Shoreline changes affect functionality of a sandy beach as a wildlife habitat and coastal erosion is among the primary causes of the changes. We examined temporal shifts in locations where loggerheads placed nests in relation to coastal erosion along a barrier island beach in the northern Gulf of Mexico. We first confirmed consistency in long-term (1855–2001), short-term (1976–2001), and more recent (2002–2012) shoreline change rates in two adjacent beach sections, one historically eroding (west beach) and the other accreting (east beach). The mean annual shoreline change rate in the two sections was significantly different in all time periods. The recent (1998–2012) mean change rate was −10.9 ± 9.9 m/year in the west beach and −2.8 ± 4.9 m/year in the east beach, which resulted in the loss of about 70% and 30% of area in the west and east beaches, respectively. Loggerheads nested significantly closer to the vegetation line in 2012 than in 2002 in the west beach but the difference between the two time periods was not significant in the east beach. However, the distance from nests to the vegetation line from 2002 to 2014 was significantly reduced annually in both beaches; on average, loggerheads nested closer to the vegetation line by 9 m/year in the west beach and 5.8 m/year in the east beach. The observed shoreline change rate and corresponding shift of nest placement sites, combined with the forecasted future beach loss, highlighted the importance of addressing the issue of beach erosion to conserve sandy beach habitats.
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\"}}]}\n\n\n","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Defining and identifying changes to seasonal ranges of migratory species is required for effective conservation. Historic sightings of migrating whooping cranes (Grus americana) have served as sole source of information to define a migration corridor in the Great Plains of North America (i.e., Canadian Prairies and United States Great Plains) for this endangered species. We updated this effort using past opportunistic sightings from 1942–2016 (n = 5,055) and more recent (2010–2016) location data from 58 telemetered birds (n = 4,423) to delineate migration corridors that included 50%, 75%, and 95% core areas. All migration corridors were well defined and relatively compact, with the 95% core corridor averaging 294 km wide, although it varied approximately ±40% in width from 170 km in central Texas to 407 km at the international border of the United States and Canada. Based on historic sightings and telemetry locations, we detected easterly movements in locations over time, primarily due to locations west of the median shifting east. This shift occurred from northern Oklahoma to central Saskatchewan at an average rate of 1.2 km/year (0.3–2.8 km/year). Associated with this directional shift was a decrease in distance of locations from the median in the same region averaging -0.7 km/year (-0.3–-1.3 km/year), suggesting a modest narrowing of the migration corridor. Changes in the corridor over the past 8 decades suggest that agencies and organizations interested in recovery of this species may need to modify where conservation and recovery actions occur. Whooping cranes showed apparent plasticity in their migratory behavior, which likely has been necessary for persistence of a wetland-dependent species migrating through the drought-prone Great Plains. Behavioral flexibility will be useful for whooping cranes to continue recovery in a future of uncertain climate and land use changes throughout their annual range.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0192737","usgsCitation":"Pearse, A.T., Rabbe, M., Juliusson, L.M., Bidwell, M.T., Craig-Moore, L., Brandt, D.A., and Harrell, W.C., 2018, Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor: PLoS ONE, v. 13, no. 2, p. 1-15, https://doi.org/10.1371/journal.pone.0192737.","productDescription":"e0192737; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090602","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0192737","text":"Publisher Index Page"},{"id":351820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-15","publicationStatus":"PW","scienceBaseUri":"5afee729e4b0da30c1bfc150","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":728990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":728991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Juliusson, Lara M.","contributorId":202593,"corporation":false,"usgs":false,"family":"Juliusson","given":"Lara","email":"","middleInitial":"M.","affiliations":[{"id":36490,"text":"USFWS, Lakewood, CO","active":true,"usgs":false}],"preferred":false,"id":728992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":202007,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36318,"text":"CWS","active":true,"usgs":false}],"preferred":false,"id":728993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Craig-Moore, Lea","contributorId":202595,"corporation":false,"usgs":false,"family":"Craig-Moore","given":"Lea","email":"","affiliations":[{"id":36491,"text":"Environment and Climate Change Canada, Saskatoon, SK","active":true,"usgs":false}],"preferred":false,"id":728994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":728995,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":728996,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195453,"text":"70195453 - 2018 - Molecular phylogeny of the Nearctic and Mesoamerican freshwater mussel genus Megalonaias","interactions":[],"lastModifiedDate":"2018-03-12T13:03:55","indexId":"70195453","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Molecular phylogeny of the Nearctic and Mesoamerican freshwater mussel genus Megalonaias","docAbstract":"Megalonaias is the most geographically widespread genus of the subfamily Ambleminae and is distributed across much of the eastern half of North America, from Minnesota to Nicaragua. Despite the large geographic distribution, the species-level diversity of Megalonaias is quite depauperate (2 spp.), suggesting the genus may not be constrained by the same physical, ecological, or physiological barriers that limit dispersal in many other amblemines. However, this hypothesis is contingent on the assumption that the current taxonomy of Megalonaiasaccurately reflects its evolutionary history, which remains incompletely understood due to the marginalization of Mesoamerican populations in systematic research. Using one mitochondrial (COI) and one nuclear marker (ITS1) sequenced from 41 individuals distributed across both the Nearctic and Mesoamerican ecoregions, we set out to better understand the species boundaries and genetic diversity within Megalonaias. The reconstructed molecular phylogeny and the observed genetic diversity suggests that Megalonaias is a monotypic genus and that Megalonaias nickliniana, currently considered a federally endangered species, is not a valid species. These results are discussed in the context of their systematic and conservation implications, as well as how the unusual life history strategy of Megalonaias may be influencing its molecular diversity.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-017-3441-7","usgsCitation":"Pfeiffer, J.M., Sharpe, A., Johnson, N.A., Emery, K.F., and Page, L.M., 2018, Molecular phylogeny of the Nearctic and Mesoamerican freshwater mussel genus Megalonaias: Hydrobiologia, v. 811, no. 1, p. 139-151, https://doi.org/10.1007/s10750-017-3441-7.","productDescription":"13 p.","startPage":"139","endPage":"151","ipdsId":"IP-087894","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":461037,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10750-017-3441-7","text":"Publisher Index Page"},{"id":351686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":351685,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.ncbi.nlm.nih.gov/popset/?term=MF960169","linkHelpText":"Megalonaias nervosa internal transcribed spacer 1 and 5.8S ribosomal RNA gene, partial sequence"},{"id":351684,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://www.ncbi.nlm.nih.gov/popset/?term=%20MF960128","linkHelpText":"Megalonaias nervosa cytochrome oxidase subunit I (COI) gene, partial cds; mitochondrial"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.830078125,\n 13.581920900545844\n ],\n [\n -77.607421875,\n 13.581920900545844\n ],\n [\n -77.607421875,\n 49.439556958940855\n ],\n [\n -110.830078125,\n 49.439556958940855\n ],\n [\n -110.830078125,\n 13.581920900545844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"811","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5afee72ce4b0da30c1bfc170","contributors":{"authors":[{"text":"Pfeiffer, John M. III","contributorId":148964,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"John","suffix":"III","email":"","middleInitial":"M.","affiliations":[{"id":17607,"text":"Cherokee Nation Technology Solutions, Contracted to U.S. Geological Survey, Southeast Ecological Science Center","active":true,"usgs":false}],"preferred":false,"id":728677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sharpe, Ashley","contributorId":202520,"corporation":false,"usgs":false,"family":"Sharpe","given":"Ashley","email":"","affiliations":[{"id":36468,"text":"2Center for Tropical Paleoecology and Archaeology, Smithsonian Tropical Research Institute, Balboa-Ancon, Panama","active":true,"usgs":false}],"preferred":false,"id":728676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":728675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Emery, Kitty F.","contributorId":202522,"corporation":false,"usgs":false,"family":"Emery","given":"Kitty","email":"","middleInitial":"F.","affiliations":[{"id":36469,"text":"Florida Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":728678,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Page, Lawrence M.","contributorId":202523,"corporation":false,"usgs":false,"family":"Page","given":"Lawrence","email":"","middleInitial":"M.","affiliations":[{"id":36469,"text":"Florida Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":728679,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196261,"text":"70196261 - 2018 - Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies","interactions":[],"lastModifiedDate":"2018-03-28T17:05:14","indexId":"70196261","displayToPublicDate":"2018-02-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies","docAbstract":"Our understanding of deglacial climate history in the southern Great Lakes region of the United States is primarily based upon fossil pollen data, with few independent and multi-proxy climate reconstructions. Here we introduce a new, well-dated fossil pollen record from Stotzel-Leis, OH, and a new deglacial temperature record based on branched glycerol dialkyl glycerol tetraethers (brGDGTs) at Silver Lake, OH. We compare these new data to previously published records and to a regional stack of pollen-based temperature reconstructions from Stotzel-Leis, Silver Lake, and three other well-dated sites. The new and previously published pollen records at Stotzel-Leis are similar, but our new age model brings vegetation events into closer alignment with known climatic events such as the Younger Dryas (YD). brGDGT-inferred temperatures correlate strongly with pollen-based regional temperature reconstructions, with the strongest correlation obtained for a global soil-based brGDGT calibration (r2 = 0.88), lending confidence to the deglacial reconstructions and the use of brGDGT and regional pollen stacks as paleotemperature proxies in eastern North America. However, individual pollen records show large differences in timing, rates, and amplitudes of inferred temperature change, indicating caution with paleoclimatic inferences based on single-site pollen records. From 16.0 to 10.0ka, both proxies indicate that regional temperatures rose by ∼10 °C, roughly double the ∼5 °C estimates for the Northern Hemisphere reported in prior syntheses. Change-point analysis of the pollen stack shows accelerated warming at 14.0 ± 1.2ka, cooling at 12.6 ± 0.4ka, and warming from 11.6 ± 0.5ka into the Holocene. The timing of Bølling-Allerød (B-A) warming and YD onset in our records lag by ∼300–500 years those reported in syntheses of temperature records from the northern mid-latitudes. This discrepancy is too large to be attributed to uncertainties in radiocarbon dating, and correlation between pollen and