Aim
The aim of the study was to investigate postfire regeneration patterns of Araucaria‐Nothofagus forests on the west slope of the Andes; to evaluate the relationship between remotely sensed burn severity and forest mortality; and to assess controls of burn severity on forest response at local spatio‐temporal scales.
Location
Araucanía region in the western Andean Range of south‐central Chile where fire occurred during the 2001–2002 season.
Methods
Sampling of prefire stand structure and postfire vegetation response was performed along a burn severity gradient a decade after the fire. We evaluated the relationship between field‐measured tree mortality and satellite‐derived burn severity using a generalized linear model. We fit zero‐inflated mixture models to regeneration data of each genus to assess the importance of abiotic variables, stand characteristics, and biotic interactions.
Results
The relative version of the delta Normalized Burn Ratio explained 85% of the variability in canopy mortality. Nearly 12,000 hectares burned; the majority at high severity (67%). Regeneration densities of both genera were lower at higher levels of burn severity and higher with greater total basal area (live, dead, and down trees). The relative effect size of burn severity on regeneration was nearly twice as large for Nothofagus, which suggests information legacies of Araucaria have cascading effects on postdisturbance material legacies.
Main conclusions
Araucaria‐Nothofagus mortality from wildfire can be readily mapped using satellite‐derived burn severity. Although environmental site characteristics and biotic interactions mediate regeneration, basal area, and burn severity are the main mechanisms controlling regeneration. Forest refugia and postfire regeneration are vulnerable to recurrent fire. Therefore, we expect future fire (either increased severity or frequency), driven by landscape level changes, as a potential mechanism that can reduce local resilience of these forests as initial postfire material legacies (e.g., refugia and regeneration) are removed from the landscape. Our findings highlight an approach to quantify important attributes of forest disturbance and refugia, and identify areas for monitoring postdisturbance regeneration as the forests throughout south‐central Chile and Argentina face a multitude of potential change agents.
Low‐temperature thermochronometry is widely used to measure the timing and rate of slip on normal faults. Rates are often derived from suites of footwall thermochronometer samples, but regression of age vs. structural depth fails to account for the trajectories of samples during fault slip. We demonstrate that in rotating fault blocks, regression of age‐depth data is susceptible to significant errors (>10%) in the identification of the initiation and rate of faulting. Advection of heat and topographic growth influence the thermal histories of exhumed particles, but for a range of geologically reasonable fault geometries and rates these effects produce Apatite (U‐Th)/He ages comparable to those derived from rotation through fixed isotherms. We apply the fixed‐isotherm model to published data from the Pine Forest Range and the East Range, Nevada, by incorporating field and thermochronologic constraints into a Markov chain Monte Carlo model. Modeled parameters for the Pine Forest Range are described by narrow ranges of geologically reasonable values. Compared to slip rates of 0.3‐0.8 km/Myr and an inititation of faulting ca. 11‐12 Ma derived from visual inspection, the model predicts an average slip rate of ~1.1 km/Myr and an onset of faulting ca. 9‐10 Ma. For the East Range fault block the model suggests faulting begain ~17 Ma with an extension rate of ~3 km/Myr and slowed to an extension rate of ~0.5 km/Myr at ~14 Ma. The absence of a preserved partial retention zone in the East Range sample set limits how well the model can predict fault block geometry.
","language":"English","publisher":"AGU","doi":"10.1029/2018TC005207","usgsCitation":"Johnstone, S., and Colgan, J.P., 2018, Interpretation of low‐temperature thermochronometer ages from tilted normal fault blocks: Tectonics, v. 37, no. 10, p. 3647-3667, https://doi.org/10.1029/2018TC005207.","productDescription":"21 p.","startPage":"3647","endPage":"3667","ipdsId":"IP-099026","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":468370,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/an3fr/","text":"External Repository"},{"id":357721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-15","publicationStatus":"PW","scienceBaseUri":"5bc02f8ce4b0fc368eb538bb","contributors":{"authors":[{"text":"Johnstone, Samuel 0000-0002-3945-2499","orcid":"https://orcid.org/0000-0002-3945-2499","contributorId":207545,"corporation":false,"usgs":true,"family":"Johnstone","given":"Samuel","email":"","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":746229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":746230,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198994,"text":"sir20185112 - 2018 - Flood-inundation maps for the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut","interactions":[],"lastModifiedDate":"2018-09-25T10:58:43","indexId":"sir20185112","displayToPublicDate":"2018-09-24T15:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5112","displayTitle":"Flood-inundation maps for the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut","title":"Flood-inundation maps for the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut","docAbstract":"A series of 11 digital flood-inundation maps was developed for a 5.5-mile reach of the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut, by the U.S. Geological Survey (USGS) in cooperation with the Town of Westerly, Rhode Island, and the Rhode Island Office of Housing and Community Development. The coverage of the maps extends from downstream from the Ashaway River inflow at the State Border between Hopkinton and Westerly, Rhode Island, and North Stonington, Connecticut, to about 500 feet (ft) downstream from the U.S. Route 1/Broad Street bridge on the State border between Westerly, Rhode Island, and Stonington, Connecticut. A one-dimensional step-backwater hydraulic model created and calibrated for an ongoing (2018) Federal Emergency Management Agency Flood-Insurance Study for New London County, Connecticut and Washington County, Rhode Island was updated for this study. The hydraulic model reflects the removal of the White Rock dam during 2015–16, and was calibrated using the stage-discharge relation at the USGS Pawcatuck River at Westerly, Rhode Island, streamgage (01118500) and documented high-water marks from the March 30, 2010, flood, which had a peak flow slightly greater than the estimated 0.2-percent annual exceedance probability floodflow.
The hydraulic model was used to compute water-surface profiles for 11 flood stages at 1-ft intervals referenced to the USGS Pawcatuck River at Westerly, Rhode Island, streamgage (01118500) and ranging from 6.0 ft (3.32 ft, North American Vertical Datum of 1988), which is the National Weather Service Advanced Hydrologic Prediction Service flood category “action stage,” to 16.0 ft (13.32 ft, North American Vertical Datum of 1988), which is the maximum stage of the stage-discharge relation at the streamgage and exceeds the National Weather Service Advanced Hydrologic Prediction Service flood category “major flood stage” of 11.0 ft. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a 1.0-ft vertical accuracy to create flood-inundation maps. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to 11 selected flood stages at the streamgage. The flood-inundation maps depict only riverine flooding and do not depict any tidal backwater or coastal storm surge that could occur in the lower part of the river reach. The flood-inundation maps can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation. Near-real-time stages and discharges at the Pawcatuck River streamgage can be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/. The National Weather Service Advanced Hydrologic Prediction Service provides flood forecast of stage for this site (WSTR1) at https://water.weather.gov/ahps/.
The availability of flood-inundation maps referenced to current and forecasted water levels at the USGS Pawcatuck River at Westerly, Rhode Island streamgage (01118500) can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during flood events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185112","collaboration":"Prepared in cooperation with the Town of Westerly, Rhode Island, and the Rhode Island Office of Housing and Community Development","usgsCitation":"Bent, G.C., and Lombard, P.J., 2018, Flood-inundation maps for the lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut: U.S. Geological Survey Scientific Investigations Report 2018–5112, 16 p., https://doi.org/10.3133/sir20185112.","productDescription":"Report: vii, 16 p.; Application Site; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-091691","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":357651,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z80 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood-Inundation Grids and Shapefiles for the Lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut"},{"id":437742,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G0N0TN","text":"USGS data release","linkHelpText":"River Channel Survey Data, Redwood Creek, California, 1953-2013"},{"id":437741,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610Z80","text":"USGS data release","linkHelpText":"Flood-Inundation Grids and Shapefiles for the Lower Pawcatuck River in Westerly, Rhode Island, and Stonington and North Stonington, Connecticut"},{"id":357652,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html ","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- Flood Inundation Mapper"},{"id":357649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5112/coverthb.jpg"},{"id":357650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5112/sir20185112.pdf","text":"Report","size":"1.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5112"}],"country":"United States","state":"Connecticut, Rhode Island","city":"North Stonington, Stonington, Westerly","otherGeospatial":"Lower Pawcatuck River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.85,\n 41.3667\n ],\n [\n -71.7833,\n 41.3667\n ],\n [\n -71.7833,\n 41.425\n ],\n [\n -71.85,\n 41.425\n ],\n [\n -71.85,\n 41.3667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Fanciful Fluorescence. Lurking Madness. Serene Expressions.
