Estimating rates of magma supply to the world's volcanoes remains one of the most fundamental aims of volcanology. Yet, supply rates can be difficult to estimate even at well-monitored volcanoes, in part because observations are noisy and are usually considered independently rather than as part of a holistic system. In this work we demonstrate a technique for probabilistically estimating time-variable rates of magma supply to a volcano through probabilistic constraint on storage and eruption rates. This approach utilizes Bayesian joint inversion of diverse datasets using predictions from a multiphysical volcano model, and independent prior information derived from previous geophysical, geochemical, and geological studies. The solution to the inverse problem takes the form of a probability density function which takes into account uncertainties in observations and prior information, and which we sample using a Markov chain Monte Carlo algorithm. Applying the technique to Kīlauea Volcano, we develop a model which relates magma flow rates with deformation of the volcano's surface, sulfur dioxide emission rates, lava flow field volumes, and composition of the volcano's basaltic magma. This model accounts for effects and processes mostly neglected in previous supply rate estimates at Kīlauea, including magma compressibility, loss of sulfur to the hydrothermal system, and potential magma storage in the volcano's deep rift zones. We jointly invert data and prior information to estimate rates of supply, storage, and eruption during three recent quasi-steady-state periods at the volcano. Results shed new light on the time-variability of magma supply to Kīlauea, which we find to have increased by 35–100% between 2001 and 2006 (from 0.11–0.17 to 0.18–0.28 km3/yr), before subsequently decreasing to 0.08–0.12 km3/yr by 2012. Changes in supply rate directly impact hazard at the volcano, and were largely responsible for an increase in eruption rate of 60–150% between 2001 and 2006, and subsequent decline by as much as 60% by 2012. We also demonstrate the occurrence of temporal changes in the proportion of Kīlauea's magma supply that is stored versus erupted, with the supply “surge” in 2006 associated with increased accumulation of magma at the summit. Finally, we are able to place some constraints on sulfur concentrations in Kīlauea magma and the scrubbing of sulfur by the volcano's hydrothermal system. Multiphysical, Bayesian constraint on magma flow rates may be used to monitor evolving volcanic hazard not just at Kīlauea but at other volcanoes around the world.
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\nUsing the HadCM3 GCM, this paper explores the impact of various combinations of potential mPWP orbital forcing, atmospheric CO2 concentrations and minimum sea ice albedo on sea ice extent and high latitude warming. The focus is on the Northern Hemisphere, due to availability of proxy data, and the large data–model discrepancies in this region. Changes in orbital forcings are demonstrated to be sufficient to alter the Arctic sea ice simulated by HadCM3 from perennial to seasonal. However, this occurs only when atmospheric CO2 concentrations exceed 300 ppm. Reduction of the minimum sea ice albedo from 0.5 to 0.2 is also sufficient to simulate seasonal sea ice, with any of the combinations of atmospheric CO2 and orbital forcing. Compared to a mPWP control simulation, monthly mean increases north of 60°N of up to 4.2 °C (SST) and 9.8 °C (SAT) are simulated.
\nWith varying CO2, orbit and sea ice albedo values we are able to reproduce proxy temperature records that lean towards modest levels of high latitude warming, but other proxy data showing greater warming remain beyond the reach of our model. This highlights the importance of additional proxy records at high latitudes and ongoing efforts to compare proxy signals between sites.
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These assessments would identify long-term trends or changes in water availability since the 1950s in the United States and help to develop the basis for an improved ability to forecast water avail- ability for future economic, energy-production, and environmental uses. The National Water Census (http://water.usgs.gov/watercensus/), a research program of the WAUSP, supports studies to develop new water accounting tools and assess water availability at the regional and national scales. Studies supported by this program target focus areas with identified water availability concerns and topical science themes related to the use of water within a specific type of environmental setting. The topical study described in this fact sheet will focus on understanding the relation between production of unconventional oil and gas (UOG) for energy and the water needed to produce and sustain this type of energy development. This relation applies to the life-cycle of renewable and nonrenewable forms of UOG energy and includes extraction, production, refinement, delivery, and disposal of waste byproducts. Water-use data and models derived from this topical study will be applied to other similar oil and gas plays within the United States to help resource managers assess and account for water used or needed in these areas. Additionally, the results from this topical study will be used to further refine the methods used in compiling water-use data for selected categories (for example, mining, domestic self-supplied, public supply, and wastewater) in the USGS’s 5-year national water-use estimates reports (http://water.usgs.gov/watuse/).
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The restoration of the Nisqually River Delta (Washington, U.S.A.) represents one of the largest efforts toward reestablishing the ecosystem function and resilience of modified habitat in the Puget Sound, particularly for anadromous salmonid species. The opportunity for outmigrating salmon to access and benefit from the expansion of available tidal habitat can be quantified by several physical attributes, which are related to the ecological and physiological responses of juvenile salmon. We monitored a variety of physical parameters to measure changes in opportunity potential from historic, pre-restoration, and post-restoration habitat conditions at several sites across the delta. These parameters included channel morphology, water quality, tidal elevation, and landscape connectivity. We conducted fish catch surveys across the delta to determine if salmon was utilizing restored estuary habitat. Overall major channel area increased 42% and major channel length increased 131% from pre- to post-restoration conditions. Furthermore, the results of our tidal inundation model indicated that major channels were accessible up to 75% of the time, as opposed to 30% pre-restoration. Outmigrating salmon utilized this newly accessible habitat as quickly as 1 year post-restoration. The presence of salmon in restored tidal channels confirmed rapid post-restoration increases in opportunity potential on the delta despite habitat quality differences between restored and reference sites.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12333","usgsCitation":"Ellings, C.S., Davis, M.J., Grossman, E., Hodgson, S., Turner, K.L., Woo PR, I., Nakai, G., Takekawa, J.E., and Takekawa, J.Y., 2016, Changes in habitat availability for outmigrating juvenile salmon (Oncorhychus spp.) following estuary restoration: Restoration Ecology, v. 24, no. 3, p. 415-427, https://doi.org/10.1111/rec.12333.","productDescription":"12 p.","startPage":"415","endPage":"427","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065021","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":323963,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n 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Glynnis","contributorId":172123,"corporation":false,"usgs":false,"family":"Nakai","given":"Glynnis","email":"","affiliations":[{"id":26986,"text":"US Fish and Wildlife Service, Nisqually Nat'l Wildlife Refuge, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":639650,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Takekawa, Jean E.","contributorId":146991,"corporation":false,"usgs":false,"family":"Takekawa","given":"Jean","email":"","middleInitial":"E.","affiliations":[{"id":16768,"text":"USFWS, Nisqually NWR, Olympia, WA","active":true,"usgs":false}],"preferred":false,"id":639652,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":639651,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70171044,"text":"70171044 - 2016 - Ecology of nonnative Siberian prawn (Palaemon modestus) in the lower Snake River, Washington, USA","interactions":[],"lastModifiedDate":"2016-11-09T10:34:31","indexId":"70171044","displayToPublicDate":"2016-05-18T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":863,"text":"Aquatic Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Ecology of nonnative Siberian prawn (Palaemon modestus) in the lower Snake River, Washington, USA","docAbstract":"We assessed the abundance, distribution, and ecology of the nonnative Siberian prawn Palaemon modestus in the lower Snake River, Washington, USA. Analysis of prawn passage abundance at three Snake River dams showed that populations are growing at exponential rates, especially at Little Goose Dam where over 464,000 prawns were collected in 2015. Monthly beam trawling during 2011–2013 provided information on prawn abundance and distribution in Lower Granite and Little Goose Reservoirs. Zero-inflated regression predicted that the probability of prawn presence increased with decreasing water velocity and increasing depth. Negative binomial models predicted higher catch rates of prawns in deeper water and in closer proximity to dams. Temporally, prawn densities decreased slightly in the summer, likely due to the mortality of older individuals, and then increased in autumn and winter with the emergence and recruitment of young of the year. Seasonal length frequencies showed that distinct juvenile and adult size classes exist throughout the year, suggesting prawns live from 1 to 2 years and may be able to reproduce multiple times during their life. Most juvenile prawns become reproductive adults in 1 year, and peak reproduction occurs from late July through October. Mean fecundity (189 eggs) and reproductive output (11.9 %) are similar to that in their native range. The current use of deep habitats by prawns likely makes them unavailable to most predators in the reservoirs. The distribution and role of Siberian prawns in the lower Snake River food web will probably continue to change as the population grows and warrants continued monitoring and investigation.