brGDGT temperature reconstructions rules out vegetation lags as a cause. However, the YD termination appears synchronous among the brGDGT record, regional pollen stack, and Northern Hemisphere stack. The cause of the larger and lagged temperature changes in the southern Great Lakes relative to Northern Hemisphere averages remains unclear, but may be due to the effects of continentality and ice sheet extent on regional climate evolution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2017.12.011","usgsCitation":"Watson, B.I., Williams, J.W., Russell, J.M., Jackson, S.T., Shane, L., and Lowell, T.V., 2018, Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies: Quaternary Science Reviews, v. 182, p. 78-92, https://doi.org/10.1016/j.quascirev.2017.12.011.","productDescription":"15 p.","startPage":"78","endPage":"92","ipdsId":"IP-088633","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":468997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2017.12.011","text":"Publisher Index Page"},{"id":352887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"182","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee72de4b0da30c1bfc180","contributors":{"authors":[{"text":"Watson, Benjamin I.","contributorId":203629,"corporation":false,"usgs":false,"family":"Watson","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":731980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":731981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, James M.","contributorId":174740,"corporation":false,"usgs":false,"family":"Russell","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":27506,"text":"Department of Earth, Environmental and Planetary Sciences, Brown University, Providence RI 02912 USA","active":true,"usgs":false}],"preferred":false,"id":731982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":731921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shane, Linda","contributorId":203630,"corporation":false,"usgs":false,"family":"Shane","given":"Linda","email":"","affiliations":[],"preferred":false,"id":731983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowell, Thomas V.","contributorId":203631,"corporation":false,"usgs":false,"family":"Lowell","given":"Thomas","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":731984,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194443,"text":"sir20175150 - 2018 - Postglacial eruptive history and geochemistry of Semisopochnoi volcano, western Aleutian Islands, Alaska","interactions":[],"lastModifiedDate":"2019-12-30T11:27:36","indexId":"sir20175150","displayToPublicDate":"2018-02-14T00:00:00","publicationYear":"2018","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":"2017-5150","title":"Postglacial eruptive history and geochemistry of Semisopochnoi volcano, western Aleutian Islands, Alaska","docAbstract":"Semisopochnoi Island, located in the Rat Islands group of the western Aleutian Islands and Aleutian volcanic arc, is a roughly circular island composed of scattered volcanic vents, the prominent caldera of Semisopochnoi volcano, and older, ancestral volcanic rocks. The oldest rocks on the island are gently radially dipping lavas that are the remnants of a shield volcano and of Ragged Top, which is an eroded stratocone southeast of the current caldera. None of these oldest rocks have been dated, but they all are likely Pleistocene in age. Anvil Peak, to the caldera’s north, has the morphology of a young stratocone and is latest Pleistocene to early Holocene in age. The oldest recognized Holocene deposits are those of the caldera-forming eruption, which produced the 7- by 6-km caldera in the center of the island, left nonwelded ignimbrite in valleys below the edifice, and left welded ignimbrite high on its flanks. The caldera-forming eruption produced rocks showing a range of intermediate whole-rock compositions throughout the eruption sequence, although a majority of clasts analyzed form a fairly tight cluster on SiO2-variation diagrams at 62.9 to 63.4 weight percent SiO2. This clustering of compositions at about 63 weight percent SiO2 includes black, dense, obsidian-like clasts, as well as tan, variably oxidized, highly inflated pumice clasts. The best estimate for the timing of the eruption is from a soil dated at 6,920±60 14C years before present underlying a thin facies of the ignimbrite deposit on the island’s north coast. Shortly after the caldera-forming eruption, two scoria cones on the northwest flank of the volcano outside the caldera, Ringworm crater and Threequarter Cone, simultaneously erupted small volumes of andesite.
The oldest intracaldera lavas, on the floor of the caldera, are andesitic to dacitic, but are mostly covered by younger lavas and tephras. These intracaldera lavas include the basaltic andesites of small Windy cone, as well as the more voluminous basaltic andesites of three-peaked Mount Cerberus, which takes up most of the west half of the caldera and has erupted lavas that flowed to the sea on the southwestern coast of the island. Apparently active at the same time as Mount Cerberus, extracaldera Sugarloaf Peak at the southern point of the island has exclusively erupted basalts. Its young satellite peak, Sugarloaf Head, has erupted morphologically young lavas and cinder cones and may be the source of the last historical eruption in 1987. Several tephra sections on the east half of the island record as many as 50 tephras, mostly from Mount Cerberus, Sugarloaf Peak, and Sugarloaf Head, over the past several thousand years.
Eruptive products of Semisopochnoi Island show an overall compositional range of basalt to dacite, though basaltic andesite and andesite constitute the largest proportions of rock types. They are tholeiitic, low to medium K, and have geochemical characteristics typical of magmatic arcs. The earliest Pleistocene lavas are mostly basalts that show the greatest geochemical diversity, as illustrated by, for example, LaN/YbN ratios of 1.9 to 3.5, suggesting fluctuations in the magma source region over the hundreds of thousands of years recorded by these older lavas. The Holocene rocks, in contrast, follow arrays in compositional space that suggest crystallization differentiation from discrete, subtly different batches of magma under varying pressure and temperature conditions. Increasingly negative Eu anomalies and an only modestly increasing alumina saturation index value with differentiation suggest that plagioclase and mafic silicates (amphibole and pyroxene) were involved to varying degrees in fractional crystallization to produce Semisopochnoi’s magmatic diversity. The crystal-poor, andesitic magmas that erupted during caldera formation likely separated from a plagioclase-, amphibole-, and clinopyroxene-dominated crystal residue in the upper crust at less than 900 °C, possibly following a period of decreased magmatic flux. During the Holocene, basaltic Sugarloaf Peak appears to bypass any upper crustal magmatic storage region and erupt crystal-rich basalts. Recent seismic swarms and long-lived warm springs attest to ongoing magmatic activity.
The Holocene eruptive record at Semisopochnoi volcano is one of diverse eruptive styles as well as frequent eruptions from multiple vents located within and outside the caldera. The number and diversity of postcaldera vents means that the sites of future eruptions cannot be predicted with certainty. Future eruptions of ash similar in magnitude to the VEI 3 or less eruptions recorded in the documented tephra deposits would pose a hazard to aircraft in the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175150","usgsCitation":"Coombs, M.L., Larsen, J.F., and Neal, C.A., 2018, Postglacial eruptive history and geochemistry of Semisopochnoi volcano, western Aleutian Islands, Alaska: U.S. Geological Survey Scientific Investigations Report 2017–5150, 33 p., https://doi.org/10.3133/sir20175150.","productDescription":"Report: iv, 33 p.; 2 Tables","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-067229","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":438015,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P925UXOR","text":"USGS data release","linkHelpText":"Digital geologic map data for Semisopochnoi Island, Alaska"},{"id":351618,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5150/sir20175150_table2.xlsx","text":"Table 2","size":"65 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017-5150","linkHelpText":" - Matrix-glass compositions of pyroclasts from Semisopochnoi volcano and Amchitka Island, Alaska, as determined by electron microprobe"},{"id":351617,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5150/sir20175150_table1.xlsx","text":"Table 1","size":"100 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2017-5150","linkHelpText":" - Whole-rock compositions, locations, and descriptions of lava and tephra samples from Semisopochnoi Island, Alaska"},{"id":351615,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5150/coverthb.jpg"},{"id":351616,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5150/sir20175150.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5150"}],"country":"United States","state":"Alaska","otherGeospatial":"Semisopochnoi Volcano","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1710231115","usgsCitation":"Dietze, M., Fox, A., Beck-Johnson, L., Betancourt, J.L., Hooten, M., Jarnevich, C.S., Keitt, T.H., Kenney, M.A., Laney, C.M., Larsen, L., Loescher, H.W., Lunch, C.K., Pijanowski, B., Randerson, J.T., Read, E., Tredennick, A.T., Vargas, R., Weathers, K.C., and White, E.P., 2018, Iterative near-term ecological forecasting: Needs, opportunities, and challenges: Proceedings of the National Academy of Sciences of the United States of America, v. 115, no. 7, p. 1424-1432, https://doi.org/10.1073/pnas.1710231115.","productDescription":"9 p.","startPage":"1424","endPage":"1432","ipdsId":"IP-087870","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":469004,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1710231115","text":"External Repository"},{"id":351515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","scienceBaseUri":"5afee730e4b0da30c1bfc19e","contributors":{"authors":[{"text":"Dietze, Mike","contributorId":190102,"corporation":false,"usgs":false,"family":"Dietze","given":"Mike","email":"","affiliations":[],"preferred":false,"id":728347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, Andrew","contributorId":190103,"corporation":false,"usgs":false,"family":"Fox","given":"Andrew","affiliations":[],"preferred":false,"id":728348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beck-Johnson, Lindsay","contributorId":202412,"corporation":false,"usgs":false,"family":"Beck-Johnson","given":"Lindsay","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":728349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":728360,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tredennick, Andrew T.","contributorId":152688,"corporation":false,"usgs":false,"family":"Tredennick","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":18962,"text":"Dept. of Wildland Resources and the Ecology Center, Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":728361,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vargas, Rodrigo","contributorId":172036,"corporation":false,"usgs":false,"family":"Vargas","given":"Rodrigo","affiliations":[],"preferred":false,"id":728362,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Weathers, Kathleen C.","contributorId":202417,"corporation":false,"usgs":false,"family":"Weathers","given":"Kathleen","email":"","middleInitial":"C.","affiliations":[{"id":36424,"text":"Cary Institute of Ecosystems Studies","active":true,"usgs":false}],"preferred":false,"id":728363,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"White, Ethan P.","contributorId":190112,"corporation":false,"usgs":false,"family":"White","given":"Ethan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":728364,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70217882,"text":"70217882 - 2018 - Results of the 2010-2011 East-Central Adirondack Stream Survey (ECASS)","interactions":[],"lastModifiedDate":"2021-02-09T13:39:27.05271","indexId":"70217882","displayToPublicDate":"2018-02-09T07:35:58","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Results of the 2010-2011 East-Central Adirondack Stream Survey (ECASS)","docAbstract":"No abstract available.
