Large-scale coal mining practices, particularly surface coal extraction and associated valley fills as well as residential wastewater discharge, are of ecological concern for aquatic systems in central Appalachia. Identifying and quantifying alterations to ecosystems along a gradient of spatial scales is a necessary first-step to aid in mitigation of negative consequences to aquatic biota. In central Appalachian headwater streams, apart from fish, salamanders are the most abundant vertebrate predator that provide a significant intermediate trophic role linking aquatic and terrestrial food webs. Stream salamander species are considered to be sensitive to aquatic stressors and environmental alterations, as past research has shown linkages among microhabitat parameters, large-scale land use such as urbanization and logging, and salamander abundances. However, there is little information examining these relationships between environmental conditions and salamander occupancy in the coalfields of central Appalachia. In the summer of 2013, 70 sites (sampled two to three times each) in the southwest Virginia coalfields were visited to collect salamanders and quantify stream and riparian microhabitat parameters. Using an information-theoretic framework, effects of microhabitat and large-scale land use on stream salamander occupancy were compared. The findings indicate that Desmognathus spp. occupancy rates are more correlated to microhabitat parameters such as canopy cover than to large-scale land uses. However, Eurycea spp. occupancy rates had a strong association with large-scale land uses, particularly recent mining and forest cover within the watershed. These findings suggest that protection of riparian habitats is an important consideration for maintaining aquatic systems in central Appalachia. If this is not possible, restoration riparian areas should follow guidelines using quick-growing tree species that are native to Appalachian riparian areas. These types of trees would rapidly establish a canopy cover, stabilize the soil, and impede invasive plant species which would, in turn, provide high-quality refuges for stream salamanders.
","language":"English","publisher":"Academic Journals","doi":"10.5897/JENE2016.0564","usgsCitation":"Sweeten, S.E., and Ford, W.M., 2016, Effects of microhabitat and large-scale land use on stream salamander occupancy in the coalfields of Central Appalachia: Journal of Ecology and the Natural Environment, v. 8, no. 9, p. 129-141, https://doi.org/10.5897/JENE2016.0564.","productDescription":"13 p.","startPage":"129","endPage":"141","ipdsId":"IP-065420","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470624,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5897/jene2016.0564","text":"Publisher Index Page"},{"id":340619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"590454a3e4b022cee40dc234","contributors":{"authors":[{"text":"Sweeten, Sara E.","contributorId":191565,"corporation":false,"usgs":false,"family":"Sweeten","given":"Sara","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693092,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170460,"text":"ds987 - 2016 - Groundwater-quality data in the Monterey–Salinas shallow aquifer study unit, 2013: Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2017-01-18T09:45:02","indexId":"ds987","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"987","title":"Groundwater-quality data in the Monterey–Salinas shallow aquifer study unit, 2013: Results from the California GAMA Program","docAbstract":"Groundwater quality in the 3,016-square-mile Monterey–Salinas Shallow Aquifer study unit was investigated by the U.S. Geological Survey (USGS) from October 2012 to May 2013 as part of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment (GAMA) Program’s Priority Basin Project. The GAMA Monterey–Salinas Shallow Aquifer study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the shallow-aquifer systems in parts of Monterey and San Luis Obispo Counties and to facilitate statistically consistent comparisons of untreated-groundwater quality throughout California. The shallow-aquifer system in the Monterey–Salinas Shallow Aquifer study unit was defined as those parts of the aquifer system shallower than the perforated depth intervals of public-supply wells, which generally corresponds to the part of the aquifer system used by domestic wells. Groundwater quality in the shallow aquifers can differ from the quality in the deeper water-bearing zones; shallow groundwater can be more vulnerable to surficial contamination.
Samples were collected from 170 sites that were selected by using a spatially distributed, randomized grid-based method. The study unit was divided into 4 study areas, each study area was divided into grid cells, and 1 well was sampled in each of the 100 grid cells (grid wells). The grid wells were domestic wells or wells with screen depths similar to those in nearby domestic wells. A greater spatial density of data was achieved in 2 of the study areas by dividing grid cells in those study areas into subcells, and in 70 subcells, samples were collected from exterior faucets at sites where there were domestic wells or wells with screen depths similar to those in nearby domestic wells (shallow-well tap sites).
Field water-quality indicators (dissolved oxygen, water temperature, pH, and specific conductance) were measured, and samples for analysis of inorganic constituents (trace elements, nutrients, major and minor ions, silica, total dissolved solids, and alkalinity) were collected at all 170 sites. In addition to these constituents, the samples from grid wells were analyzed for organic constituents (volatile organic compounds, pesticides and pesticide degradates), constituents of special interest (perchlorate and N-nitrosodimethylamine, or NDMA), radioactive constituents (radon-222 and gross-alpha and gross-beta radioactivity), and geochemical and age-dating tracers (stable isotopes of carbon in dissolved inorganic carbon, carbon-14 abundances, stable isotopes of hydrogen and oxygen in water, and tritium activities).
Three types of quality-control samples (blanks, replicates, and matrix spikes) were collected at up to 11 percent of the wells in the Monterey–Salinas Shallow Aquifer study unit, and the results for these samples were used to evaluate the quality of the data from the groundwater samples. With the exception of trace elements, blanks rarely contained detectable concentrations of any constituent, indicating that contamination from sample-collection procedures was not a significant source of bias in the data for the groundwater samples. Low concentrations of some trace elements were detected in blanks; therefore, the data were re-censored at higher reporting levels. Replicate samples generally were within the limits of acceptable analytical reproducibility. The median values of matrix-spike recoveries were within the acceptable range (70 to 130 percent) for the volatile organic compounds (VOCs) and N-nitrosodimethylamine (NDMA), but were only approximately 64 percent for pesticides and pesticide degradates.
The sample-collection protocols used in this study were designed to obtain representative samples of groundwater. The quality of groundwater can differ from the quality of drinking water because water chemistry can change as a result of contact with plumbing systems or the atmosphere; because of treatment, disinfection, or blending with water from other sources; or some combination of these. Water quality in domestic wells is not regulated in California, however, to provide context for the water-quality data presented in this report, results were compared to benchmarks established for drinking-water quality. The primary comparison benchmarks were maximum contaminant levels established by the U.S. Environmental Protection Agency and the State of California (MCL-US and MCL-CA, respectively). Non-regulatory benchmarks were used for constituents without maximum contaminant levels (MCLs), including Health
Based Screening Levels (HBSLs) developed by the USGS and State of California secondary maximum contaminant levels (SMCL-CA) and notification levels. Most constituents detected in samples from the Monterey–Salinas Shallow Aquifer study unit had concentrations less than their respective benchmarks.
Of the 148 organic constituents analyzed in the 100 grid-well samples, 38 were detected, and all concentrations were less than the benchmarks. Volatile organic compounds were detected in 26 of the grid wells, and pesticides and pesticide degradates were detected in 28 grid wells. The special-interest constituent NDMA was detected above the HBSL in three samples, one of which also had a perchlorate concentration greater than the MCL-CA.
