{"pageNumber":"631","pageRowStart":"15750","pageSize":"25","recordCount":165227,"records":[{"id":70236131,"text":"70236131 - 2020 - Peak ground motions and site response at Anza and Imperial Valley, California","interactions":[],"lastModifiedDate":"2022-08-30T14:00:58.547116","indexId":"70236131","displayToPublicDate":"2020-01-15T08:55:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Peak ground motions and site response at Anza and Imperial Valley, California","docAbstract":"Power spectra of shear-waves for eighteen earthquakes from the Anza-Imperial Valley region were inverted for source, mid-path Q, site attenuation and site response. The motivation was whether differences in site attenuation (parameterized as t*, r/cQ, where r is distance along ray path near the site, c is shear velocity and Q is the quality factor that parameterizes attenuation) and site response could be correlated with residuals in peak values of velocity or acceleration after removing the affect of distance-dependent attenuation. We decomposed spectra of S-waves from horizontal components of 18 earthquakes from 2010 to 2018 into a common source for each event with ω−2 spectral fall-off at high frequencies and then projected the residuals onto path and site terms following the methodology of Boatwright et al. (Bull Seismol Soc Am 81:1754–1782, 1991). The site terms were constrained to have an amplification at a particular frequency governed by VS30 at two of the sites which had downhole shear-wave logs. The 18 events, 3 < M < 4, had moments between approximately 1020 and 1022 dyne-cm, and stress drops between 1 and 100 bars. Average mid-crust attenuation had a Q of 844 reflecting the average path through the crystalline rock of the San Jacinto Mountains. t* for each station corresponded to the geologic environment such that stations on hard rock had low t* (e.g. stations KNW, PFO and RDM) a station in the San Jacinto fault zone (station SND) had a moderate t* of 0.035 s and stations in the Imperial Valley usually had higher t*s. Generally t* correlated with average amplification suggesting that sites characterized by low surface velocities and higher attenuation also have more amplification in the 1–6 Hz band. Residuals of peak values were determined by subtracting the prediction of Boore and Atkinson (2008). There is a correlation between average amplification and peak velocity, but not peak acceleration. Interestingly, there is less scatter at high values of amplification although there is also less data. Scatter in values of peak velocity and peak acceleration are higher at shorter compared to longer durations. When using a frequency-dependent form for Q, variances are higher, sometimes much higher; the dataset does not support frequency-dependent Q, which is not similar to results from the Imperial Valley and northeastern North America.
","language":"English","publisher":"Springer","doi":"10.1007/s00024-019-02366-2","usgsCitation":"Fletcher, J.P., and Boatwright, J., 2020, Peak ground motions and site response at Anza and Imperial Valley, California: Pure and Applied Geophysics, v. 177, p. 2753-2769, https://doi.org/10.1007/s00024-019-02366-2.","productDescription":"17 p.","startPage":"2753","endPage":"2769","ipdsId":"IP-103872","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":458127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00024-019-02366-2","text":"Publisher Index Page"},{"id":405902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Anza","otherGeospatial":"Imperial Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 32.7\n ],\n [\n -115.2,\n 32.7\n ],\n [\n -115.2,\n 33.8\n ],\n [\n -117,\n 33.8\n ],\n [\n -117,\n 32.7\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"177","noUsgsAuthors":false,"publicationDate":"2020-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Fletcher, Jon Peter B. 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":1216,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":850200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boatwright, John","contributorId":219666,"corporation":false,"usgs":false,"family":"Boatwright","given":"John","affiliations":[{"id":40044,"text":"USGS, deceased","active":true,"usgs":false}],"preferred":false,"id":850201,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70207810,"text":"sir20195151 - 2020 - Storage capacity and sedimentation characteristics of the San Antonio Reservoir, California, 2018","interactions":[],"lastModifiedDate":"2022-04-25T20:37:40.39933","indexId":"sir20195151","displayToPublicDate":"2020-01-15T08:04:46","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5151","displayTitle":"Storage Capacity and Sedimentation Characteristics of the San Antonio Reservoir, California, 2018","title":"Storage capacity and sedimentation characteristics of the San Antonio Reservoir, California, 2018","docAbstract":"The San Antonio Reservoir is a large water storage facility in Alameda County, California, and is a major component of the Hetch Hetchy Regional Water System (RWS). The RWS is a water-supply system owned and operated by the San Francisco Public Utilities Commission (SFPUC) and provides water for about 2.7 million people in the San Francisco, Santa Clara, Alameda, and San Mateo Counties. The San Antonio Reservoir is one of two RWS reservoirs in Alameda County and the third largest of the RWS reservoirs in the San Francisco Bay Area. The reservoir was formed by the James H. Turner Dam, which was completed in 1965. At the time of construction, the reservoir was estimated to have 50,500 acre-feet (acre-ft) of storage capacity. That early estimate was based on a 1963 pre-construction topographic map, which was drawn from aerial photographs. The capacity of the reservoir was later surveyed in 1994 and 2000. These two later surveys did not include the upper 18 feet (ft) of the reservoir, which represents roughly 30 percent of the overall storage volume. To determine the storage capacity and provide updated stage-capacity curves up to the spillway, the U.S. Geological Survey, in cooperation with the SFPUC, surveyed the bathymetry and shoreline of the reservoir in April 2018.
The bathymetric survey was performed by making depth soundings using a boat-mounted, multibeam echosounder. At the time of the survey, the water level was between 13 and 14 ft below the spillway elevation. To measure capacity between the water line up to the spillway elevation, topography along most of the shoreline was surveyed from the boat using a terrestrial Light Detection and Ranging (LiDAR) scanner and in other areas by using ground-survey techniques. Location during bathymetric and topographic data collection was determined using a Global Navigation Satellite System-Real Time Network system. Vertical profiles of sound speed were collected periodically. The sound-speed profiles were used to spatially and temporally adjust the sound-speed calculations used to determine depth from the soundings. Approximately 125 kilometers (78 miles) of transects with a total of about 560 million depth soundings and topographic LiDAR points were collected (about 160 per square meter). In addition, approximately 500 topographic survey points were collected in shallow, wadable areas and on land near the upper reservoir area using a Global Navigation Satellite System receiver attached to a fixed length survey rod. Depth soundings, terrestrial LiDAR points, topographic survey points, and a digitized shoreline were merged and interpolated to generate a digital elevation model (DEM) of the reservoir. Gridded elevation data extracted from the DEM were then tabulated to determine total reservoir capacity and create reservoir stage-surface area and stage-storage capacity tables.
Results of the reservoir capacity analysis indicated that the reservoir has 53,266 (plus or minus 140) acre-ft of storage capacity, which is an increase of 2,766 acre-ft (or 5.5 percent) greater than the original 1965 estimate; the increase is likely due to improved survey methods. Also, at the time of this 2018 survey, Intake #1 (the lowest intake) was not in operation. Intake #1 is estimated to be buried approximately 10 ft below the bed, whereas Intake #2 is about 20 ft above the bed. There are five intakes at different elevation levels; however, when consecutive lower intakes become inoperable due to sedimentation, the live storage capacity (capacity available for use) is reduced. At the time of this survey, the remaining live storage (above Intake #2) was approximately 52,363 acre-ft.
The 2018 stage-capacity curve was compared to the original 1965 stage-capacity curve. Although overall, the changes indicate an increase in storage capacity, the change in volume at 372.7 ft North American Vertical Datum of 1988 (370 ft National Geodetic Vertical Datum of 1929, NGVD 29) shows a decrease of 733 acre-ft (the elevation of 370 ft NGVD 29 was used because it is the lowest elevation available for the 1965 stage-capacity curves). This finding agrees with the observed accumulation of sediment over Intake #1. That volume was converted to an annual sediment yield of 0.35 acre-ft per square mile (or 165 cubic meters per square kilometer), which is of the same order of magnitude as that found in other watersheds for the Coast Ranges in California. A decrease of 733 acre-ft between 1965 and 2018 thus represents a loss of 1.5 percent of the overall storage capacity in the reservoir. The updated stage-surface area and stage-capacity tables provided in this report and online (https://doi.org/10.5066/P9KC9DU8) can be used by the SFPUC to improve reservoir operations and serve as an accurate baseline to monitor bathymetric changes in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195151","collaboration":"Prepared in cooperation with the San Francisco Public Utilities Commission","usgsCitation":"Marineau, M.D., Wright, S.A, and Lopez, J.V., 2020, Storage capacity and sedimentation characteristics of the San Antonio Reservoir, California, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5151, 34 p., https://doi.org/10.3133/sir20195151.","productDescription":"Report: vi, 34 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-105258","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":399623,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109595.htm"},{"id":371223,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KC9DU8","linkHelpText":"Bathymetry, Stage-Area, and Stage-Volume Tables for the San Antonio Reservoir, California, 2018"},{"id":371222,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5151/sir20195151.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5151"},{"id":371221,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5151/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Antonio Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.81846618652345,\n 37.596415965954684\n ],\n [\n -121.85348510742188,\n 37.57138553454929\n ],\n [\n -121.841983795166,\n 37.565262680889965\n ],\n [\n -121.8335723876953,\n 37.56186087804736\n ],\n [\n -121.82378768920898,\n 37.5711134184077\n ],\n [\n -121.81726455688477,\n 37.582541440297746\n ],\n [\n -121.80301666259766,\n 37.5814531328266\n ],\n [\n -121.80473327636719,\n 37.59083926161267\n ],\n [\n -121.81846618652345,\n 37.596415965954684\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
","tableOfContents":"- Abstract
- Introduction
- Data and Sample Collection
- Data Analysis
- Results
- Discussion of Reservoir Sedimentation
- Summary
- References Cited
- Glossary
","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-01-15","noUsgsAuthors":false,"publicationDate":"2020-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, Joan V. 0000-0003-4477-7025 jvlopez@usgs.gov","orcid":"https://orcid.org/0000-0003-4477-7025","contributorId":221656,"corporation":false,"usgs":true,"family":"Lopez","given":"Joan","email":"jvlopez@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":779410,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70224972,"text":"70224972 - 2020 - Estimation of nonlinear water-quality trends in high-frequency monitoring data","interactions":[],"lastModifiedDate":"2021-10-11T13:02:50.792784","indexId":"70224972","displayToPublicDate":"2020-01-15T07:58:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of nonlinear water-quality trends in high-frequency monitoring data","docAbstract":"Recent advances in high-frequency water-quality sensors have enabled direct measurements of physical and chemical attributes in rivers and streams nearly continuously. Water-quality trends can be used to identify important watershed-scale changes driven by natural and anthropogenic influences. Statistical methods to estimate trends using high-frequency data are lacking. To address this gap, an evaluation of the generalized additive model (GAM) approach to test for trends in high-frequency data was conducted. Our proposed framework includes methods for handling serial correlation, trend estimation and slope-change detection, and trend interpretation at arithmetic scale for log-transformed variables. Water-temperature and turbidity data, representing two analytes with different temporal patterns, collected from the James River at Cartersville, Virginia, USA, were chosen for this analysis. Results indicated that the model, including flow, season, time covariates, and interaction between flow and season performed well for both analytes. The same model structure was applied to specific conductance data, collected from a small highly urbanized watershed, with satisfactory model performance. The water temperature GAM results indicated that the significant decreasing-then-increasing patterns after 2012 were mainly driven by air temperature changes. The turbidity trend was not significant over time. The specific conductance results showed a consistently upward trend over the last decade due to ever-increasing urbanization in the small watershed. This study suggests that the GAM method has great potential as a useful tool for trend analysis on high-frequency data, and for informing watershed managers of hydro-climatic and human influences on water quality by detecting crucial signal variation over time.