","language":"English","publisher":"New York State Energy Research and Development Authority","collaboration":"New York State Energy Research and Development Authority","usgsCitation":"Lawrence, G.B., George, S.D., Burns, D., Baldigo, B.P., Passy, S., Roy, K.M., and Pound, K.L., 2018, Results of the 2010-2011 East-Central Adirondack Stream Survey (ECASS), ix, 89 p.","productDescription":"ix, 89 p.","ipdsId":"IP-098505","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":383154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383153,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/About/Publications/Research-and-Development-Technical-Reports/Environmental-Research-and-Development-Technical-Reports"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.69580078125001,\n 43.77109381775648\n ],\n [\n -75.06958007812501,\n 42.988576458321816\n ],\n [\n -73.32275390625,\n 43.11702412135048\n ],\n [\n -73.1689453125,\n 45.07352060670971\n ],\n [\n -74.89379882812501,\n 44.91035917458492\n ],\n [\n -75.69580078125001,\n 43.77109381775648\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":810028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":810029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Passy, Sophia","contributorId":248812,"corporation":false,"usgs":false,"family":"Passy","given":"Sophia","affiliations":[{"id":50025,"text":"Associate Professor, University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":810025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roy, Karen M.","contributorId":204095,"corporation":false,"usgs":false,"family":"Roy","given":"Karen","email":"","middleInitial":"M.","affiliations":[{"id":36838,"text":"Division of Air Resources, New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":810024,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pound, Katrina L.","contributorId":248833,"corporation":false,"usgs":false,"family":"Pound","given":"Katrina","email":"","middleInitial":"L.","affiliations":[{"id":50034,"text":"University of Texas, Arlington","active":true,"usgs":false}],"preferred":false,"id":810026,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195341,"text":"70195341 - 2018 - Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)","interactions":[],"lastModifiedDate":"2018-04-27T16:43:08","indexId":"70195341","displayToPublicDate":"2018-02-08T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)","title":"Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)","docAbstract":"Mercury (Hg) is a non-essential, toxic metal that is distributed worldwide. Mercury biomagnifies in food webs and can threaten the health of top predators such as seabirds. The Kittlitz's murrelet (Brachyramphus brevirostris) is a seabird endemic to Alaska and the Russian Far East and is a species of conservation concern in the region. We determined Hg concentrations in eggshells, guano, blood, and feathers of Kittlitz's murrelets sampled from four locations in Alaska. Mercury concentrations in eggshells, guano, and blood were low compared to other seabird species. Mean Hg concentrations of breast feathers from Adak Island and Glacier Bay were significantly greater than those from Agattu Island or Icy Bay. Two Kittlitz's murrelets at Glacier Bay and one Kittlitz's murrelet at Adak Island had Hg concentrations above those associated with impaired reproduction in other bird species, and may merit further investigation as a potential threat to individuals and populations.","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2017.10.055","usgsCitation":"Kenney, L.A., Kaler, R.S., Kissling, M.L., Bond, A.L., and Eagles-Smith, C.A., 2018, Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris): Marine Pollution Bulletin, v. 129, no. 2, p. 675-680, https://doi.org/10.1016/j.marpolbul.2017.10.055.","productDescription":"6 p.","startPage":"675","endPage":"680","ipdsId":"IP-079784","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":351386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -187.55859375,\n 51.069016659603896\n ],\n [\n -135.263671875,\n 51.069016659603896\n ],\n [\n -135.263671875,\n 60.84491057364912\n ],\n [\n -187.55859375,\n 60.84491057364912\n ],\n [\n -187.55859375,\n 51.069016659603896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7d6ff8e4b00f54eb24416e","contributors":{"authors":[{"text":"Kenney, Leah A.","contributorId":202222,"corporation":false,"usgs":false,"family":"Kenney","given":"Leah","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":727906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaler, Robb S.","contributorId":202223,"corporation":false,"usgs":false,"family":"Kaler","given":"Robb","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":727907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kissling, Michelle L.","contributorId":172675,"corporation":false,"usgs":false,"family":"Kissling","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":727908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bond, Alexander L.","contributorId":202224,"corporation":false,"usgs":false,"family":"Bond","given":"Alexander","email":"","middleInitial":"L.","affiliations":[{"id":36373,"text":"Ardenna Research","active":true,"usgs":false}],"preferred":false,"id":727909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":727905,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194701,"text":"sir20175151 - 2018 - Assessment of water resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico","interactions":[],"lastModifiedDate":"2018-02-07T17:11:00","indexId":"sir20175151","displayToPublicDate":"2018-02-07T00:00:00","publicationYear":"2018","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":"2017-5151","title":"Assessment of water resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, conducted a study to assess the water resources and potential effects on the water resources from oil and gas development in the Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico. Publicly available data were used to assess these resources and effects and to identify data gaps in the Tri-County planning area.
The Tri-County planning area includes approximately 9.3 million acres and is within the eastern extent of the Basin and Range Province, which consists of mountain ranges and low elevation basins. Three specific areas of interest within the Tri-County planning area are the Jornada del Muerto, Tularosa Basin, and Otero Mesa, which is adjacent to the Salt Basin. Surface-water resources are limited in the Tri-County planning area, with the Rio Grande as the main perennial river flowing from north to south through Sierra and Doña Ana Counties. The Tularosa Creek is an important surface-water resource in the Tularosa Basin. The Sacramento River, which flows southeast out of the Sacramento Mountains, is an important source of recharge to aquifers in the Salt Basin. Groundwater resources vary in aquifer type, depth to water, and water quality. For example, the Jornada del Muerto, Tularosa Basin, and Salt Basin each have shallow and deep aquifer systems, and water can range from freshwater, with less than 1,000 milligrams per liter (mg/L) of total dissolved solids, to brine, with greater than 35,000 mg/L of total dissolved solids. Water quality in the Tri-County planning area is affected by the dissolution of salt deposits and evaporation which are common in arid regions such as southern New Mexico.
The potential for oil and gas development exists in several areas within the Tri-County area. As many as 81 new conventional wells and 25 coalbed natural gas wells could be developed by 2035. Conventional oil and gas well construction in the Tri-County planning area is expected to require 1.53 acre-feet (acre-ft) (500,000 gallons) of water per well, similar to requirements in the nearby Permian Basin of New Mexico, while construction of unconventional wells is expected to require 7.3 acre-ft of water per well. Produced waters in the Permian Basin have high total dissolved solids, in the brackish to brine range.