Of the inorganic constituents, 6 were detected at concentrations above their respective MCL benchmarks in grid-well samples: arsenic (5 grid wells above the MCL of 10 micrograms per liter, μg/L), selenium (3 grid wells, MCL of 50 μg/L), uranium (4 grid wells, MCL of 30 μg/L), nitrate (16 grid wells, MCL of 10 milligrams per liter, mg/L), adjusted gross alpha particle activity (10 grid wells, MCL of 15 picocuries per liter, pCi/L), and gross beta particle activity (1 grid well, MCL of 50 pCi/L). An additional 4 inorganic constituents were detected at concentrations above their respective HBSL benchmarks in grid-well samples: boron (1 grid well above the HBSL of 6,000 μg/L), manganese (8 grid wells, HBSL of 300 μg/L), molybdenum (6 grid wells, HBSL of 40 μg/L), and strontium (6 grid wells, HBSL of 4,000 μg/L). Of the inorganic constituents, 4 were detected at concentrations above their non-health based SMCL benchmarks in grid-well samples: iron (9 grid wells above the SMCL of 300 μg/L), chloride (7 grid wells, SMCL of 500 mg/L), sulfate (14 grid wells, SMCL of 500 mg/L), and total dissolved solids (27 grid wells, SMCL of 1,000 mg/L).
Of the inorganic constituents analyzed in the 70 shallow-well tap sites, 10 were detected at concentrations above the benchmarks. Of the inorganic constituents, 3 were detected at concentrations above their respective MCL benchmarks in shallow-well tap sites: arsenic (2 shallow-well tap sites above the MCL of 10 μg/L), uranium (2 shallow-well tap sites, MCL of 30 μg/L), and nitrate (24 shallow-well tap sites, MCL of 10 mg/L). An additional 3 inorganic constituents were detected above their respective HBSL benchmarks in shallow-well tap sites: manganese (4 shallow-well tap sites above the HBSL of 300 μg/L), molybdenum (4 shallow-well tap sites, HBSL of 40 μg/L), and zinc (2 shallow-well tap sites, HBSL of 2,000 μg/L). Of the inorganic constituents, 4 were detected at concentrations above their non-health based SMCL benchmarks in shallow-well tap sites: iron (6 shallow-well tap sites above the SMCL of 300 μg/L), chloride (1 shallow-well tap site, SMCL of 500 mg/L), sulfate (9 shallow-well tap sites, SMCL of 500 mg/L), and total dissolved solids (15 shallow-well tap sites, SMCL of 1,000 mg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds987","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Goldrath, D.A., Kulongoski, J.T., and Davis, T.A., 2015, Groundwater-quality data in the Monterey–Salinas shallow aquifer study unit, (ver. 1.1, January 2017): Results from the California GAMA Program: U.S. Geological Survey Data Series 987, 132 p., https://dx.doi.org/10.3133/ds987.","productDescription":"ix, 132 p. ","numberOfPages":"146","onlineOnly":"Y","ipdsId":"IP-049716","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":333267,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/0987/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":328193,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0987/coverthb2.jpg"},{"id":328194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0987/ds0987.pdf","text":"Report","size":"17.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 987"}],"country":"United States","state":"California ","otherGeospatial":"Monterey–Salinas Shallow Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.08282470703124,\n 36.96086580957587\n ],\n [\n -122.05261230468751,\n 36.9367208722872\n ],\n [\n -122.01690673828124,\n 36.94769679250732\n ],\n [\n -121.981201171875,\n 36.954281585675965\n ],\n [\n -121.9317626953125,\n 36.95647639022989\n ],\n [\n -121.88507080078125,\n 36.94111143010772\n ],\n [\n -121.85760498046875,\n 36.88181755936464\n ],\n [\n -121.827392578125,\n 36.82687474287728\n ],\n [\n -121.80816650390625,\n 36.78949107451841\n ],\n [\n -121.827392578125,\n 36.71687068791304\n ],\n [\n -121.85211181640625,\n 36.65079252503471\n ],\n [\n -121.871337890625,\n 36.62214102821768\n ],\n [\n -121.91802978515625,\n 36.64858894203172\n ],\n [\n -121.95648193359374,\n 36.64638529597495\n ],\n [\n -121.8878173828125,\n 36.59347887826919\n ],\n [\n -121.80816650390625,\n 36.619936625629215\n ],\n [\n -121.75872802734375,\n 36.65079252503471\n ],\n [\n -121.58843994140625,\n 36.578041001498704\n ],\n [\n -121.30004882812499,\n 36.295204533693536\n ],\n [\n -121.11328124999999,\n 36.140092827322654\n ],\n [\n -120.84136962890625,\n 35.89572525865906\n ],\n [\n -120.80291748046874,\n 35.811131416437966\n ],\n [\n -120.794677734375,\n 35.708607653285505\n ],\n [\n -120.46234130859376,\n 35.5188142812306\n ],\n [\n -120.22338867187499,\n 35.42486791930558\n ],\n [\n -120.00640869140624,\n 35.33529320309331\n ],\n [\n -119.86633300781249,\n 35.290468565908775\n ],\n [\n -119.76470947265625,\n 35.3285710912542\n ],\n [\n -119.674072265625,\n 35.250105158539355\n ],\n [\n -119.5806884765625,\n 35.191766965947394\n ],\n [\n -119.4873046875,\n 35.10193405724606\n ],\n [\n -119.43237304687499,\n 35.05922870088872\n ],\n [\n -119.29229736328126,\n 35.02099970111467\n ],\n [\n -119.07531738281251,\n 35.007502842952896\n ],\n [\n -119.02587890624999,\n 35.0502352513963\n ],\n [\n -119.02862548828125,\n 35.11766197360177\n ],\n [\n -119.05334472656249,\n 35.18952235197259\n ],\n [\n -119.25933837890624,\n 35.28374272801905\n ],\n [\n -119.43237304687499,\n 35.411438052435464\n ],\n [\n -119.49005126953124,\n 35.49198366469642\n ],\n [\n -119.65484619140625,\n 35.54116627999815\n ],\n [\n -119.91577148437499,\n 35.69522525087309\n ],\n [\n -120.09979248046874,\n 35.70414710206052\n ],\n [\n -120.24261474609374,\n 35.72421761691415\n ],\n [\n -120.28930664062499,\n 35.86456960744962\n ],\n [\n -120.9320068359375,\n 36.20660692859011\n ],\n [\n -121.13525390625,\n 36.575835338491764\n ],\n [\n -121.4813232421875,\n 36.85325222344018\n ],\n [\n -121.63238525390626,\n 36.901587303978474\n ],\n [\n -121.76422119140625,\n 36.97183825093165\n ],\n [\n -121.82464599609375,\n 37.00035919622158\n ],\n [\n -121.92626953124999,\n 37.00913272027146\n ],\n [\n -122.04986572265624,\n 37.01351910258053\n ],\n [\n -122.08282470703124,\n 36.96086580957587\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: September 1, 2016; Version 1.1: January 7, 2017","contact":"Director, California Water Science Center
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6000 J Street, Placer Hall
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http://ca.water.usgs.gov
The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.
