The U.S. Geological Survey, in cooperation with the District Department of Energy & Environment, Water Quality Division, is investigating the hydrogeology of the tidal Anacostia River watershed within Washington, D.C., with the goal of improving understanding of the groundwater-flow system and the interaction of groundwater and surface water in the watershed. To help meet this goal, a three-dimensional steady-state groundwater-flow model for the Anacostia River and surrounding watersheds in Washington, D.C., Maryland, and Virginia was constructed. The goal of the modeling study was to quantify the rate and pattern of groundwater flow to the tidal Anacostia River. The model domain includes weathered and unweathered rocks of the Piedmont Physiographic Province and the southeast-dipping sediments of the Atlantic Coastal Plain Physiographic Province. The model includes processes of recharge, evapotranspiration, withdrawals from wells, and base flow to streams, rivers, and tidal waters. Final model calibration was achieved by using the objective parameter estimation and sensitivity analysis capabilities of UCODE_2005. Simulated gradients in the surficial aquifer in the vicinity of the tidal Anacostia River indicate that flow is predominantly toward the river, with changes in the magnitude and direction of the gradients from the northeast, where the Anacostia River enters Washington, D.C., to the southwest, toward the confluence with the tidal Potomac River. Flow paths to the tidal Anacostia River from the north are largely horizontal through the surficial aquifer and Patuxent aquifer. From the south, the flow paths toward the river originate in the elevated topographic areas southeast of the river and pass through the surficial aquifer and Patapsco confining unit, lower Patapsco aquifer/Arundel Clay, and to some extent, the Patuxent aquifer. Groundwater-flow rates to and from the tidal rivers (Potomac and Anacostia) are generally greatest near the land-water boundary, where the gradient in the water table is greatest, and diminish toward the middle of the tidal river channels. The tidal rivers are predominantly areas of groundwater discharge, although there are areas where tidal waters are recharging the subsurface, typically where small variations or depressions in the topography produce small locally reversed gradients in the water table. Substantial recharge of tidal waters to the groundwater system is observed for the tidal Potomac where the upper Patapsco aquifer subcrops south of Washington, D.C. Water budget calculations indicate that inflows to the groundwater system beneath the tidal Anacostia River are predominantly from the land area of Washington, D.C., followed by tidal surface water and flows from lower layers. Outflows are largely to the tidal Anacostia River, with a smaller part going to the land area underlying Washington, D.C.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135225","usgsCitation":"Raffensperger, J.P., Voronin, L.M., and Dieter, C.A., 2021, Simulation of groundwater flow in the aquifer system of the Anacostia River and surrounding watersheds, Washington, D.C., Maryland, and Virginia: U.S. Geological Survey Scientific Investigations Report 2013–5225, 59 p., https://doi.org/10.3133/sir20135225.","productDescription":"vii, 59 p.","numberOfPages":"59","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051429","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":384505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2013/5225/coverthb.jpg"},{"id":384506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5225/sir20135225.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5225"}],"country":"United States","state":"Delaware, Maryland, Washington D.C.","otherGeospatial":"Anacostia River and surrounding watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.70355224609375,\n 38.89958342598271\n ],\n [\n -76.44287109375,\n 38.1777509666256\n ],\n [\n -75.498046875,\n 39.14710270770074\n ],\n [\n -76.72027587890625,\n 39.715638134796336\n ],\n [\n -77.70355224609375,\n 38.89958342598271\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
The U.S. Geological Survey monitors a suite of intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential impact of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or biennially. Monitoring resumed in 2001 and has been completed annually since then. At the time of this report, the work is conducted by the Western Ecological Research Center’s Santa Cruz Field Station, Santa Cruz, California. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years, it reduced the population there by more than 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2020 monitoring cycle of the sites and how the current status fits into the long-term data at San Nicolas Island. Since 2001, the monitored population has increased twelvefold to approximately 9.6 percent of the pre-disease level. This increase has resulted from generally higher levels of recruitment than seen in the first two decades of monitoring, punctuated by a few unexplained high recruitment events. Most of the population growth has been at two of the nine sites (sites 7 and 8). This pattern continued in 2020, but with increasing numbers at all sites and the highest number of abalone counted and measured island-wide since 1993. Recruitment rates have fallen since a peak in 2017, but 2020 continued to show moderate levels of additional recruitment. The distance between adjacent black abalone has decreased substantially since it was first consistently measured in 2005, potentially indicating that the abalone are close enough to one another to reproduce successfully. Sand burial can have devastating localized consequences to black abalone, but there is evidence suggesting that they may be able to escape periodic sand inundation if suitable refugia exist. These data suggest that monitoring can inform adaptive management of the resource by base resource managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211023","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., 2021, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2020, annual report: U.S. Geological Survey Open-File Report 2021–1023, 33 p., https://doi.org/10.3133/ofr20211023.","productDescription":"vii, 33 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-125069","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":384507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1023/covrthb.jpg"},{"id":384508,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":384509,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1023/ofr20211023.xml"},{"id":384510,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1023/images"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.59442138671875,\n 33.20996748987798\n ],\n [\n -119.42928314208984,\n 33.20996748987798\n ],\n [\n -119.42928314208984,\n 33.28806392819752\n ],\n [\n -119.59442138671875,\n 33.28806392819752\n ],\n [\n -119.59442138671875,\n 33.20996748987798\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
