Skipped spawning, or variation in spawning periodicity, occurs in many annual spawning fish species and is an important consideration for population management. We assessed plasma sex steroid concentrations and measured gonad size and ovarian follicle diameter as metrics to nonlethally identify mass ovarian follicular atresia, which may contribute to skipped spawning in Burbot Lota lota. We maintained wild fish in captivity and exposed them to increasing water temperatures during a 3-wk period before the spawning season to induce mass ovarian follicular atresia. We collected ovarian follicles, blood plasma, and gonadal sonograms from fish weekly between January 28, 2018, and March 25, 2018. We histologically analyzed ovarian follicles to confirm stage of maturity. We measured concentrations of plasma sex steroids testosterone (T) and estradiol-17β (E2) by radioimmunoassay. We measured gonad diameter and circumference by ultrasonography and ovarian follicle diameter by image analysis. Mean plasma T concentration decreased from 8.94 ng/mL during late vitellogenesis to 1.83 ng/mL during atresia, suggesting that plasma T concentrations may be used to identify mass ovarian follicular atresia. We do not recommend using plasma E2 concentrations to identify mass ovarian follicular atresia because E2 concentrations rapidly decreased during the completion of vitellogenesis and the initiation of atresia in Burbot; therefore, plasma E2 may not accurately identify mass ovarian follicular atresia. Mean gonad diameter measured by ultrasonography decreased from 4.05 cm during late vitellogenesis to 3.65 cm during atresia. Mean diameter of ovarian follicles decreased during the final week of the study, suggesting that ovarian follicle diameter may be used to identify advanced mass ovarian follicular atresia. The nonlethal tools assessed—plasma sex steroid concentrations, ultrasonography, and ovarian follicle diameter—enable fisheries biologists to determine the occurrence and frequency of mass ovarian follicular atresia among Burbot in Lake Roosevelt and may be applied to other Burbot populations.
Increased wildfire frequency and associated replacement of sagebrush (Artemisia spp.) with invasive annual grasses contribute to declines of greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) populations across the Great Basin. However, little is known about wildfire effects on sage-grouse nest-site selection and nest survival, which can influence population persistence. The primary objective of this study was to evaluate the effects of the Rush Fire on sage-grouse nest survival using before (2007–2009) and after (2015–2018) data collected from a population of sage-grouse occupying the border of northeastern California and northwestern Nevada. We employed a before–after–control–impact (BACI) experimental design to account for spatiotemporal heterogeneity in the system and to derive estimates of relative change in survival parameters. Sage-grouse nest survival decreased after the Rush Fire but decreased more in the burned area relative to the unburned area. Although female sage-grouse continued to occupy burned areas, nest survival was reduced from 52% to 19%. Using a BACI ratio approach we found that nest survival decreased approximately 51% in the burned area, relative to the unburned area, following wildfire. Habitat analyses were restricted to the postfire period and found that female sage-grouse that nested within unburned areas selected for wider nesting substrate, taller perennial grass height, and greater low sagebrush canopy cover. Conversely, female sage-grouse that nested in burned areas used shorter sagebrush canopy cover than what was available across the entire study area but showed stronger selection for perennial grass height than their unburned counterparts. Strong nest-site fidelity in sage-grouse may explain the continued use of suboptimal habitat in wildfire-altered landscapes, resulting in a reproductive cost, and overall reproduction well below replacement rate. Results suggest that fire suppression or rapid postfire habitat restoration, especially within nesting habitat, may be essential to conserving robust sage-grouse populations into the future.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4282","usgsCitation":"Dudley, I.F., Coates, P.S., Prochazka, B.G., Davis, D.M., Gardner, S.C., and Delehanty, D.J., 2022, Maladaptive nest-site selection and reduced nest survival in female sage-grouse following wildfire: Ecosphere, v. 13, no. 12, e4282, 19 p., https://doi.org/10.1002/ecs2.4282.","productDescription":"e4282, 19 p.","ipdsId":"IP-120007","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":445715,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4282","text":"Publisher Index Page"},{"id":412686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","county":"Lassen County, Washoe County","otherGeospatial":"Buffalo-Skedaddle Population Management Unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.94518975982814,\n 40.579947239546414\n ],\n [\n -120.2542712694401,\n 40.579947239546414\n ],\n [\n -120.2542712694401,\n 40.275652408838\n ],\n [\n -119.94518975982814,\n 40.275652408838\n ],\n [\n -119.94518975982814,\n 40.579947239546414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudley, Ian F.","contributorId":294783,"corporation":false,"usgs":false,"family":"Dudley","given":"Ian","email":"","middleInitial":"F.","affiliations":[{"id":56372,"text":"Stantec","active":true,"usgs":false}],"preferred":false,"id":863313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":863314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Dawn M.","contributorId":254959,"corporation":false,"usgs":false,"family":"Davis","given":"Dawn","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":863316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":863317,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":863318,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70256601,"text":"70256601 - 2022 - As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore","interactions":[],"lastModifiedDate":"2024-08-23T16:24:30.976426","indexId":"70256601","displayToPublicDate":"2022-12-03T11:08:32","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore","docAbstract":"Migration schedules and the timing of other annual events (e.g., pair formation and molt) can affect the distribution of genetic diversity as much as where these events occur. The greater white-fronted goose (Anser albifrons) is a circumpolar goose species, exhibiting temporal and spatial variation of events among populations during the annual cycle. Previous range-wide genetic assessments of the nuclear genome based on eight microsatellite loci suggest a single, largely panmictic population despite up to five subspecies currently recognized based on phenotypic differences. We used double digest restriction-site associated DNA (ddRAD-seq) and mitochondrial DNA (mtDNA) sequence data to re-evaluate estimates of spatial genomic structure and to characterize how past and present processes have shaped the patterns of genetic diversity and connectivity across the Arctic and subarctic. We uncovered previously undetected inter-population differentiation with genetic clusters corresponding to sampling locales associated with current management groups. We further observed subtle genetic clustering within each management unit that can be at least partially explained by the timing and directionality of migration events along with other behaviors during the annual cycle. The Tule Goose (A. a. elgasi) and Greenland subspecies (A. a. flavirostris) showed the highest level of divergence among all sampling locales investigated. The recovery of previously undetected broad and fine-scale spatial structure suggests that the strong cultural transmission of migratory behavior restricts gene flow across portions of the species’ range. Our data further highlight the importance of re-evaluating previous assessments conducted based on a small number of highly variable genetic markers in phenotypically diverse species.