Data gaps identified in this study include the limited detailed data on surface-water resources, the lack of groundwater data in areas of interest, and the lack of water chemistry data related to oil and gas development issues. Surface waters in the Tri-County planning area are sparse; some streams are perennial, and most are ephemeral. A more detailed study of the ephemeral channels and their interaction with groundwater could provide a better understanding of the importance of these surface-water resources. Groundwater data used in this study are from the USGS National Water Information System, which does not have continuous water-level depth data at many of the sites in the Tri-County planning area. On Otero Mesa, no recurrent groundwater-level data are available at any one site. The water-quality data compiled in this study provide a good overview of the general chemistry of groundwater in the Tri-County planning area. To fully understand the groundwater resources, it would be helpful to have more wells in specific areas of interest for groundwater-level and water-quality measurements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175151","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Blake, J.M., Miltenberger, Keely, Stewart, Anne, Ritchie, Andre, Montoya, Jennifer, Durr, Corey, McHugh, Amy, and Charles, Emmanuel, 2018, Assessment of water resources and the potential effects from oil and gas development in the Bureau of Land Management Tri-County planning area, Sierra, Doña Ana, and Otero Counties, New Mexico: U.S. Geological Survey Scientific Investigations Report 2017–5151, 87 p., https://doi.org/10.3133/sir20175151. 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Ana\",\"state\":\"NM\"}}]}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
Floodplains and streambanks can positively and negatively influence downstream water quality through interacting geomorphic and biogeochemical processes. Few studies have measured those processes in agricultural watersheds. We measured inputs (floodplain sedimentation and dissolved inorganic loading), cycling (floodplain soil nitrogen [N] and phosphorus [P] mineralization), and losses (bank erosion) of sediment, N, and P longitudinally in stream reaches of Smith Creek, an agricultural watershed in the Valley and Ridge physiographic province. All study reaches were net depositional (floodplain deposition > bank erosion), had high N and P sedimentation and loading rates to the floodplain, high soil concentrations of N and P, and high rates of floodplain soil N and P mineralization. High sediment, N, and P inputs to floodplains are attributed to agricultural activity in the region. Rates of P mineralization were much greater than those measured in other studies of nontidal floodplains that used the same method. Floodplain connectivity and sediment deposition decreased longitudinally, contrary to patterns in most watersheds. The net trapping function of Smith Creek floodplains indicates a benefit to water quality. Further research is needed to determine if future decreases in floodplain deposition, continued bank erosion, and the potential for nitrate leaching from nutrient-enriched floodplain soils could pose a long-term source of sediment and nutrients to downstream rivers.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12624","usgsCitation":"Gillespie, J., Noe, G.E., Hupp, C.R., Gellis, A.C., and Schenk, E., 2018, Floodplain trapping and cycling compared to streambank erosion of sediment and nutrients in an agricultural watershed: Journal of the American Water Resources Association, v. 54, no. 2, p. 565-582, https://doi.org/10.1111/1752-1688.12624.","productDescription":"18 p.","startPage":"565","endPage":"582","ipdsId":"IP-081496","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":438021,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Z036BD","text":"USGS data release","linkHelpText":"Floodplain sedimentation, bank erosion, and biogeochemical cycling of sediment and nutrients in Smith Creek (Virginia) 2012-2015"},{"id":351245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.8667,\n 38.4167\n ],\n [\n -78.55,\n 38.4167\n ],\n [\n -78.55,\n 38.7333\n ],\n [\n -78.8667,\n 38.7333\n ],\n [\n -78.8667,\n 38.4167\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a7c1e6ce4b00f54eb229289","contributors":{"authors":[{"text":"Gillespie, Jaimie 0000-0002-6483-0359","orcid":"https://orcid.org/0000-0002-6483-0359","contributorId":202016,"corporation":false,"usgs":true,"family":"Gillespie","given":"Jaimie","email":"","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":727380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":727381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":727382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":727383,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schenk, Edward R.","contributorId":202017,"corporation":false,"usgs":false,"family":"Schenk","given":"Edward R.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":727384,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194995,"text":"ofr20181014 - 2018 - Relations between total phosphorus and orthophosphorus concentrations and rainfall, surface-water discharge, and groundwater levels in Big Cypress Seminole Indian Reservation, Florida, 2014–16","interactions":[],"lastModifiedDate":"2018-02-07T10:51:43","indexId":"ofr20181014","displayToPublicDate":"2018-02-06T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1014","title":"Relations between total phosphorus and orthophosphorus concentrations and rainfall, surface-water discharge, and groundwater levels in Big Cypress Seminole Indian Reservation, Florida, 2014–16","docAbstract":"The Seminole Tribe of Florida (the Tribe) is partnering with the U.S. Environmental Protection Agency to develop a numeric phosphorus criterion for the 52,000-acre Big Cypress Seminole Indian Reservation (BCSIR), which is located downgradient of the Everglades Agricultural Area, and of other public and private lands, in southeastern Hendry County and northwestern Broward County in southern Florida. The U.S. Geological Survey (USGS), in cooperation with the Tribe, used water-quality data collected between October 2014 and September 2016 by the Tribe and the South Florida Water Management District (SFWMD), along with data from rainfall gages, surface-water stage and discharge gages, and groundwater monitoring wells, to (1) examine the relations between local hydrology and measured total phosphorus (TP) and orthophosphorus (OP) concentrations and (2) identify explanatory variables for TP concentrations. Of particular concern were conditions when TP exceeded 10 parts per billion (ppb) (0.01 milligram per liter [mg/L]) given that the State of Florida and the Miccosukee Tribe of Indians Alligator Alley Reservation (located downstream of the BCSIR) have adopted a 10-ppb maximum TP criterion for surface waters.
From October 2014 to September 2016, the Tribe collected 47–52 samples at each of nine water-quality sites for analysis of TP and OP, except at one site where 28 samples were collected. For all sites sampled, concentrations of TP (as phosphorus [P]) ranged from less than 0.002 mg/L (2 ppb) to a maximum of nearly 0.50 mg/L (500 ppb), whereas concentrations of OP (as P), the reactive form of inorganic phosphorus readily absorbed by plants and (or) abiotically absorbed, ranged from less than 0.003 mg/L (3 ppb) to a maximum of 0.24 mg/L (240 ppb). The median and interquartile ranges of concentrations of TP and OP in the samples collected in 2014–16 by the Tribe were similar to the median and interquartile ranges of concentrations in samples collected by the SFWMD at nearby sites during the same period. Differences in concentrations can likely be explained by differences in sample collection methods, sampling locations, sample collection time, and the hydrology during sampling or by the number of samples collected. A major limitation of this study was the short duration of sample collection, which covers a limited range of hydrologic conditions within the BCSIR.
The effect of surface-water and groundwater hydrologic conditions on TP and OP concentrations was assessed by using rainfall data and surface-water stage and discharge records. The highest TP and OP concentrations occurred during peak surface-water flows in the canals following long dry periods. Concentrations of TP and OP increased internal to the BCSIR in the western half of the BCSIR during wet periods, but increased concentrations tended to lag behind rainfall events, likely because control structures upstream of sampling sites do not release flows until the water levels in the canals reach predetermined levels. This pattern may indicate that bed sediments in the canals contain high concentrations of phosphorus that becomes resuspended during high flows or that phosphorus salts that had accumulated on dry land during dry periods are carried into the canals by runoff. The largest TP spikes usually occurred at the beginning of high-flow events, but then quickly tapered off even when flows remained high.
Groundwater flows were assessed in the BCSIR by using groundwater level observations from two preexisting USGS monitoring well clusters, each characterized by a shallow well installed in the surficial aquifer system and a deeper well installed in the intermediate aquifer system. Groundwater levels were evaluated with respect to surface-water levels and discharge in the BCSIR during the period of surface-water sampling. During dry conditions water levels in canals were often higher than groundwater levels in the surficial aquifer, indicating the potential for surface water to recharge the surficial aquifer. During wetter conditions, this trend reversed, and there was potential for shallow groundwater discharge into the canals.
From October 2014 to September 2016, concentrations of TP tended to decrease as surface-water inflows moved across the BCSIR from north to south. In both the western and eastern halves of the reservation, the mean concentration of TP was lower in the surface-water outflows from the BCSIR than in the inflows. The mean concentration of TP in the inflows to the western reservation was 0.04 mg/L (40 ppb), whereas the mean concentration of TP in the outflows was 0.03 mg/L (30 ppb). In the eastern reservation, the mean concentration of TP in the inflows was 0.07 mg/L (70 ppb), whereas the mean concentration of TP in the outflows was 0.04 mg/L (40 ppb).