The titles of the images in this fifth edition of Earth As Art speak to the powerfully artistic qualities of Earth’s natural features when tinged with unnatural colors.
Art serves as a great partner in the communication of science, bringing emotion to the pursuit of understanding. The pieces in this collection look like abstract art but are actual satellite images.
Satellite imagery has long served the rational and disciplined approaches of science to better understand our Earth. But these images can also, with a bit of creativity, excite our imaginations with the beauty and art that surround us.
In this newest collection of Earth As Art, we continue to display the Earth as our eyes cannot see it—in creative combinations of visible and infrared light. Although beauty in art is often subjective, the science data provide objective views of the Earth’s changing land surface. However, we will let these images speak to you as art. Enjoy the latest additions to Earth As Art!
The images in the Earth As Art 5 collection can be downloaded for free from the Earth Resources Observation and Science (EROS) Center Image Gallery at
https://www.usgs.gov/centers/eros/science/earth-art-5.
Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD
In river valleys, sediment moves between active river channels, near-channel deposits including bars and floodplains, and upland environments such as terraces and aeolian dunefields. Sediment availability is a prerequisite for the sustained transfer of material between these areas, and for the eco-geomorphic functioning of river networks in general. However, the difficulty of monitoring sediment availability and movement at the reach or corridor scale has hindered our ability to quantify and forecast the response of sediment transfer to hydrologic or land cover alterations. Here we leverage spatiotemporally extensive datasets quantifying sediment areal coverage along a 28 km reach of the Colorado River in Grand Canyon, southwestern USA. In concert with information on hydrologic alteration and vegetation encroachment resulting from the operation of Glen Canyon Dam (constructed in 1963) upstream of our study reach, we model the relative and combined influence of changes in (a) flow and (b) riparian vegetation extent on the areal extent of sediment available for transport in the river valley over the period from 1921 to 2016. In addition, we use projections of future streamflow and vegetation encroachment to forecast sediment availability over the 20 year period from 2016 to 2036. We find that hydrologic alteration has reduced the areal extent of bare sediment by 9% from the pre- to post-dam periods, whereas vegetation encroachment further reduced bare sediment extent by 45%. Over the next 20 years, the extent of bare sediment is forecast to be reduced by an additional 12%. Our results demonstrate the impact of river regulation, specifically the loss of annual low flows and associated vegetation encroachment, on reducing the sediment available for transfer within river valleys. This work provides an extendable framework for using high-resolution data on streamflow and land cover to assess and forecast the impact of watershed perturbation (e.g. river regulation, land cover shifts, climate change) on sediment connectivity at the corridor scale.
","language":"English","publisher":"SAGE Publishing","doi":"10.1177/0309133318795846","usgsCitation":"Kasprak, A., Sankey, J.B., Buscombe, D.D., Caster, J., East, A.E., and Grams, P.E., 2018, Quantifying and forecasting changes in the areal extent of river valley sediment in response to altered hydrology and land cover: Progress in Physical Geography: Earth and Environment, v. 42, no. 6, p. 739-764, https://doi.org/10.1177/0309133318795846.","productDescription":"26 p.","startPage":"739","endPage":"764","ipdsId":"IP-088947","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468374,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/0309133318795846","text":"Publisher Index Page"},{"id":437745,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SX3MGY","text":"USGS data release","linkHelpText":"River Valley Sediment Connectivity Data, Colorado River, Grand Canyon"},{"id":357659,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park, Lower Marble Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.93145751953125,\n 36.16781389727332\n ],\n [\n -111.77352905273438,\n 36.16781389727332\n ],\n [\n -111.77352905273438,\n 36.4223874864237\n ],\n [\n -111.93145751953125,\n 36.4223874864237\n ],\n [\n -111.93145751953125,\n 36.16781389727332\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-13","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538d3","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":204162,"corporation":false,"usgs":true,"family":"Kasprak","given":"Alan","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buscombe, Daniel D. 0000-0001-6217-5584","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":198817,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","middleInitial":"D.","affiliations":[],"preferred":false,"id":745885,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caster, Joshua 0000-0002-2858-1228 jcaster@usgs.gov","orcid":"https://orcid.org/0000-0002-2858-1228","contributorId":199033,"corporation":false,"usgs":true,"family":"Caster","given":"Joshua","email":"jcaster@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":745886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745887,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70212475,"text":"70212475 - 2018 - A new Enceladus global control network, image mosaic, and updated pointing kernels from Cassini's thirteen-year mission","interactions":[],"lastModifiedDate":"2020-08-18T13:45:37.871805","indexId":"70212475","displayToPublicDate":"2018-09-24T09:06:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"A new Enceladus global control network, image mosaic, and updated pointing kernels from Cassini's thirteen-year mission","docAbstract":"NASA's Cassini spacecraft spent 13 years exploring the Saturn system, including 23 targeted flybys of the small, geologically active moon Enceladus. These flybys provided a wealth of image data from Cassini's Imaging Science Subsystem. To improve the usability of the Enceladus data set, we created a new, global photogrammetric control network for Enceladus that enabled compilation of a versatile cartographic package to support geologic mapping and other investigations. The network used 586 images in four image filters with a pixel scale generally between 50 and 500 m per pixel and a phase angle less than 120° and consisted of 10,362 tie points and 173,704 individual image measures, averaging nearly 17 measures per tie point. Least squares bundle adjustment resulted in a root‐mean‐square residual of 0.45 pixel, corresponding to root‐mean‐square ground point uncertainties of 66, 51, and 46 m in latitude, longitude, and radius, respectively. Using our geodetic control network, we created new global image mosaics, coregistered flyby mosaics to support geologic mapping, and updated pointing kernels for every image used in the solution. These products, including the updated pointing kernels, are available to the community through NASA's Planetary Data System Imaging Annex. The bundle adjustment solution also yielded independently determined shape information, resulting in radii within the stated uncertainty of International Astronomical Union values. The challenges of the data set, and the technical methodology described here are applicable to bodies imaged during multiple flybys with variable viewing and illumination geometry, including other midsized satellites of Saturn, and the Europa Clipper mission.
Water use in the State of Washington has evolved during the past century from small withdrawals used for domestic and stock needs to the diverse needs of current public supply systems, domestic water users, irrigation projects, industrial plants, and aquaculture industries. Increasing demand for water makes the accountability of water use an important issue.
A few State and local agencies in Washington collect water-use information for specific categories of water use; currently, only the U.S. Geological Survey (USGS) compiles cumulative water-use information across the State for a comprehensive range of uses.