Atmospheric dust can influence biogeochemical cycles, accelerate snowmelt, and affect air, water quality, and human health. Yet, the bulk of atmospherically transported material remains poorly quantified in terms of total mass fluxes and composition. This lack of information stems in part from the challenges associated with measuring dust deposition. Here we report on the design and efficacy of a new dry deposition sampler (Dry Deposition Sampling Unit (DSU)) and method that quantifies the gravitational flux of dust particles. The sampler can be used alone or within existing networks such as those employed by the National Atmospheric Deposition Program (NADP). Because the samplers are deployed sterile and the use of water to remove trapped dust is not required, this method allows for the recovery of unaltered dry material suitable for subsequent chemical and microbiological analyses. The samplers were tested in the laboratory and at 15 field sites in the western United States. With respect to material retention, sampler performance far exceeded commonly used methods. Retrieval efficiency was >97% in all trials and the sampler effectively preserved grain size distributions during wind exposure experiments. Field tests indicated favorable comparisons to dust-on-snow measurement across sites (r2 0.70, p < 0.05) and within sites to co-located aerosol data (r2 0.57–0.99, p < 0.05). The inclusion of dust deposition and composition monitoring into existing networks increases spatial and temporal understanding of the atmospheric transport on materials and substantively furthers knowledge of the effects of dust on terrestrial ecosystems and human exposure to dust and associated deleterious compounds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeolia.2020.100600","usgsCitation":"Brahney, J., Wetherbee, G.A., Sexstone, G.A., Youngbull, C., Strong, P., and Heindel, R.C., 2020, A new sampler for the collection and retrieval of dry dust deposition: Aeolian Research, v. 45, 100600, 10 p., https://doi.org/10.1016/j.aeolia.2020.100600.","productDescription":"100600, 10 p.","ipdsId":"IP-111272","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":458132,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2020.100600","text":"Publisher Index Page"},{"id":382170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Nevada, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.927734375,\n 33.7243396617476\n ],\n [\n -110.1708984375,\n 35.92464453144099\n ],\n [\n -107.5341796875,\n 38.09998264736481\n ],\n [\n -103.4033203125,\n 38.92522904714054\n ],\n [\n -102.568359375,\n 40.1452892956766\n ],\n [\n -104.853515625,\n 41.57436130598913\n ],\n [\n -109.248046875,\n 44.11914151643737\n ],\n [\n -112.67578124999999,\n 44.653024159812\n ],\n [\n -115.75195312499999,\n 44.402391829093915\n ],\n [\n -116.76269531249999,\n 39.095962936305476\n ],\n [\n -116.89453125,\n 34.19817309627726\n ],\n [\n -115.927734375,\n 33.7243396617476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brahney, J.","contributorId":247745,"corporation":false,"usgs":false,"family":"Brahney","given":"J.","affiliations":[],"preferred":false,"id":808220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294 wetherbe@usgs.gov","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":1044,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"wetherbe@usgs.gov","middleInitial":"A.","affiliations":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"preferred":true,"id":808221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sexstone, Graham A. 0000-0001-8913-0546 sexstone@usgs.gov","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":5159,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham","email":"sexstone@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Youngbull, C.","contributorId":247746,"corporation":false,"usgs":false,"family":"Youngbull","given":"C.","email":"","affiliations":[],"preferred":false,"id":808223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Strong, P.","contributorId":102292,"corporation":false,"usgs":true,"family":"Strong","given":"P.","email":"","affiliations":[],"preferred":false,"id":808224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Heindel, Ruth C. 0000-0001-6292-2076","orcid":"https://orcid.org/0000-0001-6292-2076","contributorId":225133,"corporation":false,"usgs":false,"family":"Heindel","given":"Ruth","email":"","middleInitial":"C.","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":808225,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208835,"text":"70208835 - 2020 - Integrating ecosystem resilience and resistance into decision support tools for multi-scale population management of a sagebrush indicator species","interactions":[],"lastModifiedDate":"2020-03-03T08:07:45","indexId":"70208835","displayToPublicDate":"2020-01-14T08:05:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Integrating ecosystem resilience and resistance into decision support tools for multi-scale population management of a sagebrush indicator species","docAbstract":"Imperiled sagebrush (Artemisia spp.) ecosystems of western North America are experiencing unprecedented conservation planning efforts. Advances in decision-support tools operationalize concepts of ecosystem resilience by quantitatively linking spatially explicit variation in soil and plant processes to outcomes of biotic and abiotic disturbances. However, failure to consider higher trophic-level fauna of conservation concern in these tools can hinder efforts to operationalize resilience owing to spatiotemporal lags between slower reorganization of plant and soil processes following disturbance, and faster behavioral and demographic responses of fauna to disturbance. Here, we provide multi-scale examples of decision-support tools for management and restoration actions that evaluate general resilience mapped to variation in soil moisture and temperature regimes through new lenses of habitat selection and population performance responses for an at-risk obligate species to sagebrush ecosystems, the greater sage-grouse (Centrocercus urophasianus). We then briefly describe general pathways going forward for more explicit integration of sage-grouse fitness with factors influencing variation in sagebrush resilience to disturbance and resistance to invasive species (e.g., annual grasses). The intended product of these efforts is a more targeted operational definition of resilience for managers by using quantifiable metrics that help limit chances of spatiotemporal mismatches among restoration responses owing to differences in engineering resilience between sagebrush ecosystem processes and sage-grouse population dynamics. Moreover, spatial resilience can be promoted though explicit consideration of sage-grouse and sagebrush predicted responses to active and passive management treatments across space and time. We describe tools that include multi-scale geospatial overlays and simulation analyses of post-disturbance land cover recovery aimed at prioritizing primary threats to sagebrush ecosystems in the Great Basin in the western portion of sage-grouse range (i.e., grass-fire cycles and conifer expansion), but underlying concepts have broader application to a range of ecosystems.","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2019.00493","usgsCitation":"Ricca, M.A., and Coates, P.S., 2020, Integrating ecosystem resilience and resistance into decision support tools for multi-scale population management of a sagebrush indicator species: Frontiers in Ecology and Evolution, v. 7, 493, 22 p., https://doi.org/10.3389/fevo.2019.00493.","productDescription":"493, 22 p.","ipdsId":"IP-111417","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458134,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00493","text":"Publisher Index Page"},{"id":437161,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P960W8MD","text":"USGS data release","linkHelpText":"Additional mapping tools for Great Basin wildfire and conifer management to increase operational resilience: integrating sagebrush ecosystem and sage-grouse response"},{"id":372831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":783567,"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":783566,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209626,"text":"70209626 - 2020 - The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses","interactions":[],"lastModifiedDate":"2020-04-16T12:03:44.002862","indexId":"70209626","displayToPublicDate":"2020-01-14T06:58:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses","docAbstract":"Hydrometeorologic monitoring networks are ubiquitous in contemporary earth-system science. Network stakeholders often inquire about the importance of sites and their locations when discussing funding and monitoring design. Support vector machines (SVMs) can be useful by their assigning each monitoring site as either a support or nonsupport vector. A potentiometric surface was created from synthetic data and 800 random observation locations (sites) as an analog to a groundwater-level network. Using generalized additive models for potentiometric surface prediction, simulations show that a subsample of support vectors from the 800 sites will out perform random samples of sample size equaling the support vector count. Support vector percentages from simulation quantify the recurrence that SVMs assign each site as a support vector, and these percentages in turn measure site importance. An example application of support vector percentages identifies important monitoring sites needed to regionalize the 0.1 annual exceedance probability peak streamflow. The results indicate that 152 of 283 streamgages with support vector percentages equalling 100 percent have not operated since about 2000 and generally have much smaller drainage areas than the greater streamgage network in Texas. The drainage area disparity is an indication of historical imbalance in peak streamflow data acquisition from various stream sizes in Texas.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2019.124522","collaboration":"","usgsCitation":"Asquith, W.H., 2020, The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses: Journal of Hydrology, v. 583, 124522, 10 p., https://doi.org/10.1016/j.jhydrol.2019.124522.","productDescription":"124522, 10 p.","ipdsId":"IP-104552","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":374045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70208149,"text":"70208149 - 2020 - Soil surface elevation dynamics in a mangrove-to-marsh ecotone characterized by vegetation shifts","interactions":[],"lastModifiedDate":"2020-02-25T08:17:01","indexId":"70208149","displayToPublicDate":"2020-01-13T17:56:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Soil surface elevation dynamics in a mangrove-to-marsh ecotone characterized by vegetation shifts","docAbstract":"Mangrove forest encroachment into coastal marsh habitats has been described in subtropical regions worldwide in recent decades. To better understand how soil processes may influence vegetation change, we studied soil surface elevation change, accretion rates, and soil subsurface change across a coastal salinity gradient in Florida, USA, an area with documented mangrove encroachment into saline marshes. Our aim was to identify if variations in the soil variables studied exist and to document any associated vegetation shifts. We used surface elevation tables and marker horizons to document the soil variables over 5 years in a mangrove-to-marsh transition zone or ecotone. Study sites were located in three marsh types (brackish, salt, and transition) and in riverine mangrove forests. Mangrove forest sites had significantly higher accretion rates than marsh sites and were the only locations where elevation gain occurred. Significant loss in surface elevation occurred at transition and salt marsh sites. Transition marshes, which had a significantly higher rate of shallow subsidence compared to other wetland types, appear to be most vulnerable to submergence or to a shift to mangrove forest. 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]\n}","volume":"847","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":780716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"From, Andrew 0000-0002-6543-2627 froma@usgs.gov","orcid":"https://orcid.org/0000-0002-6543-2627","contributorId":169668,"corporation":false,"usgs":true,"family":"From","given":"Andrew","email":"froma@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research 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0000-0003-2453-9900 cormiern@usgs.gov","orcid":"https://orcid.org/0000-0003-2453-9900","contributorId":4262,"corporation":false,"usgs":true,"family":"Cormier","given":"Nicole","email":"cormiern@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":780720,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allain, Larry K. 0000-0002-7717-9761 allainl@usgs.gov","orcid":"https://orcid.org/0000-0002-7717-9761","contributorId":2414,"corporation":false,"usgs":true,"family":"Allain","given":"Larry","email":"allainl@usgs.gov","middleInitial":"K.