{"pageNumber":"546","pageRowStart":"13625","pageSize":"25","recordCount":40783,"records":[{"id":70191815,"text":"70191815 - 2015 - Life-stage-specific physiology defines invasion extent of a riverine fish","interactions":[],"lastModifiedDate":"2017-10-18T10:54:22","indexId":"70191815","displayToPublicDate":"2015-05-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Life-stage-specific physiology defines invasion extent of a riverine fish","docAbstract":"
  1. Many ecologists have called for mechanism-based investigations to identify the underlying controls on species distributions. Understanding these controls can be especially useful to construct robust predictions of how a species range may change in response to climate change or the extent to which a non-native species may spread in novel environments.
  2. Here, we link spatially intensive observations with mechanistic models to illustrate how physiology determines the upstream extent of the aquatic ectotherm smallmouth bass (Micropterus dolomieu) in two headwater rivers.
  3. Our results demonstrate that as temperatures become increasingly cold across a downstream to upstream gradient, food consumption in age 0 bass becomes increasingly constrained, and as a result, these fish become growth limited. Sufficient first summer growth of age 0 bass is essential for overwinter survival because young bass must persist from energy reserves accumulated during the summer, and those reserves are determined by body size.
  4. Our field data reveal the upstream extent of adult bass reproduction corresponds to a point in the downstream/upstream gradient where cold temperatures impair growth opportunities in young bass. This pattern was repeated in both study streams and explained why bass positioned nests twice as far upstream in the warm compared to the cold stream in the same basin. Placement of spawning nests by adult bass is likely subject to strong evolutionary selection in temperate systems: if bass spawn too far upstream, their young are unlikely to grow large enough to survive the winter. Consumption and growth in older bass (age 3–4) was far less sensitive to temperature. Based on these data, we suggest that temperature-sensitive age 0 bass constrain the upstream distribution limits of bass within temperate streams.
  5. In this study, we investigated how temperature-dependent physiology changed through the life history of a species and, in doing so, identified a climate-sensitive life-history stage that likely sets the distributional limits of all other life-history stages. We anticipate the framework developed here could be employed to identify how similar stage-specific environmental sensitivity determines distribution in many other ectothermic species.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2656.12332","usgsCitation":"Lawrence, D.J., Beauchamp, D.A., and Olden, J., 2015, Life-stage-specific physiology defines invasion extent of a riverine fish: Journal of Animal Ecology, v. 84, no. 3, p. 879-888, https://doi.org/10.1111/1365-2656.12332.","productDescription":"9 p.","startPage":"879","endPage":"888","ipdsId":"IP-058065","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472116,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12332","text":"Publisher Index Page"},{"id":346834,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"North Fork John Day River, Middle Fork John Day River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.3,\n 44.67\n ],\n [\n -118.5,\n 44.67\n ],\n [\n -118.5,\n 45.1\n ],\n [\n -119.3,\n 45.1\n ],\n [\n -119.3,\n 44.67\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-06","publicationStatus":"PW","scienceBaseUri":"59e8683ce4b05fe04cd4d238","contributors":{"authors":[{"text":"Lawrence, David J.","contributorId":34374,"corporation":false,"usgs":true,"family":"Lawrence","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":713268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":713220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olden, Julian D.","contributorId":66951,"corporation":false,"usgs":true,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":713269,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191691,"text":"70191691 - 2015 - Consequences of actively managing a small Bull Trout population in a fragmented landscape","interactions":[],"lastModifiedDate":"2017-10-24T13:03:28","indexId":"70191691","displayToPublicDate":"2015-05-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of actively managing a small Bull Trout population in a fragmented landscape","docAbstract":"

Habitat fragmentation, which affects many native salmonid species, is one of the major factors contributing to the declines in distribution and abundance of Bull Trout Salvelinus confluentus. Increasingly, managers are considering options to maintain and enhance the persistence of isolated local populations through active management strategies. Understanding the ecological consequences of such actions is a necessary step in conservation planning. We used an individual-based model to evaluate the consequences of an ongoing management program aimed at mitigating the anthropogenic fragmentation of the lower Clark Fork River in Montana. Under this program juvenile Bull Trout are trapped and transported from small, headwater source populations to Lake Pend Oreille, Idaho, for rearing, and adults are subsequently recaptured in their upstream migration and returned to the natal population for spawning. We examined one of these populations and integrated empirical estimates of demographic parameters to simulate different management scenarios where moderate (n = 4) and high (n = 8) numbers of age-2, age-3, or age-4 Bull Trout were removed for transport with variable return rates under both demographic stochasticity and environmental perturbations. Our results indicated the risks from removal with no returns increased substantially when removal totals and age of Bull Trout removed from the simulated population increased. Specifically, removing eight age-3 or age-4 individuals resulted in 26% and 62% reductions in average adult population size, respectively, across simulations. We found the risks of transport were not likely alleviated with low (3%) or moderate (6%) return rates, and there were considerable risks of declines for the source population even when return rates were extremely high (>12%). Our simulations indicated little risk of declines for the source population with removals of age-2 Bull Trout, and any risks were alleviated with low return rates. However, we found higher return rates were particularly beneficial in the presence of large, density-independent perturbations.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2015.1007162","usgsCitation":"Al-Chokhachy, R.K., Moran, S., McHugh, P., Bernall, S., Fredenberg, W., and DosSantos, J.M., 2015, Consequences of actively managing a small Bull Trout population in a fragmented landscape: Transactions of the American Fisheries Society, v. 144, no. 3, p. 515-531, https://doi.org/10.1080/00028487.2015.1007162.","productDescription":"17 p.","startPage":"515","endPage":"531","ipdsId":"IP-062899","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":347234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork River, Cooper Gulch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.73248291015624,\n 47.344406158662125\n ],\n [\n -115.01861572265624,\n 47.344406158662125\n ],\n [\n -115.01861572265624,\n 48.367198426439465\n ],\n [\n -116.73248291015624,\n 48.367198426439465\n ],\n [\n -116.73248291015624,\n 47.344406158662125\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-22","publicationStatus":"PW","scienceBaseUri":"59f05124e4b0220bbd9a1db1","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":713074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Sean","contributorId":197260,"corporation":false,"usgs":false,"family":"Moran","given":"Sean","email":"","affiliations":[],"preferred":false,"id":713075,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHugh, Peter","contributorId":12313,"corporation":false,"usgs":true,"family":"McHugh","given":"Peter","affiliations":[],"preferred":false,"id":715152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernall, Shana","contributorId":197261,"corporation":false,"usgs":false,"family":"Bernall","given":"Shana","email":"","affiliations":[],"preferred":false,"id":713076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredenberg, Wade","contributorId":197262,"corporation":false,"usgs":false,"family":"Fredenberg","given":"Wade","affiliations":[],"preferred":false,"id":713077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DosSantos, Joseph M.","contributorId":197263,"corporation":false,"usgs":false,"family":"DosSantos","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":713078,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190555,"text":"70190555 - 2015 - Intertidal biological indicators of coseismic subsidence during the Mw 7.8 Haida Gwaii, Canada, earthquake","interactions":[],"lastModifiedDate":"2017-09-07T12:05:54","indexId":"70190555","displayToPublicDate":"2015-05-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Intertidal biological indicators of coseismic subsidence during the Mw 7.8 Haida Gwaii, Canada, earthquake","title":"Intertidal biological indicators of coseismic subsidence during the Mw 7.8 Haida Gwaii, Canada, earthquake","docAbstract":"

The 28 October 2012 Mw 7.8 Haida Gwaii earthquake was a megathrust earthquake along the very obliquely convergent Queen Charlotte margin of British Columbia, Canada. Coseismic deformation is not well constrained by geodesy, with only six Global Positioning System (GPS) sites and two tide gauge stations within 250 km of the rupture area. To better constrain vertical coseismic deformation, we measured the upper growth limits of two sessile intertidal organisms, which are controlled by physical conditions, relative to sea level at 25 sites 5 months after the earthquake. We measured the positions of rockweed (Fucus distichus, 617 observations) and the common acorn barnacle (Balanus balanoides, 686 observations). The study focused on the western side of the islands where rupture models indicated that the greatest amount of vertical displacement, but we also investigated sites well away from the inferred rupture area to provide a control on the upper limit of the organisms unaffected by vertical displacement. We also made 322 measurements of sea level to relate the growth limits to a tidal datum using the TPXO7.2 tidal model, rather than ellipsoid heights determined by GPS. Three methods of examining the data all indicate 0.4–0.6 m subsidence along the western coast of Moresby Island as a result of the 28 October 2012 Haida Gwaii earthquake. Our data are, within the errors, consistent with data from two campaign GPS sites along the west coast of Haida Gwaii and with rupture models that indicate megathrust rupture offshore, but not beneath, the islands.

