Flood-frequency (hereinafter frequency) estimates provide information used to design, operate, and maintain hydraulic structures such as bridges and dams. Failures of these structures could cause catastrophic loss of property, life, or both. In addition to frequency estimates that use annual peak streamflow, frequency estimates of flood durations are required to safely and effectively operate the numerous dams in the Columbia River Basin of the northwestern United States, and British Columbia, Canada. Frequency studies rely on U.S. Geological Survey Guidelines for Determining Flood Flow Frequency (Bulletin 17C, published in 2018). A major consideration in estimating frequencies is the use of skew coefficients, which measure the asymmetry of flood flow distributions. Large uncertainties are associated with estimating the at-site skew coefficients directly from streamflow records, which are limited in length. Skew also is sensitive to extreme events for limited record lengths. Bulletin 17C recommends using regional skew coefficients to weight with the at-site skew estimate for more reliable frequency estimates. In this study, streamflow records from 313 unregulated U.S. Geological Survey streamgage sites and 97 regulated sites with naturalized streamflow records provided by the U.S. Army Corps of Engineers were used to develop regional skew models for the Columbia River Basin. The naturalized streamflow records were synthesized by removing regulatory components such as withdrawals and reservoir storage. Skew models were developed for 1-, 3-, 7-, 10-, 15-, 30-, and 60-day flood durations and used to estimate regional skew coefficients for the Columbia River Basin.
This report used Bayesian statistical regression methods to develop and analyze regional skew models based on hydrologically important basin characteristics. After examining a suite of available basin characteristics, mean annual precipitation had the strongest correlation to skew across the flood durations. Regional skew regression models were fit using mean annual precipitation for selected subbasins in the Columbia River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205073","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Lind, G.D., Lamontagne, J.R., and Stonewall, A.J., 2020, Development of regional skew coefficients for selected flood durations in the Columbia River Basin, northwestern United States and British Columbia, Canada (ver. 1.1, October 2020): U.S. Geological Survey Scientific Investigations Report 2020–5073, 48 p., https://doi.org/10.3133/sir20205073.","productDescription":"Report: viii, 48 p.; 8 Tables; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109443","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":377840,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table1.csv","text":"Table 1","size":"26 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U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Nearly one-sixth of U.S. river basins are unable to consistently meet societal water demands while also providing sufficient water for the environment. Water scarcity is expected to intensify and spread as populations increase, new water demands emerge, and climate changes. Improving water productivity by meeting realistic benchmarks for all water users could allow U.S. communities to expand economic activity and improve environmental flows. Here we utilize a spatially detailed database of water productivity to set realistic benchmarks for over 400 industries and products. We assess unrealized water savings achievable by each industry in each river basin within the conterminous U.S. by bringing all water users up to industry- and region-specific water productivity benchmarks. Some of the most water stressed areas throughout the U.S. West and South have the greatest potential for water savings, with around half of these water savings obtained by improving water productivity in the production of corn, cotton, and alfalfa. By incorporating benchmark-meeting water savings within a national hydrological model (WaSSI), we demonstrate that depletion of river flows across Western U.S. regions can be reduced on average by 6.2–23.2%, without reducing economic production. Lastly, we employ an environmentally extended input-output model to identify the U.S. industries and locations that can make the biggest impact by working with their suppliers to reduce water use 'upstream' in their supply chain. The agriculture and manufacturing sectors have the largest indirect water footprint due to their reliance on water-intensive inputs but these sectors also show the greatest capacity to reduce water consumption throughout their supply chains.
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V","contributorId":145892,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":797431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richter, Brian","contributorId":239628,"corporation":false,"usgs":false,"family":"Richter","given":"Brian","email":"","affiliations":[],"preferred":false,"id":797432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruddell, Benjamin 0000-0003-2967-9339","orcid":"https://orcid.org/0000-0003-2967-9339","contributorId":239629,"corporation":false,"usgs":false,"family":"Ruddell","given":"Benjamin","email":"","affiliations":[{"id":47944,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":797433,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rushforth, Richard","contributorId":239630,"corporation":false,"usgs":false,"family":"Rushforth","given":"Richard","email":"","affiliations":[],"preferred":false,"id":797434,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davis, Kyle F. 0000-0003-4504-1407","orcid":"https://orcid.org/0000-0003-4504-1407","contributorId":239631,"corporation":false,"usgs":false,"family":"Davis","given":"Kyle","email":"","middleInitial":"F.","affiliations":[{"id":47945,"text":"Department of Geography and Spatial Sciences & Department of Plant and Soil Sciences, University of Delaware","active":true,"usgs":false}],"preferred":false,"id":797435,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70228386,"text":"70228386 - 2020 - Groundwater upwelling regulates thermal hydrodynamics and salmonid movements during high-temperature events at a montane tributary confluence","interactions":[],"lastModifiedDate":"2022-02-10T17:53:31.41775","indexId":"70228386","displayToPublicDate":"2020-08-25T11:41:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Groundwater upwelling regulates thermal hydrodynamics and salmonid movements during high-temperature events at a montane tributary confluence","docAbstract":"The Smith River is a popular recreational sport fishery in western Montana, but salmonid abundances there are thought to be artificially limited by riparian land-use alterations, irrigation water withdrawals, and high summer water temperatures. We used integrated networks of temperature loggers, PIT tag antenna stations, and in situ temperature mapping to investigate the thermal hydrodynamics and associated movements of PIT-tagged salmonids at the confluence of Tenderfoot Creek, a major, unaltered coldwater tributary of the Smith River. Contrary to expectations, Tenderfoot Creek itself was not used as a thermal refuge by salmonids during periods of high water temperatures in Smith River; rather, its cool outflow plume into the main stem was used instead. Mean daily outflow water temperatures averaged 2.9°C lower than those of the Smith River during summer and ranged from 0.5°C to 6.1°C lower. Moreover, measured and estimated temperatures in the outflow were cooler (by up to 2.8°C) than in Tenderfoot Creek itself at times as a result of groundwater upwelling at the confluence. Detections of PIT-tagged fish in the thermal plume increased, especially at night, when daily mean water temperatures exceeded 20°C in the main-stem Smith River; more than four times as many PIT-tagged fish were detected in the plume (N = 52) than along the opposite bank (N = 12), which ostensibly afforded better cover. Coldwater tributary confluences may provide superior thermal refuges for salmonids—cooler than the tributaries themselves—when water temperatures in river main stems are stressful.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10259","usgsCitation":"Ritter, T.D., Zale, A.V., Grisak, G., and Lance, M.J., 2020, Groundwater upwelling regulates thermal hydrodynamics and salmonid movements during high-temperature events at a montane tributary confluence: Transactions of the American Fisheries Society, v. 149, no. 5, p. 600-619, https://doi.org/10.1002/tafs.10259.","productDescription":"20 p.","startPage":"600","endPage":"619","ipdsId":"IP-115228","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":455533,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10259","text":"Publisher Index Page"},{"id":395786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Smith River, Tenderfoot Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.2964391708374,\n 46.98804000472103\n ],\n [\n -111.25751495361327,\n 46.98804000472103\n ],\n [\n -111.25751495361327,\n 46.9993095934231\n ],\n [\n -111.2964391708374,\n 46.9993095934231\n ],\n [\n -111.2964391708374,\n 46.98804000472103\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"149","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritter, Thomas David","contributorId":275611,"corporation":false,"usgs":false,"family":"Ritter","given":"Thomas","email":"","middleInitial":"David","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":834174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zale, Alexander V. 