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":780721,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Savarese, 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,{"id":70211824,"text":"70211824 - 2020 - Pulsed flow-through auto-feeding beaker systems for the laboratory culture of juvenile freshwater mussels","interactions":[],"lastModifiedDate":"2020-08-10T12:37:20.374625","indexId":"70211824","displayToPublicDate":"2020-01-13T17:06:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":853,"text":"Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Pulsed flow-through auto-feeding beaker systems for the laboratory culture of juvenile freshwater mussels","docAbstract":"Newly metamorphosed freshwater mussels are small and delicate, so that captive laboratory culture presents challenges for handling; for maintenance of suitable microhabitat, water quality, and food; and for avoidance of competitors and predators. To address these challenges, a new pulsed flow-through auto-feeding beaker system was developed for culturing juvenile mussels. In this system, groups of mussels were maintained in 300- to 1000-mL beakers with a thin layer of sand substrate. The water in the beakers was static except for pulses that were delivered every 1 or 2 h and that displaced about half of the water in each beaker per water cycle. A peristaltic pump delivered food to multiple mixing cells where the water was automatically mixed with food just before the water delivery. In testing this approach, newly metamorphosed mussels of 4 species were cultured in the system for 84 to 357 d. The sand and beakers were replaced weekly. Survival was high (>85% at day 84) for Lampsilis siliquoidea and Villosa iris, but relatively lower for Anodonta californiensis (29% at day 155) and Margaritifera falcata (23% at day 357). Growth rate ranged among the 4 species from 27 to 60 μm/d, with the slowest rate for M. falcata and fastest for A. californiensis. Overall, the new pulsed flow-through auto-feeding beaker system improved survival and growth of juvenile mussels versus other methods previously tested. Additionally, a simplified system for the water and food delivery was developed with a single mixing cell. The use of both systems indicate that they are suitable for laboratory experiments and for captive culture of juvenile mussels.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquaculture.2020.734959","usgsCitation":"Kunz, J.L., Brunson, E., Barnhart, M., Glidewell, E.A., Wang, N., and Ingersoll, C.G., 2020, Pulsed flow-through auto-feeding beaker systems for the laboratory culture of juvenile freshwater mussels: Aquaculture, v. 520, 734959, 8 p., https://doi.org/10.1016/j.aquaculture.2020.734959.","productDescription":"734959, 8 p.","ipdsId":"IP-113839","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437163,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P989BFTB","text":"USGS data release","linkHelpText":"Survival and growth of juvenile freshwater mussels in a flow-through auto-feeding system"},{"id":377215,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"520","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brunson, Eric 0000-0001-6624-0902","orcid":"https://orcid.org/0000-0001-6624-0902","contributorId":201761,"corporation":false,"usgs":true,"family":"Brunson","given":"Eric","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795251,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnhart, M. Christopher","contributorId":189301,"corporation":false,"usgs":false,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":795250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glidewell, Elizabeth A.","contributorId":189302,"corporation":false,"usgs":false,"family":"Glidewell","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":795252,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795249,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":795253,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208025,"text":"70208025 - 2020 - A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels","interactions":[],"lastModifiedDate":"2020-10-28T15:09:08.954274","indexId":"70208025","displayToPublicDate":"2020-01-13T16:41:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5840,"text":"Environmental DNA","active":true,"publicationSubtype":{"id":10}},"title":"A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels","docAbstract":"Resource managers may be hesitant to make decisions based on environmental (e)DNA results alone since eDNA is an indirect method of species detection. One way to reduce the uncertainty of eDNA is to identify laboratory‐based protocols that ensure repeatable and reproducible results. We conducted a double‐blind round‐robin analysis of probe‐based assays for DNA of dreissenid (Dreissena spp.) mussels, which are prolific aquatic invaders that can cause significant economic and ecological impacts. DNA extract from water samples spiked with known amounts of dreissenid DNA and from water samples collected from waters with and without dreissenids were analyzed by four independent research laboratories. We used results to calculate detection repeatability within laboratories and assays, detection reproducibility among laboratories and assays, and estimated dreissenid DNA copy number precision and accuracy. Laboratory and assay repeatability and reproducibility of detection results were high, 91% and 92%, respectively. The estimated copy numbers were neither precise nor accurate for samples spiked with <773 gene copies. These results suggest that eDNA surveillance of dreissenid mussels, using the protocols evaluated herein, can generate reliable detection data for decision‐making. However, managers should be cautious about using the quantitative information often associated with eDNA detections, especially when DNA is at lower abundance. Our results provide strong support that eDNA has the potential to provide repeatable and reproducible evidence under varying laboratory conditions and for different sample water chemistries. This is reassuring since the demand for eDNA surveillance is widespread and number of laboratories that process eDNA samples is growing steadily.
","language":"English","publisher":"Wiley","doi":"10.1002/edn3.68","usgsCitation":"Sepulveda, A.J., Hutchins, P.R., Jackson, C., Ostberg, C.O., Laramie, M., Amberg, J., Counihan, T., Hoegh, A.B., and Pilliod, D.S., 2020, A round-robin evaluation of the repeatability and reproducibility of environmental DNA assays for dreissenid mussels: Environmental DNA, v. 2, no. 4, p. 446-459, https://doi.org/10.1002/edn3.68.","productDescription":"14 p.","startPage":"446","endPage":"459","ipdsId":"IP-111602","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":458141,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/edn3.68","text":"Publisher Index Page"},{"id":437164,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NMZZNP","text":"USGS data release","linkHelpText":"PCR results from dreissenid mussel round robin assay analyses, 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,{"id":70228284,"text":"70228284 - 2020 - Walleye growth declines following zebra mussel and Bythotrephes invasion","interactions":[],"lastModifiedDate":"2022-02-08T21:52:56.045081","indexId":"70228284","displayToPublicDate":"2020-01-13T15:38:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Walleye growth declines following zebra mussel and Bythotrephes invasion","title":"Walleye growth declines following zebra mussel and Bythotrephes invasion","docAbstract":"Invasive species represent a threat to aquatic ecosystems globally; however, impacts can be heterogenous across systems. Documented impacts of invasive zebra mussels (Dreissena polymorpha) and spiny water fleas (Bythotrephes cederströmii; hereafter Bythotrephes) on native fishes are variable and context dependent across locations and time periods. Here, we use a hierarchical Bayesian analysis of a 35-year dataset on two fish species from 9 lakes to demonstrate that early life growth of ecologically important fishes are influenced by these aquatic invasive species. Walleye (Sander vitreus) in their first year of life grew more slowly in the presence of either invader after correcting for temperature (measured by degree days), and were on average 12 or 14% smaller at the end of their first summer following invasion by Bythotrephes or zebra mussels, respectively. Yellow perch (Perca flavescens) growth was less affected by invasion. Yellow perch on average grew more slowly in their first year of life following invasion by zebra mussels, although this effect was not statistically distinguishable from zero. Early life growth of both walleye and yellow perch was less tightly coupled to degree days in invaded systems, as demonstrated by increased variance surrounding the degree day-length relationship. Smaller first-year size is related to walleye survival and recruitment to later life stages and has important implications for lake food webs and fisheries management. Future research quantifying effects of zebra mussels and Bythotrephes on other population-level processes and across a wider gradient of lake types is needed to understand the mechanisms driving observed changes in walleye growth.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-020-02198-5","usgsCitation":"Ahrenstorff, T.D., Hansen, G., Bethke, B.J., Dumke, J., Hirsch, J., Kovalenko, K., LeDuc, J., Maki, R.P., Rantala, H., and Wagner, T., 2020, Walleye growth declines following zebra mussel and Bythotrephes invasion: Biological Invasions, v. 22, p. 1481-1495, https://doi.org/10.1007/s10530-020-02198-5.","productDescription":"15 p.","startPage":"1481","endPage":"1495","ipdsId":"IP-110055","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":458143,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-020-02198-5","text":"Publisher Index Page"},{"id":395656,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.91015624999999,\n 45.398449976304086\n ],\n [\n -89.736328125,\n 45.398449976304086\n ],\n [\n -89.736328125,\n 49.03786794532644\n ],\n [\n -97.91015624999999,\n 49.03786794532644\n ],\n [\n -97.91015624999999,\n 45.398449976304086\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","noUsgsAuthors":false,"publicationDate":"2020-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahrenstorff, Tyler D.","contributorId":275045,"corporation":false,"usgs":false,"family":"Ahrenstorff","given":"Tyler","email":"","middleInitial":"D.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Gretchen J. A.","contributorId":275043,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen J. A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":833603,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bethke, Bethany J.","contributorId":275047,"corporation":false,"usgs":false,"family":"Bethke","given":"Bethany","email":"","middleInitial":"J.","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dumke, Josh","contributorId":275049,"corporation":false,"usgs":false,"family":"Dumke","given":"Josh","email":"","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":833606,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hirsch, Jodie","contributorId":275051,"corporation":false,"usgs":false,"family":"Hirsch","given":"Jodie","email":"","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833607,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kovalenko, Katya E.","contributorId":275052,"corporation":false,"usgs":false,"family":"Kovalenko","given":"Katya E.","affiliations":[{"id":18006,"text":"University of Minnesota Duluth","active":true,"usgs":false}],"preferred":false,"id":833608,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeDuc, Jaime F.","contributorId":275056,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime F.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":833609,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Maki, Ryan P","contributorId":275061,"corporation":false,"usgs":false,"family":"Maki","given":"Ryan","email":"","middleInitial":"P","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":833610,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rantala, Heidi","contributorId":275065,"corporation":false,"usgs":false,"family":"Rantala","given":"Heidi","affiliations":[{"id":34923,"text":"Minnesota DNR","active":true,"usgs":false}],"preferred":false,"id":833611,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833602,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70211201,"text":"70211201 - 2020 - A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States","interactions":[],"lastModifiedDate":"2020-08-06T19:35:20.478446","indexId":"70211201","displayToPublicDate":"2020-01-13T12:07:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States","docAbstract":"Nearly 60,000 utility-scale wind turbines are installed in the United States as of July, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-020-0353-6","usgsCitation":"Rand, J., Kramer, L., Garrity, C.P., Hoen, B., Diffendorfer, J., Hunt, H., and Spears, M., 2020, A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States: Scientific Data, v. 7, 15, 12 p., https://doi.org/10.1038/s41597-020-0353-6.","productDescription":"15, 12 p.","ipdsId":"IP-112062","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":458145,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-020-0353-6","text":"Publisher Index Page"},{"id":437165,"rank":0,"type":{"id":30,"text":"Data 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,{"id":70215186,"text":"70215186 - 2020 - Longitudinal distribution of uncommon fishes in a species-rich basin","interactions":[],"lastModifiedDate":"2020-10-09T14:12:44.050435","indexId":"70215186","displayToPublicDate":"2020-01-13T09:09:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Longitudinal distribution of uncommon fishes in a species-rich basin","docAbstract":"- The spatial organization of fishes in a river system was investigated to evaluate the longitudinal distribution of uncommon species. It was anticipated that overall richness of the fish community would increase in a downstream direction together with habitat extent, but that more uncommon species would occur upstream owing to greater heterogeneity among sites.
