The Younger Dryas (YD, 12.9–11.7 ka) is the most recent, near-global interval of abrupt climate change with rates similar to modern global warming. Understanding the causes and biodiversity effects of YD climate changes requires determining the spatial fingerprints of past temperature changes. Here we build pollen-based and branched glycerol dialkyl glycerol tetraether-based temperature reconstructions in eastern North America (ENA) to better understand deglacial temperature evolution. YD cooling was pronounced in the northeastern United States and muted in the north central United States. Florida sites warmed during the YD, while other southeastern sites maintained a relatively stable climate. This fingerprint is consistent with an intensified subtropical high during the YD and demonstrates that interhemispheric responses were more complex spatially in ENA than predicted by the bipolar seesaw model. Reduced-amplitude or antiphased millennial-scale temperature variability in the southeastern United States may support regional hotspots of biodiversity and endemism.
Spectral analysis is widely used to estimate and refine earthquake source parameters such as source radius, seismic moment, and stress drop. This study aims to quantify the precision of the single spectra and empirical Green's function spectral ratio approach using the Large‐n Seismic Survey in Oklahoma (LASSO) array. The dense station coverage in an area of local saltwater disposal offers a unique opportunity to observe and quantify radiation pattern effects and subsequent precision of spectral estimates of small earthquakes (M < 3). The results suggest that the precision of source properties estimated from direct phase arrivals for arrays with less than 20 stations should be assumed to be not less than 30% and could be as high as 150% if less than five stations are used. Furthermore, we do not see clear evidence for, or against, a scaling of stress drop with magnitude of small earthquakes (M < 3) as observed by other studies.
Chlorinated volatile organic compounds (CVOCs) have migrated to groundwater beneath a former 9-acre landfill at Operable Unit 1 (OU-1) on Naval Base Kitsap, which was active from the 1930s through 1973 on the Keyport Peninsula, in Kitsap County, Washington. Biodegradation of CVOCs at OU-1 limits the mass of dissolved-phase CVOCs in groundwater that discharges to surface water, but contaminant concentrations up to 630 milligrams per liter persist in localized areas, likely from the dissolution of residual, non-aqueous phase liquids. Variable-density groundwater-flow and contaminant-transport models were developed using the SEAWAT-Version 4 computer program to simulate the direction and rate of groundwater flow in a 5.9 square-mile (mi2) - area surrounding the Keyport Peninsula, to estimate the CVOC mass in groundwater and the rate of mass loading, and to assess possible remedial activities at OU-1.
The study area is underlain by Quaternary deposits consisting of alternating glacial and interglacial sediments ranging from 500 to 1,500 feet (ft) thick. A hydrogeologic model delineated a sequence of 10 units including a relatively thin package (less than 100 ft) of recent sediments (Vashon Stade and younger) beneath the Keyport Peninsula that are underlain by the much thicker (more than 300 ft) Clover Park Aquitard, which overlies a confined, sea-level aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205066","collaboration":"Prepared in cooperation with the Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Yager, R.M., Welch, W.B., Headman, A., and Dinicola, R.S., 2020, Variable-density groundwater flow and contaminant transport, Operable Unit 1, Naval Base Kitsap, Keyport, Washington: U.S. Geological Survey Scientific Investigations Report 2020–5066, 58 p., https://doi.org/10.3133/sir20205066.","productDescription":"x, 62 p.","onlineOnly":"Y","ipdsId":"IP-112628","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":379666,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95WQ7TM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Soil water balance (SWB) model of Keyport, Washington"},{"id":379617,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5066/sir20205066.pdf","text":"Report","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5066"},{"id":379667,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YNPPNL","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-2005, MODFLOW-NWT, and SEAWAT V.4 models used to simulate variable-density groundwater flow and contaminant transport at Naval Base Kitsap, Keyport, Washington"},{"id":379616,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5066/coverthb2.jpg"}],"country":"United States","state":"Washington","city":"Keyport","otherGeospatial":"Naval Base Kitsap","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.65,\n 47.6666\n ],\n [\n -122.60833,\n 47.6666\n ],\n [\n -122.60833,\n 47.71666\n ],\n [\n -122.65,\n 47.71666\n ],\n [\n -122.65,\n 47.6666\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Declining water levels and reduced natural discharge at springs, seeps, and phreatophyte areas primarily are the result of decades of groundwater development in the Death Valley regional flow system, in Nevada and California. A calibrated groundwater-flow model was used to simulate potential future effects of groundwater pumping on water levels and natural groundwater discharge in the study area. Effects of climate change on future groundwater pumping were not considered and were beyond the scope of the study. Four groundwater-pumping scenarios were developed by stakeholders to predict and compare (1) the extent of regional water-level declines; (2) drawdown at Devils Hole; and (3) reductions in natural discharge at select discharge areas, including the Amargosa Wild and Scenic River, the Ash Meadows discharge area, the Furnace Creek area, and Stump Spring. Scenarios were simulated from 1913 to 2120, with historical pumping occurring from 1913 to 2010, historical 2010 pumping rates projected from 2010 to 2020, and scenario pumping beginning in 2020. Pumping scenarios included a base case and scenarios A, B, and C. The base case projected 2010 pumping rates from 2010 to 2120, and scenarios A, B, and C projected base case pumping plus additional pumping at various locations from 2020 to 2120. By 2020, historical (1913–2020) pumping resulted in the propagation of simulated drawdown of 1 foot (ft) or more westward from Pahrump Valley to areas north of Shoshone in the Pahrump to Death Valley South (PDVS) groundwater basin and the merging of simulated 1-ft drawdown contours between the Alkali Flat–Furnace Creek Ranch (AFFCR) and Ash Meadows groundwater basins. In the base case scenario, extent and magnitude of simulated drawdown continued to increase in the Ash Meadows and AFFCR groundwater basins from 2020 to 2120. In the base case, the magnitude of simulated drawdown continued to increase in western Pahrump Valley from 2020 to 2120, whereas simulated water levels rose in eastern Pahrump Valley from 2020 to 2070 and then stabilized from 2070 to 2120. Scenarios A and B primarily affected the PDVS and AFFCR groundwater basins by increasing the magnitude of drawdown in 2120, compared to the base case. In scenario C, drawdown propagated throughout a high-transmissivity part of the carbonate aquifer known as the megachannel, greatly affecting water levels in the Ash Meadows discharge area. Scenario C resulted in an additional 10–100 ft of drawdown (compared to the base case) throughout the southeastern part of the Ash Meadows groundwater basin by 2120. Simulated drawdowns in Devils Hole in 2120 were 3.2, 3.4, 3.8, and 25.4 ft for the base case and scenarios A, B, and C, respectively. The federally mandated minimum water level for Devils Hole is 2.7 ft below a reference point. In 2020, the simulated water level in Devils Hole was above the minimum water level, at 1.7 ft below the reference. Simulated water levels in Devils Hole fell below the federally mandated water level by 2078, 2073, 2058, and 2025 for the base case and scenarios A, B, and C, respectively, assuming a hypothetical recharge scenario of constant natural recharge. Simulated reductions in predevelopment (natural) discharge at select discharge areas ranged from 3 to 38 percent by 2120 for all scenarios. Amargosa Wild and Scenic River was the least affected discharge area with simulated capture rates ranging from 3 to 4 percent of predevelopment discharge by 2120. Ash Meadows discharge area was greatly affected by groundwater pumping in scenario C with a simulated capture rate of 38 percent, compared to simulated capture rates of 8, 8, and 9 percent for the base case, scenario A, and scenario B, respectively, in 2120. Simulated capture rates in the Furnace Creek area ranged from 10 to 11 percent for all scenarios in 2120. Simulated capture rates at Stump Spring ranged from 32 to 36 percent for all scenarios in 2120.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205103","collaboration":"Prepared in cooperation with the Bureau of Land Management; National Park Service; Nevada Division of Wildlife; Nye County, Nevada; and U.S. Fish and Wildlife Service","usgsCitation":"Nelson, N.C., and Jackson, T.R., 2020, Simulated effects of pumping in the Death Valley Regional Groundwater Flow System, Nevada and California—Selected management scenarios projected to 2120: U.S. Geological Survey Scientific Investigations Report 2020–5103, 30 p., https://doi.org/10.3133/sir20205103.","productDescription":"Report: vii, 30 p.; Data Releases","onlineOnly":"Y","ipdsId":"IP-112177","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":379438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5103/coverthb.jpg"},{"id":379439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5103/sir20205103.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5103"},{"id":379440,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OBUPXU","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-2005 models used to simulate effects of pumping in the Death Valley Regional Groundwater Flow System, Nevada and California—Selected management scenarios projected to 2120"},{"id":379476,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75H7FH3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Update to the groundwater withdrawals database for the Death Valley regional groundwater flow system, Nevada and California, 1913 -2010"},{"id":379477,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HIYVG2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-2005 model and supplementary data used to characterize groundwater flow and effects of pumping in the Death Valley regional groundwater flow system, Nevada and California, with special reference to Devils Hole"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley Regional Groundwater Flow System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3779296875,\n 33.62376800118811\n ],\n [\n -114.08203125,\n 33.62376800118811\n ],\n [\n -114.08203125,\n 38.62545397209084\n ],\n [\n -117.3779296875,\n 38.62545397209084\n ],\n [\n -117.3779296875,\n 33.62376800118811\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