0000-0003-1703-885X","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":244099,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":834173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grisak, Grant","contributorId":275612,"corporation":false,"usgs":false,"family":"Grisak","given":"Grant","email":"","affiliations":[{"id":48627,"text":"mtfwp","active":true,"usgs":false}],"preferred":false,"id":834175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lance, Michael J.","contributorId":275613,"corporation":false,"usgs":false,"family":"Lance","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":834176,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212621,"text":"sim3459 - 2020 - Stratigraphic units of shallow unconsolidated deposits in Deadwood, South Dakota, delineated by real-time kinematic surveys","interactions":[],"lastModifiedDate":"2020-08-26T13:05:12.542236","indexId":"sim3459","displayToPublicDate":"2020-08-25T11:11:39","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3459","displayTitle":"Stratigraphic Units of Shallow Unconsolidated Deposits in Deadwood, South Dakota, Delineated by Real-Time Kinematic Surveys","title":"Stratigraphic units of shallow unconsolidated deposits in Deadwood, South Dakota, delineated by real-time kinematic surveys","docAbstract":"The City of Deadwood, South Dakota, has been working on a new archeological investigation in preparation for economic growth and expansion within the city limits, through the Deadwood Historic Preservation Office. During the excavation process, buried artifacts and historical features from the late 1800s have been uncovered. The stratigraphy of shallow unconsolidated deposits in the city of Deadwood, S. Dak., was surveyed on January 29, 2020, using real-time kinematic survey methods and described to identify variations in geologic material, thickness, and depth from the land surface in support of archeological studies by the city. The findings of the study will provide city managers and the public with reliable and impartial information for their use by advancing field or analytical methodology and understanding of hydrologic processes in the study area. The primary excavation site was surveyed, and stratigraphic units were delineated from changes in material properties or depositional environment. The primary excavation site consisted of nine stratigraphic units; however, some units were not consistent along the length of the excavation and pinched out along the cross section. Survey data points also were collected for artifacts and other sites of interest. The shallow surficial geology in the study area was affected by human construction, fires, and flooding.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3459","collaboration":"Prepared in cooperation with the City of Deadwood, South Dakota","usgsCitation":"Tatge, W.S., Medler, C.J., Eldridge, W.G., and Valder, J.F., 2020, Stratigraphic units of shallow unconsolidated deposits in Deadwood, South Dakota, delineated by real-time kinematic surveys: U.S. Geological Survey Scientific Investigations Map 3459, pamphlet 7 p., 1 sheet, https://dx.doi.org/10.3133/sim3459.","productDescription":"Pamphlet: vi, 7 p.; 1 Sheet: 42.75 x 35.40 inches; 1 Table","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-119064","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":377805,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3459/sim3459_table1.csv","text":"Table 1","size":"32.7 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIM 3459 Table 1","linkHelpText":"— Survey points collected for delineation of selected stratigraphic units."},{"id":377804,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3459/sim3459_pamphlet.pdf","text":"Pamphlet","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3459 Pamphlet"},{"id":377803,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3459/sim3459.pdf","text":"Sheet 1","size":"5.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3459","linkHelpText":"— Stratigraphic Units of Shallow Unconsolidated Deposits in Deadwood, South Dakota, Delineated by Real-Time Kinematic Surveys"},{"id":377802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3459/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Deadwood","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.74698638916016,\n 44.364237624976326\n ],\n [\n -103.71814727783202,\n 44.364237624976326\n ],\n [\n -103.71814727783202,\n 44.38558741441454\n ],\n [\n -103.74698638916016,\n 44.38558741441454\n ],\n [\n -103.74698638916016,\n 44.364237624976326\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Sediment in lakes and meadows forms a powerful archive that can be used to reconstruct environmental change through time. Reconstructions of lake level, of chemical, biological, and hydrological conditions, and of surrounding vegetation provide detailed information about past climate conditions, both locally and regionally. Indeed, most of our current knowledge of centennial- to millennial-scale climate variability in the arid western United States, where information about past hydroclimate is particularly important, comes from such sediment-based reconstructions. The pressing need for robust, precise predictions of future conditions is a significant motivation for paleoclimate science, and current research questions frequently require Holocene reconstructions to be resolved at sub-centennial timescales. Increasingly, regional syntheses seek to identify synoptic-scale patterns similar to those defined from modern observations (seasonal, interannual, multi-decadal, etc.) or to compare with the output of climate model simulations. However, the age control on existing records, especially those more than about 20 years old, is often sufficient only for millennial-scale interpretation. Here we assess the age control for 84 published and unpublished records from lakes and meadows in the Great Basin, California, and desert southwest, and use Bayesian modeling to evaluate the 95% uncertainty ranges for the 42 best-dated records. In the Late Holocene, about half of the 42 records have <400-year mean uncertainty ranges; however, high-precision age control is especially critical for young records, used to develop an accurate understanding of a proxy’s response to known climate variations. In the Middle Holocene, records vary from 400 to >800-year mean uncertainty and records of the Early Holocene have 600- to >1400-year mean uncertainty ranges. We find that the largest control on modeled uncertainties is dating density, with at least 2 dates/kyr being optimal and suggest obtaining “range-finder” dates at the onset of a study to better predict the total number of dates needed for an adequate age model. Such a density avoids a commonly observed phenomenon of significant peaks in uncertainty arising in gaps between age control points. Analysis of the uncertainties associated with proxy shifts reveal that more than half are >400 years. Although such large uncertainties currently prevent sub-centennial interpretations in most cases, increased dating density, strategic use of limited funds (including budgeting for a 2 date/kyr minimum at the proposal stage), construction of age-depth models with Bayesian methods, and critical evaluation of chronological uncertainty will shed light on past climate variability at finer timescales, enhancing our understanding of global and regional drivers of western U.S. climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2020.106487","usgsCitation":"Zimmerman, S., and Wahl, D., 2020, Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers: Quaternary Science Reviews, v. 246, 106487, 26 p., https://doi.org/10.1016/j.quascirev.2020.106487.","productDescription":"106487, 26 p.","ipdsId":"IP-117485","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":455535,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1901504","text":"Publisher Index Page"},{"id":379657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.78271484375,\n 32.69486597787505\n ],\n [\n -111.005859375,\n 32.69486597787505\n ],\n [\n -111.005859375,\n 43.97700467496408\n ],\n [\n -124.78271484375,\n 43.97700467496408\n ],\n [\n -124.78271484375,\n 32.69486597787505\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"246","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmerman, Susan 0000-0002-1320-1878","orcid":"https://orcid.org/0000-0002-1320-1878","contributorId":243580,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Susan","email":"","affiliations":[{"id":48737,"text":"CAMS, LLNL","active":true,"usgs":false}],"preferred":false,"id":802616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":802617,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70213158,"text":"70213158 - 2020 - Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw","interactions":[],"lastModifiedDate":"2020-09-10T13:48:58.413233","indexId":"70213158","displayToPublicDate":"2020-08-25T08:34:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Large stocks of peatland carbon and nitrogen are vulnerable to permafrost thaw","docAbstract":"Over many millennia, northern peatlands have accumulated large amounts of carbon and nitrogen, thus cooling the global climate. Over shorter timescales, peatland disturbances can trigger losses of peat and release of greenhouses gases. Despite their importance to the global climate, peatlands remain poorly mapped, and the vulnerability of permafrost peatlands to warming is uncertain. This study compiles over 7,000 field observations to present a data-driven map of northern peatlands and their carbon and nitrogen stocks. We use these maps to model the impact of permafrost thaw on peatlands and find that warming will likely shift the greenhouse gas balance of northern peatlands. At present, peatlands cool the climate, but anthropogenic warming can shift them into a net source of warming.