Since 1950, on a 5-year cycle, the USGS has compiled and published estimates of water withdrawal and use for specific categories aggregated at the county, State, and national level. The information is shared publicly through the USGS Water Use in the United States website (https://water.usgs.gov/watuse/) and national publications that detail water use definitions, categories, trends, and data for every state. The data are compiled individually by each state from available sources, and are augmented by estimates from national models for categories that have limited data. The USGS Washington Water Science Center is responsible for compiling their estimates and maintains the State water use webpage (https://wa.water.usgs.gov/data/wuse/) of State-level information and links to the national program.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183058","usgsCitation":"Fasser, E.T., 2018, Water use in Washington, 2015: U.S. Geological Survey Fact Sheet 2018-3058, 4 p., https://doi.org/10.3133/fs20183058.","productDescription":"4 p.","ipdsId":"IP-098099","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":357683,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3058/coverthb2.jpg"},{"id":357592,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3058/fs20183058.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3058"}],"country":"United 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\"}}]}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The 2018 census of southern sea otters (Enhydra lutris nereis) was conducted from late April to mid-May along the mainland coast of central California and in April at San Nicolas Island in southern California. The 3-year average of combined counts from the mainland range and San Nicolas Island was 3,128, a decrease of 58 sea otters from the previous year. The 5-year average trend in abundance, including both the mainland range and San Nicolas Island populations, remains positive at 1.3 percent per year. Continuing lack of growth in the range peripheries likely explains the cessation of range expansion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1097","usgsCitation":"Hatfield, B.B., Yee, J.L., Kenner, M.C., Tomoleoni, J.A., and Tinker, M.T., 2018, California sea otter (Enhydra lutris nereis) census results, spring 2018: U.S. Geological Survey Data Series 1097, 10 p., https://doi.org/10.3133/ds1097.","productDescription":"Report: iv, 10 p.; Data release","onlineOnly":"Y","ipdsId":"IP-101451","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":357646,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98012HE","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Annual California sea otter census—2018 spring census summary"},{"id":357644,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1097/coverthb.jpg"},{"id":357645,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1097/ds1097.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1097"}],"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 -123,\n 33\n ],\n [\n -119,\n 33\n ],\n [\n -119,\n 37.2009909007\n ],\n [\n -123,\n 37.2009909007\n ],\n [\n -123,\n 33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
Modoc Hall, Room 4004
Sacramento, California 95819
We tested the use of high‐resolution infrared (IR) camera technology and distance sampling analyses to estimate abundance of feral horses (Equus caballus) during 2015–2016 in the McCullough Peaks Herd Management Area, Wyoming, USA. Infrared technology is becoming more common in ungulate population monitoring. The quality of IR cameras now allows ungulate species to be differentiated. Imperfect detection is a common problem in aerial surveys, so we tested the use of distance sampling analyses to account for imperfect detection probability. We conducted 2 aerial surveys in a sagebrush ecosystem with a demographically closed horse population. True abundance was known to within ±4 animals as a result of intensive, ground‐based monitoring of each animal, all of which are uniquely identifiable. After truncation of our data, the most supported detection function was a uniform function with a detection probability equal to 1.0 out to 255 m. Our analyses yielded results that were within 10% of true abundance, but the coefficient of variation (CV) was large (36–58%) assuming a small sampling fraction. However, our truncated surveys covered approximately 95% of the herd management area. By including a finite population correction factor in our calculations of variance estimates, CVs (8–13%) were dramatically reduced. We found the combination of IR surveys and distance sampling analysis to be a useful method to estimate feral horse abundance in sagebrush vegetation type, which had limited cover to obscure horses. Repeated testing in sagebrush ecosystems as well as further testing in other habitat types and under differing conditions will inform how general our approach can be.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.912","usgsCitation":"Schoenecker, K.A., Doherty, P., Hourt, J., and Romero, J., 2018, Testing infrared camera surveys and distance analyses to estimate feral horse abundance in a known population: Wildlife Society Bulletin, v. 42, no. 3, p. 452-459, https://doi.org/10.1002/wsb.912.","productDescription":"8 p.","startPage":"452","endPage":"459","ipdsId":"IP-085078","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468376,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doaj.org/article/fcd332e3ab024f1d9ae4580186a01eee","text":"Publisher Index Page"},{"id":373552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"McCullough Peaks Herd Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.8416,\n 44.3333\n ],\n [\n -108.5083,\n 44.3333\n ],\n [\n -108.5083,\n 44.8333\n ],\n [\n -108.8416,\n 44.8333\n ],\n [\n -108.8416,\n 44.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X schoeneckerk@usgs.gov","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":2001,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn","email":"schoeneckerk@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":785659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doherty, Paul","contributorId":223632,"corporation":false,"usgs":false,"family":"Doherty","given":"Paul","email":"","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":785660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hourt, Jacob","contributorId":223633,"corporation":false,"usgs":false,"family":"Hourt","given":"Jacob","email":"","affiliations":[{"id":40752,"text":"Owyhee Air Research","active":true,"usgs":false}],"preferred":false,"id":785661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Romero, John","contributorId":223634,"corporation":false,"usgs":false,"family":"Romero","given":"John","affiliations":[{"id":40752,"text":"Owyhee Air Research","active":true,"usgs":false}],"preferred":false,"id":785662,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199616,"text":"70199616 - 2018 - Assessing the impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek watershed, Ohio","interactions":[],"lastModifiedDate":"2018-09-24T11:21:25","indexId":"70199616","displayToPublicDate":"2018-09-21T11:21:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek watershed, Ohio","docAbstract":"The Eagle Creek watershed, a small subbasin (125 km2) within the Maumee River Basin, Ohio, was selected as a part of the Great Lakes Restoration Initiative (GLRI) “Priority Watersheds” program to evaluate the effectiveness of agricultural Best Management Practices (BMPs) funded through GLRI at the field and watershed scales. The location and quantity of BMPs were obtained from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) database. A Soil and Water Assessment Tool (SWAT) model was built and calibrated for this predominantly agricultural Eagle Creek watershed, incorporating NCP BMPs and monitoring data at the watershed outlet, an edge-of-field (EOF), and tile monitoring sites. Input air temperature modifications were required to induce simulated tile flow to match monitoring data. Calibration heavily incorporated tile monitoring data to correctly proportion surface and subsurface flow, but calibration statistics were unsatisfactory at the EOF and tile monitoring sites. At the watershed outlet, satisfactory to very good calibration statistics were achieved over a 2-year calibration period, and satisfactory statistics were found in the 2-year validation period. SWAT fixes parameters controlling nutrients primarily at the watershed level; a refinement of these parameters at a smaller-scale could improve field-level calibration. Field-scale modeling results indicate that filter strips (FS) are the most effective single BMPs at reducing dissolved reactive phosphorus, and FS typically decreased sediment and nutrient yields when added to any other BMP or BMP combination. Cover crops were the most effective single, in-field practice by reducing nutrient loads over winter months. Watershed-scale results indicate BMPs can reduce sediment and nutrients, but reductions due to NCP BMPs in the Eagle Creek watershed for all water-quality constituents were less than 10%. Hypothetical scenarios simulated with increased BMP acreages indicate larger investments of the appropriate BMP or BMP combination can decrease watershed level loads.