","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120140197","usgsCitation":"Haeussler, P.J., Witter, R., and Wang, K., 2015, Intertidal biological indicators of coseismic subsidence during the Mw 7.8 Haida Gwaii, Canada, earthquake: Bulletin of the Seismological Society of America, v. 105, no. 2B, p. 1265-1279, https://doi.org/10.1785/0120140197.","productDescription":"15 p.","startPage":"1265","endPage":"1279","ipdsId":"IP-061096","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":345541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","volume":"105","issue":"2B","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-14","publicationStatus":"PW","scienceBaseUri":"59b25b01e4b020cdf7db1fc4","contributors":{"authors":[{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":709779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":709780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Kelin","contributorId":194791,"corporation":false,"usgs":false,"family":"Wang","given":"Kelin","email":"","affiliations":[],"preferred":false,"id":709781,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70143907,"text":"fs20153029 - 2015 - The 3D Elevation Program: summary for South Carolina","interactions":[],"lastModifiedDate":"2016-08-17T15:01:20","indexId":"fs20153029","displayToPublicDate":"2015-04-30T16:45:00","publicationYear":"2015","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":"2015-3029","title":"The 3D Elevation Program: summary for South Carolina","docAbstract":"

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of South Carolina, elevation data are critical for flood risk management, natural resources conservation, agriculture and precision farming, infrastructure and construction management, forest resources management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.

\n

The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153029","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for South Carolina: U.S. Geological Survey Fact Sheet 2015-3029, 2 p., https://doi.org/10.3133/fs20153029.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059996","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":300004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153029.jpg"},{"id":300002,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3029/"},{"id":300003,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3029/pdf/fs2015-3029.pdf","text":"Report","size":"811 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"South 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implicit one-line model to predict long-term shoreline change","docAbstract":"We present the formulation, validation, and application of a nonlinear, implicit one-line model to simulate long-term (decadal and longer) shoreline change. The purpose of the implicit numerical method presented here is to allow large time steps without sacrificing model stability compared to explicit approaches, and thereby improve computational efficiency. The model uses a Jacobian-free Newton-Krylov solver to compute the solution to the governing equations, i.e. the shoreline position. The model is validated against an analytical solution for alongshore shoreline diffusion. The model is applied to simulate a decade of observed shoreline change at Ocean Beach (2004-2014). When wave transformation is included (implemented via SWAN and a look-up table) there is a 100% increase in the number of profiles where erosion or accretion is correctly predicted.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The proceedings of the coastal sediments 2015","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2015","conferenceDate":"May 11-15, 2015","conferenceLocation":"San Diego, CA","language":"English","publisher":"World Scientific","doi":"10.1142/9789814689977_0215","usgsCitation":"Vitousek, S., and Barnard, P., 2015, A nonlinear, implicit one-line model to predict long-term shoreline change, in The proceedings of the coastal sediments 2015, San Diego, CA, May 11-15, 2015, 12 p., https://doi.org/10.1142/9789814689977_0215.","productDescription":"12 p.","ipdsId":"IP-064826","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":382177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":576798,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70147340,"text":"70147340 - 2015 - Precise interpolar phasing of abrupt climate change during the last ice age","interactions":[],"lastModifiedDate":"2015-05-11T13:00:59","indexId":"70147340","displayToPublicDate":"2015-04-30T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Precise interpolar phasing of abrupt climate change during the last ice age","docAbstract":"

The last glacial period exhibited abrupt Dansgaard–Oeschger climatic oscillations, evidence of which is preserved in a variety of Northern Hemisphere palaeoclimate archives1. Ice cores show that Antarctica cooled during the warm phases of the Greenland Dansgaard–Oeschger cycle and vice versa2, 3, suggesting an interhemispheric redistribution of heat through a mechanism called the bipolar seesaw4, 5, 6. Variations in the Atlantic meridional overturning circulation (AMOC) strength are thought to have been important, but much uncertainty remains regarding the dynamics and trigger of these abrupt events7, 8, 9. Key information is contained in the relative phasing of hemispheric climate variations, yet the large, poorly constrained difference between gas age and ice age and the relatively low resolution of methane records from Antarctic ice cores have so far precluded methane-based synchronization at the required sub-centennial precision2, 3,10. Here we use a recently drilled high-accumulation Antarctic ice core to show that, on average, abrupt Greenland warming leads the corresponding Antarctic cooling onset by 218 ± 92 years (2σ) for Dansgaard–Oeschger events, including the Bølling event; Greenland cooling leads the corresponding onset of Antarctic warming by 208 ± 96 years. Our results demonstrate a north-to-south directionality of the abrupt climatic signal, which is propagated to the Southern Hemisphere high latitudes by oceanic rather than atmospheric processes. The similar interpolar phasing of warming and cooling transitions suggests that the transfer time of the climatic signal is independent of the AMOC background state. Our findings confirm a central role for ocean circulation in the bipolar seesaw and provide clear criteria for assessing hypotheses and model simulations of Dansgaard–Oeschger dynamics.

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The State of New Hampshire has initiated a coordinated effort to proactively prepare for the effects of climate change on the natural and human resources of New Hampshire. An important aspect of this effort is to develop a vulnerability assessment of hydrologic response to climate change. The U.S. Geological Survey, in cooperation with the New Hampshire Department of Health and Human Services, is developing tools to predict how projected changes in temperature and precipitation will affect change in the hydrology of watersheds in the State. This study is a test case to assemble the information and create the tools to assess the hydrologic vulnerabilities in four specific watersheds.

\n

The study uses output from general circulation models to drive hydrologic simulations of streamflow, groundwater base flow (hereafter referred to as base flow), and snowfall in four representative watersheds in New Hampshire during the 21st century, including the watersheds of the Ashuelot, Oyster, Pemigewasset, and Souhegan Rivers. Simulations show that on average, relative to current conditions, streamflow is likely to increase and base flow is likely to decrease, although this change is highly variable by geographic location and season. Streamflow variability will likely increase, with more high streamflows and more low streamflows. The largest increases in streamflow are in the winter, with small decreases in summer. Change in base flow varies across the State with the largest change in the northern Pemigewasset River watershed. Changes in snowfall are consistently decreasing for all watersheds on average, with the largest change also in the Pemigewasset. However, monthly snowfall totals during any given winter could be higher in the future than expected under current conditions.

\n

Increasing frequency of floods (the largest seven floods expected to occur in 20 years) could be more significant than the size of the floods, except in the northern high altitude watersheds. In other words, the projections indicate a pattern of multiple floods that might not breach the riverbanks, yet the increased frequency could put additional strain on the existing river banks, infrastructure, and nearby human settlements. There is also likely to be an increase in high flows during the winter and spring months, which could result in more uncertainty in planning for the design, operation, and maintenance of infrastructure, including roads and utilities. Similarly, it is expected that, on average, there will be less base flow available and a wider range of seasonal fluctuation in base flow than experienced historically. These issues could necessitate more attention to planning and management of the resource. Based on past experience, the most important effects of climate change could be less certain planning options and a greater need for planning that accounts for the effects of larger streamflows than are currently available.

\n

The effects of hydrologic change on human health and well-being could be most readily apparent with respect to changes in streamflow and the subsequent increase in the frequency of minor flooding and the frequency of summer and fall low streamflows. These changes could require the development of plans to adapt, protect, and upgrade infrastructure, such as bridges, culverts, roads, and other structures. The precipitation runoff modeling shows that rivers and watersheds in New Hampshire will likely change in response to climate change, and that this response varies with season and latitude. Although four representative areas were simulated in this study, additional models could be used to predict the response over the entire State.

