New findings about old puzzles occasion rethinking of the Grand Coulee, greatest of the scabland channels. Those puzzles begin with antecedents of current upper Grand Coulee. By a recent interpretation, the upper coulee exploited the former high-level valley of a preflood trunk stream that had drained to the southwest beside and across Coulee anticline or monocline. In any case, a constriction and sharp bend in nearby Columbia valley steered Missoula floods this direction. Completion of upper Grand Coulee by megaflood erosion captured flood drainage that would otherwise have continued to enlarge Moses Coulee.
Upstream in the Sanpoil valley, deposits and shorelines of last-glacial Lake Columbia varied with the lake’s Grand Coulee outlet while also recording scores of Missoula floods. The Sanpoil evidence implies that upper Grand Coulee had approached its present intake depth early the last glaciation at latest, or more simply during a prior glaciation. An upper part of the Sanpoil section provides varve counts between the last tens of Missoula floods in a stratigraphic sequence that may now be linked to flood rhythmites of southern Washington by a set-S tephra from Mount St. Helens.
On the floor of upper Grand Coulee itself, recently found striated rock and lodgement till confirm the long-held view, which Bretz and Flint had shared, that cutting of upper Grand Coulee preceded its last-glacial occupation by the Okanogan ice lobe. A dozen or more late Missoula floods registered as sand and silt in the lee of Steamboat Rock.
Some of this field evidence about upper Grand Coulee may conflict with results of recent two-dimensional simulations for a maximum Lake Missoula. In these simulations only a barrier high above the present coulee intake enables floods to approach high-water marks near Wenatchee that predate stable blockage of Columbia valley by the Okanogan lobe. Above the walls of upper Grand Coulee, scabland limits provide high-water targets for two-dimensional simulations of watery floods. The recent models sharpen focus on water sources, prior coulee incision, and coulee’s occupation by the Okanogan ice lobe.
Field reappraisal continues downstream from Grand Coulee on Ephrata fan. There, some of the floods exiting lower Grand Coulee had bulked up with fine sediment from glacial Lake Columbia, upper coulee till, and a lower coulee lake that the fan itself impounded. Floods thus of debris-flow consistency carried outsize boulders previously thought transported by watery floods.
Below Ephrata fan, a backflooded reach of Columbia valley received Grand Coulee outflow of small, late Missoula floods. These late floods can—by varve counts in post-S-ash deposits of Sanpoil valley—be clocked now as a decade or less apart. Still farther downstream, Columbia River gorge choked the largest Missoula floods, passing peak discharge only one-third to one-half that released by the breached Lake Missoula ice dam.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.0062(07)","usgsCitation":"Waitt, R.B., Atwater, B., Lehnigk, K., Larsen, I., Bjornstad, B., Hanson, M., and O'Connor, J., 2021, Upper Grand Coulee: New views of a channeled scabland megafloods enigma, chap. of From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest, v. 62, p. 245-300, https://doi.org/10.1130/2021.0062(07).","productDescription":"56 p.","startPage":"245","endPage":"300","ipdsId":"IP-129810","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":481101,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2021.0062(07)","text":"Publisher Index Page"},{"id":480733,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Upper Grand Coulee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.50054736602212,\n 49.462558518080414\n ],\n [\n -125.44572643872874,\n 49.462558518080414\n ],\n [\n -125.44572643872874,\n 44.60810790414203\n ],\n [\n -117.50054736602212,\n 44.60810790414203\n ],\n [\n -117.50054736602212,\n 49.462558518080414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Waitt, Richard B. 0000-0002-6392-5604 waitt@usgs.gov","orcid":"https://orcid.org/0000-0002-6392-5604","contributorId":2343,"corporation":false,"usgs":true,"family":"Waitt","given":"Richard","email":"waitt@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":924412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwater, Brian F.","contributorId":349552,"corporation":false,"usgs":true,"family":"Atwater","given":"Brian F.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":924413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehnigk, Karin","contributorId":349556,"corporation":false,"usgs":false,"family":"Lehnigk","given":"Karin","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":924415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Isaac J.","contributorId":349557,"corporation":false,"usgs":false,"family":"Larsen","given":"Isaac J.","affiliations":[{"id":83490,"text":"University of Massachusetts, Amherst, Mass.","active":true,"usgs":false}],"preferred":false,"id":924416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjornstad, Bruce N.","contributorId":349558,"corporation":false,"usgs":false,"family":"Bjornstad","given":"Bruce N.","affiliations":[{"id":83492,"text":"Ice Age Floodscapes, Richland, Wash.","active":true,"usgs":false}],"preferred":false,"id":924417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hanson, Michelle A.","contributorId":349554,"corporation":false,"usgs":false,"family":"Hanson","given":"Michelle A.","affiliations":[{"id":83488,"text":"Saskatchewan Geological Survey, Regina, Sask.","active":true,"usgs":false}],"preferred":false,"id":924414,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":924418,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224546,"text":"70224546 - 2021 - The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020","interactions":[],"lastModifiedDate":"2021-10-18T15:08:18.866454","indexId":"70224546","displayToPublicDate":"2021-09-24T08:50:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020","docAbstract":"This data note describes the Biscuit Brook and Neversink Reservoir watershed Long-Term Monitoring Data that includes: 1) stream discharge, (1983 – 2020 for Biscuit Brook and 1937 – 2020 for the Neversink Reservoir watershed), 2) stream water chemistry, 1983-2020, at 4 stations, 3) fish survey data from 16 locations in the watershed 1990-2019, 4) soil chemistry data from 2 headwater sub-watersheds, 1993-2012, and 5) periodic stream water chemistry sampling data from 364 locations throughout the watershed, 1983-2020. The Neversink Reservoir watershed in the Catskill Mountains of New York, USA drains an area of 172.5 km2. The watershed feeds one of 6 reservoirs in New York City's West of Hudson water supply, which accounts for about 90% of the city's water supply. Biscuit Brook is a 9.63 km2 tributary sub-watershed within the Neversink Reservoir watershed.