TP and OP concentrations were evaluated relative to other water-quality parameters, including turbidity, suspended solids, nitrate plus nitrite, dissolved oxygen, pH, and specific conductance, to determine if any relations existed between TP and other variables. Weak relations were indicated for turbidity and suspended solids at two sites, which indicates that there may be a relation of increased TP to mobilization of sediment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181014","collaboration":"Prepared in cooperation with the Seminole Tribe of Florida","usgsCitation":"McBride, W.S., and Sifuentes, D.F., 2018, Relations between total phosphorus and orthophosphorus concentrations and rainfall, surface-water discharge, and groundwater levels in Big Cypress Seminole Indian Reservation, Florida, 2014–16: U.S. Geological Survey Open File Report 2018–1014, 63 p., https://doi.org/10.3133/ofr20181014.","productDescription":"xi, 63 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-086087","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":351046,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1014/ofr20181014.pdf","text":"Report","size":"6.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1014"},{"id":351045,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1014/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Big Cypress Seminole Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.8333,\n 26.1667\n ],\n [\n -81.0833,\n 26.1667\n ],\n [\n -81.0833,\n 26.4167\n ],\n [\n -80.8333,\n 26.4167\n ],\n [\n -80.8333,\n 26.1667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane
Lutz, FL 33559
Cytokines have important roles in the mammalian response to viral and bacterial infections, trauma, and wound healing. Because of early cytokine production after physiologic stresses, the regulation of messenger RNA (mRNA) transcripts can be used to assess immunologic responses before changes in protein production. To detect and assess early immune changes in endangered Florida manatees (Trichechus manatus latirostris), we developed and validated a panel of quantitative PCR assays to measure mRNA transcription levels for the cytokines interferon (IFN)-γ; interleukin (IL)-2, -6, and -10; tumor necrosis factor-α, and the housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and β-actin (reference genes). Assays were successfully validated using blood samples from free-ranging, apparently healthy manatees from the east and west coasts of central Florida. No cytokine or housekeeping gene transcription levels were significantly different among age classes or sexes. However, the transcription levels for GAPDH, IL-2, IL-6, and IFN-γ were significantly higher (P<0.05) in manatees from the east coast of Florida than they were from those from the west coast. We found IL-10 and β-actin to be consistent between sites and identified β-actin as a good candidate for use as a reference gene in future studies. Our assays can aid in the investigation of manatee immune response to physical trauma and novel or ongoing environmental stressors.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2017-06-139","usgsCitation":"Ferrante, J.A., Hunter, M., and Wellehan, J.F., 2018, Development and validation of quantitative PCR assays to measure cytokine transcript levels in the Florida manatee (Trichechus manatus latirostris): Journal of Wildlife Diseases, v. 54, no. 2, p. 283-294, https://doi.org/10.7589/2017-06-139.","productDescription":"12 p.","startPage":"283","endPage":"294","ipdsId":"IP-080601","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":438027,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TB163Q","text":"USGS data release","linkHelpText":"Quantitative PCR assays to measure Florida manatee cytokine mRNA and preliminary data from free-ranging manatees, 2013-14"},{"id":351011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","volume":"54","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a797b91e4b00f54eb1f5e0e","contributors":{"authors":[{"text":"Ferrante, Jason A. 0000-0003-3453-4636 jferrante@usgs.gov","orcid":"https://orcid.org/0000-0003-3453-4636","contributorId":201638,"corporation":false,"usgs":true,"family":"Ferrante","given":"Jason","email":"jferrante@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":726649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunter, Margaret 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140627,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","email":"mhunter@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":726648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wellehan, James F.X.","contributorId":201640,"corporation":false,"usgs":false,"family":"Wellehan","given":"James","email":"","middleInitial":"F.X.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":726650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70212316,"text":"70212316 - 2018 - Development of a species status assessment process for decisions under the U.S. Endangered Species Act","interactions":[],"lastModifiedDate":"2020-08-17T12:36:08.764155","indexId":"70212316","displayToPublicDate":"2018-02-02T10:04:43","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Development of a species status assessment process for decisions under the U.S. Endangered Species Act","docAbstract":"Decisions under the U.S. Endangered Species Act (ESA) require scientific input on the risk that the species will become extinct. A series of critiques on the role of science in ESA decisions have called for improved consistency and transparency in species risk assessments and clear distinctions between science input and policy application. To address the critiques and document the emerging practice of the U.S. Fish and Wildlife Service (USFWS), we outline an assessment process based on principles and practices of risk and decision analyses that results in a scientific report on species status. The species status assessment (SSA) process has three successive stages: 1) document the life history and ecological relationships of the species in question to provide the foundation for the assessment, 2) describe and hypothesize causes for the current condition of the species, and 3) forecast the species' future condition. The future condition refers to the ability of a species to sustain populations in the wild under plausible future scenarios. The scenarios help explore the species' response to future environmental stressors and to assess the potential for conservation to intervene to improve its status. The SSA process incorporates modeling and scenario planning for prediction of extinction risk and applies the conservation biology principles of representation, resiliency, and redundancy to evaluate the current and future condition. The SSA results in a scientific report distinct from policy application, which contributes to streamlined, transparent, and consistent decision-making and allows for greater technical participation by experts outside of the USFWS, for example, by state natural resource agencies. We present two case studies based on assessments of the eastern massasauga rattlesnake Sistrurus catenatus and the Sonoran Desert tortoise Gopherus morafkai to illustrate the process. The SSA builds upon the past threat-focused assessment by including systematic and explicit analyses of a species' future response to stressors and conservation, and as a result, we believe it provides an improved scientific analysis for ESA decisions.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/052017-JFWM-041","usgsCitation":"Smith, D.R., Allan, N.L., McGowan, C.P., Szymankski, J.A., Oetker, S.R., and Bell, H.M., 2018, Development of a species status assessment process for decisions under the U.S. Endangered Species Act: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 302-320, https://doi.org/10.3996/052017-JFWM-041.","productDescription":"19 p.","startPage":"302","endPage":"320","ipdsId":"IP-079068","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052017-jfwm-041","text":"Publisher Index Page"},{"id":377524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-02-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":796340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allan, Nathan L.","contributorId":193025,"corporation":false,"usgs":false,"family":"Allan","given":"Nathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":796341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":796342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szymankski, Jennifer A.","contributorId":238520,"corporation":false,"usgs":false,"family":"Szymankski","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oetker, Susan R.","contributorId":238519,"corporation":false,"usgs":false,"family":"Oetker","given":"Susan","email":"","middleInitial":"R.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bell, Heather M.","contributorId":238521,"corporation":false,"usgs":false,"family":"Bell","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195002,"text":"70195002 - 2018 - Potential for western US seasonal snowpack prediction","interactions":[],"lastModifiedDate":"2018-02-14T14:09:54","indexId":"70195002","displayToPublicDate":"2018-02-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Potential for western US seasonal snowpack prediction","docAbstract":"Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of th ecentury and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 month sin advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.1716760115","usgsCitation":"Kapnick, S.B., Yang, X., Vecchi, G., Delworth, T.L., Gudgel, R., Malyshev, S., Milly, P.C., Shevliakova, E., Underwood, S., and Margulis, S.A., 2018, Potential for western US seasonal snowpack prediction: Proceedings of the National Academy of Sciences of the United States of America, v. 115, no. 6, p. 1180-1185, https://doi.org/10.1073/pnas.1716760115.","productDescription":"6 p.","startPage":"1180","endPage":"1185","ipdsId":"IP-090874","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469039,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1716760115","text":"External Repository"},{"id":350944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -128.49609375,\n 30.56226095049944\n ],\n [\n -101.162109375,\n 30.56226095049944\n ],\n [\n -101.162109375,\n 49.809631563563094\n ],\n [\n -128.49609375,\n 49.809631563563094\n ],\n [\n -128.49609375,\n 30.56226095049944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"115","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","scienceBaseUri":"5a7586d3e4b00f54eb1d81c8","contributors":{"authors":[{"text":"Kapnick, Sarah B.","contributorId":189908,"corporation":false,"usgs":false,"family":"Kapnick","given":"Sarah","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":726514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Xiaosong","contributorId":201610,"corporation":false,"usgs":false,"family":"Yang","given":"Xiaosong","email":"","affiliations":[],"preferred":false,"id":726515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vecchi, Gabriel A.","contributorId":201585,"corporation":false,"usgs":false,"family":"Vecchi","given":"Gabriel A.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":726516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Delworth, Thomas L.","contributorId":189909,"corporation":false,"usgs":false,"family":"Delworth","given":"Thomas","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":726518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gudgel, Rich","contributorId":201586,"corporation":false,"usgs":false,"family":"Gudgel","given":"Rich","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":726517,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Malyshev, Sergey","contributorId":22175,"corporation":false,"usgs":true,"family":"Malyshev","given":"Sergey","affiliations":[],"preferred":false,"id":726519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":726513,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shevliakova, Elena","contributorId":9596,"corporation":false,"usgs":true,"family":"Shevliakova","given":"Elena","affiliations":[],"preferred":false,"id":726520,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Underwood, Seth","contributorId":201611,"corporation":false,"usgs":false,"family":"Underwood","given":"Seth","email":"","affiliations":[],"preferred":false,"id":726521,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Margulis, Steven A.","contributorId":201612,"corporation":false,"usgs":false,"family":"Margulis","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":726522,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70194989,"text":"70194989 - 2018 - Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","interactions":[],"lastModifiedDate":"2018-02-02T10:29:37","indexId":"70194989","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","docAbstract":"Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ∼ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha−1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-689-2018","usgsCitation":"Lee, S., Yeo, I., Sadeghi, A.M., McCarty, G.W., Hively, W., Lang, M.W., and Sharifi, A., 2018, Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model: Hydrology and Earth System Sciences, v. 22, p. 689-708, https://doi.org/10.5194/hess-22-689-2018.","productDescription":"10 p.","startPage":"689","endPage":"708","ipdsId":"IP-090233","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-689-2018","text":"Publisher Index Page"},{"id":350956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Greensboro Watershed, Tuckahoe Creek Watershed","volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-25","publicationStatus":"PW","scienceBaseUri":"5a7586d6e4b00f54eb1d81d4","contributors":{"authors":[{"text":"Lee, Sangchul","contributorId":201237,"corporation":false,"usgs":false,"family":"Lee","given":"Sangchul","email":"","affiliations":[],"preferred":false,"id":726400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeo, In-Young","contributorId":131145,"corporation":false,"usgs":false,"family":"Yeo","given":"In-Young","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":726402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sadeghi, Ali M.","contributorId":131147,"corporation":false,"usgs":false,"family":"Sadeghi","given":"Ali","email":"","middleInitial":"M.","affiliations":[{"id":7262,"text":"USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":726401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":726403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hively, Wells whively@usgs.gov","contributorId":201563,"corporation":false,"usgs":true,"family":"Hively","given":"Wells","email":"whively@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":726399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":726404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sharifi, Amir","contributorId":201564,"corporation":false,"usgs":false,"family":"Sharifi","given":"Amir","email":"","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":726405,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196629,"text":"70196629 - 2018 - Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA","interactions":[],"lastModifiedDate":"2018-04-23T10:01:33","indexId":"70196629","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1718,"text":"GCB Bioenergy","active":true,"publicationSubtype":{"id":10}},"title":"Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA","docAbstract":"Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario‐based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long‐term (1981–2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528 km2 of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232 km2 (~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide useful information to land managers to make land use decisions regarding switchgrass development.