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Identification of ecological factors that drive animal distributions allows us to understand why distributions vary temporally and spatially, and to develop models to predict future changes to populations–vital tools for effective wildlife management and conservation. For waterbird broods in the boreal forest, distributions are likely driven by factors affecting quality of nesting and brood-rearing habitats, and the influence of these factors may extend beyond singles species, affecting the entire waterbird community. We used occupancy models to assess factors influencing species richness of waterbird broods on 72 boreal lakes, along with brood distributions of 3 species of conservation concern: lesser scaup (Aythya affinis), white-winged scoters (Melanitta fusca), and horned grebe (Podiceps auritus). Factors examined included abundance of invertebrate foods (Amphipoda, Diptera, Gastropoda, Hemiptera, Odonata), physical lake attributes (lake area, emergent vegetation), water chemistry (nitrogen, phosphorus, chlorophyll a concentrations), and nesting habitats (water edge, non-forest cover). Of the 5 invertebrates, only amphipod density was related to richness and occupancy, consistently having a large and positive relationship. Despite this importance to waterbirds, amphipods were the most patchily distributed invertebrate, with 17% of the study lakes containing 70% of collected amphipods. Lake area was the only other covariate that strongly and positively influenced species richness and occupancy of scaup, scoters, and grebes. All 3 water chemistry covariates, which provided alternative measures of lake productivity, were positively related to species richness but had little effect on scaup, scoter, and grebe occupancy. Conversely, emergent vegetation was negatively related to richness, reflecting avoidance of overgrown lakes by broods. Finally, nesting habitats had no influence on richness and occupancy, indicating that, at a broad spatial scale, brood distributions are largely driven by the presence of quality brood-rearing lakes, not nesting habitats. Our findings are relevant to generating conservation plans or management goals; specifically, boreal lakes with abundant amphipods and surface areas >25 ha are important habitat for waterbird broods and merit conservation, especially given the patchy distribution of amphipods. Moreover, these high quality brood-rearing lakes are much rarer, and thus more constraining, than are quality nesting habitats, which are likely abundant in the boreal.

","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.837","usgsCitation":"Lewis, T., Lindberg, M., Schmutz, J.A., Bertram, M.R., and Dubour, A.J., 2015, Species richness and distributions of boreal waterbirds in relation to nesting and brood-rearing habitats: Journal of Wildlife Management, v. 79, no. 2, p. 296-310, https://doi.org/10.1002/jwmg.837.","productDescription":"15 p.","startPage":"296","endPage":"310","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053141","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":299954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.4747314453125,\n 65.96661446478602\n ],\n [\n -146.326904296875,\n 66.3132419108725\n ],\n [\n -144.64599609375,\n 65.96437717203096\n ],\n [\n -143.843994140625,\n 66.45408107252952\n ],\n [\n -145.843505859375,\n 66.77458576472547\n ],\n [\n -148.721923828125,\n 66.46943736242146\n ],\n [\n -148.4747314453125,\n 65.96661446478602\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-13","publicationStatus":"PW","scienceBaseUri":"5541f2d1e4b0a658d793b243","chorus":{"doi":"10.1002/jwmg.837","url":"http://dx.doi.org/10.1002/jwmg.837","publisher":"Wiley-Blackwell","authors":"Lewis Tyler L., Lindberg Mark S., Schmutz Joel A., Bertram Mark R., Dubour Adam J.","journalName":"The Journal of Wildlife Management","publicationDate":"2/2015","auditedOn":"2/8/2015"},"contributors":{"authors":[{"text":"Lewis, Tyler L.","contributorId":22904,"corporation":false,"usgs":false,"family":"Lewis","given":"Tyler L.","affiliations":[{"id":12437,"text":"Simon Fraser University, Centre for Wildlife Ecology","active":true,"usgs":false}],"preferred":false,"id":545752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindberg, Mark S.","contributorId":89466,"corporation":false,"usgs":false,"family":"Lindberg","given":"Mark S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":545753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":545742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bertram, Mark R.","contributorId":140463,"corporation":false,"usgs":false,"family":"Bertram","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":545754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubour, Adam J.","contributorId":140464,"corporation":false,"usgs":false,"family":"Dubour","given":"Adam","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":545755,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147246,"text":"70147246 - 2015 - Projected changes in wildlife habitats in Arctic natural areas of northwest Alaska","interactions":[],"lastModifiedDate":"2015-04-29T10:49:20","indexId":"70147246","displayToPublicDate":"2015-04-29T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1252,"text":"Climatic Change","active":true,"publicationSubtype":{"id":10}},"title":"Projected changes in wildlife habitats in Arctic natural areas of northwest Alaska","docAbstract":"

We project the effects of transitional changes among 60 vegetation and other land cover types (“ecotypes”) in northwest Alaska over the 21st century on habitats of 162 bird and 39 mammal species known or expected to occur regularly in the region. This analysis, encompassing a broad suite of arctic and boreal wildlife species, entailed building wildlife-habitat matrices denoting levels of use of each ecotype by each species, and projecting habitat changes under historic and expected accelerated future rates of change from increasing mean annual air temperature based on the average of 5 global climate models under the A1B emissions scenario, and from potential influence of a set of 23 biophysical drivers. Under historic rates of change, we project that 52 % of the 201 species will experience an increase in medium- and high-use habitats, 3 % no change, and 45 % a decrease, and that a greater proportion of mammal species (62 %) will experience habitat declines than will bird species (50 %). Outcomes become more dire (more species showing habitat loss) under projections made from effects of biophysical drivers and especially from increasing temperature, although species generally associated with increasing shrub and tree ecotypes will likely increase in distribution. Changes in wildlife habitats likely will also affect trophic cascades, ecosystem function, and ecosystem services; of particular significance are the projected declines in habitats of most small mammals that form the prey base for mesocarnivores and raptors, and habitat declines in 25 of the 50 bird and mammal species used for subsistence hunting and trapping.

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Monthly water yields from 105,829 catchments and corresponding flows in 107,691 stream segments were estimated for water years 1951–2012 in the Great Lakes Basin in the United States. Both sets of estimates were computed by using the Analysis of Flows In Networks of CHannels (AFINCH) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. For this study, the U.S. Great Lakes Basin was partitioned into seven study areas by grouping selected hydrologic subregions and adjoining cataloguing units. This report documents the regression models and data used to estimate monthly water yields and flows in each study area. Estimates of monthly water yields and flows are presented in a Web-based mapper application. Monthly flow time series for individual stream segments can be retrieved from the Web application and used to approximate monthly flow-duration characteristics and to identify possible trends.

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]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5540a120e4b0a658d7939273","contributors":{"authors":[{"text":"Luukkonen, Carol L. clluukko@usgs.gov","contributorId":3489,"corporation":false,"usgs":true,"family":"Luukkonen","given":"Carol","email":"clluukko@usgs.gov","middleInitial":"L.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtschlag, David J. 0000-0001-5185-4928 dholtschlag@usgs.gov","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":5447,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","email":"dholtschlag@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoard, Christopher J. 0000-0003-2337-506X cjhoard@usgs.gov","orcid":"https://orcid.org/0000-0003-2337-506X","contributorId":191767,"corporation":false,"usgs":true,"family":"Hoard","given":"Christopher","email":"cjhoard@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Lori M. lmfuller@usgs.gov","contributorId":2100,"corporation":false,"usgs":true,"family":"Fuller","given":"Lori","email":"lmfuller@usgs.gov","middleInitial":"M.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545697,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173411,"text":"70173411 - 2015 - Brown Trout removal effects on short-term survival and movement of Myxobolus cerebralis-resistant rainbow trout","interactions":[],"lastModifiedDate":"2016-06-16T16:35:55","indexId":"70173411","displayToPublicDate":"2015-04-28T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Brown Trout removal effects on short-term survival and movement of Myxobolus cerebralis-resistant rainbow trout","docAbstract":"