We present a novel method for measuring the fluctuating basal normal and shear stresses of debris flows by using along‐channel seismic recordings. Our method couples a simple parameterization of a debris flow as a seismic source with direct measurements of seismic path effects using empirical Green's functions generated with a force hammer. We test this method using two large‐scale (8 and 10 m3) experimental flows at the U.S. Geological Survey debris‐flow flume that were recorded by dozens of three‐component seismic sensors. The seismically derived basal stress fluctuations compare well in amplitude and timing to independent force plate measurements within the valid frequency range (15–50 Hz). We show that although the high‐frequency seismic signals provide band‐limited forcing information, there are systematic relations between the fluctuating stresses and independently measured flow properties, especially mean basal shear stress and flow thickness. However, none of the relationships are simple, and since the flow properties also correlate with one another, we cannot isolate a single factor that relates in a simple way to the fluctuating forces. Nevertheless, our observations, most notably the gradually declining ratio of fluctuating to mean basal stresses during flow passage and the distinctive behavior of the coarse, unsaturated flow front, imply that flow style may be a primary control on the conversion of translational to vibrational kinetic energy. This conversion ultimately controls the radiation of high‐frequency seismic waves. Thus, flow style may provide the key to revealing the nature of the relationship between fluctuating forces and other flow properties.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JF005590","usgsCitation":"Allstadt, K.E., Farin, M., Iverson, R.M., Obryk, M., Kean, J.W., Tsai, V.C., Rapstine, T.D., and Logan, M., 2020, Measuring basal force fluctuations of debris flows using seismic recordings and empirical green's functions: Journal of Geophysical Research Earth Surface, v. 125, no. 9, e2020JF005590, 28 p., https://doi.org/10.1029/2020JF005590.","productDescription":"e2020JF005590, 28 p.","ipdsId":"IP-120262","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455542,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020jf005590","text":"Publisher Index Page"},{"id":378389,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":798635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farin, Maxime 0000-0002-0250-2499","orcid":"https://orcid.org/0000-0002-0250-2499","contributorId":221438,"corporation":false,"usgs":false,"family":"Farin","given":"Maxime","email":"","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":798636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":798637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":798638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":798639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsai, Victor C. 0000-0003-1809-6672","orcid":"https://orcid.org/0000-0003-1809-6672","contributorId":199684,"corporation":false,"usgs":false,"family":"Tsai","given":"Victor","email":"","middleInitial":"C.","affiliations":[{"id":27150,"text":"Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":798640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rapstine, Thomas D 0000-0001-5939-9587","orcid":"https://orcid.org/0000-0001-5939-9587","contributorId":224777,"corporation":false,"usgs":true,"family":"Rapstine","given":"Thomas","email":"","middleInitial":"D","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":798641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Logan, Matthew 0000-0002-3558-2405 mlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-2405","contributorId":638,"corporation":false,"usgs":true,"family":"Logan","given":"Matthew","email":"mlogan@usgs.gov","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":798642,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70216213,"text":"70216213 - 2020 - Spatial ecology and resource selection of eastern box turtles","interactions":[],"lastModifiedDate":"2020-11-10T12:50:03.733272","indexId":"70216213","displayToPublicDate":"2020-08-25T06:48:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecology and resource selection of eastern box turtles","docAbstract":"Eastern box turtles (Terrapene carolina carolina) are widely distributed throughout the eastern United States. Although once common throughout much of its distribution, the species has experienced declines in local populations. Understanding resource selection is important for the conservation of this species; however, few data exist on resource selection for eastern box turtles in the southeastern United States. We estimated home range and resource selection for 100 individual turtles in the Blue Ridge, Ridge and Valley, and Cumberland Plateau and Mountains physiographic regions in Tennessee, USA, from 2016 to 2018. We used step‐selection functions to investigate eastern box turtle resource selection during May–August 2017 and May–August 2018 at 2 spatial scales. We classified vegetation type, measured vegetation composition and structure, recorded time since fire, and measured coarse woody debris abundance at 1,225 used telemetry locations and 1,225 associated available points. Home range sizes averaged 9.3 ha ± 3.0 (SE) using minimum convex polygon analysis, 8.25 ha ± 2.88 using 95% kernel density analysis, and 1.50 ha ± 0.56 using 50% kernel density analysis. Box turtles selected areas with greater visual obstruction at the 0–0.25‐m level, greater amounts of 10‐hour and 100‐hour fuels (timelag categories used in fire‐danger ratings), and greater litter depths compared to available locations. Box turtles were more likely to select areas with greater cover of brambles and coarser woody debris and were less likely to select areas with less vegetation cover. Vegetation type and time since last fire did not affect selection. Our data suggest that management activities that encourage greater understory vegetation cover, greater visual obstruction at the 0–0.25‐m level, and greater bramble cover will enhance habitat quality for eastern box turtles.
Understanding the effects of predicted rising sea levels, combined with changes in precipitation and freshwater inflow on key estuarine ecosystem engineers such as the eastern oyster would provide critical information to inform restoration design and predictive models. Using oyster ladders with shell bags placed at three heights to capture a range of inundation levels, oyster growth of naturally recruited spat was monitored over the course of 6 months. Oyster numbers and shell heights were consistently highest in bottom and mid bags experiencing greater than 50% inundation (mid: 63 ± 7%; bottom: 95 ± 3%). Identifying thresholds for optimal oyster growth and survival to enhance restoration engineering would require finer scale evaluation of inundation levels.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/exp.2020.35","usgsCitation":"Marshall, D., and La Peyre, M., 2020, Effects of inundation duration on southeastern Louisiana oyster reefs: Experimental Results, v. 1, e30, 8 p., https://doi.org/10.1017/exp.2020.35.","productDescription":"e30, 8 p.","ipdsId":"IP-117860","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":455546,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/exp.2020.35","text":"Publisher Index Page"},{"id":395933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.2691650390625,\n 29.563901551414418\n ],\n [\n -89.3353271484375,\n 29.563901551414418\n ],\n [\n -89.3353271484375,\n 30.259067203213018\n ],\n [\n -90.2691650390625,\n 30.259067203213018\n ],\n [\n -90.2691650390625,\n 29.563901551414418\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","noUsgsAuthors":false,"publicationDate":"2020-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, Danielle A.","contributorId":239867,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle A.","affiliations":[{"id":48014,"text":"School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":834532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70210900,"text":"fs20203028 - 2020 - Effects of urbanization on water quality in the Edwards aquifer, San Antonio and Bexar County, Texas","interactions":[],"lastModifiedDate":"2020-08-24T17:44:46.374795","indexId":"fs20203028","displayToPublicDate":"2020-08-24T09:58:13","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3028","displayTitle":"Effects of Urbanization on Water Quality in the Edwards Aquifer, San Antonio and Bexar County, Texas","title":"Effects of urbanization on water quality in the Edwards aquifer, San Antonio and Bexar County, Texas","docAbstract":"Continuous water-quality monitoring data and chemical analysis of surface-water and groundwater samples collected during 2017–19 in the recharge zone of the Edwards aquifer were used to develop a better understanding of the surface-water/groundwater connection in and around Bexar County in south-central Texas. This fact sheet is provided to inform water-resource managers, city planners, the scientific community, and the general public about the effects of urbanization on water quality in the Edwards aquifer recharge zone.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203028","collaboration":"Prepared in cooperation with the City of San Antonio","usgsCitation":"Opsahl, S.P., Musgrove, M., and Mecum, K.E., 2020, Effects of urbanization on water quality in the Edwards aquifer, San Antonio and Bexar County, Texas: U.S. Geological Survey Fact Sheet 2020–3028, 4 p., https://doi.org/10.3133/fs20203028.","productDescription":"Report: 4 p.; Companion Report","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-115922","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":376080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3028/coverthb2.jpg"},{"id":376081,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3028/fs20203028.pdf","text":"Report","size":"1.27 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urbanization on the Edwards aquifer recharge zone in the greater San Antonio area raises concern about the potential adverse effects on the public water supply from development. To address this concern, the U.S. Geological Survey, in cooperation with the City of San Antonio, studied patterns of temporal and spatial changes in water quality at selected surface-water and groundwater sites in the Edwards aquifer recharge zone, with an emphasis on changes during periods of groundwater recharge. Water-quality characteristics were continuously monitored and discrete water samples were collected at two sets of paired surface-water (stream) and groundwater (well) sites during a 2-year period (2017–19) that included relatively dry conditions and a large recharge event in September 2018 when as much as 16 inches of rain fell in parts of the study area.