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Many of its remaining strongholds are in headwater basins with minimal human disturbances. Understanding the life histories, vital rates, and behaviors of Yellowstone Cutthroat Trout within headwater stream networks remains limited yet is critical for effective management and conservation. We estimated annual relative growth in length and weight, annual survival rates, and movement patterns of Yellowstone Cutthroat Trout from three tributaries of Spread Creek, Wyoming, and two tributaries of Shields River, Montana, from 2011 through 2013 using PIT tag antennas within a mark–recapture framework. Mean annual growth rates varied among tributaries and size-classes, but were slow compared with populations of Yellowstone Cutthroat Trout from large, low-elevation streams. Survival rates were relatively high compared with those of other Cutthroat Trout subspecies, but we found an inverse relationship between survival and size, a pattern contrary to what has been reported for Cutthroat Trout in large streams. Mean annual survival rates ranged from 0.32 (SE = 0.04) to 0.68 (SE = 0.05) in the Spread Creek basin and from 0.30 (SE = 0.07) to 0.69 (SE = 0.10) in the Shields River basin. Downstream movements from tributaries were substantial, with as much as 26.5% of a tagging cohort leaving over the course of the study. Integrating our growth, survival, and movement results demonstrates the importance of considering strategies to enhance headwater stream habitats and highlights the importance of connectivity with larger stream networks.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1206643","usgsCitation":"Uthe, P., Al-Chokhachy, R.K., Zale, A.V., Shepard, B.B., McMahon, T., and Stephens, T., 2016, Life history characteristics and vital rates of Yellowstone Cutthroat Trout in two headwater basins: North American Journal of Fisheries Management, v. 36, no. 6, p. 1240-1253, https://doi.org/10.1080/02755947.2016.1206643.","productDescription":"14 p.","startPage":"1240","endPage":"1253","ipdsId":"IP-076407","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"58cba41be4b0849ce97dc746","contributors":{"authors":[{"text":"Uthe, Patrick","contributorId":189424,"corporation":false,"usgs":false,"family":"Uthe","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":684806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":684805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":684807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shepard, Bradley B.","contributorId":145880,"corporation":false,"usgs":false,"family":"Shepard","given":"Bradley","email":"","middleInitial":"B.","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":684808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Thomas E.","contributorId":189425,"corporation":false,"usgs":false,"family":"McMahon","given":"Thomas E.","affiliations":[],"preferred":false,"id":684809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephens, Tracy","contributorId":189426,"corporation":false,"usgs":false,"family":"Stephens","given":"Tracy","email":"","affiliations":[],"preferred":false,"id":684810,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193141,"text":"70193141 - 2016 - Nesting ecology of Whimbrels in boreal Alaska","interactions":[],"lastModifiedDate":"2017-11-21T13:43:44","indexId":"70193141","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5557,"text":"Wader Study","active":true,"publicationSubtype":{"id":10}},"title":"Nesting ecology of Whimbrels in boreal Alaska","docAbstract":"Breeding ecology studies of boreal waders have been relatively scarce in North America. This paucity is due in part to boreal habitats being difficult to access, and boreal waders being widely dispersed and thus difficult to monitor. Between 2008 and 2014 we studied the nesting ecology of Whimbrels Numenius phaeopus hudsonicus in interior Alaska, a region characterized by an active wildfire regime. Our objectives were to (1) describe the nesting ecology of Whimbrels in tundra patches within the boreal forest, (2) assess the influence of habitat features at multiple scales on nest-site selection, and (3) characterize factors affecting nest survival. Whimbrels nested in the largest patches and exhibited a consistently compressed annual breeding schedule. We hypothesized that these Whimbrels would exhibit synchronous and clustered nesting, but observed synchronous nesting in only 2009 and 2011, and evidence of clustered nesting at just one study area in 2009, providing limited support for the hypothesis. Nests tended to be on hummocks and exhibited lateral concealment around the bowl, suggesting a trade-off between a greater view from the nest and concealment. However, our analysis failed to identify other important habitat features at scales from 1–400 m from the nest. Our best-supported nest survival model showed a strong difference between our two main study areas, but this difference remains largely unexplained. Given the increased frequency, severity, and extent of wildfires predicted under climate change scenarios, our study highlights the importance of monitoring the persistence of boreal tundra patches and the Whimbrels breeding therein.
","language":"English","publisher":"International Wader Study Group","doi":"10.18194/ws.00037","usgsCitation":"Harwood, C.M., Gill, R., and Powell, A., 2016, Nesting ecology of Whimbrels in boreal Alaska: Wader Study, v. 123, no. 2, p. 99-113, https://doi.org/10.18194/ws.00037.","productDescription":"15 p.","startPage":"99","endPage":"113","ipdsId":"IP-070372","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":349212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kanuti National Wildlife Refuge","volume":"123","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-25","publicationStatus":"PW","scienceBaseUri":"5a60fcd3e4b06e28e9c24389","contributors":{"authors":[{"text":"Harwood, Christopher M.","contributorId":40515,"corporation":false,"usgs":true,"family":"Harwood","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":723064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gill, Robert E. Jr. 0000-0002-6385-4500 rgill@usgs.gov","orcid":"https://orcid.org/0000-0002-6385-4500","contributorId":171747,"corporation":false,"usgs":true,"family":"Gill","given":"Robert E.","suffix":"Jr.","email":"rgill@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":718089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Powell, Abby 0000-0002-9783-134X abby_powell@usgs.gov","orcid":"https://orcid.org/0000-0002-9783-134X","contributorId":176843,"corporation":false,"usgs":true,"family":"Powell","given":"Abby","email":"abby_powell@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":718088,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182077,"text":"70182077 - 2016 - Evidence for wild waterfowl origin of H7N3 influenza A virus detected in captive-reared New Jersey pheasants","interactions":[],"lastModifiedDate":"2018-08-16T21:28:42","indexId":"70182077","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":892,"text":"Archives of Virology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for wild waterfowl origin of H7N3 influenza A virus detected in captive-reared New Jersey pheasants","docAbstract":"In August 2014, a low-pathogenic H7N3 influenza A virus was isolated from pheasants at a New Jersey gamebird farm and hunting preserve. In this study, we use phylogenetic analyses and calculations of genetic similarity to gain inference into the genetic ancestry of this virus and to identify potential routes of transmission. Results of maximum-likelihood (ML) and maximum-clade-credibility (MCC) phylogenetic analyses provide evidence that A/pheasant/New Jersey/26996-2/2014 (H7N3) had closely related H7 hemagglutinin (HA) and N3 neuraminidase (NA) gene segments as compared to influenza A viruses circulating among wild waterfowl in the central and eastern USA. The estimated time of the most recent common ancestry (TMRCA) between the pheasant virus and those most closely related from wild waterfowl was early 2013 for both the H7 HA and N3 NA gene segments. None of the viruses from waterfowl identified as being most closely related to A/pheasant/New Jersey/26996-2/2014 at the HA and NA gene segments in ML and MCC phylogenetic analyses shared ≥99 % nucleotide sequence identity for internal gene segment sequences. This result indicates that specific viral strains identified in this study as being closely related to the HA and NA gene segments of A/pheasant/New Jersey/26996-2/2014 were not the direct predecessors of the etiological agent identified during the New Jersey outbreak. However, the recent common ancestry of the H7 and N3 gene segments of waterfowl-origin viruses and the virus isolated from pheasants suggests that viral diversity maintained in wild waterfowl likely played an important role in the emergence of A/pheasant/New Jersey/26996-2/2014.