Following establishment of Myxobolus cerebralis (the parasite responsible for salmonid whirling disease) in Colorado, populations of Rainbow Trout Oncorhynchus mykissexperienced significant declines, whereas Brown Trout Salmo trutta densities increased in many locations across the state, potentially influencing the success of M. cerebralis-resistant Rainbow Trout reintroductions. We examined the effects of Brown Trout removal on the short-term (3-month) survival and movement of two crosses of reintroduced, M. cerebralis-resistant Rainbow Trout in the Cache la Poudre River, Colorado. Radio frequency identification passive integrated transponder tags and antennas were used to track movements of wild Brown Trout and stocked Rainbow Trout in reaches where Brown Trout had or had not been removed. Multistate mark–recapture models were used to estimate tagged fish apparent survival and movement in these sections 3 months following Brown Trout removal. A cross between the German Rainbow Trout and Colorado River Rainbow Trout strains exhibited similar survival and movement probabilities in the reaches, suggesting that the presence of Brown Trout did not affect its survival or movement. However, a cross between the German Rainbow Trout and Harrison Lake Rainbow Trout exhibited less movement from the reach in which Brown Trout had been removed. Despite this, the overall short-term benefits of the removal were equivocal, suggesting that Brown Trout removal may not be beneficial for the reintroduction of Rainbow Trout. Additionally, the logistical constraints of conducting removals in large river systems are substantial and may not be a viable management option in many rivers.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2015.1007166","usgsCitation":"Fetherman, E.R., Winkelman, D.L., Bailey, L., Schisler, G.J., and Davies, K., 2015, Brown Trout removal effects on short-term survival and movement of Myxobolus cerebralis-resistant rainbow trout: Transactions of the American Fisheries Society, v. 144, no. 3, p. 610-626, https://doi.org/10.1080/00028487.2015.1007166.","productDescription":"17 p.","startPage":"610","endPage":"626","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060281","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":323830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Cache la Poudre River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.73293685913086,\n 40.472154983547576\n ],\n [\n -105.7437515258789,\n 40.4713714599763\n ],\n [\n -105.75542449951172,\n 40.46810668002513\n ],\n [\n -105.765380859375,\n 40.456613392013615\n ],\n [\n -105.78752517700195,\n 40.444726219263586\n ],\n [\n -105.80160140991211,\n 40.43453554052651\n ],\n [\n -105.80743789672852,\n 40.42486603279224\n ],\n [\n -105.8056354522705,\n 40.424277977344246\n ],\n [\n -105.79876899719238,\n 40.430746304509185\n ],\n [\n -105.78349113464355,\n 40.44152546734412\n ],\n [\n -105.75525283813477,\n 40.4611195176856\n ],\n [\n -105.74435234069824,\n 40.46797608552582\n ],\n [\n -105.73473930358887,\n 40.46889024168825\n ],\n [\n -105.73233604431151,\n 40.4713714599763\n ],\n [\n -105.73293685913086,\n 40.472154983547576\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-28","publicationStatus":"PW","scienceBaseUri":"5763cdb0e4b07657d19ba756","contributors":{"authors":[{"text":"Fetherman, Eric R.","contributorId":15096,"corporation":false,"usgs":true,"family":"Fetherman","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":639463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637095,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bailey, Larissa L.","contributorId":93183,"corporation":false,"usgs":true,"family":"Bailey","given":"Larissa L.","affiliations":[],"preferred":false,"id":639464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schisler, George J.","contributorId":32432,"corporation":false,"usgs":true,"family":"Schisler","given":"George","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":639465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, K.","contributorId":172056,"corporation":false,"usgs":false,"family":"Davies","given":"K.","email":"","affiliations":[],"preferred":false,"id":639466,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70146893,"text":"70146893 - 2015 - Rapidly expanding range of highly pathogenic avian influenza viruses","interactions":[],"lastModifiedDate":"2016-01-26T15:37:45","indexId":"70146893","displayToPublicDate":"2015-04-23T14:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1493,"text":"Emerging Infectious Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Rapidly expanding range of highly pathogenic avian influenza viruses","docAbstract":"

The movement of highly pathogenic avian influenza (H5N8) virus across Eurasia and into North America and the virus’ propensity to reassort with co-circulating low pathogenicity viruses raise concerns among poultry producers, wildlife biologists, aviculturists, and public health personnel worldwide. Surveillance, modeling, and experimental research will provide the knowledge required for intelligent policy and management decisions.

","language":"English","publisher":"Centers for Disease Control and Prevention","doi":"10.3201/eid2107.150403","usgsCitation":"Hall, J.S., Dusek, R., and Spackman, E., 2015, Rapidly expanding range of highly pathogenic avian influenza viruses: Emerging Infectious Diseases, v. 21, no. 7, p. 1251-1252, https://doi.org/10.3201/eid2107.150403.","productDescription":"2 p.","startPage":"1251","endPage":"1252","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064628","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":472133,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3201/eid2107.150403","text":"Publisher Index Page"},{"id":299850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"7","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553a09cce4b0c1efddaed141","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":545494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":140066,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert J.","email":"rdusek@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spackman, Erica","contributorId":82126,"corporation":false,"usgs":false,"family":"Spackman","given":"Erica","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":545496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70146868,"text":"70146868 - 2015 - Isolation and characterization of microsatellite DNA loci in the threatened flat-spired three-toothed land snail Triodopsis platysayoides","interactions":[],"lastModifiedDate":"2015-08-17T15:08:51","indexId":"70146868","displayToPublicDate":"2015-04-23T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"title":"Isolation and characterization of microsatellite DNA loci in the threatened flat-spired three-toothed land snail Triodopsis platysayoides","docAbstract":"

The hermaphroditic flat-spired three-tooth land snail (Triodopsis platysayoides) is endemic to a 21-km stretch of the Cheat River Gorge of northeastern West Virginia, USA. We document isolation and characterization of ten microsatellite DNA markers in this at-risk species. The markers displayed a moderate level of allelic diversity (averaging 7.1 alleles/locus) and heterozygosity (averaging 58.6 %). Allelic diversity at seven loci was sufficient to produce unique multilocus genotypes; no indication of selfing was detected in this cosexual species. Minimal deviations from Hardy–Weinberg equilibrium and no linkage disequilibrium were observed within subpopulations. All loci deviated from Hardy–Weinberg expectations when individuals from subpopulations were pooled. Microsatellite markers developed for T. platysayoides yielded sufficient genetic diversity to (1) distinguish all individuals sampled and the level of selfing; (2) be appropriate for addressing fine-scale population structuring; (3) provide novel demographic insights for the species; and (4) cross-amplify and detect allelic diversity in the congeneric T. juxtidens.

","language":"English","publisher":"Springer","doi":"10.1007/s12686-015-0456-0","usgsCitation":"King, T.L., Eackles, M.S., Garner, B.A., van Tuinen, M., and Arbogast, B.S., 2015, Isolation and characterization of microsatellite DNA loci in the threatened flat-spired three-toothed land snail Triodopsis platysayoides: Conservation Genetics Resources, v. 7, no. 3, p. 767-769, https://doi.org/10.1007/s12686-015-0456-0.","productDescription":"3 p.","startPage":"767","endPage":"769","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063973","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":299846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-08","publicationStatus":"PW","scienceBaseUri":"553a09c2e4b0c1efddaed13b","contributors":{"authors":[{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":545389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eackles, Michael S. meackles@usgs.gov","contributorId":4371,"corporation":false,"usgs":true,"family":"Eackles","given":"Michael","email":"meackles@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":545483,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garner, B. A.","contributorId":140387,"corporation":false,"usgs":false,"family":"Garner","given":"B.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":545484,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Tuinen, M.","contributorId":140388,"corporation":false,"usgs":false,"family":"van Tuinen","given":"M.","email":"","affiliations":[],"preferred":false,"id":545485,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arbogast, B. S.","contributorId":140389,"corporation":false,"usgs":false,"family":"Arbogast","given":"B.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":545486,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70146810,"text":"70146810 - 2015 - Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska","interactions":[],"lastModifiedDate":"2017-01-18T10:03:03","indexId":"70146810","displayToPublicDate":"2015-04-23T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska","docAbstract":"

Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2015.1004764","usgsCitation":"Ji, L., Wylie, B.K., Brown, D.R., Peterson, B.E., Alexander, H.D., Mack, M., Rover, J.R., Waldrop, M.P., McFarland, J.W., Chen, X., and Pastick, N.J., 2015, Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska: International Journal of Remote Sensing, v. 36, no. 4, p. 939-953, https://doi.org/10.1080/01431161.2015.1004764.","productDescription":"15 p.","startPage":"939","endPage":"953","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045071","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":299844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -164.53125,\n 60.973107109199404\n ],\n [\n -158.466796875,\n 61.60639637138628\n ],\n [\n -155.0390625,\n 63.11463763252091\n ],\n [\n -152.490234375,\n 63.704722429433225\n ],\n [\n -150.99609375,\n 63.54855223203644\n ],\n [\n -151.435546875,\n 62.99515845212052\n ],\n [\n -150.556640625,\n 62.2679226294176\n ],\n [\n -147.744140625,\n 62.63376960786813\n ],\n [\n -144.580078125,\n 62.3903694381427\n ],\n [\n -141.064453125,\n 61.22795717667785\n ],\n [\n -141.15234374999997,\n 69.06856318696033\n ],\n [\n -145.37109375,\n 69.47296854140573\n ],\n [\n -156.357421875,\n 69.2249968541159\n ],\n [\n -157.763671875,\n 69.38031271734351\n ],\n [\n -157.763671875,\n 68.8159271333607\n ],\n [\n -159.873046875,\n 66.89559561140706\n ],\n [\n -160.6640625,\n 63.93737246791484\n ],\n [\n -164.61914062499997,\n 63.23362741232569\n ],\n [\n -166.2890625,\n 61.77312286453148\n ],\n [\n -164.53125,\n 60.973107109199404\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-17","publicationStatus":"PW","scienceBaseUri":"553a09d0e4b0c1efddaed145","contributors":{"authors":[{"text":"Ji, Lei 0000-0002-6133-1036 lji@usgs.gov","orcid":"https://orcid.org/0000-0002-6133-1036","contributorId":139587,"corporation":false,"usgs":true,"family":"Ji","given":"Lei","email":"lji@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":545380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":545383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Dana R. N.","contributorId":140386,"corporation":false,"usgs":false,"family":"Brown","given":"Dana","email":"","middleInitial":"R. 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In this paper, we report on the adaptation and application of a one-dimensional marsh surface elevation model, the Wetland Accretion Rate Model of Ecosystem Resilience (WARMER), to explore the conditions that lead to sustainable tidal freshwater marshes in the Sacramento–San Joaquin Delta. We defined marsh accretion parameters to encapsulate the range of observed values over historic and modern time-scales based on measurements from four marshes in high and low energy fluvial environments as well as possible future trends in sediment supply and mean sea level. A sensitivity analysis of 450 simulations was conducted encompassing a range of eScholarship provides open access, scholarly publishing services to the University of California and delivers a dynamic research platform to scholars worldwide. porosity values, initial elevations, organic and inorganic matter accumulation rates, and sea-level rise rates. For the range of inputs considered, the magnitude of SLR over the next century was the primary driver of marsh surface elevation change. Sediment supply was the secondary control. More than 84% of the scenarios resulted in sustainable marshes with 88 cm of SLR by 2100, but only 32% and 11% of the scenarios resulted in surviving marshes when SLR was increased to 133 cm and 179 cm, respectively. Marshes situated in high-energy zones were marginally more resilient than those in low-energy zones because of their higher inorganic sediment supply. Overall, the results from this modeling exercise suggest that marshes at the upstream reaches of the Delta—where SLR may be attenuated—and high energy marshes along major channels with high inorganic sediment accumulation rates will be more resilient to global SLR in excess of 88 cm over the next century than their downstream and low-energy counterparts. However, considerable uncertainties exist in the projected rates of sea-level rise and sediment avail-ability. In addition, more research is needed to constrain future rates of aboveground and belowground plant productivity under increased CO<sub>2</sub> concentrations and flooding.

","language":"English","publisher":"John Muir Institute of the Environment","publisherLocation":"Sacramento, CA","doi":"10.15447/sfews.2015v13iss1art3","usgsCitation":"Swanson, K.M., Drexler, J., Fuller, C.C., and Schoellhamer, D., 2015, Modeling tidal freshwater marsh sustainability in the Sacramento-San Joaquin Delta under a broad suite of potential future scenarios: San Francisco Estuary and Watershed Science, v. 13, no. 1, p. 1-21, https://doi.org/10.15447/sfews.2015v13iss1art3.","productDescription":"21 p.","startPage":"1","endPage":"21","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042916","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":472134,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2015v13iss1art3","text":"Publisher Index Page"},{"id":299841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacremento-San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.135009765625,\n 37.59682400108367\n ],\n [\n -122.135009765625,\n 38.601846852838094\n ],\n [\n -121.08581542968751,\n 38.601846852838094\n ],\n [\n -121.08581542968751,\n 37.59682400108367\n ],\n [\n -122.135009765625,\n 37.59682400108367\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-27","publicationStatus":"PW","scienceBaseUri":"553a09c7e4b0c1efddaed13d","contributors":{"authors":[{"text":"Swanson, Kathleen M. kathswan@usgs.gov","contributorId":3757,"corporation":false,"usgs":true,"family":"Swanson","given":"Kathleen","email":"kathswan@usgs.gov","middleInitial":"M.","affiliations":[{"id":34319,"text":"Mission-Aransas National Estuarine Research Reserve, Port Aransas, TX, USA","active":true,"usgs":false}],"preferred":false,"id":545421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":1659,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith Z.","email":"jdrexler@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":545418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545419,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70146874,"text":"70146874 - 2015 - Identifying a reliable blubber measurement site to assess body condition in a marine mammal with topographically variable blubber, the Pacific walrus","interactions":[],"lastModifiedDate":"2018-06-16T17:52:03","indexId":"70146874","displayToPublicDate":"2015-04-23T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying a reliable blubber measurement site to assess body condition in a marine mammal with topographically variable blubber, the Pacific walrus","docAbstract":"

Pacific walruses may be unable to meet caloric requirements in the changing Arctic ecosystem, which could affect body condition and have population-level consequences. Body condition has historically been monitored by measuring blubber thickness over the xiphoid process (sternum). This may be an unreliable condition index because blubber at other sites along the body may be preferentially targeted to balance energetic demands. Animals in aquaria provided an opportunity for controlled study of how blubber topography is altered by caloric intake. Morphology, body mass, blubber thickness (21 sites), and caloric intake of five mature, nonpregnant, nonlactating female walruses were measured monthly (12 month minimum). Body condition (mass × standard length−1) was described by a model that included caloric intake and a seasonal effect, and scaled positively with estimates of total blubber mass. Blubber thicknesses (1.91–10.69 cm) varied topographically and were similar to values reported for free-ranging female walruses. Body condition was most closely related to blubber thickness measured dorsomedially in the region of the anterior insertion of the pectoral flippers (shoulders); sternum blubber thickness was a relatively poor indicator of condition. This study demonstrates the importance of validating condition metrics before using them to monitor free-ranging populations.

","language":"English","publisher":"Wiley","doi":"10.1111/mms.12186","usgsCitation":"Noren, S.R., Udevitz, M.S., Triggs, L., Paschke, J., Oland, L., and Jay, C.V., 2015, Identifying a reliable blubber measurement site to assess body condition in a marine mammal with topographically variable blubber, the Pacific walrus: Marine Mammal Science, v. 31, no. 2, p. 658-676, https://doi.org/10.1111/mms.12186.","productDescription":"9 p.","startPage":"658","endPage":"676","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052012","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":299839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-03","publicationStatus":"PW","scienceBaseUri":"553a09bbe4b0c1efddaed137","chorus":{"doi":"10.1111/mms.12186","url":"http://dx.doi.org/10.1111/mms.12186","publisher":"Wiley-Blackwell","authors":"Noren Shawn R., Udevitz Mark S., Triggs Lisa, Paschke Jessa, Oland Lisa, Jay Chadwick V.","journalName":"Marine Mammal Science","publicationDate":"12/3/2014","auditedOn":"1/6/2015"},"contributors":{"authors":[{"text":"Noren, Shawn R.","contributorId":127697,"corporation":false,"usgs":false,"family":"Noren","given":"Shawn","email":"","middleInitial":"R.","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":545473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":545427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Triggs, Lisa","contributorId":140383,"corporation":false,"usgs":false,"family":"Triggs","given":"Lisa","affiliations":[],"preferred":false,"id":545474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paschke, Jessa","contributorId":140384,"corporation":false,"usgs":false,"family":"Paschke","given":"Jessa","email":"","affiliations":[],"preferred":false,"id":545475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oland, Lisa","contributorId":140385,"corporation":false,"usgs":false,"family":"Oland","given":"Lisa","email":"","affiliations":[],"preferred":false,"id":545476,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":545477,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70137582,"text":"ofr20151003 - 2015 - Southern Great Plains Rapid Ecoregional Assessment: pre-assessment report","interactions":[],"lastModifiedDate":"2018-11-21T11:23:23","indexId":"ofr20151003","displayToPublicDate":"2015-04-23T10:30:00","publicationYear":"2015","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":"2015-1003","title":"Southern Great Plains Rapid Ecoregional Assessment: pre-assessment report","docAbstract":"

The purpose of the Pre-Assessment Report for the Southern Great Plains Rapid Ecoregional Assessment (REA) is to document the selection process for and final list of Conservation Elements, Change Agents, and Management Questions developed during Phase I. The overall goal of the REAs being conducted for the Bureau of Land Management (BLM) is to provide information that supports regional planning and analysis for the management of ecological resources. The REA provides an assessment of baseline ecological conditions, an evaluation of current risks from drivers of ecosystem change, and a predictive capacity for evaluating future risks. The REA also may be used for identifying priority areas for conservation or restoration and for assessing the cumulative effects of a variety of land uses. There are several components of the REAs. Management Questions, developed by the BLM and partners for the ecoregion, identify the information needed for addressing land-management responsibilities. Conservation Elements represent regionally significant terrestrial and aquatic species and communities that are to be conserved and (or) restored. For each Conservation Element, key ecological attributes will be evaluated to determine the status of each species and community. The REA also will evaluate major drivers of ecosystem change, or Change Agents, currently affecting or likely to affect the status of Conservation Elements in the future. The relationships between Change Agents and key ecological attributes will be summarized using conceptual models. The REA process is a two-phase process. Phase I (pre-assessment) includes developing and finalizing the lists of priority Management Questions, Conservation Elements, and Change Agents, culminating in the REA Pre-Assessment Report.