Continuous monitoring of water-level altitude, specific conductance, and concentrations of nitrate in two wells completed in the Edwards aquifer provided high-resolution data showing detailed changes in water quality across a broad range of hydrologic conditions. Water levels in the wells responded rapidly (within hours to days) to recharge from both small and large rainfall and runoff events; changes in groundwater quality as a consequence of the influx of surface-derived recharge were indicated by changes in values of the monitored characteristics. A broad range in measured values of the stable isotopes of water expressed as delta deuterium and delta oxygen-18 in the water samples collected from two streams (Salado and West Elm Creeks), in comparison to the tight clustering of the values of these isotopes in groundwater samples, indicates that source waters (surface waters) of widely varying chemical characteristics become homogenized within the aquifer system.
Concentrations of major ions, trace ions, and nutrient concentrations in stormwater runoff indicate a combination of land-derived and rainfall-derived constituents. The distribution of concentrations of nitrogen species (nitrite, nitrate, and nitrogen in ammonia) among sampling sites transitions from a more variable distribution in stormwater runoff to a more uniform distribution in groundwater in which the dominant form is nitrate. Differences in nitrate isotopic composition and concentration in groundwater across the study area are likely controlled by the relative contributions of natural and anthropogenic nitrogen (with the anthropogenic nitrogen component including a wastewater source) and by the process of nitrification. Among all measured constituents, pesticides detected in discrete stormwater-runoff samples provided the clearest indication that urbanization was adversely affecting water quality; specifically, the more urbanized surface-water site had a greater number of detections and greater variety of detected pesticides. Though temporal variability in the numbers and types of pesticides was evident, the overall proportion of pesticides was dominated by triazine herbicides including atrazine, atrazine degradates, and simazine. The observed hydrologic responses to rainfall and corresponding changes in water quality in wells are thought to result from the direct hydrologic connectivity of surface water and unconfined groundwater; however, patterns of groundwater-quality change indicate mixing from multiple sources such as ambient groundwater, recent surface-derived recharge, and possibly inflow from other aquifers. Therefore, understanding the connection between urbanization and groundwater quality cannot be inferred from the input of stormwater runoff alone as changes related to local and regional hydrologic conditions also need to be considered. It should be noted that a single study comparing the results from two site pairs is not able to support definitive conclusions about the full effect of urbanization on surface water/groundwater quality; however, this study does provide useful insights about the spatial and temporal variability of both stormwater runoff and unconfined groundwater that are consistent with expectations based on the current conceptual model that depicts the Edwards aquifer surface-water/groundwater system as a single water resource.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205033","collaboration":"Prepared in cooperation with the City of San Antonio","usgsCitation":"Opsahl, S.P., Musgrove, M., and Mecum, K.E., 2020, Temporal and spatial variability of water quality in the San Antonio segment of the Edwards aquifer recharge zone, Texas, with an emphasis on periods of groundwater recharge, September 2017–July 2019: U.S. Geological Survey Scientific Investigations Report 2020–5033, 37 p., https://doi.org/10.3133/sir20205033.","productDescription":"Report: x, 37 p.; Companion Report","numberOfPages":"51","onlineOnly":"Y","ipdsId":"IP-112400","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":376131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5033/sir20205033.pdf","text":"Report","size":"1.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5033"},{"id":376132,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/fs20203028","text":"FS 2020-3028","size":"852 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–5028","linkHelpText":"— Effects of urbanization on water quality in the Edwards aquifer, San Antonio and Bexar County"},{"id":376130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5033/coverthb.jpg"}],"country":"United States","state":"Texas","city":"San Antonio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.909912109375,\n 28.613459424004414\n ],\n [\n -97.05322265625,\n 29.635545914466675\n ],\n [\n -98.02001953125,\n 30.472348632640834\n ],\n [\n -99.744873046875,\n 29.49698759653577\n ],\n [\n -98.909912109375,\n 28.613459424004414\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Coral reefs are degrading due to many synergistic stressors. Recently there have been a number of global reports of corals occupying mangrove habitats that provide a supportive environment or refugium for corals, sheltering them by reducing stressors such as oxidative light stress and low pH. This study used satellite imagery and manual ground-truthing surveys to search for mangrove-coral habitats in the Florida Keys National Marine Sanctuary and then collected basic environmental parameters (temperature, salinity, dissolved oxygen, pHNBS, turbidity) at identified sites using a multi-parameter water quality sonde. Two kinds of mangrove-coral habitats were found in both the Upper and Lower Florida Keys: (1) prop-root corals, where coral colonies were growing directly on (and around) mangrove prop roots, and (2) channel corals, where coral colonies were growing in mangrove channels under the shade of the mangrove canopy, at deeper depths and not in as close proximity to the mangroves. Coral species found growing on and directly adjacent to prop roots included Porites porites (multiple morphs, including P. divaricata and P. furcata), Siderastrea radians, and Favia fragum. Channel coral habitats predominantly hosted S. radians and a few S. siderea, although single colonies of Solenastrea bournoni and Stephanocoenia intersepta were observed. Although clear, low-turbidity water was a consistent feature of these mangrove-coral habitats, the specific combination of environmental factors that determine which mangrove habitats are favorable for coral recruitment remains to be defined. Circumstantial evidence suggests additional coral communities existed on mangrove shorelines of oceanside and backcountry islands until destroyed, likely by Hurricane Irma. These mangrove-coral habitats may be climate refugia for corals and could be included in ecosystem management plans and considered for their applications in coral restoration.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.9776","usgsCitation":"Kellogg, C.A., Moyer, R.P., Jacobsen, M., and Yates, K.K., 2020, Identifying mangrove-coral habitats in the Florida Keys: PeerJ, v. 8, e9776, 23 p., https://doi.org/10.7717/peerj.9776.","productDescription":"e9776, 23 p.","ipdsId":"IP-118550","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":455549,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.7717/peerj.9776","text":"External Repository"},{"id":377822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys National Marine Sanctuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.3265380859375,\n 25.117932276583332\n ],\n [\n -80.5023193359375,\n 25.227304826281653\n ],\n [\n -81.08184814453125,\n 25.132852490910697\n ],\n [\n -81.815185546875,\n 25.160201483133374\n ],\n [\n -82.8314208984375,\n 24.864010555361574\n ],\n [\n -82.9083251953125,\n 24.549621500516615\n ],\n [\n -82.09808349609375,\n 24.41714202537204\n ],\n [\n -80.97198486328125,\n 24.65450599548674\n ],\n [\n -80.3265380859375,\n 25.117932276583332\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":797210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moyer, Ryan P.","contributorId":198993,"corporation":false,"usgs":false,"family":"Moyer","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":13560,"text":"Florida Fish and Wildlife Conservation Commission, Eustis, FL","active":true,"usgs":false}],"preferred":false,"id":797211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobsen, Mary","contributorId":239561,"corporation":false,"usgs":false,"family":"Jacobsen","given":"Mary","email":"","affiliations":[{"id":47917,"text":"Fish and Wildlife Research Institute, Florida FWC","active":true,"usgs":false}],"preferred":false,"id":797212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yates, Kimberly K. 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":214349,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":797213,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223730,"text":"70223730 - 2020 - Longer-lived tropical songbirds reduce breeding activity as they buffer impacts of drought","interactions":[],"lastModifiedDate":"2021-09-03T12:45:55.962583","indexId":"70223730","displayToPublicDate":"2020-08-24T07:42:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Longer-lived tropical songbirds reduce breeding activity as they buffer impacts of drought","docAbstract":"Droughts are expected to increase in frequency and severity with climate change. Population impacts of such harsh environmental events are theorized to vary with life history strategies among species. However, existing demographic models generally do not consider behavioural plasticity that may modify the impact of harsh events. Here we show that tropical songbirds in the New and Old Worlds reduced reproduction during drought, with greater reductions in species with higher average long-term survival. Large reductions in reproduction by longer-lived species were associated with higher survival during drought than predrought years in Malaysia, whereas shorter-lived species maintained reproduction and survival decreased. Behavioural strategies of longer-lived, but not shorter-lived, species mitigated the effect of increasing drought frequency on long-term population growth. Behavioural plasticity can buffer the impact of climate change on populations of some species and differences in plasticity among species related to their life histories are critical for predicting population trajectories.