With declining capture fisheries production, maintaining nutrient supplies largely hinges on substituting wild fish with economically comparable farmed animals. Although such transitions are increasingly commonplace across global inland and coastal communities, their nutritional consequences are unknown. Here, using human demographic and health information, and fish nutrient composition data from the Peruvian Amazon, we show that substituting wild inland fisheries with chicken and aquaculture has the potential to exacerbate iron deficiencies and limit essential fatty acid supplies in a region already experiencing high prevalence of anaemia and malnutrition. Substituting wild fish with chicken, however, can increase zinc and protein supplies. Chicken and aquaculture production also increase greenhouse gas emissions, agricultural land use and eutrophication. Thus, policies that enable access to wild fisheries and their sustainable management while improving the quality, diversity and environmental impacts of farmed species will be instrumental in ensuring healthy and sustainable food systems.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s43016-021-00242-8","usgsCitation":"Heilpern, S., Fiorella, K., Canas, C., Flecker, A., Moya, L., Naeem, S., Sethi, S., Uriarte, M., and DeFries, R., 2021, Substitution of inland fisheries with aquaculture and chicken undermines human nutrition in the Peruvian Amazon: Nature Food, v. 2, p. 192-197, https://doi.org/10.1038/s43016-021-00242-8.","productDescription":"6 p.","startPage":"192","endPage":"197","ipdsId":"IP-121798","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":396547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Peru","otherGeospatial":"Peruvian Amazon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.53125,\n -8.363692651835823\n ],\n [\n -73.212890625,\n -4.915832801313164\n ],\n [\n -70.927734375,\n -4.083452772038619\n ],\n [\n -70.8837890625,\n -2.85526278436657\n ],\n [\n -74.794921875,\n -0.8349313860427057\n ],\n [\n -77.51953125,\n -0.08789059053082422\n ],\n [\n -78.046875,\n -2.8991526985043006\n ],\n [\n -77.5634765625,\n -5.703447982149503\n ],\n [\n -75.1904296875,\n -8.102738577783168\n ],\n [\n -74.53125,\n -8.363692651835823\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Heilpern, Sebastian A.","contributorId":287013,"corporation":false,"usgs":false,"family":"Heilpern","given":"Sebastian A.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fiorella, Kathryn","contributorId":287014,"corporation":false,"usgs":false,"family":"Fiorella","given":"Kathryn","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Canas, Carlos","contributorId":287015,"corporation":false,"usgs":false,"family":"Canas","given":"Carlos","email":"","affiliations":[{"id":34928,"text":"Independent Researcher","active":true,"usgs":false}],"preferred":false,"id":836435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flecker, Alexander S.","contributorId":287016,"corporation":false,"usgs":false,"family":"Flecker","given":"Alexander S.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":836436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moya, Luis","contributorId":287017,"corporation":false,"usgs":false,"family":"Moya","given":"Luis","email":"","affiliations":[{"id":13272,"text":"Wildlife Conservation Society","active":true,"usgs":false}],"preferred":false,"id":836437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Naeem, Shahid","contributorId":287018,"corporation":false,"usgs":false,"family":"Naeem","given":"Shahid","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836438,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":836432,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Uriarte, Maria","contributorId":287019,"corporation":false,"usgs":false,"family":"Uriarte","given":"Maria","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836439,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeFries, Ruth","contributorId":287020,"corporation":false,"usgs":false,"family":"DeFries","given":"Ruth","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":836440,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70219164,"text":"70219164 - 2021 - Water temperature and availability shape the spatial ecology of a hot springs endemic toad","interactions":[],"lastModifiedDate":"2021-03-29T13:21:00.83852","indexId":"70219164","displayToPublicDate":"2021-03-19T08:17:00","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1892,"text":"Herpetologica","active":true,"publicationSubtype":{"id":10}},"title":"Water temperature and availability shape the spatial ecology of a hot springs endemic toad","docAbstract":"Desert amphibians are limited to exploiting ephemeral resources and aestivating or to inhabiting scarce refuges of permanent water, such as springs. Understanding how amphibians use these resources is essential for their conservation. Dixie Valley Toads (Anaxyrus williamsi) are precinctive to a small system of cold and hot springs in the Dixie Valley, Nevada, USA. The toads have been petitioned for listing under the US Endangered Species Act, and information about how they use terrestrial and aquatic resources will help managers to conserve the toads and identify threats like geothermal energy development that might affect these toads. We used radiotelemetry to study the seasonal home ranges, movements, and habitat associations of Dixie Valley Toads in autumn 2018 and spring 2019. We found that toads were very closely associated with water in both seasons, with most observations occurring in water, especially for males in spring and all toads in the autumn. Even when found in terrestrial habitat, toads were a median distance of 4.2 m (95% credible interval = 3.3–5.3) from water; 95% of the time in spring and autumn, toads were within 14 m of water. Dixie Valley Toad habitat selection indicated a similar pattern, with selection in both spring and autumn for locations closer to water and for warmer water and substrates than at nearby available locations. In autumn, toads also avoided bare ground and terrestrial graminoids. Dixie Valley Toads selected brumation sites in, over (within dense vegetation), or near water, often near springs where water depths and temperatures are likely stable through the winter. The reliance of Dixie Valley Toads on water in spring, autumn, and during brumation suggests that alteration to historical flows and water temperatures are likely to affect the toads. Changes to the hydrothermal environment when toads are brumating could be particularly detrimental, potentially killing inactive toads.
The Cascades back-arc in northern California is dominated by monogenetic tholeiitic basalts that erupted throughout the Pleistocene. Elucidating their eruptive history and processes is important for understanding potential future eruptions here. We focus on the well-exposed monogenetic volcano that emplaced the Brushy Butte flow field, which constructed a ∼150 m tall edifice, has flow lobes up to >10 km long, and in total covers ∼150 km2 with an eruptive volume of 3.5 km3. We use a multidisciplinary approach of field mapping, petrography, geochemistry, paleomagnetism, geochronology, and lidar imagery to unravel the eruptive history and processes that emplaced this flow field. Tholeiitic basalts in northern California have diverse surface morphology and vegetation cover but similar petrographic appearances, which makes them hard to distinguish in the field. Geochemistry and paleomagnetism offer an independent means of distinguishing tholeiitic basalts. Brushy Butte flow field lavas are similar in major-oxide and trace-element abundances but differ from adjacent tholeiitic basalts. This is also apparent in remanent magnetic directions. Additionally, paleomagnetism indicates that the flow field was emplaced during a geologically brief time interval (10–20 years), which 36Cl cosmogenic dating puts at 35.7 ± 1.7 ka. Lidar imagery shows that these flows erupted from at least 28 vents encompassing multiple scoria cones, spatter cones, and craters. Flows can be grouped into four pulses using stratigraphic position and volume. Pulse 1 is the most voluminous, comprising eight eruptions and ∼2.3 km3. Each subsequent pulse started rapidly but decayed quickly, and each successive pulse erupted less lava (i.e., 2.3 km3 for pulse 1, 0.6 km3 for pulse 2, 0.3 km3 for pulse 3, and 0.2 km3 for pulse 4). Many of these flows host well-established lava channels and levees (with channel breakouts) that lead to lava fans, with some flows hosting lava ponds. Similar flow features from tholeiitic eruptions elsewhere demonstrate that these morphologies generally occur over weeks, months, or longer (e.g., Puʻu ʻŌʻō eruption at K–llauea, Hawaiʻi). This multidisciplinary study shows the range of eruptive styles and durations of a Cascades back-arc eruption and illustrates how potential future tholeiitic eruptive activity in the western United States might progress.