","language":"English","publisher":"MDPI","doi":"10.3390/w10101299","usgsCitation":"Merriman, K.R., Daggupati, P., Srinivasan, R., Toussant, C., Russell, A.M., and Hayhurst, B.A., 2018, Assessing the impact of site-specific BMPs using a spatially explicit, field-scale SWAT model with edge-of-field and tile hydrology and water-quality data in the Eagle Creek watershed, Ohio: Water, v. 10, no. 10, p. 1-37, https://doi.org/10.3390/w10101299.","productDescription":"Article 1299; 37 p.","startPage":"1","endPage":"37","ipdsId":"IP-092960","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468377,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10101299","text":"Publisher Index Page"},{"id":357665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Eagle Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.8333,\n 40.67\n ],\n [\n -83.5,\n 40.67\n ],\n [\n -83.5,\n 41\n ],\n [\n -83.8333,\n 41\n ],\n [\n -83.8333,\n 40.67\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-21","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538d9","contributors":{"authors":[{"text":"Merriman, Katherine R. 0000-0002-1303-2410 kmerriman@usgs.gov","orcid":"https://orcid.org/0000-0002-1303-2410","contributorId":4973,"corporation":false,"usgs":true,"family":"Merriman","given":"Katherine","email":"kmerriman@usgs.gov","middleInitial":"R.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":745973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daggupati, Prasad","contributorId":203354,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","affiliations":[{"id":36214,"text":"Univeristy of Guelph","active":true,"usgs":false}],"preferred":false,"id":745974,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Srinivasan, Raghavan","contributorId":203355,"corporation":false,"usgs":false,"family":"Srinivasan","given":"Raghavan","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":745975,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Toussant, Chad","contributorId":208117,"corporation":false,"usgs":true,"family":"Toussant","given":"Chad","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745976,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russell, Amy M. 0000-0003-0582-0094 arussell@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0094","contributorId":200011,"corporation":false,"usgs":true,"family":"Russell","given":"Amy","email":"arussell@usgs.gov","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745977,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayhurst, Brett A. 0000-0002-1717-2015 bhayhurs@usgs.gov","orcid":"https://orcid.org/0000-0002-1717-2015","contributorId":3398,"corporation":false,"usgs":true,"family":"Hayhurst","given":"Brett","email":"bhayhurs@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745978,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199551,"text":"70199551 - 2018 - Using tectonic tremor to constrain seismic‐wave attenuation in Cascadia","interactions":[],"lastModifiedDate":"2018-10-23T16:49:12","indexId":"70199551","displayToPublicDate":"2018-09-20T15:52:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Using tectonic tremor to constrain seismic‐wave attenuation in Cascadia","docAbstract":"Tectonic tremor can be used to constrain seismic‐wave attenuation for use in ground‐motion prediction equations (GMPEs) in regions where moderately sized earthquakes occur infrequently. Here we quantify seismic‐wave attenuation by inverting tremor ground motion amplitudes in different frequency bands of interest, to determine frequency dependence of and spatial variations in seismic‐wave attenuation in Cascadia. Due to the density of tremor data, we are able to resolve along‐strike variations in the attenuation parameter. We find that tectonic tremor exhibits the frequency dependence expected for attenuation, as determined from GMPEs developed from moderate‐to‐large magnitude earthquakes. This implies that attenuation along these paths is independent of the source mechanism. This study demonstrates that tectonic tremor can be used to provide insight into the physical factors responsible for attenuation, and to refine estimates of attenuation for ground‐motion prediction, thus having important implications for hazard assessment and engineering seismology.
","language":"English","publisher":"AGU","doi":"10.1029/2018GL079344","usgsCitation":"Littel, G.F., Thomas, A.M., and Baltay Sundstrom, A.S., 2018, Using tectonic tremor to constrain seismic‐wave attenuation in Cascadia: Geophysical Research Letters, v. 45, no. 18, p. 9579-9587, https://doi.org/10.1029/2018GL079344.","productDescription":"9 p.","startPage":"9579","endPage":"9587","ipdsId":"IP-101242","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl079344","text":"Publisher Index Page"},{"id":357578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128,\n 39.5\n ],\n [\n -121,\n 39.5\n ],\n [\n -121,\n 50.5\n ],\n [\n -128,\n 50.5\n ],\n [\n -128,\n 39.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","issue":"18","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-27","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538db","contributors":{"authors":[{"text":"Littel, Geena F.","contributorId":208081,"corporation":false,"usgs":false,"family":"Littel","given":"Geena","email":"","middleInitial":"F.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":745834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Amanda M.","contributorId":200641,"corporation":false,"usgs":false,"family":"Thomas","given":"Amanda","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":745835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":745833,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199530,"text":"70199530 - 2018 - Compositional data analysis of coal combustion products with an application to a Wyoming power plant","interactions":[],"lastModifiedDate":"2018-09-20T15:40:17","indexId":"70199530","displayToPublicDate":"2018-09-20T15:40:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2701,"text":"Mathematical Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Compositional data analysis of coal combustion products with an application to a Wyoming power plant","docAbstract":"A mathematically sound approach for summarizing chemical analyses of feed coal and all its combustion products (bottom ash, economizer fly ash, and fly ash) is presented. The nature of the data requires the application of compositional techniques when conducting statistical analysis, techniques that have not been applied before to the study of partitioning of elements between the coal that enters the boiler and the associated coal combustion products. A collection of descriptive and inferential compositional techniques was used to analyze the coal combustion products from a Wyoming power plant burning Paleocene Wyodak–Anderson coal. The significance of the fluctuation in ash composition is determined by using a Hotelling’s T-squared test and bootstrapping. Tree displays allow for visualization of the progressive effect of filters in removal of chemical species based on their geochemical composition. Results indicate that, in general, as the suspended combustion products entrained in the flue gases move closer to the stack, chemical species are removed from the combustion gas, starting with minerals associated with elements having the lowest volatility.
","language":"English","publisher":"Springer","doi":"10.1007/s11004-018-9736-z","usgsCitation":"Martín-Fernández, J., Olea, R., and Ruppert, L.F., 2018, Compositional data analysis of coal combustion products with an application to a Wyoming power plant: Mathematical Geosciences, v. 50, no. 6, p. 639-657, https://doi.org/10.1007/s11004-018-9736-z.","productDescription":"19 p.","startPage":"639","endPage":"657","ipdsId":"IP-089735","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-03","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538dd","contributors":{"authors":[{"text":"Martín-Fernández, J. A.","contributorId":208080,"corporation":false,"usgs":false,"family":"Martín-Fernández","given":"J. A.","affiliations":[],"preferred":false,"id":745831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruppert, Leslie F. 0000-0002-7453-1061 lruppert@usgs.gov","orcid":"https://orcid.org/0000-0002-7453-1061","contributorId":660,"corporation":false,"usgs":true,"family":"Ruppert","given":"Leslie","email":"lruppert@usgs.gov","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":745832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199535,"text":"70199535 - 2018 - The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts","interactions":[],"lastModifiedDate":"2018-09-21T10:58:38","indexId":"70199535","displayToPublicDate":"2018-09-20T15:35:21","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts","docAbstract":"Ecologists regularly use animal contact networks to describe interactions underlying pathogen transmission, gene flow, and information transfer. However, empirical descriptions of contact often overlook some features of individual movement, and decisions about what kind of network to use in a particular setting are commonly ad hoc. Here, we relate individual movement trajectories to contact networks through a tripartite network model of individual, space, and time nodes. Most networks used in animal contact studies (e.g. individual association networks, home range overlap networks, and spatial networks) are simplifications of this tripartite model. The tripartite structure can incorporate a broad suite of alternative ecological metrics like home range sizes and patch occupancy patterns into inferences about contact network metrics such as modularity and degree distribution. We demonstrate the model's utility with two simulation studies using alternative forms of ecological data to constrain the tripartite network's structure and inform expectations about the harder-to-measure metrics related to contact.