The complete mitogenome of the northern long-eared bat (Myotis septentrionalis) was determined to be 17,362 bp and contained 22 tRNA genes, 2 rRNA genes and one control region. The whole genome base composition was 33.8% GC. Phylogenetic analysis suggests that M. septentrionalis be positioned next to M. auriculus in the Nearctic subclade of the Myotis genus. This complete mitochondrial genome provides essential molecular markers for resolving phylogeny and future conservation efforts.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23802359.2020.1830726","usgsCitation":"Gaughan, S.J., Pope, K.L., White, J.A., Lemen, C.A., and Freeman, P.W., 2020, Mitogenome of northern long-eared bat: Mitochondrial DNA Part B, v. 5, no. 3, p. 3592-3593, https://doi.org/10.1080/23802359.2020.1830726.","productDescription":"2 p.","startPage":"3592","endPage":"3593","ipdsId":"IP-115702","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":454996,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/23802359.2020.1830726","text":"Publisher Index Page"},{"id":395783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gaughan, S. J.","contributorId":275637,"corporation":false,"usgs":false,"family":"Gaughan","given":"S.","email":"","middleInitial":"J.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":834186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, J. A.","contributorId":275639,"corporation":false,"usgs":false,"family":"White","given":"J.","email":"","middleInitial":"A.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lemen, C. A.","contributorId":275640,"corporation":false,"usgs":false,"family":"Lemen","given":"C.","email":"","middleInitial":"A.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":834188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, P. W.","contributorId":275642,"corporation":false,"usgs":false,"family":"Freeman","given":"P.","email":"","middleInitial":"W.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":834189,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216947,"text":"70216947 - 2020 - Advancements towards selective barrier passage by automatic species identification: Applications of deep convolutional neural networks on images of dewatered fish","interactions":[],"lastModifiedDate":"2021-01-25T16:51:53.379463","indexId":"70216947","displayToPublicDate":"2020-10-21T10:47:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Advancements towards selective barrier passage by automatic species identification: Applications of deep convolutional neural networks on images of dewatered fish","docAbstract":"Invasive species negatively affect enterprises such as fisheries, agriculture, and international trade. In the Laurentian Great Lakes Basin, threats include invasive sea lamprey (Petromyzon marinus) and the four major Chinese carps. Barriers have proven to be an effective mechanism for managing invasive species but are detrimental in that they also limit the migration of desirable, native species. Fish passage technologies that selectively pass desirable species while blocking undesirable species are needed. Key to an automated selective barrier passage system is a high precision fish classifier to assign fish to be passed or blocked. Presented is an evaluation of two classifiers developed using images of partially dewatered fish captured from a commercial, high-speed camera array. For a lamprey vs. non-lamprey classification task, an ensemble prediction approach achieved near perfect accuracy on both a validation and test dataset. For a species classification task for 13 species found in the Great Lakes region, an ensemble prediction approach achieved accuracies of 96% and 97% on a validation and test dataset, respectively. Both prediction approaches were based on deep convolutional neural networks constructed using transfer learning and image augmentation. The study provides an important proof-of-concept for the viability in fully automated, selective fish passage systems.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/icesjms/fsaa150","usgsCitation":"Eickholt, J., Kelly, D., Bryan, J., Miehls, S.M., and Zielinski, D., 2020, Advancements towards selective barrier passage by automatic species identification: Applications of deep convolutional neural networks on images of dewatered fish: ICES Journal of Marine Science, v. 77, no. 7-8, p. 2804-2813, https://doi.org/10.1093/icesjms/fsaa150.","productDescription":"10 p.","startPage":"2804","endPage":"2813","ipdsId":"IP-114452","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":454998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsaa150","text":"Publisher Index Page"},{"id":382555,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Michigan,Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.59374999999999,\n 40.68063802521456\n ],\n [\n -82.1337890625,\n 40.68063802521456\n ],\n [\n -82.1337890625,\n 46.5286346952717\n ],\n [\n -88.59374999999999,\n 46.5286346952717\n ],\n [\n -88.59374999999999,\n 40.68063802521456\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2020-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Eickholt, Jesse","contributorId":245809,"corporation":false,"usgs":false,"family":"Eickholt","given":"Jesse","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":807048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelly, Dylan","contributorId":245810,"corporation":false,"usgs":false,"family":"Kelly","given":"Dylan","email":"","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":807049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryan, Janine","contributorId":245811,"corporation":false,"usgs":false,"family":"Bryan","given":"Janine","email":"","affiliations":[{"id":49332,"text":"Whooshh Innovations","active":true,"usgs":false}],"preferred":false,"id":807050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":807051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zielinski, Daniel","contributorId":245812,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":807052,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215538,"text":"70215538 - 2020 - Land subsidence contributions to relative sea level rise at tide gauge Galveston Pier 21, Texas","interactions":[],"lastModifiedDate":"2020-11-10T19:06:57.624092","indexId":"70215538","displayToPublicDate":"2020-10-21T09:43:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Land subsidence contributions to relative sea level rise at tide gauge Galveston Pier 21, Texas","docAbstract":"Relative sea level rise at tide gauge Galveston Pier 21, Texas, is the combination of absolute sea level rise and land subsidence. We estimate subsidence rates of 3.53 mm/a during 1909–1937, 6.08 mm/a during 1937–1983, and 3.51 mm/a since 1983. Subsidence attributed to aquifer-system compaction accompanying groundwater extraction contributed as much as 85% of the 0.7 m relative sea level rise since 1909, and an additional 1.9 m is projected by 2100, with contributions from land subsidence declining from 30 to 10% over the projection interval. We estimate a uniform absolute sea level rise rate of 1.10 mm ± 0.19/a in the Gulf of Mexico during 1909–1992 and its acceleration of 0.270 mm/a2 at Galveston Pier 21 since 1992. This acceleration is 87% of the value for the highest scenario of global mean sea level rise. Results indicate that evaluating this extreme scenario would be valid for resource-management and flood-hazard-mitigation strategies for coastal communities in the Gulf of Mexico, especially those affected by subsidence.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-020-74696-4","usgsCitation":"Liu, Y., Li, J., Fasullo, J., and Galloway, D., 2020, Land subsidence contributions to relative sea level rise at tide gauge Galveston Pier 21, Texas: Scientific Reports, v. 10, 17905, 11 p., https://doi.org/10.1038/s41598-020-74696-4.","productDescription":"17905, 11 p.","ipdsId":"IP-116040","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":455000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-74696-4","text":"Publisher Index Page"},{"id":379653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","city":"Galveston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.90951538085938,\n 29.235481227452947\n ],\n [\n -94.72206115722656,\n 29.235481227452947\n ],\n [\n -94.72206115722656,\n 29.367215978710348\n ],\n [\n -94.90951538085938,\n 29.367215978710348\n ],\n [\n -94.90951538085938,\n 29.235481227452947\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Yi","contributorId":244757,"corporation":false,"usgs":false,"family":"Liu","given":"Yi","affiliations":[],"preferred":false,"id":804523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Jiang","contributorId":167428,"corporation":false,"usgs":false,"family":"Li","given":"Jiang","email":"","affiliations":[],"preferred":false,"id":802619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fasullo, John","contributorId":243581,"corporation":false,"usgs":false,"family":"Fasullo","given":"John","email":"","affiliations":[{"id":48738,"text":"National Center for Atmospheric Research, Climate and Global Dynamics Lab, Boulder, CO 80305","active":true,"usgs":false}],"preferred":false,"id":802620,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galloway, Devin 0000-0003-0904-5355","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":215888,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802621,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215548,"text":"70215548 - 2020 - Simulated estuary-wide response of seagrass (Zostera marina) to future scenarios of temperature and sea level","interactions":[],"lastModifiedDate":"2020-10-22T14:19:07.016285","indexId":"70215548","displayToPublicDate":"2020-10-21T09:10:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Simulated estuary-wide response of seagrass (Zostera marina) to future scenarios of temperature and sea level","docAbstract":"Seagrass communities are a vital component of estuarine ecosystems, but are threatened by projected sea level rise (SLR) and temperature increases with climate change. To understand these potential effects, we developed a spatially explicit model that represents seagrass (Zostera marina) habitat and estuary-wide productivity for Barnegat Bay-Little Egg Harbor (BB-LEH) in New Jersey, United States. Our modeling approach included an offline coupling of a numerical seagrass biomass model with the spatially variable environmental conditions from a hydrodynamic model to calculate above and belowground biomass at each grid cell of the hydrodynamic model domain. Once calibrated to represent present day seagrass habitat and estuary-wide annual productivity, we applied combinations of increasing air temperature and sea level following regionally specific climate change projections, enabling analysis of the individual and combined impacts of these variables on seagrass biomass and spatial coverage. Under the SLR scenarios, the current model domain boundaries were maintained, as the land surrounding BB-LEH is unlikely to shift significantly in the future. SLR caused habitat extent to decrease dramatically, pushing seagrass beds toward the coastline with increasing depth, with a 100% loss of habitat by the maximum SLR scenario. The dramatic loss of seagrass habitat under SLR was in part due to the assumption that surrounding land would not be inundated, as the model did not allow for habitat expansion outside the current boundaries of the bay. Temperature increases slightly elevated the rate of summer die-off and decreased habitat area only under the highest temperature increase scenarios. In combined scenarios, the effects of SLR far outweighed the effects of temperature increase. Sensitivity analysis of the model revealed the greatest sensitivity to changes in parameters affecting light limitation and seagrass mortality, but no sensitivity to changes in nutrient limitation constants. The high vulnerability of seagrass in the bay to SLR exceeded that demonstrated for other systems, highlighting the importance of site- and region-specific assessments of estuaries under climate change.
Biological assemblages are commonly used for assessing stream health, but there is increased interest among the freshwater research community in incorporating measures of stream function, such as metabolism, to strengthen stream-health assessments. Presently, there is limited information about the relationships between stream metabolism and biological assemblages, along with the measurement period required to relate metabolism with stream biota. Our study assessed which environmental factors explained stream metabolism and to what degree stream metabolism and minimum dissolved oxygen (DOmin) were related to invertebrate and fish metrics in streams distributed across several regions of the United States. Furthermore, we evaluated the number of metabolism monitoring days required for maximizing the ability to detect relationships between stream metabolism and biological assemblage metrics. We sampled 17 sites distributed among reference, agricultural, and urban areas for stream metabolism, nutrients, habitat, and biological assemblages (invertebrates and fishes). Overall, sites were heterotrophic with gross primary production (GPP) and ecosystem respiration (ER) related primarily to days since last high flow, canopy cover, maximum water temperature, and total phosphorus. DOmin was related to days since last high flow, canopy cover, and maximum water temperature. We were unable to determine a clear statistical relationship between invertebrate metrics (invertebrate richness; Ephemeroptera, Plecoptera, and Trichoptera richness; and scraper-taxa richness) and GPP, ER, or DOmin. In contrast, we found that 2 fish-assemblage metrics were associated with stream metabolism and DOmin. A fish multimetric index (FMMI) was negatively correlated with GPP (r = −0.5, p = 0.048) and positively correlated with DOmin (r = 0.47, p = 0.06). Percentage of omnivorous fish taxa was positively correlated with GPP (r = 0.72, p = 0.001) and ER (r = 0.55, p = 0.02) and negatively correlated with DOmin (r = −0.67, p = 0.003). The lack of detected relationships for most of the biological-assemblage metrics with stream metabolism may be partially due to 1 or more factors, including high variability, low sample size, limited range in metabolism values, assemblage metrics used, and geographic distribution of sites. Comparing stream-metabolism measurement periods (in days) to biological-assemblage metrics indicated that optimum correlations occurred at 2 d for DOmin, 3 d for GPP, and 14 d for ER. Although our study found limited relationships of stream metabolism and DOmin with biological assemblages, future studies should consider a larger sample size (≥30), 14-d or longer metabolism measurement period, and assessment of other taxa-specific or assemblage metrics.