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14394","usgsCitation":"Murdoch, P.S., Burns, D., McHale, M., Siemion, J., Baldigo, B., Lawrence, G.B., George, S.D., Antidormi, M.R., and Bonville, D.B., 2021, The Biscuit Brook and Neversink Reservoir Watersheds: Long-term investigations of stream chemistry, soil chemistry, and aquatic ecology in the Catskill Mountains, New York, USA, 1983 to 2020: Hydrological Processes, v. 35, e14394, 12 p., https://doi.org/10.1002/hyp.14394.","productDescription":"e14394, 12 p.","ipdsId":"IP-126065","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":450676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.14394","text":"Publisher Index Page"},{"id":389807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Biscuit Brook and Neversink Reservoir Watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.62188720703125,\n 41.840920397579936\n ],\n [\n -74.60403442382812,\n 41.85319643776675\n ],\n [\n -74.53811645507812,\n 41.881831370505594\n ],\n [\n -74.44129943847656,\n 41.92629234083705\n ],\n [\n -74.28337097167969,\n 42.007978804701\n ],\n [\n -74.278564453125,\n 42.06509700139039\n ],\n [\n -74.30671691894531,\n 42.11095834849246\n ],\n [\n -74.3341827392578,\n 42.13133052651052\n ],\n [\n -74.4049072265625,\n 42.132858175814626\n ],\n [\n -74.44747924804688,\n 42.11707068963613\n ],\n [\n -74.48867797851562,\n 42.042153895364\n ],\n [\n -74.57725524902344,\n 41.984504674276074\n ],\n [\n -74.652099609375,\n 41.9528519300999\n ],\n [\n -74.73518371582031,\n 41.89869952106346\n ],\n [\n -74.74273681640625,\n 41.86291329896065\n ],\n [\n -74.70497131347656,\n 41.81636125072054\n ],\n [\n -74.64866638183594,\n 41.81175536180908\n ],\n [\n -74.62188720703125,\n 41.840920397579936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","noUsgsAuthors":false,"publicationDate":"2021-10-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Murdoch, Peter S. 0000-0001-9243-505X pmurdoch@usgs.gov","orcid":"https://orcid.org/0000-0001-9243-505X","contributorId":2453,"corporation":false,"usgs":true,"family":"Murdoch","given":"Peter","email":"pmurdoch@usgs.gov","middleInitial":"S.","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":824014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":824015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siemion, Jason 0000-0001-5635-6469 jsiemion@usgs.gov","orcid":"https://orcid.org/0000-0001-5635-6469","contributorId":127562,"corporation":false,"usgs":true,"family":"Siemion","given":"Jason","email":"jsiemion@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":824019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":824020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bonville, Donald B. 0000-0003-4480-9381","orcid":"https://orcid.org/0000-0003-4480-9381","contributorId":248849,"corporation":false,"usgs":true,"family":"Bonville","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":824022,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70244091,"text":"70244091 - 2021 - Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach","interactions":[],"lastModifiedDate":"2023-06-01T14:04:48.814131","indexId":"70244091","displayToPublicDate":"2021-09-24T08:41:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach","docAbstract":"A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics, and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2021.117685","usgsCitation":"Qian, S.S., Kennen, J., May, J., Freeman, M., and Cuffney, T.F., 2021, Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach: Water Research, v. 205, 117685, 11 p., https://doi.org/10.1016/j.watres.2021.117685.","productDescription":"117685, 11 p.","ipdsId":"IP-125255","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":450679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2021.117685","text":"Publisher Index Page"},{"id":417645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.52179800853753,\n 32.86310990611119\n ],\n [\n -78.95424437482033,\n 33.20732442214225\n ],\n [\n -78.83061042748197,\n 33.62402639579081\n ],\n [\n -78.03123021414571,\n 33.81848745598903\n ],\n [\n -77.49960057459164,\n 34.229007941502374\n ],\n [\n -77.20942075405912,\n 34.57053494448374\n ],\n [\n -78.04925882655441,\n 35.593623760054015\n ],\n [\n -79.61149509648914,\n 36.3847977489354\n ],\n [\n -80.69994996842892,\n 36.980415621762745\n ],\n [\n -81.2368093995407,\n 36.697683304342775\n ],\n [\n -81.66006417146134,\n 35.81807327161229\n ],\n [\n -80.92321025597303,\n 33.67553987083947\n ],\n [\n -80.06864524456462,\n 32.587876038945694\n ],\n [\n -79.52179800853753,\n 32.86310990611119\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"205","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Qian, Song S. 0000-0002-2346-4903","orcid":"https://orcid.org/0000-0002-2346-4903","contributorId":306033,"corporation":false,"usgs":false,"family":"Qian","given":"Song","email":"","middleInitial":"S.","affiliations":[{"id":62440,"text":"Department of Environmental Sciences, University of Toledo, Toledo, OH 43606","active":true,"usgs":false}],"preferred":false,"id":874463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"May, Jason 0000-0002-5699-2112","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":224991,"corporation":false,"usgs":false,"family":"May","given":"Jason","affiliations":[{"id":41015,"text":"Deceased (ex-USGS)","active":true,"usgs":false}],"preferred":false,"id":874465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":874466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F 0000-0003-1164-5560","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":306032,"corporation":false,"usgs":false,"family":"Cuffney","given":"Thomas","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":874467,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70225172,"text":"70225172 - 2021 - miR133b microinjection during early development targets transcripts of sardiomyocyte ion channels and induces oil-like cardiotoxicity in zebrafish (Danio rerio) embryos","interactions":[],"lastModifiedDate":"2021-10-18T15:13:36.286802","indexId":"70225172","displayToPublicDate":"2021-09-24T07:40:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9529,"text":"Chemical Research in Toxicology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"miR133b microinjection during early development targets transcripts of sardiomyocyte ion channels and induces oil-like cardiotoxicity in zebrafish (Danio rerio) embryos","title":"miR133b microinjection during early development targets transcripts of sardiomyocyte ion channels and induces oil-like cardiotoxicity in zebrafish (Danio rerio) embryos","docAbstract":"Previous studies have shown that altered expression of a family of small noncoding RNAs (microRNAs, or miRs) regulates the expression of downstream mRNAs and is associated with diseases and developmental disorders. miR133b is highly expressed in mammalian cardiac and skeletal muscle, and aberrant expression is associated with cardiac disorders and electrophysiological changes in cardiomyocytes. Similarly, cardiac dysfunction has been observed in early life-stage mahi-mahi (Coryphaena hippurus) exposed to crude oil, a phenotype that has been associated with an upregulation of miR133b as well as subsequent downregulation of a delayed rectifier potassium channel (IKr) and calcium signaling genes that are important for proper heart development during embryogenesis. To examine the potential role of miR133b in oil-induced early life-stage cardiotoxicity in fish, cleavage-stage zebrafish (Danio rerio) embryos were either (1) microinjected with ∼3 nL of negative control miR (75 μM) or miR133b (75 μM) or (2) exposed to a treatment solution containing 5 μM benzo(a)pyrene (BaP), a model polycyclic aromatic hydrocarbon, as a positive control. At 72 h post fertilization (hpf), miR133b-injected fish exhibited BaP-like cardiovascular malformations, including a significantly increased pericardial area relative to negative control miR-injected embryos, as well as a significantly reduced eye area. qPCR revealed that miR133b microinjection decreased the abundance of cardiac-specific IKrkcnh6 at 5 hpf, which may contribute to action potential elongation in oil-exposed cardiomyocytes. Additionally, ryanodine receptor 2, a crucial calcium receptor in the sarcoplasmic reticulum, was also downregulated by miR133b. These results indicate that an oil-induced increase in miR133b may contribute to cardiac abnormalities in oil-exposed fish by targeting cardiac-specific genes essential for proper heart development.