","language":"English","publisher":"Springer","doi":"10.1007/s10452-016-9581-4","usgsCitation":"Erhardt, J.M., and Tiffan, K.F., 2016, Ecology of nonnative Siberian prawn (Palaemon modestus) in the lower Snake River, Washington, USA: Aquatic Ecology, v. 50, no. 4, p. 607-621, https://doi.org/10.1007/s10452-016-9581-4.","productDescription":"15 p.","startPage":"607","endPage":"621","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072347","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":321375,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.36669921875,\n 46.1912395780416\n ],\n [\n -118.36669921875,\n 46.848921470800455\n ],\n [\n -116.83959960937499,\n 46.848921470800455\n ],\n [\n -116.83959960937499,\n 46.1912395780416\n ],\n [\n -118.36669921875,\n 46.1912395780416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-10","publicationStatus":"PW","scienceBaseUri":"573d841be4b0dae0d5e4c04d","contributors":{"authors":[{"text":"Erhardt, John M. 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":5380,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":629665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiffan, Kenneth F. 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":3200,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","middleInitial":"F.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":629664,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70171046,"text":"70171046 - 2016 - Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass","interactions":[],"lastModifiedDate":"2017-11-22T17:34:52","indexId":"70171046","displayToPublicDate":"2016-05-18T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass","docAbstract":"The Landsat 8 mission provides new opportunities for quantifying the distribution of above-ground carbon at moderate spatial resolution across the globe, and in particular drylands. Furthermore, coupled with structural information from space-based and airborne laser altimetry, Landsat 8 provides powerful capabilities for large-area, long-term studies that quantify temporal and spatial changes in above-ground biomass and cover. With the planned launch of ICESat-2 in 2017 and thus the potential to couple Landsat 8 and ICESat-2 data, we have unprecedented opportunities to address key challenges in drylands, including quantifying fuel loads, habitat quality, biodiversity, carbon cycling, and desertification.
\nIn this study, we explore the strengths of Landsat 8's Operational Land Imager (OLI) in estimating vegetation structure in a dryland ecosystem, and compare these results to Landsat 5's Thematic Mapper (TM). We also demonstrate the potential of OLI when coupled with light detection and ranging (lidar) in estimating vegetation cover and biomass in a dryland ecosystem. The OLI and TM predictions were similarly positive, indicating data from these sensors may be used in tandem for long-term time-series analysis. Results indicate shrub and herbaceous cover are well predicted with multi-temporal OLI data, and a combination of OLI and lidar derivatives improves most of these estimates and reduces uncertainty. For example, significant improvements were made for shrub cover (R2 = 0.64 and 0.78 using OLI only and both OLI and lidar data, respectively). Importantly, a time series of OLI, with some improvement from lidar, provides strong estimates of herbaceous cover (68% of the variance is explained with OLI alone). In contrast, OLI data explain roughly 59% of the variance in total shrub biomass, however approximately 71% of the variance is explained when combined with lidar derivatives.
\nTo estimate the potential synergies of OLI and ICESat-2 we used simulated ICESat-2 photon data to predict vegetation structure. In a shrubland environment with a vegetation mean height of 1 m and mean vegetation cover of 33%, vegetation photons are able to explain nearly 50% of the variance in vegetation height. These results, and those from a comparison site, suggest that a lower detection threshold of ICESat-2 may be in the range of 30% canopy cover and roughly 1 m height in comparable dryland environments and these detection thresholds could be used to combine future ICESat-2 photon data with OLI spectral data for improved vegetation structure. Overall, the synergistic use of Landsat 8 and ICESat-2 may improve estimates of above-ground biomass and carbon storage in drylands that meet these minimum thresholds, increasing our ability to monitor drylands for fuel loading and the potential to sequester carbon.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.02.039","usgsCitation":"Glenn, N.F., Neuenschwander, A., Vierling, L.A., Spaete, L., Li, A., Shinneman, D.J., Pilliod, D.S., Arkle, R., and McIlroy, S., 2016, Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass: Remote Sensing of Environment, v. 185, p. 233-242, https://doi.org/10.1016/j.rse.2016.02.039.","productDescription":"10 p.","startPage":"233","endPage":"242","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065442","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"573d841ce4b0dae0d5e4c05b","contributors":{"authors":[{"text":"Glenn, Nancy F.","contributorId":95321,"corporation":false,"usgs":true,"family":"Glenn","given":"Nancy","email":"","middleInitial":"F.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":629668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neuenschwander, Amy","contributorId":169442,"corporation":false,"usgs":false,"family":"Neuenschwander","given":"Amy","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":629669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":629670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spaete, Lucas","contributorId":169444,"corporation":false,"usgs":false,"family":"Spaete","given":"Lucas","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":629671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Aihua","contributorId":169445,"corporation":false,"usgs":false,"family":"Li","given":"Aihua","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":629672,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":629673,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":149254,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","email":"dpilliod@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":629667,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Arkle, Robert 0000-0003-3021-1389 rarkle@usgs.gov","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":149893,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","email":"rarkle@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":629674,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McIlroy, Susan K. 0000-0001-5088-3700 smcilroy@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-3700","contributorId":169446,"corporation":false,"usgs":true,"family":"McIlroy","given":"Susan","email":"smcilroy@usgs.gov","middleInitial":"K.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":629675,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70171055,"text":"70171055 - 2016 - A review of the relationships between drought and forest fire in the United States","interactions":[],"lastModifiedDate":"2016-06-16T11:18:51","indexId":"70171055","displayToPublicDate":"2016-05-18T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"A review of the relationships between drought and forest fire in the United States","docAbstract":"The historical and pre-settlement relationships between drought and wildfire are well documented in North America, with forest fire occurrence and area clearly increasing in response to drought. There is also evidence that drought interacts with other controls (forest productivity, topography, fire weather, management activities) to affect fire intensity, severity, extent, and frequency. Fire regime characteristics arise across many individual fires at a variety of spatial and temporal scales, so both weather and climate—including short- and long-term droughts—are important and influence several, but not all, aspects of fire regimes. We review relationships between drought and fire regimes in United States forests, fire-related drought metrics and expected changes in fire risk, and implications for fire management under climate change. Collectively, this points to a conceptual model of fire on real landscapes: fire regimes, and how they change through time, are products of fuels and how other factors affect their availability (abundance, arrangement, continuity) and flammability (moisture, chemical composition). Climate, management, and land use all affect availability, flammability, and probability of ignition differently in different parts of North America. From a fire ecology perspective, the concept of drought varies with scale, application, scientific or management objective, and ecosystem.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13275","usgsCitation":"Littell, J.S., Peterson, D.L., Riley, K.L., Liu, Y., and Luce, C.H., 2016, A review of the relationships between drought and forest fire in the United States: Global Change Biology, v. 22, no. 7, p. 2353-2369, https://doi.org/10.1111/gcb.13275.","productDescription":"17 p.","startPage":"2353","endPage":"2369","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070107","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":321369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-19","publicationStatus":"PW","scienceBaseUri":"573d841ae4b0dae0d5e4c036","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":629688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, David L.","contributorId":94643,"corporation":false,"usgs":false,"family":"Peterson","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":629689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riley, Karin L.","contributorId":169453,"corporation":false,"usgs":false,"family":"Riley","given":"Karin","email":"","middleInitial":"L.","affiliations":[{"id":25512,"text":"US Forest Service Fire Science Lab","active":true,"usgs":false}],"preferred":false,"id":629690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Yongquiang","contributorId":169454,"corporation":false,"usgs":false,"family":"Liu","given":"Yongquiang","email":"","affiliations":[{"id":25513,"text":"USDA Forest Service Southern Research Station","active":true,"usgs":false}],"preferred":false,"id":629691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luce, Charles H.","contributorId":65980,"corporation":false,"usgs":true,"family":"Luce","given":"Charles","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":629692,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170166,"text":"pp1825 - 2016 - Conditions and processes affecting sand resources at archeological sites in the Colorado River corridor below Glen Canyon Dam, Arizona","interactions":[],"lastModifiedDate":"2016-06-24T17:19:42","indexId":"pp1825","displayToPublicDate":"2016-05-17T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1825","title":"Conditions and processes affecting sand resources at archeological sites in the Colorado River corridor below Glen Canyon Dam, Arizona","docAbstract":"This study examined links among fluvial, aeolian, and hillslope geomorphic processes that affect archeological sites and surrounding landscapes in the Colorado River corridor downstream from Glen Canyon Dam, Arizona. We assessed the potential for Colorado River sediment to enhance the preservation of river-corridor archeological resources through aeolian sand deposition or mitigation of gully erosion. By identifying locally prevailing wind directions, locations of modern sandbars, and likely aeolian-transport barriers, we determined that relatively few archeological sites are now ideally situated to receive aeolian sand supply from sandbars deposited by recent controlled floods. Whereas three-fourths of the 358 river-corridor archeological sites we examined include Colorado River sediment as an integral component of their geomorphic context, only 32 sites currently appear to have a high degree of connectivity (coupled interactions) between modern fluvial sandbars and sand-dominated landscapes downwind. This represents a substantial decrease from past decades, as determined by aerial-photograph analysis. Thus, we infer that recent controlled floods have had a limited, and declining, influence on archeological-site preservation.