","language":"English","publisher":"MDPI","doi":"10.3390/d14121067","usgsCitation":"Wilson, R., Sonsthagen, S.A., DaCost, J.M., Sorenson, M., Fox, A., Weaver, M., Skalos, D., Kondratyev, A., Scribner, K., Walsh, A., Ely, C.R., and Talbot, S.L., 2022, As the goose flies: Migration routes and timing influence patterns of genetic diversity in a circumpolar migratory herbivore: Diversity, v. 14, no. 12, 1067, 23 p., https://doi.org/10.3390/d14121067.","productDescription":"1067, 23 p.","ipdsId":"IP-145453","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":445720,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d14121067","text":"Publisher Index Page"},{"id":433109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Greenland, Russia, United States","otherGeospatial":"Circumpolar Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -179.9,\n 73.8\n ],\n [\n -179.9,\n 55\n ],\n [\n -44.563059444221864,\n 55\n ],\n [\n -44.563059444221864,\n 73.8\n ],\n [\n -179.9,\n 73.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 36.467721150184104,\n 73.8\n ],\n [\n 36.467721150184104,\n 60\n ],\n [\n 179.9,\n 60\n ],\n [\n 179.9,\n 73.8\n ],\n [\n 36.467721150184104,\n 73.8\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E.","contributorId":341321,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert E.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":908234,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","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":908235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DaCost, Jeffrey M.","contributorId":341322,"corporation":false,"usgs":false,"family":"DaCost","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[{"id":13422,"text":"Boston College","active":true,"usgs":false}],"preferred":false,"id":908236,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sorenson, Michael 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Dan","contributorId":341326,"corporation":false,"usgs":false,"family":"Skalos","given":"Dan","email":"","affiliations":[{"id":81725,"text":"California Department of Fish and Wildlife,","active":true,"usgs":false}],"preferred":false,"id":908240,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kondratyev, Alexander V.","contributorId":341327,"corporation":false,"usgs":false,"family":"Kondratyev","given":"Alexander V.","affiliations":[{"id":81726,"text":"Institute of Biological Problems of the North, FEB RAS, Magadan","active":true,"usgs":false}],"preferred":false,"id":908241,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scribner, Kim T.","contributorId":341328,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":908242,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walsh, Alyn","contributorId":341329,"corporation":false,"usgs":false,"family":"Walsh","given":"Alyn","email":"","affiliations":[{"id":81727,"text":"National Parks and Wildlife Services, Ireland","active":true,"usgs":false}],"preferred":false,"id":908243,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":908244,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Talbot, Sandra L.","contributorId":341330,"corporation":false,"usgs":false,"family":"Talbot","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":63248,"text":"Far Northwestern Institute of Art and Science","active":true,"usgs":false}],"preferred":false,"id":908245,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70238881,"text":"70238881 - 2022 - Optimizing Landsat Next shortwave infrared bands for crop residue characterization","interactions":[],"lastModifiedDate":"2022-12-15T13:48:36.566374","indexId":"70238881","displayToPublicDate":"2022-12-03T07:44:55","publicationYear":"2022","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":"Optimizing Landsat Next shortwave infrared bands for crop residue characterization","docAbstract":"This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (fR) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured fR. A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) < 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on fR estimation. For the two-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top fR estimation performance (R2 = 0.8222; RMSE = 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (R2 = 0.8145; RMSE = 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (R2 = 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized ratio-based index with a 2031–2085–2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (R2 = 0.8397; RMSE = 0.1231). Three-band indices with CAI-type wavelengths maintained top fR estimation performance for the full-NDVI dataset with a 2036–2111–2217 nm band combination (R2 = 0.7581; RMSE = 0.1548). The 2036–2111–2217 nm band combination was also top performing in fR estimation (R2 = 0.8690; RMSE = 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (±5 nm), 2097 nm (±14 nm), and 2214 (±11 nm) would optimize Landsat Next SWIR bands for fR estimation.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14236128","usgsCitation":"Lamb, B.T., Dennison, P., Hively, W.D., Kokaly, R.F., Serbin, G., Wu, Z., Dabney, P.W., Masek, J.G., Campbell, M., and Daughtry, C.S., 2022, Optimizing Landsat Next shortwave infrared bands for crop residue characterization: Remote Sensing, v. 14, no. 23, 6128, 29 p., https://doi.org/10.3390/rs14236128.","productDescription":"6128, 29 p.","ipdsId":"IP-144753","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236128","text":"Publisher Index Page"},{"id":410537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, Phillip 0000-0002-0241-1917","orcid":"https://orcid.org/0000-0002-0241-1917","contributorId":266031,"corporation":false,"usgs":false,"family":"Dennison","given":"Phillip","email":"","affiliations":[{"id":54865,"text":"Dept. Geography, Utah State University","active":true,"usgs":false}],"preferred":false,"id":859053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":859054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":859055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serbin, Guy 0000-0001-9345-1772","orcid":"https://orcid.org/0000-0001-9345-1772","contributorId":266030,"corporation":false,"usgs":false,"family":"Serbin","given":"Guy","email":"","affiliations":[{"id":54864,"text":"EOAnalytics","active":true,"usgs":false}],"preferred":false,"id":859056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":859057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dabney, Philip W.","contributorId":214572,"corporation":false,"usgs":false,"family":"Dabney","given":"Philip","email":"","middleInitial":"W.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Masek, Jeffery G.","contributorId":294418,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Campbell, Michael","contributorId":299937,"corporation":false,"usgs":false,"family":"Campbell","given":"Michael","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":859060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. 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The Northern Cordillera in North America is the second largest zinc-lead province, containing a further two of the world’s top ten deposits (Red Dog and Howards Pass). Despite this world-class endowment, exploration in both mineral provinces during the past 2 decades has not been particularly successful, yielding only two significant discoveries (Teena, Australia, and Boundary, Canada). One of the most important aspects of exploration is to choose mineral provinces and districts within geological belts that have the greatest potential for discovery. Here, we present results from these two zinc belts that highlight previously unused datasets for area selection and targeting. Lead isotope mapping using analyses of mineralized material has identified gradients in μ (238U/204Pb) that coincide closely with many major deposits. Locations of these deposits also coincide with a gradient in the depth of the lithosphere-asthenosphere boundary determined from calibrated surface wave tomography models converted to temperature. Furthermore, gradients in upward-continued gravity anomalies and a step in Moho depth correspond to a pre-existing major crustal boundary in both zinc belts. A spatial association of deposits with a linear mid- to lower-crustal resistivity anomaly from magnetotelluric data is also observed in the North Australian Zinc Belt. The change from thicker to thinner lithosphere is interpreted to localize prospective basins for zinc-lead mineralization and to control the gradient in lead isotope and geophysical data. These data, when combined with data indicative of paleoenvironment and changes in plate motion at the time of mineralization, provide new exploration criteria that can be used to identify prospective mineralized basins and define the most favorable parts of these basins.