- Fish were collected between 1995 and 2014 at 85 sites distributed throughout the Duck River Basin, Tennessee, USA. A site usually consisted of four habitat types: riffles, runs, pools and shoreline. Each habitat type was sampled with a multipass electrofishing protocol.
- In all, 136 native fish species were collected. Of these, 71% were classified as uncommon but represented only 16% of the total count of fish collected. As expected, overall species richness increased downstream, but contrary to expectation, uncommon species did too. Some uncommon species were restricted exclusively to tributaries and headwaters, some to tributaries and mainstem, many to mainstem only, but the largest fraction of uncommon species occurred throughout the basin, but even this last group increased in richness downstream.
- Conservation often focuses on uncommon species. This study suggests that a greater number of uncommon species can be conserved with an emphasis on large downstream reaches, which not only include more aquatic habitat to support larger concentrations of fish, but also shelter the uncomm
","language":"English","publisher":"Wiley","doi":"10.1002/aqc.3262","usgsCitation":"Miranda, L.E., and Killgore, K., 2020, Longitudinal distribution of uncommon fishes in a species-rich basin: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 30, no. 3, p. 577-585, https://doi.org/10.1002/aqc.3262.","productDescription":"9 p.","startPage":"577","endPage":"585","ipdsId":"IP-106148","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aqc.3262","text":"Publisher Index Page"},{"id":379275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","otherGeospatial":"Duck River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.61547851562499,\n 34.92197103616377\n ],\n [\n -86.87988281249999,\n 34.92197103616377\n ],\n [\n -86.87988281249999,\n 36.5184659896759\n ],\n [\n -89.61547851562499,\n 36.5184659896759\n ],\n [\n -89.61547851562499,\n 34.92197103616377\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":801094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Killgore, K.J.","contributorId":200191,"corporation":false,"usgs":false,"family":"Killgore","given":"K.J.","email":"","affiliations":[{"id":33009,"text":"Engineer Research and Development Center, U. S. Army Corps of Engineers, Vicksburg, Mississippi","active":true,"usgs":false}],"preferred":false,"id":801095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70225829,"text":"70225829 - 2020 - Using the Lomb-Scargle method for wave statistics from gappy time series","interactions":[],"lastModifiedDate":"2021-11-10T14:50:24.002282","indexId":"70225829","displayToPublicDate":"2020-01-13T08:43:38","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using the Lomb-Scargle method for wave statistics from gappy time series","docAbstract":"Sandwich Town Neck Beach in Sandwich, MA, has experienced substantial erosion and has been the subject of efforts by the town and private landowners to limit the sand loss. Erosion has been particularly dramatic in the past five years with the loss of dwellings. Sandwich's nourishment efforts presented a unique opportunity for scientists at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center to monitor beach morphology and to test new technologies and techniques such as geo-referenced drone imaging. Two bottom lander deployments were performed in Cape Cod Bay at a location that was key to model the fate of waves at Sandwich Town Neck Beach and to support the study of beach morphological evolution. The study period was after the town nourished the beach and during a time when several intense winter storms reshaped the beach and removed much of the nourished sand. A TRDI Workhorse Sentinel V ADCP was used for both deployments. For wave bursts, the instruments collected 2048 samples at 2 Hz every hour. The first deployment during the winter of 2016 returned good quality data. The second deployment during the following winter had gaps throughout the time series from a wiring problem in the external battery pack. The timing of the gaps was random, the duration approximately 100 s. While most of the bursts started at the top of each hour, many had 1-3 gaps within. Time series data with random gaps are problematic for computing spectral density, and thus, wave statistics. This kind of situation is familiar in other scientific disciplines such as astrophysics [1], where techniques exist to find stationary signals in sparse data. One of these methods is the Lomb-Scargle technique for computing periodograms. The most useful feature of the Lomb-Scargle (LS) method is that it allows the spectral analysis of incomplete records, without having to manipulate the record to extrapolate from or replace missing data. We compared the effectiveness of LS against common methods of averaging Fourier transforms such as a simple un-windowed Fast Fourier transform (FFT), Welch's method, and TRDI's Wavesmon software; methods that are commonly used in oceanography for non-gappy data. Synthetic data series that have been artificially modified to introduce gaps were used to evaluate the performance of each method. The LS approach was able to recover spectral density even with several 100-s gaps present. The method was applied here to the gappy and non-gappy data from both Sandwich deployments, and wave statistics were obtained and compared to the wave-buoy data. LS was used to process data that contains gaps that was rejected by Wavesmon, which was approximately 39% of the dataset. Significant wave height and peak period from LS compared well with buoy data. Mean period computed on gappy data using LS produced values biased low, compared with other methods when gaps were filled with the mean value. The LS technique has potential to uncover low-frequency signals such as infragravity waves from gappy records where the non-gappy segments are not long enough to resolve them. It has potential to unlock new information from older data sets.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2019 IEEE/OES twelfth current, waves and turbulence measurement (CWTM)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"IEEE Oceanic Engineering Society - Current, Waves, Turbulence and Measurement Applications Workshop","conferenceDate":"Mar 10-13, 2019","language":"English","publisher":"IEEE","doi":"10.1109/CWTM43797.2019.8955285","usgsCitation":"Martini, M.A., Aretxabaleta, A., and Sherwood, C.R., 2020, Using the Lomb-Scargle method for wave statistics from gappy time series, in 2019 IEEE/OES twelfth current, waves and turbulence measurement (CWTM), Mar 10-13, 2019, 9 p., https://doi.org/10.1109/CWTM43797.2019.8955285.","productDescription":"9 p.","ipdsId":"IP-105269","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":391573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Sandwich","otherGeospatial":"Sandwich Town Neck Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.48888206481934,\n 41.762413206292656\n ],\n [\n -70.47154426574707,\n 41.762413206292656\n ],\n [\n -70.47154426574707,\n 41.77297600540535\n ],\n [\n -70.48888206481934,\n 41.77297600540535\n ],\n [\n -70.48888206481934,\n 41.762413206292656\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Martini, Marinna A. 0000-0002-7757-5158 mmartini@usgs.gov","orcid":"https://orcid.org/0000-0002-7757-5158","contributorId":2456,"corporation":false,"usgs":true,"family":"Martini","given":"Marinna","email":"mmartini@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826576,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208001,"text":"70208001 - 2020 - Mercury and selenium concentrations in fishes of the Upper Colorado River Basin, southwestern United States: A retrospective assessment","interactions":[],"lastModifiedDate":"2020-01-23T06:22:49","indexId":"70208001","displayToPublicDate":"2020-01-13T06:18:45","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Mercury and selenium concentrations in fishes of the Upper Colorado River Basin, southwestern United States: A retrospective assessment","docAbstract":"Mercury (Hg) and selenium (Se) are contaminants of concern for fish in the Upper Colorado River Basin (UCRB). We explored Hg and Se in fish tissues (2,324 individuals) collected over 50 years (1962–2011) from the UCRB. Samples include native and non-native fish collected from lotic waterbodies spanning 7 major tributaries to the Colorado River. There was little variation of total mercury (THg) in fish assemblages basin-wide and only 13% (272/1959) of individual fish samples exceeded the fish health benchmark (0.27 μg THg/g ww). Most THg exceedances were observed in the White-Yampa tributary whereas the San Juan had the lowest mean THg concentration. Risks associated with THg are species specific with exceedances dominated by Colorado Pikeminnow (mean = 0.38 and standard error ± 0.08 μg THg/g ww) and Roundtail Chub (0.24 ± 0.06 μg THg/g ww). For Se, 48% (827/1720) of all individuals exceeded the fish health benchmark (5.1 μg Se/g dw). The Gunnison river had the most individual exceedances of the Se benchmark (74%) whereas the Dirty Devil had the fewest. We identified that species of management concern accumulate THg and Se to levels above risk thresholds and that fishes of the White-Yampa (THg) and Gunnison (Se) rivers are at the greatest risk in the UCRB.","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0226824","usgsCitation":"Day, N.K., Schmidt, T.S., Roberts, J., Osmundson, B., Willacker, J., and Eagles-Smith, C., 2020, Mercury and selenium concentrations in fishes of the Upper Colorado River Basin, southwestern United States: A retrospective assessment: PLoS ONE, v. 15, no. 1, e0226824, https://doi.org/10.1371/journal.pone.0226824.","productDescription":"e0226824","ipdsId":"IP-100771","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458151,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0226824","text":"Publisher Index Page"},{"id":437167,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71N802D","text":"USGS data release","linkHelpText":"Fish tissue mercury and selenium concentrations in Upper Colorado River Basin: 1962-2011"},{"id":371485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.0703125,\n 36.56260003738545\n ],\n [\n -114.521484375,\n 34.77771580360469\n ],\n [\n -107.05078125,\n 34.59704151614417\n ],\n [\n -105.2490234375,\n 36.24427318493909\n ],\n [\n -104.4140625,\n 39.095962936305476\n ],\n [\n -105.380859375,\n 41.64007838467894\n ],\n [\n -106.962890625,\n 42.16340342422401\n ],\n [\n -112.8955078125,\n 42.74701217318067\n ],\n [\n -116.27929687499999,\n 42.61779143282346\n ],\n [\n -118.5205078125,\n 40.81380923056958\n ],\n [\n -118.3447265625,\n 38.37611542403604\n ],\n [\n -117.0703125,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Day, Natalie K. 0000-0002-8768-5705","orcid":"https://orcid.org/0000-0002-8768-5705","contributorId":207302,"corporation":false,"usgs":true,"family":"Day","given":"Natalie","middleInitial":"K.