Avian haemosporidian parasites are a closely related group of apicomplexan parasites with important similarities in their life cycles, development, physiology, and reproduction. Current phylogenies based on mitochondrial and nuclear genes reflect more traditional attempts to classify these organisms based on life history characteristics and morphology, but limited sampling from poorly characterized taxa such as the Garniidae from tropical and subtropical regions continues to limit our understanding of their phylogeny and evolution. Recent advances in molecular diagnostics and the ability to barcode these parasites using mitochondrial cytochrome b sequences have revolutionized the field, but traditional methodology based on microscopy of Giemsa-stained blood smears remains essential for diagnostics and understanding life history characteristics and biodiversity of these organisms. The relative strengths and weaknesses of current methods in wildlife haemosporidian research are discussed. We call for a combination of microscopic, PCR-based, and serological diagnostic methodologies for better estimates of true distribution and other aspects of biology of haemosporidians, particularly in studies on virulence, prevalence, and biodiversity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Avian Malaria and Related Parasites in the Tropics","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-51633-8","usgsCitation":"Valkiunas, G., and Atkinson, C.T., 2020, Introduction to life cycles, taxonomy, distribution and basic research techniques, chap. of Avian Malaria and Related Parasites in the Tropics, p. 45-80, https://doi.org/10.1007/978-3-030-51633-8.","productDescription":"36 p.","startPage":"45","endPage":"80","ipdsId":"IP-109471","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":383823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Valkiunas, Gediminas","contributorId":205399,"corporation":false,"usgs":false,"family":"Valkiunas","given":"Gediminas","email":"","affiliations":[{"id":37095,"text":"Nature Research Centre,Vilnius, Lithuania","active":true,"usgs":false}],"preferred":false,"id":811315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":811316,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215759,"text":"70215759 - 2020 - An interactive data visualization framework for exploring geospatial environmental datasets and model predictions","interactions":[],"lastModifiedDate":"2020-10-29T13:11:24.16641","indexId":"70215759","displayToPublicDate":"2020-10-20T08:03:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"An interactive data visualization framework for exploring geospatial environmental datasets and model predictions","docAbstract":"Margaritifera monodonta, or the Spectaclecase Mussel, is a federally endangered freshwater mussel species that has experienced a 55% reduction in range and is currently concentrated in 3 rivers in the Midwest region of the United States (Gasconade and Meramec rivers, Missouri, and St Croix River, Wisconsin). The detection of new populations by traditional survey methods has been limited because these mussels tend to occur under large rocks and boulders. Environmental DNA (eDNA) technology has been used to detect invasive and rare species, but its use for detection of rare, benthic-dwelling species in large flowing systems has been limited. Here, we propose using eDNA to assess known populations of M. monodonta. We designed a M. monodonta-specific quantitative polymerase chain reaction (qPCR) assay and tested it using water samples from multiple M. monodonta housing tanks, water samples from 2 known mussel beds on the St Croix River, and water samples from 3 known mussel beds on the Mississippi River. We observed higher overall eDNA detection rates on the St Croix River (30.2%) compared to the upper Mississippi River (0.60%). We also observed higher eDNA detection rates (73.3–93.1%) in 2018 for samples collected during the larval release period in May compared to samples collected in August after the reproductive period had ended (55.6–70.8%) on the St Croix River. We tested samples collected at 3 distances downstream from the 2 mussel beds found in the St Croix River, but we did not observe a substantial effect of distance on our detection rates. However, we did observe greater detection rates for samples collected near the bottom compared to at the surface. Our results indicate that this novel qPCR assay can successfully detect M. monodonta eDNA and could be used to rapidly screen locations to guide intensive physical searches for populations in riverine systems.
","language":"English","publisher":"The University of Chicago Press-Society for Freshwater Science","doi":"10.1086/711673","usgsCitation":"Lor, Y., Schreier, T.M., Waller, D.L., and Merkes, C.M., 2020, Using environmental DNA (eDNA) to detect the endangered Spectaclecase Mussel (Margaritifera monodonta): Freshwater Science, v. 39, no. 4, p. 837-847, https://doi.org/10.1086/711673.","productDescription":"11 p.","startPage":"837","endPage":"847","ipdsId":"IP-111712","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":455012,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/711673","text":"Publisher Index Page"},{"id":436750,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F0COLN","text":"USGS data release","linkHelpText":"Transformation methods for glochidia of the Spectaclecase mussel Cumberlandia monodonta: Data"},{"id":381160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin, Missouri","otherGeospatial":"Gasconade River, Meramec River, St. Croix River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.6534423828125,\n 38.68122173079789\n ],\n [\n -92.021484375,\n 38.33734763569314\n ],\n [\n -92.098388671875,\n 37.87051721701939\n ],\n [\n -91.9281005859375,\n 37.88352498087131\n ],\n [\n -91.505126953125,\n 38.61687046392973\n ],\n [\n -91.6534423828125,\n 38.68122173079789\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.4669189453125,\n 38.56212645363985\n ],\n [\n -90.63514709472656,\n 38.54923944473397\n ],\n [\n -90.74569702148436,\n 38.487994609214795\n ],\n [\n -90.73127746582031,\n 38.44014444555175\n ],\n [\n -90.61454772949219,\n 38.44821130413263\n ],\n [\n -90.46005249023438,\n 38.52775596312173\n ],\n [\n -90.4669189453125,\n 38.56212645363985\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.054443359375,\n 46.28622391806706\n ],\n [\n -92.98828125,\n 45.82879925192134\n ],\n [\n -92.8564453125,\n 45.251688256117646\n ],\n [\n -92.867431640625,\n 44.5435052132082\n ],\n [\n -92.28515625,\n 44.42593442145313\n ],\n [\n -92.054443359375,\n 46.28622391806706\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lor, Yer 0000-0002-5738-2412","orcid":"https://orcid.org/0000-0002-5738-2412","contributorId":210011,"corporation":false,"usgs":true,"family":"Lor","given":"Yer","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":806610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":806611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":806612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merkes, Christopher M. 0000-0001-8191-627X cmerkes@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-627X","contributorId":139516,"corporation":false,"usgs":true,"family":"Merkes","given":"Christopher","email":"cmerkes@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":806613,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216551,"text":"70216551 - 2020 - Warming of alpine tundra enhances belowground production and shifts community towards resource acquisition traits","interactions":[],"lastModifiedDate":"2020-11-25T17:18:23.314417","indexId":"70216551","displayToPublicDate":"2020-10-20T07:33:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Warming of alpine tundra enhances belowground production and shifts community towards resource acquisition traits","docAbstract":"Climate warming is expected to stimulate plant growth in high‐elevation and high‐latitude ecosystems, significantly increasing aboveground net primary production (ANPP). However, the effects of simultaneous changes in temperature, snowmelt timing, and summer water availability on total net primary production (NPP)—and elucidation of both above‐ and belowground responses—remain an important area in need of further study. In particular, measures of belowground net primary productivity (BNPP) are required to understand whether ANPP changes reflect changes in allocation or are indicative of a whole plant NPP response. Further, plant functional traits provide a key way to scale from the individual plant to the community level and provide insight into drivers of NPP responses to environmental change. We used infrared heaters to warm an alpine plant community at Niwot Ridge, Colorado, and applied supplemental water to compensate for soil water loss induced by warming. We measured ANPP, BNPP, and leaf and root functional traits across treatments after 5 yr of continuous warming. Community‐level ANPP and total NPP (ANPP + BNPP) did not respond to heating or watering, but BNPP increased in response to heating. Heating decreased community‐level leaf dry matter content and increased total root length, indicating a shift in strategy from resource conservation to acquisition in response to warming. Water use efficiency (WUE) decreased with heating, suggesting alleviation of moisture constraints that may have enabled the plant community to increase productivity. Heating may have decreased WUE by melting snow earlier and creating more days early in the growing season with adequate soil moisture, but stimulated dry mass investment in roots as soils dried down later in the growing season. Overall, this study highlights how ANPP and BNPP responses to climate change can diverge, and encourages a closer examination of belowground processes, especially in alpine systems, where the majority of NPP occurs belowground.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3270","usgsCitation":"Yang, Y., Klein, J.A., Winkler, D.E., Peng, A., Lazarus, B., Germino, M., Suding, K., Smith, J., and Kueppers, L.M., 2020, Warming of alpine tundra enhances belowground production and shifts community towards resource acquisition traits: Ecosphere, v. 11, no. 10, e03270, 15 p., https://doi.org/10.1002/ecs2.3270.","productDescription":"e03270, 15 p.","ipdsId":"IP-114058","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3270","text":"Publisher Index Page"},{"id":380791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Niwot Ridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.62324523925781,\n 40.04732864506094\n ],\n [\n -105.56548118591309,\n 40.04732864506094\n ],\n [\n -105.56548118591309,\n 40.07189770843059\n ],\n [\n -105.62324523925781,\n 40.07189770843059\n ],\n [\n -105.62324523925781,\n 40.04732864506094\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Yang, Yan","contributorId":245243,"corporation":false,"usgs":false,"family":"Yang","given":"Yan","affiliations":[],"preferred":false,"id":805674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klein, Julia A.","contributorId":76873,"corporation":false,"usgs":true,"family":"Klein","given":"Julia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":805675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peng, Ahui","contributorId":245244,"corporation":false,"usgs":false,"family":"Peng","given":"Ahui","email":"","affiliations":[],"preferred":false,"id":805676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lazarus, Brynne E. 0000-0002-6352-486X","orcid":"https://orcid.org/0000-0002-6352-486X","contributorId":242732,"corporation":false,"usgs":true,"family":"Lazarus","given":"Brynne E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":805591,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":805592,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Suding, Katherine","contributorId":167086,"corporation":false,"usgs":false,"family":"Suding","given":"Katherine","email":"","affiliations":[{"id":6709,"text":"University of Colorado, Denver","active":true,"usgs":false}],"preferred":false,"id":805677,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smith, Jane G.","contributorId":245245,"corporation":false,"usgs":false,"family":"Smith","given":"Jane G.","affiliations":[],"preferred":false,"id":805678,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kueppers, Lara M.","contributorId":89778,"corporation":false,"usgs":false,"family":"Kueppers","given":"Lara","email":"","middleInitial":"M.","affiliations":[{"id":6670,"text":"Lawrence Berkeley National