\n

Chapter 1 provides an overview of the REA process. Chapter 2 describes the biophysical and anthropogenic features of the Southern Great Plains, and Chapter 3 explains the process used to identify Conservation Elements, Change Agents and Management Questionss. The remaining chapters each feature one of 19 Conservation Elements—6 ecological communities and 13 species (including 2 species assemblages)—to be addressed in Phase II. For each Conservation Element, we will address the four primary Change Agents—development, fire, invasive species, and climate change—required for the REA. In addition, we will evaluate insect pests and disease for particular Conservation Elements. Development includes effects related to energy and infrastructure, agricultural activities, and other human activities, including urbanization and recreation.

\n

An overview on the ecology and management issues for each Conservation Element is provided, including distribution and ecology, landscape structure and dynamics, and associated species of management concern affiliated with each Conservation Element. For each Conservation Element, effects of the Change Agents are described. An overview of potential key ecological attributes and potential Change Agents are summarized by conceptual models and tables. The tables provide an organizational framework and background information for evaluating the key ecological attributes and Change Agents in Phase II.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151003","collaboration":"Prepared in cooperation with Bureau of Land Management","usgsCitation":"Assal, T.J., Melcher, C.P., and Carr, N.B., 2015, Southern Great Plains Rapid Ecoregional Assessment: pre-assessment report: U.S. Geological Survey Open-File Report 2015-1003, xiv, 284 p., https://doi.org/10.3133/ofr20151003.","productDescription":"xiv, 284 p.","numberOfPages":"302","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059315","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":299833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151003.jpg"},{"id":299825,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1003/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":299832,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1003/pdf/ofr2015-1003.pdf","text":"Report","size":"19.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Colorado, Kansas, New Mexico, Oklahoma, Texas","otherGeospatial":"Southern Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.22656249999999,\n 31.16580958786196\n ],\n [\n -107.22656249999999,\n 41.3108238809182\n ],\n [\n -95.44921875,\n 41.3108238809182\n ],\n [\n -95.44921875,\n 31.16580958786196\n ],\n [\n -107.22656249999999,\n 31.16580958786196\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553a09cee4b0c1efddaed143","contributors":{"authors":[{"text":"Assal, Timothy J. 0000-0001-6342-2954 assalt@usgs.gov","orcid":"https://orcid.org/0000-0001-6342-2954","contributorId":2203,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","email":"assalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":545422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melcher, Cynthia P. 0000-0002-8044-9689 melcherc@usgs.gov","orcid":"https://orcid.org/0000-0002-8044-9689","contributorId":5094,"corporation":false,"usgs":true,"family":"Melcher","given":"Cynthia","email":"melcherc@usgs.gov","middleInitial":"P.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":545423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Natasha B. 0000-0002-4842-0632 carrn@usgs.gov","orcid":"https://orcid.org/0000-0002-4842-0632","contributorId":1918,"corporation":false,"usgs":true,"family":"Carr","given":"Natasha","email":"carrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":545424,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70146802,"text":"ofr20151070 - 2015 - Incorporating induced seismicity in the 2014 United States National Seismic Hazard Model: results of the 2014 workshop and sensitivity studies","interactions":[],"lastModifiedDate":"2015-04-23T09:07:42","indexId":"ofr20151070","displayToPublicDate":"2015-04-23T09:45:00","publicationYear":"2015","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":"2015-1070","title":"Incorporating induced seismicity in the 2014 United States National Seismic Hazard Model: results of the 2014 workshop and sensitivity studies","docAbstract":"

The U.S. Geological Survey National Seismic Hazard Model for the conterminous United States was updated in 2014 to account for new methods, input models, and data necessary for assessing the seismic ground shaking hazard from natural (tectonic) earthquakes. The U.S. Geological Survey National Seismic Hazard Model project uses probabilistic seismic hazard analysis to quantify the rate of exceedance for earthquake ground shaking (ground motion). For the 2014 National Seismic Hazard Model assessment, the seismic hazard from potentially induced earthquakes was intentionally not considered because we had not determined how to properly treat these earthquakes for the seismic hazard analysis. The phrases “potentially induced” and “induced” are used interchangeably in this report, however it is acknowledged that this classification is based on circumstantial evidence and scientific judgment. For the 2014 National Seismic Hazard Model update, the potentially induced earthquakes were removed from the NSHM’s earthquake catalog, and the documentation states that we would consider alternative models for including induced seismicity in a future version of the National Seismic Hazard Model. As part of the process of incorporating induced seismicity into the seismic hazard model, we evaluate the sensitivity of the seismic hazard from induced seismicity to five parts of the hazard model: (1) the earthquake catalog, (2) earthquake rates, (3) earthquake locations, (4) earthquake Mmax (maximum magnitude), and (5) earthquake ground motions. We describe alternative input models for each of the five parts that represent differences in scientific opinions on induced seismicity characteristics. In this report, however, we do not weight these input models to come up with a preferred final model. Instead, we present a sensitivity study showing uniform seismic hazard maps obtained by applying the alternative input models for induced seismicity. The final model will be released after further consideration of the reliability and scientific acceptability of each alternative input model. Forecasting the seismic hazard from induced earthquakes is fundamentally different from forecasting the seismic hazard for natural, tectonic earthquakes. This is because the spatio-temporal patterns of induced earthquakes are reliant on economic forces and public policy decisions regarding extraction and injection of fluids. As such, the rates of induced earthquakes are inherently variable and nonstationary. Therefore, we only make maps based on an annual rate of exceedance rather than the 50-year rates calculated for previous U.S. Geological Survey hazard maps.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151070","usgsCitation":"Petersen, M.D., Mueller, C., Moschetti, M.P., Hoover, S.M., Rubinstein, J.L., Llenos, A.L., Michael, A.J., Ellsworth, W.L., McGarr, A.F., Holland, A.A., and Anderson, J.G., 2015, Incorporating induced seismicity in the 2014 United States National Seismic Hazard Model: results of the 2014 workshop and sensitivity studies: U.S. Geological Survey Open-File Report 2015-1070, vi, 69 p., https://doi.org/10.3133/ofr20151070.","productDescription":"vi, 69 p.","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063971","costCenters":[{"id":300,"text":"Geologic Hazards Science 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Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5050","title":"Estimates of natural streamflow at two streamgages on the Esopus Creek, New York, water years 1932 to 2012","docAbstract":"

Streamflow in the Esopus Creek watershed is altered by two major watershed management activities carried out by the New York City Department of Environmental Protection as part of its responsibility to maintain a water supply for New York City: (1) diversion of water from the Schoharie Creek watershed to the Esopus Creek through the Shandaken Tunnel, and (2) impoundment of the Esopus Creek by a dam that forms the Ashokan Reservoir and subsequent release through the Catskill Aqueduct. Stakeholders in the Catskill region are interested and concerned about the extent to which these watershed management activities have altered streamflow, especially low and high flows, in the Esopus Creek. To address these concerns, natural (in the absence of diversion and impoundment) daily discharge from October 1, 1931, to September 30, 2012, was estimated for the U.S. Geological Survey streamgages at Coldbrook (station number 01362500), downstream of the Shandaken Tunnel discharge, and at Mount Marion (01364500), downstream of the Ashokan Reservoir.