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/feart.2021.639459","usgsCitation":"Downs, D.T., Champion, D.E., Clynne, M.A., and Muffler, L.P., 2021, A multidisciplinary investigation into the eruptive style, processes, and duration of a Cascades back-arc tholeiitic basalt: A case study of the Brushy Butte flow field, northern California, United States: Frontiers in Earth Science, v. 9, 18 p., https://doi.org/10.3389/feart.2021.639459.","productDescription":"18 p.","ipdsId":"IP-122177","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":453012,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2021.639459","text":"Publisher Index Page"},{"id":384534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.23339843749999,\n 38.496593518947584\n ],\n [\n -120.03662109374999,\n 38.496593518947584\n ],\n [\n -120.03662109374999,\n 41.983994270935625\n ],\n [\n -124.23339843749999,\n 41.983994270935625\n ],\n [\n -124.23339843749999,\n 38.496593518947584\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2021-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":812604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":812605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":812606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muffler, L.J. Patrick 0000-0001-6638-7218 pmuffler@usgs.gov","orcid":"https://orcid.org/0000-0001-6638-7218","contributorId":3322,"corporation":false,"usgs":true,"family":"Muffler","given":"L.J.","email":"pmuffler@usgs.gov","middleInitial":"Patrick","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":812607,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223703,"text":"70223703 - 2021 - The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US","interactions":[],"lastModifiedDate":"2021-09-02T12:58:27.982991","indexId":"70223703","displayToPublicDate":"2021-03-19T07:56:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Ground motion models in the central and eastern US","docAbstract":"The United States Geological Survey (USGS) National Seismic Hazard Model (NSHM) is the scientific foundation of seismic design regulations in the United States and is regularly updated to consider the best available science and data. The 2018 update of the conterminous US NSHM includes major changes to the underlying ground motion models (GMMs). Most of the changes are motivated by the new multi-period response spectra requirements of seismic design regulations that use hazard results for 22 spectral periods and 8 site classes. In the central and eastern United States (CEUS), the 2018 NSHM incorporates 31 new GMMs for hard-rock site conditions
The University of Kentucky (U KY) has owned Robinson Forest (37.460723° N, 83.158598° W) since 1923, conducting experiments crucial to understanding the environmental effects of land management in the region. Part of the management of Robinson Forest has been collection of environmental data, including precipitation quantity, bulk‐deposition chemistry, streamflow, stream‐water chemistry, and air and stream temperature. Over the years, these data have been collected and archived using various technologies and have been mostly inaccessible for research use – unedited and uncompiled, scattered across several spreadsheets and paper records. Through a partnership between the U.S. Geological Survey (USGS) and U KY, daily precipitation data for six stations and stream data from four watersheds in Robinson Forest have been compiled for 1971–2018, checked for transcription errors, and annotated for changes in methodologies. These data are available as a USGS data release at https://doi.org/10.5066/P9FPLG1O. Improved accessibility of this data set provides an important research resource for understanding water quality in minimally effected forests in the region. Preliminary results indicate that these data present a valuable opportunity to evaluate linkages among atmospheric deposition and stream chemistry, the effects of environmental policy, such as the Clean Air Act, and effects from nearby land disturbance in the form of surface mining. Furthermore, these data fill a geographic and physiographic gap in what is available to examine deposition and streamflow patterns over the last 45 years, supplementing those long‐term records of research sites in northern (e.g., Hubbard Brook Experimental Forest), central (e.g., Fernow Experimental Forest) and southern Appalachia (e.g., Coweeta Hydrologic Laboratory). As an oasis in the midst of significant surface mining activity, Robinson Forest presents a unique opportunity to understand environmental conditions characteristic of minimally disturbed forests similar to pre‐mining conditions in the Central Appalachian region.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.14133","usgsCitation":"Sena, K., Barton, C.D., and Williamson, T.N., 2021, The Robinson Forest environmental monitoring network: Long‐term evaluation of streamflow and precipitation quantity and stream‐water and bulk deposition chemistry in eastern Kentucky watersheds: Hydrological Processes, v. 35, no. 4, e14133, 6 p., https://doi.org/10.1002/hyp.14133.","productDescription":"e14133, 6 p.","ipdsId":"IP-122607","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":385638,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"southeast Kentucky","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.27636718749999,\n 36.756490329505176\n ],\n [\n -81.36474609375,\n 36.756490329505176\n ],\n [\n -81.36474609375,\n 37.82280243352756\n ],\n [\n -83.27636718749999,\n 37.82280243352756\n ],\n [\n -83.27636718749999,\n 36.756490329505176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Sena, Kenton 0000-0003-1822-9375","orcid":"https://orcid.org/0000-0003-1822-9375","contributorId":258046,"corporation":false,"usgs":false,"family":"Sena","given":"Kenton","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":815604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barton, Chris D. 0000-0003-0692-3079","orcid":"https://orcid.org/0000-0003-0692-3079","contributorId":236883,"corporation":false,"usgs":false,"family":"Barton","given":"Chris","email":"","middleInitial":"D.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":815605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Tanja N. 0000-0002-7639-8495 tnwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-7639-8495","contributorId":198329,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja","email":"tnwillia@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815606,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219101,"text":"70219101 - 2021 - Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry","interactions":[],"lastModifiedDate":"2021-03-25T11:47:28.121179","indexId":"70219101","displayToPublicDate":"2021-03-19T07:19:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Dating fault damage along the eastern Denali fault zone with hematite (U-Th)/He thermochronometry","docAbstract":"Unraveling complex slip histories in fault damage zones to understand relations among deformation, hydrothermal alteration, and surface uplift remains a challenge. The dextral eastern Denali fault zone (EDFZ; southwest Yukon, Canada) bounds the Kluane Ranges and hosts a variety of fault-related rocks, including hematite fault surfaces, which have been exhumed through the brittle regime over a protracted period of geologic time. Scanning electron microscopy-based microtextural observations and hematite (U-Th)/He (hematite He) thermochronometry from these surfaces indicate multiple generations of foliated, high-aspect ratio hematite plates. Single-aliquot hematite He dates (