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":780096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Travis S. 0000-0003-1400-0637 tschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-1400-0637","contributorId":221742,"corporation":false,"usgs":true,"family":"Schmidt","given":"Travis","email":"tschmidt@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":780097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":780098,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Osmundson, Barbara C.","contributorId":221743,"corporation":false,"usgs":false,"family":"Osmundson","given":"Barbara C.","affiliations":[{"id":40411,"text":"(Emeritus) U.S. Fish and Wildlife Service, Grand Junction, CO","active":true,"usgs":false}],"preferred":false,"id":780099,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Willacker, James 0000-0002-6286-5224","orcid":"https://orcid.org/0000-0002-6286-5224","contributorId":221744,"corporation":false,"usgs":true,"family":"Willacker","given":"James","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":780100,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":780101,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208449,"text":"70208449 - 2020 - Effects of montane watershed development on vulnerability of domestic groundwater supply during drought","interactions":[],"lastModifiedDate":"2020-02-10T18:22:15","indexId":"70208449","displayToPublicDate":"2020-01-11T18:13:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of montane watershed development on vulnerability of domestic groundwater supply during drought","docAbstract":"Climate change is expected to reduce recharge to montane aquifers in the western United States, but it is unclear how this will impact groundwater resources in watersheds where intensive surface-water development has disrupted the natural hydrologic regime. To better understand sources of recharge and associated vulnerabilities of groundwater supply in this setting, we made a detailed geochemical survey of domestic wells finished in fractured bedrock throughout the Yuba and Bear River watersheds (Sierra Nevada foothills, northern California)during historic drought (2015–2016). Stable isotopes of water and noble gas recharge temperatures closely tracked atmospheric lapse rates across a broad elevation gradient (100–2000 m), indicating groundwater inputs are dominated by local precipitation that rapidly recharges fractured bedrock during the winter wet-season. However, nearly one-quarter of wells had water isotopes that were fractionated by evaporation and warm recharge temperatures, indicative of mixing with dry-season recharge by surface water. Monte Carlo mixing models suggest evaporation-impacted groundwater samples are mixtures of local rain with an average of 28% ± 13% from diverted surface water that can recharge bedrock aquifers during the dry-season by either irrigation return flow or seepage from extensive distribution infrastructure. Wells that received recharge subsidies from diverted surface water had elevated levels of nitrate and coliform bacteria compared to those replenished exclusively by local precipitation,\nwhich are more vulnerable to supply shortage during drought. It is important to consider the impacts of increased surface-water development on the quantity and quality of groundwater recharge in rapidly developing montane watersheds.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2020.124567","usgsCitation":"Levy, Z., Fram, M.S., Faulkner, K., Alpers, C.N., Soltero, E.M., and Taylor, K.A., 2020, Effects of montane watershed development on vulnerability of domestic groundwater supply during drought: Journal of Hydrology, v. 583, 124567, 18 p., https://doi.org/10.1016/j.jhydrol.2020.124567.","productDescription":"124567, 18 p.","ipdsId":"IP-107517","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":458154,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2020.124567","text":"Publisher Index Page"},{"id":437168,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YETK9P","text":"USGS data release","linkHelpText":"Dissolved Noble Gas Concentrations and Modeled Recharge Temperatures for Groundwater from Northern Sierra Nevada Foothills Shallow Aquifer Assessment Study Units, 2015-2017: Results from the California GAMA Priority Basin Project"},{"id":372204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bear River watershed, Yuba River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.2451171875,\n 38.86323626888358\n ],\n [\n -120.13275146484374,\n 38.86323626888358\n ],\n [\n -120.13275146484374,\n 39.85282948915942\n ],\n [\n -121.2451171875,\n 39.85282948915942\n ],\n [\n -121.2451171875,\n 38.86323626888358\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"583","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Levy, Zeno F. 0000-0003-4580-2309","orcid":"https://orcid.org/0000-0003-4580-2309","contributorId":222340,"corporation":false,"usgs":true,"family":"Levy","given":"Zeno","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Kirsten 0000-0003-1628-2877","orcid":"https://orcid.org/0000-0003-1628-2877","contributorId":222341,"corporation":false,"usgs":true,"family":"Faulkner","given":"Kirsten","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781922,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781923,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soltero, Evelyn M","contributorId":222342,"corporation":false,"usgs":false,"family":"Soltero","given":"Evelyn","email":"","middleInitial":"M","affiliations":[{"id":40530,"text":"All About Wells","active":true,"usgs":false}],"preferred":false,"id":781924,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taylor, Kimberly A. 0000-0002-0095-6403 ktaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-0095-6403","contributorId":1601,"corporation":false,"usgs":true,"family":"Taylor","given":"Kimberly","email":"ktaylor@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781925,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70260133,"text":"70260133 - 2020 - Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2024-10-29T16:44:36.747968","indexId":"70260133","displayToPublicDate":"2020-01-11T11:38:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska","docAbstract":"Ejection of ballistic blocks was a characteristic feature of the 2016–2017 Bogoslof eruption. High-resolution satellite images acquired throughout the duration of the 9-month long eruptive period permitted the recognition and mapping of ballistic blocks on the surface of Bogoslof Island. Many of the satellite images recorded the accumulation of ballistic material over several individual eruptive events, but a few images recorded the effects of a single event. The nonuniform spatial distribution of blocks suggests that some of the eruption columns were inclined. Ballistic trajectories were estimated using the Eject! model and indicate that accumulation of blocks on Bogoslof Island required launch angles of 45–80° and initial velocities of 50–100 ms−1 to reproduce observed travel distances. The amount of ballistic fallout observed in satellite data indicates that there must have been a shallow submarine source of rock within the conduit/upper edifice system. Dense, accidental cryptodome trachyandesite, and juvenile basalt to trachybasalt scoria make up the bulk of the surface ejecta. Abundant accidental fragments and inclined eruption columns point to periodic vent-wall collapse and jetting around edges of temporarily blocked vents as the likely cause of ballistic ejection.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-019-1351-4","usgsCitation":"Waythomas, C.F., and Mastin, L.G., 2020, Mechanisms for ballistic block ejection during the 2016–2017 shallow submarine eruption of Bogoslof volcano, Alaska: Bulletin of Volcanology, v. 82, 13, 20 p., https://doi.org/10.1007/s00445-019-1351-4.","productDescription":"13, 20 p.","ipdsId":"IP-113632","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.04572245314344,\n 53.93741980478987\n ],\n [\n -168.04572245314344,\n 53.92361535465113\n ],\n [\n -168.0255939265047,\n 53.92361535465113\n ],\n [\n -168.0255939265047,\n 53.93741980478987\n ],\n [\n -168.04572245314344,\n 53.93741980478987\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Waythomas, Christopher F. 0000-0002-3898-272X cwaythomas@usgs.gov","orcid":"https://orcid.org/0000-0002-3898-272X","contributorId":640,"corporation":false,"usgs":true,"family":"Waythomas","given":"Christopher","email":"cwaythomas@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917131,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237952,"text":"70237952 - 2020 - Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers","interactions":[],"lastModifiedDate":"2022-11-01T14:06:22.857819","indexId":"70237952","displayToPublicDate":"2020-01-11T08:57:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers","docAbstract":"Hydraulic head and groundwater age data are effective in building understanding of groundwater systems. Yet their joint role in detecting and characterising low-permeability geological structures, i.e. hydrogeologic barriers such as faults and dykes, has not been widely studied. Here, numerical flow and transport models, using MODFLOW-NWT and MT3D-USGS, were developed with different hydrogeologic barrier configurations in a hypothetical aquifer. Computed hydraulic head and groundwater age distributions were compared to those without a barrier. The conjoint use of these datasets helps in detecting vertically-oriented barriers. Two forms of recharge were compared: (1) applied across the entire aquifer surface (uniform), and (2) applied to the upstream part of the aquifer (upgradient). The hydraulic head distribution is significantly impacted by a barrier that penetrates the aquifer’s full vertical thickness. This barrier also perturbs the groundwater age distribution when upgradient recharge prevails; however, with uniform recharge, groundwater age is not successful in detecting the barrier. When a barrier is buried, such as by younger sediment, hydraulic head data also do not clearly identify the barrier. Groundwater age data could, on the other hand, prove to be useful if sampled at depth-specific intervals. These results are important for the detection and characterisation of hydrogeologic barriers, which may play a significant role in the compartmentalisation of groundwater flow, spring dynamics, and drawdown and recovery associated with groundwater extraction.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-02095-9","usgsCitation":"Marshall, S.K., Cook, P., Konikow, L.F., Simmons, C., and Dogramaci, S., 2020, Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers: Hydrogeology Journal, v. 28, p. 1003-1019, https://doi.org/10.1007/s10040-019-02095-9.","productDescription":"17 p.","startPage":"1003","endPage":"1019","ipdsId":"IP-109151","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":408987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Sarah K.","contributorId":298728,"corporation":false,"usgs":false,"family":"Marshall","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":856337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Peter G.","contributorId":298729,"corporation":false,"usgs":false,"family":"Cook","given":"Peter G.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":856338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":856339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simmons, Craig T.","contributorId":298730,"corporation":false,"usgs":false,"family":"Simmons","given":"Craig T.