Petroleum in shale reservoirs is hosted in organic matter and mineral pores as well as in natural fractures and voids. For thermally mature plays, e.g., the Marcellus Shale, methane and other light alkane gases are thought to be primarily contained in organic matter pores with radii ≦50 nm. Thus, in order to understand natural gas occurrence, transport, storage, and recoverability within unconventional reservoirs at the dry-gas stage of thermal maturity, it is critical to characterize the associated organic matter porosity across length scales from 50 nm down to the angstrom level. We utilized wide Q-range neutron total scattering to characterize deuterated methane (CD4) adsorption at 60ºC up to the zero average contrast (ZAC) pressure (~60 MPa) within two mineralogically different samples collected from the same producing interval from the Middle Devonian Marcellus Shale. The neutron scattering approach used here provides structural information from the inter-atomic regime up to a nominal pore radius of ~12.5 nm and, by reaching the CD4 ZAC pressure (~60 MPa), it is possible to examine the distribution of open versus closed pores within this pore size range in the samples. Our results indicate that ~10% of the largest pores measured are closed to CD4 for a quartz-rich sample whereas up to 25% of pores with a nominal radius of ~12.5 nm are inaccessible within a sample with an equivalent proportion of quartz, carbonate, and clay. As pore size decreases, accessibility also decreases; all pores with radii ~0.5 nm are effectively closed to CD4 in both samples. Additionally, up to ~4.5× more CD4 is adsorbed within the quartz-rich sample at 60 MPa and we see no evidence for densification of CD4 within the shale pores. These findings suggest that, for shale samples within the dry-gas window, (i) nanometer-scale porosity is primarily located within organic matter, (ii) the amount of available nano-porosity can vary widely over meter scales, and (iii) mineralogy plays a secondary role in dictating methane behavior within these systems.
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A.","affiliations":[{"id":36465,"text":"Disordered Materials Group (ISIS), STFC Rutherford Appleton Laboratory, U.K.","active":true,"usgs":false}],"preferred":false,"id":797284,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Headen, Thomas","contributorId":239572,"corporation":false,"usgs":false,"family":"Headen","given":"Thomas","affiliations":[],"preferred":false,"id":797285,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217208,"text":"70217208 - 2020 - Hydrothermal alteration on composite volcanoes: Mineralogy, hyperspectral imaging and aeromagnetic study of Mt Ruapehu, New Zealand","interactions":[],"lastModifiedDate":"2021-01-12T12:51:59.427134","indexId":"70217208","displayToPublicDate":"2020-08-24T06:45:24","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Hydrothermal alteration on composite volcanoes: Mineralogy, hyperspectral imaging and aeromagnetic study of Mt Ruapehu, New Zealand","docAbstract":"Prolonged volcanic activity can induce surface weathering and hydrothermal alteration that is a primary control on edifice instability, posing a complex hazard with its challenges to accurately forecast and mitigate. This study uses a frequently active composite volcano, Mt Ruapehu, New Zealand, to develop a conceptual model of surface weathering and hydrothermal alteration applicable to long‐lived composite volcanoes. The alteration on Mt Ruapehu was classified using ground samples as non‐altered, supergene argillic, intermediate argillic, and advanced argillic. The first two classes have a paragenesis that is consistent with surficial infiltration and circulation of low‐temperature (<40°C) neutral to mildly acidic fluids, inducing chemical weathering and formation of weathering rims on rock surfaces. The intermediate and advanced argillic alteration formed from hotter (≥100°C) hydrothermal fluids with lower pH, interacting with the andesitic to dacitic host rocks. The distribution of weathering and hydrothermal alteration has been mapped with airborne hyperspectral imaging through image classification, while aeromagnetic data inversion was used to map alteration to up to 500‐m depth. The joint use of hyperspectral imaging complements the geophysical methods since it can spectrally identify hydrothermal alteration mineralogy. This study established a conceptual model of hydrothermal alteration history of Mt Ruapehu, exemplifying a long‐lived and nested active and ancient hydrothermal system. This study's combination approach can be used to indicate the most likely sources of future debris avalanches, which are a significant hazard on Ruapehu.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020GC009270","usgsCitation":"Kereszturi, G., Schaefer, L.N., Miller, C.A., and Mead, S., 2020, Hydrothermal alteration on composite volcanoes: Mineralogy, hyperspectral imaging and aeromagnetic study of Mt Ruapehu, New Zealand: Geochemistry, Geophysics, Geosystems, v. 21, no. 9, e2020GC009270, 28 p., https://doi.org/10.1029/2020GC009270.","productDescription":"e2020GC009270, 28 p.","ipdsId":"IP-121751","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455555,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/7f0a71d89f2449cb949ef5b223d16534","text":"External Repository"},{"id":382079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Mt Ruapehu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 175.166015625,\n -40.71395582628604\n ],\n [\n 176.57226562500003,\n -40.71395582628604\n ],\n [\n 176.57226562500003,\n -36.738884124394296\n ],\n [\n 175.166015625,\n -36.738884124394296\n ],\n [\n 175.166015625,\n -40.71395582628604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Kereszturi, Gabor 0000-0003-4336-2012","orcid":"https://orcid.org/0000-0003-4336-2012","contributorId":247601,"corporation":false,"usgs":false,"family":"Kereszturi","given":"Gabor","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":808007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":808008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Craig A. 0000-0001-8499-0352","orcid":"https://orcid.org/0000-0001-8499-0352","contributorId":219638,"corporation":false,"usgs":false,"family":"Miller","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":808009,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mead, Stuart","contributorId":247602,"corporation":false,"usgs":false,"family":"Mead","given":"Stuart","email":"","affiliations":[{"id":49587,"text":"Volcanic Risk Solutions, Massey University, Palmerston North, 4474, New Zealand","active":true,"usgs":false}],"preferred":false,"id":808010,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216219,"text":"70216219 - 2020 - Impact of smallmouth bass predation on subyearling fall Chinook salmon over a broad river continuum","interactions":[],"lastModifiedDate":"2020-11-10T12:38:40.915087","indexId":"70216219","displayToPublicDate":"2020-08-24T06:36:15","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Impact of smallmouth bass predation on subyearling fall Chinook salmon over a broad river continuum","docAbstract":"Smallmouth bass (Micropterus dolomieu) predation on subyearling fall Chinook salmon (Oncorhynchus tshawytscha) was examined in the Snake River (USA) to identify seasonal and habitat-related changes in bass diets, and associated subyearling consumption and loss in various riverine and impounded reaches. Smallmouth bass diets reflected opportunistic foraging that at times showed predation on subyearlings is influenced by the consumption of other prey such as crayfish, sand roller (Percopsis transmontana), and smaller invertebrates. Estimated loss of subyearlings was influenced by bass abundance and consumption rates. The highest bass abundances (> 1,000 bass/river kilometer) were observed in the upper reach of Hells Canyon early in April and May, and in Lower Granite Reservoir. Peak consumption rates of subyearlings (≥ 0.12 subyearlings/bass/day) occurred in the upper reach of Hells Canyon during May and in most reservoir reaches in June. Predation losses accumulated evenly along the river continuum from riverine to reservoir habitats. We estimated that 869,371 subyearlings could be lost to smallmouth bass predation between riverine production areas and Lower Granite Dam in a given year. To provide a context for this estimated loss, we provide an illustration of its potential effect on the adult population. Assuming no juvenile mortality occurred downstream of the dam and depending on smolt-to-adult return rates, this represented up to 3.9–16.0% of the potential adult run that could have returned to Lower Granite Dam had no subyearling predation by smallmouth bass occurred upstream of the dam. Although this study was limited by a number of assumptions and constraints, it does provide an illustration of how predation affects juvenile and adult salmon loss over a broad, changing river landscape.