Recent production of light sweet oil has prompted reevaluation of Devonian petroleum systems in the central Appalachian Basin. Upper Devonian Ohio Shale (lower Huron Member) and Middle Devonian Marcellus Shale organic-rich source rocks from eastern Ohio and nearby areas were examined using organic petrography and geochemical analysis of solvent extracts to test ideas related to organic matter sources, oil–source rock correlation, thermal maturity, and distances of petroleum migration. The data from these analyses indicate organic matter in the Ohio and Marcellus Shales primarily was derived from marine algae and its degradation products, including bacterial biomass. Absence of odd-over-even n-alkane distributions (n-C13 to n-C21 range) in gas chromatograms and low gammacerane index values in Devonian source rocks are similar to those of Devonian-reservoired oils in eastern Ohio, suggesting an oil–source rock correlation. Lower Paleozoic oils from eastern Ohio, in contrast, are characterized by the presence of odd-over-even n-alkane distributions (n-C13 to n-C21 range) and higher gammacerane values, which discriminate them from Devonian shale-derived oils. Thermal maturity estimates from equilibrium(?) biomarker isomerization ratios suggest that some of the Devonian source rock samples are at middle to peak oil window conditions (i.e., approximate vitrinite reflectance values of 0.8%–0.9%). This observation requires local to short-distance (<50 mi) lateral migration for emplacement of Devonian-sourced oils into Devonian reservoirs of eastern Ohio and may impact exploration and assessment of petroleum resources in the Upper Devonian Berea Sandstone.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/08192019076","usgsCitation":"Hackley, P.C., and Ryder, R.T., 2021, Organic geochemistry and petrology of Devonian shale in eastern Ohio: Implications for petroleum systems assessment: American Association of Petroleum Geologists Bulletin, v. 105, no. 3, p. 543-573, https://doi.org/10.1306/08192019076.","productDescription":"31 p.","startPage":"543","endPage":"573","ipdsId":"IP-099052","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":384494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Eastern and central Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.57373046875,\n 41.97582726102573\n ],\n [\n -82.06787109374999,\n 41.5579215778042\n ],\n [\n -82.85888671875,\n 41.46742831254425\n ],\n [\n -82.94677734375,\n 40.763901280945866\n ],\n [\n -82.90283203125,\n 39.791654835253425\n ],\n [\n -82.935791015625,\n 38.75408327579141\n ],\n [\n -82.68310546875,\n 38.831149809348744\n ],\n [\n -82.584228515625,\n 40.17887331434696\n ],\n [\n -82.59521484375,\n 41.1455697310095\n ],\n [\n -80.518798828125,\n 41.73852846935917\n ],\n [\n -80.57373046875,\n 41.97582726102573\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812493,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryder, Robert T. rryder@usgs.gov","contributorId":211801,"corporation":false,"usgs":false,"family":"Ryder","given":"Robert","email":"rryder@usgs.gov","middleInitial":"T.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":false,"id":812494,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219029,"text":"70219029 - 2021 - Organic petrology and geochemistry of the Sunbury and Ohio Shales in eastern Kentucky and southeastern Ohio","interactions":[],"lastModifiedDate":"2021-03-22T11:51:52.617715","indexId":"70219029","displayToPublicDate":"2021-03-19T07:03:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrology and geochemistry of the Sunbury and Ohio Shales in eastern Kentucky and southeastern Ohio","docAbstract":"As part of a study to determine the origin of oil and gas in the Berea Sandstone in northeastern Kentucky and southeastern Ohio, 158 samples of organic-rich shale from the Upper Devonian Olentangy and Ohio Shales and the Lower Mississippian Sunbury Shale, collectively referred to as the “black shale,” were collected and analyzed from 12 cores. The samples were analyzed for total organic carbon (TOC) content, organic petrography, and programmed pyrolysis. Previously acquired analytical data for 11 samples from 2 additional wells in eastern Kentucky were also used.
Most of the samples were organic rich (>5 wt. % TOC), high in sulfur (>2.0 wt. %), and dominated by liptinite macerals. The vitrinite reflectance (VRo) and equivalent vitrinite reflectance (VReq) values, calculated from bitumen reflectance (BRo) measurements, were found to be in close agreement. The calculated reflectance values from programmed pyrolysis temperature at which the maximum release of hydrocarbons occurs (Tmax) showed better agreement with measured VRo after Tmax was corrected for excessive hydrogen index values for several samples. Thermal maturation parameters were found to increase in a northwest–southeast direction, paralleling an increase in black shale thickness and depth of burial. The thermal maturity proxies indicate the northwestern part of the study area to be more thermally mature than previously indicated. Geochemical and biomarker data from Berea oils indicate migration of oil from more thermally mature to less thermally mature areas. As such, the occurrence of petroleum liquids in the Berea Sandstone cannot be predicted directly from conventional thermal maturity proxies (Tmax, VRo, and BRo) because these methods do not account for migrated petroleum.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/09242019089","usgsCitation":"Eble, C.F., Hackley, P.C., Parris, T.M., and Greb, S.F., 2021, Organic petrology and geochemistry of the Sunbury and Ohio Shales in eastern Kentucky and southeastern Ohio: AAPG Bulletin, v. 105, no. 3, p. 493-515, https://doi.org/10.1306/09242019089.","productDescription":"23 p.","startPage":"493","endPage":"515","ipdsId":"IP-100494","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":384493,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio, Kentucky","otherGeospatial":"Eastern Kentucky and southeastern Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.814453125,\n 39.21523130910491\n ],\n [\n -84.990234375,\n 37.49229399862877\n ],\n [\n -82.41943359375,\n 37.31775185163688\n ],\n [\n -81.93603515625,\n 37.579412513438385\n ],\n [\n -82.6171875,\n 38.09998264736481\n ],\n [\n -82.50732421875,\n 38.788345355085625\n ],\n [\n -82.4853515625,\n 39.605688178320804\n ],\n [\n -84.83642578125,\n 39.740986355883564\n ],\n [\n -84.814453125,\n 39.21523130910491\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eble, Cortland F.","contributorId":255518,"corporation":false,"usgs":false,"family":"Eble","given":"Cortland","email":"","middleInitial":"F.","affiliations":[{"id":51568,"text":"Kentucky Geological Survey, U. of Kentucky","active":true,"usgs":false}],"preferred":false,"id":812495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":812496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parris, Thomas M.","contributorId":255526,"corporation":false,"usgs":false,"family":"Parris","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greb, Stephen F.","contributorId":255517,"corporation":false,"usgs":false,"family":"Greb","given":"Stephen","email":"","middleInitial":"F.","affiliations":[{"id":51568,"text":"Kentucky Geological Survey, U. of Kentucky","active":true,"usgs":false}],"preferred":false,"id":812498,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220304,"text":"70220304 - 2021 - Before the first meal: The elusive pre-feeding juvenile stage of the sea lamprey","interactions":[],"lastModifiedDate":"2023-01-19T16:33:51.934229","indexId":"70220304","displayToPublicDate":"2021-03-19T07:02:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Before the first meal: The elusive pre-feeding juvenile stage of the sea lamprey","docAbstract":"Although sea lamprey (Petromyzon marinus) in the Laurentian Great Lakes have been studied intensively for more than 70 years, many questions remain about their complex life cycle. One of the least understood portions is the post-metamorphic stage (hereafter pre-feeding juvenile, PFJ) that occurs prior to parasitic feeding. PFJ must emerge from stream sediments and migrate downstream into nearshore feeding areas. Key uncertainties include the internal and exogenous triggers that regulate the timing and duration of the migration, and the mechanisms the animal uses to navigate, avoid predators, and locate their first host. However, many of these factors may vary predictably among natal streams in response to stable geomorphological and hydraulic characteristics that regulate the timing of movements (e.g., flood phenology), energetic costs (e.g., stream length), and risk (e.g., predator density). An improved understanding of the PFJ stage presents two opportunities to improve the success of sea lamprey control: (1) identification of streams where natural mortality during the PFJ stage is high, allowing for the reallocation of larval control to streams more likely to produce successful parasites, and (2) removal or killing of PFJs in streams where natural mortality is low. Either approach represents an opportunity to limit parasitic damage to valuable fish stocks. Here, we review the state of knowledge of the PFJ stage and identify critical knowledge gaps that, if addressed, could facilitate sea lamprey assessment and control by exploiting the behavior of PFJ as they outmigrate from streams in search of their first meal.