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2018.0670","usgsCitation":"Manlove, K.R., Aiello, C.M., Sah, P., Cummins, B., Hudson, P.J., and Cross, P.C., 2018, The ecology of movement and behaviour: a saturated tripartite network for describing animal contacts: Proceedings of the Royal Society B: Biological Sciences, v. 285, no. 1887, https://doi.org/10.1098/rspb.2018.0670.","ipdsId":"IP-092136","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468381,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rspb.2018.0670","text":"External Repository"},{"id":357568,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"285","issue":"1887","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-19","publicationStatus":"PW","scienceBaseUri":"5bc02f99e4b0fc368eb538df","contributors":{"authors":[{"text":"Manlove, Kezia R.","contributorId":198305,"corporation":false,"usgs":false,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":745807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiello, Christina M. 0000-0002-2399-5464 caiello@usgs.gov","orcid":"https://orcid.org/0000-0002-2399-5464","contributorId":5617,"corporation":false,"usgs":true,"family":"Aiello","given":"Christina","email":"caiello@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":745808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sah, Pratha","contributorId":127768,"corporation":false,"usgs":false,"family":"Sah","given":"Pratha","email":"","affiliations":[{"id":7145,"text":"Department of Biology, Georgetown University, Washington DC","active":true,"usgs":false}],"preferred":false,"id":745809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cummins, Bree","contributorId":208072,"corporation":false,"usgs":false,"family":"Cummins","given":"Bree","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":745810,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":204377,"corporation":false,"usgs":false,"family":"Hudson","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":745811,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":745806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70201121,"text":"70201121 - 2018 - Segmentation of Mississippi’s natural and artificial lakes","interactions":[],"lastModifiedDate":"2019-01-28T08:42:44","indexId":"70201121","displayToPublicDate":"2018-09-20T14:21:48","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Segmentation of Mississippi’s natural and artificial lakes","docAbstract":"Segmentations divide a diverse resource into groups, or segments, based on distinctive attributes that may respond similarly to management actions. A 4-way segmentation based on lake origin (natural or artificial) and size (small or large) was constructed for Mississippi lakes using a 30 yr data set. We aimed to document elements distinguishing these segments to understand relationships among them and to seek insight into lake management that may be apparent at the segment scale but not at the lake scale. Analyses pinpointed differences among the 4 segments relative to nutrient levels, fish assemblage composition, fishery characteristics, angler catch, and fishery management objectives. In general, most artificial lakes were eutrophic, varied widely relative to species composition depending on whether they impounded small or large rivers, their fish assemblages could be heavily influenced by stocking, provided principally centrarchid fisheries, and the management focus was on angler harvest. Most natural lakes were hypereutrophic, included higher species richness, provided a greater diversity of fisheries, and the management focus was on fish populations and habitat. Fishing success was similar across segments. The group-wise differences substantiate the segmentation and bring into focus a new level of concepts not typically relevant when considering lakes in isolation, such as issues about lake quantities, similarities, and geographical distributions. The segmentation represents the framework needed for considering lakes as parts of a larger and interactive management system.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2018.1481469","usgsCitation":"Miranda, L.E., Bull, L.A., Colvin, M., Hubbard, W., and Pugh, L., 2018, Segmentation of Mississippi’s natural and artificial lakes: Lake and Reservoir Management, v. 34, no. 4, p. 376-391, https://doi.org/10.1080/10402381.2018.1481469.","productDescription":"16 p.","startPage":"376","endPage":"391","ipdsId":"IP-091414","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":359806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"34","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-20","publicationStatus":"PW","scienceBaseUri":"5c0108d4e4b0815414cc2df9","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":752796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bull, L. A.","contributorId":204902,"corporation":false,"usgs":false,"family":"Bull","given":"L.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":752802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colvin, M.E.","contributorId":53190,"corporation":false,"usgs":true,"family":"Colvin","given":"M.E.","affiliations":[],"preferred":false,"id":752803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hubbard, W.D.","contributorId":6245,"corporation":false,"usgs":true,"family":"Hubbard","given":"W.D.","email":"","affiliations":[],"preferred":false,"id":752804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pugh, L.L.","contributorId":73763,"corporation":false,"usgs":true,"family":"Pugh","given":"L.L.","email":"","affiliations":[],"preferred":false,"id":752805,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70213242,"text":"70213242 - 2018 - A method to detect discontinuities in census data","interactions":[],"lastModifiedDate":"2020-09-16T13:31:14.714975","indexId":"70213242","displayToPublicDate":"2018-09-20T13:35:09","publicationYear":"2018","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":"A method to detect discontinuities in census data","docAbstract":"The distribution of pattern across scales has predictive power in the analysis of complex systems. Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.4297","usgsCitation":"Barichievy, C., Angeler, D., Eason, T.N., Garmestani, A.S., Nash, K., Stow, C., Sundstrom, S., and Allen, C.R., 2018, A method to detect discontinuities in census data: Ecology and Evolution, v. 8, no. 19, p. 9614-9623, https://doi.org/10.1002/ece3.4297.","productDescription":"10 p.","startPage":"9614","endPage":"9623","ipdsId":"IP-098532","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":468382,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.4297","text":"Publisher Index Page"},{"id":378407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"19","noUsgsAuthors":false,"publicationDate":"2018-09-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Barichievy, C. 0000-0003-4088-953X","orcid":"https://orcid.org/0000-0003-4088-953X","contributorId":240685,"corporation":false,"usgs":false,"family":"Barichievy","given":"C.","affiliations":[{"id":13431,"text":"Zoological Society of London","active":true,"usgs":false}],"preferred":false,"id":798757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angeler, D. G.","contributorId":240686,"corporation":false,"usgs":false,"family":"Angeler","given":"D. G.","affiliations":[{"id":12665,"text":"University of Cape Town","active":true,"usgs":false}],"preferred":false,"id":798758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eason, T. N.","contributorId":205437,"corporation":false,"usgs":false,"family":"Eason","given":"T.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":798759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garmestani, A. S.","contributorId":240687,"corporation":false,"usgs":false,"family":"Garmestani","given":"A.","email":"","middleInitial":"S.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":798760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nash, K.L. 0000-0003-0976-3197","orcid":"https://orcid.org/0000-0003-0976-3197","contributorId":240688,"corporation":false,"usgs":false,"family":"Nash","given":"K.L.","email":"","affiliations":[{"id":48132,"text":"Centre for Marine Socioecology","active":true,"usgs":false}],"preferred":false,"id":798761,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stow, C.A.","contributorId":240689,"corporation":false,"usgs":false,"family":"Stow","given":"C.A.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":798762,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sundstrom, S.","contributorId":240690,"corporation":false,"usgs":false,"family":"Sundstrom","given":"S.","affiliations":[{"id":36892,"text":"University of Nebraska","active":true,"usgs":false}],"preferred":false,"id":798763,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":798764,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198571,"text":"sir20185107 - 2018 - Annual and approximately quarterly series peak streamflow derived from interpretations of indirect measurements for a crest-stage gage network in Texas through water year 2015","interactions":[],"lastModifiedDate":"2018-09-20T15:59:50","indexId":"sir20185107","displayToPublicDate":"2018-09-20T11:57:01","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5107","title":"Annual and approximately quarterly series peak streamflow derived from interpretations of indirect measurements for a crest-stage gage network in Texas through water year 2015","docAbstract":"In 2006, the U.S. Geological Survey (USGS), in
cooperation with the Texas Department of Transportation,
began collecting annual and approximately quarterly series
peak-streamflow data at streamflow-gaging stations in smallto
medium-sized watersheds in central and western Texas
as part of a crest-stage gage (CSG) network, along with
selected flood-hydrograph data at a subset of these stations.
CSGs record the peak stage during storm events, which is
the maximum gage height (elevation of water surface above
a local vertical datum), at each CSG station. Established and
widely used indirect methods of peak streamflow estimation
and interpretation, such as culvert-flow, slope-area, and
flow-over-road methods, are used in conjunction with peak
gage height data to create the database of peak streamflow
described herein. The CSG network is focused on hydrology
of small- to medium-sized watersheds in central and western
Texas because additional streamflow data for this semiarid
to arid study area will eventually provide for more statistical
information and presumably reduced uncertainty in regional
regression equations or other regionalized statistical methods
for peak-streamflow frequency estimation at ungaged
locations. The database of annual and approximately quarterly
peak streamflow is published through USGS ScienceBase and
described in this report.
Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Perchlorate (ClO4−) in groundwater can be from synthetic or natural sources. Natural sources include ClO4− associated with historical application of imported natural nitrate fertilizer from the Atacama Desert of Chile, and indigenous ClO4− that accumulates locally in arid regions from atmospheric deposition. The Rialto-Colton groundwater subbasin, 80 km east of Los Angeles, California, includes two mapped ClO4− plumes from known military/industrial sources. Larger areas downgradient from those plumes, and in the Chino subbasin to the southwest, also contain ClO4−. Perchlorate from wells was analyzed for chlorine and oxygen stable isotope ratios (δ37Cl, δ18O, Δ17O) and radioactive chlorine-36(36Cl) isotopic abundance, along with other geochemical, isotopic, and hydrogeologic data. Isotopic data show that synthetic ClO4− was the dominant source within the mapped plumes. Downgradient from the mapped plumes, and in the Chino subbasin, the dominant source of ClO4− was related to past agricultural use of Chilean (Atacama) nitrate fertilizer. The 36Cl and δ18O data indicate that wells having predominantly synthetic or Atacama ClO4− also contained small fractions of indigenous ClO4−. Little or no differences were observed in isotopic composition or ClO4− source with depth in depth-dependent data from selected wells. Indigenous ClO4− was most evident in upgradient wells having ClO4− concentrations <1 μg/L, consistent with its occurrence as a background constituent throughout the region. Stable isotope ratios of chlorine and oxygen and 36Cl isotopic abundance data provided relatively unambiguous discrimination of synthetic and Atacama sources in most wells having ClO4− concentrations greater than 1 μg/L.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2018.08.020","usgsCitation":"Hatzinger, P.B., Bohlke, J., Sturchio, N.C., Izbicki, J.A., and Teague, N.F., 2018, Four-dimensional isotopic approach to identify perchlorate sources in groundwater: Application to the Rialto-Colton and Chino subbasins, southern California (USA): Applied Geochemistry, v. 97, p. 213-225, https://doi.org/10.1016/j.apgeochem.2018.08.020.","productDescription":"13 p.","startPage":"213","endPage":"225","ipdsId":"IP-095009","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468383,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2018.08.020","text":"Publisher Index Page"},{"id":357543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Rialto-Colton and Chino subbasins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.5,\n 34.0333\n ],\n [\n -117.25,\n 34.0333\n ],\n [\n -117.25,\n 34.1833\n ],\n [\n -117.5,\n 34.1833\n ],\n [\n -117.5,\n 34.0333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"97","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f9ae4b0fc368eb538e5","contributors":{"authors":[{"text":"Hatzinger, Paul B.","contributorId":149376,"corporation":false,"usgs":false,"family":"Hatzinger","given":"Paul","email":"","middleInitial":"B.","affiliations":[{"id":17721,"text":"Shaw Environmental, Princeton, NJ","active":true,"usgs":false}],"preferred":false,"id":745394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":745393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturchio, Neil C.","contributorId":149375,"corporation":false,"usgs":false,"family":"Sturchio","given":"Neil","email":"","middleInitial":"C.","affiliations":[{"id":15289,"text":"University of Illinois, Ven Te Chow Hydrosystems Laboratory","active":true,"usgs":false}],"preferred":false,"id":745395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":152474,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","email":"jaizbick@usgs.gov","middleInitial":"A.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teague, Nicholas F. 0000-0001-5289-1210 nteague@usgs.gov","orcid":"https://orcid.org/0000-0001-5289-1210","contributorId":2145,"corporation":false,"usgs":true,"family":"Teague","given":"Nicholas","email":"nteague@usgs.gov","middleInitial":"F.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745397,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199223,"text":"ofr20181148 - 2018 - PRISM marine sites—The history of PRISM sea surface temperature estimation","interactions":[],"lastModifiedDate":"2018-09-19T16:44:54","indexId":"ofr20181148","displayToPublicDate":"2018-09-19T14:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1148","title":"PRISM marine sites—The history of PRISM sea surface temperature estimation","docAbstract":"For more than three decades, the U.S. Geological Survey (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project has compiled paleoenvironmental data with the goal of reconstructing global conditions during the warm interval in the middle of the Piacenzian Age of the Pliocene Epoch (about 3.3 to 3.0 million years ago). Because this is the most recent interval of time in which climatic conditions were similar to those expected in the near future, a global reconstruction of conditions from this interval offers an imperfect yet useful representation of near future conditions. PRISM reconstructions have been used extensively as boundary conditions in general circulation model experiments aimed at better understanding Pliocene climate. They have also served as hindcasting targets when testing the ability of climate models to simulate real climates of the past, an exercise in estimating a model’s ability to accurately predict future climate. As data coverage has grown and model precision has improved, PRISM datasets have become important validation tools for pinpointing discrete areas of data-model disagreement and model-model disagreement. The Pliocene sea surface temperature (SST) dataset is the best developed component of the PRISM reconstructions and is the keystone of Pliocene paleoclimate research. For the first time, we compile all data related to PRISM SST estimation. This discussion chronicles the history of PRISM SST research as it evolved, responding to advances in paleochronology and paleotemperature estimation. Paleoclimatic considerations unique to each location are illustrated, as are any new developments since the initial publication of the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181148","usgsCitation":"Robinson, M.M., Dowsett, H.J., Foley, K.M., and Riesselman, C.R., 2018, PRISM marine sites—The history of PRISM sea surface temperature estimation: U.S. Geological Survey Open-File Report 2018–1148, 49 p., https://doi.org/10.3133/ofr20181148.","productDescription":"vi, 49 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087999","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":357306,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1148/ofr20181148.pdf","text":"Report","size":"1 MB","description":"OFR 2018-1148"},{"id":357305,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1148/coverthb3.jpg"}],"contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
A large subaerial landslide entered Taan Fiord, Alaska, on 17 October 2015 producing a tsunami with runup to 193 m. We use LiDAR data to show the slide volume to be 76 + 3/−4 million cubic meters and that 51,000,000 m3 entered Taan Fiord. In 2016, we mapped the fjord with multibeam bathymetry and high‐resolution seismic data. Landslide and postlandslide deposits extend 6 km downfjord, are up to 70 ± 11 m thick, and have a total volume of ~147,000,000 m3. Seismic data image a blocky landslide unit and two units deposited immediately after the landslide. The blocky landslide unit is ~65,000,000 m3. We infer it consists dominantly of subaerially derived material and secondarily of fjord floor sediment. The overlying units are likely megaturbidites presumably deposited within minutes to days after the landslide. We infer that these deposits dominantly consist of fjord floor material mobilized and suspended as the slide entered and traveled downfjord. The lower postlandslide unit is up to 35 ± 6 m thick, and the upper unit is up to 12 ± 3 m thick. These deposits are distinctive and will leave a lasting record of the event. This subaerial‐to‐submarine landslide deposit is distinct from other submarine landslide deposits studied in Alaskan fjords because it has a much greater thickness, larger and more angular blocks, distinctive postlandslide megaturbidites, and a higher‐amplitude acoustic signature of the blocky deposit. The tight constraints on the landslide source and deposit volumes, topography, bathymetry, and tsunami runup heights and flow directions should make this a benchmark site for landslide‐tsunami models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JF004608","usgsCitation":"Haeussler, P., Gulick, S.P., McCall, N., Walton, M.A., Reece, R., Larson, C., Shugar, D.H., Geertsema, M., Venditti, J.G., and Labay, K.A., 2018, Submarine deposition of a subaerial landslide in Taan Fiord, Alaska: Journal of Geophysical Research, v. 123, no. 10, p. 2443-2463, https://doi.org/10.1029/2018JF004608.","productDescription":"21 p.","startPage":"2443","endPage":"2463","ipdsId":"IP-094084","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":460847,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jf004608","text":"Publisher Index Page"},{"id":382581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Taan Fiord","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -141.6,\n 60.25\n ],\n [\n -141.6,\n 59.75\n ],\n [\n -141,\n 59.75\n ],\n [\n -141,\n 60.25\n ],\n [\n -141.6,\n 60.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"123","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":809031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gulick, S. 