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In this study, the analyzers were the Hach EZ7800 TOPHO, Hach Phosphax sc, Sea-Bird Scientific HydroCycle-PO4, and the YSI Inc. Alyza IQ PO4. Verification tests included laboratory trials comparing analyzer results to known standards with several known concentrations of dissolved organic matter and waste production estimates. Field trials were completed at the Vermilion River near Danville, Illinois (U.S. Geological Survey station 03339000), where analyzer-measured concentrations were compared against discrete samples across a wide range of environmental conditions from November 2020 to August 2021. Data coverage was closely tracked for analyzer malfunctions and operator errors that caused missing data. Laboratory and field trials indicated that each analyzer is a viable option for scientific surface-water studies depending on environmental conditions. Because of the complexity of the analyzers, a substantial time investiture was required to get maximum data coverage including considerable site infrastructure investments and well-trained technicians. Data coverage was closely related to each analyzer’s ability to handle elevated turbidity levels.
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This study used the complete set of continuous water-quality (WQ) data and discrete measurements of total ammonia collected by the U.S. Geological Survey from 2005 to 2019 at the four core sites in Upper Klamath Lake, Oregon, to examine relations between variables and extreme conditions that may be harmful for endemic Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris). Several graphical and tabular approaches were used to compare variables, sites, and years to better understand the factors contributing to and timing of extreme WQ in the lake. Extreme WQ thresholds were defined as the 1st or 99th percentiles of the daily average dataset of water temperature, pH, and dissolved oxygen (DO) concentration, and the weekly estimated un-ionized ammonia (NH3) from 2005 to 2019. Extreme WQ days were defined as those when at least 12 hours of measurements exceeded the extreme WQ threshold. The core site at Mid-Trench, which was also the deepest measurement site with a full-pool depth of 15 meters and at which water-quality sondes were deployed at the top and bottom of the water column, had the most extreme conditions of high water temperature, low DO, and high NH3. The upper sonde at Mid-Trench represented 40 percent of all days of extremely high water temperature (days with at least 12 hours exceeding 24.38 degrees Celsius) in the lake and 71 percent of all weekly estimates of extremely high NH3 (greater than 264 micrograms per liter) in the lake. The lower sonde at Mid-Trench represented 85 percent of all days of extremely low DO (days with at least 12 hours of DO concentrations less than 1.76 milligrams per liter) in the lake. In each of the study years, poor water quality at Mid-Trench, as represented by several metrics, lasted for multiple days. The shallowest site at the Williamson River outlet represented 54 percent of all days of extremely high pH (days with at least 12 hours of pH measurements exceeding 10.04) in the lake. The seasonality of extreme WQ during the summer sampling period (limited to June through September) was evaluated and most days of extremely high water temperature (83 percent) and extremely high pH (54 percent) occurred in July, whereas most days of extremely low DO (57 percent) and extremely high NH3 (57 percent) occurred in August. The years with the most days of extreme WQ accumulated for all variables (high water temperature, low DO, high pH, and high NH3) were 2012–15 and 2017, which all occurred in the latter half of the study period. The years with the fewest accumulated days of extreme WQ were 2010 and 2011.
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The Chesapeake Bay is a region along the eastern coast of the United States where sea-level rise is confounded with poorly resolved rates of land subsidence, thus new constraints on vertical land motions (VLM) in the region are warranted. In this paper, we provide a description of two campaign-style Global Positioning System (GPS) datasets, explain the methods used in data collection and validation, and present the experiment designed to quantify a new baseline of VLM in the Chesapeake Bay region of eastern North America. Data from GPS campaigns in 2019 and 2020 are presented as ASCII RINEX2.11 files and logsheets for each observation from the campaigns. Data were quality checked using the open-source program TEQC, resulting in average multipath 1 and 2 values of 0.68 and 0.57, respectively. All data are archived and publicly available for open access at the geodesy facility UNAVCO to abide by Findable, Accessible, Interoperable, Reusable (FAIR) data principles.