\n

A multiple linear regression approach, using nearby discharge records from unimpounded streams as predictive variables, was applied to estimate natural discharge at the Coldbrook streamgage. Estimated values of natural daily discharge at the Coldbrook streamgage were lower than values of gaged daily discharge throughout the flow range at this site. At moderate- and low-flow conditions, gaged daily-discharge values were about two to three times greater than natural daily-discharge estimates, whereas the difference between the two records was less than 5 percent for the highest 1 percent of daily-discharge values. These results indicate that Shandaken Tunnel discharge has a minor effect on flooding in the Esopus Creek Basin. However, a difference of 5 percent is within the uncertainty of the regression-based natural discharge estimates for Coldbrook; thus, it cannot be stated with certainty that the Tunnel has on average any effect on flow for the highest 1 percent of daily discharge values.

\n

Natural discharge at the Mount Marion streamgage was estimated by summing the natural discharge estimated for the Coldbrook streamgage and the discharge estimated for the intervening basin area through application of the New York Streamflow Estimation Tool, recently developed for estimating unaltered streamflow at ungaged locations in the State. Estimates of natural daily discharge at the Mount Marion streamgage were about three times greater than gaged daily discharge throughout the moderate- to low-flow range from October 1, 1970, to September 30, 2012, the period of record for full water years at this streamgage. The relative difference between the two discharge time series declined as flow increased beyond the moderate range, but gaged daily discharge was still 25 to 43 percent less than estimated natural daily discharge for the high-flow metrics calculated in this analysis, and the mean relative difference was 43 percent for the annual 1-day maximum discharge. Overall, these estimates of natural discharge reflect the absence of effects of the Shandaken Tunnel and Ashokan Reservoir on flows in the Esopus Creek over broad time frames. However, caution is warranted if one is attempting to apply the natural estimates at short time scales because the regression prediction intervals indicate that uncertainty at a daily time step ranges from about 40 to 80 percent.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155050","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Burns, D.A., and Gazoorian, C.L., 2015, Estimates of natural streamflow at two streamgages on the Esopus Creek, New York, water years 1932 to 2012: U.S. Geological Survey Scientific Investigations Report 2015-5050, v, 20 p., https://doi.org/10.3133/sir20155050.","productDescription":"v, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1931-10-01","temporalEnd":"2012-09-30","ipdsId":"IP-057285","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":299831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155050.jpg"},{"id":299830,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5050/pdf/sir2015-5050.pdf","text":"Report","size":"2.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299829,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5050/"}],"country":"United States","state":"New York","otherGeospatial":"Esopus Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.57244873046875,\n 41.81636125072054\n ],\n [\n -74.57244873046875,\n 42.14507804381756\n ],\n [\n -73.8885498046875,\n 42.14507804381756\n ],\n [\n -73.8885498046875,\n 41.81636125072054\n ],\n [\n -74.57244873046875,\n 41.81636125072054\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"553a09b7e4b0c1efddaed135","contributors":{"authors":[{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543779,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155207,"text":"70155207 - 2015 - Suspended-sediment concentrations, yields, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011","interactions":[],"lastModifiedDate":"2016-12-20T13:47:07","indexId":"70155207","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Suspended-sediment concentrations, yields, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011","docAbstract":"Excessive sediment transport in rivers causes problems for flood control, soil conservation, irrigation, aquatic health, and navigation, as well as transporting harmful contaminants like organic chemicals and eutrophication-causing nutrients. In Minnesota, more than 5,800 miles of streams are identified as impaired by the Minnesota Pollution Control Agency (MPCA) due to elevated levels of suspended sediment. \n\nThe U.S. Geological Survey, in cooperation with the MPCA, established a sediment monitoring network in 2007 and began systematic sampling of suspended-sediment concentration (SSC), total suspended solids (TSS), and turbidity in rivers across Minnesota to improve the understanding of fluvial sediment transport relations. Suspended-sediment samples were collected from 14 sites from 2007 through 2011. Analyses of these data indicated that the Zumbro River at Kellogg in southeast Minnesota had the highest mean SSC of 226 milligrams per liter (mg/L) followed by the Minnesota River at Mankato with a mean SSC of 193 mg/L. The single highest SSC of 1,250 mg/L was measured at the Zumbro River during the 2011 spring runoff. The lowest mean SSC of 21 mg/L was measured at Rice Creek in the northern Minneapolis-St. Paul metropolitan area.\n\nTotal suspended solids (TSS) have been used as a measure of fluvial sediment by the MPCA since the early 1970s; however, TSS concentrations have been known to underrepresent the amount of suspended sediment. For this study, comparisons between concurrently sampled SSC and TSS indicated significant differences at every site, with SSC on average two times larger than TSS concentrations. \n\nRegression analysis indicated that 7 out of 14 sites had poor or no relation between SSC and streamflow. Only two sites, the Knife River and the Wild Rice River at Twin Valley, had strong correlations between SSC and streamflow, with coefficient of determination (R2) values of 0.82 and 0.80, respectively. In contrast, turbidity had moderate to strong relations with SSC at 10 of 14 sites and was superior to streamflow for estimating SSC at all sites. Suspended-sediment basin yields indicated that the Minnesota River had the largest mean annual sediment basin yield of 120 tons of sediment per year per square mile.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of joint federal Interagency conference 2015","conferenceTitle":"5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation","conferenceDate":" April 19 – 23, 2015","conferenceLocation":"Reno, NV","language":"English","collaboration":"Minnesota Pollution Control Agency","usgsCitation":"Ellison, C.A., Savage, B.E., and Johnson, G., 2015, Suspended-sediment concentrations, yields, total suspended solids, turbidity, and particle-size fractions for selected rivers in Minnesota, 2007 through 2011, in Proceedings of joint federal Interagency conference 2015, Reno, NV, April 19 – 23, 2015, p. 869-880.","productDescription":"12 p. ","startPage":"869","endPage":"880","ipdsId":"IP-061247","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":332345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":305837,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/Proceedings.pdf"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51bfe4b01224f329b5f3","contributors":{"authors":[{"text":"Ellison, Christopher A. 0000-0002-5886-6654 cellison@usgs.gov","orcid":"https://orcid.org/0000-0002-5886-6654","contributorId":4891,"corporation":false,"usgs":true,"family":"Ellison","given":"Christopher","email":"cellison@usgs.gov","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":565075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savage, Brett E. besavage@usgs.gov","contributorId":5188,"corporation":false,"usgs":true,"family":"Savage","given":"Brett","email":"besavage@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Gregory D.","contributorId":14326,"corporation":false,"usgs":true,"family":"Johnson","given":"Gregory D.","affiliations":[],"preferred":false,"id":565077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148359,"text":"70148359 - 2015 - Large river bed sediment characterization with low-cost sidecan sonar: Case studies from two setting in the Colorado (Arizona) and Penobscot (Maine) Rivers","interactions":[],"lastModifiedDate":"2018-04-23T13:11:33","indexId":"70148359","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Large river bed sediment characterization with low-cost sidecan sonar: Case studies from two setting in the Colorado (Arizona) and Penobscot (Maine) Rivers","docAbstract":"Mapping subaqueous riverbed sediment grain size across channels and in nearshore areas typically used by fish and benthic invertebrates is difficult where and when the water flow is too swift or deep to wade yet impractical to access with large boats and instruments. Fluvial characteristics can further constrain sampling options, particularly where flow depth, water column turbidity or channel bottom structure prohibit use of aerial or bottom deployed imaging platforms.\nHere we discuss considerations in the use of sidescan sonar for riverbed sediment classification using examples from two large rivers, the Colorado River below Glen Canyon Dam in Arizona and the Upper Penobscot River in northern Maine (Figure 3). These case studies represent two fluvial systems that differ in recent history, physiography, sediment transport, and fluvial morphologies. The bed of the Colorado River in Glen Canyon National Recreation Area is predominantly graveled with extensive mats of submerged vegetation, and ephemeral surficial sand deposits exist below major tributaries. The bed is imaged periodically to assess the importance of substrate type and variability on rainbow trout spawning and juvenile rearing habitats and controls on aquatic invertebrate population dynamics. The Colorado River bed further below the dam in Grand Canyon National Park is highly dynamic. Tributary inputs of sand, gravel and boulders are spatially variable, and hydraulics of individual pools and eddies vary considerably in space and in response to varying dam operations, including experimental controlled flood releases to rebuild eroding sandbars. The bed encompasses the full range of noncohesive sediments, deposited in complicated spatial patterns. The mobile portion of the Penobscot River is generally more uniform, and consists predominantly of embedded gravels interspersed between bedrock outcrops with small isolated sand patches in sections with modest or low gradients. Patches of large cobbles, boulders and bedrock outcrops are present in the lower reaches of the river near locations of two recent dam removal projects but are of limited extent below the \"head of tide\" on the river. Aggregations of coarse materials often correspond to locations with abrupt bed elevation drops in the Upper Penobscot River.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the 3rd joint federal interagency conference on sedimentation and hydrologic modeling","conferenceTitle":"5th federal interagency hydrologic modeling conference and the 10th federal interagency sedimentation conference ","conferenceDate":"April 19 – 23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Conference","usgsCitation":"Buscombe, D.D., Grams, P.E., Melis, T., and Smith, S., 2015, Large river bed sediment characterization with low-cost sidecan sonar: Case studies from two setting in the Colorado (Arizona) and Penobscot (Maine) Rivers, in Proceedings of the 3rd joint federal interagency conference on sedimentation and hydrologic modeling, Reno, NV, April 19 – 23, 2015, p. 1273-1277.","productDescription":"5 p. 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Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications could greatly expand the usage of these methods. Suspended sediment load estimation could occur as soon as flow and turbidity monitoring commence at a site, suspended sediment sampling frequencies for various projects potentially could be reduced, and special-project applications (sediment monitoring following dam removal, for example) could be significantly enhanced. The objective of this effort was to investigate the turbidity-suspended sediment concentration (SSC) relations at all available USGS monitoring sites within Virginia to determine whether meaningful turbidity-sediment regression models can be developed by combining the data from multiple monitoring stations into a single model, known as a “regional” model. Following the development of the regional model, additional objectives included a comparison of predicted SSCs between the regional model and commonly used site-specific models, as well as an evaluation of why specific monitoring stations did not fit the regional model.