","language":"English","publisher":"Wiley","doi":"10.1111/gcbb.12468","usgsCitation":"Gu, Y., and Wylie, B., 2018, Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA: GCB Bioenergy, v. 10, no. 2, p. 76-83, https://doi.org/10.1111/gcbb.12468.","productDescription":"8 p.","startPage":"76","endPage":"83","ipdsId":"IP-087756","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":469053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcbb.12468","text":"Publisher Index Page"},{"id":353641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.1845703125,\n 40.01078714046552\n ],\n [\n -95.30639648437499,\n 40.01078714046552\n ],\n [\n -95.30639648437499,\n 42.99661231842139\n ],\n [\n -99.1845703125,\n 42.99661231842139\n ],\n [\n -99.1845703125,\n 40.01078714046552\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-12","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1d7","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":733834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":197161,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce K.","email":"wylie@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":733835,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195941,"text":"70195941 - 2018 - Malassezia vespertilionis sp. nov.: A new cold-tolerant species of yeast isolated from bats","interactions":[],"lastModifiedDate":"2018-03-08T12:19:48","indexId":"70195941","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5648,"text":"Persoonia - Molecular Phylogeny and Evolution of Fungi","active":true,"publicationSubtype":{"id":10}},"title":"Malassezia vespertilionis sp. nov.: A new cold-tolerant species of yeast isolated from bats","docAbstract":"Malassezia is a genus of medically-important, lipid-dependent yeasts that live on the skin of warm-blooded animals. The 17 described species have been documented primarily on humans and domestic animals, but few studies have examined Malassezia species associated with more diverse host groups such as wildlife. While investigating the skin mycobiota of healthy bats, we isolated a Malassezia sp. that exhibited only up to 92 % identity with other known species in the genus for the portion of the DNA sequence of the internal transcribed spacer region that could be confidently aligned. The Malassezia sp. was cultured from the skin of nine species of bats in the subfamily Myotinae; isolates originated from bats sampled in both the eastern and western United States. Physiological features and molecular characterisation at seven additional loci (D1/D2 region of 26S rDNA, 18S rDNA, chitin synthase, second largest subunit of RNA polymerase II, β-tubulin, translation elongation factor EF-1α, and minichromosome maintenance complex component 7) indicated that all of the bat Malasseziaisolates likely represented a single species distinct from other named taxa. Of particular note was the ability of the Malassezia sp. to grow over a broad range of temperatures (7–40 °C), with optimal growth occurring at 24 °C. These thermal growth ranges, unique among the described Malassezia, may be an adaptation by the fungus to survive on bats during both the host's hibernation and active seasons. The combination of genetic and physiological differences provided compelling evidence that this lipid-dependent yeast represents a novel species described herein as Malassezia vespertilionis sp. nov. Whole genome sequencing placed the new species as a basal member of the clade containing the species M. furfur, M. japonica, M. obtusa, and M. yamatoensis. The genetic and physiological uniqueness of Malassezia vespertilionis among its closest relatives may make it important in future research to better understand the evolution, life history, and pathogenicity of the Malasseziayeasts.
","language":"English","publisher":"Naturalis Biodiversity Center","doi":"10.3767/persoonia.2018.41.04","usgsCitation":"Lorch, J.M., Palmer, J.M., Vanderwolf, K.J., Schmidt, K.Z., Verant, M.L., Weller, T.J., and Blehert, D.S., 2018, Malassezia vespertilionis sp. nov.: A new cold-tolerant species of yeast isolated from bats: Persoonia - Molecular Phylogeny and Evolution of Fungi, v. 41, p. 56-70, https://doi.org/10.3767/persoonia.2018.41.04.","productDescription":"15 p.","startPage":"56","endPage":"70","ipdsId":"IP-091447","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":461065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3767/persoonia.2018.41.04","text":"Publisher Index Page"},{"id":352336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee742e4b0da30c1bfc1f5","contributors":{"authors":[{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":730601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Jonathan M.","contributorId":172601,"corporation":false,"usgs":false,"family":"Palmer","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[{"id":27066,"text":"Center for Forest Mycology Research, Northern Research Station, US Forest Service, Madison, Wisconsin, USAb","active":true,"usgs":false}],"preferred":false,"id":730602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderwolf, Karen J. 0000-0003-0963-3093","orcid":"https://orcid.org/0000-0003-0963-3093","contributorId":203200,"corporation":false,"usgs":true,"family":"Vanderwolf","given":"Karen","email":"","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":730603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, Katie Z.","contributorId":176251,"corporation":false,"usgs":false,"family":"Schmidt","given":"Katie","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":730604,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verant, Michelle L.","contributorId":201556,"corporation":false,"usgs":false,"family":"Verant","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":36202,"text":"School of Veterinary Medicine, University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":730605,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weller, Theodore J.","contributorId":105961,"corporation":false,"usgs":false,"family":"Weller","given":"Theodore","email":"","middleInitial":"J.","affiliations":[{"id":13261,"text":"USDA Forest Service, Pacific Southwest Research Station, Davis, California","active":true,"usgs":false}],"preferred":false,"id":730606,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blehert, David S. 0000-0002-1065-9760 dblehert@usgs.gov","orcid":"https://orcid.org/0000-0002-1065-9760","contributorId":140392,"corporation":false,"usgs":true,"family":"Blehert","given":"David","email":"dblehert@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":730607,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196822,"text":"70196822 - 2018 - Three-dimensional foraging habitat use and niche partitioning in two sympatric seabird species, Phalacrocorax auritus and P. penicillatus","interactions":[],"lastModifiedDate":"2018-05-03T13:44:36","indexId":"70196822","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Three-dimensional foraging habitat use and niche partitioning in two sympatric seabird species, Phalacrocorax auritus and P. penicillatus","title":"Three-dimensional foraging habitat use and niche partitioning in two sympatric seabird species, Phalacrocorax auritus and P. penicillatus","docAbstract":"Ecological theory predicts that co-existing, morphologically similar species will partition prey resources when faced with resource limitations. We investigated local movements, foraging dive behavior, and foraging habitat selection by breeding adults of 2 closely related cormorant species, double-crested cormorants Phalacrocorax auritus and Brandt’s cormorants P. penicillatus. These species nest sympatrically at East Sand Island in the Columbia River estuary at the border of Oregon and Washington states, USA. Breeding individuals of each species were tracked using GPS tags with integrated temperature and depth data-loggers. The overall foraging areas and core foraging areas (defined as the 95% and 50% kernel density estimates of dive locations, respectively) of double-crested cormorants were much larger and covered a broader range of riverine, mixed-estuarine, and nearshore marine habitats. Brandt’s cormorant foraging areas were less expansive, were exclusively marine, and mostly overlapped with double-crested cormorant foraging areas. Within these areas of overlap, Brandt’s cormorants tended to dive deeper (median depth = 6.48 m) than double-crested cormorants (median depth = 2.67 m), and selected dive locations where the water was deeper. Brandt’s cormorants also utilized a deeper, more benthic portion of the water column than did double-crested cormorants. Nevertheless, the substantial overlap in foraging habitat between the 2 cormorant species in the Columbia River estuary, particularly for Brandt’s cormorants, suggests that superabundant prey resources allow these 2 large and productive cormorant colonies to coexist on a single island near the mouth of the Columbia River.