","language":"English","publisher":"Springer","doi":"10.1007/s00705-016-2947-z","usgsCitation":"Ramey, A.M., Kim Torchetti, M., Poulson, R.L., Carter, D.L., Reeves, A.B., Link, P., Walther, P., Lebarbenchon, C., and Stallknecht, D.E., 2016, Evidence for wild waterfowl origin of H7N3 influenza A virus detected in captive-reared New Jersey pheasants: Archives of Virology, v. 161, no. 9, p. 2519-2526, https://doi.org/10.1007/s00705-016-2947-z.","productDescription":"8 p.","startPage":"2519","endPage":"2526","ipdsId":"IP-073296","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470618,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11302360","text":"External Repository"},{"id":335678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"161","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-02","publicationStatus":"PW","scienceBaseUri":"58a6c832e4b025c46428628c","chorus":{"doi":"10.1007/s00705-016-2947-z","url":"http://dx.doi.org/10.1007/s00705-016-2947-z","publisher":"Springer Nature","authors":"Ramey Andrew M., Kim Torchetti Mia, Poulson Rebecca L., Carter Deborah, Reeves Andrew B., Link Paul, Walther Patrick, Lebarbenchon Camille, Stallknecht David E.","journalName":"Archives of Virology","publicationDate":"7/2/2016","auditedOn":"2/8/2017","publiclyAccessibleDate":"7/2/2016"},"contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":669532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim Torchetti, Mia","contributorId":139355,"corporation":false,"usgs":false,"family":"Kim Torchetti","given":"Mia","email":"","affiliations":[{"id":12747,"text":"USDA APHIS VS National Veterinary Services Laboratories, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":669533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poulson, Rebecca L.","contributorId":68669,"corporation":false,"usgs":true,"family":"Poulson","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":669534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carter, Deborah L.","contributorId":87473,"corporation":false,"usgs":true,"family":"Carter","given":"Deborah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":669535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":669536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Link, Paul","contributorId":22707,"corporation":false,"usgs":true,"family":"Link","given":"Paul","affiliations":[],"preferred":false,"id":669537,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walther, Patrick","contributorId":42153,"corporation":false,"usgs":true,"family":"Walther","given":"Patrick","affiliations":[],"preferred":false,"id":669538,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lebarbenchon, Camille","contributorId":140670,"corporation":false,"usgs":false,"family":"Lebarbenchon","given":"Camille","email":"","affiliations":[],"preferred":false,"id":669539,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stallknecht, David E.","contributorId":20230,"corporation":false,"usgs":true,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":669540,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70182088,"text":"70182088 - 2016 - Low survival rates of Swan Geese (Anser cygnoides) estimated from neck-collar resighting and telemetry","interactions":[],"lastModifiedDate":"2017-02-16T09:31:19","indexId":"70182088","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Low survival rates of Swan Geese (Anser cygnoides) estimated from neck-collar resighting and telemetry","docAbstract":"Waterbird survival rates are a key component of demographic modeling used for effective conservation of long-lived threatened species. The Swan Goose (Anser cygnoides) is globally threatened and the most vulnerable goose species endemic to East Asia due to its small and rapidly declining population. To address a current knowledge gap in demographic parameters of the Swan Goose, available datasets were compiled from neck-collar resighting and telemetry studies, and two different models were used to estimate their survival rates. Results of a mark-resighting model using 15 years of neck-collar data (2001–2015) provided age-dependent survival rates and season-dependent encounter rates with a constant neck-collar retention rate. Annual survival rate was 0.638 (95% CI: 0.378–0.803) for adults and 0.122 (95% CI: 0.028–0.286) for first-year juveniles. Known-fate models were applied to the single season of telemetry data (autumn 2014) and estimated a mean annual survival rate of 0.408 (95% CI: 0.152–0.670) with higher but non-significant differences for adults (0.477) vs. juveniles (0.306). Our findings indicate that Swan Goose survival rates are comparable to the lowest rates reported for European or North American goose species. Poor survival may be a key demographic parameter contributing to their declining trend. Quantitative threat assessments and associated conservation measures, such as restricting hunting, may be a key step to mitigate for their low survival rates and maintain or enhance their population.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.039.0307","usgsCitation":"Choi, C., Lee, K., Poyarkov, N.D., Park, J., Lee, H., Takekawa, J.Y., Smith, L.M., Ely, C.R., Wang, X., Cao, L., Fox, A.D., Goroshko, O., Batbayar, N., Prosser, D.J., and Xiao, X., 2016, Low survival rates of Swan Geese (Anser cygnoides) estimated from neck-collar resighting and telemetry: Waterbirds, v. 39, no. 3, p. 277-286, https://doi.org/10.1675/063.039.0307.","productDescription":"10 p.","startPage":"277","endPage":"286","ipdsId":"IP-075702","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":335672,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Mongolia, Russia, South Korea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n 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Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":669520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Lacy M. 0000-0001-6733-1080 lmsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6733-1080","contributorId":4772,"corporation":false,"usgs":true,"family":"Smith","given":"Lacy","email":"lmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":669521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology 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Oleg","contributorId":181790,"corporation":false,"usgs":false,"family":"Goroshko","given":"Oleg","email":"","affiliations":[],"preferred":false,"id":669526,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Batbayar, Nyambaya","contributorId":181791,"corporation":false,"usgs":false,"family":"Batbayar","given":"Nyambaya","affiliations":[],"preferred":false,"id":669527,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":669514,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Xiao, Xiangming","contributorId":181792,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiangming","email":"","affiliations":[],"preferred":false,"id":669528,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70187173,"text":"70187173 - 2016 - Environmental covariates associated with Cambarus veteranus (Decapoda: Cambaridae), an imperiled Appalachian crayfish endemic to West Virginia, USA","interactions":[],"lastModifiedDate":"2018-03-16T15:31:45","indexId":"70187173","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2235,"text":"Journal of Crustacean Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental covariates associated with Cambarus veteranus (Decapoda: Cambaridae), an imperiled Appalachian crayfish endemic to West Virginia, USA","title":"Environmental covariates associated with Cambarus veteranus (Decapoda: Cambaridae), an imperiled Appalachian crayfish endemic to West Virginia, USA","docAbstract":"Cambarus veteranus Faxon, 1914, a narrow endemic crayfish native to the Upper Guyandotte River Basin (UGB) in West Virginia, USA, was petitioned in 2014 by the United States Fish and Wildlife Service to be listed as endangered, but a status survey was recommended to determine if listing was warranted. During May and June 2015, surveys were undertaken across the UGB to determine the current distribution of the species. A total of 71 sites were sampled, including all streams where the species was previously recorded, as well as semi-randomly selected streams, with 1-9 125 m long sites sampled per wadeable stream. Physiochemical and physical habitat data (based on the Qualitative Habitat Evaluation Index, QHEI) were obtained at each site to determine abiotic factors that were associated with the presence of C. veteranus. Site detection or non-detection of C. veteranus and associated site covariates were modeled using logistic regression to determine covariates associated with the presence of the species. Cambarus veteranus was present in both the Pinnacle Creek and Clear Fork/Laurel Fork watersheds at 10 sites, but it was not observed in the remaining 61 sites. An additive effects model with conductivity and QHEI was selected as the best approximating model. Cambarusveteranus was associated with lower than average UGB conductivity (379 µS) and high (>80) QHEI score. All sites where C. veteranus was not detected had higher conductivity and/or lower QHEI scores.