Laboratory, Berkeley, CA","active":true,"usgs":false},{"id":16805,"text":"University of California, Merced","active":true,"usgs":false}],"preferred":false,"id":805679,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70215717,"text":"70215717 - 2020 - Modeling false positives","interactions":[],"lastModifiedDate":"2020-10-29T11:45:30.1053","indexId":"70215717","displayToPublicDate":"2020-10-19T08:48:46","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Modeling false positives","docAbstract":"Many of the models we are concerned with included explicit descriptions of false negative errors. However, false positive errors can also be commin in practice, especially in citizen science applications where observer skill is highly variable. In addition, new methods which determine detection based on statistical classification or machine learning methods are also prone to false positive errors which must be accounted for. \n An early treatment of the false positive detection problem by Royle & Link (2006) recognized that false positive errors can be accommodated by a mixture model for detection probability: one value of detection at occupied sites and another non-zero value at unoccupied sites. This model has been extended greatly in recent years to include more informative data about false positives including validation or confirmation data (Miller et al. 2011) and multiple detection methods, among others. \n A new frontier for the application of false positives models lies in the use of modern technologies such as bioacoustics for efficient automated monitoring. For these technologies to realize their promise there must be improvements in automated processing of the vast quantities of output produced. Statistical classification methods (machine learning) are fallible and necessarily produce false positive detections. Therefore models which account for this process are necessary (Chambert et al. 2017). It stands to reason that false positives will need to be accounted for in other new technologies that rely on automated digital processing, including eDNA, genetic barcoding, and automated detection in remote camera studies.\n We devise a new occupancy model that integrates data from bioacoustics sampling with an occupancy model. This integrated model allows occupancy probability to inform species classification of samples and vice versa bioacoustics detection data inform occupancy. We provide a proof of concept for this new model in this chapter. \n As the core hierarchical model for the false positives models covered in this chapter are just ordinary occupancy models, extension of the ideas to open systems poses no technical challenges. We provide a suite of illustrations of these extensions. \n Perhaps the most prominent mechanism that leads to false positive errors it he mis-classification of species detections, or the confusion of one species for another. Very little work has been done on developing models based on this mechanistic understanding although Chambert et al. (2018) develop this idea as a 2-species occupancy model with error. We believe one important area of future research is to extend these ideas to truly multi-species systems.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","usgsCitation":"Kery, M., and Royle, A., 2020, Modeling false positives, chap. 7 of Applied hierarchical modeling in ecology: Analysis of distribution, abundance and species richness in R and BUGS, v. 2, p. 401-454.","productDescription":"54 p.","startPage":"401","endPage":"454","ipdsId":"IP-104271","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":379868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379846,"type":{"id":15,"text":"Index Page"},"url":"https://www.elsevier.com/books/applied-hierarchical-modeling-in-ecology-analysis-of-distribution-abundance-and-species-richness-in-r-and-bugs/kery/978-0-12-809585-0"}],"volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kery, Marc","contributorId":168361,"corporation":false,"usgs":false,"family":"Kery","given":"Marc","affiliations":[{"id":12551,"text":"Swiss Ornithological Institute, Sempach, Switzerland","active":true,"usgs":false}],"preferred":false,"id":803278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":803191,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216466,"text":"70216466 - 2020 - Diurnal timing of nonmigratory movement by birds: The importance of foraging spatial scales","interactions":[],"lastModifiedDate":"2020-12-29T21:55:39.324174","indexId":"70216466","displayToPublicDate":"2020-10-19T08:27:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Diurnal timing of nonmigratory movement by birds: The importance of foraging spatial scales","docAbstract":"Timing of activity can reveal an organism's efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non‐migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad‐scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.02612","usgsCitation":"Mallon, J.M., Tucker, M.A., Beard, A., Bierregaard, R.O., Bildstein, K.L., Böhning-Gaese, K., Brzorad, J.N., Buechley, E., Bustamante, J., Carrapato, C., Castillo-Guerrero, J.A., Clingham, E., Desholm, M., DeSorbo, C.R., Domenech, R., Douglas, H., Duriez, O., Enggist, P., Farwig, N., Fiedler, W., Gagliardo, A., García‐Ripollés, C., Gil Gallus, J.A., Gilmour, M., Harel, R., Harrison, A., Henry, L., Katzner, T., Kays, R., Kleyheeg, E., Limiñana, R., Lopez-Lopez, P., Lucia, G., Maccarone, A., Mallia, E., Mellone, U., Mojica, E., Nathan, R., Newman, S., Oppel, S., Orchan, Y., Prosser, D.J., Riley, H., Rösner, S., Schabo, D.G., Schulz, H., Shaffer, S.A., Shreading, A., Silva, J., Sim, J., Skov, H., Spiegel, O., Stuber, M.J., Takekawa, J.Y., Urios, V., Vidal-Mateo, J., Warner, K., Watts, B.D., Weber, N., Weber, S., Wikelski, M., Zydelis, R., Mueller, T., and Fagan, W., 2020, Diurnal timing of nonmigratory movement by birds: The importance of foraging spatial scales: Journal of Avian Biology, v. 51, no. 12, e02612, 11 p., https://doi.org/10.1111/jav.02612.","productDescription":"e02612, 11 p.","ipdsId":"IP-115942","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":455018,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/jav.02612","text":"External Repository"},{"id":380648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Mallon, Julie M.","contributorId":150853,"corporation":false,"usgs":false,"family":"Mallon","given":"Julie","email":"","middleInitial":"M.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":805210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Marlee A.","contributorId":204648,"corporation":false,"usgs":false,"family":"Tucker","given":"Marlee","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":805211,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beard, Annalea","contributorId":245030,"corporation":false,"usgs":false,"family":"Beard","given":"Annalea","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":805212,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bierregaard, Richard O","contributorId":245032,"corporation":false,"usgs":false,"family":"Bierregaard","given":"Richard","email":"","middleInitial":"O","affiliations":[{"id":12436,"text":"University of North Carolina at Charlotte","active":true,"usgs":false}],"preferred":false,"id":805213,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":805214,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Böhning-Gaese, Katrin","contributorId":174361,"corporation":false,"usgs":false,"family":"Böhning-Gaese","given":"Katrin","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":805312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brzorad, John N.","contributorId":245085,"corporation":false,"usgs":false,"family":"Brzorad","given":"John","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":805313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Buechley, Evan R.","contributorId":245086,"corporation":false,"usgs":false,"family":"Buechley","given":"Evan R.","affiliations":[],"preferred":false,"id":805314,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bustamante, Javier","contributorId":245087,"corporation":false,"usgs":false,"family":"Bustamante","given":"Javier","email":"","affiliations":[],"preferred":false,"id":805315,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Carrapato, Carlos","contributorId":245088,"corporation":false,"usgs":false,"family":"Carrapato","given":"Carlos","email":"","affiliations":[],"preferred":false,"id":805316,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Castillo-Guerrero, Jose Alfredo","contributorId":245089,"corporation":false,"usgs":false,"family":"Castillo-Guerrero","given":"Jose","email":"","middleInitial":"Alfredo","affiliations":[],"preferred":false,"id":805317,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Clingham, Elizabeth","contributorId":245090,"corporation":false,"usgs":false,"family":"Clingham","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":805318,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Desholm, Mark","contributorId":245091,"corporation":false,"usgs":false,"family":"Desholm","given":"Mark","email":"","affiliations":[],"preferred":false,"id":805319,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"DeSorbo, Christopher R.","contributorId":127667,"corporation":false,"usgs":false,"family":"DeSorbo","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":805320,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Domenech, Robert","contributorId":199743,"corporation":false,"usgs":false,"family":"Domenech","given":"Robert","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":805321,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Douglas, Hayley","contributorId":245092,"corporation":false,"usgs":false,"family":"Douglas","given":"Hayley","email":"","affiliations":[],"preferred":false,"id":805322,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Duriez, Olivier","contributorId":245093,"corporation":false,"usgs":false,"family":"Duriez","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":805323,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Enggist, Peter","contributorId":245094,"corporation":false,"usgs":false,"family":"Enggist","given":"Peter","email":"","affiliations":[],"preferred":false,"id":805324,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Farwig, Nina","contributorId":245095,"corporation":false,"usgs":false,"family":"Farwig","given":"Nina","email":"","affiliations":[],"preferred":false,"id":805325,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Fiedler, Wolfgang","contributorId":205077,"corporation":false,"usgs":false,"family":"Fiedler","given":"Wolfgang","email":"","affiliations":[],"preferred":false,"id":805326,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Gagliardo, Anna","contributorId":245096,"corporation":false,"usgs":false,"family":"Gagliardo","given":"Anna","email":"","affiliations":[],"preferred":false,"id":805327,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"García‐Ripollés, Clara","contributorId":245097,"corporation":false,"usgs":false,"family":"García‐Ripollés","given":"Clara","affiliations":[],"preferred":false,"id":805328,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Gil Gallus, Jose Antonio","contributorId":245098,"corporation":false,"usgs":false,"family":"Gil Gallus","given":"Jose","email":"","middleInitial":"Antonio","affiliations":[],"preferred":false,"id":805329,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Gilmour, Morgan E.","contributorId":245099,"corporation":false,"usgs":false,"family":"Gilmour","given":"Morgan