\nWithin the study area, overland-flow (gully) erosion is less severe in sand landscapes with active aeolian sand than in landscapes that lack aeolian transport; gullies terminate more commonly in active sand (sand that is mobile by wind rather than stabilized by biologic soil crust). We infer that these characteristics largely result from aeolian sand transport being an effective gully-limiting and gully-annealing mechanism. Aeolian sand activity in the river corridor varies substantially as a function of reach morphology and dominant wind direction relative to the river-corridor orientation, factors that control accommodation space for river-derived sand and the modern sand supply to aeolian dunes. These attributes, together with an inverse correlation between aeolian sand activity and gully occurrence, define varying degrees of net long-term gully-erosion risk for sediment deposits and associated archeological sites in different regions of the river corridor. Over most of the river corridor, including some of the archeologically richest regions, sand is too inactive with respect to aeolian transport to anneal gullies effectively. At eight selected archeological sites that we studied with high-resolution terrestrial lidar scans for more than a year, sand loss by overland flow (gully erosion) and aeolian deflation generally exceeded deposition, such that erosion dominated over most monitoring intervals—even at four sites with strong connectivity to modern sand supply.
\nThe Glen Canyon reach of the river corridor appears especially vulnerable to gully erosion. Among the sites that we monitored in detail, erosion generally dominated over deposition to a greater degree at four Glen Canyon sites with no modern sand supply than at four Marble–Grand Canyon sites with aeolian sand supply from controlled-flood sandbars. Although gross annual-scale erosion rates were similar among the Glen Canyon sites and among the Marble–Grand Canyon sites, a relative lack of depositional processes led to greater net erosion at the Glen Canyon sites. Having found no differences in weather patterns to suggest greater erosive forcing in Glen Canyon, and no conclusively influential differences in the slope or watershed area contributing to gully formation, we attribute the greater erosion at the Glen Canyon sites to a combination of inherent geomorphic context (high terraces that do not receive modern sediment supply) and pronounced effects of postdam sediment-supply limitation.
\nWe conclude that most of the river-corridor archeological sites are at elevated risk of net erosion under present dam operations. In the present flow regime, controlled floods do not simulate the magnitude or frequency of natural floods, and are not large enough to deposit sand at elevations that were flooded at annual to decadal intervals in predam time. For archeological sites that depend upon river-derived sand, we infer elevated erosion risk owing to a combination of reduced sand supply (both fluvial and aeolian) through (1) the lower-than-natural flood magnitude, frequency, and sediment supply of the controlled-flooding protocol; (2) reduction of open, dry sand area available for wind redistribution under current normal (nonflood) dam operations, which do not include flows as low as natural seasonal low flows and do include substantial daily flow fluctuations; and (3) impeded aeolian sand entrainment and transport owing to increased riparian vegetation growth in the absence of larger, more-frequent floods. If dam operations were to increase the supply of sand available for windblown transport—for example, through larger floods, sediment augmentation, or increased fluvial sandbar exposure by low flows—and also decrease riparian vegetation, the prevalence of active aeolian sand could increase over time, and the propensity for unmitigated gully erosion could decrease. Although the evolution of river-corridor landscapes and archeological sites has been altered fundamentally by the lack of large, sediment-rich floods (flows on the order of 5,000 m3/s), some combination of sediment-rich flows above 1,270 m3/s, seasonal flows below 226 m3/s, and riparian-vegetation removal might increase the preservation potential for sand-dependent archeological resources in the Colorado River corridor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1825","usgsCitation":"East, A.E., Collins, B.D., Sankey, J.B., Corbett, S.C., Fairley, H.C., and Caster, J., 2016, Conditions and processes affecting sand resources at archeological sites in the Colorado River corridor below Glen Canyon Dam, Arizona: U.S. Geological Survey Professional Paper 1825, 104 p., https://dx.doi.org/10.3133/pp1825.","productDescription":"ix, 104 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066266","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":321261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1825/coverthb.jpg"},{"id":321262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1825/pp1825.pdf","text":"Report","size":"30.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP1825"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River corridor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.555,\n 37.05\n ],\n [\n -114.555,\n 35.45\n ],\n [\n -110.75,\n 35.45\n ],\n [\n -110.75,\n 37.05\n ],\n [\n -114.555,\n 37.05\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL) was extensively modified to increase the spatial sampling density and to improve performance in water ranging from 3 to 44 meters (m). The new (EAARL-B) sensor features a higher spatial density that was achieved by optically splitting each laser pulse into three pulses spatially separated by 1.6 m along the flight track and 2.0 m across the flight track, on the water surface when flown at a nominal altitude of 300 m (984 feet). The sample spacing can be optionally increased to 1.0 m across the flight track. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10 and by designing a new “deep-water” receiver, which is optimized to exclusively receive refracted and scattered light from deeper water (15–44 m).
\nTwo different clear-water flight missions were conducted over the U.S. Navy's South Florida Testing Facility (SFTF) to determine the EAARL-B calibration coefficients. The SFTF is an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. We used 23 selected polygons at 23 distinct depths to compare a reference dataset from this site to determine EAARL-B calibration constants over the depth range of 6.5 to 34 m.
\nWe also conducted a near-simultaneous single-beam jet-ski-based sonar survey of selected transects ranging from 1 to 33 m depth in the same area. The near-concurrent jet ski data were used to evaluate the EAARL-B performance over the depth range from 0.9 to 10 m. The more timely jet ski data were necessary because the primary reference dataset was 9 years old, and areas shallower than 6.5 m are dominated by shifting sand. We determined the jet ski data were not useful as a calibration reference in water deeper than 10 m due to large uncertainty in the vertical measurement introduced by the lack of any sensor orientation data, that is, for pitch, roll, and heading to correct the measured slant range to a vertical measurement.
\nThe resulting calibrated EAARL-B data were then analyzed and compared with the original reference dataset, the jet-ski-based dataset from the same Fort Lauderdale site, as well as the depth-accuracy requirements of the International Hydrographic Organization (IHO). We do not claim to meet all of the IHO requirements and standards. The IHO minimum depth-accuracy requirements were used as a reference only and we do not address the other IHO requirements such as “ Full Seafloor Search”. Our results show good agreement between the calibrated EAARL-B data and all reference datasets, with results that are within the 95 percent depth accuracy of the IHO Order 1 (a and b) depth-accuracy requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161048","usgsCitation":"Wright, C.W., Kranenburg, C.J., Troche, R.J., Mitchell, R.W., and, Nagle, D.B., 2016, Depth calibration of the experimental advanced airborne research lidar, EAARL-B: U.S. Geological Survey Open-File Report 2016–1048, 23 p., https://dx.doi.org/10.3133/ofr20161048.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061552","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1048/coverthb.jpg"},{"id":320951,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79S1P4S","text":"Data Release"},{"id":320938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1048/ofr20161048.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1048"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
We applied a management strategy evaluation (MSE) model to examine the potential cost-effectiveness of using pheromone-baited trapping along with conventional lampricide treatment to manage invasive sea lamprey. Four pheromone-baited trapping strategies were modeled: (1) stream activation wherein pheromone was applied to existing traps to achieve 10−12 mol/L in-stream concentration, (2) stream activation plus two additional traps downstream with pheromone applied at 2.5 mg/hr (reverse-intercept approach), (3) trap activation wherein pheromone was applied at 10 mg/hr to existing traps, and (4) trap activation and reverse-intercept approach. Each new strategy was applied, with remaining funds applied to conventional lampricide control. Simulating deployment of these hybrid strategies on fourteen Lake Michigan streams resulted in increases of 17 and 11% (strategies 1 and 2) and decreases of 4 and 7% (strategies 3 and 4) of the lakewide mean abundance of adult sea lamprey relative to status quo. MSE revealed performance targets for trap efficacy to guide additional research because results indicate that combining lampricides and high efficacy trapping technologies can reduce sea lamprey abundance on average without increasing control costs.