Shallow production of sweet high-gravity oil from the Upper Devonian Berea Sandstone in northeastern Kentucky has caused the region to become the leading oil producer in the state. Potential nearby source rocks, namely, the overlying Mississippian Sunbury Shale and underlying Ohio Shale, are immature for commercial oil generation according to vitrinite reflectance and programmed pyrolysis analyses. We used organic geochemical measurements from Berea oils and solvent extracts from potential Upper Devonian–Mississippian source rocks to better understand organic matter sources, oil–oil and oil–source rock correlations, and thermal maturity in the shallow Berea oil play. Multiple geochemical proxies suggest Berea oils are from one family and from similar source rocks. Oils and organic matter in the potential source rocks are from a marine source based on pristane-to-phytane (Pr/Ph) and terrestrial-to-aquatic ratios, carbon preference index values, n-alkane maxima, C-isotopic composition, and tricyclic terpane and hopane ratios. Any or all of the Devonian to Mississippian black shale source rocks could be potential source rocks for Berea oils based on similarities in oil and solvent extract Pr/n-C17 and Ph/n-C18 ratios, sterane distributions, C-isotopic values, and sterane/hopane and tricyclic terpane ratios. Multiple biomarker ratios suggest Berea oils formed at thermal maturities of approximately 0.7% –0.9% vitrinite reflectance. These data require significant updip lateral migration of 30–50 mi from a downdip Devonian black shale source kitchen to emplace low-sulfur oils in the shallow updip oil-play area and indicate that immature source rocks nearby to Berea oil production are not contributing to produced hydrocarbons.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/08192019077","usgsCitation":"Hackley, P.C., Parris, T., Eble, C.F., Greb, S.F., and Harris, D., 2021, Oil–source correlation studies in the shallow Berea Sandstone petroleum system, eastern Kentucky: American Association of Petroleum Geologists Bulletin, v. 105, no. 3, p. 517-542, https://doi.org/10.1306/08192019077.","productDescription":"26 p.","startPage":"517","endPage":"542","ipdsId":"IP-098811","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":384491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","otherGeospatial":"Northeast Kentucky","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.671875,\n 38.74551518488265\n ],\n [\n -83.81469726562499,\n 37.95286091815649\n ],\n [\n -83.001708984375,\n 37.448696585910376\n ],\n [\n -82.2216796875,\n 37.709899354855125\n ],\n [\n -82.562255859375,\n 38.05674222065296\n ],\n [\n -82.562255859375,\n 38.47079371120379\n ],\n [\n -82.90283203125,\n 38.805470223177466\n ],\n [\n -83.177490234375,\n 38.62545397209084\n ],\n [\n -83.671875,\n 38.74551518488265\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":812510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parris, T.M.","contributorId":255535,"corporation":false,"usgs":false,"family":"Parris","given":"T.M.","email":"","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eble, C. F.","contributorId":255536,"corporation":false,"usgs":false,"family":"Eble","given":"C.","email":"","middleInitial":"F.","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812512,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greb, S. F.","contributorId":255538,"corporation":false,"usgs":false,"family":"Greb","given":"S.","email":"","middleInitial":"F.","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812513,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harris, D.C.","contributorId":255540,"corporation":false,"usgs":false,"family":"Harris","given":"D.C.","email":"","affiliations":[{"id":40489,"text":"Kentucky Geological Survey","active":true,"usgs":false}],"preferred":false,"id":812514,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219120,"text":"70219120 - 2021 - Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA","interactions":[],"lastModifiedDate":"2021-05-28T14:11:19.896547","indexId":"70219120","displayToPublicDate":"2021-03-19T06:49:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7788,"text":"Environmental International","active":true,"publicationSubtype":{"id":10}},"title":"Public and private tapwater: Comparative analysis of contaminant exposure and potential risk, Cape Cod, Massachusetts, USA","docAbstract":"Humans are primary drivers of environmental contamination worldwide, including in drinking-water resources. In the United States (US), federal and state agencies regulate and monitor public-supply drinking water while private-supply monitoring is rare; the current lack of directly comparable information on contaminant-mixture exposures and risks between private- and public-supplies undermines tapwater (TW) consumer decision-making.
We compared private- and public-supply residential point-of-use TW at Cape Cod, Massachusetts, where both supplies share the same groundwater source. TW from 10 private- and 10 public-supply homes was analyzed for 487 organic, 38 inorganic, 8 microbial indicators, and 3 in vitro bioactivities. Concentrations were compared to existing protective health-based benchmarks, and aggregated Hazard Indices (HI) of regulated and unregulated TW contaminants were calculated along with ratios of in vitro exposure-activity cutoffs.
Seventy organic and 28 inorganic constituents were detected in TW. Median detections were comparable, but median cumulative concentrations were substantially higher in public supply due to 6 chlorine–disinfected samples characterized by disinfection byproducts and corresponding lower heterotrophic plate counts. Public-supply applicable maximum contaminant (nitrate) and treatment action (lead and copper) levels were exceeded in private-supply TW samples only. Exceedances of health-based HI screening levels of concern were common to both TW supplies.
These Cape Cod results indicate comparable cumulative human-health concerns from contaminant exposures in private- and public-supply TW in a shared source-water setting. Importantly, although this study’s analytical coverage exceeds that currently feasible for water purveyors or homeowners, it nevertheless is a substantial underestimation of the full breadth of contaminant mixtures documented in the environment and potentially present in drinking water.
Regardless of the supply, increased public engagement in source-water protection and drinking-water treatment, including consumer point-of-use treatment, is warranted to reduce risks associated with long-term TW contaminant exposures, especially in vulnerable populations.