","conferenceTitle":"10th Federal Interagency Sedimentation Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","usgsCitation":"Hyer, K., Jastram, J.D., Moyer, D., Webber, J., and Chanat, J.G., 2015, Evaluation and application of regional turbidity-sediment regression models in Virginia, 10th Federal Interagency Sedimentation Conference, Reno, NV, April 19-23, 2015, 9 p.","productDescription":"9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061841","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":311618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.001708984375,\n 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Science Center","active":true,"usgs":true}],"preferred":true,"id":543202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Douglas 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":2670,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webber, James S. jwebber@usgs.gov","contributorId":139839,"corporation":false,"usgs":true,"family":"Webber","given":"James S.","email":"jwebber@usgs.gov","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543205,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70137268,"text":"70137268 - 2015 - Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery","interactions":[],"lastModifiedDate":"2015-10-26T11:27:56","indexId":"70137268","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery","docAbstract":"

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

","conferenceTitle":"SEDHYD 2015","conferenceDate":"19-23 April, 2015","conferenceLocation":"Reno, Nevada","language":"English","collaboration":"Federal Interagency Sediment Program","usgsCitation":"Mosbrucker, A.R., Spicer, K.R., Christianson, T.S., and Uhrich, M.A., 2015, Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery, SEDHYD 2015, Reno, Nevada, 19-23 April, 2015, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060181","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":310634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562f4eb1e4b093cee780a287","contributors":{"authors":[{"text":"Mosbrucker, Adam R. 0000-0003-0298-0324 amosbrucker@usgs.gov","orcid":"https://orcid.org/0000-0003-0298-0324","contributorId":4968,"corporation":false,"usgs":true,"family":"Mosbrucker","given":"Adam","email":"amosbrucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spicer, Kurt R. 0000-0001-5030-3198 krspicer@usgs.gov","orcid":"https://orcid.org/0000-0001-5030-3198","contributorId":2684,"corporation":false,"usgs":true,"family":"Spicer","given":"Kurt","email":"krspicer@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christianson, Tami S. 0000-0002-6873-9229 tchristianson@usgs.gov","orcid":"https://orcid.org/0000-0002-6873-9229","contributorId":5986,"corporation":false,"usgs":true,"family":"Christianson","given":"Tami","email":"tchristianson@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Uhrich, Mark A. 0000-0002-5202-8086 mauhrich@usgs.gov","orcid":"https://orcid.org/0000-0002-5202-8086","contributorId":1149,"corporation":false,"usgs":true,"family":"Uhrich","given":"Mark","email":"mauhrich@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":537626,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70137942,"text":"70137942 - 2015 - The upper bound of abutment scour defined by selected laboratory and field data","interactions":[],"lastModifiedDate":"2016-11-30T14:38:26","indexId":"70137942","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"The upper bound of abutment scour defined by selected laboratory and field data","docAbstract":"

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted a field investigation of abutment scour in South Carolina and used that data to develop envelope curves defining the upper bound of abutment scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with abutment-scour data from other sources and evaluate the upper bound of abutment scour with the larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published abutment-scour data, and selected data, consisting of 446 laboratory and 331 field measurements, were compiled for the analysis. These data encompassed a wide range of laboratory and field conditions and represent field data from 6 states within the United States. The data set was used to evaluate the South Carolina abutment-scour envelope curves. Additionally, the data were used to evaluate a dimensionless abutment-scour envelope curve developed by Melville (1992), highlighting the distinct difference in the upper bound for laboratory and field data. The envelope curves evaluated in this investigation provide simple but useful tools for assessing the potential maximum abutment-scour depth in the field setting.

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The confluence of the Sacramento and San Joaquin Rivers, CA, forms a large network of interconnected channels, referred to as the Sacramento-San Joaquin Delta (the Delta). The Delta comprises the transition zone from the fluvial influences of the upstream rivers and tidal influences of San Francisco Bay downstream. Formerly an extensive tidal marsh, the hydrodynamics and geomorphology of Delta have been substantially modified by humans to support agriculture, navigation, and water supply. These modifications, including construction of new channels, diking and draining of tidal wetlands, dredging of navigation channels, and the operation of large pumping facilities for distribution of freshwater from the Delta to other parts of the state, have had a dramatic impact on the physical and ecological processes within the Delta. To better understand the current physical processes, and their linkages to ecological processes, the USGS maintains an extensive network of flow, sediment, and water quality gages in the Delta. Flow gaging is accomplished through use of the index-velocity method, and sediment monitoring uses turbidity as a surrogate for suspended-sediment concentration. Herein, we present analyses of the transport and dispersal of suspended sediment through the complex network of channels in the Delta. The primary source of sediment to the Delta is the Sacramento River, which delivers pulses of sediment primarily during winter and spring runoff events. Upon reaching the Delta, the sediment pulses move through the fluvial-tidal transition while also encountering numerous channel junctions as the Sacramento River branches into several distributary channels. The monitoring network allows us to track these pulses through the network and document the dominant transport pathways for suspended sediment. Further, the flow gaging allows for an assessment of the relative effects of advection (the fluvial signal) and dispersion (from the tides) on the sediment pulses as they move through the system. Herein, we present analyses of the “first flush” sediment pulse that occurred on the Sacramento River in December 2012, documenting the transport pathways as well as the effects of advection and dispersion on the sediment as it moved through the fluvial-tidal transition in the Delta. The analyses identified an important transport pathway through the interior of the Delta toward the large pumping facilities in the south Delta, which has important implications for native fish (because their movements are triggered by sediment/turbidity). The results also reveal the dramatic transition from fluvial-dominated transport (advection) to tidal-dominated transport (dispersion) as the sediment pulse approaches the estuary.

","conferenceTitle":"SEDHYD 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, Nevada","language":"English","usgsCitation":"Wright, S., and Morgan-King, T.L., 2015, Suspended sediment transport trough a large fluvial-tidal channel network, SEDHYD 2015, Reno, Nevada, April 19-23, 2015, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061555","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":311116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311115,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2015/openconf/modules/request.php?module=oc_program&action=summary.php&id=173"}],"country":"United States","state":"California","otherGeospatial":"Sacramento and San Joaquin Rivers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.94549560546875,\n 37.85316995894978\n ],\n [\n -121.47033691406249,\n 37.85316995894978\n ],\n [\n -121.47033691406249,\n 38.31149091244452\n ],\n [\n -121.94549560546875,\n 38.31149091244452\n ],\n [\n -121.94549560546875,\n 37.85316995894978\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5641d1c3e4b0831b7d62e74b","contributors":{"authors":[{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan-King, Tara L. 0000-0001-5632-5232 tamorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-5632-5232","contributorId":554,"corporation":false,"usgs":true,"family":"Morgan-King","given":"Tara","email":"tamorgan@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}