","language":"English","publisher":"Oxford Academic","doi":"10.1163/1937240x-00002456","usgsCitation":"Loughman, Z.J., Welsh, S., Sadecky, N., Dillard, Z.W., and Scott, R.K., 2016, Environmental covariates associated with Cambarus veteranus (Decapoda: Cambaridae), an imperiled Appalachian crayfish endemic to West Virginia, USA: Journal of Crustacean Biology, v. 36, no. 5, p. 642-648, https://doi.org/10.1163/1937240x-00002456.","productDescription":"7 p.","startPage":"642","endPage":"648","ipdsId":"IP-078754","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470619,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1163/1937240x-00002456","text":"Publisher Index Page"},{"id":340355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Upper Guyandotte River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.14501953125,\n 38.37611542403604\n ],\n [\n -80.83740234375,\n 38.315801006824984\n ],\n [\n -80.5517578125,\n 38.22091976683121\n ],\n [\n -80.26611328125,\n 38.08268954483802\n ],\n [\n -80.22216796875,\n 37.93553306183642\n ],\n [\n -80.343017578125,\n 37.75334401310656\n ],\n [\n -80.66162109375,\n 37.61423141542417\n ],\n [\n -81.01318359375,\n 37.501010429493284\n ],\n [\n -81.76025390625,\n 37.50972584293751\n ],\n [\n -81.968994140625,\n 37.58811876638322\n ],\n [\n -82.276611328125,\n 37.735969208590504\n ],\n [\n -82.37548828125,\n 37.95286091815649\n ],\n [\n -82.496337890625,\n 38.14319750166766\n ],\n [\n -82.4853515625,\n 38.28993659801203\n ],\n [\n -82.30957031249999,\n 38.41055825094609\n ],\n [\n -82.0458984375,\n 38.57393751557591\n ],\n [\n -81.82617187499999,\n 38.57393751557591\n ],\n [\n -81.507568359375,\n 38.53957267203905\n ],\n [\n -81.287841796875,\n 38.46219172306828\n ],\n [\n -81.14501953125,\n 38.37611542403604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006063e4b0e85db3a5ddd7","contributors":{"authors":[{"text":"Loughman, Zachary J.","contributorId":76157,"corporation":false,"usgs":false,"family":"Loughman","given":"Zachary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":692929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":692923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sadecky, Nicole M.","contributorId":179375,"corporation":false,"usgs":false,"family":"Sadecky","given":"Nicole M.","affiliations":[],"preferred":false,"id":692930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dillard, Zachary W.","contributorId":179376,"corporation":false,"usgs":false,"family":"Dillard","given":"Zachary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":692931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scott, R. Katie","contributorId":179377,"corporation":false,"usgs":false,"family":"Scott","given":"R.","email":"","middleInitial":"Katie","affiliations":[],"preferred":false,"id":692932,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184981,"text":"70184981 - 2016 - The water content of recurring slope lineae on Mars","interactions":[],"lastModifiedDate":"2017-03-14T15:35:52","indexId":"70184981","displayToPublicDate":"2016-09-01T00:00:00","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":"The water content of recurring slope lineae on Mars","docAbstract":"Observations of recurring slope lineae (RSL) from the High-Resolution Imaging Science Experiment have been interpreted as present-day, seasonally variable liquid water flows; however, orbital spectroscopy has not confirmed the presence of liquid H2O, only hydrated salts. Thermal Emission Imaging System (THEMIS) temperature data and a numerical heat transfer model definitively constrain the amount of water associated with RSL. Surface temperature differences between RSL-bearing and dry RSL-free terrains are consistent with no water associated with RSL and, based on measurement uncertainties, limit the water content of RSL to at most 0.5–3 wt %. In addition, distinct high thermal inertia regolith signatures expected with crust-forming evaporitic salt deposits from cyclical briny water flows are not observed, indicating low water salinity (if any) and/or low enough volumes to prevent their formation. Alternatively, observed salts may be preexisting in soils at low abundances (i.e., near or below detection limits) and largely immobile. These RSL-rich surfaces experience ~100 K diurnal temperature oscillations, possible freeze/thaw cycles and/or complete evaporation on time scales that challenge their habitability potential. The unique surface temperature measurements provided by THEMIS are consistent with a dry RSL hypothesis or at least significantly limit the water content of Martian RSL.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2016GL070179","usgsCitation":"Edwards, C.S., and Piqueux, S., 2016, The water content of recurring slope lineae on Mars: Geophysical Research Letters, v. 43, no. 17, p. 8912-8919, https://doi.org/10.1002/2016GL070179.","productDescription":"8 p.","startPage":"8912","endPage":"8919","ipdsId":"IP-062637","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":500022,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/cf107a42de8c405cbe062d62efb1f576","text":"External Repository"},{"id":337537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"17","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-14","publicationStatus":"PW","scienceBaseUri":"58c90126e4b0849ce97abcdd","contributors":{"authors":[{"text":"Edwards, Christopher S. cedwards@usgs.gov","contributorId":147153,"corporation":false,"usgs":true,"family":"Edwards","given":"Christopher","email":"cedwards@usgs.gov","middleInitial":"S.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":683815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Piqueux, Sylvain","contributorId":56986,"corporation":false,"usgs":false,"family":"Piqueux","given":"Sylvain","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":683816,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185062,"text":"70185062 - 2016 - SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate","interactions":[],"lastModifiedDate":"2017-03-13T17:00:12","indexId":"70185062","displayToPublicDate":"2016-09-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate","docAbstract":"Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.
","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.12560","usgsCitation":"Roffler, G.H., Amish, S.J., Smith, S., Cosart, T.F., Kardos, M., Schwartz, M.K., and Luikart, G., 2016, SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate: Molecular Ecology Resources, v. 16, no. 5, p. 1147-1164, https://doi.org/10.1111/1755-0998.12560.","productDescription":"18 p.","startPage":"1147","endPage":"1164","ipdsId":"IP-077118","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470614,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1755-0998.12560","text":"Publisher Index Page"},{"id":337477,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-18","publicationStatus":"PW","scienceBaseUri":"58c7afa0e4b0849ce9795e9c","chorus":{"doi":"10.1111/1755-0998.12560","url":"http://dx.doi.org/10.1111/1755-0998.12560","publisher":"Wiley-Blackwell","authors":"Roffler Gretchen H., Amish Stephen J., Smith Seth, Cosart Ted, Kardos Marty, Schwartz Michael K., Luikart Gordon","journalName":"Molecular Ecology Resources","publicationDate":"7/18/2016"},"contributors":{"authors":[{"text":"Roffler, Gretchen H. groffler@usgs.gov","contributorId":1946,"corporation":false,"usgs":true,"family":"Roffler","given":"Gretchen","email":"groffler@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":684124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amish, Stephen J.","contributorId":104799,"corporation":false,"usgs":false,"family":"Amish","given":"Stephen","email":"","middleInitial":"J.