The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services, is undertaking a study on per- and polyfluoroalkyl substances (PFAS) in soils and biosolids. The study will characterize PFAS concentrations in shallow soil and selected biosolids throughout the State of New Hampshire, conduct laboratory experiments to improve understanding of how mobile PFAS are in the environment, and implement a site-specific field study of PFAS transport from soil to water.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip208","collaboration":"Prepared in cooperation with the New Hampshire Department of Environmental Services","usgsCitation":"Tokranov, A.K., Schlosser, K.E.A., Marts, J.M., Drouin, A.F., Santangelo, L.M., and Welch, S.M., 2021, Per- and polyfluoroalkyl substances (PFAS) in New Hampshire soils and biosolids: U.S. Geological Survey General Information Product 208, 2 p., https://doi.org/10.3133/gip208.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-123740","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":384461,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/208/coverthb2.jpg"},{"id":384462,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/208/gip208.pdf","text":"Report","size":"895 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Hampshire\",\"nation\":\"USA \"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Many US federal agencies apply principles from risk communication science across a wide variety of hazards. In so doing, they identify key research and practice gaps that, if addressed, could help better serve the nation’s communities and greatly enhance practice, research, and policy development.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41562-021-01081-0","usgsCitation":"Klein, W.M., Boutte, A., Brake, H., Beal, M., Lyon-Daniel, K., Eisenhauer, E., Grasso, M., Hubbell, B., Jenni, K., Lauer, C., Lupia, A., Prue, C., Rausch, P., Shapiro, C.D., Smith, M.D., and Riley, W., 2021, Leveraging risk communication science across US federal agencies: Nature Human Behavior, v. 5, p. 411-413, https://doi.org/10.1038/s41562-021-01081-0.","productDescription":"3 p.","startPage":"411","endPage":"413","ipdsId":"IP-122303","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":453026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41562-021-01081-0","text":"Publisher Index Page"},{"id":421069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Klein, William M. 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P.","affiliations":[],"preferred":false,"id":883898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boutte, Alycia","contributorId":330014,"corporation":false,"usgs":false,"family":"Boutte","given":"Alycia","email":"","affiliations":[{"id":29855,"text":"National Cancer Institute","active":true,"usgs":false}],"preferred":false,"id":883860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brake, Heather","contributorId":330035,"corporation":false,"usgs":false,"family":"Brake","given":"Heather","email":"","affiliations":[],"preferred":false,"id":883861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beal, Madeline","contributorId":330017,"corporation":false,"usgs":false,"family":"Beal","given":"Madeline","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":883862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyon-Daniel, Katherine","contributorId":330019,"corporation":false,"usgs":false,"family":"Lyon-Daniel","given":"Katherine","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":883863,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eisenhauer, Emily","contributorId":330021,"corporation":false,"usgs":false,"family":"Eisenhauer","given":"Emily","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":883864,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grasso, Monica","contributorId":211877,"corporation":false,"usgs":false,"family":"Grasso","given":"Monica","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":883865,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubbell, Bryan","contributorId":330023,"corporation":false,"usgs":false,"family":"Hubbell","given":"Bryan","email":"","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":883866,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jenni, Karen 0000-0001-9927-7509","orcid":"https://orcid.org/0000-0001-9927-7509","contributorId":219401,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen","email":"","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":883867,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lauer, Christopher","contributorId":330025,"corporation":false,"usgs":false,"family":"Lauer","given":"Christopher","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":883868,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lupia, Arthur","contributorId":330027,"corporation":false,"usgs":false,"family":"Lupia","given":"Arthur","email":"","affiliations":[{"id":65942,"text":"NSF","active":true,"usgs":false}],"preferred":false,"id":883869,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Prue, Christine","contributorId":330029,"corporation":false,"usgs":false,"family":"Prue","given":"Christine","email":"","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":883870,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rausch, Paula","contributorId":330031,"corporation":false,"usgs":false,"family":"Rausch","given":"Paula","email":"","affiliations":[{"id":78768,"text":"FDA","active":true,"usgs":false}],"preferred":false,"id":883871,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":883874,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Smith, Michael D.","contributorId":206173,"corporation":false,"usgs":false,"family":"Smith","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":883872,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Riley, William","contributorId":222533,"corporation":false,"usgs":false,"family":"Riley","given":"William","affiliations":[],"preferred":false,"id":883873,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70219046,"text":"70219046 - 2021 - Whole‐genome resequencing reveals persistence of forest‐associated mammals in Late Pleistocene refugia along North America’s North Pacific Coast","interactions":[],"lastModifiedDate":"2021-05-13T15:51:18.012368","indexId":"70219046","displayToPublicDate":"2021-03-18T08:23:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Whole‐genome resequencing reveals persistence of forest‐associated mammals in Late Pleistocene refugia along North America’s North Pacific Coast","docAbstract":"Numerous glacial refugia have been hypothesized along North America's North Pacific Coast that may have increased divergence of refugial taxa, leading to elevated endemism and subsequently clustered hybrid zones following deglaciation. The locations and community composition of these ice‐free areas remains controversial, but whole‐genome sequences now enable detailed analysis of the demographic and evolutionary histories of refugial taxa. Here, we use genomic data to test spatial and temporal processes of diversification among martens with respect to the Coastal Refugium Hypothesis, to understand the role of climate cycling in shaping diversity across complex landscapes.
North America and North Pacific Coast archipelagos.
North American martens (Martes).
Short‐read whole‐genome resequencing data were generated for 11 martens: four M. americana, four M. caurina, two hybrids, and one outgroup (Martes zibellina). Sampling was representative of known genetic clades within New World martens, including sampling within insular and continental hybrid zones and along the North Pacific Coast (five island populations). ADMIXTURE, F‐statistics, and D‐statistics (ABBA‐BABA) were used to identify introgression and infer directionality. Heterozygosity densities, estimated via PSMC, were used to characterize historical demography at and below the species level to infer refugial and colonization processes.
Forest‐associated Pacific martens (M. caurina) are divided into distinct insular and continental clades consistent with the Coastal Refugium Hypothesis. There was no evidence of introgression on islands that received historical translocations of American pine martens (M. americana), but introgression was detected in two active zones of secondary contact: one insular and one continental. Only early‐generational hybrids were identified across multiple hybrid zones, a pattern consistent with potential genetic swamping of M. caurina by M. americana.
Despite an incomplete fossil record, genomic evidence supports the persistence of forest‐associated martens, likely the insular Pacific marten lineage, along the western edges of the Alexander Archipelago during the Last Glacial Maximum. This discovery informs our understanding of refugial paleoenvironments, critical to interpreting refugial timing, duration, and community composition. Genomic reevaluations of other taxa along North America's North Pacific Coast may yield new and deeper perspectives on the history of refugial forest communities and the role of dynamic climate shifts in shaping high‐latitude diversity across complex insular landscapes.