The U.S. Geological Survey mined data from a variety of national and state agencies including USGS, Oregon Water Resources Department, National Oceanic and Atmospheric Administration, Washington Department of Ecology, Pacific Northwest National Laboratory, Portland State University, and U.S. Army Corps of Engineers. A comprehensive dataset of streamflow, stage, and tidal elevations for the Lower Columbia River basin was compiled. Data were compiled from gaging stations in Oregon and Washington along the Columbia River from Astoria to The Dalles and along the Willamette River from Salem to Portland. Tidal gages along the Washington, Oregon, and California coasts were also compiled. Seasonal maximum values were calculated for both streamflow and stage for the winter (November–March) and spring (April–July) flow seasons, as well as for the full water year when underlying data were available. The aggregated datasets are available at https://doi.org/10.5066/P9R6RT0Z.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201138","collaboration":"Prepared in cooperation with U.S. Army Corps of Engineers","usgsCitation":"Boudreau, C.L., Stewart, M.A., and Stonewall, A.J., 2021, Historical streamflow and stage data compilation for the Lower Columbia River, Pacific Northwest: U.S. Geological Survey Open-File Report 2020–1138, 50 p., https://doi.org/10.3133/ofr20201138.","productDescription":"Report: viii, 50 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-101122","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":389696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1138/coverthb.jpg"},{"id":389697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1138/ofr20201138.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1138"},{"id":389698,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6RT0Z","text":"USGS data release","description":"USGS Data release","linkHelpText":"Historical streamflow and stage data for the lower Columbia River basin and the coasts of Washington, Oregon, and northern California"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Lower Columbia River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.63964843750001,\n 41.672911819602085\n ],\n [\n -120.80566406250001,\n 41.672911819602085\n ],\n [\n -120.80566406250001,\n 49.26780455063753\n ],\n [\n -125.63964843750001,\n 49.26780455063753\n ],\n [\n -125.63964843750001,\n 41.672911819602085\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
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2130 SW 5th Avenue
Portland, Oregon 97201
Temperature fluctuations and climate change impacts may substantially affect spawning success of fish, especially migratory species with a limited spawning window. Factors affecting American shad (Alosa sapidissima) spawning success and survival were investigated at different temperatures and periods (peak- and late-spawning periods) during the Connecticut River, USA, spawning migration in 2017. Wild caught American shad were exposed to constant temperatures regimes of 15, 18, 21, 24 and 27 °C for 2 weeks. During the peak-spawning period, an increase in temperature (15–24 °C) was shown to increase spawning success factors, including spawning probability, number of eggs, and fertilization success, but decreased egg size. Temperatures between 18 and 27 °C did not affect these factors during the late-spawning period. Glochidia infection by the alewife floater (Anodonta implicata) was much higher in the late-spawning period and significantly decreased the survival of American shad. Further research should investigate the parasite-host relationship between the alewife floater and American shad to determine annual variability of glochidia infections and how they affect American shad from physiological and passage perspectives. Higher temperatures were shown to increase spawning success of American shad during the peak-spawning period, but temperature had no effect during the late-spawning period. However, any effect during the late-spawning period may have been masked by a high level of glochidia infection.
For species with variable phenology, it is often challenging to produce reliable estimates of population dynamics or changes in occupancy. The Arizona Toad (Anaxyrus microscaphus) is a southwestern USA endemic that has been petitioned for legal protection, but status assessments are limited by a lack of information on population trends. Also, timing and consistency of Arizona Toad breeding varies greatly, making it difficult to predict optimal survey times or effort required for detection. To help fill these information gaps, we conducted breeding season call surveys during 2013–2016 and 2019 at 86 historically occupied sites and 59 control sites across the species' range in New Mexico. We estimated variation in mean dates of arrival and departure from breeding sites, changes in occupancy, and site-level extinction since 1959 with recently developed multi-season staggered-entry models, which relax the within-season closure assumption common to most occupancy models. Optimal timing of surveys in our study areas was approximately 5–30 March. Averaged across years, estimated probability of occupancy was 0.58 (SE = 0.09) for historical sites and 0.19 (SE = 0.08) for control sites. Occupancy increased from 2013 through 2019. Notably, even though observer error was trivial, annual detection probabilities varied from 0.23 to 0.75 and declined during the study; this means naïve occupancy values would have been misleading, indicating apparent declines in toad occupancy. Occupancy was lowest during the first year of the study, possibly due to changes in stream flows and conditions in many waterbodies following extended drought and recent wildfires. Although within-season closure was violated by variable calling phenology, simple multi-season models provided nearly identical estimates as staggered-entry models. Surprisingly, extinction probability was unrelated to the number of years since the first or last record at historically occupied sites. Collectively, our results suggest a lack of large, recent declines in occupancy by Arizona Toads in New Mexico, but we still lack population information from most of the species' range.
Old-growth forests serve as critical habitat for many sensitive species, but management practices have diminished their prevalence, and former regions of old-growth are now dominated by second-growth stands lacking the structural heterogeneity, diversity, and species richness that these older forests possess. In western Washington state in the Pacific Northwest of the United States, the Olympic Habitat Development Study was designed to address this issue and hasten the development of specific old-growth features in second-growth stands using variable-density thinning. One concern with such methods, however, is the potential to introduce non-native plants, which can have negative ecological and economic impacts. Here, we examine how variable-density thinning influences desirable forest characteristics, such as increased plant species diversity, versus the less desirable effects of non-native plant species introduction. We test two hypotheses regarding plant invasions. First, thinning would promote establishment of non-native, shade-intolerant species, but their abundance would gradually decline over time. Second, thinning disturbance and increased heterogeneity of canopy cover would initially promote understory richness of all species, although richness would decline over time with canopy closure and increased cover of shrubs and regenerating trees. We found that the number and cover of non-native species initially increased after thinning, peaking at 16 species present in variable-density thinned treatments in year three. By year 17, 11 species remained throughout the seven 6.5 ha treatment plots sampled, and cover was negligible. As predicted, species richness increased following thinning, however, native species richness remained elevated through year 17, contrary to our hypothesis. Furthermore, native species diversity also increased following thinning and remained higher in thinned treatments than controls through year 17. Our results show that variable-density thinning in temperate coniferous forests can enhance native, but not exotic, plant richness and diversity in the long term.
Discoveries in the 1980s greatly expanded speleologists’ understanding of the role that hypogenic groundwater flow can play in developing caves at depth. Ascending groundwater charged with carbon dioxide and, especially, hydrogen sulfide can readily dissolve carbonate bedrock just below and above the water table. Sulfuric acid speleogenesis, in which anoxic, rising, sulfidic groundwater mixes with oxygenated cave atmosphere to form aggressive sulfuric acid (H2SO4) formed spectacular caves in Carlsbad Caverns National Park, USA. Cueva de Villa Luz in Mexico provides an aggressively active example of sulfuric acid speleogenesis processes, and the Frasassi Caves in Italy preserve the results of sulfuric acid speleogenesis in its upper levels while sulfidic groundwater currently enlarges cave passages in the lower levels.