","language":"English","publisher":"Resource Modeling Association","publisherLocation":"Tempe, AZ","doi":"10.1111/nrm.12096","usgsCitation":"Dawson, H., Jones, M.L., Irwin, B.J., Johnson, N., Wagner, C., and Szymanski, M., 2016, Management strategy evaluation of pheromone-baited trapping techniques to improve management of invasive sea lamprey: Natural Resource Modeling, v. 29, no. 3, p. 448-469, https://doi.org/10.1111/nrm.12096.","startPage":"448","endPage":"469","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064352","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470990,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2027.42/133607","text":"External Repository"},{"id":326443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-17","publicationStatus":"PW","scienceBaseUri":"57aef343e4b0fc09faae03a6","contributors":{"authors":[{"text":"Dawson, Heather","contributorId":96577,"corporation":false,"usgs":true,"family":"Dawson","given":"Heather","affiliations":[{"id":27267,"text":"University of Michigan-Flint","active":true,"usgs":false}],"preferred":false,"id":645330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Michael L.","contributorId":139526,"corporation":false,"usgs":false,"family":"Jones","given":"Michael","email":"","middleInitial":"L.","affiliations":[{"id":6596,"text":"Quantitative Fisheries Center, Department of Fisheries and Wildlife Michigan State University","active":true,"usgs":false}],"preferred":false,"id":645331,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irwin, Brian J. 0000-0002-0666-2641 bjirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-0666-2641","contributorId":4037,"corporation":false,"usgs":true,"family":"Irwin","given":"Brian","email":"bjirwin@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":645332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":645329,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wagner, C. Michael","contributorId":173006,"corporation":false,"usgs":false,"family":"Wagner","given":"C. Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":645333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Szymanski, Melissa","contributorId":173647,"corporation":false,"usgs":false,"family":"Szymanski","given":"Melissa","email":"","affiliations":[{"id":27267,"text":"University of Michigan-Flint","active":true,"usgs":false}],"preferred":false,"id":645334,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170990,"text":"70170990 - 2016 - Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA","interactions":[],"lastModifiedDate":"2018-09-18T10:01:55","indexId":"70170990","displayToPublicDate":"2016-05-17T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA","docAbstract":"Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3− reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He),14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3− and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3− reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3− trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.
","language":"English","publisher":"European Geophysical Society","doi":"10.1016/j.jhydrol.2016.05.018","usgsCitation":"Green, C.T., Jurgens, B.C., Zhang, Y., Starn, J., Singleton, M.J., and Esser, B.K., 2016, Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA: Journal of Hydrology, v. 145, p. 47-55, https://doi.org/10.1016/j.jhydrol.2016.05.018.","productDescription":"9 p.","startPage":"47","endPage":"55","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067486","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.05.018","text":"Publisher Index Page"},{"id":321295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 37\n ],\n [\n -121.5,\n 38\n ],\n [\n -120,\n 38\n ],\n [\n -120,\n 37\n ],\n [\n -121.5,\n 37\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d566fe4b07e28b667f7a0","contributors":{"authors":[{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":629354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yong","contributorId":19029,"corporation":false,"usgs":true,"family":"Zhang","given":"Yong","affiliations":[],"preferred":false,"id":629356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starn, Jeffrey jjstarn@usgs.gov","contributorId":149231,"corporation":false,"usgs":true,"family":"Starn","given":"Jeffrey","email":"jjstarn@usgs.gov","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singleton, Michael J.","contributorId":44400,"corporation":false,"usgs":true,"family":"Singleton","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629358,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Esser, Bradley K.","contributorId":33161,"corporation":false,"usgs":true,"family":"Esser","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":629359,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170871,"text":"ofr20161066 - 2016 - Preliminary investigation of groundwater flow and trichloroethene transport in the Surficial Aquifer System, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota","interactions":[],"lastModifiedDate":"2016-05-18T09:54:58","indexId":"ofr20161066","displayToPublicDate":"2016-05-16T16:00:00","publicationYear":"2016","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":"2016-1066","title":"Preliminary investigation of groundwater flow and trichloroethene transport in the Surficial Aquifer System, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota","docAbstract":"Industrial practices at the Naval Industrial Reserve Ordnance Plant, in Fridley, Minnesota, caused soil and groundwater contamination. Some volatile organic compounds from the plant might have discharged to the Mississippi River, forced by the natural hydraulic gradient in the surficial aquifer system. The U.S. Environmental Protection Agency included the Naval Industrial Reserve Ordnance Plant on the Superfund National Priorities List in 1989.
\nThis report describes a preliminary characterization of trichloroethene transport in the surficial and Cambrian-Ordovician aquifer systems at the Naval Industrial Reserve Ordnance Plant. The characterization first involved simulation of 2001 conditions using a model, followed by an application of this 2001 simulator to 2011 conditions.
\nThe U.S. Geological Survey, in cooperation with the U.S. Department of the Navy, used a steady-state, uniform-density groundwater flow model to simulate measured potentiometric heads in aquifer systems on August 20, 2001, and a single-phase, conservative, non-reactive, miscible transport model to simulate trichloroethene concentrations in aquifer systems measured in 2001. The U.S. Department of the Navy furnished trichloroethene source areas and trichloroethene source area concentrations to the U.S. Geological Survey for this model simulation. Furnished delineations were postulated and informed by data collected from 1995 to 2011. The groundwater flow simulation of August 20, 2001, was superior to the trichloroethene transport simulation at replicating measurements; simulated potentiometric heads matched 90 percent of measured potentiometric heads on August 20, within 2 feet at selected locations whereas simulated trichloroethene concentration contours of 3, 10, 100, 1000, and 10,000 micrograms per liter (µg/L) correctly bounded 52 percent of measured concentrations in 2001 at selected locations. The degree to which the simulated trichloroethene plume does not match trichloroethene measurements in the surficial aquifer system during the 2001 simulation may suggest that furnished trichloroethene source areas and trichloroethene source area concentrations did not accurately represent all trichloroethene sources in the hydrogeologic system.
\nDuring the model simulation of 2001, trichloroethene discharged to the Mississippi River. A simulated 900-foot-long zone of benthic trichloroethene discharge flux existed in the shallow flow zone, across which simulated trichloroethene discharged from the surficial aquifer system to the Mississippi River at simulated trichloroethene concentrations that ranged from 3 µg/L to more than 100 µg/L. The Mississippi River was not sampled for volatile organic compounds in Fridley, Minn., from 1999 to 2016 (the publication of this report). Trichloroethene concentrations were measured in wells close to the Mississippi River in the surficial aquifer system on the downgradient side of the Naval Industrial Reserve Ordnance Plant groundwater flow field; for example, at well MS–43 in the shallow flow zone of the surficial aquifer system 280 feet east of the Mississippi River between December 1999 and August 2012, trichloroethene concentrations ranged from 130 to 220 µg/L. The 220-µg/L maximum concentration was reached in March 2003 and October 2006. The August 2012 concentration was 140 µg/L.