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":684170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Seth","contributorId":189234,"corporation":false,"usgs":false,"family":"Smith","given":"Seth","email":"","affiliations":[],"preferred":false,"id":684171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cosart, Ted F.","contributorId":177052,"corporation":false,"usgs":false,"family":"Cosart","given":"Ted","email":"","middleInitial":"F.","affiliations":[{"id":5091,"text":"Flathead Lake Biological Station, Fish and Wildlife Genomics Group, Division of Biological Sciences, University of Montana, Polson, MT 59860, USA","active":true,"usgs":false}],"preferred":false,"id":684172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kardos, Marty","contributorId":189235,"corporation":false,"usgs":false,"family":"Kardos","given":"Marty","affiliations":[],"preferred":false,"id":684173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwartz, Michael K.","contributorId":102326,"corporation":false,"usgs":true,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":684174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Luikart, Gordon","contributorId":145746,"corporation":false,"usgs":false,"family":"Luikart","given":"Gordon","email":"","affiliations":[{"id":16220,"text":"Flathead Lake Biological Station, Div. Biological Science, UM","active":true,"usgs":false}],"preferred":false,"id":684175,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176178,"text":"70176178 - 2016 - Safety of the molluscicide Zequanox (R) to nontarget macroinvertebrates Gammarus lacustris (Amphipoda: Gammaridae) and Hexagenia spp. (Ephemeroptera: Ephemeridae)","interactions":[],"lastModifiedDate":"2016-08-31T16:05:18","indexId":"70176178","displayToPublicDate":"2016-08-31T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Safety of the molluscicide Zequanox (R) to nontarget macroinvertebrates Gammarus lacustris (Amphipoda: Gammaridae) and Hexagenia spp. (Ephemeroptera: Ephemeridae)","docAbstract":"Zequanox® is a commercial formulation of the killed bacterium, Pseudomonas fluorescens (strain CL145A), that was developed to control dreissenid mussels. In 2014, Zequanox became the second product registered by the United States Environmental Protection Agency (USEPA) for use in open water environments as a molluscicide. Previous nontarget studies demonstrated the safety and selectivity of P. fluorescens CL154A, but the database on the toxicity of the formulation (Zequanox) is limited for macroinvertebrate taxa and exposure conditions. We evaluated the safety of Zequanox to the amphipod Gammarus lacustris lacustris, and nymphs of the burrowing mayfly, Hexagenia spp. at the maximum approved concentration (100 mg/L active ingredient, A.I.) and exposure duration (8 h). Survival of animals was assessed after 8 h of exposure and again at 24 and 96 h post-exposure. Histopathology of the digestive tract of control and treated animals was compared at 96 h post-exposure. The results showed no significant effect of Zequanox on survival of either species. Survival of G. lacustris exceeded 85% in all concentrations at all three sampling time points. Survival of Hexagenia spp. ranged from 71% (control) to 91% at 8 h, 89–93% at 24 h post-exposure, and 70–73% at 96 h post-exposure across all treatments. We saw no evidence of pathology in the visceral organs of treated animals. Our results indicate that application of Zequanox at the maximum approved concentration and exposure duration did not cause significant mortality or treatment-related histopathological changes to G. lacustris and Hexagenia spp.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre - REABIC","doi":"10.3391/mbi.2016.7.3.06","usgsCitation":"Waller, D.L., Luoma, J.A., and Erickson, R.A., 2016, Safety of the molluscicide Zequanox (R) to nontarget macroinvertebrates Gammarus lacustris (Amphipoda: Gammaridae) and Hexagenia spp. (Ephemeroptera: Ephemeridae): Management of Biological Invasions, v. 7, no. 3, p. 269-280, https://doi.org/10.3391/mbi.2016.7.3.06.","productDescription":"12 p.","startPage":"269","endPage":"280","ipdsId":"IP-071502","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":470630,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2016.7.3.06","text":"Publisher Index Page"},{"id":328153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7f1ade4b0f2f0cebf11b3","contributors":{"authors":[{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":647611,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173721,"text":"sir20165076 - 2016 - Documentation of a groundwater flow model developed to assess groundwater availability in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina","interactions":[],"lastModifiedDate":"2017-01-18T13:29:05","indexId":"sir20165076","displayToPublicDate":"2016-08-31T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5076","title":"Documentation of a groundwater flow model developed to assess groundwater availability in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina","docAbstract":"The U.S. Geological Survey developed a groundwater flow model for the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to northeastern North Carolina as part of a detailed assessment of the groundwater availability of the area and included an evaluation of how these resources have changed over time from stresses related to human uses and climate trends. The assessment was necessary because of the substantial dependency on groundwater for agricultural, industrial, and municipal needs in this area.
The three-dimensional, groundwater flow model developed for this investigation used the numerical code MODFLOW–NWT to represent changes in groundwater pumping and aquifer recharge from predevelopment (before 1900) to future conditions, from 1900 to 2058. The model was constructed using existing hydrogeologic and geospatial information to represent the aquifer system geometry, boundaries, and hydraulic properties of the 19 separate regional aquifers and confining units within the Northern Atlantic Coastal Plain aquifer system and was calibrated using an inverse modeling parameter-estimation (PEST) technique.
The parameter estimation process was achieved through history matching, using observations of heads and flows for both steady-state and transient conditions. A total of 8,868 annual water-level observations from 644 wells from 1986 to 2008 were combined into 29 water-level observation groups that were chosen to focus the history matching on specific hydrogeologic units in geographic areas in which distinct geologic and hydrologic conditions were observed. In addition to absolute water-level elevations, the water-level differences between individual measurements were also included in the parameter estimation process to remove the systematic bias caused by missing hydrologic stresses prior to 1986. The total average residual of –1.7 feet was normally distributed for all head groups, indicating minimal bias. The average absolute residual value of 12.3 feet is about 3 percent of the total observed water-level range throughout the aquifer system.
Streamflow observation data of base flow conditions were derived for 153 sites from the U.S. Geological Survey National Hydrography Dataset Plus and National Water Information System. An average residual of about –8 cubic feet per second and an average absolute residual of about 21 cubic feet per second for a range of computed base flows of about 417 cubic feet per second were calculated for the 122 sites from the National Hydrography Dataset Plus. An average residual of about 10 cubic feet per second and an average absolute residual of about 34 cubic feet per second were calculated for the 568 flow measurements in the 31 sites obtained from the National Water Information System for a range in computed base flows of about 1,141 cubic feet per second.
The numerical representation of the hydrogeologic information used in the development of this regional flow model was dependent upon how the aquifer system and simulated hydrologic stresses were discretized in space and time. Lumping hydraulic parameters in space and hydrologic stresses and time-varying observational data in time can limit the capabilities of this tool to simulate how the groundwater flow system responds to changes in hydrologic stresses, particularly at the local scale.
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The U.S. Geological Survey began a multiyear regional assessment of groundwater availability in the Northern Atlantic Coastal Plain (NACP) aquifer system in 2010 as part of its ongoing regional assessments of groundwater availability of the principal aquifers of the Nation. The goals of this national assessment are to document effects of human activities on water levels and groundwater storage, explore climate variability effects on the regional water budget, and provide consistent and integrated information that is useful to those who use and manage the groundwater resource. As part of this nationwide assessment, the USGS evaluated available groundwater resources within the NACP aquifer system from Long Island, New York, to northeastern North Carolina.
The northern Atlantic Coastal Plain physiographic province depends heavily on groundwater to meet agricultural, industrial, and municipal needs. The groundwater assessment of the NACP aquifer system included an evaluation of how water use has changed over time; this evaluation primarily used groundwater budgets and development of a numerical modeling tool to assess system responses to stresses from future human uses and climate trends.
This assessment focused on multiple spatial and temporal scales to examine changes in groundwater pumping, storage, and water levels. The regional scale provides a broad view of the sources and demands on the system with time. The sub-regional scale provides an evaluation of the differing response of the aquifer system across geographic areas allowing for closer examination of the interaction between different aquifers and confining units and the changes in these interactions under pumping and recharge conditions in 2013 and hydrologic stresses as much as 45 years in the future. By focusing on multiple scales, water-resource managers may utilize this study to understand system response to changes as they affect the system as a whole.