","language":"English","publisher":"Wiley","doi":"10.1111/jbi.14068","usgsCitation":"Colella, J.P., Lan, T., Talbot, S.L., Lindqvist, C., and Cook, J.A., 2021, Whole‐genome resequencing reveals persistence of forest‐associated mammals in Late Pleistocene refugia along North America’s North Pacific Coast: Journal of Biogeography, v. 48, no. 5, p. 1153-1169, https://doi.org/10.1111/jbi.14068.","productDescription":"17 p.","startPage":"1153","endPage":"1169","ipdsId":"IP-117301","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":384540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, California, Oregon, Washington, Yukon","otherGeospatial":"North Pacific Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.796875,\n 61.438767493682825\n ],\n [\n -165.58593749999997,\n 53.54030739150022\n ],\n [\n -154.68749999999997,\n 55.3791104480105\n ],\n [\n -147.3046875,\n 58.07787626787517\n ],\n [\n -139.5703125,\n 56.559482483762245\n ],\n [\n -129.375,\n 48.45835188280866\n ],\n [\n -127.61718749999999,\n 38.272688535980976\n ],\n [\n -121.640625,\n 38.54816542304656\n ],\n [\n -120.9375,\n 47.754097979680026\n ],\n [\n -128.671875,\n 58.07787626787517\n ],\n [\n -138.515625,\n 62.75472592723178\n ],\n [\n -156.796875,\n 61.438767493682825\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Colella, Jocelyn P.","contributorId":190332,"corporation":false,"usgs":false,"family":"Colella","given":"Jocelyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":812554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lan, Tianying","contributorId":207037,"corporation":false,"usgs":false,"family":"Lan","given":"Tianying","email":"","affiliations":[{"id":37434,"text":"Department of Biological Scineces, State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":812555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":812556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindqvist, Charlotte","contributorId":207038,"corporation":false,"usgs":false,"family":"Lindqvist","given":"Charlotte","email":"","affiliations":[{"id":37434,"text":"Department of Biological Scineces, State University of New York at Buffalo","active":true,"usgs":false}],"preferred":false,"id":812557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, Joseph A.","contributorId":8323,"corporation":false,"usgs":false,"family":"Cook","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":812558,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222613,"text":"70222613 - 2021 - A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system","interactions":[],"lastModifiedDate":"2021-08-09T13:25:19.177377","indexId":"70222613","displayToPublicDate":"2021-03-18T08:22:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9137,"text":"Journal of Geophysical Research-Oceans","active":true,"publicationSubtype":{"id":10}},"title":"A numerical study of wave-driven mean flows and setup dynamics at a coral reef-lagoon system","docAbstract":"Two-dimensional mean wave-driven flow and setup dynamics were investigated at a reef-lagoon system at Ningaloo Reef, Western Australia, using the numerical wave-flow model, SWASH. Phase-resolved numerical simulations of the wave and flow fields, validated with highly detailed field observations (including >10 sensors through the energetic surf zone), were used to quantify the main mechanisms that govern the mean momentum balances and resulting mean current and setup patterns, with particular attention to the role of nonlinear wave shapes. Momentum balances from the phase-resolved model indicated that onshore flows near the reef crest were primarily driven by the wave force (dominated by radiation stress gradients) due to intense breaking, whereas the flow over the reef flat and inside the lagoon and channels was primarily driven by a pressure gradient. Wave setup inside the lagoon was primarily controlled by the wave force and bottom stress. The bottom stress reduced the setup on the reef flat and inside the lagoon. Excluding the bottom stress contribution in the setup balance resulted in an over prediction of the wave-setup inside the lagoon by up to 200–370%. The bottom stress was found to be caused by the combined presence of onshore directed wave-driven currents and (nonlinear) waves. Exclusion of the bottom stress contribution from nonlinear wave shapes led to an over prediction of the setup inside the lagoon by approximately 20–40%. The inclusion of the nonlinear wave shape contribution to the bottom stress term was found to be particularly relevant in reef regions that experience a net onshore mass flux over the reef crest.
No abstract available.
","language":"English","publisher":"New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Blake, J., 2021, Geology and calcite deposition of Fort Stanton-Snowy River Cave: Lite Geology, v. 48, p. 7-8.","productDescription":"2 p.","startPage":"7","endPage":"8","ipdsId":"IP-125320","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":384809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384785,"type":{"id":15,"text":"Index Page"},"url":"https://geoinfo.nmt.edu/publications/periodicals/litegeology/current/home.cfml"}],"country":"United States","state":"New Meico","otherGeospatial":"Fort Stanton-Snowy River Cave","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.43280029296875,\n 32.637061996573436\n ],\n [\n -105.43304443359374,\n 32.637061996573436\n ],\n [\n -105.43304443359374,\n 33.277731642555224\n ],\n [\n -106.43280029296875,\n 33.277731642555224\n ],\n [\n -106.43280029296875,\n 32.637061996573436\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813304,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70219109,"text":"70219109 - 2021 - Evaluating a laboratory flume microbiome as a window into natural riverbed biogeochemistry","interactions":[],"lastModifiedDate":"2021-03-24T12:13:12.940737","indexId":"70219109","displayToPublicDate":"2021-03-18T07:10:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating a laboratory flume microbiome as a window into natural riverbed biogeochemistry","docAbstract":"Riverbeds are hotspots for microbially-mediated reactions that exhibit pronounced variability in space and time. It is challenging to resolve biogeochemical mechanisms in natural riverbeds, as uncontrolled settings complicate data collection and interpretation. To overcome these challenges, laboratory flumes are often used as proxies for natural riverbed systems. Flumes capture spatiotemporal variability and thus allow for controlled investigations of riverbed biogeochemistry. These investigations implicitly rely on the assumption that the flume microbiome is similar to the microbiome of natural riverbeds. However, this assumption has not been tested and it is unknown how the microbiome of a flume compares to natural aquatic settings, including riverbeds. To evaluate the fundamental assumption that a flume hosts a microbiome similar to natural riverbed systems, we used 16s rRNA gene sequencing and publicly available data to compare the sediment microbiome of a single large laboratory flume to a wide variety of natural ecosystems including lake and marine sediments, river, lake, hyporheic, soil, and marine water, and bank and wetland soils. Richness and Shannon diversity metrics, analyses of variance, Bray-Curtis dissimilarity, and analysis of the common microbiomes between flume and river sediment all indicated that the flume microbiome more closely resembled natural riverbed sediments than other ecosystems, supporting the use of flume experiments for investigating natural microbially-mediated biogeochemical processes in riverbeds.