Many caves in east-central Nevada and western Utah (USA) are products of hypogenic speleogenesis and formed before the current topography fully developed. Wet climate during the late Neogene and Pleistocene brought extensive meteoric infiltration into the caves, and calcite speleothems (e.g., stalactites, stalagmites, shields) coat the walls and floors of the caves, concealing evidence of the earlier hypogenic stage. However, by studying the speleogenetic features in well-established sulfuric acid speleogenesis caves, evidence of hypogenic, probably sulfidic, speleogenesis in many Great Basin caves can be teased out. Compelling evidence of hypogenic speleogenesis in these caves include folia, mammillaries, bubble trails, cupolas, and metatyuyamunite. Sulfuric acid speleogenesis signs include hollow coralloid stalagmites, trays, gypsum crust, pseudoscallops, rills, and acid pool notches. Lehman Caves in Great Basin National Park is particularly informative because a low-permeability capstone protected about half of the cave from significant meteoric infiltration, preserving early speleogenetic features.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field Excursions from the 2021 GSA Section Meetings","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2020.0061(05)","usgsCitation":"Hose, L.D., DuChene, H.R., Jones, D., Baker, G.M., Havlena, Z., Sweetkind, D.S., and Powell, D., 2021, Hypogenic karst of the Great Basin, chap. of Field Excursions from the 2021 GSA Section Meetings, v. 61, p. 77-114, https://doi.org/10.1130/2020.0061(05).","productDescription":"38 p.","startPage":"77","endPage":"114","ipdsId":"IP-124815","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":450693,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/fld.s.16620391.v1","text":"External Repository"},{"id":392721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"New Mexico, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.172119140625,\n 31.952162238024975\n ],\n [\n -104.161376953125,\n 31.952162238024975\n ],\n [\n -104.161376953125,\n 32.59310597426537\n ],\n [\n -105.172119140625,\n 32.59310597426537\n ],\n [\n -105.172119140625,\n 31.952162238024975\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.79589843749999,\n 39.027718840211605\n ],\n [\n -114.169921875,\n 39.027718840211605\n ],\n [\n -114.169921875,\n 40.88029480552824\n ],\n [\n -115.79589843749999,\n 40.88029480552824\n ],\n [\n -115.79589843749999,\n 39.027718840211605\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.59277343749999,\n 17.97873309555617\n ],\n [\n -90.7470703125,\n 17.97873309555617\n ],\n [\n -90.7470703125,\n 18.979025953255267\n ],\n [\n -92.59277343749999,\n 18.979025953255267\n ],\n [\n -92.59277343749999,\n 17.97873309555617\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hose, Louise D.","contributorId":269963,"corporation":false,"usgs":false,"family":"Hose","given":"Louise","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":828185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DuChene, Harvey R.","contributorId":269964,"corporation":false,"usgs":false,"family":"DuChene","given":"Harvey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":828186,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Daniel","contributorId":269965,"corporation":false,"usgs":false,"family":"Jones","given":"Daniel","affiliations":[],"preferred":false,"id":828187,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Gretchen M.","contributorId":54894,"corporation":false,"usgs":true,"family":"Baker","given":"Gretchen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":828188,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Havlena, Zoe","contributorId":269966,"corporation":false,"usgs":false,"family":"Havlena","given":"Zoe","email":"","affiliations":[],"preferred":false,"id":828189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sweetkind, Donald S. 0000-0003-0892-4796 dsweetkind@usgs.gov","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":139913,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":828190,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Powell, Doug","contributorId":269967,"corporation":false,"usgs":false,"family":"Powell","given":"Doug","email":"","affiliations":[],"preferred":false,"id":828191,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70230597,"text":"70230597 - 2021 - Pathology and mineralogy demonstrate respirable crystalline silica is a major cause of severe pneumoconiosis in US coal miners","interactions":[],"lastModifiedDate":"2022-04-18T11:40:55.030702","indexId":"70230597","displayToPublicDate":"2021-09-24T06:37:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10563,"text":"Annals of the American Thoracic Society","active":true,"publicationSubtype":{"id":10}},"title":"Pathology and mineralogy demonstrate respirable crystalline silica is a major cause of severe pneumoconiosis in US coal miners","docAbstract":"Populations of the green turtle (Chelonia mydas), a mega-herbivore that consumes seagrasses, are recovering worldwide. Understanding green turtle adaptations to herbivory and responses to changes in seagrass availability will be critical to interpreting plant–herbivore interactions as green turtle populations continue to rebound. Ingesta particle size and diet composition of two green turtle foraging aggregations (Bermuda, 32.3° N, 64.8° W; U.S. Virgin Islands [USVI], 17.8° N, 64.6° W) in the Northwest Atlantic (NWA) were evaluated to assess the prevalence of herbivory across foraging sites and life stages, determine if there is an optimum ingesta particle size, and evaluate green turtle responses to changes in seagrass availability. Both aggregations were herbivorous (> 90% seagrass/algae) across size classes (straight carapace length, SCL). Ingesta particle size (mean ± SD) did not differ between Bermuda (2.6 ± 1.4 cm) and the USVI (2.3 ± 1.2 cm). Of seagrass leaves ingested, 20–30% were 1.7 cm in length, indicating a potential optimum for maximizing digestion rates. Turtle size (SCL) had a significant effect on particle size in Bermuda (p = 0.01, R2 = 0.16) (35.1 ± 9.9 cm SCL) but not in the USVI aggregation, which was comprised of larger turtles (49.0 ± 6.1 cm SCL). In Bermuda, there was no apparent response to the declines in seagrass availability. Ingesta particle size and volume of seagrass leaves did not decline from 2015 to 2019, nor was there an increase in volume of seagrass roots and rhizomes. These results indicate herbivory is prevalent across size classes at two NWA foraging sites and ingesta particle size has important implications for optimizing the green turtle grazing strategy and facilitating ontogenetic diet shifts to herbivory in juveniles. Ingesta particle size is a valuable tool for assessing green turtle responses to seagrass declines that should be interpreted within the context of population demographics.
Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2021.112685","usgsCitation":"Seegers, B., Werdell, P., Vandermeulen, R., Salls, W., Stumpf, R., Schaeffer, B., Owens, T., Bailey, S., Scott, J., and Loftin, K.A., 2021, Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a: Remote Sensing of the Environment, v. 266, 112685, 14 p., https://doi.org/10.1016/j.rse.2021.112685.","productDescription":"112685, 14 p.","ipdsId":"IP-129074","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":450699,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2021.112685","text":"Publisher Index Page"},{"id":392623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.42675781249999,\n 43.229195113965005\n ],\n [\n -89.2529296875,\n 43.229195113965005\n ],\n [\n -89.2529296875,\n 49.15296965617042\n ],\n [\n -97.42675781249999,\n 49.15296965617042\n ],\n [\n -97.42675781249999,\n 43.229195113965005\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.078125,\n 53.74871079689897\n ],\n [\n -128.32031249999997,\n 55.677584411089526\n ],\n [\n -134.82421875,\n 60.75915950226991\n ],\n [\n -139.5703125,\n 61.438767493682825\n ],\n [\n -140.09765625,\n 69.71810669906763\n ],\n [\n -156.09375,\n 71.85622888185527\n ],\n [\n -166.2890625,\n 68.84766505841037\n ],\n [\n -167.6953125,\n 65.29346780107583\n ],\n [\n -166.2890625,\n 59.44507509904714\n ],\n [\n -161.89453125,\n 54.36775852406841\n ],\n [\n -153.80859375,\n 55.87531083569679\n ],\n [\n -145.01953124999997,\n 59.80063426102869\n ],\n [\n -134.47265625,\n 55.07836723201515\n ],\n [\n -132.36328125,\n 51.83577752045248\n ],\n [\n -131.1328125,\n 52.05249047600099\n ],\n [\n -130.078125,\n 53.74871079689897\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"266","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Seegers, Bridget","contributorId":269867,"corporation":false,"usgs":false,"family":"Seegers","given":"Bridget","affiliations":[{"id":37453,"text":"National Aeronautics and Space Administration","active":true,"usgs":false}],"preferred":false,"id":828030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werdell, P. 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The Colorado River Salinity Control Act of 1974 (Public Law 93–320) authorized “the construction, operation, and maintenance of certain works in the Colorado River Basin to control the salinity of water delivered to users in the United States and Mexico.” Water-quality standards for salinity in the lower Colorado River Basin were adopted in 1975. To help meet these standards, the Bureau of Reclamation, Natural Resource Conservation Service, and States within the Colorado River Basin have implemented salinity control projects that focus on reducing salt loading associated with irrigated agriculture by improving water delivery systems and water management practices. The term salinity is synonymous with dissolved solids in this report.
The Bureau of Reclamation, in conjunction with the Colorado River Basin Salinity Control Forum, was interested in determining the contribution of dissolved solids from Blacks Fork above Smiths Fork to the Colorado River and initiated a study of Blacks Fork above Smiths Fork in 2018. In early 2018, the U.S. Geological Survey installed a streamgage at the most downstream location on the Blacks Fork, upstream from the convergence with Smiths Fork, to characterize the stream. The Blacks Fork above Smiths Fork, near Lyman, Wyoming, streamgage (U.S. Geological Survey identifier 09219200) was operated from April 4, 2018, through September 30, 2019, collecting continuous stream stage and specific-conductance data, from which continuous discharge, dissolved-solids concentrations, and dissolved-solids loads were calculated. Seven sites were selected on Blacks Fork and a tributary to describe a snapshot of the discharge and dissolved-solids characteristics. These sites were sampled during July, August, and September 2018 and June, July, August, and September 2019 report.