","language":"English","publisher":"Nature","doi":"10.1038/s41597-022-01864-8","usgsCitation":"Troia, G., Stamps, S., Lotspeich, R., Duda, J.M., McCoy, K., Moore, W., Hensel, P., Hippenstiel, R., McKenna, T., Andreasen, D.C., Geoghegan, C., Ulizo, T.P., Kronebusch, M., Carr, J., Walters, D., and Winn, N., 2022, GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions: Scientific Data, v. 9, no. 1, 744, 9 p., https://doi.org/10.1038/s41597-022-01864-8.","productDescription":"744, 9 p.","ipdsId":"IP-122566","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":445723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-022-01864-8","text":"Publisher Index Page"},{"id":410538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.29568067904435,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 40.12967557474843\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Troia, Gabrielle 0000-0001-6566-4623","orcid":"https://orcid.org/0000-0001-6566-4623","contributorId":299921,"corporation":false,"usgs":false,"family":"Troia","given":"Gabrielle","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamps, Sarah 0000-0002-3531-1752","orcid":"https://orcid.org/0000-0002-3531-1752","contributorId":299923,"corporation":false,"usgs":false,"family":"Stamps","given":"Sarah","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lotspeich, R. 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2022 - Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon","interactions":[],"lastModifiedDate":"2023-02-24T13:00:00.092972","indexId":"70240837","displayToPublicDate":"2022-12-02T06:57:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon","docAbstract":"Laterally directed explosive eruptions are responsible for multiple fatalities over the past decade and are an increasingly important volcanology problem. To understand the energy dynamics for these events, we collected field-scale explosion data from nine acoustic sensors surrounding a tiltable cannon as part of an exploratory experimental design. For each cannon discharge, the blast direction was varied systematically at 0°, 12°, and 24° from vertical, capturing acoustic wavefield directivity related to the tilt angle. While each event was similar in energy discharge potential, the resulting acoustic signal features were variable event-to-event, producing non-repetitious waveforms and spectra. Systematic features were observed in a subset of individual events for vertical and lateral discharges. For vertical discharges, the acoustic energy had a uniform radiation pattern. The lateral discharges showed an asymmetric radiation pattern with higher frequencies in the direction of the blast and depletion of those frequencies behind the cannon. Results suggest that, in natural volcanic systems, near-field blast directionality may be elucidated from acoustic sensors in absence of visual data, with implications for volcano monitoring and hazard assessment.
","language":"English","publisher":"Springer","doi":"10.1186/s40623-022-01732-0","usgsCitation":"Jolly, A., Kennedy, B., Matoza, R.S., Iezzi, A., Christensen, B.W., Johnson, R., Sork, A., and Fee, D., 2022, Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon: Earth, Planets and Space, v. 74, 177, 16 p., https://doi.org/10.1186/s40623-022-01732-0.","productDescription":"177, 16 p.","ipdsId":"IP-138530","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-022-01732-0","text":"Publisher Index Page"},{"id":413396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":865016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Benjamin","contributorId":302666,"corporation":false,"usgs":false,"family":"Kennedy","given":"Benjamin","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":865018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":865019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Bruce W.","contributorId":196298,"corporation":false,"usgs":false,"family":"Christensen","given":"Bruce","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":865020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Richard","contributorId":190189,"corporation":false,"usgs":false,"family":"Johnson","given":"Richard","email":"","affiliations":[],"preferred":false,"id":865021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sork, Amilea","contributorId":302667,"corporation":false,"usgs":false,"family":"Sork","given":"Amilea","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":865023,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236050,"text":"70236050 - 2022 - Wetland ecosystem health and biodiversity","interactions":[],"lastModifiedDate":"2024-03-27T20:46:12.939206","indexId":"70236050","displayToPublicDate":"2022-12-01T15:45:15","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"chapter":"14","title":"Wetland ecosystem health and biodiversity","docAbstract":"• Cropland expansion from 2008 to 2016 was mostly from losses of grassland (88%), with 3% losses from wetlands (a total of nearly 275,000 acres of wetlands, concentrated in the Prairie Pothole Region). Given the lack of national or regional datasets to track changes in RFS acreage, the extent of wetland losses directly attributable to the RFS cannot be more accurately estimated in the RtC3.
• Wetlands gains and losses are not distributed evenly across wetland types or sizes. Since 2007, the nation has lost 120.3 thousand acres of palustrine (marsh-like) wetlands and gained 205.9 thousand acres of lacustrine (lake-like) habitats in the conterminous United States. The diverse wetlands within these classes support different species and perform different ecosystem functions, including loss of functions that impact watershed hydrology, water quality, and water quantity.
• Small, seasonal wetlands are being lost at the fastest rate. The loss and consolidation of small wetlands to promote crop production has negatively impacted amphibians, invertebrates, and other aquatic species that depend on shallow water depths for reproduction. Shifts to longer hydroperiods in large or consolidated wetlands have more uniform (less diverse) invertebrate communities and can support fish that prey on insects and amphibians.
• Small wetlands and ponds are primary sources of water for aquifer recharge in the Northern Prairies. Recent studies in the Canadian portion of the Prairie Pothole Region found that while permanent ponds and wetlands are sources for recharge to aquifers, wetlands with surface water ponds that dry out every year play the dominant role in groundwater replenishment.
• While some Endangered Species Act-listed and other waterbirds have declined, waterfowl (ducks, geese, swans) as a group have not experienced declines over the past decade, possibly due to availability of food (grains), increased precipitation, and the interspersion of ponded waters and agricultural fields along migration routes.
• Shifts to corn and soybean production have resulted in more frequent application of chemicals, including pesticides and fertilizers. Increased usage of neonicotinoid insecticides is of particular concern because of their high toxicity to invertebrates, which are important food sources for wetland-dependent taxa.
• Evidence from the Prairie Pothole Region suggests that trends in larger wetland size, shifts to lakes and ponds (vs. vegetated wetlands), and prolonged and more frequent flooding are due to the combined effects of climate change and increased wetland ditching and consolidation. These trends are highly correlated with increased annual precipitation, which is projected to continue.