E.","affiliations":[],"preferred":false,"id":805330,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Harel, Roi","contributorId":245100,"corporation":false,"usgs":false,"family":"Harel","given":"Roi","email":"","affiliations":[],"preferred":false,"id":805331,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Harrison, Autumn-Lynn","contributorId":199253,"corporation":false,"usgs":false,"family":"Harrison","given":"Autumn-Lynn","email":"","affiliations":[{"id":17600,"text":"Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC","active":true,"usgs":false}],"preferred":false,"id":805332,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Henry, Leeann","contributorId":245101,"corporation":false,"usgs":false,"family":"Henry","given":"Leeann","affiliations":[],"preferred":false,"id":805333,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":805334,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Kays, Roland","contributorId":243449,"corporation":false,"usgs":false,"family":"Kays","given":"Roland","affiliations":[],"preferred":false,"id":805335,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Kleyheeg, Erik","contributorId":245102,"corporation":false,"usgs":false,"family":"Kleyheeg","given":"Erik","email":"","affiliations":[],"preferred":false,"id":805336,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Limiñana, Rubén","contributorId":245103,"corporation":false,"usgs":false,"family":"Limiñana","given":"Rubén","affiliations":[],"preferred":false,"id":805337,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Lopez-Lopez, Pascual","contributorId":205095,"corporation":false,"usgs":false,"family":"Lopez-Lopez","given":"Pascual","email":"","affiliations":[],"preferred":false,"id":805338,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Lucia, Giuseppe","contributorId":245105,"corporation":false,"usgs":false,"family":"Lucia","given":"Giuseppe","email":"","affiliations":[],"preferred":false,"id":805339,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Maccarone, Alan","contributorId":245106,"corporation":false,"usgs":false,"family":"Maccarone","given":"Alan","email":"","affiliations":[],"preferred":false,"id":805340,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Mallia, Egidio","contributorId":245107,"corporation":false,"usgs":false,"family":"Mallia","given":"Egidio","email":"","affiliations":[],"preferred":false,"id":805341,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Mellone, Ugo","contributorId":205099,"corporation":false,"usgs":false,"family":"Mellone","given":"Ugo","email":"","affiliations":[],"preferred":false,"id":805342,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Mojica, E.K.","contributorId":10513,"corporation":false,"usgs":true,"family":"Mojica","given":"E.K.","affiliations":[],"preferred":false,"id":805343,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Nathan, Ran","contributorId":205106,"corporation":false,"usgs":false,"family":"Nathan","given":"Ran","email":"","affiliations":[],"preferred":false,"id":805344,"contributorType":{"id":1,"text":"Authors"},"rank":38},{"text":"Newman, Scott H.","contributorId":245108,"corporation":false,"usgs":false,"family":"Newman","given":"Scott H.","affiliations":[],"preferred":false,"id":805345,"contributorType":{"id":1,"text":"Authors"},"rank":39},{"text":"Oppel, Steffen 0000-0002-8220-3789","orcid":"https://orcid.org/0000-0002-8220-3789","contributorId":216431,"corporation":false,"usgs":false,"family":"Oppel","given":"Steffen","email":"","affiliations":[],"preferred":false,"id":805346,"contributorType":{"id":1,"text":"Authors"},"rank":40},{"text":"Orchan, Yotam","contributorId":245109,"corporation":false,"usgs":false,"family":"Orchan","given":"Yotam","email":"","affiliations":[],"preferred":false,"id":805347,"contributorType":{"id":1,"text":"Authors"},"rank":41},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":805348,"contributorType":{"id":1,"text":"Authors"},"rank":42},{"text":"Riley, Hannah","contributorId":245110,"corporation":false,"usgs":false,"family":"Riley","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":805349,"contributorType":{"id":1,"text":"Authors"},"rank":43},{"text":"Rösner, Sascha","contributorId":245111,"corporation":false,"usgs":false,"family":"Rösner","given":"Sascha","affiliations":[],"preferred":false,"id":805350,"contributorType":{"id":1,"text":"Authors"},"rank":44},{"text":"Schabo, Dana G.","contributorId":245112,"corporation":false,"usgs":false,"family":"Schabo","given":"Dana","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":805351,"contributorType":{"id":1,"text":"Authors"},"rank":45},{"text":"Schulz, Holger","contributorId":245113,"corporation":false,"usgs":false,"family":"Schulz","given":"Holger","email":"","affiliations":[],"preferred":false,"id":805352,"contributorType":{"id":1,"text":"Authors"},"rank":46},{"text":"Shaffer, Scott A. 0000-0002-7751-5059","orcid":"https://orcid.org/0000-0002-7751-5059","contributorId":202761,"corporation":false,"usgs":false,"family":"Shaffer","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":805353,"contributorType":{"id":1,"text":"Authors"},"rank":47},{"text":"Shreading, Adam","contributorId":199745,"corporation":false,"usgs":false,"family":"Shreading","given":"Adam","email":"","affiliations":[{"id":35594,"text":"Raptor View Research Institute","active":true,"usgs":false}],"preferred":false,"id":805354,"contributorType":{"id":1,"text":"Authors"},"rank":48},{"text":"Silva, João Paulo","contributorId":245114,"corporation":false,"usgs":false,"family":"Silva","given":"João Paulo","affiliations":[],"preferred":false,"id":805355,"contributorType":{"id":1,"text":"Authors"},"rank":49},{"text":"Sim, Jolene","contributorId":245115,"corporation":false,"usgs":false,"family":"Sim","given":"Jolene","email":"","affiliations":[],"preferred":false,"id":805356,"contributorType":{"id":1,"text":"Authors"},"rank":50},{"text":"Skov, Henrik","contributorId":245116,"corporation":false,"usgs":false,"family":"Skov","given":"Henrik","email":"","affiliations":[],"preferred":false,"id":805357,"contributorType":{"id":1,"text":"Authors"},"rank":51},{"text":"Spiegel, Orr","contributorId":205125,"corporation":false,"usgs":false,"family":"Spiegel","given":"Orr","email":"","affiliations":[],"preferred":false,"id":805358,"contributorType":{"id":1,"text":"Authors"},"rank":52},{"text":"Stuber, Matthew J.","contributorId":213765,"corporation":false,"usgs":false,"family":"Stuber","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":805359,"contributorType":{"id":1,"text":"Authors"},"rank":53},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":196611,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":805360,"contributorType":{"id":1,"text":"Authors"},"rank":54},{"text":"Urios, Vicente","contributorId":220945,"corporation":false,"usgs":false,"family":"Urios","given":"Vicente","email":"","affiliations":[],"preferred":false,"id":805361,"contributorType":{"id":1,"text":"Authors"},"rank":55},{"text":"Vidal-Mateo, Javier","contributorId":245117,"corporation":false,"usgs":false,"family":"Vidal-Mateo","given":"Javier","email":"","affiliations":[],"preferred":false,"id":805362,"contributorType":{"id":1,"text":"Authors"},"rank":56},{"text":"Warner, Kevin","contributorId":245118,"corporation":false,"usgs":false,"family":"Warner","given":"Kevin","affiliations":[],"preferred":false,"id":805363,"contributorType":{"id":1,"text":"Authors"},"rank":57},{"text":"Watts, Bryan D.","contributorId":112075,"corporation":false,"usgs":true,"family":"Watts","given":"Bryan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":805364,"contributorType":{"id":1,"text":"Authors"},"rank":58},{"text":"Weber, Nicola","contributorId":245119,"corporation":false,"usgs":false,"family":"Weber","given":"Nicola","email":"","affiliations":[],"preferred":false,"id":805365,"contributorType":{"id":1,"text":"Authors"},"rank":59},{"text":"Weber, Sam","contributorId":245120,"corporation":false,"usgs":false,"family":"Weber","given":"Sam","email":"","affiliations":[],"preferred":false,"id":805366,"contributorType":{"id":1,"text":"Authors"},"rank":60},{"text":"Wikelski, Martin","contributorId":76451,"corporation":false,"usgs":true,"family":"Wikelski","given":"Martin","affiliations":[],"preferred":false,"id":805367,"contributorType":{"id":1,"text":"Authors"},"rank":61},{"text":"Zydelis, Ramunas","contributorId":203738,"corporation":false,"usgs":false,"family":"Zydelis","given":"Ramunas","email":"","affiliations":[{"id":35135,"text":"DHI, Hørsholm, Denmark","active":true,"usgs":false}],"preferred":false,"id":805368,"contributorType":{"id":1,"text":"Authors"},"rank":62},{"text":"Mueller, Thomas","contributorId":91393,"corporation":false,"usgs":true,"family":"Mueller","given":"Thomas","affiliations":[],"preferred":false,"id":805369,"contributorType":{"id":1,"text":"Authors"},"rank":63},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":805370,"contributorType":{"id":1,"text":"Authors"},"rank":64}]}} ,{"id":70215554,"text":"70215554 - 2020 - Modeling three-dimensional flow over spur-and-groove morphology","interactions":[],"lastModifiedDate":"2020-11-30T16:06:18.953016","indexId":"70215554","displayToPublicDate":"2020-10-19T08:24:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Modeling three-dimensional flow over spur-and-groove morphology","docAbstract":"Spur-and-groove (SAG) morphology characterizes the fore reef of many coral reefs worldwide. Although the existence and geometrical properties of SAG have been well documented, an understanding of the hydrodynamics over them is limited. Here, the three-dimensional flow patterns over SAG formations, and a sensitivity of those patterns to waves, currents, and SAG geometry were characterized using the physics-based Delft3D-FLOW and SWAN models. Shore-normal shoaling waves over SAG formations were shown to drive two circulation cells: a cell on the lower fore reef with offshore flow over the spurs and onshore flow over the grooves, except near the seabed where velocities were always onshore, and a cell on the upper fore reef with offshore surface velocities and onshore bottom currents, which result in depth-averaged onshore and offshore flow over the spurs and grooves, respectively. The mechanism driving this flow results from the net of the radiation stress gradients and pressure gradient, which is balanced by the Reynolds stress gradients and bottom friction that differ over the spur and over the groove. Waves were the primary driver of variations in modelled flow over SAG, with the flow strength increasing for increasing wave heights and periods. Spur height, SAG wavelength, and the water depth at peak spur height were the dominant influences on the hydrodynamics, with spur heights directly proportional to the strength of SAG circulation cells. SAG formations with shorter SAG wavelengths only presented one circulation cell on the shallower portion of the reef, as opposed to the two circulation cells for longer SAG wavelengths. SAG formations with peak spur heights occurring in shallower water had stronger circulation than those with peak spur heights occurring in deeper water. These hydrodynamic patterns also likely affect coral and reef development through sediment and nutrient fluxes.
Induced earthquakes from waste disposal operations in otherwise tectonically stable regions significantly increases seismic hazard. It remains unclear why injections induce large earthquakes on non‐optimally oriented faults kilometers below the injection horizon, particularly since fluids are not injected under pressure, but rather poured, into the well as observed in the Milan, Kansas area. Here we propose a mechanism for induced earthquakes whereby the karstic lower Arbuckle provides the short‐circuit that establishes a tens of MPa stepwise fluid pressure increase within the basement upon arrival of the hydraulic connection to the free surface and ultimately induce slip on the deeper fault. We investigate this scenario through modeling and mechanical analysis and show that earthquakes near Milan are likely induced by large (and sudden) fluid pressure changes when the karst network links two previously isolated hydrological systems.
Large-domain hydrological models are increasingly needed to support water-resource assessment and management in large river basins. Here, we describe results for the first Brazilian application of the SPAtially Referenced Regression On Watershed attributes (SPARROW) model using a new open-source modeling and interactive decision support system tool (RSPARROW) to quantify the origin, flux, and fate of total nitrogen (TN) in two sub-basins of the Grande River Basin (GRB; 43,000 km2). Land under cultivation for sugar cane, urban land, and point source inputs from wastewater treatment plants was estimated to each contribute approximately 30% of the TN load at the outlet, with pasture land contributing about 10% of the load. Hypothetical assessments of wastewater treatment plant upgrades and the building of new facilities that could treat currently untreated urban runoff suggest that these management actions could potentially reduce loading at the outlet by as much as 20–25%. This study highlights the ability of SPARROW and the RSPARROW mapping tool to assist with the development and evaluation of management actions aimed at reducing nutrient pollution and eutrophication. The freely available RSPARROW modeling tool provides new opportunities to improve understanding of the sources, delivery, and transport of water-quality contaminants in watersheds throughout the world.