Discharge at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) from April through September in 2018 was lower and less variable than during the same period in 2019. The mean daily (mean of the daily means) discharge during those 6 months in 2018 (15.1 cubic feet per second [ft3/s]) was about one-tenth of the discharge during the same period in 2019 (152 ft3/s). The cumulative monthly discharge during April through September in 2018 was 5,360 acre-feet, about one-tenth of the discharge during the same period in 2019 which was 54,700 acre-feet. Similar differences in discharge between the 2018 and 2019 periods also are noted at other Blacks Fork streamgages in the area.
Continuous specific conductance data and the statistical relation between specific conductance and dissolved-solids concentrations were used to calculate the daily mean dissolved-solids concentrations. Dissolved solids often have an inverse relation with discharge because higher discharges typically have a diluting effect that lowers the dissolved-solids concentrations. In general, when discharges at the Blacks Fork above Smiths Fork streamgage (09219200) are higher, dissolved-solids concentrations are generally lower. However, the high dissolved-solids concentrations that are measured during high discharges indicate that the system has natural variability and the dissolved-solids concentrations are determined by more factors than just discharge. The mean daily dissolved-solids concentration during April through September 2018 was 1,630 milligrams per liter and during the same period in 2019 was 1,100 milligrams per liter.
Dissolved-solids loads were calculated as the product of the discharge and dissolved-solids concentration. The daily mean dissolved-solids loads during 2018 were typically lower than during 2019. This result is primarily because the discharge was much lower in 2018 than in 2019. Therefore, although the daily mean dissolved-solids concentrations tended to be higher in 2018, the substantially higher discharges in 2019 had more of an effect on the dissolved-solids loads than the dissolved-solids concentrations.
The cumulative dissolved-solids load at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) during the 18-month study was 81,200 tons, with a mean daily load of 149 tons per day. During the 6-month period from April through September 2018, the cumulative dissolved-solids load at the streamgage was estimated to be 8,740 tons and, during the same 6 months in 2019, the cumulative dissolved-solids load was estimated to be 60,900 tons. During the fall and winter between the two periods, the cumulative dissolved-solids load was 11,600 tons.
Discharge and dissolved-solids concentrations from samples collected during the synoptic sampling events were highly variable among most sites during most synoptic sampling events and also highly variable at most sites among different sampling events. The two sites upstream from the tributary input from Threemile Creek had lower dissolved-solids concentrations than sites including and downstream from the tributary. Sites including and downstream from the tributary had similar values and variability of dissolved-solids loads, with the exception of the farthest downstream site at the Blacks Fork above Smiths Fork, near Lyman, Wyo., streamgage (09219200) that tended to have larger dissolved-solids loads and higher variability among synoptic sampling events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215095","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Eddy-Miller, C.A., Wheeler, J.D., Law, R.M., and Moran, S.W., 2021, Discharge and dissolved-solids characteristics of Blacks Fork above Smiths Fork, Wyoming, April 2018 through September 2019: U.S. Geological Survey Scientific Investigations Report 2021–5095, 32 p., https://doi.org/10.3133/sir20215095.","productDescription":"vii, 32 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-125542","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":389699,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5095/sir20215095.xml","size":"220 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5095 xml"},{"id":389653,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5095/sir20215095.pdf","text":"Report","size":"2.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5095"},{"id":389652,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5095/coverthb3.jpg"}],"contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
521 Progress Circle, Suite 6
Cheyenne, WY 82007
Surface-water and groundwater resources in the Big Lost River Basin of south-central Idaho are extensively interconnected; this interchange affects and is affected by water-resource management for irrigated agriculture and other uses in the basin. Concerns from water users regarding declining groundwater levels, declining streamflows, and drought helped motivate an updated evaluation of water resources in the Big Lost River Basin. The hydrogeologic framework presented in this report provides a conceptual basis for understanding groundwater resources in the Big Lost River Basin and comprises three major parts: (1) conceptual description of four hydrogeologic units, (2) development of a three-dimensional hydrogeologic framework model representing the spatial distribution of the hydrogeologic units, and (3) a description of groundwater occurrence and movement. This hydrogeologic framework represents the first of three planned reports describing water resources in the Big Lost River Basin; subsequent reports are intended to present a groundwater budget for the basin and to describe the results of a series of events measuring gains to and losses from streamflow in the Big Lost River. This report was prepared by the U.S. Geological Survey in cooperation with the Idaho Department of Water Resources.
The Big Lost River Basin has four hydrogeologic units. First, the Quaternary unconsolidated sediments unit comprises the basin-fill alluvial aquifer and generally is used within 250 feet of the land surface. The Quaternary unconsolidated sediments unit is spatially heterogeneous, with locally confining conditions in some areas, and is the most heavily used hydrogeologic unit in the basin. Second, the Paleozoic sedimentary rocks unit, composed primarily of carbonates with some siliciclastic rocks, represents the major bedrock aquifer and contributes subsurface recharge at the margins of the alluvial aquifer. Third, the Tertiary volcanic rocks unit, composed primarily of andesite and dacite with lesser tuff, is locally important to water production, particularly in faulted and fractured zones. The Paleozoic sedimentary rocks hydrogeologic unit occurs at the valley margins and underlies tributaries throughout the basin, whereas the Tertiary volcanic rocks hydrogeologic unit primarily occurs in uplands in the western one-half of the basin. Fourth, the Quaternary basalt rocks unit consists of multiple basalt flows that are interbedded with the Quaternary unconsolidated sediments unit in the southern end of the Big Lost River Basin and contains at least three water-bearing zones. Insights gained from this updated hydrogeologic framework will help inform current water-resource management in the Big Lost River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215078A","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Zinsser, L.M., 2021, Hydrogeologic framework of the Big Lost River Basin, south-central Idaho, chap. A of Zinsser, L.M., ed., Characterization of water resources in the Big Lost River Basin, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2021–5078–A, 42 p., https://doi.org/10.3133/sir20215078A.","productDescription":"Report: viii, 42 p.; Appendix; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-125228","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":396956,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A.XML"},{"id":396955,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/images"},{"id":389624,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P911S9LF","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic framework of the Big Lost River Basin, south-central Idaho—Hydrogeologic framework model and well data"},{"id":389623,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A_app1.pdf","text":"Appendix 1","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078A Appendix 1"},{"id":389622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/sir20215078A.pdf","text":"Report","size":"8.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5078A"},{"id":389621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/coverthb.jpg"},{"id":409279,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5078/a/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2021-5078A Version History"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.169921875,\n 43.229195113965005\n ],\n [\n -112.2802734375,\n 43.229195113965005\n ],\n [\n -112.2802734375,\n 44.15068115978094\n ],\n [\n -114.169921875,\n 44.15068115978094\n ],\n [\n -114.169921875,\n 43.229195113965005\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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The Earth Resources Observation and Science (EROS) Center is the largest facility of its kind within the U.S. Geological Survey. As both a science and data center, EROS serves a unique and critical role in shaping our understanding of a changing planet.
EROS opened its doors in 1973 as a receiving station, data archive, and data distribution hub for the USGS Landsat series of Earth observing satellites. In the nearly five decades since, EROS has grown into a globally recognized leader in land change science.