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":856340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dogramaci, Shawan","contributorId":298731,"corporation":false,"usgs":false,"family":"Dogramaci","given":"Shawan","email":"","affiliations":[{"id":64684,"text":"Rio Tinto Iron Ore Co.","active":true,"usgs":false}],"preferred":false,"id":856341,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209325,"text":"70209325 - 2020 - Heterogeneity in migration strategies of the whooping crane","interactions":[],"lastModifiedDate":"2020-04-01T08:27:50","indexId":"70209325","displayToPublicDate":"2020-01-11T08:21:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneity in migration strategies of the whooping crane","docAbstract":"Migratory birds use numerous strategies to successfully complete twice-annual movements between breeding and wintering sites. Context for conservation and management can be provided by characterizing these strategies. Variations in strategy among and within individuals support population persistence in response to changes in land use and climate. We used location data from 58 marked Whooping Cranes (Grus americana) from 2010–2016 to characterize migration strategies in the U.S. Great Plains and Canadian Prairies and southern boreal region, and to explore sources of heterogeneity in their migration strategy, including space use, timing, and performance. Whooping Cranes completed approximately 3,900-km migrations that averaged 29 days during spring and 45 days during autumn, while making 11–12 nighttime stops. At the scale of our analysis, individual Whooping Cranes showed little consistency in stopover sites used among migration seasons (i.e., low site fidelity). In contrast, individuals expressed a measure of consistency in timing, especially migration initiation date. Whooping Cranes migrated at different times based on age and reproductive status, where adults with young initiated autumn migration after other birds, and adults with and without young initiated spring migration before subadult birds. Time spent at stopover sites was associated with migration bout length and time spent at previous stopover sites, suggesting Whooping Cranes acquired energy resources at some stopover sites that they used to fuel migration. Whooping Cranes were faithful to a defined migration corridor but showed less fidelity in their selection of nighttime stopover sites; hence, spatial targeting of conservation actions may be better informed by associations with landscape and habitat features rather than documented past use at specific locations. The preservation of variation in migration strategies existing within this species that experienced a severe population bottleneck suggests that Whooping Cranes have maintained a capacity to adjust strategies when confronted with future changes in land use and climate.","language":"English","publisher":"American Ornithological Society","doi":"10.1093/condor/duz056","usgsCitation":"Pearse, A.T., Metzger, K.L., Brandt, D.A., Bidwell, M.T., Harner, M.J., Baasch, D.M., and Harrell, W.C., 2020, Heterogeneity in migration strategies of the whooping crane: The Condor, v. 122, no. 1, duz056, https://doi.org/10.1093/condor/duz056.","productDescription":"duz056","ipdsId":"IP-099078","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":437169,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NRAY6F","text":"USGS data release","linkHelpText":"Characterization of whooping crane migrations and stopover sites used in the Central Flyway, 2010-2016"},{"id":373699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Great Plains, Canadian Prairies ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.09765625,\n 29.38217507514529\n ],\n [\n -95.97656249999999,\n 33.797408767572485\n ],\n [\n -97.119140625,\n 39.027718840211605\n ],\n [\n -98.349609375,\n 45.1510532655634\n ],\n [\n -100.107421875,\n 48.922499263758255\n ],\n [\n -102.83203125,\n 51.781435604431195\n ],\n [\n -105.29296874999999,\n 53.27835301753182\n ],\n [\n -108.369140625,\n 54.00776876193478\n ],\n [\n -109.51171875,\n 53.225768435790194\n ],\n [\n -108.720703125,\n 51.67255514839674\n ],\n [\n -104.32617187499999,\n 49.61070993807422\n ],\n [\n -104.150390625,\n 44.653024159812\n ],\n [\n -102.3046875,\n 38.54816542304656\n ],\n [\n -100.81054687499999,\n 30.524413269923986\n ],\n [\n -97.998046875,\n 27.916766641249065\n ],\n [\n -95.09765625,\n 29.38217507514529\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"122","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":786077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Metzger, Kristine L.","contributorId":147144,"corporation":false,"usgs":false,"family":"Metzger","given":"Kristine","email":"","middleInitial":"L.","affiliations":[{"id":16794,"text":"USFWS, Div of Biol Serv, Albuquerque, NM","active":true,"usgs":false}],"preferred":false,"id":786080,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":786078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":202007,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36318,"text":"CWS","active":true,"usgs":false}],"preferred":false,"id":786079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":786082,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":786083,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208875,"text":"70208875 - 2020 - Demography of snowshoe hare population cycles","interactions":[],"lastModifiedDate":"2020-03-04T16:16:48","indexId":"70208875","displayToPublicDate":"2020-01-10T16:01:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Demography of snowshoe hare population cycles","docAbstract":"Cyclic fluctuations in abundance exhibited by some mammalian populations in northern habitats (“population cycles”) are key processes in the functioning of many boreal and tundra ecosystems. Understanding population cycles, essentially demographic processes, necessitates discerning the demographic mechanisms that underlie numerical changes. Using mark–recapture data spanning five population cycles (1977–2017), we examined demographic mechanisms underlying the 9–10‐yr cycles exhibited by snowshoe hares (Lepus americanus Erxleben) in southwestern Yukon, Canada. Snowshoe hare populations always decreased during winter and increased during summer; the balance between winter declines and summer increases characterized the four, multiyear cyclic phases: increase, peak, decline, and low. Little or no recruitment occurred during winter, but summer recruitment varied markedly across the four phases with the highest and lowest recruitment observed during the increase and decline phase, respectively. Population crashes during the decline were triggered by a substantial decline in winter survival and by a lack of subsequent summer recruitment. In contrast, initiation of the increase phase was triggered by a twofold increase in summer recruitment abetted secondarily by improvements in subsequent winter survival. We show that differences in peak density across cycles are explained by differences in overall population growth rate, amount of time available for population growth to occur, and starting population density. Demographic mechanisms underlying snowshoe hare population cycles were consistent across cycles in our study site but we do not yet know if similar demographic processes underlie population cycles in other northern snowshoe hare populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ecy.2969","usgsCitation":"Oli, M.K., Krebs, C., Kenney, A.J., Boonstra, R., Boutin, S., and Hines, J.E., 2020, Demography of snowshoe hare population cycles: Ecology, v. 101, no. 3, 02969, 15 p., https://doi.org/10.1002/ecy.2969.","productDescription":"02969, 15 p.","ipdsId":"IP-106392","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":501028,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1807/144262","text":"External Repository"},{"id":372927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","state":"Yukon","otherGeospatial":"Kluane Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140.526123046875,\n 60.267066292456654\n ],\n [\n -136.065673828125,\n 60.267066292456654\n ],\n [\n -136.065673828125,\n 62.3190027860309\n ],\n [\n -140.526123046875,\n 62.3190027860309\n ],\n [\n -140.526123046875,\n 60.267066292456654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"101","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2020-02-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Oli, Madan K. 0000-0001-6944-0061","orcid":"https://orcid.org/0000-0001-6944-0061","contributorId":201302,"corporation":false,"usgs":false,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":783801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krebs, Charles J","contributorId":146456,"corporation":false,"usgs":false,"family":"Krebs","given":"Charles J","affiliations":[{"id":16701,"text":"Dept. of Zoology, University of British Columbia, Vancouver","active":true,"usgs":false}],"preferred":false,"id":783802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kenney, Alice J","contributorId":223008,"corporation":false,"usgs":false,"family":"Kenney","given":"Alice","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":783803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boonstra, Rudy","contributorId":223009,"corporation":false,"usgs":false,"family":"Boonstra","given":"Rudy","affiliations":[],"preferred":false,"id":783804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boutin, Stan","contributorId":223010,"corporation":false,"usgs":false,"family":"Boutin","given":"Stan","email":"","affiliations":[],"preferred":false,"id":783805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":783800,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70208357,"text":"70208357 - 2020 - Phosphorus, nitrogen and dissolved organic carbon fluxes from sediments in freshwater rivermouths entering Green Bay (Lake Michigan; USA)","interactions":[],"lastModifiedDate":"2020-02-05T16:05:31","indexId":"70208357","displayToPublicDate":"2020-01-10T15:56:54","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Phosphorus, nitrogen and dissolved organic carbon fluxes from sediments in freshwater rivermouths entering Green Bay (Lake Michigan; USA)","docAbstract":"Transitional areas between ecosystem types are often active biogeochemically due to resource limitation changes. Lotic-to-lentic transitions in freshwaters appear active biogeochemically, but few studies have directly measured nutrient processing rates to assess whether processing within the rivermouth is important for load estimates or the local communities. We measured oxic fluxes of inorganic nitrogen and phosphorus and dissolved organic carbon (DOC) from sediments in two rivermouths of Green Bay (Lake Michigan, USA). Soluble reactive phosphorus (SRP) flux was positive in most cases (overall mean 1.74 mg SRP m− 2 day− 1), as was ammonium (NH4) flux (40.6 mg NH4 m− 2 day− 1). Partial least square regression (PLSR) indicated a latent variable associated with both sediment [loosely bound phosphorus (P), iron bound P, organic content] and water column properties [temperature, DOC:dissolved inorganic nitrogen (DIN) and DOC:SRP ratios (negatively)] that was moderately associated with variation in SRP flux. PLSR analysis also indicated several sediment characteristics were moderately related to NH4 flux, especially organic content, density (negative), and porosity. Flux of nitrates/nitrites (NOX) and DOC were positively associated with the water column concentrations of NOX and DOC and qualitative estimates of the labile, non-humic types of DOC. In early summer, water column NOX and DOC concentrations were high and labile DOC may have fueled denitrification, resulting in net flux into sediments of both NOX and DOC. By late summer, water column NOX and DOC were very low and both these constituents were fluxing out of sediments into the water column. Based on our estimates for the entire period from April through September, rivermouth sediments were a net source of SRP and DIN, with a DIN:SRP ratio of ~ 44 and a NH4:NOX > 1. We estimated that the sediments in the Fox rivermouth probably contributed a small proportion of the total Fox River load during the growing season 2016 (< 5%), but at times may have contributed as much as 14% of the daily load. Despite the small size of the Fox rivermouth (< 0.5% of the watershed area), these results indicate that at times sediments can contribute substantially to the overall delivery of nitrogen and phosphorus to the nearshore zone.
