen-15 NMR study on the incorporation of nitrogen into aquatic NOM upon chloramination","docAbstract":"Chloramination is being used increasingly in water treatment to lower the formation of regulated disinfection byproducts (DBPs). How monochloramine nitrogen becomes incorporated into aquatic natural organic matter (NOM) and potentially affects the formation of nitrogenous DBPs is an unresolved question in the chemistry of humic substances. To address the problem, Suwannee River NOM and Suwannee River fulvic acid were reacted with preformed 15NH2Cl and analyzed by solid and liquid state 15N NMR spectrometry. Both samples were also reacted with 15NH4Cl as a control. A majority of the monochloramine nitrogen incorporated into the samples matched the structural forms resulting from the control reaction with ammonia, indicating that condensation reactions of ammonia with the carbonyl functionality can partly explain the transformation of the 15NH2Cl nitrogen into the NOM. These structural forms include aminohydroquinone, 1° amide, indole, and pyridine-like nitrogens. Spectra of the samples reacted with 15NH2Cl also showed possible evidence for nitrosophenol nitrogens, which would arise from the reaction of hydroxylamine or nitrite, intermediates in the chemical oxidation of the inorganic nitrogen to nitrate.
The shovelnose sturgeon (Scaphirhynchus platorynchus) and endangered pallid sturgeon (S. albus) deposit demersal and adhesive eggs in swift currents, near or over coarse substrate. Hydrographic surveys have demonstrated the dynamic nature of spawning habitats and that coarse substrates may episodically be buried (partially or completely) by fine sediments. To evaluate embryo survival of both species in various substrate conditions, laboratory trials were conducted with substrates of clean glass, gravel, medium-coarse sand (MCS), and fine sand-silt (FSS). Embryos in MCS and FSS were tested three ways: unburied, partially buried, and fully buried (1–2-mm depth). Embryos were exposed to trial conditions for 10 days from the day of fertilization (5 days beyond expected hatching). For both species, mean hatch of normally developed free embryos was highest in unburied treatments where embryos were incubated on substrates and not covered with sediments and ranged from 81.0 to 87.1% for shovelnose sturgeon and 55.2–80.0% for pallid sturgeon. Mean hatch of normal free embryos was lowest where incubating embryos were fully buried by MCS or FSS and ranged from 2.4 to 11.6% for shovelnose sturgeon and 4.8–15.2% for pallid sturgeon. We observed free embryos with physical abnormalities in all treatments; however, the occurrence was most variable in treatments fully and partially buried by MCS. Hatch of both species was also delayed in treatments where embryos were incubated fully and partially buried by MCS. Our results may be useful to estimate the relative suitability of spawning substrates in relevant river reaches.
Cycles of stress build-up and release are inherent to tectonically active planets. Such stress oscillations impart strain and damage, prompting mechanically loaded rocks and materials to fail. Here, we investigate, under uniaxial conditions, damage accumulation and weakening caused by time-dependent creep (at 60, 65, and 70% of the rocks’ expected failure stress) and repeating stress oscillations (of ± 2.5, 5.0 or 7.5% of the creep load), simulating earthquakes at a shaking frequency of ~ 1.3 Hz in volcanic rocks. The results show that stress oscillations impart more damage than constant loads, occasionally prompting sample failure. The magnitudes of the creep stresses and stress oscillations correlate with the mechanical responses of our porphyritic andesites, implicating progressive microcracking as the cause of permanent inelastic strain. Microstructural investigation reveals longer fractures and higher fracture density in the post-experimental rock. We deconvolve the inelastic strain signal caused by creep deformation to quantify the amount of damage imparted by each individual oscillation event, showing that the magnitude of strain is generally largest with the first few oscillations; in instances where pre-existing damage and/or the oscillations’ amplitude favour the coalescence of micro-cracks towards system scale failure, the strain signal recorded shows a sharp increase as the number of oscillations increases, regardless of the creep condition. We conclude that repetitive stress oscillations during earthquakes can amplify the amount of damage in otherwise mechanically loaded materials, thus accentuating their weakening, a process that may affect natural or engineered structures. We specifically discuss volcanic scenarios without wholesale failure, where stress oscillations may generate damage, which could, for example, alter pore fluid pathways, modify stress distribution and affect future vulnerability to rupture and associated hazards.