Warming of lake surface waters has become a concern to limnologists and water managers because air temperatures, which directly affect near-surface water temperatures, are projected to increase in Wisconsin (WICCI 2011) as well as globally (IPCC 2018). This projected increase is in addition to the changes in air temperatures that have already occurred in recent decades(WICCI 2011, NOAA 2017).The deleterious effects of increased temperatures in lake surface waters have been extensively reviewed (e.g., Blenckner 2005, Keller 2007, Adrian et al. 2009, George 2010). Briefly, the exceedance of thermal preferences or tolerances of aquatic biota can cause altered food webs and loss of biodiversity in lakes (DeStasio et al. 1996, Chu et al. 2005, Graham and Harrod 2009, Woodward et al. 2010, Comte et al. 2013). Warmer surface water temperature scan result in stronger and longer thermal stratification in deep lakes(Robertson and Ragotzkie1990, Hondzo and Stefan 1993, Livingstone 2003, Butcher et al. 2015). This process in turn can cause the duration and extent of hypolimnetic anoxia to increase, thus reducing hypolimnetic refugia needed for cold-and cool-water fish (De Stasio et al. 1996, Magnuson et al. 1997, Jeppesen et al. 2012, Missaghi et al. 2017). Longer duration of hypolimnetic anoxia can enhance eutrophication because of more internal loading of phosphorus from bottom sediments (Blenckner et al. 2002, North et al. 2014). Of particular concern, warmer water temperatures favor the growth of toxic cyanobacteria in eutrophic systems (Paerl and Huisman 2008, Wagner and Adrian 2009, Kosten et al. 2012).Another effect of warmer lake surface temperatures is increased evaporation that can result in lower water levels(Spence et al. 2013, Gronewold and Stow 2014).
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Baddeleyite, zirconolite, and zircon, in that sequence, formed in hornblende + biotite granites (type 1) and hedenbergite–fayalite granites (type 2). The peralkaline microgranite (type 3) of Ailsa Craig contains zircon, dalyite, a eudialyte-group mineral, a fibrous phase which is possibly lemoynite, and Zr-bearing aegirine. Hydrothermal zircon is also present in all three granite types and documents the transition from a silicate-melt environment to an incompatible element-rich aqueous-dominated fluid. No textures indicative of inherited zircon were observed. The minerals crystallized in stages from magmatic through late-magmatic to hydrothermal. The zirconolite and eudialyte-group mineral are notably Y+REE-rich (REE signifies rare earth element). The crystallization sequence of the minerals may have been related to the activities of Si and Ca, to melt peralkalinity, and to local disequilibrium.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ejm-33-537-2021","usgsCitation":"Belkin, H.E., and MacDonald, R., 2021, Zirconium-bearing accessory minerals in UK Paleogene granites: Textural, compositional, and paragenetic relationships: European Journal of Mineralogy, v. 37, p. 537-570, https://doi.org/10.5194/ejm-33-537-2021.","productDescription":"34 p.","startPage":"537","endPage":"570","ipdsId":"IP-124385","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":450702,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ejm-33-537-2021","text":"Publisher Index Page"},{"id":413625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Northern Ireland, Scotland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -4.371029936775869,\n 57.27175687671797\n ],\n [\n -7.259167863003029,\n 57.27175687671797\n ],\n [\n -7.259167863003029,\n 54.061864482791236\n ],\n [\n -4.371029936775869,\n 54.061864482791236\n ],\n [\n -4.371029936775869,\n 57.27175687671797\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Belkin, Harvey E. 0000-0001-7879-6529 hbelkin@usgs.gov","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":581,"corporation":false,"usgs":true,"family":"Belkin","given":"Harvey","email":"hbelkin@usgs.gov","middleInitial":"E.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":865503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"MacDonald, Ray","contributorId":9704,"corporation":false,"usgs":true,"family":"MacDonald","given":"Ray","email":"","affiliations":[],"preferred":false,"id":865504,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70224408,"text":"sir20215071 - 2021 - Origin of unconsolidated Quaternary deposits at Harriet Point near Redoubt Volcano, Alaska","interactions":[],"lastModifiedDate":"2021-09-23T16:53:40.644109","indexId":"sir20215071","displayToPublicDate":"2021-09-23T09:25:43","publicationYear":"2021","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":"2021-5071","displayTitle":"Origin of Unconsolidated Quaternary Deposits at Harriet Point near Redoubt Volcano, Alaska","title":"Origin of unconsolidated Quaternary deposits at Harriet Point near Redoubt Volcano, Alaska","docAbstract":"Unconsolidated boulder-rich diamicton units exposed in sea cliffs at Harriet Point southeast of Redoubt Volcano were evaluated to better understand their provenance relative to the late Quaternary eruptive history of the volcano. A previous study concluded that deposits at Harriet Point were emplaced by a large volcanic landslide originating on the southeast flank of Redoubt Volcano (Begét and Nye, 1994). Field-based analysis of the stratigraphy and sedimentology of the Harriet Point deposits and numerical simulations of the volcanic landslide area of inundation indicate that none of the deposits are volcanogenic. All of the unconsolidated boulder-rich diamicton units at Harriet Point are glacial in origin and can be reconciled using the presently available model for late Quaternary glaciation of Cook Inlet.
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Anchorage, AK 99508
The Harney Basin is a closed river basin in southeastern Oregon. Surface water in the basin is used for a variety of social, economic, and ecological benefits. While some surface water uses compete with one another, others are complementary or jointly produce multiple beneficial outcomes. The objective of this study is to conduct an economic assessment of surface water in the basin as it relates to wet meadow pasture production and outdoor recreation. Given the complex interactions between surface water management on public and private land and the various goods and services that are derived from adequate water resources, an economic assessment of surface water management can be used to assist future decision making in the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211087","usgsCitation":"Bair, L.S., Flyr, M., and Huber, C., 2021, Economic assessment of surface water in the Harney Basin, Oregon: U.S. Geological Survey Open-File Report 2021-1087, 43 p., https://doi.org/10.3133/ofr20211087.","productDescription":"vii, 43 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-122032","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":389611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1087/covrthb.jpg"},{"id":389612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1087/ofr20211087.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.05859375,\n 42.24478535602799\n ],\n [\n -117.454833984375,\n 42.24478535602799\n ],\n [\n -117.454833984375,\n 44.38669150215206\n ],\n [\n -120.05859375,\n 44.38669150215206\n ],\n [\n -120.05859375,\n 42.24478535602799\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"This paper considers mutualistic interactions between two consumers, in which one consumer can consume a resource only by exchange of service for service with the other. By rigorous analysis on the one-resource and two-consumer model with Holling-type I response, we show periodic oscillations and tri-stability in the mutualism system: when their initial densities decrease, the consumers' interaction outcomes would change from coexistence in periodic oscillation, to persistence at a steady state, and to extinction. Under certain conditions, we also show two types of bi-stability in the system: the consumers would change from coexisting in periodic oscillation (resp. at a steady state) to going to extinction when their initial densities decrease. Then we analyze a modified system with Holling-type II response. Based on theoretical analysis and numerical computation, we show that there also exist tri-stability and two types of bi-stability in this system. Moreover, it is shown that varying the degree of obligation can lead to transition of interaction outcomes between coexistence in periodic oscillation (resp. at a steady state) and extinction of both consumers. These results are important in understanding complexity in mutualism.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jmaa.2021.125672","usgsCitation":"Wang, Y., Wu, H., and DeAngelis, D.L., 2021, Periodic oscillation and tri-stability in mutualism systems with two consumers: Journal of Mathematical Analysis and Applications, v. 506, no. 2, 125672, https://doi.org/10.1016/j.jmaa.2021.125672.","productDescription":"125672","ipdsId":"IP-131197","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":408694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Yuanshi","contributorId":207814,"corporation":false,"usgs":false,"family":"Wang","given":"Yuanshi","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":855730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Hong","contributorId":207815,"corporation":false,"usgs":false,"family":"Wu","given":"Hong","email":"","affiliations":[{"id":37637,"text":"School of Mathematics and Computational Science Sun Yat-sen University","active":true,"usgs":false}],"preferred":false,"id":855731,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":855732,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224528,"text":"70224528 - 2021 - Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016","interactions":[],"lastModifiedDate":"2021-11-01T16:02:45.091989","indexId":"70224528","displayToPublicDate":"2021-09-23T08:38:20","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016","docAbstract":"The Arctic Ocean is undergoing rapid transformation toward a seasonally ice-free ecosystem. As ice-adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food-web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska's SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite-telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8139","usgsCitation":"Bromaghin, J.F., Douglas, D.C., Durner, G.M., Simac, K.S., and Atwood, T.C., 2021, Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016: Ecology and Evolution, v. 11, no. 20, p. 14250-14267, https://doi.org/10.1002/ece3.8139.","productDescription":"18 p.","startPage":"14250","endPage":"14267","ipdsId":"IP-125254","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":450707,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.8139","text":"External Repository"},{"id":389724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -166.2890625,\n 68.23682270936281\n ],\n [\n -156.4453125,\n 71.24435551310674\n ],\n [\n -140.9765625,\n 69.59589006237648\n ],\n [\n -141.15234374999997,\n 76.24781659441473\n ],\n [\n -166.55273437499997,\n 76.03731657616542\n ],\n [\n -166.2890625,\n 68.23682270936281\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"20","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823893,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simac, Kristin S. 0000-0002-4072-1940 ksimac@usgs.gov","orcid":"https://orcid.org/0000-0002-4072-1940","contributorId":131096,"corporation":false,"usgs":true,"family":"Simac","given":"Kristin","email":"ksimac@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":823894,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":823895,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228980,"text":"70228980 - 2021 - Modelling presence versus abundance for invasive species risk assessment","interactions":[],"lastModifiedDate":"2022-02-25T14:26:41.787468","indexId":"70228980","displayToPublicDate":"2021-09-23T08:22:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Modelling presence versus abundance for invasive species risk assessment","docAbstract":"Invasive species prevention and management can be guided by comparisons of invasion risk across space and among species. Species distribution models are widely used to assess invasion risk and typically estimate suitability for species presence. However, suitability for presence may not capture patterns of abundance and impact. We asked how models estimating suitability for presence versus suitability for abundance aligned in their implications for risk assessment.