","language":"English","publisher":"Springer Nature Switzerland AG","doi":"10.1007/s10533-020-00635-0","usgsCitation":"Larson, J.H., James, W.F., Fitzpatrick, F.A., Frost, P.C., Evans, M.A., Reneau, P., and Xenopoulos, M.A., 2020, Phosphorus, nitrogen and dissolved organic carbon fluxes from sediments in freshwater rivermouths entering Green Bay (Lake Michigan; USA): Biogeochemistry, v. 147, p. 179-197, https://doi.org/10.1007/s10533-020-00635-0.","productDescription":"19 p.","startPage":"179","endPage":"197","ipdsId":"IP-101349","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437171,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LVTWS8","text":"USGS data release","linkHelpText":"Data from 92 sediment incubation experiments using sediments collected from the Fox and Duck rivermouths (adjacent to Green Bay, Lake Michigan; 2016 data)"},{"id":437170,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P995SMVW","text":"USGS data release","linkHelpText":"\tR Code to analyze data from sediment incubation experiments (Fox and Duck Rivermouths; 2016)"},{"id":372096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Green Bay","otherGeospatial":"Duck Creek, Fox River, Green Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.077392578125,\n 44.44162421758805\n ],\n [\n -87.99121856689453,\n 44.44162421758805\n ],\n [\n -87.99121856689453,\n 44.57873024377564\n ],\n [\n -88.077392578125,\n 44.57873024377564\n ],\n [\n -88.077392578125,\n 44.44162421758805\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":781554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"James, William F.","contributorId":213265,"corporation":false,"usgs":false,"family":"James","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":38729,"text":"University of Wisconsin-Stout","active":true,"usgs":false}],"preferred":false,"id":781555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075 fafitzpa@usgs.gov","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":196543,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","email":"fafitzpa@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":781556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Paul C.","contributorId":138628,"corporation":false,"usgs":false,"family":"Frost","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":781557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":149358,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":781558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reneau, Paul C.","contributorId":222219,"corporation":false,"usgs":false,"family":"Reneau","given":"Paul C.","affiliations":[{"id":40507,"text":"former employee, Wisconsin Water Science Center","active":true,"usgs":false}],"preferred":false,"id":781559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xenopoulos, Marguerite A.","contributorId":138629,"corporation":false,"usgs":false,"family":"Xenopoulos","given":"Marguerite","email":"","middleInitial":"A.","affiliations":[{"id":12467,"text":"Department of Biology, Trent University, Peterborough, ON CA","active":true,"usgs":false}],"preferred":false,"id":781560,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70249354,"text":"70249354 - 2020 - Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires","interactions":[],"lastModifiedDate":"2023-10-05T00:14:25.937585","indexId":"70249354","displayToPublicDate":"2020-01-10T12:32:34","publicationYear":"2020","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":"Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires","docAbstract":"Fire Radiative Power (FRP) is related to fire combustion rates and is used to quantify the atmospheric emissions of greenhouse gases and aerosols. FRP over gas flares and wildfires can be retrieved remotely using satellites that observe in shortwave infrared (SWIR) to middle infrared (MIR) wavelengths. Heritage techniques to retrieve FRP developed for wildland fires using the MIR 4 μm radiances have been adapted for the hotter burning gas flares using the SWIR 2 μm observations. Effects of atmosphere, including smoke and aerosols, are assumed to be minimal in these algorithms because of the use of longer than visual wavelengths. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and Landsat 8 observations acquired before and during emergency oil and gas flaring in eastern Saudi Arabia to show that dark, sooty smoke affects both 4 μm and 2 μm observations. While the 2 μm observations used to retrieve gas FRP may be reliable during clear atmospheric conditions, performance is severely impacted by dark smoke. Global remote sensing-based inventories of wildfire and gas flaring need to consider the possibility that soot and dark smoke can potentially lead to an underestimation of FRP over fires.
","language":"English","publisher":"MPDI","doi":"10.3390/rs12020238","usgsCitation":"Kumar, S.S., Hult, J.E., Picotte, J., and Peterson, B., 2020, Potential underestimation of satellite fire radiative power retrievals over gas flares and wildland fires: Remote Sensing, v. 12, no. 2, 238, 9 p., https://doi.org/10.3390/rs12020238.","productDescription":"238, 9 p.","ipdsId":"IP-113025","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":458161,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12020238","text":"Publisher Index Page"},{"id":421611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Saudi Arabia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[42.77933,16.34789],[42.64957,16.77464],[42.34799,17.07581],[42.27089,17.47472],[41.75438,17.83305],[41.22139,18.6716],[40.93934,19.48649],[40.24765,20.17463],[39.80168,20.33886],[39.1394,21.2919],[39.0237,21.98688],[39.06633,22.57966],[38.49277,23.68845],[38.02386,24.07869],[37.48363,24.28549],[37.15482,24.85848],[37.20949,25.08454],[36.93163,25.60296],[36.6396,25.82623],[36.24914,26.57014],[35.64018,27.37652],[35.13019,28.06335],[34.63234,28.05855],[34.78778,28.60743],[34.83222,28.95748],[34.95604,29.35655],[36.06894,29.19749],[36.50121,29.50525],[36.74053,29.86528],[37.50358,30.00378],[37.66812,30.33867],[37.99885,30.5085],[37.00217,31.50841],[39.00489,32.01022],[39.19547,32.16101],[40.39999,31.88999],[41.88998,31.19001],[44.7095,29.17889],[46.56871,29.09903],[47.45982,29.00252],[47.70885,28.52606],[48.41609,28.552],[48.80759,27.68963],[49.29955,27.46122],[49.47091,27.11],[50.15242,26.68966],[50.21294,26.27703],[50.1133,25.94397],[50.23986,25.60805],[50.52739,25.32781],[50.66056,24.9999],[50.81011,24.75474],[51.11242,24.55633],[51.38961,24.62739],[51.57952,24.2455],[51.61771,24.01422],[52.00073,23.00115],[55.0068,22.49695],[55.20834,22.70833],[55.66666,22],[54.99998,19.99999],[52.00001,19],[49.11667,18.61667],[48.18334,18.16667],[47.46669,17.11668],[47,16.95],[46.74999,17.28334],[46.36666,17.23332],[45.4,17.33334],[45.21665,17.43333],[44.06261,17.41036],[43.79152,17.31998],[43.38079,17.57999],[43.1158,17.08844],[43.21838,16.66689],[42.77933,16.34789]]]},\"properties\":{\"name\":\"Saudi Arabia\"}}]}","volume":"12","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Kumar, Sanath S. 0000-0003-4067-4926","orcid":"https://orcid.org/0000-0003-4067-4926","contributorId":330540,"corporation":false,"usgs":true,"family":"Kumar","given":"Sanath","email":"","middleInitial":"S.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":885282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hult, John Edward 0000-0001-8895-3727","orcid":"https://orcid.org/0000-0001-8895-3727","contributorId":330551,"corporation":false,"usgs":true,"family":"Hult","given":"John","email":"","middleInitial":"Edward","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":885283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Picotte, Joshua J. 0000-0002-4021-4623","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":202800,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":885284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885285,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208629,"text":"70208629 - 2020 - Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure","interactions":[],"lastModifiedDate":"2020-02-21T10:40:13","indexId":"70208629","displayToPublicDate":"2020-01-10T10:29:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure","docAbstract":"Infiltration-based green infrastructure has become a popular means of reducing stormwater hazards in urban areas. However, the long-term effects of green infrastructure on the geochemistry of roadside environments are poorly defined, particularly given the considerable roadside legacy metal contamination from historic industrial activity and vehicle emissions (e.g., Pb). Most current research on green infrastructure geochemistry is restricted to time periods of less than a year or limited sets of chemical species. This further limits our understanding of systems that evolve over time and are subject to seasonal variability. Between 2016 and 2018, two infiltration trenches in Pittsburgh, PA, were monitored to determine infiltration rates and dissolved nutrient and metal content. The trench water was analyzed to characterize seasonal patterns in both trench function and chemistry. Shifting patterns in infiltration rate and geochemical activity show trends corresponding with seasonal changes. Trench function is dependent on the local water table, with the highest infiltration rates occurring when evapotranspiration is active and groundwater elevation is low. Two seasonal chemical patterns were identified. The first is driven by road salt application in the winter and interaction of the salt pulse increase Pb and Cu concentrations. The second is driven by the formation of summer reducing environments that increase dissolved Fe and Mn. These findings suggest that chemical and hydrological activity in infiltration-based green infrastructure varies seasonally and may remobilize legacy contamination.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136503","usgsCitation":"Mullins, A.R., Bain, D.J., Pfeil McCullough, E., Hopkins, K.G., Lavin, S., and Copeland, E., 2020, Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure: Science of the Total Environment, v. 714, 136503, 9 p., https://doi.org/10.1016/j.scitotenv.2020.136503.","productDescription":"136503, 9 p.","ipdsId":"IP-107782","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":372502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","city":"Pittsburgh","otherGeospatial":"Schenley Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.95034217834473,\n 40.428067577817366\n ],\n [\n -79.93197441101074,\n 40.428067577817366\n ],\n [\n -79.93197441101074,\n 40.4415907903353\n ],\n [\n -79.95034217834473,\n 40.4415907903353\n ],\n [\n -79.95034217834473,\n 40.428067577817366\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"714","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mullins, Angela R.","contributorId":222657,"corporation":false,"usgs":false,"family":"Mullins","given":"Angela","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":782814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bain, Daniel J 0000-0003-1979-7016","orcid":"https://orcid.org/0000-0003-1979-7016","contributorId":197634,"corporation":false,"usgs":true,"family":"Bain","given":"Daniel","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":782815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeil McCullough, Erin","contributorId":222658,"corporation":false,"usgs":false,"family":"Pfeil McCullough","given":"Erin","email":"","affiliations":[],"preferred":false,"id":782816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hopkins, Kristina G. 0000-0003-1699-9384 khopkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1699-9384","contributorId":195604,"corporation":false,"usgs":true,"family":"Hopkins","given":"Kristina","email":"khopkins@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":782817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lavin, S.","contributorId":107127,"corporation":false,"usgs":true,"family":"Lavin","given":"S.","email":"","affiliations":[],"preferred":false,"id":782818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Copeland, Erin","contributorId":222659,"corporation":false,"usgs":false,"family":"Copeland","given":"Erin","email":"","affiliations":[],"preferred":false,"id":782819,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209414,"text":"70209414 - 2020 - Calcite precipitation in Lake Powell reduces alkalinity and total salt loading to the Lower Colorado River Basin","interactions":[],"lastModifiedDate":"2020-08-04T13:59:38.294865","indexId":"70209414","displayToPublicDate":"2020-01-10T08:25:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Calcite precipitation in Lake Powell reduces alkalinity and total salt loading to the Lower Colorado River Basin","docAbstract":"Reservoirs can retain and transform carbon, nitrogen, phosphorus, and silica, but less is known about their effects on other biogeochemically relevant solutes. The salinization of freshwater ecosystems is a growing concern in many regions, and the role of reservoirs in salinity transport is an important research frontier. Here, we examine how a large desert southwest reservoir, Lake Powell, has altered the downstream transport of total dissolved solids (TDSs) as well as the dominant cations and anions comprising the TDS pool (![\"urn:x-wiley:00243590:media:lno11399:lno11399-math-0001\"](\"https://aslopubs.onlinelibrary.wiley.com/cms/asset/e804c3ff-bfd7-48f1-aae4-42cd05a557b1/lno11399-math-0001.png\")