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Seabirds are highly mobile, with species-specific seasonal migrations that result in variable patterns of distribution in space and time. In remote offshore marine areas, obtaining useful and current information on resources is difficult to achieve and maintain, both fiscally and logistically, necessitating collaborative effort (Danielson et al. 2022). We used seabird at-sea survey data (2007-2021) and new modeling techniques to develop spatio-temporal models of seasonal abundance and distribution of species in waters of the Pacific Arctic. For six species groups selected as model test cases, we identified fine-scale distributions for each year, using data collected during summer to early fall (June through September). Our approach uses the best available data and can be updated as new data are generated, providing up-to-date information for regions with existing or potential future oil and gas development.
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","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., 2022, Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report: Annual Report, 3 p.","productDescription":"3 p.","ipdsId":"IP-152071","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415836,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573318","linkFileType":{"id":5,"text":"html"}},{"id":426324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Fort Laramie National Historic Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -104.56770704017384,\n 42.210821091328\n ],\n [\n -104.56770704017384,\n 42.19287280305102\n ],\n [\n -104.52383325080481,\n 42.19287280305102\n ],\n [\n -104.52383325080481,\n 42.210821091328\n ],\n [\n -104.56770704017384,\n 42.210821091328\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869741,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70242767,"text":"70242767 - 2022 - Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T16:41:17.236689","indexId":"70242767","displayToPublicDate":"2022-12-01T09:55:41","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.”
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","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., and Richardson, T., 2022, Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 4 p.","productDescription":"4 p.","ipdsId":"IP-152075","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415835,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573317","linkFileType":{"id":5,"text":"html"}},{"id":426321,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Wind Cave National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.49938816977327,\n 43.633694711675986\n ],\n [\n -103.5024470931983,\n 43.55944982284214\n ],\n [\n -103.52141241843475,\n 43.54383294926339\n ],\n [\n -103.52202420312013,\n 43.52023368800823\n ],\n [\n -103.45748091884613,\n 43.51534889803226\n ],\n [\n -103.45657280095472,\n 43.53372182682589\n ],\n [\n -103.43975828125109,\n 43.5356829718161\n ],\n [\n -103.44038918420713,\n 43.58528414983906\n ],\n [\n -103.41717960271762,\n 43.58473704935065\n ],\n [\n -103.41664429111844,\n 43.56545928494155\n ],\n [\n -103.38062546778514,\n 43.56346760240271\n ],\n [\n -103.38009015618593,\n 43.56812536845743\n ],\n [\n -103.36058951934952,\n 43.56694573600919\n ],\n [\n -103.3588306383801,\n 43.592360590123576\n ],\n [\n -103.34185361336944,\n 43.59180514516018\n ],\n [\n -103.33680638971731,\n 43.60876454212675\n ],\n [\n -103.33665344354603,\n 43.62660987781496\n ],\n [\n -103.3485832449052,\n 43.62505981511873\n ],\n [\n -103.35317163004311,\n 43.63059510828057\n ],\n [\n -103.43729202423958,\n 43.63170210623065\n ],\n [\n -103.45365726456492,\n 43.640225573499706\n ],\n [\n -103.48019342527975,\n 43.641830445497\n ],\n [\n -103.49938816977327,\n 43.633694711675986\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, Timm","contributorId":334581,"corporation":false,"usgs":false,"family":"Richardson","given":"Timm","email":"","affiliations":[],"preferred":false,"id":895967,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238720,"text":"70238720 - 2022 - PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements","interactions":[],"lastModifiedDate":"2024-02-23T16:04:23.105819","indexId":"70238720","displayToPublicDate":"2022-12-01T09:55:30","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements","docAbstract":"The PHREEQ-N-AMDTreat+REYs water-quality modeling tools have the fundamental capability to simulate aqueous chemical reactions and predict the formation of metal-rich solids during the treatment of acid mine drainage (AMD). These new user-friendly, publicly available tools were expanded from the PHREEQ-N-AMDTreat tools to include the precipitation of rare-earth elements plus yttrium (REYs) and the adsorption of REYs onto hydrous Fe, Al, and Mn oxides. The tool set consists of a caustic titration model that indicates equilibrium surface and aqueous speciation of REYs as functions of pH and caustic agent, and a kinetics+adsorption model that simulates progressive changes in pH, major ions, and REYs in water and solids during sequential steps through passive and/or active treatment. Each model has a user interface (UI) that facilitates the input of water-quality data and adjustment to geochemical or treatment system variables; for example, retention time and aeration rate are adjustable parameters in the kinetics model. On-screen graphs display results of changes in metals and associated solute concentrations as functions of pH or retention time; details are summarized in output tables. A goal of such modeling is to identify strategies that could produce a concentrated REYs extract from AMD or mine waste leachate. For example, if REYs could be concentrated after first removing substantial Fe and Al, the final REYs-bearing phase(s) could be more efficiently processed for REYs recovery and, therefore, may represent a more valuable commodity. Preliminary modeling supports the hypothesis that Fe and Al can be removed at pH < 5.5 using conventional sequential oxidation and neutralization treatment processes without removing REYs, and that further increasing pH can promote the adsorption of REYs by hydrous Mn oxides. Alternatively, chemicals such as oxalate or phosphate may be added to precipitate REYs compounds following initial steps to decrease Fe and Al concentrations. The aqueous geochemical model framework is comprehensive and permits evaluation of effects from interactive chemical and physical variables. Field studies that demonstrate REYs attenuation from AMD and corresponding solid-phase formation during specific treatment steps plus laboratory studies of aqueous/solid interactions are helpful to corroborate, refine, and constrain modelin parameters.