The NACP aquifer system extends from Long Island to northeastern North Carolina, and includes aquifers primarily within New York, New Jersey, Delaware, Maryland, Virginia, and North Carolina. The seaward-dipping sedimentary wedge that underlies the northern Atlantic Coastal Plain physiographic province forms a complex groundwater system. Although the NACP aquifer system is recognized by the U.S. Geological Survey as one of the smallest of the 66 principal aquifer systems in the Nation, it ranks 13th overall in terms of total groundwater withdrawals and is 7th in population served. Despite abundant precipitation [about 45 inches per year (in/yr)], the supply of fresh surface water in this region is limited because many of the surface waters in this area are brackish estuaries, contributing to why many communities in the northern Atlantic Coastal Plain physiographic province rely heavily on groundwater to meet their water needs.
Increases in population and changes in land use during the past 100 years have resulted in diverse increased demands for freshwater throughout the northern Atlantic Coastal Plain physiographic province with groundwater serving as a vital source of drinking water for the nearly 20 million people who live in the region. Total groundwater withdrawal in 2013 was estimated to be about 1,300 million gallons per day (Mgal/d) and accounts for about 40 percent of the drinking water supply with the densely populated areas tending to have the highest rates of withdrawals and, therefore, being most susceptible to effects from these withdrawals over time.
Water levels in many of the confined aquifers are decreasing by as much as 2 feet per year (ft/yr) in response to extensive development and subsequent increased withdrawals throughout the region. Total water-level decreases (drawdowns) are more than 100 feet (ft) in some aquifers from their predevelopment (before 1900) levels. These drawdowns extend across state lines and under the Chesapeake and Delaware Bays, creating the potential for interstate aquifer management issues. Regional water-resources managers in the northern Atlantic Coastal Plain physiographic province face challenges beyond competing local domestic, industrial, agricultural, and environmental demands for water. Large changes in regional water use have made the State-level management of aquifer resources more difficult because of hydrologic effects that extend beyond State boundaries.
The northern Atlantic Coastal Plain physiographic province is underlain by a wedge of unconsolidated to partially consolidated sediments that are typically thousands of feet thick along the coastline with a maximum thickness of about 10,000 ft near the edge of the continental shelf. The NACP aquifer system consists of nine confined aquifers and nine confining units capped by an unconfined surficial aquifer that is bounded laterally from the west by the contact between Coastal Plain sediments and the upland Piedmont bedrock. This aquifer system extends to the east to the limit of the Continental Shelf, however, the boundary between fresh and saline groundwater is considered to be much closer to the shoreline and varies vertically by aquifer.
Precipitation over the region for average conditions from 2005 to 2009 is about 61,800 Mgal/d, but about 70 percent of it is lost to evapotranspiration resulting in an inflow of about 19,600 Mgal/d entering the groundwater system as aquifer recharge. Most of this recharge enters the aquifer system and flows through the shallow unconfined aquifer and either discharges to streams or directly to coastal waters without reaching the deep, confined aquifer system. In addition to recharge from precipitation, other sources of water include the return of wastewater from domestic septic systems of about 240 Mgal/d, about 60 Mgal/d of water released from storage in the confined system, and about 30 Mgal/d of lateral inflow at the boundary between freshwater and saltwater in response to pumping for conditions in 2013.
The outflow needed to balance the inflows was subdivided between streamflow, discharge to tidal portions of streams, and coastal discharge. The hydrologic budget developed for current [2013] conditions determined that 93 percent of the total outflow was to surface waters with about 70 percent divided evenly between streamflow and shallow coastal discharge and 23 percent as discharge to tidal waters. The remaining 7 percent of the total outflow components include withdrawals from both the surficial and confined aquifers of the groundwater system.
The groundwater availability assessment of the NACP aquifer system highlights the importance of analyses at both the regional and local scales to understand how changes in land use, water use, and climate have affected groundwater resources and how these resources may change in the future. The investigation included assessments of the regional changes in water levels and budgets across State lines, the importance of considering storage change in the confining units, the response of the aquifer system to a continuation of current [2013] hydrologic stresses into the future, and the potential effects of climate change and sea-level rise on the aquifer system.
The Potomac aquifer group includes two of the most widely used aquifers in the NACP aquifer system, the Potomac-Patapsco and Potomac-Patuxent regional aquifers, providing about 24 percent of the total groundwater used in the region. Withdrawals from large pumping centers in this deep, confined aquifer group have resulted in substantial decreases in water-levels across state lines, particularly between southern Virginia and northeastern North Carolina as well as between southern New Jersey and northern Delaware where water levels in the Potomac-Patapsco aquifer have decreased by as much as 200 ft and 50 ft, respectively from predevelopment to current [2013] conditions. This response in water levels also is reflected in changes in water budgets where, for example, about 20 percent of the total response to pumping in Virginia is met by inducing flow from adjacent States. Understanding and quantifying these hydrologic effects that extend beyond State boundaries is critical for the State- and regional-level management of aquifer resources.
The cumulative storage loss from the intervening confining units throughout the entire NACP aquifer system was about 35 percent of the total storage loss from predevelopment to current [2013] conditions. In geographic areas such as Delmarva Peninsula, Maryland, and New Jersey, the water released from storage in the confining units makes up the majority of the total storage release from the groundwater system and is becoming proportionally more important over time as the surficial aquifer approaches equilibrium with respect to pumping and recharge stresses as of 2013.
Storage loss from the confining units is of particular concern because, unlike in the sands that comprise the confined aquifers, water removed from the clayey confining unit sediments cannot be replenished as these units gradually compress. This non-recoverable storage loss, if great enough, can result in land subsidence where these units are thick and the release from storage is relatively large and contributes to increased concerns for sea-level rise in areas such as the lower portion of the Chesapeake Bay.
Groundwater usage increased dramatically in the NACP aquifer system during post-World War II era from the mid-1940s to early the 1980s, with withdrawals increasing from about 400 Mgal/d to more than 1,300 Mgal/d. Although groundwater withdrawals have been relatively constant since the early 1980s, about half of the total groundwater withdrawn from the NACP aquifer system since 1900 was withdrawn in the past 30 years. An analysis of the response of the groundwater system to a continuation of the current [2013] pumping for an additional 30 years into the future shows that the flow system continues to adjust in terms of changes in water budget components, water levels, and the boundary between freshwater and saltwater as it approaches equilibrium. The largest change in water budget components is the reduction in the amount of water released from storage.
Across the entire NACP aquifer system, the reduction of storage release from 7 to 4 percent of the total water budget change is accounted for by reductions in groundwater discharge to streams and coastal waters. Locally, a similar response is calculated for each of the geographic areas except for Virginia where the amount of water released from storage accounts for about 25 percent of the total change in water budget. This finding suggests that the groundwater flow system in Virginia is not approaching equilibrium under the current [2013] stresses and, therefore, water levels will continue to decrease even if the pumping remains constant.
An analysis of the change in water levels in the Potomac-Patapsco aquifer as pumping is continued 30 years into the future reveals that the largest decreases in water levels throughout the NACP aquifer system will occur in the southern Virginia and northeastern North Carolina parts of the study area. It is these areas that also see the greatest potential for increased lateral movement of saline groundwater in the deep, confined portion of the groundwater flow system in response to a continuation of the current [2013] pumping rates.