, ![\"urn:x-wiley:00243590:media:lno11399:lno11399-math-0002\"](\"https://aslopubs.onlinelibrary.wiley.com/cms/asset/6502c6e0-db3d-4fd2-b57f-0736ce6bea4a/lno11399-math-0002.png\")
, and Ca2+). Average downstream TDS concentrations have declined significantly since river impoundment and seasonal fluctuations in TDS concentrations have become more modulated, but year to year variation in TDS concentrations has remained similar. While some of the reductions in TDS concentration can be attributed to watershed management, we find that Lake Powell retains about 10% of the TDS loaded to the system (1991 Mg TDS d−1). Much of this retention is occurring in the forms of calcium and bicarbonate, likely via calcite precipitation, and is equivalent to an average burial of 522 mg C m−2 d−1, thus reducing the alkalinity of downstream water. Flow‐weighted modeling suggests that, in the absence of Lake Powell, downstream salinity limits would be surpassed at the outflow to Lake Powell 41% of the time (vs. 0% of the time currently). Understanding the dominant mechanisms regulating solute transport through the reservoir is important given the relevance for downstream drinking water and irrigation concerns, biogeochemical cycling, and the high potential for reduced flows in the future.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11399","usgsCitation":"Deemer, B., Stets, E.G., and Yackulic, C.B., 2020, Calcite precipitation in Lake Powell reduces alkalinity and total salt loading to the Lower Colorado River Basin: Limnology and Oceanography, v. 65, no. 7, p. 1439-1455, https://doi.org/10.1002/lno.11399.","productDescription":"17 p.","startPage":"1439","endPage":"1455","ipdsId":"IP-112663","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437173,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A9P44R","text":"USGS data release","linkHelpText":"Calcium, magnesium and total dissolved solids data as well as modeled salinity and mass balance estimates for Lake Powell, 1952-2017"},{"id":373749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Lower Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.4228515625,\n 36.87962060502676\n ],\n [\n -109.3798828125,\n 35.02999636902566\n ],\n [\n -104.765625,\n 35.639441068973944\n ],\n [\n -104.19433593749999,\n 37.996162679728116\n ],\n [\n -104.4580078125,\n 40.74725696280421\n ],\n [\n -107.5341796875,\n 43.42100882994726\n ],\n [\n -110.56640625,\n 43.739352079154706\n ],\n [\n -112.54394531249999,\n 43.58039085560784\n ],\n [\n -113.115234375,\n 41.672911819602085\n ],\n [\n -112.412109375,\n 40.3130432088809\n ],\n [\n -112.1484375,\n 39.13006024213511\n ],\n [\n -112.8955078125,\n 37.61423141542417\n ],\n [\n -113.4228515625,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":786378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":786379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":786380,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70227653,"text":"70227653 - 2020 - Resilience management for conservation of inland recreational fisheries","interactions":[],"lastModifiedDate":"2022-01-25T14:28:09.045933","indexId":"70227653","displayToPublicDate":"2020-01-10T08:22:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Resilience management for conservation of inland recreational fisheries","docAbstract":"Resilience thinking has generated much interest among scientific communities, yet most resilience concepts have not materialized into management applications. We believe that using resilience concepts to characterize systems and the social and ecological processes affecting them is a way to integrate resilience into better management decisions. This situation is exemplified by inland recreational fisheries, which represent complex socioecological systems that face unpredictable and unavoidable change. Making management decisions in the context of resilience is increasingly important given mounting environmental and anthropogenic perturbations to inland systems. Herein, we propose a framework that allows resilience concepts to be better incorporated into management by (i) recognizing how current constraints and management objectives focus on desired or undesired systems (specific fish and anglers), (ii) evaluating the state of a system in terms of how both social and ecological forces enforce or erode the desired or undesired system, (iii) identifying the resilience-stage cycles a system state may undergo, and (iv) determining the broad management strategies that may be viable given the system state and resilience stage. We use examples from inland recreational fisheries to illustrate different system state and resilience stages and synthesize several key results. Across all combinations of socioecological forces, five common types of viable management strategies emerge: (i) adopt a different management preference or focus, (ii) change stakeholder attitudes or behaviors via stakeholder outreach, (iii) engage in (sometimes extreme) biological intervention, (iv) engage in fishery intervention, and (v) adopt landscape-level management approaches focusing on achieving different systems in different waters. We then discuss the challenges and weaknesses of our approach, including specifically the cases in which there are multiple strong social forces (i.e., stakeholders holding competing objectives or values) and situations where waters are not readily divisible, such as rivers or great lakes, and in which spatial separation of competing objectives will be difficult. We end with our vision of how we believe these types of operationalized resilience approaches could improve or transform inland recreational fisheries management.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2019.00498","usgsCitation":"Camp, E.V., Kaemingk, M.A., Ahrens, R.N., Potts, W.M., Pine, W.E., Weyl, O.L., and Pope, K.L., 2020, Resilience management for conservation of inland recreational fisheries: Frontiers in Ecology and Evolution, v. 7, 498, 17 p., https://doi.org/10.3389/fevo.2019.00498.","productDescription":"498, 17 p.","ipdsId":"IP-108306","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00498","text":"Publisher Index Page"},{"id":394818,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Camp, E. V.","contributorId":272121,"corporation":false,"usgs":false,"family":"Camp","given":"E.","email":"","middleInitial":"V.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":831557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaemingk, M. A.","contributorId":271091,"corporation":false,"usgs":false,"family":"Kaemingk","given":"M.","email":"","middleInitial":"A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":831558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahrens, R. N. M.","contributorId":272122,"corporation":false,"usgs":false,"family":"Ahrens","given":"R.","email":"","middleInitial":"N. M.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":831559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Potts, W. M.","contributorId":268289,"corporation":false,"usgs":false,"family":"Potts","given":"W.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":831560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pine, W. E. III","contributorId":272123,"corporation":false,"usgs":false,"family":"Pine","given":"W.","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":831561,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weyl, O. L. F","contributorId":272124,"corporation":false,"usgs":false,"family":"Weyl","given":"O.","email":"","middleInitial":"L. F","affiliations":[{"id":48725,"text":"South African Institute for Aquatic Biodiversity","active":true,"usgs":false}],"preferred":false,"id":831562,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":831563,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70208310,"text":"70208310 - 2020 - How often can Earthquake Early Warning systems alert sites with high intensity ground motion?","interactions":[],"lastModifiedDate":"2020-02-04T07:34:49","indexId":"70208310","displayToPublicDate":"2020-01-10T07:33:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"How often can Earthquake Early Warning systems alert sites with high intensity ground motion?","docAbstract":"Although numerous Earthquake Early Warning (EEW) algorithms have been developed we still lack a detailed understanding of how often and under what circumstances useful ground motion alerts can be provided to end-users. Here we analyze the alerting performance of the PLUM, EPIC and FinDer algorithms by running them retrospectively on the seismic strong motion data of the 219 earthquakes in Japan since 1996 that exceeded Modified Mercalli Intensity (MMI) of 4.5 on at least 10 sites (Mw 4.5-9.1). Our analysis suggests that, irrespective of the algorithm, EEW end-users should be prepared that EEW can often but not always provide useful ground motion alerts. A majority of sites with moderate-strong ground motion (MMI 5-6) can generally get at least a few seconds of warning time from all algorithms. If such shaking is caused by a shallow crustal event, around 50% of such sites receive alerts with warning times >5 s. Many sites with severe-extreme ground motion (MMI >=8) can be alerted successfully in the case of very large offshore earthquakes, but less than 20% can be alerted ahead of time if such shaking is caused by a shallow crustal event. Our results provide detailed quantitative insight into the expected alerting performance for EEW algorithms under realistic conditions. The main caveat is that the largest shallow crustal event in our data set has Mw7.0, i.e. the data set does not contain very large strike slip events.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019JB017718","usgsCitation":"Meier, M., Kodera, Y., Bose, M., Chung, A.I., Hoshiba, M., Cochran, E.S., Minson, S.E., Hauksson, E., and Heaton, T., 2020, How often can Earthquake Early Warning systems alert sites with high intensity ground motion?: Journal of Geophysical Research, v. 125, e2019JB017718, 17 p., https://doi.org/10.1029/2019JB017718.","productDescription":"e2019JB017718, 17 p.","ipdsId":"IP-107685","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":458167,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019jb017718","text":"Publisher Index Page"},{"id":371988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Meier, M.-A.","contributorId":222138,"corporation":false,"usgs":false,"family":"Meier","given":"M.-A.","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":781351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kodera, Y.","contributorId":216381,"corporation":false,"usgs":false,"family":"Kodera","given":"Y.","affiliations":[{"id":39398,"text":"JMA","active":true,"usgs":false}],"preferred":false,"id":781352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bose, M.","contributorId":222139,"corporation":false,"usgs":false,"family":"Bose","given":"M.","email":"","affiliations":[{"id":40494,"text":"ETH-Zurich","active":true,"usgs":false}],"preferred":false,"id":781353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chung, A. I.","contributorId":39293,"corporation":false,"usgs":false,"family":"Chung","given":"A.","email":"","middleInitial":"I.","affiliations":[{"id":7033,"text":"School of Earth Sciences, Stanford University","active":true,"usgs":false}],"preferred":false,"id":781354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoshiba, M.","contributorId":222140,"corporation":false,"usgs":false,"family":"Hoshiba","given":"M.","affiliations":[{"id":39398,"text":"JMA","active":true,"usgs":false}],"preferred":false,"id":781355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":781350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Minson, Sarah E. 0000-0001-5869-3477 sminson@usgs.gov","orcid":"https://orcid.org/0000-0001-5869-3477","contributorId":5357,"corporation":false,"usgs":true,"family":"Minson","given":"Sarah","email":"sminson@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":781356,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hauksson, E.","contributorId":196003,"corporation":false,"usgs":false,"family":"Hauksson","given":"E.","affiliations":[],"preferred":false,"id":781357,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Heaton, T.","contributorId":222141,"corporation":false,"usgs":false,"family":"Heaton","given":"T.","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":781358,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
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