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Acid Mine Drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Mine Drainage","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Cravotta, C., 2022, PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements, in Proceedings of the 12th International Conference on Acid Mine Drainage, September 18-24, 2022, p. 788-804.","productDescription":"7 p.","startPage":"788","endPage":"804","ipdsId":"IP-137202","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":410097,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022","linkFileType":{"id":5,"text":"html"}},{"id":425945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858359,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237203,"text":"70237203 - 2022 - USGS invasive carp database management and integration support","interactions":[],"lastModifiedDate":"2024-03-28T14:21:02.969407","indexId":"70237203","displayToPublicDate":"2022-12-01T09:16:29","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"USGS invasive carp database management and integration support","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2022 Invasive carp monitoring and response plan (MRP)","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Invasive Carp Regional Coordinating Committee (ICRCC)","usgsCitation":"Hlavacek, E., and Harrison, T.J., 2022, USGS invasive carp database management and integration support, 3 p.","productDescription":"3 p.","startPage":"77","endPage":"79","ipdsId":"IP-137577","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":427215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427214,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hlavacek, Enrika 0000-0002-9872-2305","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":297184,"corporation":false,"usgs":false,"family":"Hlavacek","given":"Enrika","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":853619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":853620,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70238472,"text":"70238472 - 2022 - Benefits of genetic data for the design of Brook Trout translocation efforts","interactions":[],"lastModifiedDate":"2024-02-23T15:02:52.482747","indexId":"70238472","displayToPublicDate":"2022-12-01T08:58:28","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Benefits of genetic data for the design of Brook Trout translocation efforts","docAbstract":"With wild trout populations in decline, many conservation practitioners are evaluating the feasibility of incorporating reintroduction and genetic rescue into management frameworks. As interest in these conservation tools continues to grow, so too has the need for rigorous science to evaluate translocation success and improve the efficacy of future efforts. From this, it has become increasingly apparent that approaches which consider both demographics and genetics are most likely to result in successful translocations. In particular, while demographic data are often a central component of project designs, they are insufficient for diagnosing genetic threats such as low diversity, maladaptation, and introgression that characterize many wild trout populations. Consideration for these genetic characteristics is important for long-term project success and to reduce the unintended spread of domestic lineages across the landscape. Using a case study of reintroduction of Brook Trout Salvelinus fontinalis into a North Carolina stream, we show how a combined demographic and genetic approach can be used throughout all stages of project design. In particular, we highlight how genetic data were informative for identifying source populations that had the greatest potential to establish a population with the genetic diversity needed for future adaptation. We also discuss how genetic monitoring of the reintroduced population provided insights into reproductive success and genetic diversity that could be indicative of long-term population persistence. While monitoring is ongoing, this combined genetic and demographic approach provides a promising framework for helping meet reintroduction goals and provides more opportunities for adaptive management following translocation.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Wild Trout XIII Symposium","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Wild Trout XIII Symposium","conferenceDate":"September 27-30, 2022","conferenceLocation":"West Yellowstone, MT","language":"English","publisher":"Wild Trout Symposium","usgsCitation":"White, S.L., Johnson, T.C., Rash, J.M., Lubinski, B.A., and Kazyak, D., 2022, Benefits of genetic data for the design of Brook Trout translocation efforts, in Proceedings of the Wild Trout XIII Symposium, West Yellowstone, MT, September 27-30, 2022, p. 179-184.","productDescription":"6 p.","startPage":"179","endPage":"184","ipdsId":"IP-143325","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":425938,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildtroutsymposium.com/wildTroutXIII.php"},{"id":425939,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"White, Shannon L. 0000-0003-4687-6596","orcid":"https://orcid.org/0000-0003-4687-6596","contributorId":263424,"corporation":false,"usgs":true,"family":"White","given":"Shannon","email":"","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":857572,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Thomas C","contributorId":245999,"corporation":false,"usgs":false,"family":"Johnson","given":"Thomas","email":"","middleInitial":"C","affiliations":[{"id":36454,"text":"North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":857573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rash, Jacob M","contributorId":218128,"corporation":false,"usgs":false,"family":"Rash","given":"Jacob","email":"","middleInitial":"M","affiliations":[{"id":39760,"text":"Division of Inland Fisheries, North Carolina Wildlife Resources Commission","active":true,"usgs":false}],"preferred":false,"id":857574,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lubinski, Barbara A. 0000-0003-3568-2569","orcid":"https://orcid.org/0000-0003-3568-2569","contributorId":202483,"corporation":false,"usgs":true,"family":"Lubinski","given":"Barbara","email":"","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":857575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":857576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242763,"text":"70242763 - 2022 - Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","interactions":[],"lastModifiedDate":"2024-03-05T15:12:59.931116","indexId":"70242763","displayToPublicDate":"2022-12-01T08:53:45","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":7577,"text":"Annual Report","active":true,"publicationSubtype":{"id":4}},"title":"Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model","docAbstract":"The annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. 