","language":"English","publisher":"Inter-Research","doi":"10.3354/meps12407","usgsCitation":"Peck-Richardson, A.G., Lyons, D.E., Roby, D.D., Cushing, D.A., and Lerczak, J.A., 2018, Three-dimensional foraging habitat use and niche partitioning in two sympatric seabird species, Phalacrocorax auritus and P. penicillatus: Marine Ecology Progress Series, v. 586, p. 251-264, https://doi.org/10.3354/meps12407.","productDescription":"14 p.","startPage":"251","endPage":"264","ipdsId":"IP-087206","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":353941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"586","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1cd","contributors":{"authors":[{"text":"Peck-Richardson, Adam G.","contributorId":204662,"corporation":false,"usgs":false,"family":"Peck-Richardson","given":"Adam","email":"","middleInitial":"G.","affiliations":[{"id":13016,"text":"Department of Fisheries and Wildlife, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":734610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, Donald E.","contributorId":204663,"corporation":false,"usgs":false,"family":"Lyons","given":"Donald","email":"","middleInitial":"E.","affiliations":[{"id":13016,"text":"Department of Fisheries and Wildlife, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":734611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cushing, Daniel A.","contributorId":204664,"corporation":false,"usgs":false,"family":"Cushing","given":"Daniel","email":"","middleInitial":"A.","affiliations":[{"id":13016,"text":"Department of Fisheries and Wildlife, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":734612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lerczak, James A.","contributorId":204665,"corporation":false,"usgs":false,"family":"Lerczak","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12961,"text":"College of Earth, Ocean, and Atmospheric Sciences, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":734613,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195393,"text":"70195393 - 2018 - On factors influencing air-water gas exchange in emergent wetlands","interactions":[],"lastModifiedDate":"2018-02-23T11:13:10","indexId":"70195393","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"On factors influencing air-water gas exchange in emergent wetlands","docAbstract":"Knowledge of gas exchange in wetlands is important in order to determine fluxes of climatically and biogeochemically important trace gases and to conduct mass balances for metabolism studies. Very few studies have been conducted to quantify gas transfer velocities in wetlands, and many wind speed/gas exchange parameterizations used in oceanographic or limnological settings are inappropriate under conditions found in wetlands. Here six measurements of gas transfer velocities are made with SF6 tracer release experiments in three different years in the Everglades, a subtropical peatland with surface water flowing through emergent vegetation. The experiments were conducted under different flow conditions and with different amounts of emergent vegetation to determine the influence of wind, rain, water flow, waterside thermal convection, and vegetation on air-water gas exchange in wetlands. Measured gas transfer velocities under the different conditions ranged from 1.1 cm h−1 during baseline conditions to 3.2 cm h−1 when rain and water flow rates were high. Commonly used wind speed/gas exchange relationships would overestimate the gas transfer velocity by a factor of 1.2 to 6.8. Gas exchange due to thermal convection was relatively constant and accounted for 14 to 51% of the total measured gas exchange. Differences in rain and water flow among the different years were responsible for the variability in gas exchange, with flow accounting for 37 to 77% of the gas exchange, and rain responsible for up to 40%.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017JG004299","usgsCitation":"Ho, D.T., Engel, V.C., Ferron, S., Hickman, B., Choi, J., and Harvey, J.W., 2018, On factors influencing air-water gas exchange in emergent wetlands: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 1, p. 178-192, https://doi.org/10.1002/2017JG004299.","productDescription":"15 p.","startPage":"178","endPage":"192","ipdsId":"IP-093042","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004299","text":"Publisher Index Page"},{"id":351532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.63,\n 25.84\n ],\n [\n -80.60,\n 25.84\n ],\n [\n -80.60,\n 25.87\n ],\n [\n -80.63,\n 25.87\n ],\n [\n -80.63,\n 25.84\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-24","publicationStatus":"PW","scienceBaseUri":"5afee743e4b0da30c1bfc205","contributors":{"authors":[{"text":"Ho, David T.","contributorId":202425,"corporation":false,"usgs":false,"family":"Ho","given":"David","email":"","middleInitial":"T.","affiliations":[{"id":36430,"text":"University of Hawaii, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":728385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engel, Victor C. 0000-0002-3858-7308","orcid":"https://orcid.org/0000-0002-3858-7308","contributorId":202426,"corporation":false,"usgs":false,"family":"Engel","given":"Victor","email":"","middleInitial":"C.","affiliations":[{"id":36431,"text":"U.S. Forest Service, Fort Collins","active":true,"usgs":false}],"preferred":false,"id":728386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferron, Sara","contributorId":199936,"corporation":false,"usgs":false,"family":"Ferron","given":"Sara","email":"","affiliations":[],"preferred":false,"id":728387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hickman, Benjamin","contributorId":202427,"corporation":false,"usgs":false,"family":"Hickman","given":"Benjamin","email":"","affiliations":[{"id":36430,"text":"University of Hawaii, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":728388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Choi, Jay jchoi@usgs.gov","contributorId":4731,"corporation":false,"usgs":true,"family":"Choi","given":"Jay","email":"jchoi@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":728389,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":728384,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197205,"text":"70197205 - 2018 - Attributes of seasonal home range influence choice of migratory strategy in white-tailed deer","interactions":[],"lastModifiedDate":"2018-05-22T16:36:46","indexId":"70197205","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Attributes of seasonal home range influence choice of migratory strategy in white-tailed deer","docAbstract":"Partial migration is a common life-history strategy among ungulates living in seasonal environments. The decision to migrate or remain on a seasonal range may be influenced strongly by access to high-quality habitat. We evaluated the influence of access to winter habitat of high quality on the probability of a female white-tailed deer (Odocoileus virginianus) migrating to a separate summer range and the effects of this decision on survival. We hypothesized that deer with home ranges of low quality in winter would have a high probability of migrating, and that survival of an individual in winter would be influenced by the quality of their home range in winter. We radiocollared 67 female white-tailed deer in 2012 and 2013 in eastern Washington, United States. We estimated home range size in winter using a kernel density estimator; we assumed the size of the home range was inversely proportional to its quality and the proportion of crop land within the home range was proportional to its quality. Odds of migrating from winter ranges increased by 3.1 per unit increase in home range size and decreased by 0.29 per unit increase in the proportion of crop land within a home range. Annual survival rate for migrants was 0.85 (SD = 0.05) and 0.84 (SD = 0.09) for residents. Our finding that an individual with a low-quality home range in winter is likely to migrate to a separate summer range accords with the hypothesis that competition for a limited amount of home ranges of high quality should result in residents having home ranges of higher quality than migrants in populations experiencing density dependence. We hypothesize that density-dependent competition for high-quality home ranges in winter may play a leading role in the selection of migration strategy by female white-tailed deer.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/jmammal/gyx148","usgsCitation":"Henderson, C.R., Mitchell, M.S., Myers, W.L., Lukacs, P.M., and Nelson, G.P., 2018, Attributes of seasonal home range influence choice of migratory strategy in white-tailed deer: Journal of Mammalogy, v. 99, no. 1, p. 89-96, https://doi.org/10.1093/jmammal/gyx148.","productDescription":"8 p.","startPage":"89","endPage":"96","ipdsId":"IP-076163","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469063,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jmammal/gyx148","text":"Publisher Index Page"},{"id":354400,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"99","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-22","publicationStatus":"PW","scienceBaseUri":"5b155db9e4b092d9651e1b81","contributors":{"authors":[{"text":"Henderson, Charles R. Jr.","contributorId":205132,"corporation":false,"usgs":false,"family":"Henderson","given":"Charles","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[{"id":37028,"text":"Montana Cooperative Wildlife Research Unit, University of Montana, Natural Sciences, Missoula, MT","active":true,"usgs":false}],"preferred":false,"id":736180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":736179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Woodrow L.","contributorId":200876,"corporation":false,"usgs":false,"family":"Myers","given":"Woodrow","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":736181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lukacs, Paul M.","contributorId":101240,"corporation":false,"usgs":true,"family":"Lukacs","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":736232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Gerald P.","contributorId":205134,"corporation":false,"usgs":false,"family":"Nelson","given":"Gerald","email":"","middleInitial":"P.","affiliations":[{"id":37030,"text":"Wildlife Program, Washington Department of Fish and Wildlife, Olympia, WA, USA","active":true,"usgs":false}],"preferred":false,"id":736182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197788,"text":"70197788 - 2018 - Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","interactions":[],"lastModifiedDate":"2018-06-20T10:54:13","indexId":"70197788","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3568,"text":"The Leading Edge","active":true,"publicationSubtype":{"id":10}},"title":"Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States","docAbstract":"Probabilistic seismic hazard analysis (PSHA) characterizes ground-motion hazard from earthquakes. Typically, the time horizon of a PSHA forecast is long, but in response to induced seismicity related to hydrocarbon development, the USGS developed one-year PSHA models. In this paper, we present a display of the variability in USGS hazard curves due to epistemic uncertainty in its informed submodel using a simple bootstrapping approach. We find that variability is highest in low-seismicity areas. On the other hand, areas of high seismic hazard, such as the New Madrid seismic zone or Oklahoma, exhibit relatively lower variability simply because of more available data and a better understanding of the seismicity. Comparing areas of high hazard, New Madrid, which has a history of large naturally occurring earthquakes, has lower forecast variability than Oklahoma, where the hazard is driven mainly by suspected induced earthquakes since 2009. Overall, the mean hazard obtained from bootstrapping is close to the published model, and variability increased in the 2017 one-year model relative to the 2016 model. Comparing the relative variations caused by individual logic-tree branches, we find that the highest hazard variation (as measured by the 95% confidence interval of bootstrapping samples) in the final model is associated with different ground-motion models and maximum magnitudes used in the logic tree, while the variability due to the smoothing distance is minimal. It should be pointed out that this study is not looking at the uncertainty in the hazard in general, but only as it is represented in the USGS one-year models.