\nThe August 20, 2001, groundwater flow model simulator and the 2001 trichloroethene transport simulator were applied to a groundwater extraction and treatment system that existed in 2011. Furnished trichloroethene source areas and concentrations in the 2001 simulator were replaced with different, furnished, hypothetical source areas and concentrations. Forcing in 2001 was replaced with forcing in 2011. No trichloroethene concentrations greater than 3 µg/L were simulated as discharging to the Mississippi River during applications of the 2001 simulator to the 2011 groundwater extraction and treatment system. These applications were not intended to represent historical conditions. Differences between furnished and actual trichloroethene sources may explain differences between measurements and simulation results for the 2001 trichloroethene transport simulator. Causes of differences between furnished and actual trichloroethene sources may cause differences between hypothetical application results and the performance of the actual U.S. Department of the Navy groundwater extraction and treatment system at the Naval Industrial Reserve Ordnance Plant. Other limitations may also cause differences between application results and performance.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161066","collaboration":"Prepared in cooperation with the U.S. Department of the Navy, Naval Facilities Engineering Command","usgsCitation":"King, J.N., and Davis, J.H., 2016, Preliminary investigation of groundwater flow and trichloroethene transport in the surficial aquifer system, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota: U.S. Geological Survey Open File Report 2016–1066, 120 p., https://dx.doi.org/10.3133/ofr20161066.","productDescription":"Report: x, 120 p.; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-039553","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":321042,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F798853M","text":"Data Release","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1066"},{"id":321040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1066/coverthb.jpg"},{"id":321041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1066/ofr20161066.pdf","text":"Report","size":"12,1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1066"}],"country":"United States","state":"Minnesota","city":"Fridley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.38172912597656,\n 45.09582203415993\n ],\n [\n -93.34877014160155,\n 45.03228854011639\n ],\n [\n -93.27735900878906,\n 45.02986219868277\n ],\n [\n -92.96905517578125,\n 45.180584858570136\n ],\n [\n -93.043212890625,\n 45.25652199219273\n ],\n [\n -93.38172912597656,\n 45.09582203415993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
(763) 783-3100
http://mn.water.usgs.gov/
Several lines of earthquake evidence indicate that the lithospheric plate is broken under the load of the island of Hawai`i, where the geometry of the lithosphere is circular with a central depression. The plate bends concave downward surrounding a stress-free hole, rather than bending concave upward as with past assumptions. Earthquake focal mechanisms show that the center of load stress and the weak hole is between the summits of Mauna Loa and Mauna Kea where the load is greatest. The earthquake gap at 21 km depth coincides with the predicted neutral plane of flexure where horizontal stress changes sign. Focal mechanism P axes below the neutral plane display a striking radial pattern pointing to the stress center. Earthquakes above the neutral plane in the north part of the island have opposite stress patterns; T axes tend to be radial. The M6.2 Honomu and M6.7 Kiholo main shocks (both at 39 km depth) are below the neutral plane and show radial compression, and the M6.0 Kiholo aftershock above the neutral plane has tangential compression. Earthquakes deeper than 20 km define a donut of seismicity around the stress center where flexural bending is a maximum. The hole is interpreted as the soft center where the lithospheric plate is broken. Kilauea's deep conduit is seismically active because it is in the ring of maximum bending. A simplified two-dimensional stress model for a bending slab with a load at one end yields stress orientations that agree with earthquake stress axes and radial P axes below the neutral plane. A previous inversion of deep Hawaiian focal mechanisms found a circular solution around the stress center that agrees with the model. For horizontal faults, the shear stress within the bending slab matches the slip in the deep Kilauea seismic zone and enhances outward slip of active flanks.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JB012746","usgsCitation":"Klein, F.W., 2016, Lithospheric flexure under the Hawaiian volcanic load: Internal stresses and a broken plate revealed by earthquakes: Journal of Geophysical Research B: Solid Earth, v. 121, no. 4, p. 2400-2428, https://doi.org/10.1002/2015JB012746.","productDescription":"29 p.","startPage":"2400","endPage":"2428","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070787","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470994,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012746","text":"Publisher Index Page"},{"id":321234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.08551025390625,\n 18.890695349102117\n ],\n [\n -156.08551025390625,\n 20.2982655686933\n ],\n [\n -154.78912353515625,\n 20.2982655686933\n ],\n [\n -154.78912353515625,\n 18.890695349102117\n ],\n [\n -156.08551025390625,\n 18.890695349102117\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-08","publicationStatus":"PW","scienceBaseUri":"574d5667e4b07e28b667f77b","contributors":{"authors":[{"text":"Klein, Fred W. klein@usgs.gov","contributorId":4417,"corporation":false,"usgs":true,"family":"Klein","given":"Fred","email":"klein@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":629311,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170981,"text":"70170981 - 2016 - Wind energy development: Methods for assessing risks to birds and bats pre-construction","interactions":[],"lastModifiedDate":"2020-12-21T15:09:19.820867","indexId":"70170981","displayToPublicDate":"2016-05-16T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Wind energy development: Methods for assessing risks to birds and bats pre-construction","docAbstract":"Wind power generation is rapidly expanding. Although wind power is a low-carbon source of energy, it can impact negatively birds and bats, either directly through fatality or indirectly by displacement or habitat loss. Pre-construction risk assessment at wind facilities within the United States is usually required only on public lands. When conducted, it generally involves a 3-tier process, with each step leading to more detailed and rigorous surveys. Preliminary site assessment (U.S. Fish and Wildlife Service, Tier 1) is usually conducted remotely and involves evaluation of existing databases and published materials. If potentially at-risk wildlife are present and the developer wishes to continue the development process, then on-site surveys are conducted (Tier 2) to verify the presence of those species and to assess site-specific features (e.g., topography, land cover) that may influence risk from turbines. The next step in the process (Tier 3) involves quantitative or scientific studies to assess the potential risk of the proposed project to wildlife. Typical Tier-3 research may involve acoustic, aural, observational, radar, capture, tracking, or modeling studies, all designed to understand details of risk to specific species or groups of species at the given site. Our review highlights several features lacking from many risk assessments, particularly the paucity of before-and-after-control- impact (BACI) studies involving modeling and a lack of understanding of cumulative effects of wind facilities on wildlife. Both are essential to understand effective designs for pre-construction monitoring and both would help expand risk assessment beyond eagles.
","language":"English","publisher":"Berryman Institute","doi":"10.26077/phxc-zh11","usgsCitation":"Katzner, T., Bennett, V., Miller, T., Duerr, A.E., Braham, M., and Hale, A., 2016, Wind energy development: Methods for assessing risks to birds and bats pre-construction: Human-Wildlife Interactions, v. 10, no. 1, p. 42-52, https://doi.org/10.26077/phxc-zh11.","productDescription":"11 p.","startPage":"42","endPage":"52","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063881","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"574d567fe4b07e28b667f7bf","contributors":{"authors":[{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":629316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, Victoria","contributorId":169316,"corporation":false,"usgs":false,"family":"Bennett","given":"Victoria","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":629317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Tricia A.","contributorId":64790,"corporation":false,"usgs":true,"family":"Miller","given":"Tricia A.","affiliations":[],"preferred":false,"id":629318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duerr, Adam E.","contributorId":102324,"corporation":false,"usgs":true,"family":"Duerr","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":629319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Braham, Melissa A.","contributorId":140127,"corporation":false,"usgs":false,"family":"Braham","given":"Melissa A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":629320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hale, Amanda","contributorId":169317,"corporation":false,"usgs":false,"family":"Hale","given":"Amanda","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":629321,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171015,"text":"70171015 - 2016 - Exotic plant infestation is associated with decreased modularity and increased numbers of connectors in mixed-grass prairie pollination networks","interactions":[],"lastModifiedDate":"2016-05-17T10:22:01","indexId":"70171015","displayToPublicDate":"2016-05-16T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Exotic plant infestation is associated with decreased modularity and increased numbers of connectors in mixed-grass prairie pollination networks","docAbstract":"The majority of pollinating insects are generalists whose lifetimes overlap flowering periods of many potentially suitable plant species. Such generality is instrumental in allowing exotic plant species to invade pollination networks. The particulars of how existing networks change in response to an invasive plant over the course of its phenology are not well characterized, but may shed light on the probability of long-term effects on plant-pollinator interactions and the stability of network structure. Here we describe changes in network topology and modular structure of infested and non-infested networks during the flowering season of the generalist non-native flowering plant, Cirsium arvense in mixed-grass prairie at Badlands National Park, South Dakota, USA. Objectives were to compare network-level effects of infestation as they propagate over the season in infested and non-infested (with respect to C. arvense) networks. We characterized plant-pollinator networks on 5 non-infested and 7 infested 1-ha plots during 4 sample periods that collectively covered the length of C. arvense flowering period. Two other abundantly-flowering invasive plants were present during this time: Melilotus officinalis had highly variable floral abundance in both C. arvense-infested and non-infested plots andConvolvulus arvensis, which occurred almost exclusively in infested plots and peaked early in the season. Modularity, including roles of individual species, and network topology were assessed for each sample period as well as in pooled infested and non-infested networks. Differences in modularity and network metrics between infested and non-infested networks were limited to the third and fourth sample periods, during flower senescence of C. arvenseand the other invasive species; generality of pollinators rose concurrently, suggesting rewiring of the network and a lag effect of earlier floral abundance. Modularity was lower and number of connectors higher in infested networks, whether they were assessed in individual sample periods or pooled into infested and non-infested networks over the entire blooming period of C.arvense. Connectors typically did not reside within the same modules as C. arvense, suggesting that effects of the other invasive plants may also influence the modularity results, and that effects of infestation extend to co-flowering native plants. We conclude that the presence of abundantly flowering invasive species is associated with greater network stability due to decreased modularity, but whether this is advantageous for the associated native plant-pollinator communities depends on the nature of perturbations they experience.