Long Island, New York, has a mix of urban/suburban to agricultural/horticultural land use and nearly 3 million residents that rely on a sole-source aquifer for drinking water. The analysis of shallow groundwater (<40 m below land surface) collected from 54 monitoring wells across Long Island detected 53 pesticides or pesticide degradates. Maximum concentrations for individual pesticides or pesticide degradates ranged from 3 to 368,000 ng/L. The highest concentrations and most frequent pesticide detections occurred in samples collected from the pesticide management (PM) network, set in an agricultural/horticultural area in eastern Long Island with coordinated pesticide management by state and local agencies. The other two networks (Suffolk and Nassau/Queens) were set in suburban and urban areas, respectively, and had less frequent detections and lower pesticide concentrations than the PM network. Pesticide detections and concentration patterns (herbicide, insecticide, or fungicide) differed among the three networks revealing broad differences in land use. The predominance of fungicides metalaxyl, 1H-1,2,4-triazole (propiconazole/myclobutanil degradate), and 4-hydroxychlorothalonil (HCTL, chlorothalonil degradate) in samples from the PM network reflects their intensive use in agricultural settings. Total fungicide concentrations in the PM network ranged from <10 to >300,000 ng/L. The widespread detection of imidacloprid and triazine herbicides, simazine and atrazine, reveal a mixture of current and past use pesticides across the Long Island region. Low concentrations (<200 ng/L) of the triazines in the Suffolk and Nassau/Queens networks may reflect a change in land use and application. Acetanilide herbicides and aldicarb have been discontinued for 20 and 40 years, respectively, yet the concentrations of their degradates were among the highest observed in this study. Acetanilide (total concentrations up to 10,000 ng/L) and aldicarb degradates (up to 270 ng/L) are present in the PM network at much lower concentrations than previous Long Island studies and reflect changes in agricultural practices and pesticide management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.141895","usgsCitation":"Fisher, I., Phillips, P.J., Bayraktar, B., Chen, S., McCarthy, B.A., and Sandstrom, M.W., 2020, Pesticides and their degradates in groundwater reflect past use and current management strategies, Long Island, New York, USA: Science of the Total Environment, v. 752, 141895, 13 p., https://doi.org/10.1016/j.scitotenv.2020.141895.","productDescription":"141895, 13 p.","ipdsId":"IP-118513","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":377819,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.806640625,\n 41.05035951931887\n ],\n [\n -72.18292236328125,\n 41.24270715552139\n ],\n [\n -72.6910400390625,\n 41.03585891144301\n ],\n [\n -73.35296630859375,\n 40.9964840143779\n ],\n [\n -73.707275390625,\n 40.907285514728756\n ],\n [\n -73.948974609375,\n 40.77430186363723\n ],\n [\n -74.0313720703125,\n 40.686886382151116\n ],\n [\n -74.058837890625,\n 40.622291783092706\n ],\n [\n -74.02313232421875,\n 40.55972134684838\n ],\n [\n -73.86383056640625,\n 40.53258931069554\n ],\n [\n -72.96844482421875,\n 40.62437645591559\n ],\n [\n -71.806640625,\n 41.05035951931887\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"752","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fisher, Irene 0000-0002-3792-7235 ifisher@usgs.gov","orcid":"https://orcid.org/0000-0002-3792-7235","contributorId":223594,"corporation":false,"usgs":true,"family":"Fisher","given":"Irene","email":"ifisher@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bayraktar, Banu 0000-0003-3612-6767","orcid":"https://orcid.org/0000-0003-3612-6767","contributorId":217670,"corporation":false,"usgs":true,"family":"Bayraktar","given":"Banu","email":"","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Shirley 0000-0002-3330-4110","orcid":"https://orcid.org/0000-0002-3330-4110","contributorId":239545,"corporation":false,"usgs":false,"family":"Chen","given":"Shirley","email":"","affiliations":[{"id":47905,"text":"USGS NYWSC - 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2020 - 2,200-Year tree-ring and lake-sediment based snowpack reconstruction for the northern Rocky Mountains highlights the historic magnitude of recent snow drought","interactions":[],"lastModifiedDate":"2020-10-22T15:05:12.329713","indexId":"70215531","displayToPublicDate":"2020-08-22T09:57:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7169,"text":"Quaternary Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"2,200-Year tree-ring and lake-sediment based snowpack reconstruction for the northern Rocky Mountains highlights the historic magnitude of recent snow drought","docAbstract":"In recent decades, Rocky Mountain accumulated snowpack levels have experienced rapid declines, yet long-term records of snowpack prior to the installation of snowpack observation stations in the early and mid 20th century are limited. To date, a small number of tree-ring based reconstructions of April 1 Snow Water Equivalent (SWE) in the northern Rocky Mountains have extended modern records of snowpack variability to ∼1200 C.E. Carbonate isotope lake sediment records, provide an opportunity to further extend tree-ring based reconstructions through the Holocene, providing a millennial-scale temporal record that allows for an evaluation of multi-scale drivers of snowpack variability, from internal climate dynamics to orbital-scale forcings. Here we present a ∼2200 year preliminary reconstruction of northern Rockies snowpack based on δ18O measurements of sediment carbonates collected from Foy Lake, Montana. We explore the statistical calibration of lake sediment δ18O to an annually resolved snowpack reconstruction from tree rings, and develop an approach to assess and quantify potential sources of error in this reconstruction approach. The sediment-based snowpack reconstruction shows strong low-frequency variability in snowpack over the last two millennia with few snow droughts approaching the magnitude of recent snowpack declines. Given the growing availability of high-resolution, carbonate-rich lake sediment records, such reconstructions could help improve our understanding of how snowpack conditions varied under previous climatic events (mid-Holocene climate optimum ca. 9−6 ka), providing critical insights for anticipating future snowpack conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.qsa.2020.100013","usgsCitation":"Schoenemann, S., Martin, J.T., Pederson, G.T., and McWethy, D.B., 2020, 2,200-Year tree-ring and lake-sediment based snowpack reconstruction for the northern Rocky Mountains highlights the historic magnitude of recent snow drought: Quaternary Science Advances, v. 2, 100013, 13 p., https://doi.org/10.1016/j.qsa.2020.100013.","productDescription":"100013, 13 p.","ipdsId":"IP-118382","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":455564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.qsa.2020.100013","text":"Publisher Index Page"},{"id":379658,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, British Columbia, Idaho, Montana, Nevada, Oregon, Washington, Wyoming","otherGeospatial":"Nothern Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.1044921875,\n 49.26780455063753\n ],\n [\n -116.76269531249999,\n 53.067626642387374\n ],\n [\n -122.16796875,\n 53.38332836757156\n ],\n [\n -121.37695312499999,\n 49.89463439573421\n ],\n [\n -119.00390625,\n 46.46813299215554\n ],\n [\n -117.20214843749999,\n 43.03677585761058\n ],\n [\n -115.4443359375,\n 43.48481212891603\n ],\n [\n -112.939453125,\n 43.29320031385282\n ],\n [\n -115.400390625,\n 41.83682786072714\n ],\n [\n -114.345703125,\n 40.245991504199026\n ],\n [\n -110.5224609375,\n 42.84375132629021\n ],\n [\n -107.314453125,\n 42.16340342422401\n ],\n [\n -105.3369140625,\n 43.644025847699496\n ],\n [\n -108.45703125,\n 46.649436163350245\n ],\n [\n -112.1044921875,\n 49.26780455063753\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenemann, Spruce W.","contributorId":243573,"corporation":false,"usgs":false,"family":"Schoenemann","given":"Spruce W.","affiliations":[{"id":48731,"text":"University of Western Montana","active":true,"usgs":false}],"preferred":false,"id":802603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Justin T. 0000-0002-3523-6596","orcid":"https://orcid.org/0000-0002-3523-6596","contributorId":215418,"corporation":false,"usgs":true,"family":"Martin","given":"Justin","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":802604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":802605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McWethy, David B.","contributorId":207232,"corporation":false,"usgs":false,"family":"McWethy","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":802606,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212659,"text":"70212659 - 2020 - Evaluating stereo DTM quality at Jezero Crater, Mars with HRSC, CTX, and HiRISE images","interactions":[],"lastModifiedDate":"2020-08-25T15:51:05.37368","indexId":"70212659","displayToPublicDate":"2020-08-21T10:50:52","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Evaluating stereo DTM quality at Jezero Crater, Mars with HRSC, CTX, and HiRISE images","docAbstract":"We have used a high-precision, high-resolution digital terrain model (DTM) of the NASA Mars 2020 rover Perseverance landing site in Jezero crater based on mosaicked images from the Mars Reconnaissance Orbiter High Resolution Imaging Science Experiment (MRO HiRISE) camera as a reference dataset to evaluate DTMs based on Mars Express High Resolution Stereo Camera (MEX HRSC) and MRO Context camera (CTX) images. Results are consistent with our earlier HRSC-HiRISE comparisons at the Mars Science Laboratory (MSL) Curiosity landing site in Gale crater, confirming that those results were not compromised by the small area compared and potential problems with spatial registration. Specifically, height errors are on the order of half a pixel and correspond to an image matching error of 0.2–0.3 pixel but estimates of horizontal resolution are 10–20 pixels. Products from the HRSC team pipeline at DLR are smoother but more precise vertically than those produced by using the commercial stereo package SOCET SET®. The DLR products are also homogenous in quality, whereas the SOCET products are less smoothed and have higher errors in rougher terrain. Despite this weak variation, our results are consistent with a rule of thumb of 0.2–0.3 pixel matching precision based on many prior studies. Horizontal resolution is significantly coarser than the DTM ground sample distance (GSD), which is typically 3–5 pixels.