Western United States.
We developed ensembles of species distribution models for presence and for abundance for four invasive plants. We visualized the distribution of presence and abundance in environmental and geographic space and compared model outputs using criteria relevant for decision-making: a comparison of risk across management units for each species, and a ranking of risk among species for each management unit.
We found good overall agreement between models of presence versus abundance in the relative risk across management units and among species. However, the area predicted to be suitable for invasive species presence was often substantially higher than the area predicted to be suitable for abundance, especially within uninvaded management units.
Models of suitability for invasive species presence and abundance yielded similar assessments of relative risk in comparisons across space and species. In addition, we found patterns of presence and abundance in environmental space can guide modelling decisions and model interpretation. Suitability for abundance can improve relative risk assessment when abundance locations occupy a well-defined subset of the environmental space corresponding to presence. Where abundance locations occur throughout this environmental space, as was particularly striking for Taeniatherum caput-medusae, suitability for presence may better reflect risk of ongoing population increases and spread. This species is at risk of becoming abundant across a substantial portion of the western United States.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13414","usgsCitation":"Jarnevich, C.S., Sofaer, H., and Engelstad, P., 2021, Modelling presence versus abundance for invasive species risk assessment: Diversity and Distributions, v. 27, no. 12, p. 2454-2464, https://doi.org/10.1111/ddi.13414.","productDescription":"11 p.","startPage":"2454","endPage":"2464","ipdsId":"IP-123563","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450709,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13414","text":"Publisher Index Page"},{"id":436188,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MVEPP4","text":"USGS data release","linkHelpText":"Presence and abundance data and models for four invasive plant species"},{"id":396476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":836066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sofaer, Helen 0000-0002-9450-5223","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":216681,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":836067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Engelstad, Peder","contributorId":238758,"corporation":false,"usgs":false,"family":"Engelstad","given":"Peder","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":836068,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70224629,"text":"70224629 - 2021 - Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance","interactions":[],"lastModifiedDate":"2021-11-16T15:49:41.376419","indexId":"70224629","displayToPublicDate":"2021-09-23T08:21:55","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance","docAbstract":"A respiratory disease epizootic at the National Bison Range (NBR) in Montana in 2016–2017 caused an 85% decline in the bighorn sheep population, documented by observations of its unmarked but individually identifiable members, the subjects of an ongoing long-term study. The index case was likely one of a small group of young bighorn sheep on a short-term exploratory foray in early summer of 2016. Disease subsequently spread through the population, with peak mortality in September and October and continuing signs of respiratory disease and sporadic mortality of all age classes through early July 2017. Body condition scores and clinical signs suggested that the disease affected ewe groups before rams, although by the end of the epizootic, ram mortality (90% of 71) exceeded ewe mortality (79% of 84). Microbiological sampling 10 years to 3 months prior to the epizootic had documented no evidence of infection or exposure to Mycoplasma ovipneumoniae at NBR, but during the epizootic, a single genetic strain of M. ovipneumoniae was detected in affected animals. Retrospective screening of domestic sheep flocks near the NBR identified the same genetic strain in one flock, presumptively the source of the epizootic infection. Evidence of fatal lamb pneumonia was observed during the first two lambing seasons following the epizootic but was absent during the third season following the death of the last identified M. ovipneumoniae carrier ewe. Monitoring of life-history traits prior to the epizootic provided no evidence that environmentally and/or demographically induced nutritional or other stress contributed to the epizootic. Furthermore, the epizootic occurred despite proactive management actions undertaken to reduce risk of disease and increase resilience in this population. This closely observed bighorn sheep epizootic uniquely illustrates the natural history of the disease including the (presumptive) source of spillover, course, severity, and eventual pathogen clearance.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8166","usgsCitation":"Besser, T., Cassirer, E.F., Lisk, A., Nelson, D., Manlove, K.R., Cross, P., and Hogg, J.T., 2021, Natural history of a bighorn sheep pneumonia epizootic: Source of infection, course of disease, and pathogen clearance: Ecology and Evolution, v. 11, no. 21, p. 14366-14382, https://doi.org/10.1002/ece3.8166.","productDescription":"17 p.","startPage":"14366","endPage":"14382","ipdsId":"IP-126913","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8166","text":"Publisher Index Page"},{"id":390113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"National Bison Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.51873779296875,\n 47.148633511301426\n ],\n [\n -113.93646240234375,\n 47.148633511301426\n ],\n [\n -113.93646240234375,\n 47.57837853860192\n ],\n [\n -114.51873779296875,\n 47.57837853860192\n ],\n [\n -114.51873779296875,\n 47.148633511301426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"21","noUsgsAuthors":false,"publicationDate":"2021-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Besser, T. E.","contributorId":266154,"corporation":false,"usgs":false,"family":"Besser","given":"T. E.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":824438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassirer, E. Frances","contributorId":198303,"corporation":false,"usgs":false,"family":"Cassirer","given":"E.","email":"","middleInitial":"Frances","affiliations":[],"preferred":false,"id":824439,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisk, Amy","contributorId":266155,"corporation":false,"usgs":false,"family":"Lisk","given":"Amy","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":824440,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Danielle","contributorId":266156,"corporation":false,"usgs":false,"family":"Nelson","given":"Danielle","email":"","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":824441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manlove, Kezia R.","contributorId":198305,"corporation":false,"usgs":false,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":824442,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":824443,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hogg, John T.","contributorId":245903,"corporation":false,"usgs":false,"family":"Hogg","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":824444,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224529,"text":"70224529 - 2021 - Evidence for humans in North America during the Last Glacial Maximum","interactions":[],"lastModifiedDate":"2021-09-24T13:39:08.628097","indexId":"70224529","displayToPublicDate":"2021-09-23T08:19:29","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for humans in North America during the Last Glacial Maximum","docAbstract":"Archaeologists and researchers in allied fields have long sought to understand human colonization of North America. When, how, and from where did people migrate, and what were the consequences of their arrival for the established fauna and landscape are enduring questions. Here, we present evidence from excavated surfaces of in situ human footprints from White Sands National Park (New Mexico, USA), where multiple human footprints are stratigraphically constrained and bracketed by seed layers that yield calibrated ages between ~23 and 21 ka. These findings confirm the presence of humans in North America during the Last Glacial Maximum, adding evidence to the antiquity of human colonization of the Americas, and provide a temporal range extension for the