","language":"English","publisher":"Frontiers","doi":"10.3389/frwa.2021.596260","usgsCitation":"Kaufman, M., Warden, J.G., Cardenas, M.B., Stegen, J.C., Graham, E.B., and Brown, J., 2021, Evaluating a laboratory flume microbiome as a window into natural riverbed biogeochemistry: Frontiers in Water, v. 21, no. 3, 12 p., https://doi.org/10.3389/frwa.2021.596260.","productDescription":"12 p.","ipdsId":"IP-096581","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":453034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2021.596260","text":"Publisher Index Page"},{"id":384625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Kaufman, Matthew H.","contributorId":255711,"corporation":false,"usgs":false,"family":"Kaufman","given":"Matthew H.","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":812810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warden, John G. 0000-0003-1384-458X","orcid":"https://orcid.org/0000-0003-1384-458X","contributorId":215846,"corporation":false,"usgs":true,"family":"Warden","given":"John","email":"","middleInitial":"G.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":812811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cardenas, M. Bayani","contributorId":181932,"corporation":false,"usgs":false,"family":"Cardenas","given":"M.","email":"","middleInitial":"Bayani","affiliations":[],"preferred":false,"id":812812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stegen, James C.","contributorId":255712,"corporation":false,"usgs":false,"family":"Stegen","given":"James","email":"","middleInitial":"C.","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":812813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Graham, Emily B.","contributorId":202683,"corporation":false,"usgs":false,"family":"Graham","given":"Emily","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":812814,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Joseph","contributorId":255713,"corporation":false,"usgs":false,"family":"Brown","given":"Joseph","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":812815,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70219158,"text":"70219158 - 2021 - Ecosystem response persists after a prolonged marine heatwave","interactions":[],"lastModifiedDate":"2021-03-26T21:05:46.368776","indexId":"70219158","displayToPublicDate":"2021-03-18T07:09:45","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem response persists after a prolonged marine heatwave","docAbstract":"Some of the longest and most comprehensive marine ecosystem monitoring programs were established in the Gulf of Alaska following the environmental disaster of the Exxon Valdez oil spill over 30 years ago. These monitoring programs have been successful in assessing recovery from oil spill impacts, and their continuation decades later has now provided an unparalleled assessment of ecosystem responses to another newly emerging global threat, marine heatwaves. The 2014–2016 northeast Pacific marine heatwave (PMH) in the Gulf of Alaska was the longest lasting heatwave globally over the past decade, with some cooling, but also continued warm conditions through 2019. Our analysis of 187 time series from primary production to commercial fisheries and nearshore intertidal to offshore oceanic domains demonstrate abrupt changes across trophic levels, with many responses persisting up to at least 5 years after the onset of the heatwave. Furthermore, our suite of metrics showed novel community-level groupings relative to at least a decade prior to the heatwave. Given anticipated increases in marine heatwaves under current climate projections, it remains uncertain when or if the Gulf of Alaska ecosystem will return to a pre-PMH state.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-021-83818-5","usgsCitation":"Suryan, R.M., Arimitsu, M.L., Coletti, H.A., Hopcroft, R.R., Lindeberg, M., Barbeaux, S.J., Batten, S., Burt, W.J., Bishop, M.A., Bodkin, J.L., Brenner, R., Campbell, R.W., Cushing, D.A., Danielson, S.L., Dorn, M.W., Drummond, B., Esler, D., Gelatt, T.S., Hanselman, D.H., Iken, K., Irons, D.B., Hatch, S.A., Haught, S., Holderied, K., Kimmel, D.G., Konar, B.H., Kuletz, K.J., Kettle, A.B., Laurel, B.J., Maniscalco, J.M., Monson, D., Matkin, C.O., McKinstry, C., Moran, J., Olsen, D., Piatt, J., Palsson, W.A., Pegau, W., Rogers, L.A., Rojek, N.A., Schaefer, A., Spies, I.B., Straley, J., Strom, S.L., Szymkowiak, M., Sweeney, K.L., Weitzman, B., Yasumiishi, E.M., and Zador, S., 2021, Ecosystem response persists after a prolonged marine heatwave: Scientific Reports, v. 11, 6235, 17 p., https://doi.org/10.1038/s41598-021-83818-5.","productDescription":"6235, 17 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Effective management of forests requires accurate, precise estimates of deer population abundance to plan and justify management actions. Spotlight surveys in combination with distance sampling are a common method of estimating deer population abundance; however, spotlight surveys are known to have serious drawbacks such as high costs and sampling biases. Therefore, we tested the effectiveness of enumerating deer from unmanned aerial vehicle (UAV) flights, conducted 1 and 6 March 2018, to develop population and density estimates in 2 United States National Parks: Harpers Ferry National Historic Park (HAFE) and Monocacy National Battlefield (MONO). Concurrent spotlight surveys at MONO enabled us to compare estimates obtained by the 2 methods. Deer density estimates by 4 observers of UAV‐obtained thermal imagery from HAFE were 94.5 ± 3.9 deer/km2. Concurrent UAV and spotlight surveys at MONO found 19.7 ± 0.5 deer/km2 and 6.4 ± 4.9 deer/km2, respectively; suggesting that spotlight surveys may significantly underestimate deer densities. Despite the logistical challenges to UAV operation, our findings demonstrate that UAVs will become an invaluable tool for wildlife management as technology improves. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
Spatial cross-correlation among flood sequences impacts the accuracy of regional predictors. Our study investigates this impact for two regionalization procedures, generalized least squares (GLS) regression and top-kriging (TK), which deal with cross-correlation in two fundamentally different ways and therefore might be associated with different accuracy and uncertainty of predicted flood quantiles. We perform a Monte Carlo experiment based on a dataset of annual maximum flood series for 20 catchments in a hydrologically homogeneous region. Based on a log-Pearson type III parent distribution, we generate 3000 realizations of the region with different degrees of cross-correlation. For each realization, GLS and TK are applied in leave-one-out cross-validation to predict at-site flood quantiles. Our study shows that (a) TK outperforms GLS when catchment area is the only catchment descriptor used for predicting “true” population (theoretical) flood quantiles, regardless of the level of cross-correlation, and (b) GLS and TK perform similarly when multiple catchment descriptors are used.
Bat fatalities at wind energy facilities in North America are predominantly comprised of migratory, tree-dependent species, but it is unclear why these bats are at higher risk. Factors influencing bat susceptibility to wind turbines might be revealed by temporal patterns in their behaviors around these dynamic landscape structures. In northern temperate zones, fatalities occur mostly from July through October, but whether this reflects seasonally variable behaviors, passage of migrants, or some combination of factors remains unknown. In this study, we examined video imagery spanning one year in the state of Colorado in the United States, to characterize patterns of seasonal and nightly variability in bat behavior at a wind turbine. We detected bats on 177 of 306 nights representing approximately 3,800 hr of video and > 2,000 discrete bat events. We observed bats approaching the turbine throughout the night across all months during which bats were observed. Two distinct seasonal peaks of bat activity occurred in July and September, representing 30% and 42% increases in discrete bat events from the preceding months June and August, respectively. Bats exhibited behaviors around the turbine that increased in both diversity and duration in July and September. The peaks in bat events were reflected in chasing and turbine approach behaviors. Many of the bat events involved multiple approaches to the turbine, including when bats were displaced through the air by moving blades. The seasonal and nightly patterns we observed were consistent with the possibility that wind turbines invoke investigative behaviors in bats in late summer and autumn coincident with migration and that bats may return and fly close to wind turbines even after experiencing potentially disruptive stimuli like moving blades. Our results point to the need for a deeper understanding of the seasonality, drivers, and characteristics of bat movement across spatial scales.