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"International archives of the photogrammetry, remote sensing, and spatial information sciences","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"XXIV ISPRS Congress 2020","conferenceDate":"Aug 31-Sep 2, 2020","conferenceLocation":"Nice, France","language":"English","publisher":"International Society for Photogrammetry and Remote Sensing","doi":"10.5194/isprs-archives-XLIII-B3-2020-1129-2020","usgsCitation":"Kirk, R.L., Fergason, R.L., Redding, B.L., Galuszka, D.M., Smith, E., Mayer, D., Hare, T.M., and Gwinner, K., 2020, Evaluating stereo DTM quality at Jezero Crater, Mars with HRSC, CTX, and HiRISE images, in International archives of the photogrammetry, remote sensing, and spatial information sciences, v. 43, no. 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However, the extraction and interpretation of phenology in ecosystems with subtle growth dynamics can be challenging. US National Park Service monitoring of evergreen pinyon-juniper ecosystems in the western US revealed an unexpected winter-peaking phenological pattern in normalized difference vegetation index (NDVI) time-series derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. In this paper, we assess the validity of the winter peaks through ground-based observation of phenology and examination of solar and satellite geometry effects. To test the premise of a true vegetation response, we analyzed NDVI values extracted from a time series of ground-based digital camera (‘phenocam’) images collected September 2017 to December 2018 in a pinyon-juniper woodland in Arizona, US. Results show pinyon and juniper growth peaked in the warm season, as did the other species in the phenocam field of view. NDVI time series from four other sensors (Landsat 7, Sentinel-2, VIIRS, and Proba-V) confirmed that winter peaks in this ecosystem are not limited to MODIS products. Examination of NDVI time series (2003–2018) derived from daily 250-m MODIS data in the broader pinyon-juniper ecosystem revealed that solar-to-sensor angle, sensor zenith angle, and forward/back-scatter reflectance explained >80% of intra-annual variability. Solar-to-sensor angle exerted the greatest control, and the direction of its correlation (positive) was the opposite of that which would be expected if it were driven by vegetation greenness. Solar-to-sensor angle is controlled seasonally by solar zenith angle and daily by variations in satellite overpass geometry. We mapped winter peaks across the western US in Google Earth Engine using 500-m MODIS MCD43A4 data, which correct for reflectance differences caused by view angle. In areas where winter vegetation peaks are ecologically improbable (i.e., locations with sub-freezing December temperatures), consistent winter peaks (≥ 14 years in 2003 to 2018) are widespread in both pinyon-juniper and non-pinyon-juniper conifer ecosystems; winter peaks are common (≥ 5 years in 2003 to 2018) across areas of shrubland. We attribute winter peaks to the positive correlation of NDVI with solar-to-sensor angle and solar zenith angle in combination with sparse, vertically oriented evergreen vegetation canopies. Increasing shadow visibility has been shown to increase overall NDVI, and the prevalence of the winter peaking in evergreen western sparse canopy ecosystems is consistent with this hypothesis. The extent of winter peaking patterns may have been previously overlooked due to temporal compositing, curve fitting, and incomplete snow screening.
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However, conclusions from most previous studies do not provide information about local climate effects, and little research has directly quantified how LCLUC intensity within different ecoregions relates to climate variation. In this study, we present an observation-based analysis of climate sensitivity to LCLUC based on decadal LCLUC and climate data in different ecoregions. Our results revealed that variations in land surface temperature and vapor pressure were most sensitive to LCLUC across the conterminous United States, while precipitation was less sensitive. Persistent warming effects were produced from LCLUC in Appalachian and some of the central U.S., High Plains, and northwest ecoregions, but cooling effects were evident in the many southeast, northeast and some Great Lakes and Intermountain West ecoregions. Most of the warming and a few cooling ecoregions were sensitive to LCLUC. Ecoregions with increasing vapor pressure were found across the Great Plains, Intermountain West, and West Coast ecoregions and several of these regions in the Great Plains and West Coast were sensitive to LCLUC. A combination of changes in temperature, precipitation, and vapor pressure was used to characterize climate sensitivity associated with LCLUC forcing, and five major persistent patterns were found in some ecoregions. These findings suggest that climate conditions, especially temperature and vapor pressure, in some ecoregions are sensitive to LCLUC and such change should be better incorporated into regional climate assessments.
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0000-0002-0804-5823","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":223104,"corporation":false,"usgs":false,"family":"Vogelmann","given":"James","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":796909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zeng, Xubin","contributorId":139490,"corporation":false,"usgs":false,"family":"Zeng","given":"Xubin","email":"","affiliations":[],"preferred":false,"id":796910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Homer, Collin 0000-0003-4755-8139 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8139","contributorId":238939,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":796911,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212840,"text":"70212840 - 2020 - Identifying sustainable winter habitat for whooping cranes","interactions":[],"lastModifiedDate":"2020-09-24T16:04:27.058967","indexId":"70212840","displayToPublicDate":"2020-08-21T08:59:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6474,"text":"Journal of Nature Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Identifying sustainable winter habitat for whooping cranes","docAbstract":"The only self-sustaining population of endangered whooping cranes (Grus americana) requires a network of conservation lands for wintering along the Texas Gulf Coast (USA), so that this increasing population can reach downlisting under the Endangered Species Act (1,000 birds). We identify locations providing the highest quality and most sustainable wintering habitat for these whooping cranes through 2100 by predicting future habitats under three projections of sea level rise (0.6, 1.0 and 2.0 m by 2100), while incorporating two scenarios of future urban development. Our method combines predictions of future habitat quality with current whooping crane density estimates to calculate the potential carrying capacity of whooping cranes for each 10 m pixel within this 17,725 km2 area. We found whooping cranes used locations with salt marsh at twice the rate of places lacking marsh. Areas > 15 km from development or < 2 km from estuarine water had increased crane use. Predicted area of salt marsh habitat oscillated across time given different rates of sea level rise. One urbanization scenario predicted 3% and the other 1% of the area converting to development by 2100. We estimated the study area can support 4414 (95% CI: 4096-4789) whooping cranes currently, 4795 (95% CI: 4402-5269) with 0.6 m sea level rise, 3559 (95% CI: 3352-3791) with 1 m sea level rise, and 2480 (95% CI: 2375-2592) with 2 m sea level rise by 2100, under the more aggressive urban development scenario. By anticipating climate-induced habitat loss with species population expansion we provide the requisite spatial information for conservation planners to build a sustainable conservation estate for downlisting whooping cranes. By coupling wildlife biology with conservation planning and on-the-ground implementation, our work exemplifies a proactive approach to recover endangered species.