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This annual report provides raw results of these treatments applied to plots at Badlands National Park established specifically to accumulate this type of data and therefore accelerate the rate of learning accomplished in the adaptive management cycle.","language":"English","publisher":"National Park Service","usgsCitation":"Symstad, A., 2022, Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model: Annual Report, 4 p.","productDescription":"4 p.","ipdsId":"IP-152066","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":415833,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/RPRS/IAR/Profile/573319"},{"id":426319,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.9816413781004,\n 43.81545397317089\n ],\n [\n -102.10404473861178,\n 43.820721999747335\n ],\n [\n -102.18038072914308,\n 43.900094036554435\n ],\n [\n -102.43056276472474,\n 43.93869274314153\n ],\n [\n -102.46588237645057,\n 43.87808438644481\n ],\n [\n -102.46227631796151,\n 43.81240136470154\n ],\n [\n -102.52583495138943,\n 43.76271118438757\n ],\n [\n -102.61056188331933,\n 43.745312984118215\n ],\n [\n -102.61512488487168,\n 43.697319743127245\n ],\n [\n -102.79687064513114,\n 43.69924298806647\n ],\n [\n -102.80984003809536,\n 43.66341493167664\n ],\n [\n -102.90154396748794,\n 43.662470844462945\n ],\n [\n -102.91146582849841,\n 43.47194100980886\n ],\n [\n -102.80317094893881,\n 43.47397686938032\n ],\n [\n -102.71249040143672,\n 43.53766576763433\n ],\n [\n -102.60922465539478,\n 43.48525504065212\n ],\n [\n -102.55509069073659,\n 43.49459163360207\n ],\n [\n -102.49109164390808,\n 43.49135456209459\n ],\n [\n -102.40294493885204,\n 43.47379006618429\n ],\n [\n -102.3098505724263,\n 43.465209713416414\n ],\n [\n -102.27255837742683,\n 43.48077466407841\n ],\n [\n -102.25880034575657,\n 43.582995671627835\n ],\n [\n -102.35279341761728,\n 43.577534191075756\n ],\n [\n -102.44677360300271,\n 43.541331165393316\n ],\n [\n -102.54267701175816,\n 43.56638417465828\n ],\n [\n -102.58354318324504,\n 43.60646020158184\n ],\n [\n -102.53234630194093,\n 43.63244149516539\n ],\n [\n -102.49724178055375,\n 43.716432342349705\n ],\n [\n -102.34297147119695,\n 43.748511777562356\n ],\n [\n -102.2746784068271,\n 43.781173073417534\n ],\n [\n -102.25598001505656,\n 43.80871222310375\n ],\n [\n -102.08569317423665,\n 43.7448827308326\n ],\n [\n -101.86229425624181,\n 43.732224058910504\n ],\n [\n -101.87763233485761,\n 43.800704970828534\n ],\n [\n -101.9816413781004,\n 43.81545397317089\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869738,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70248701,"text":"70248701 - 2022 - COSMOS Ground-Motion Simulation Working Group workshops #1 and #2","interactions":[],"lastModifiedDate":"2023-09-19T13:31:46.411719","indexId":"70248701","displayToPublicDate":"2022-12-01T08:30:08","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"COSMOS Ground-Motion Simulation Working Group workshops #1 and #2","docAbstract":"These 2 workshops were held in response to interest generated from sessions on the use of simulated earthquake ground motions at the 2020 and 2021 Consortium of Organizations for Strong Motion Observation Systems (COSMOS) Technical Sessions. The discussions at the Technical Sessions highlighted desires to promote the use of simulated earthquake ground motions for engineering applications and the need to coordinate efforts to validate and disseminate the data. Our first workshop focused on curating and disseminating simulated earthquake ground-motion data. Our second workshop focused on validating simulated ground-motions for engineering applications. Both workshops included a few invited presentations from providers (ground-motion simulators) and engineering user perspectives followed by open discussions. About 100 people participated in each of the workshops.","language":"English","publisher":"Consortium of Organizations for Strong Motion Observation Systems","usgsCitation":"Aagaard, B.T., Askan, A., Rezaeian, S., Ahdi, S.K., and Yong, A., 2022, COSMOS Ground-Motion Simulation Working Group workshops #1 and #2, 16 p.","productDescription":"16 p.","ipdsId":"IP-151830","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":420949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":420879,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://strongmotion.org/simulation-working-group/"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":883243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Askan, Aysegul 0000-0003-4827-9058","orcid":"https://orcid.org/0000-0003-4827-9058","contributorId":296102,"corporation":false,"usgs":false,"family":"Askan","given":"Aysegul","email":"","affiliations":[{"id":49823,"text":"Middle East Technical University","active":true,"usgs":false}],"preferred":false,"id":883244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":238513,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883245,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahdi, Sean Kamran 0000-0003-0274-5180","orcid":"https://orcid.org/0000-0003-0274-5180","contributorId":265143,"corporation":false,"usgs":true,"family":"Ahdi","given":"Sean","email":"","middleInitial":"Kamran","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883246,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":883247,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239124,"text":"70239124 - 2022 - Effects of release techniques on parent-reared whooping cranes in the eastern migratory population","interactions":[],"lastModifiedDate":"2022-12-28T13:42:34.222167","indexId":"70239124","displayToPublicDate":"2022-12-01T07:40:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12807,"text":"Proceedings of the North American Crane Workshop","active":true,"publicationSubtype":{"id":10}},"title":"Effects of release techniques on parent-reared whooping cranes in the eastern migratory population","docAbstract":"Reintroduction of an Eastern Migratory Population (EMP) of whooping cranes (Grus americana) in the United States by release of captive-reared individuals began in 2001. As of 2020, the EMP has approximately 21 breeding pairs and has had limited recruitment of wild-hatched individuals, thus captive-reared juveniles continue to be released into breeding areas in Wisconsin to maintain the population. We investigated the effects of release techniques on survival, behavior, site fidelity, and conspecific associations of 42 captive-parent-reared whooping cranes released during 2013-2019 into the EMP. Individuals were monitored intensively post-release, then as a part of a long-term monitoring program, locational, behavioral, and habitat use data were collected and analyzed. Most cranes roosted in water post-release; however, we documented 4 parent-reared cranes roosting on dry land. Most cranes eventually associated with other whooping cranes; however, juveniles released near single adult cranes were less likely to associate with other whooping cranes during their first migration or winter than juveniles released near other types of whooping crane pairs or groups. Parent-reared and costume-reared whooping cranes had similar rates of survival 1 year post-release (69.0% and 64.4%, respectively). The highest risk of mortality was within the first 100 days post-release, and the leading known causes of death were predation and impact trauma due to powerline or vehicle collisions. Both costume- and parent-reared cranes had strong fidelity to release sites. We advise releasing parent-reared cranes near pairs or groups of whooping cranes and taking measures to reduce the risk of mortality during the immediate period after release (e.g., predator aversion training, marking powerlines).