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0155068","usgsCitation":"Larson, D.L., Rabie, P.A., Droege, S., Larson, J.L., and Haar, M., 2016, Exotic plant infestation is associated with decreased modularity and increased numbers of connectors in mixed-grass prairie pollination networks: PLoS ONE, v. 11, no. 5, p. 1-18, https://doi.org/10.1371/journal.pone.0155068.","productDescription":"18 p.","startPage":"1","endPage":"18","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069178","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0155068","text":"Publisher Index Page"},{"id":321287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-16","publicationStatus":"PW","scienceBaseUri":"574d565ee4b07e28b667f764","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":2120,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":629541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rabie, Paul A. 0000-0003-4364-2268","orcid":"https://orcid.org/0000-0003-4364-2268","contributorId":74328,"corporation":false,"usgs":true,"family":"Rabie","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":true,"id":629542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Droege, Sam sdroege@usgs.gov","contributorId":3464,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","email":"sdroege@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":629543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, Jennifer L. 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":68144,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":629544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haar, Milton","contributorId":14302,"corporation":false,"usgs":true,"family":"Haar","given":"Milton","email":"","affiliations":[],"preferred":false,"id":629545,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199499,"text":"70199499 - 2016 - Calorific value and compositional ultimate analysis with a case study of a Texas lignite","interactions":[],"lastModifiedDate":"2018-09-20T10:52:43","indexId":"70199499","displayToPublicDate":"2016-05-15T10:52:21","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Calorific value and compositional ultimate analysis with a case study of a Texas lignite","docAbstract":"Measurements to determine coal quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an adequate modeling already described in a previous publication for the case of proximate analysis data.1 Here we model the results of calorific value and ultimate analysis. We propose to use two different binary partitions, one per analysis, map the corresponding isometric logratio transformations, and backtransform the results. The methodology is illustrated using the same coal bed in the previous paper modeling proximate analysis data. Results are summarized using probability maps that, in the case of this deposit, show a prominent channel crossing the deposit and separating the best quality coal from that of lower quality.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2016.05.005","usgsCitation":"Olea, R., Luppens, J., Egozcue, J.J., and Pawlowsky-Glahn, V., 2016, Calorific value and compositional ultimate analysis with a case study of a Texas lignite: International Journal of Coal Geology, v. 162, p. 27-33, https://doi.org/10.1016/j.coal.2016.05.005.","productDescription":"7 p.","startPage":"27","endPage":"33","ipdsId":"IP-071169","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357542,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"162","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc0335ae4b0fc368eb53a80","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":120616,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luppens, James 0000-0001-7607-8750","orcid":"https://orcid.org/0000-0001-7607-8750","contributorId":208009,"corporation":false,"usgs":true,"family":"Luppens","given":"James","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Egozcue, Juan J.","contributorId":208010,"corporation":false,"usgs":false,"family":"Egozcue","given":"Juan","email":"","middleInitial":"J.","affiliations":[{"id":37677,"text":"Dept. Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona, Spain","active":true,"usgs":false}],"preferred":false,"id":745596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pawlowsky-Glahn, Vera","contributorId":208011,"corporation":false,"usgs":false,"family":"Pawlowsky-Glahn","given":"Vera","email":"","affiliations":[{"id":37678,"text":"Dept. Informatics, Applied Matematics and Statistics, Universitat de Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":745597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191097,"text":"70191097 - 2016 - Fluvial erosion as a mechanism for crater modification on Titan","interactions":[],"lastModifiedDate":"2017-09-26T13:48:41","indexId":"70191097","displayToPublicDate":"2016-05-15T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial erosion as a mechanism for crater modification on Titan","docAbstract":"There are few identifiable impact craters on Titan, especially in the polar regions. One explanation for this observation is that the craters are being destroyed through fluvial processes, such as weathering, mass wasting, fluvial incision and deposition. In this work, we use a landscape evolution model to determine whether or not this is a viable mechanism for crater destruction on Titan. We find that fluvial degradation can modify craters to the point where they would be unrecognizable by an orbiting spacecraft such as Cassini, given enough time and a large enough erosion rate. A difference in the erosion rate between the equator and the poles of a factor of a few could explain the latitudinal variation in Titan’s crater population. Fluvial erosion also removes central peaks and fills in central pits, possibly explaining their infrequent occurrence in Titan craters. Although many craters on Titan appear to be modified by aeolian infilling, fluvial modification is necessary to explain the observed impact crater morphologies. Thus, it is an important secondary modification process even in Titan’s drier equatorial regions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2015.07.022","usgsCitation":"Neish, C.D., Molaro, J.L., Lora, J.M., Howard, A., Kirk, R.L., Schenk, P., Bray, V., and Lorenz, R.D., 2016, Fluvial erosion as a mechanism for crater modification on Titan: Icarus, v. 270, p. 114-129, https://doi.org/10.1016/j.icarus.2015.07.022.","productDescription":"16 p.","startPage":"114","endPage":"129","ipdsId":"IP-079697","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":346097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"270","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59cb6733e4b017cf3141c69e","contributors":{"authors":[{"text":"Neish, Catherine D.","contributorId":13355,"corporation":false,"usgs":true,"family":"Neish","given":"Catherine","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molaro, J. L.","contributorId":196706,"corporation":false,"usgs":false,"family":"Molaro","given":"J.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":711185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lora, J. M.","contributorId":196707,"corporation":false,"usgs":false,"family":"Lora","given":"J.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":711186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howard, A.D.","contributorId":95538,"corporation":false,"usgs":true,"family":"Howard","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":711187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirk, Randolph L. 0000-0003-0842-9226 rkirk@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-9226","contributorId":2765,"corporation":false,"usgs":true,"family":"Kirk","given":"Randolph","email":"rkirk@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":711188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schenk, P.","contributorId":105484,"corporation":false,"usgs":true,"family":"Schenk","given":"P.","affiliations":[],"preferred":false,"id":711189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bray, V.J.","contributorId":72692,"corporation":false,"usgs":true,"family":"Bray","given":"V.J.","email":"","affiliations":[],"preferred":false,"id":711190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lorenz, R. D.","contributorId":90441,"corporation":false,"usgs":false,"family":"Lorenz","given":"R.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":711191,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70176281,"text":"70176281 - 2016 - Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","interactions":[],"lastModifiedDate":"2016-09-07T12:00:19","indexId":"70176281","displayToPublicDate":"2016-05-14T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns","docAbstract":"The export of nitrogen (N), phosphorus (P), and suspended sediment (SS) is a long-standing management concern for the Chesapeake Bay watershed, USA. Here we present a comprehensive evaluation of nutrient and sediment loads over the last three decades at multiple locations in the Susquehanna River basin (SRB), Chesapeake's largest tributary watershed. Sediment and nutrient riverine loadings, including both dissolved and particulate fractions, have generally declined at all sites upstream of Conowingo Dam (non-tidal SRB outlet). Period-of-record declines in riverine yield are generally smaller than those in source input, suggesting the possibility of legacy contributions. Consistent with other watershed studies, these results reinforce the importance of considering lag time between the implementation of management actions and achievement of river quality improvement. Whereas flow-normalized loadings for particulate species have increased recently below Conowingo Reservoir, those for upstream sites have declined, thus substantiating conclusions from prior studies about decreased reservoir trapping efficiency. In regard to streamflow effects, statistically significant log-linear relationships between annual streamflow and annual constituent load suggest the dominance of hydrological control on the inter-annual variability of constituent export. Concentration-discharge relationships revealed general chemostasis and mobilization effects for dissolved and particulate species, respectively, both suggesting transport-limitation conditions. In addition to affecting annual export rates, streamflow has also modulated the relative importance of dissolved and particulate fractions, as reflected by its negative correlations with dissolved P/total P, dissolved N/total N, particulate P/SS, and total N/total P ratios. For land-use effects, period-of-record median annual yields of N, P, and SS all correlate positively with the area fraction of non-forested land but negatively with that of forested land under all hydrological conditions. Overall, this work has informed understanding with respect to four major factors affecting constituent export (i.e., source input, reservoir modulation, streamflow, and land use) and demonstrated the value of long-term river monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.104","usgsCitation":"Zhang, Q., Ball, W.P., and Moyer, D.L., 2016, Decadal-scale export of nitrogen, phosphorus, and sediment from the Susquehanna River basin, USA: Analysis and synthesis of temporal and spatial patterns: Science of the Total Environment, v. 563-564, p. 1016-1029, https://doi.org/10.1016/j.scitotenv.2016.03.104.","productDescription":"14 p.","startPage":"1016","endPage":"1029","ipdsId":"IP-070367","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":471000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.104","text":"Publisher Index Page"},{"id":328310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Pennsylvania","otherGeospatial":"Chesapeake Bay, Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.51953125,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 42.309815415686664\n ],\n [\n -75.73974609375,\n 39.30029918615029\n ],\n [\n -77.51953125,\n 39.30029918615029\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"563-564","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a39e4b0571647cf8dbb","contributors":{"authors":[{"text":"Zhang, Qian 0000-0003-0500-5655","orcid":"https://orcid.org/0000-0003-0500-5655","contributorId":174393,"corporation":false,"usgs":false,"family":"Zhang","given":"Qian","email":"","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":648192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, William P.","contributorId":174394,"corporation":false,"usgs":false,"family":"Ball","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":27446,"text":"Johns Hopkins University, Department of Geography and Environmental Engineering","active":true,"usgs":false}],"preferred":false,"id":648193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moyer, Douglas L. 0000-0001-6330-478X dlmoyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6330-478X","contributorId":174389,"corporation":false,"usgs":true,"family":"Moyer","given":"Douglas","email":"dlmoyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":648191,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175345,"text":"70175345 - 2016 - Linkages between unpaved forest roads and streambed sediment: why context matters in directing road restoration","interactions":[],"lastModifiedDate":"2016-09-16T16:28:55","indexId":"70175345","displayToPublicDate":"2016-05-13T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Linkages between unpaved forest roads and streambed sediment: why context matters in directing road restoration","docAbstract":"Unpaved forest roads remain a pervasive disturbance on public lands and mitigating sediment from road networks remains a priority for management agencies. Restoring roaded landscapes is becoming increasingly important for many native coldwater fishes that disproportionately rely on public lands for persistence. However, effectively targeting restoration opportunities requires a comprehensive understanding of the effects of roads across different ecosystems. Here, we combine a review and a field study to evaluate the status of knowledge supporting the conceptual framework linking unpaved forest roads with streambed sediment. Through our review, we specifically focused on those studies linking measures of the density of forest roads or sediment delivery with empirical streambed sediment measures. Our field study provides an example of a targeted effort of linking spatially explicit estimates of sediment production with measures of streambed sediment. Surprisingly, our review uncovered few studies (n = 8) that empirically tested the conceptual framework linking unpaved forest roads and streambed sediment, and the results varied considerably. Field results generally supported the conceptual model that unpaved forest roads can control streambed sediment quality, but demonstrated high-spatial variability in the effects of forest roads on streambed sediment and the need to address hotspots of sediment sources. The importance of context in the effects of forest roads is apparent in both our review and field data, suggesting the need for in situ studies to avoid misdirected restoration actions.