","language":"English","publisher":"MDPI","doi":"10.3390/w12102911","usgsCitation":"Miller, M., de Souza, M.L., Alexander, R.B., Gorman Sanisaca, L.E., de Amorim Teixeira, A., and Appling, A.P., 2020, Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil: Water, v. 12, no. 10, 2911, 20 p., https://doi.org/10.3390/w12102911.","productDescription":"2911, 20 p.","ipdsId":"IP-122604","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":455023,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12102911","text":"Publisher Index Page"},{"id":436752,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FZV0Z0","text":"USGS data release","linkHelpText":"RSPARROW Model Archive Files for the Grande River Basin TN SPARROW Model"},{"id":379649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Grande River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -50.95458984374999,\n -20.324023603422507\n ],\n [\n -49.32861328125,\n -21.46329344189928\n ],\n [\n -48.284912109375,\n -22.451648819126202\n ],\n [\n -46.73583984375,\n -23.29181053244191\n ],\n [\n -45.37353515625,\n -22.61401087437028\n ],\n [\n -44.05517578124999,\n -21.881889807629257\n ],\n [\n -43.5498046875,\n -21.125497636606266\n ],\n [\n -45.736083984375,\n -20.33432561683554\n ],\n [\n -46.35131835937499,\n -20.478481600090554\n ],\n [\n -46.966552734375,\n -20.014645445341355\n ],\n [\n -47.647705078125,\n -19.797717490704724\n ],\n [\n -48.944091796875,\n -19.9526963975442\n ],\n [\n -49.32861328125,\n -19.652934210612436\n ],\n [\n -50.28442382812499,\n -19.425153718960143\n ],\n [\n -50.86669921875,\n -19.756364230752375\n ],\n [\n -50.95458984374999,\n -20.324023603422507\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":220622,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew P.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Souza, Marcelo L","contributorId":243598,"corporation":false,"usgs":false,"family":"de Souza","given":"Marcelo","email":"","middleInitial":"L","affiliations":[{"id":48748,"text":"Brazilian National Water and Sanitation Agency","active":true,"usgs":false}],"preferred":false,"id":802666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Richard B 0000-0001-9166-0626","orcid":"https://orcid.org/0000-0001-9166-0626","contributorId":243599,"corporation":false,"usgs":false,"family":"Alexander","given":"Richard","email":"","middleInitial":"B","affiliations":[{"id":38108,"text":"NA","active":true,"usgs":false}],"preferred":false,"id":802667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gorman Sanisaca, Lillian E. 0000-0003-1711-3864","orcid":"https://orcid.org/0000-0003-1711-3864","contributorId":210381,"corporation":false,"usgs":true,"family":"Gorman Sanisaca","given":"Lillian","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":802668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Amorim Teixeira, Alexandre","contributorId":243600,"corporation":false,"usgs":false,"family":"de Amorim Teixeira","given":"Alexandre","email":"","affiliations":[{"id":48748,"text":"Brazilian National Water and Sanitation Agency","active":true,"usgs":false}],"preferred":false,"id":802669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":802670,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227625,"text":"70227625 - 2020 - Estimating population-specific predation effects on Chinook salmon via data integration","interactions":[],"lastModifiedDate":"2022-01-21T14:54:34.2629","indexId":"70227625","displayToPublicDate":"2020-10-18T08:33:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating population-specific predation effects on Chinook salmon via data integration","docAbstract":"In 2015, about 84,600 million gallons per day (Mgal/d) of groundwater were withdrawn in the United States for various uses including public supply, self-supplied domestic, industrial, mining, thermoelectric power, aquaculture, livestock, and irrigation. Of this total, about 94 percent (79,200 Mgal/d) was withdrawn from principal aquifers, which are defined as regionally extensive aquifers or aquifer systems that have the potential to be used as sources of water of suitable quality and quantity to meet various needs. The remaining 6 percent (5,400 Mgal/d) was withdrawn from other, nonprincipal aquifers in the United States.
Sixty-six principal aquifers belonging to 5 major lithologic groups have been identified and delineated in the United States, including Puerto Rico and the U.S. Virgin Islands. Of the water withdrawn from principal aquifers in 2015, 81 percent (63,900 Mgal/d) was from the unconsolidated and semiconsolidated sand and gravel lithologic group, 7.1 percent (5,630 Mgal/d) was from the igneous and metamorphic-rock lithologic group, 6.8 percent (5,360 Mgal/d) was from the carbonate-rock lithologic group, 3.4 percent (2,680 Mgal/d) was from the sandstone lithologic group, and 2.2 percent (1,710 Mgal/d) was from the sandstone and carbonate-rock lithologic group.
The most heavily pumped of the 24 principal aquifers and aquifer systems within the unconsolidated and semiconsolidated sand and gravel lithologic group were the High Plains aquifer (12,300 Mgal/d), Mississippi River Valley alluvial aquifer (12,100 Mgal/d), Central Valley aquifer system (11,100 Mgal/d), and Basin and Range basin-fill aquifers (7,390 Mgal/d). Withdrawals for irrigation were 48,100 Mgal/d and accounted for 75 percent of the total withdrawals from this lithologic group. Although unconsolidated sand and gravel aquifers are widely distributed and were used as sources of water in all States except Hawaii and the U.S. Virgin Islands, 56 percent of the total withdrawn from unconsolidated and semiconsolidated sand and gravel aquifers was in just four States: California (15,600 Mgal/d), Arkansas (9,560 Mgal/d), Nebraska (5,570 Mgal/d), and Texas (4,830 Mgal/d).
The most heavily pumped of the seven principal aquifers within the igneous and metamorphic-rock lithologic group were the Snake River Plain (2,930 Mgal/d) and Columbia Plateau basaltic-rock aquifers (1,080 Mgal/d), which are located in the northwestern United States and together accounted for 71 percent of the water withdrawn from this lithologic group. Withdrawals for irrigation were 4,190 Mgal/d and accounted for more than 74 percent of the total withdrawals from this lithologic group. Seventy-eight percent of the withdrawals from igneous and metamorphic-rock aquifers were in three States: Idaho (3,230 Mgal/d), Washington (614 Mgal/d), and Oregon (528 Mgal/d).
The most heavily pumped of the 15 principal aquifers and aquifer systems within the carbonate-rock lithologic group were the Floridan aquifer system (3,180 Mgal/d) and the Biscayne aquifer (679 Mgal/d), which are in the southeastern United States and together accounted for almost 72 percent of the withdrawals from this lithologic group. Withdrawals for public supply (2,440 Mgal/d) and irrigation (1,610 Mgal/d) together accounted for almost 76 percent of the total withdrawals from this lithologic group. Although water was withdrawn from carbonate-rock aquifers in 35 States, 71 percent of the total withdrawn was in Florida (3,020 Mgal/d) and Georgia (785 Mgal/d).
The most heavily pumped of the 15 principal aquifers within the sandstone lithologic group was the Cambrian-Ordovician aquifer system (921 Mgal/d), which is in the north-central United States and accounted for 34 percent of the water withdrawn from this lithologic group. Withdrawals for public supply were 1,030 Mgal/d and accounted for 38 percent of the total withdrawals from this lithologic group. Although sandstone aquifers were used as sources of water in 32 States, 45 percent of the total withdrawn from sandstone aquifers was in five States: Minnesota (321 Mgal/d), Wisconsin (319 Mgal/d), Kansas (193 Mgal/d), Illinois (187 Mgal/d), and Pennsylvania (179 Mgal/d).
The most heavily pumped of the five principal aquifers and aquifer systems within the sandstone and carbonate-rock lithologic group were the Edwards-Trinity aquifer system (661 Mgal/d) in the south-central United States and the Valley and Ridge aquifers (551 Mgal/d) of the eastern United States, which together accounted for 71 percent of total withdrawals from this lithologic group. Withdrawals from sandstone and carbonate-rock aquifers for public-supply (713 Mgal/d), irrigation (469 Mgal/d), and self-supplied domestic (253 Mgal/d) uses accounted for about 84 percent of the total withdrawals from this lithologic group. Although water was withdrawn from sandstone and carbonate-rock aquifers in 25 States, 65 percent of the total withdrawn was in Texas (651 Mgal/d), Pennsylvania (238 Mgal/d), and Florida (223 Mgal/d).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1464","usgsCitation":"Lovelace, J.K., Nielsen, M.G., Read, A.L., Murphy, C.J., and Maupin, M.A., 2020, Estimated groundwater withdrawals from principal aquifers in the United States, 2015 (ver. 1.2, October 2020): U.S. Geological Survey Circular 1464, 70 p., https://doi.org/10.3133/cir1464.","productDescription":"Report: vii, 70 p.; Data Release","numberOfPages":"82","onlineOnly":"N","ipdsId":"IP-107784","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":374027,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1464/coverthb3.jpg"},{"id":375193,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1464/versionHist.txt","text":"Version History","description":"CIR 1464 Version History"},{"id":374028,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1464/circ1464.pdf","text":"Report","size":"23.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1464"},{"id":374029,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EI0KMR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Estimated groundwater withdrawals from principal aquifers in the United States—County-level data for 2015"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.67138671875,\n 54.686534234529695\n ],\n [\n -129.9462890625,\n 55.36662484928637\n ],\n [\n -130.1220703125,\n 56.145549500679074\n ],\n [\n -131.9677734375,\n 56.9449741808516\n ],\n [\n -135.3076171875,\n 59.833775202184206\n ],\n [\n -136.38427734375,\n 59.65664225341022\n ],\n [\n -136.6259765625,\n 59.23217626921806\n ],\n [\n -137.52685546875,\n 58.938673187948304\n ],\n [\n -137.65869140625,\n 59.33318942659219\n ],\n [\n -138.8232421875,\n 60.009970961180386\n ],\n [\n -139.21874999999997,\n 60.108670463036\n ],\n [\n -139.04296875,\n 60.403001945865476\n ],\n [\n -139.85595703125,\n 60.337823495982015\n ],\n [\n -140.99853515625,\n 60.337823495982015\n ],\n [\n -141.15234374999997,\n 69.71810669906763\n ],\n [\n -143.4375,\n 70.17020068549206\n ],\n [\n -145.1953125,\n 70.08056215839737\n ],\n [\n -149.765625,\n 70.58341752317065\n ],\n [\n -152.40234375,\n 70.61261423801925\n ],\n [\n -152.314453125,\n 70.95969716686398\n ],\n [\n -157.1484375,\n 71.35706654962706\n ],\n [\n -159.9609375,\n 70.8734913192635\n ],\n [\n -162.0703125,\n 70.31873847853124\n ],\n [\n -163.916015625,\n 69.06856318696033\n ],\n [\n -166.376953125,\n 68.942606818121\n ],\n [\n -166.376953125,\n 68.26938680456564\n ],\n [\n -163.30078125,\n 66.86108230224609\n ],\n [\n -161.982421875,\n 66.47820814385636\n ],\n [\n -163.564453125,\n 66.08936427047088\n ],\n [\n -163.564453125,\n 66.6181218846659\n ],\n [\n -165.76171875,\n 66.40795547978848\n ],\n [\n -168.0908203125,\n 65.69447579373418\n ],\n [\n -166.55273437499997,\n 65.14611484756372\n ],\n [\n -166.904296875,\n 65.05360170595502\n ],\n [\n -166.3330078125,\n 64.41592147626879\n ],\n [\n -162.861328125,\n 64.39693778132846\n ],\n [\n -160.927734375,\n 