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H. 0000-0002-6279-8420","orcid":"https://orcid.org/0000-0002-6279-8420","contributorId":248400,"corporation":false,"usgs":false,"family":"Shugar","given":"D.","email":"","middleInitial":"H.","affiliations":[{"id":49887,"text":"Water, Sediment, Hazards, and Earth-surface Dynamics (waterSHED) Lab, University of Washington, Tacoma, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":809037,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Geertsema, M. 0000-0002-4650-8251","orcid":"https://orcid.org/0000-0002-4650-8251","contributorId":167412,"corporation":false,"usgs":false,"family":"Geertsema","given":"M.","affiliations":[],"preferred":false,"id":809038,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Venditti, J. 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Considering the importance of hillslope hydrology for rainfall-induced landsliding, we develop and test a method for identifying hybrid hydro-meteorological thresholds to assess landslide initiation potential. We outline a series of steps for using a landslide inventory in combination with triggering rainfall and antecedent wetness to identify empirical thresholds that can inform landslide early warning systems. The method is semi-automated but remains flexible enough to allow threshold developers to consider data inputs and various performance metrics with different priorities for balancing failed versus false alarms. We demonstrate the utility of our approach for two monitoring sites near Seattle, Washington and in Portland, Oregon, USA, to develop daily bilinear thresholds within a two-dimensional parameter space, which rely on accurate 24 h forecasts, measured recent rainfall and in situ soil saturation. Although there were no prior landslide thresholds for Portland, our new hybrid threshold for the Seattle area outperforms established rainfall-only thresholds for the same region. Introducing subsurface hydrologic monitoring into landslide initiation thresholds has the potential to greatly improve early warning capabilities and help reduce losses.
","language":"English","publisher":"MDPI","doi":"10.3390/w10091274","usgsCitation":"Mirus, B.B., Morphew, M.D., and Smith, J.B., 2018, Developing hydro-meteorological thresholds for shallow landslide initiation and early warning: Water, v. 10, no. 9, p. 1-19, https://doi.org/10.3390/w10091274.","productDescription":"Article 1274; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-101411","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10091274","text":"Publisher Index Page"},{"id":357440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7367,\n 45.5217\n ],\n [\n -122.7333,\n 45.5217\n ],\n [\n -122.7333,\n 45.5233\n ],\n [\n -122.7367,\n 45.5233\n ],\n [\n -122.7367,\n 45.5217\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.34100341796875,\n 47.874907453605935\n ],\n [\n -122.31628417968749,\n 47.874907453605935\n ],\n [\n -122.31628417968749,\n 47.892866512069666\n ],\n [\n -122.34100341796875,\n 47.892866512069666\n ],\n [\n -122.34100341796875,\n 47.874907453605935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-18","publicationStatus":"PW","scienceBaseUri":"5bc02f9ce4b0fc368eb538f7","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":745347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morphew, Michael D. 0000-0003-0072-1652","orcid":"https://orcid.org/0000-0003-0072-1652","contributorId":207959,"corporation":false,"usgs":false,"family":"Morphew","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":37668,"text":"USGS, Student- Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":745348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745349,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199446,"text":"70199446 - 2018 - Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere","interactions":[],"lastModifiedDate":"2018-09-18T13:35:39","indexId":"70199446","displayToPublicDate":"2018-09-18T13:35:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere","docAbstract":"Recent local-scale observations of glaciers, streams, and soil surfaces in the McMurdo Dry Valleys of Antarctica (MDV) have documented evidence for rapid ice loss, glacial thinning, and ground surface subsidence associated with melting of ground ice. To evaluate the extent, magnitude, and location of decadal-scale landscape change in the MDV, we collected airborne lidar elevation data in 2014–2015 and compared these data to a 2001–2002 airborne lidar campaign. This regional assessment of elevation change spans the recent acceleration of warming and melting observed by long-term meteorological and ecosystem response experiments, allowing us to assess the response of MDV surfaces to warming and potential thawing feedbacks. We find that locations of thermokarst subsidence are strongly associated with the presence of excess ground ice and with proximity to surface or shallow subsurface (active layer) water. Subsidence occurs across soil types and landforms, in low-lying, low-slope areas with impeded drainage and also high on steep valley walls. Glacier thinning is widespread and is associated with the growth of fine-scale roughness. Pond levels are rising in most closed-basin lakes in the MDV, across all microclimate zones. These observations highlight the continued importance of insolation-driven melting in the MDV. The regional melt pattern is consistent with an overall transition of water storage from the local cryosphere (glaciers, permafrost) to the hydrosphere (closed basin lakes and ponds as well as the Ross Sea). We interpret this regional melting pattern to reflect a transition to Arctic and alpine-style, hydrologically mediated permafrost and glacial melt.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2018.09.012","usgsCitation":"Levy, J., Fountain, A., Obryk, M., Telling, J., Glennie, C., Pettersson, R., Gooseff, M., and van Horn, D., 2018, Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere: Geomorphology, v. 323, p. 80-97, https://doi.org/10.1016/j.geomorph.2018.09.012.","productDescription":"18 p.","startPage":"80","endPage":"97","ipdsId":"IP-098526","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2018.09.012","text":"Publisher Index Page"},{"id":357438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"McMurdo Dry Valleys, Antarctica","volume":"323","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f9ce4b0fc368eb538f9","contributors":{"authors":[{"text":"Levy, J.S.","contributorId":207960,"corporation":false,"usgs":false,"family":"Levy","given":"J.S.","email":"","affiliations":[{"id":37669,"text":"Colgate University","active":true,"usgs":false}],"preferred":false,"id":745351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fountain, A.G.","contributorId":207961,"corporation":false,"usgs":false,"family":"Fountain","given":"A.G.","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":745352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":745350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Telling, J.","contributorId":207962,"corporation":false,"usgs":false,"family":"Telling","given":"J.","email":"","affiliations":[{"id":37670,"text":"National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":745353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glennie, C.","contributorId":207963,"corporation":false,"usgs":false,"family":"Glennie","given":"C.","affiliations":[{"id":37670,"text":"National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":745354,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pettersson, R.","contributorId":207964,"corporation":false,"usgs":false,"family":"Pettersson","given":"R.","email":"","affiliations":[{"id":37671,"text":"Uppsala University","active":true,"usgs":false}],"preferred":false,"id":745355,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gooseff, M.","contributorId":201026,"corporation":false,"usgs":false,"family":"Gooseff","given":"M.","email":"","affiliations":[],"preferred":false,"id":745356,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"van Horn, D.J.","contributorId":207965,"corporation":false,"usgs":false,"family":"van Horn","given":"D.J.","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":745357,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199232,"text":"fs20183060 - 2018 - Hydrologic conditions in Kansas, water year 2017","interactions":[],"lastModifiedDate":"2018-09-18T14:06:38","indexId":"fs20183060","displayToPublicDate":"2018-09-18T08:37:23","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3060","title":"Hydrologic conditions in Kansas, water year 2017","docAbstract":"The U.S. Geological Survey, in cooperation with Federal, State, and local agencies, maintains a long-term network of hydrologic monitoring stations in Kansas. These data and associated analyses provide a unique overview of the hydrologic conditions and help improve the understanding of Kansas’ water resources. Yearly assessments of hydrologic conditions are made by comparing statistical analysis of current and past water year data for the period of record. These data provide critical information for protecting life and property, managing water supplies, forecasting floods, operating reservoirs, designing bridges and culverts, processing interstate and intrastate water rights claims, ecological monitoring, and many other uses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183060","usgsCitation":"Lukasz, B.S., 2018, Hydrologic conditions in Kansas, water year 2017: U.S. Geological Survey Fact Sheet 2018–3060, 6 p., https://doi.org/10.3133/fs20183060.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-092067","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":357374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3060/fs20183060.pdf","text":"Report","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3060"},{"id":357373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3060/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Dr.