Laura K. Lautz is a premier mentor, collaborator, and researcher at the intersection of natural hydrologic systems and humans. Her research has shifted the paradigm around measuring and understanding the impacts of surface water and groundwater interactions across spatial and temporal scales. She has done this by testing and refining new methods and by collaborating with, training, supporting, and mentoring diverse scientists. Here, we review her research across five themes, summarizing the prior status of the field, what Lautz contributed, as well as new directions in the field inspired by her work. Lautz’s research expanded our understanding of the impacts of stream restoration on surface water-groundwater interactions, where she tested new field methods and showed that restoration structures increase hyporheic exchange, locally altering biogeochemical function of the streambed. She refined novel methods for measuring surface water-groundwater exchanges and worked to make these methods easily accessible through freely available software. Her research group greatly expanded the use of heat as a quantitative tracer of hydrologic processes via the well-used VFLUX and HFLUX programs. Her research evaluated the impacts of surface water-groundwater interactions in urban streams, showing the substantial fluxes of nutrients and chloride that can move through those exchanges and the potential for groundwater to help buffer contamination. To assess groundwater impacts on streamflow below tropical glaciers, she used a wide range of field methods to reveal the sensitivity of these systems to climate change. Finally, she built tools to quantify natural brine contamination of drinking water wells in areas that may later be subject to high-volume hydraulic fracturing, creating a needed ‘pre-fracking’ dataset. Through this process, she identified multiple sources of salinity that are already reaching wells in these systems. Overall, this research has been done with a focus on mentoring and training the next generation of hydrologists, including work to specifically train for careers beyond academia, and facilitating early career scientists to realize their innate potentials. With former trainees in careers across industry, government, and academia, Dr. Laura K. Lautz is now working to build cross-disciplinary research at even larger scales, across federal research units, guaranteeing that an even larger impact on hydrology is still to come.
The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.
Walleye, Sander vitreus (Mitchill), natural recruitment has declined in northern Wisconsin lakes over time. Age-0 and age-1 walleye relative abundance (catch per unit effort; CPE) data from northern Wisconsin (1986–2019) were used to test for abiotic (i.e. lake characteristics and temperature variables) and biotic (age-0 and age-1 CPE) factors influencing age-0 to age-1 walleye mortality. Age-0 to age-1 walleye mortality was elevated at high age-0 CPE and variable at low age-0 CPE, which indicated strong density-dependence. Environmental factors such as spawning and ontogenetic phenology (climate change and ice-off dates), trophic mismatches, and metabolic and consumptive demand influenced age-0 to age-1 walleye mortality less strongly. Elevated age-0 to age-1 walleye mortality at low age-0 CPE supports previous findings of depensatory recruitment dynamics in northern Wisconsin walleye populations. Additional research is needed to address elevated juvenile walleye mortality at low adult stock sizes and/or with declining natural recruitment to inform management decisions.
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\"}}]}","volume":"29","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Zebro, Logan R.","contributorId":348716,"corporation":false,"usgs":false,"family":"Zebro","given":"Logan R.","affiliations":[{"id":83401,"text":"Escanaba Lake Research Station","active":true,"usgs":false}],"preferred":false,"id":923713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mrnak, Joseph T.","contributorId":348717,"corporation":false,"usgs":false,"family":"Mrnak","given":"Joseph T.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":923714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Stephanie L.","contributorId":348718,"corporation":false,"usgs":false,"family":"Shaw","given":"Stephanie L.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sass, Greg G.","contributorId":348719,"corporation":false,"usgs":false,"family":"Sass","given":"Greg G.","affiliations":[{"id":83401,"text":"Escanaba Lake Research Station","active":true,"usgs":false}],"preferred":false,"id":923717,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70238529,"text":"sir20225098 - 2022 - Verification of irrigated agricultural land acreage in 55 counties in Florida, 2013–21","interactions":[],"lastModifiedDate":"2022-12-01T13:40:32.676448","indexId":"sir20225098","displayToPublicDate":"2022-11-30T11:35:28","publicationYear":"2022","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":"2022-5098","displayTitle":"Verification of Irrigated Agricultural Land Acreage in 55 Counties in Florida, 2013–21","title":"Verification of irrigated agricultural land acreage in 55 counties in Florida, 2013–21","docAbstract":"In 2012, the Florida Legislature mandated that the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy, promote an agricultural water-conservation program that would include a cost-share program and best management practices and that would aid the five water management districts in the development of consistent agricultural water-supply planning, assisting the districts in projecting future agricultural water needs and promoting consistency in water-use estimates among the districts. Beginning in 2013, the FDACS created a series of agriculture and irrigated land-use maps for all Florida counties for the purpose of estimating current and forecasting future water demands. These maps, produced and updated periodically by The Balmoral Group, were based on baseline data from 2010 and have been updated with a combination of satellite images and land-use data from water management districts in subsequent years (2013–21) to help create a statewide database of irrigated agricultural lands. The purpose of this multiyear cooperative study between the U.S. Geological Survey and the FDACS is to provide (1) a detailed geospatial database of verified irrigated field locations with selected attributes as ArcGIS shapefiles and (2) aggregated acreage totals by crop type for all or parts of 55 of the 67 counties within Florida. Ten of the remaining 12 counties were fully mapped by the St. John’s River Water Management District in 2015; the other 2 counties were not mapped because they contained very little irrigated agricultural land. Irrigated agricultural fields identified on The Balmoral Group baseline maps for each of the 55 counties were either physically observed by U.S. Geological Survey or were verified through water management district’s consumptive water-use permit database. A select group of counties were chosen to be field verified each year, concluding with a total of 55 counties in Florida field verified between October 2013 and August 2021. The results provided from this multiyear study can help increase the accuracy of irrigation water-use estimates for counties in Florida.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
https://www.usgs.gov/centers/car-fl-water