64.90491004905083\n ],\n [\n -161.0595703125,\n 64.47279382008166\n ],\n [\n -161.4990234375,\n 64.49172504435471\n ],\n [\n -160.8837890625,\n 63.87939001720202\n ],\n [\n -161.1474609375,\n 63.470144746565424\n ],\n [\n -162.6416015625,\n 63.64625919492172\n ],\n [\n -163.212890625,\n 63.05495931065107\n ],\n [\n -164.2236328125,\n 63.37183226679281\n ],\n [\n -166.1572265625,\n 61.75233128411639\n ],\n [\n -165.3662109375,\n 60.54377524118842\n ],\n [\n -167.431640625,\n 60.326947742998414\n ],\n [\n -167.255859375,\n 59.866883195210214\n ],\n [\n -165.8935546875,\n 59.7563950493563\n ],\n [\n -162.68554687499997,\n 59.734253447591364\n ],\n [\n -162.3779296875,\n 60.174306261926034\n ],\n [\n -161.806640625,\n 59.46740794183739\n ],\n [\n -162.0263671875,\n 59.108308258604964\n ],\n [\n -161.806640625,\n 58.768200159239576\n ],\n [\n -162.20214843749997,\n 58.65408464530598\n ],\n [\n -160.83984375,\n 58.44773280389084\n ],\n [\n -159.9609375,\n 58.6769376725869\n ],\n [\n -159.08203125,\n 58.309488840677645\n ],\n [\n -156.88476562499997,\n 58.92733441827545\n ],\n [\n -157.5,\n 58.516651799363785\n ],\n [\n -157.8076171875,\n 57.61010702068388\n ],\n [\n -161.54296875,\n 56.022948079627454\n ],\n [\n -168.6181640625,\n 53.4357192066942\n ],\n [\n -174.9462890625,\n 52.26815737376817\n ],\n [\n -178.2421875,\n 51.83577752045248\n ],\n [\n -173.1884765625,\n 51.590722643120145\n ],\n [\n -162.5537109375,\n 54.23955053156177\n ],\n [\n -155.302734375,\n 55.52863052257191\n ],\n [\n -151.4794921875,\n 57.51582286553883\n ],\n [\n -146.9970703125,\n 60.08676274626006\n ],\n [\n -145.546875,\n 60.21799073323445\n ],\n [\n -144.228515625,\n 59.689926220143356\n ],\n [\n -142.3828125,\n 59.93300042374631\n ],\n [\n -138.3837890625,\n 58.83649009392136\n ],\n [\n -135.6591796875,\n 56.31653672211301\n ],\n [\n -133.2421875,\n 54.521081495443596\n ],\n [\n -130.67138671875,\n 54.686534234529695\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.796875,\n 44.902577996288876\n ],\n [\n -67.67578124999999,\n 45.583289756006316\n ],\n [\n -67.939453125,\n 47.57652571374621\n ],\n [\n -69.2578125,\n 47.338822694822\n ],\n [\n -71.19140625,\n 45.27488643704891\n ],\n [\n -75.146484375,\n 44.96479793033101\n ],\n [\n -78.046875,\n 43.644025847699496\n ],\n [\n -79.1015625,\n 43.51668853502906\n ],\n [\n -79.1015625,\n 42.87596410238256\n ],\n [\n -82.68310546875,\n 41.65649719441145\n ],\n [\n -83.14453125,\n 42.049292638686836\n ],\n [\n -83.07861328125,\n 42.374778361114195\n ],\n [\n -82.529296875,\n 42.601619944327965\n ],\n [\n -82.24365234375,\n 43.6599240747891\n ],\n [\n -82.41943359375,\n 45.058001435398275\n ],\n [\n -83.60595703125,\n 45.85941212790755\n ],\n [\n -83.49609375,\n 46.027481852486645\n ],\n [\n -83.7158203125,\n 46.164614496897094\n ],\n [\n -83.95751953125,\n 46.07323062540835\n ],\n [\n -84.24316406249999,\n 46.558860303117164\n ],\n [\n -84.72656249999999,\n 46.558860303117164\n ],\n [\n -84.90234375,\n 46.92025531537451\n ],\n [\n -88.41796875,\n 48.3416461723746\n ],\n [\n -89.3408203125,\n 47.96050238891509\n ],\n [\n -90.76904296874999,\n 48.122101028190805\n ],\n [\n -90.87890625,\n 48.22467264956519\n ],\n [\n -91.51611328125,\n 48.10743118848039\n ],\n [\n -92.2412109375,\n 48.37084770238366\n ],\n [\n -92.39501953125,\n 48.23930899024907\n ],\n [\n -92.94433593749999,\n 48.61838518688487\n ],\n [\n -93.44970703125,\n 48.63290858589535\n ],\n [\n -94.7021484375,\n 48.748945343432936\n ],\n [\n -94.833984375,\n 49.23912083246698\n ],\n [\n -95.1416015625,\n 49.396675075193976\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -123.22265625000001,\n 48.99463598353405\n ],\n [\n -123.0908203125,\n 48.80686346108517\n ],\n [\n -123.24462890625,\n 48.66194284607006\n ],\n [\n -123.1787109375,\n 48.32703913063476\n ],\n [\n -124.78271484375,\n 48.472921272487824\n ],\n [\n -124.93652343749999,\n 48.16608541901253\n ],\n [\n -124.365234375,\n 46.58906908309182\n ],\n [\n -124.541015625,\n 44.15068115978094\n ],\n [\n -124.93652343749999,\n 42.69858589169842\n ],\n [\n -124.541015625,\n 41.22824901518529\n ],\n [\n -124.73876953125,\n 40.43022363450862\n ],\n [\n -124.03564453125,\n 39.35129035526705\n ],\n [\n -124.01367187499999,\n 38.8225909761771\n ],\n [\n -122.05810546875,\n 36.12012758978146\n ],\n [\n -120.95947265624999,\n 34.88593094075317\n ],\n [\n -120.80566406250001,\n 34.08906131584994\n ],\n [\n -118.21289062499999,\n 32.2313896627376\n ],\n [\n -117.22412109375,\n 32.54681317351514\n ],\n [\n -114.78515624999999,\n 32.713355353177555\n ],\n [\n -114.78515624999999,\n 32.491230287947594\n ],\n [\n -110.98388671874999,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.297327991404266\n ],\n [\n -108.2373046875,\n 31.765537409484374\n ],\n [\n -106.435546875,\n 31.765537409484374\n ],\n [\n -104.9853515625,\n 30.600093873550072\n ],\n [\n -104.47998046875,\n 29.592565403314087\n ],\n [\n -103.20556640625,\n 28.94086176940557\n ],\n [\n -102.65625,\n 29.76437737516313\n ],\n [\n -102.3486328125,\n 29.84064389983441\n ],\n [\n -101.49169921875,\n 29.7453016622136\n ],\n [\n -100.83251953125,\n 29.267232865200878\n ],\n [\n -100.30517578125,\n 28.246327971048842\n ],\n [\n -99.60205078124999,\n 27.586197857692664\n ],\n [\n -99.47021484375,\n 27.31321389856826\n ],\n [\n -99.228515625,\n 26.52956523826758\n ],\n [\n -98.2177734375,\n 26.05678288577881\n ],\n [\n -97.75634765625,\n 26.03704188651584\n ],\n [\n -97.44873046875,\n 25.839449402063185\n ],\n [\n -97.20703125,\n 25.93828707492375\n ],\n [\n -96.8994140625,\n 26.194876675795218\n ],\n [\n -96.78955078125,\n 27.858503954841247\n ],\n [\n -93.75732421875,\n 29.420460341013133\n ],\n [\n -90.2197265625,\n 28.998531814051795\n ],\n [\n -88.22021484375,\n 29.05616970274342\n ],\n [\n -87.91259765625,\n 30.14512718337613\n ],\n [\n -86.5283203125,\n 30.183121842195515\n ],\n [\n -85.2978515625,\n 29.49698759653577\n ],\n [\n -84.13330078125,\n 29.80251790576445\n ],\n [\n -82.81494140625,\n 28.555576049185973\n ],\n [\n -83.21044921875,\n 27.800209937418252\n ],\n [\n -82.77099609375,\n 26.941659545381516\n ],\n [\n -82.08984375,\n 25.878994400196202\n ],\n [\n -81.5625,\n 25.264568475331583\n ],\n [\n -82.28759765625,\n 24.467150664739002\n ],\n [\n -82.0458984375,\n 24.046463999666567\n ],\n [\n -80.6396484375,\n 24.56710835257599\n ],\n [\n -79.78271484375,\n 25.34402602913433\n ],\n [\n -79.60693359375,\n 27.27416111737468\n ],\n [\n -80.68359375,\n 30.713503990354965\n ],\n [\n -80.66162109375,\n 31.50362930577303\n ],\n [\n -76.81640625,\n 34.07086232376631\n ],\n [\n -75.16845703124999,\n 35.263561862152095\n ],\n [\n -75.498046875,\n 37.055177106660814\n ],\n [\n -73.58642578125,\n 39.90973623453719\n ],\n [\n -71.3671875,\n 40.84706035607122\n ],\n [\n -69.63134765625,\n 40.9964840143779\n ],\n [\n -70.0048828125,\n 42.342305278572816\n ],\n [\n -70.3564453125,\n 42.89206418807337\n ],\n [\n -67.2802734375,\n 44.37098696297173\n ],\n [\n -67.0166015625,\n 44.69989765840318\n ],\n [\n -66.796875,\n 44.902577996288876\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.2308349609375,\n 17.96305758238804\n ],\n [\n -67.2198486328125,\n 17.910795834978483\n ],\n [\n -66.5716552734375,\n 17.866361230891894\n ],\n [\n -66.16790771484375,\n 17.90556881196468\n ],\n [\n -65.85205078125,\n 17.973508079068797\n ],\n [\n -65.7861328125,\n 18.04142122189195\n ],\n [\n -65.50323486328125,\n 18.06231230454674\n ],\n [\n -65.2587890625,\n 18.114529138838503\n ],\n [\n -65.269775390625,\n 18.15629140283545\n ],\n [\n -65.4400634765625,\n 18.18238775108558\n ],\n [\n -65.51422119140625,\n 18.14324176648384\n ],\n [\n -65.5609130859375,\n 18.40665471391907\n ],\n [\n -65.64880371093749,\n 18.404048629104647\n ],\n [\n -65.77789306640625,\n 18.417078658661257\n ],\n [\n -65.9124755859375,\n 18.46918890441719\n ],\n [\n -66.24755859375,\n 18.510865709091377\n ],\n [\n -66.4837646484375,\n 18.503052080569763\n ],\n [\n -66.98638916015625,\n 18.51347017266187\n ],\n [\n -67.115478515625,\n 18.534304453676864\n ],\n [\n -67.181396484375,\n 18.48742375381096\n ],\n [\n -67.16217041015625,\n 18.432713391700858\n ],\n [\n -67.2637939453125,\n 18.375379094031825\n ],\n [\n -67.19238281249999,\n 18.2397859708389\n ],\n [\n -67.2308349609375,\n 17.96305758238804\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 27, 2020; Version 1.1: June 2, 2020; Version 1.2: October 16, 2020","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, Tennessee 37211
Soils represent the largest terrestrial reservoir of organic carbon, and the balance between soil organic carbon (SOC) formation and loss will drive powerful carbon‐climate feedbacks over the coming century. To date, efforts to predict SOC dynamics have rested on pool‐based models, which assume classes of SOC with internally homogenous physicochemical properties. However, emerging evidence suggests that soil carbon turnover is not dominantly controlled by the chemistry of carbon inputs, but rather by restrictions on microbial access to organic matter in the spatially heterogeneous soil environment. The dynamic processes that control the physicochemical protection of carbon translate poorly to pool‐based SOC models; as a result, we are challenged to mechanistically predict how environmental change will impact movement of carbon between soils and the atmosphere. Here, we propose a novel conceptual framework to explore controls on belowground carbon cycling: Probabilistic Representation of Organic Matter Interactions within the Soil Environment (PROMISE). In contrast to traditional model frameworks, PROMISE does not attempt to define carbon pools united by common thermodynamic or functional attributes. Rather, the PROMISE concept considers how SOC cycling rates are governed by the stochastic processes that influence the proximity between microbial decomposers and organic matter, with emphasis on their physical location in the soil matrix. We illustrate the applications of this framework with a new biogeochemical simulation model that traces the fate of individual carbon atoms as they interact with their environment, undergoing biochemical transformations and moving through the soil pore space. We also discuss how the PROMISE framework reshapes dialogue around issues related to SOC management in a changing world. We intend the PROMISE framework to spur the development of new hypotheses, analytical tools, and model structures across disciplines that will illuminate mechanistic controls on the flow of carbon between plant, soil, and atmospheric pools.