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12365","collaboration":"USDA Forest Service, The Wilderness Society, Clearwater Resource Council","usgsCitation":"Al-Chokhachy, R.K., Black, T.A., Thomas, C., Luce, C.H., Rieman, B., Cissel, R., Carlson, A., Hendrickson, S., Archer, E.K., and Kershner, J.L., 2016, Linkages between unpaved forest roads and streambed sediment: why context matters in directing road restoration: Restoration Ecology, v. 24, no. 5, p. 589-598, https://doi.org/10.1111/rec.12365.","productDescription":"10 p.","startPage":"589","endPage":"598","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072870","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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SC","active":true,"usgs":false}],"preferred":false,"id":644806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Luce, Charlie H.","contributorId":173471,"corporation":false,"usgs":false,"family":"Luce","given":"Charlie","email":"","middleInitial":"H.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":644807,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rieman, Bruce","contributorId":101140,"corporation":false,"usgs":true,"family":"Rieman","given":"Bruce","affiliations":[],"preferred":false,"id":644808,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cissel, Richard","contributorId":173472,"corporation":false,"usgs":false,"family":"Cissel","given":"Richard","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":644809,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carlson, Anne","contributorId":173473,"corporation":false,"usgs":false,"family":"Carlson","given":"Anne","email":"","affiliations":[{"id":27234,"text":"The Wilderness Society","active":true,"usgs":false}],"preferred":false,"id":644810,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hendrickson, Shane","contributorId":173474,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Shane","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":644811,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Archer, Eric K.","contributorId":173475,"corporation":false,"usgs":false,"family":"Archer","given":"Eric","email":"","middleInitial":"K.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":644812,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644813,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70170966,"text":"70170966 - 2016 - Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA)","interactions":[],"lastModifiedDate":"2016-05-13T13:39:46","indexId":"70170966","displayToPublicDate":"2016-05-13T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA)","docAbstract":"Sugar maple (Acer saccharum) is among the most ecologically and economically important tree species in North America, and its growth and regeneration is often the focus of silvicultural practices in northern hardwood forests. A key stressor for sugar maple (SM) is acid rain, which depletes base cations from poorly-buffered forest soils and has been associated with much lower SM vigor, growth, and recruitment. However, the potential interactions between forest management and soil acidification – and their implications for the sustainability of SM and its economic and cultural benefits – have not been investigated. In this study, we simulated the development of 50 extant SM stands in the western Adirondack region of NY (USA) for 100 years under different soil chemical conditions and silvicultural prescriptions. We found that interactions between management prescription and soil base saturation will strongly shape the ability to maintain SM in managed forests. Below 12% base saturation, SM did not regenerate sufficiently after harvest and was replaced mainly by red maple (Acer rubrum) and American beech (Fagus grandifolia). Loss of SM on acid-impaired sites was predicted regardless of whether the shelterwood or diameter-limit prescriptions were used. On soils with sufficient base saturation, models predicted that SM will regenerate after harvest and be sustained for future rotations. We then estimated how these different post-harvest outcomes, mediated by acid impairment of forest soils, would affect the potential monetary value of ecosystem services provided by SM forests. Model simulations indicated that a management strategy focused on syrup production – although not feasible across the vast areas where acid impairment has occurred – may generate the greatest economic return. Although pollution from acid rain is declining, its long-term legacy in forest soils will shape future options for sustainable forestry and ecosystem stewardship in the northern hardwood forests of North America.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2016.04.008","collaboration":"New York State Energy Research and Development Authority; USGS","usgsCitation":"Caputo, J., Beier, C.M., Sullivan, T.J., and Lawrence, G.B., 2016, Modeled effects of soil acidification on long-term ecological and economic outcomes for managed forests in the Adirondack region (USA): Science of the Total Environment, v. 565, p. 401-411, https://doi.org/10.1016/j.scitotenv.2016.04.008.","productDescription":"11 p.","startPage":"401","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073095","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471002,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.04.008","text":"Publisher Index 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Jesse","contributorId":169306,"corporation":false,"usgs":false,"family":"Caputo","given":"Jesse","email":"","affiliations":[{"id":24722,"text":"Graduate Student, SUNY College of Environmental Science & Forestry","active":true,"usgs":false}],"preferred":false,"id":629268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beier, Colin M.","contributorId":17107,"corporation":false,"usgs":true,"family":"Beier","given":"Colin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":629269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Timothy J.","contributorId":77812,"corporation":false,"usgs":true,"family":"Sullivan","given":"Timothy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":629270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629267,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170756,"text":"70170756 - 2016 - Reply to comments by Riley and Dunlop on He et al. (2015)","interactions":[],"lastModifiedDate":"2016-05-12T10:13:47","indexId":"70170756","displayToPublicDate":"2016-05-12T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Reply to comments by Riley and Dunlop on He et al. (2015)","docAbstract":"He et al. (2015) described piscivory patterns in the main basin of Lake Huron 1984-2010, during which there was also a pattern of stepwise declines in the abundance of dominant prey fish species. The approach of He et al. (2015) was to couple age-structured stock assessment and fish bioenergetics models to estimate prey fish consumption, and to compare these patterns with prey fish biomass from a bottom trawl survey. Riley and Dunlop (2015) were highly critical of the methods and conclusions reached by He et al. (2015). They claimed that we incorrectly interpreted the bottom trawl survey data, and did not account for uncertainty. We respond to these and other criticisms below, which we find do not undermine our findings.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0522","usgsCitation":"Bence, J., Madenjian, C.P., He, J.X., Fielder, D.G., Pothoven, S.A., Dobiesz, N.E., Johnson, J.E., Ebener, M.P., Cottrill, R.A., Mohr, L.C., and Koproski, S.R., 2016, Reply to comments by Riley and Dunlop on He et al. (2015): Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 5, p. 865-868, https://doi.org/10.1139/cjfas-2015-0522.","productDescription":"4 p.","startPage":"865","endPage":"868","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070920","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":321175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57359b1ce4b0dae0d5dee781","contributors":{"authors":[{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":628282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madenjian, Charles P. 0000-0002-0326-164X cmadenjian@usgs.gov","orcid":"https://orcid.org/0000-0002-0326-164X","contributorId":2200,"corporation":false,"usgs":true,"family":"Madenjian","given":"Charles","email":"cmadenjian@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":628281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"He, Ji X.","contributorId":53254,"corporation":false,"usgs":true,"family":"He","given":"Ji","email":"","middleInitial":"X.","affiliations":[],"preferred":false,"id":628283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fielder, David G.","contributorId":127528,"corporation":false,"usgs":false,"family":"Fielder","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":628284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":628285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dobiesz, Norine E.","contributorId":75115,"corporation":false,"usgs":false,"family":"Dobiesz","given":"Norine","email":"","middleInitial":"E.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":628286,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, James E.","contributorId":45668,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":628287,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ebener, Mark P.","contributorId":25099,"corporation":false,"usgs":false,"family":"Ebener","given":"Mark","email":"","middleInitial":"P.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":628288,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cottrill, R. Adam","contributorId":169047,"corporation":false,"usgs":false,"family":"Cottrill","given":"R.","email":"","middleInitial":"Adam","affiliations":[{"id":6780,"text":"Ontario Ministry of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":628289,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mohr, Lloyd C.","contributorId":77493,"corporation":false,"usgs":false,"family":"Mohr","given":"Lloyd","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":628290,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Koproski, Scott R.","contributorId":138499,"corporation":false,"usgs":false,"family":"Koproski","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":628291,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70238510,"text":"70238510 - 2016 - Survival of translocated sharp-tailed grouse: Temporal threshold and age effects","interactions":[],"lastModifiedDate":"2022-11-28T14:13:14.953943","indexId":"70238510","displayToPublicDate":"2016-05-12T08:08:42","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Survival of translocated sharp-tailed grouse: Temporal threshold and age effects","docAbstract":"Context: The Columbian sharp-tailed grouse (Tympanuchus phasianellus columbianus) is a subspecies of conservation concern in the western United States, currently occupying ≤10% of its historic range. Land and management agencies are employing translocation techniques to restore Columbian sharp-tailed grouse (CSTG) populations. However, establishing self-sustaining populations by translocating grouse often is unsuccessful, owing, in part, to low survivorship of translocated grouse following release.