co-existence of early inhabitants and Pleistocene megafauna.","language":"English","doi":"10.1126/science.abg7586","usgsCitation":"Bennett, M.R., Bustos, D., Pigati, J.S., Springer, K.B., Urban, T.M., Holliday, V.T., Reynolds, S.C., Budka, M., Honke, J.S., Hudson, A.M., Fenerty, B., Connelly, C., Martinez, P., Santucci, V.L., and Odess, D., 2021, Evidence for humans in North America during the Last Glacial Maximum: Science, p. 1528-1531, https://doi.org/10.1126/science.abg7586.","productDescription":"4 p.","startPage":"1528","endPage":"1531","ipdsId":"IP-125967","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":450714,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eprints.bournemouth.ac.uk/36202/7/science_manuscript_WHSA_rev3_17Aug21.pdf","text":"External Repository"},{"id":436190,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ABZEM9","text":"USGS data release","linkHelpText":"Data release for Evidence of humans in North America during the Last Glacial Maximum"},{"id":389708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"White Sands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.49734497070312,\n 32.62434010409917\n ],\n [\n -106.12792968749999,\n 32.62434010409917\n ],\n [\n -106.12792968749999,\n 32.90495631913751\n ],\n [\n -106.49734497070312,\n 32.90495631913751\n ],\n [\n -106.49734497070312,\n 32.62434010409917\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bennett, Matthew R.","contributorId":265968,"corporation":false,"usgs":false,"family":"Bennett","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":54847,"text":"Bournemouth University, U.K.","active":true,"usgs":false}],"preferred":false,"id":823896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bustos, David","contributorId":265969,"corporation":false,"usgs":false,"family":"Bustos","given":"David","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823898,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823899,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Urban, Thomas. M.","contributorId":265970,"corporation":false,"usgs":false,"family":"Urban","given":"Thomas.","email":"","middleInitial":"M.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":823900,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holliday, Vance T.","contributorId":265971,"corporation":false,"usgs":false,"family":"Holliday","given":"Vance","email":"","middleInitial":"T.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":823901,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reynolds, Sally C.","contributorId":265972,"corporation":false,"usgs":false,"family":"Reynolds","given":"Sally","email":"","middleInitial":"C.","affiliations":[{"id":54847,"text":"Bournemouth University, U.K.","active":true,"usgs":false}],"preferred":false,"id":823902,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Budka, Marcin","contributorId":265973,"corporation":false,"usgs":false,"family":"Budka","given":"Marcin","email":"","affiliations":[{"id":54847,"text":"Bournemouth University, U.K.","active":true,"usgs":false}],"preferred":false,"id":823903,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Honke, Jeffrey S. 0000-0003-4357-9297 jhonke@usgs.gov","orcid":"https://orcid.org/0000-0003-4357-9297","contributorId":201389,"corporation":false,"usgs":true,"family":"Honke","given":"Jeffrey","email":"jhonke@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823904,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":823905,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fenerty, Brendan","contributorId":261639,"corporation":false,"usgs":false,"family":"Fenerty","given":"Brendan","email":"","affiliations":[{"id":52636,"text":"Department of Geosciences, University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":823906,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Connelly, Clare","contributorId":265974,"corporation":false,"usgs":false,"family":"Connelly","given":"Clare","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823907,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Martinez, Patrick J.","contributorId":239661,"corporation":false,"usgs":false,"family":"Martinez","given":"Patrick J.","affiliations":[{"id":47955,"text":"Colorado Division of Wildlife, retired; USFWS, retired","active":true,"usgs":false}],"preferred":false,"id":823908,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Santucci, Vincent L.","contributorId":192886,"corporation":false,"usgs":false,"family":"Santucci","given":"Vincent","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":823909,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Odess, Daniel","contributorId":265975,"corporation":false,"usgs":false,"family":"Odess","given":"Daniel","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":823910,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70230404,"text":"70230404 - 2021 - Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida","interactions":[],"lastModifiedDate":"2022-04-12T13:20:09.477273","indexId":"70230404","displayToPublicDate":"2021-09-23T08:12:11","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida","docAbstract":"This project evaluated habitat conditions for two species found in the imperiled pine rockland ecosystem—the Rim Rock Crowned Snake (Tantilla oolitica) and the Key Ring-Necked Snake (Diadophis punctatus acricus). The Rim Rock Crowned Snake historically occurred in eastern Miami-Dade County (hereafter, mainland) as well as throughout the Florida Keys, whereas the Key Ring-Necked Snake occurs only in lower Florida Keys (Enge et al. 2004; Mays and Enge 2016). Both species are very elusive, small (< 20 cm in length) and primarily fossorial. Pine rockland habitat is rapidly disappearing in South Florida, with < 3 percent of its original extent remaining. Saltwater intrusion from hurricanes and sea-level rise (SLR), and human development pose the greatest threats to the longevity of this ecosystem which, in turn, places species that are endemic to this unique habitat at risk of extinction.
The Rim Rock Crowned Snake and the Key Ringed-Necked Snake are being considered for listing by the U.S. Fish and Wildlife Service (USFWS). To aid the agency’s decision, it must be able to forecast species’ responses to potential future environmental conditions, as well as to different conservation and management actions. Yet, the information needed to complete these forecasts—such as population trends, life history traits, habitat use, and future land use and climate conditions—is often lacking for most rare species. This is especially problematic for assessments of species resiliency to changes in climate and land use.
When these types of data are lacking, information on habitat quality can be used to help determine how a species will respond to change. First, this project gathered current and historical records for both species from various sources such as museum specimens, inventories, and other personal account. Then, we identified potential future changes in habitat that could result from different management actions, such as habitat acquisition or restoration, and environmental conditions, such as changes in the frequency and intensity of tropical storms and rates of SLR. Researchers then explored the potential impacts of these habitat condition changes on the Rim Rock Crowned Snake and Key Ring-Necked Snake.
This information can be used by the USFWS to help make decisions about the need to protect these species under the Endangered Species Act and could inform the conservation, management, and recovery of other at-risk species found in the pine rockland ecosystem. This work supports the Secretary of Interior’s priority to create a conservation stewardship legacy by using science to identify best practices to manage land and water resource and adapt to changes in the environment.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Walls, S.C., 2021, Informing future condition scenario planning for habitat specialists of the imperiled pine rockland ecosystem of South Florida: Final Report, 18 p.","productDescription":"18 p.","ipdsId":"IP-129367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":398518,"type":{"id":15,"text":"Index Page"},"url":"https://secasc.ncsu.edu/science/pine-rocklands/"}],"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 -82.0458984375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 24.287026865376436\n ],\n [\n -79.9365234375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 26.244156283890756\n ],\n [\n -82.0458984375,\n 24.287026865376436\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":138952,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":840331,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}