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15365","usgsCitation":"Waring, B.G., Sulman, B.N., Reed, S., Smith, A.P., Averill, C., Creamer, C., Cusack, D.F., Hall, S.J., Jastrow, J., Kemner, K.M., Kleber, M., Liu, X.A., Pett-Ridge, J., and Schulz, M., 2020, From pools to flow: The PROMISE framework for new insights on soil carbon cycling in a changing world: Global Change Biology, v. 26, no. 12, p. 6631-6643, https://doi.org/10.1111/gcb.15365.","productDescription":"13 p.","startPage":"6631","endPage":"6643","ipdsId":"IP-112861","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455027,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1782302","text":"External Repository"},{"id":380844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Waring, Bonnie G. 0000-0002-8457-5164","orcid":"https://orcid.org/0000-0002-8457-5164","contributorId":245284,"corporation":false,"usgs":false,"family":"Waring","given":"Bonnie","email":"","middleInitial":"G.","affiliations":[{"id":49130,"text":"Utah State University, Department of Biology and Ecology Center, Logan UT 84322","active":true,"usgs":false}],"preferred":false,"id":805742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":805743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":805744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, A. Peyton","contributorId":245298,"corporation":false,"usgs":false,"family":"Smith","given":"A.","email":"","middleInitial":"Peyton","affiliations":[],"preferred":false,"id":805745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Averill, Colin","contributorId":245299,"corporation":false,"usgs":false,"family":"Averill","given":"Colin","email":"","affiliations":[],"preferred":false,"id":805746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cusack, Daniela F. 0000-0003-4681-7449","orcid":"https://orcid.org/0000-0003-4681-7449","contributorId":245300,"corporation":false,"usgs":false,"family":"Cusack","given":"Daniela","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":805822,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, Steven J. 0000-0002-7841-2019","orcid":"https://orcid.org/0000-0002-7841-2019","contributorId":244336,"corporation":false,"usgs":false,"family":"Hall","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":805823,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jastrow, Julie","contributorId":243114,"corporation":false,"usgs":false,"family":"Jastrow","given":"Julie","affiliations":[{"id":17946,"text":"Argonne National Laboratory","active":true,"usgs":false}],"preferred":false,"id":805824,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kemner, Kenneth M.","contributorId":245301,"corporation":false,"usgs":false,"family":"Kemner","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":805825,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kleber, Markus","contributorId":92182,"corporation":false,"usgs":true,"family":"Kleber","given":"Markus","email":"","affiliations":[],"preferred":false,"id":805826,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Liu, Xiao-Jun Allen","contributorId":245302,"corporation":false,"usgs":false,"family":"Liu","given":"Xiao-Jun","email":"","middleInitial":"Allen","affiliations":[],"preferred":false,"id":805827,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pett-Ridge, Jennifer","contributorId":6726,"corporation":false,"usgs":true,"family":"Pett-Ridge","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":805828,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":805829,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70215294,"text":"sir20205082 - 2020 - Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California","interactions":[],"lastModifiedDate":"2024-06-05T14:01:50.726878","indexId":"sir20205082","displayToPublicDate":"2020-10-16T10:48:16","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5082","displayTitle":"Delineation of Flood-Inundation Areas in Grapevine Canyon Near Scotty’s Castle, Death Valley National Park, California","title":"Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California","docAbstract":"On October 18, 2015, a large flood caused considerable damage in Grapevine Canyon near Death Valley Scotty Historic District, in Death Valley National Park, California. Significant channel changes had limited the applicability of previously created flood-inundation maps to current conditions. Predicted flood-inundation maps for Scotty’s Castle were updated using one-dimensional hydraulic models. A digital terrain model was created for the study area using a terrestrial laser scanner for use in the hydraulic models. Estimations of the 4, 2, 1, 0.5, and 0.2-percent annual exceedance probability flood streamflows (previously known as the 25, 50, 100, 250, and 500-year floods) were computed from regional flood regression equations. The estimated flood streamflows were used with the hydraulic models to compute water surface elevations that were mapped on the digital terrain model. The results indicate inundation of the visitor center and park offices occurs by the 4-percent annual exceedance probability flood. Bridge and embankment overtopping occurs by the 2-percent annual exceedance probability flood. Sections of Grapevine Canyon Road and the parking lot are inundated by the 4-percent annual exceedance probability flood and above streamflows. None of the computed streamflows reach Scotty’s Castle main building.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205082","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Morris, C.M., Welborn, T.L., and Minear, J.T., 2020, Delineation of flood-inundation areas in Grapevine Canyon near Scotty’s Castle, Death Valley National Park, California: U.S. Geological Survey Scientific Investigations Report 2020–5082, 27 p., https://doi.org/10.3133/sir20205082.","productDescription":"Report: vi, 27 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091560","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":379474,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IPKW55","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial Data, Tabular Data, and Surface-Water Model Archive for Delineation of Flood-Inundation Areas in Grapevine Canyon Near Scotty's Castle, Death Valley National Park, California"},{"id":379390,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5082/sir20205082.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5082"},{"id":379389,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5082/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Death Valley National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.960205078125,\n 36.5670120564234\n ],\n [\n -116.8670654296875,\n 36.5670120564234\n ],\n [\n -116.8670654296875,\n 37.19095471582605\n ],\n [\n -117.960205078125,\n 37.19095471582605\n ],\n [\n -117.960205078125,\n 36.5670120564234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
Results are presented and compared for the Community Earth System Model version 2 (CESM2) simulations of the middle Holocene (MH, 6 ka) and Last Interglacial (LIG, 127 ka). These simulations are designated as Tier 1 experiments (midHolocene and lig127k) for the Coupled Model Intercomparison Project phase 6 (CMIP6) and the Paleoclimate Modeling Intercomparison Project phase 4 (PMIP4). They use the low-top, standard 1° version of CESM2 contributing to CMIP6 DECK, historical, and future projection simulations, and to other modeling intercomparison projects. The midHolocene and lig127k provide the opportunity to examine the responses in CESM2 to the orbitally induced changes in the seasonal and latitudinal distribution of insolation. The insolation anomalies result in summer warming over the Northern Hemisphere continents, reduced Arctic summer minimum sea ice, and increased areal extent of the North African monsoon. The Arctic remains warm throughout the year. These changes are greater in the lig127k than midHolocene simulation. Other notable changes are reduction of the Niño3.4 variability and Drake Passage transport and a small increase in the Atlantic Meridional Overturning Circulation from the piControl to midHolocene to lig127k simulation. Comparisons to paleo-data and to simulations from previous model versions are discussed. Possible reasons for mismatches with the paleo-observations are proposed, including missing processes in CESM2, simplifications in the CMIP6 protocols for these experiments, and dating and calibration uncertainties in the data reconstructions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020PA003957","usgsCitation":"Otto-Bliesner, B., Brady, E.C., Tomas, R.A., Albani, S., Bartlein, P.J., Mahowald, N.M., Shafer, S., Kluzek, E., Lawrence, P.J., Leguy, G., Rothstein, M., and Sommers, A., 2020, A comparison of the CMIP6 midHolocene and lig127k simulations in CESM2: Paleoceanography and Paleoclimatology, v. 35, e2020PA003957, 30 p., https://doi.org/10.1029/2020PA003957.","productDescription":"e2020PA003957, 30 p.","ipdsId":"IP-116661","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455028,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2020pa003957","text":"Publisher Index Page"},{"id":436753,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D9S4EY","text":"USGS data release","linkHelpText":"Biomes simulated by BIOME4 using CESM2 lig127k, midHolocene, and piControl climate data on a global 0.5-degree grid"},{"id":397601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","noUsgsAuthors":false,"publicationDate":"2020-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Otto-Bliesner, Bette L.","contributorId":279720,"corporation":false,"usgs":false,"family":"Otto-Bliesner","given":"Bette L.","affiliations":[{"id":57353,"text":"Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":838791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Esther C. 0000-0001-7833-2249","orcid":"https://orcid.org/0000-0001-7833-2249","contributorId":289169,"corporation":false,"usgs":false,"family":"Brady","given":"Esther","email":"","middleInitial":"C.","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tomas, Robert A","contributorId":289243,"corporation":false,"usgs":false,"family":"Tomas","given":"Robert","email":"","middleInitial":"A","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Albani, Samuel","contributorId":289245,"corporation":false,"usgs":false,"family":"Albani","given":"Samuel","email":"","affiliations":[{"id":35744,"text":"University of Milano-Bicocca","active":true,"usgs":false}],"preferred":false,"id":838794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bartlein, Patrick J. 0000-0001-7657-5685","orcid":"https://orcid.org/0000-0001-7657-5685","contributorId":211587,"corporation":false,"usgs":false,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":33397,"text":"U of Oregon","active":true,"usgs":false}],"preferred":false,"id":838795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mahowald, Natalie M","contributorId":289246,"corporation":false,"usgs":false,"family":"Mahowald","given":"Natalie","email":"","middleInitial":"M","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":838796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":838797,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kluzek, Erik 0000-0002-1606-9219","orcid":"https://orcid.org/0000-0002-1606-9219","contributorId":289172,"corporation":false,"usgs":false,"family":"Kluzek","given":"Erik","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838798,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lawrence, Peter J","contributorId":289248,"corporation":false,"usgs":false,"family":"Lawrence","given":"Peter","email":"","middleInitial":"J","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838799,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leguy, Gunter 0000-0002-9963-8076","orcid":"https://orcid.org/0000-0002-9963-8076","contributorId":289175,"corporation":false,"usgs":false,"family":"Leguy","given":"Gunter","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838800,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rothstein, Matthew","contributorId":289250,"corporation":false,"usgs":false,"family":"Rothstein","given":"Matthew","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":838801,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sommers, Aleah 0000-0001-8718-0603","orcid":"https://orcid.org/0000-0001-8718-0603","contributorId":289162,"corporation":false,"usgs":false,"family":"Sommers","given":"Aleah","email":"","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":838802,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ]}