Aims: We measured and modelled patterns of CSTG mortality for 150 days following translocation into historic range, to better understand patterns and causes of success or failure in conservation efforts to re-establish grouse populations.
Methods: We conducted two independent multi-year translocations and evaluated individual and temporal factors associated with CSTG survival up to 150 days following their release. Both translocations were reintroduction attempts in Nevada, USA, to establish viable populations of CSTG into their historic range.
Key results: We observed a clear temporal threshold in survival probability, with CSTG mortality substantially higher during the first 50 days following release than during the subsequent 100 days. Additionally, translocated yearling grouse exhibited higher overall survival (0.669 ± 0.062) than did adults (0.420 ± 0.052) across the 150-day period and higher survival than adults both before and after the 50-day temporal threshold.
Conclusions: Translocated CSTG are especially vulnerable to mortality for 50 days following release, whereas translocated yearling grouse are more resistant to mortality than are adult grouse. On the basis of the likelihood of survival, yearling CSTG are better candidates for population restoration through translocation than are adult grouse.
Implications: Management actions that ameliorate mortality factors for 50 days following translocation and translocations that employ yearling grouse will increase the likelihood of population establishment.
","language":"English","publisher":"CSIRO","doi":"10.1071/WR15158","usgsCitation":"Mathews, S.R., Coates, P.S., and Delehanty, D.J., 2016, Survival of translocated sharp-tailed grouse: Temporal threshold and age effects: Wildlife Research, v. 76, p. 220-227, https://doi.org/10.1071/WR15158.","productDescription":"8 p.","startPage":"220","endPage":"227","ipdsId":"IP-123166","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":471005,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr15158","text":"Publisher Index Page"},{"id":409691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Nevada","otherGeospatial":"Bull Run release site, Snake Mountains release site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.67565479843591,\n 42.00580017615141\n ],\n [\n -112.67565479843591,\n 42.488307313013934\n ],\n [\n -113.4597271559782,\n 42.488307313013934\n ],\n [\n -113.4597271559782,\n 42.00580017615141\n ],\n [\n -112.67565479843591,\n 42.00580017615141\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.62435655087742,\n 41.93556552613373\n ],\n [\n -116.62435655087742,\n 41.015476877982934\n ],\n [\n -114.27213947825084,\n 41.015476877982934\n ],\n [\n -114.27213947825084,\n 41.93556552613373\n ],\n [\n -116.62435655087742,\n 41.93556552613373\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"76","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mathews, Steven R. 0000-0002-3165-9460 smathews@usgs.gov","orcid":"https://orcid.org/0000-0002-3165-9460","contributorId":176922,"corporation":false,"usgs":true,"family":"Mathews","given":"Steven","email":"smathews@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":857690,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70174265,"text":"70174265 - 2016 - Latest Miocene-earliest Pliocene evolution of the ancestral Rio Grande at the Española-San Luis Basin boundary, northern New Mexico","interactions":[],"lastModifiedDate":"2016-07-06T17:31:05","indexId":"70174265","displayToPublicDate":"2016-05-12T02:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2860,"text":"New Mexico Geology","active":true,"publicationSubtype":{"id":10}},"title":"Latest Miocene-earliest Pliocene evolution of the ancestral Rio Grande at the Española-San Luis Basin boundary, northern New Mexico","docAbstract":"The Colorado River has been identified as the most overallocated river in the world. Considering predicted future imbalances between water supply and demand and the growing recognition that base flow (a proxy for groundwater discharge to streams) is critical for sustaining flow in streams and rivers, there is a need to develop methods to better quantify present-day base flow across large regions. We adapted and applied the spatially referenced regression on watershed attributes (SPARROW) water quality model to assess the spatial distribution of base flow, the fraction of streamflow supported by base flow, and estimates of and potential processes contributing to the amount of base flow that is lost during in-stream transport in the Upper Colorado River Basin (UCRB). On average, 56% of the streamflow in the UCRB originated as base flow, and precipitation was identified as the dominant driver of spatial variability in base flow at the scale of the UCRB, with the majority of base flow discharge to streams occurring in upper elevation watersheds. The model estimates an average of 1.8 × 1010 m3/yr of base flow in the UCRB; greater than 80% of which is lost during in-stream transport to the Lower Colorado River Basin via processes including evapotranspiration and water diversion for irrigation. Our results indicate that surface waters in the Colorado River Basin are dependent on base flow, and that management approaches that consider groundwater and surface water as a joint resource will be needed to effectively manage current and future water resources in the Basin.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR017963","usgsCitation":"Miller, M.P., Buto, S.G., Susong, D.D., and Rumsey, C., 2016, The importance of base flow in sustaining surface water flow in the Upper Colorado River Basin: Water Resources Research, v. 52, no. 5, p. 3547-3562, https://doi.org/10.1002/2015WR017963.","productDescription":"16 p.","startPage":"3547","endPage":"3562","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068216","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":471007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr017963","text":"Publisher Index Page"},{"id":321122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.357421875,\n 35.88905007936091\n ],\n [\n -111.357421875,\n 43.389081939117496\n ],\n [\n -105.8203125,\n 43.389081939117496\n ],\n [\n -105.8203125,\n 35.88905007936091\n ],\n [\n -111.357421875,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5734499ee4b0dae0d5dd6915","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629146,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Susong, David D. ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rumsey, Christine 0000-0001-7536-750X crumsey@usgs.gov","orcid":"https://orcid.org/0000-0001-7536-750X","contributorId":146240,"corporation":false,"usgs":true,"family":"Rumsey","given":"Christine","email":"crumsey@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629148,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170896,"text":"70170896 - 2016 - Ephemerality of discrete methane vents in lake sediments","interactions":[],"lastModifiedDate":"2016-06-02T11:16:13","indexId":"70170896","displayToPublicDate":"2016-05-11T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Ephemerality of discrete methane vents in lake sediments","docAbstract":"Methane is a potent greenhouse gas whose emission from sediments in inland waters and shallow oceans may both contribute to global warming and be exacerbated by it. The fraction of methane emitted by sediments that bypasses dissolution in the water column and reaches the atmosphere as bubbles depends on the mode and spatiotemporal characteristics of venting from the sediments. Earlier studies have concluded that hot spots—persistent, high-flux vents—dominate the regional ebullitive flux from submerged sediments. Here the spatial structure, persistence, and variability in the intensity of methane venting are analyzed using a high-resolution multibeam sonar record acquired at the bottom of a lake during multiple deployments over a 9 month period. We confirm that ebullition is strongly episodic, with distinct regimes of high flux and low flux largely controlled by changes in hydrostatic pressure. Our analysis shows that the spatial pattern of ebullition becomes homogeneous at the sonar's resolution over time scales of hours (for high-flux periods) or days (for low-flux periods), demonstrating that vents are ephemeral rather than persistent, and suggesting that long-term, lake-wide ebullition dynamics may be modeled without resolving the fine-scale spatial structure of venting.
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