Lawrence, KS 66049
Quantifying and understanding the natural streamflow regime, defined as expected streamflow that would occur in the absence of anthropogenic modification to the hydrologic system, is critically important for the development of management strategies aimed at protecting aquatic ecosystems. Water balance models have been applied frequently to estimate natural flows, but are limited in the number of predictor variables that can be included. Here, a statistical machine learning technique — random forest modeling — was applied to estimate natural flows at a monthly time‐step from 1950 to 2015 for >2.5 million stream reaches in the conterminous United States (U.S.) using 200 potential predictor variables. We describe the development and documentation of this dataset and assess model performance. Model fit statistics (mean Nash–Sutcliffe efficiency = 0.85; observed/expected ratio = 0.94) indicate good correspondence between predicted and observed flows at nearly 2,000 streamgages. As an example application of the dataset, the observed streamflow record at a site prior to and after the construction of an upstream reservoir was compared with estimated natural flows to demonstrate the magnitude of seasonal depletions in streamflow due to the reservoir. This dataset can be applied to quantify natural and anthropogenic processes contributing to streamflow depletion or augmentation, and assess associated ecological effects.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12685","usgsCitation":"Miller, M.P., Carlisle, D.M., Wolock, D.M., and Wieczorek, M., 2018, A database of natural monthly streamflow estimates from 1950 to 2015 for the conterminous United States: Journal of the American Water Resources Association, v. 54, no. 6, p. 1258-1269, https://doi.org/10.1111/1752-1688.12685.","productDescription":"12 p.","startPage":"1258","endPage":"1269","ipdsId":"IP-094353","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468395,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12685","text":"Publisher Index Page"},{"id":437752,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CC0ZMG","text":"USGS data release","linkHelpText":"Natural Monthly Flow Estimates for the Conterminous United States, 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Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":745159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745160,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198035,"text":"ofr20181108 - 2018 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2016","interactions":[],"lastModifiedDate":"2018-09-17T15:12:35","indexId":"ofr20181108","displayToPublicDate":"2018-09-17T08:52:41","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1108","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2016","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, plans to deepen the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel, beginning at the mouth of the river at the Atlantic Ocean, to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey installed continuous data-collection stations to monitor discharge, salinity, and associated parameters at 22 sites prior to the commencement of dredging. The U.S. Geological Survey monitored stage and discharge at 13 sites, and water temperature, specific conductance, and salinity at 15 sites; some sites included all parameters.
This report contains information pertinent to the data collection sites from their installation date to September 2016, with additional information and data from Hurricane Matthew in October 2016. Site installations began in October 2015; all sites were installed and began collecting data by January 2016. All data available for each site after October 2015 are included in this report.
Discharge and salinity ranged widely during the data collection period, which included the effects of Hurricane Hermine in September 2016 and Hurricane Matthew in October 2016. Of the tributaries, annual mean discharge was greatest at Ortega River, followed by Cedar River, Julington Creek, Durbin Creek, and Clapboard Creek. Annual mean salinity for the main-stem sites indicates that salinity decreases with distance upstream, which is expected. The closest tributary site to the Atlantic Ocean (Clapboard Creek) produced the highest annual mean salinity of the tributaries, and Durbin Creek salinity was the lowest of all monitoring locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181108","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2018, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2016: U.S. Geological Survey Open-File Report 2018–1108, 28 p., https://doi.org/10.3133/ofr20181108.","productDescription":"viii, 28 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-086635","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":357273,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1108/coverthb.jpg"},{"id":357274,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1108/ofr20181108.pdf","text":"Report","size":"7.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1108"}],"country":"United States","state":"Florida","otherGeospatial":"St. Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82,\n 29\n ],\n [\n -81,\n 29\n ],\n [\n -81,\n 30.5\n ],\n [\n -82,\n 30.5\n ],\n [\n -82,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The salt marsh harvest mouse (SMHM, Reithrodontomys raviventris) is an endangered species, endemic to the San Francisco Estuary. Despite being protected for almost half a century and being included in a large number of recovery, restoration, and management plans, significant data gaps hinder conservation and management of the species, a challenge further complicated by developing threats such as climate change. In this review, we present the current state of knowledge; highlight research gaps on habitat requirements and distribution, taxonomic status and genetic structure, physiology, reproduction and demographics, population dynamics, and behavior and community interactions; and present an overview of threats to the species. Our review indicates that substantial data gaps exist; although some aspects of SMHM ecology, such as habitat use, have been addressed extensively, others, such as the effects of environmental contamination, are largely unaddressed. We suggest that conservation and restoration-planning processes consider experimental approaches within restoration designs to address these deficiencies. Continued investment in basic and applied SMHM ecology to collect baseline and long-term data will also be beneficial. Additionally, further coordination among managers and researchers can facilitate more effective responses to uncertainties and emerging threats, especially climate change, which threatens the SMHM and its habitat throughout its range.
","language":"English","publisher":"University of California","doi":"10.15447/sfews.2018v16iss2art2","usgsCitation":"Smith, K.R., Riley, M.K., Barthman-Thompson, L., Woo, I., Statham, M.J., Estrella, S., and Kelt, D.A., 2018, Toward salt marsh harvest mouse recovery: A review: San Francisco Estuary and Watershed Science, v. 16, no. 2, Article 2; 24 p., https://doi.org/10.15447/sfews.2018v16iss2art2.","productDescription":"Article 2; 24 p.","ipdsId":"IP-097923","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468402,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2018v16iss2art2","text":"Publisher Index Page"},{"id":357297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-28","publicationStatus":"PW","scienceBaseUri":"5bc02f9fe4b0fc368eb5391b","contributors":{"authors":[{"text":"Smith, Katherine R.","contributorId":207840,"corporation":false,"usgs":false,"family":"Smith","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":744863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riley, Melissa K.","contributorId":207841,"corporation":false,"usgs":false,"family":"Riley","given":"Melissa","email":"","middleInitial":"K.","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":744864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barthman-Thompson, Laureen","contributorId":207842,"corporation":false,"usgs":false,"family":"Barthman-Thompson","given":"Laureen","email":"","affiliations":[{"id":6952,"text":"California Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":744865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":744862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Statham, Mark J.","contributorId":207843,"corporation":false,"usgs":false,"family":"Statham","given":"Mark","email":"","middleInitial":"J.","affiliations":[{"id":37642,"text":"University of California,Davis","active":true,"usgs":false}],"preferred":false,"id":744866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Estrella, Sarah","contributorId":207844,"corporation":false,"usgs":false,"family":"Estrella","given":"Sarah","email":"","affiliations":[{"id":12939,"text":"California Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":744867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelt, Douglas A.","contributorId":207845,"corporation":false,"usgs":false,"family":"Kelt","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":744868,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}