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/tle37020141a1.1","usgsCitation":"Mousavi, S.M., Beroza, G.C., and Hoover, S.M., 2018, Variabilities in probabilistic seismic hazard maps for natural and induced seismicity in the central and eastern United States: The Leading Edge, v. 37, no. 2, p. 141a1-141a9, https://doi.org/10.1190/tle37020141a1.1.","productDescription":"9 p.","startPage":"141a1","endPage":"141a9","ipdsId":"IP-093220","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":355202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -115,\n 25\n ],\n [\n -65,\n 25\n ],\n [\n -65,\n 50\n ],\n [\n -115,\n 50\n ],\n [\n -115,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e5d3e4b060350a15d21c","contributors":{"authors":[{"text":"Mousavi, S. Mostafa","contributorId":205790,"corporation":false,"usgs":false,"family":"Mousavi","given":"S.","email":"","middleInitial":"Mostafa","affiliations":[{"id":37167,"text":"Department of Geophysics, Stanford University, Stanford, CA","active":true,"usgs":false}],"preferred":false,"id":738494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beroza, Gregory C.","contributorId":191201,"corporation":false,"usgs":false,"family":"Beroza","given":"Gregory","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":738495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoover, Susan M. 0000-0002-8682-6668 shoover@usgs.gov","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":5715,"corporation":false,"usgs":true,"family":"Hoover","given":"Susan","email":"shoover@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198104,"text":"70198104 - 2018 - Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings","interactions":[],"lastModifiedDate":"2018-07-24T15:57:54","indexId":"70198104","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5722,"text":"ERDC Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"ERDC/EL TR-18-3","title":"Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings","docAbstract":"On an annual basis, federal and state agencies are responsible for mapping and removing large expanses of aquatic nuisance vegetation from navigable waterways. This study set out to achieve four primary objectives: (1) utilize recent advancements in remote sensing techniques to classify the extent and distribution of aquatic vegetation in coastal ecosystems using satellite imagery, (2) assess primary aquatic vegetation growth and management efforts in coastal Louisiana, (3) statistically identify the ecological drivers that promote growth and infestation of aquatic nuisance vegetation, and (4) develop numerical models and a spatial tool to predict the probability of occurrence and growth of aquatic vegetation given ecological drivers. Moderate spatial resolution multispectral satellite imagery were used in conjunction with environmental variables from available data streams to generate regression models that predict aquatic vegetation occurrence in the eastern coastal region of south Louisiana. Geospatial tools were developed to execute the model logic using recent environmental conditions, thereby predicting aquatic vegetation occurrence and producing classified maps for end users. These products provide more efficient and enhanced capabilities for management of aquatic nuisance vegetation.
","language":"English","publisher":"Engineer Research and Development Center","doi":"10.21079/11681/26649","usgsCitation":"Suir, G.M., Suir, K.J., and Sapkota, S., 2018, Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings: ERDC Technical Report ERDC/EL TR-18-3, xi, 87 p., https://doi.org/10.21079/11681/26649.","productDescription":"xi, 87 p.","ipdsId":"IP-079845","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":461061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.21079/11681/26649","text":"Publisher Index Page"},{"id":355961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.6968994140625,\n 28.86391842622456\n ],\n [\n -88.9617919921875,\n 28.86391842622456\n ],\n [\n -88.9617919921875,\n 30.538607878854556\n ],\n [\n -93.6968994140625,\n 30.538607878854556\n ],\n [\n -93.6968994140625,\n 28.86391842622456\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-10","publicationStatus":"PW","scienceBaseUri":"5b6fc4a7e4b0f5d57878eab5","contributors":{"authors":[{"text":"Suir, Glenn M.","contributorId":206307,"corporation":false,"usgs":false,"family":"Suir","given":"Glenn","email":"","middleInitial":"M.","affiliations":[{"id":37304,"text":"U.S. Army Engineer Research and Development Center","active":true,"usgs":false}],"preferred":false,"id":740035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Suir, Kevin J. 0000-0003-1570-9648 suirk@usgs.gov","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":4894,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","email":"suirk@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":740034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sapkota, Sijan","contributorId":206308,"corporation":false,"usgs":false,"family":"Sapkota","given":"Sijan","affiliations":[{"id":37305,"text":"U.S. Army Medical Department Center and School","active":true,"usgs":false}],"preferred":false,"id":740036,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194519,"text":"sim3392 - 2018 - Quaternary sediment thickness and bedrock topography of the glaciated United States east of the Rocky Mountains","interactions":[],"lastModifiedDate":"2018-01-29T09:58:24","indexId":"sim3392","displayToPublicDate":"2018-01-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3392","title":"Quaternary sediment thickness and bedrock topography of the glaciated United States east of the Rocky Mountains","docAbstract":"Beginning roughly 2.6 million years ago, global climate entered a cooling phase known as the Pleistocene Epoch. As snow in northern latitudes compacted into ice several kilometers thick, it flowed as glaciers southward across the North American continent. These glaciers extended across the northern United States, dramatically altering the landscape they covered. East of the Rocky Mountains, the ice coalesced into continental glaciers (called the Laurentide Ice Sheet) that at times blanketed much of the north-central and northeastern United States. To the west of the Laurentide Ice Sheet, glaciers formed in the mountains of western Canada and the United States and coalesced into the Cordilleran ice sheet; this relatively smaller ice mass extended into the conterminous United States in the northernmost areas of western Montana, Idaho, and Washington. Throughout the Pleistocene, landscape alteration occurred by (1) glacial erosion of the rocks and sediments; (2) redeposition of the eroded earth materials in a form substantially different from their source rocks, in terms of texture and overall character; and (3) disruption of preexisting drainage patterns by the newly deposited sediments. In many cases, pre-glacial drainage systems (including, for example, the Mississippi River) were rerouted because their older drainage courses became blocked with glacial sediment.
The continental glaciers advanced and retreated many times across those areas. During each ice advance, or glaciation, erosion and deposition occurred, and the landscape was again altered. Through successive glaciations, the landscape and the bedrock surface gradually came to resemble their present configurations. As continental ice sheets receded and the Pleistocene ended, erosion and deposition of sediment (for example in stream valleys) continued to shape the landscape up to the present day (albeit to a lesser extent than during glaciation). The interval of time since the last recession of the glaciers is called the Holocene and, together with the Pleistocene, constitutes the Quaternary Period of geologic time; this publication characterizes the three-dimensional geometry of the Quaternary sediments and the bedrock surface that lies beneath.
The pre-glacial landscape was underlain mostly by weathered bedrock generally similar in nature to that found in many areas of the non-glaciated United States. Glacial erosion and redeposition of earth materials produced a young, mineral-rich soil that formed the basis for the highly productive agricultural economy in the U.S. midcontinent. Extensive buried sands and gravels within the glacial deposits also provided a stimulus to other economic sectors by serving as high-quality aquifers supplying groundwater to the region’s industry and cities. An understanding of the three-dimensional distribution of these glacial sediments has direct utility for addressing various societal issues including groundwater quality and supply, and landscape and soil response to earthquake-induced shaking.
The Quaternary sediment thickness map and bedrock topographic map shown here provide a regional overview and are intended to supplement the more detailed work on which they are based. Detailed mapping is particularly useful in populated areas for site-specific planning. In contrast, regional maps such as these serve to place local, detailed mapping in context; to permit the extrapolation of data into unmapped areas; and to depict large-scale regional geologic features and patterns that are beyond the scope of local, detailed mapping. They also can enhance the reader’s general understanding of the region’s landscape and geologic history and provide a source of information for regional decision making that could benefit by improved predictability of bedrock depth beneath the unconsolidated Quaternary sediments. To enable these maps to be analyzed in conjunction with other types of information, this publication also includes the map data in GIS compatible format.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3392","usgsCitation":"Soller, D.R., and Garrity, C.P., 2018, Quaternary sediment thickness and bedrock topography of the glaciated United States east of the Rocky Mountains: U.S. Geological Survey Scientific Investigations Map 3392, 2 sheets, scale 1:5,000,000. https://doi.org/10.3133/sim3392.","productDescription":"2 Sheets: 42.5 x 23.0 inches; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-084769","costCenters":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"links":[{"id":350668,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3392/sim3392_spatialdata.zip","text":"Spatial Data","size":"16 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3392","linkHelpText":"– Contains raster image files, layer file, and 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\"}}]}","contact":"National Cooperative Geologic Mapping Program
U.S. Geological Survey
12201 Sunrise Valley Drive Mail Stop 908
Reston, VA 20192
Fax: (703) 648-6937