The growth hormone (Gh)/insulin-like growth-factor (Igf)/Igf binding protein (Igfbp) system regulates growth and osmoregulation in salmonid fishes, but how this system interacts with other endocrine systems is largely unknown. Given the well-documented consequences of mounting a glucocorticoid stress response on growth, we hypothesized that cortisol inhibits anabolic processes by modulating the expression of hepatic igfbp mRNAs. Atlantic salmon (Salmo salar) parr were implanted intraperitoneally with cortisol implants (0, 10, and 40 μg g−1 body weight) and sampled after 3 or 14 days. Cortisol elicited a dose-dependent reduction in specific growth rate (SGR) after 14 days. While plasma Gh and Igf1 levels were unchanged, hepatic igf1 mRNA was diminished and hepatic igfbp1b1 and -1b2 were stimulated by the high cortisol dose. Plasma Igf1 was positively correlated with SGR at 14 days. Hepatic gh receptor (ghr), igfbp1a, -2a, -2b1, and -2b2 levels were not impacted by cortisol. Muscle igf2, but not igf1 or ghr, levels were stimulated at 3 days by the high cortisol dose. As both cortisol and the Gh/Igf axis promote seawater (SW) tolerance, and particular igfbps respond to SW exposure, we also assessed whether cortisol coordinates the expression of branchial igfbps and genes associated with ion transport. Cortisol stimulated branchial igfbp5b2 levels in parallel with Na+/K+-ATPase (NKA) activity and nka-α1b, Na+/K+/2Cl--cotransporter 1 (nkcc1), and cystic fibrosis transmembrane regulator 1 (cftr1) mRNA levels. The collective results indicate that cortisol modulates the growth of juvenile salmon via the regulation of hepatic igfbp1s whereas no clear links between cortisol and branchial igfbps previously shown to be salinity-responsive could be established.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mce.2020.110989","usgsCitation":"Breves, J.P., Springer-Miller, R., Chenoweth, D., Paskavitz, A.L., Chang, A.Y., Regish, A.M., Einarsdottir, I., Bjornsson, B., and McCormick, S.D., 2020, Cortisol regulates insulin-like growth-factor binding protein (igfbp) gene expression in Atlantic salmon parr: Molecular and Cellular Endocrinology, v. 518, 110989, 10 p., https://doi.org/10.1016/j.mce.2020.110989.","productDescription":"110989, 10 p.","ipdsId":"IP-120328","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":455576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mce.2020.110989","text":"Publisher Index Page"},{"id":378448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"518","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Breves, Jason P.","contributorId":6349,"corporation":false,"usgs":false,"family":"Breves","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":798854,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springer-Miller, R.H.","contributorId":240717,"corporation":false,"usgs":false,"family":"Springer-Miller","given":"R.H.","email":"","affiliations":[{"id":35659,"text":"Skidmore College","active":true,"usgs":false}],"preferred":false,"id":798855,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chenoweth, D A","contributorId":240718,"corporation":false,"usgs":false,"family":"Chenoweth","given":"D A","affiliations":[{"id":35659,"text":"Skidmore College","active":true,"usgs":false}],"preferred":false,"id":798856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paskavitz, A L","contributorId":240719,"corporation":false,"usgs":false,"family":"Paskavitz","given":"A","email":"","middleInitial":"L","affiliations":[{"id":35659,"text":"Skidmore College","active":true,"usgs":false}],"preferred":false,"id":798857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chang, A Y H","contributorId":240720,"corporation":false,"usgs":false,"family":"Chang","given":"A","email":"","middleInitial":"Y H","affiliations":[{"id":35659,"text":"Skidmore College","active":true,"usgs":false}],"preferred":false,"id":798858,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Regish, Amy M. 0000-0003-4747-4265 aregish@usgs.gov","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":5415,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"aregish@usgs.gov","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":798859,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Einarsdottir, I E","contributorId":240721,"corporation":false,"usgs":false,"family":"Einarsdottir","given":"I E","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":798860,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bjornsson, Bjorn","contributorId":240722,"corporation":false,"usgs":false,"family":"Bjornsson","given":"Bjorn","affiliations":[{"id":12695,"text":"University of Gothenburg","active":true,"usgs":false}],"preferred":false,"id":798861,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":798862,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70214577,"text":"70214577 - 2020 - The recurrence interval of post-fire debris-flow generating rainfall in the southwestern United States","interactions":[],"lastModifiedDate":"2020-09-30T13:48:02.082388","indexId":"70214577","displayToPublicDate":"2020-08-21T08:43:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The recurrence interval of post-fire debris-flow generating rainfall in the southwestern United States","docAbstract":"In the southwestern United States, post-fire debris flows commonly initiate during short bursts of intense rainfall. To date, the frequency of the rainfall rates has not been quantified. Here, we combine an existing database of debris-flow occurrences and corresponding peak storm intensities with a geospatial library of rainfall recurrence interval (RI) information and climate type to determine the distribution of the estimated frequencies of the rainfall associated with 316 observed post-fire debris flows in the southwestern United States. Our results indicate that a majority (77%) of the observed debris flows were triggered by rainfall intensities with RI less than 2 years. Climatic and geographic differences in RI were evident in our analysis. Debris flows in most of the analyzed climates within California, Colorado, and New Mexico were primarily associated with 1-year or less RI intensities, whereas debris flows in arid portions of Arizona, Colorado, and Utah tended to be generated during storms greater than 2-year RI. Event consequence, as defined by the impact on downstream communities and infrastructure, was not directly related to RI, as very destructive debris flows were initiated at a wide range of RI intensities. Our results highlight that post-fire debris-flow initiation can be expected during common rainstorms in the southwestern United States, therefore emergency management plans and risk mitigation efforts must focus on both extreme and frequent rainstorms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2020.107392","usgsCitation":"Staley, D.M., Kean, J.W., and Rengers, F.K., 2020, The recurrence interval of post-fire debris-flow generating rainfall in the southwestern United States: Geomorphology, v. 370, 107392, 10 p., https://doi.org/10.1016/j.geomorph.2020.107392.","productDescription":"107392, 10 p.","ipdsId":"IP-120705","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455579,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2020.107392","text":"Publisher Index Page"},{"id":436814,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CHY45I","text":"USGS data release","linkHelpText":"Data supporting an analysis of the recurrence interval of post-fire debris-flow generating rainfall in the southwestern United States"},{"id":378897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.71679687499999,\n 31.42866311735861\n ],\n [\n -102.5244140625,\n 31.42866311735861\n ],\n [\n -102.5244140625,\n 42.58544425738491\n ],\n [\n -124.71679687499999,\n 42.58544425738491\n ],\n [\n -124.71679687499999,\n 31.42866311735861\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"370","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":800141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":800142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":800143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}