The potential effects of long-term climate change and variability on the hydrologic system and availability of water resources in the NACP aquifer system continue to be of serious societal concern. These concerns include the effects of changes in aquifer recharge and in sea-level rise on the groundwater flow system. An assessment of the potential effects of a prolonged drought during current [2013] pumping conditions indicated that the reductions in recharge associated with droughts, including additional irrigation withdrawals required to meet increased crop water demand, have the greatest effects on water levels and streamflows in the surficial aquifer, and changes in water levels in the confined aquifers primarily resulted from the increased withdrawals associated with increased irrigation pumping; this response was most apparent in the Delmarva Peninsula. These results suggest that water levels may not be susceptible to the effects of droughts in the confined aquifers of the NACP aquifer system not used for irrigation, unlike in the unconfined surficial aquifer.
A second analysis also was conducted to assess the effects of sea-level rise on the groundwater system throughout the northern Atlantic Coastal Plain physiographic province because recent analyses of the relative rates of sea-level rise along the Atlantic coast indicate that the Mid-Atlantic region represents a hot spot with anomalously higher rates of sea-level rise than observed elsewhere in the United States. Groundwater levels rose from 0 to 3 ft in response to a 3-ft simulated change in sea-level position, with the largest response occurring along the shoreline and away from non-tidal streams. About 37 percent (or 10,000 square miles) of the area of the northern Atlantic Coastal Plain physiographic province may experience about a 0.5-ft or more increase in water levels with the 3-ft increase in sea-level position, whereas about 18 percent (almost 5,000 square miles) of land of the northern Atlantic Coastal Plain physiographic province may experience a 2-ft or more increase in water levels with the 3-ft increase in sea-level position.
These increases in the water table are of particular concern in low-lying areas where the unsaturated (vadose) zone is already thin, thus creating concerns for groundwater inundation of subsurface infrastructure, such as basements, septic systems, and subway systems. This increase in the water table also will likely alter the distribution of groundwater discharge to surface-water bodies thus increasing groundwater flow to streams that would have otherwise discharged directly to coastal waters. Throughout the NACP aquifer system, this redistribution of groundwater discharge results in an additional 2 percent of base flow in streams. Although the increases in groundwater discharge to streams (and corresponding decreases in discharge to coastal waters) calculated for the entire NACP aquifer system and its geographic areas represent only a small increase compared with current [2013] conditions, this redistribution of groundwater discharge from the coast to streams locally can alter the delivery of freshwater input to coastal receiving waters and have ecohydrological implications on the sensitive ecosystems which rely on a balance of groundwater discharge and surface-water flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1829","usgsCitation":"Masterson, J.P., Pope, J.P., Fienen, M.N., Monti, Jack, Jr., Nardi, M.R., and Finkelstein, J.S., 2016, Assessment of groundwater availability in the Northern Atlantic Coastal Plain aquifer system from Long Island, New York, to North Carolina: U.S. Geological Survey Professional Paper 1829, 76 p., https://dx.doi.org/10.3133/pp1829.","productDescription":"Report: ix, 76 p.; Data Releases","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-067132","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":326315,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165076","text":"Scientific Investigations Report 2016–5076 -","description":"PP 1829","linkHelpText":"Documentation of a Groundwater Flow Model Developed To Assess Groundwater Availability in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326316,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165034","text":"Scientific Investigations Report 2016–5034 -","description":"PP 1829","linkHelpText":"Regional Chloride Distribution in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326318,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20163046","text":"Fact Sheet 2016–3046 -","description":"PP 1829","linkHelpText":"Sustainability of Groundwater Supplies in the Northern Atlantic Coastal Plain Aquifer System"},{"id":326317,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ds996","text":"Data Series 996 -","description":"PP 1829","linkHelpText":"Digital Elevations and Extents of Regional Hydrogeologic Units in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326314,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1829/pp1829.pdf","text":"Report","size":"11.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1829"},{"id":326886,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F70V89WN","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital elevations and extents of hydrogeologic units"},{"id":326313,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1829/coverthb.jpg"},{"id":327883,"rank":9,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/wausp/","text":"USGS Water Availability and Use Science Program","description":"Project Site"},{"id":326885,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7MG7MKR","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-NWT model"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, North Carolina, Virginia","otherGeospatial":"Northern Atlantic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {\n \"stroke\": \"#555555\",\n \"stroke-width\": 2,\n \"stroke-opacity\": 1,\n \"fill\": \"#555555\",\n \"fill-opacity\": 0.5\n },\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.57568359375,\n 41.32732632036622\n ],\n [\n -71.630859375,\n 41.343824581185686\n ],\n [\n -71.21337890625,\n 41.261291493919856\n ],\n [\n -71.015625,\n 41.0130657870063\n ],\n [\n -71.30126953124999,\n 40.88029480552824\n ],\n [\n -71.78466796874999,\n 40.04443758460859\n ],\n [\n -72.6416015625,\n 38.37611542403604\n ],\n [\n -73.32275390625,\n 37.317751851636906\n ],\n [\n -73.564453125,\n 36.4566360115962\n ],\n [\n -74.06982421875,\n 35.15584570226544\n ],\n [\n -75.16845703124999,\n 34.939985151560435\n ],\n [\n -76.92626953125,\n 35.585851593232356\n ],\n [\n -77.2998046875,\n 36.26199220445664\n ],\n [\n -77.27783203125,\n 37.37015718405753\n ],\n [\n -76.81640625,\n 38.75408327579141\n ],\n [\n -75.7177734375,\n 39.757879992021756\n ],\n [\n -75.21240234375,\n 40.26276066437183\n ],\n [\n -74.8828125,\n 40.613952441166596\n ],\n [\n -74.6630859375,\n 40.6639728763869\n ],\n [\n -74.35546875,\n 40.78054143186031\n ],\n [\n -74.1357421875,\n 40.79717741518769\n ],\n [\n -73.89404296875,\n 40.830436877649255\n ],\n [\n -73.54248046875,\n 40.9964840143779\n ],\n [\n -73.19091796875,\n 41.1455697310095\n ],\n [\n -72.57568359375,\n 41.32732632036622\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Water Availability and Use Science Program
U.S. Geological Survey
150 National Center
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Reston, VA 20192
http://water.usgs.gov/wausp/
The aquifers of the Northern Atlantic Coastal Plain are the principal source of water supply for the region’s nearly 20 million residents. Water quality and water levels in the aquifers, and maintenance of streamflow, are of concern because of the use of this natural resource for water supply and because of the possible effects of climate change and changes in land use on groundwater. The long-term sustainability of this natural resource is a concern at the local community scale, as well as at a regional scale, across state boundaries. In 2010, the U.S. Geological Survey (USGS) began a regional assessment of the Northern Atlantic Coastal Plain aquifers. An important part of this assessment is a regional interpretation of the extent of saltwater and the proximity of saltwater to fresh-groundwater resources and includes samples and published interpretations of chloride concentrations newly available since the last regional chloride assessment in 1989. This updated assessment also includes consideration of chloride samples and refined interpretations that stem from the 1994 discovery of the buried 35 million year old Chesapeake Bay impact structure that has substantially altered the understanding of the hydrogeologic framework and saltwater distribution in eastern Virginia.
\nIn this study, the regional area of concern for the chloride samples and interpretations extends from the Fall Line in the west to the outer edge of the Continental Shelf in the east and from the eastern tip of Long Island in the north to about halfway down the North Carolina coast in the south. Discussions of chloride distribution are presented for each of the 10 regional aquifer layers of the Northern Atlantic Coastal Plain, including the offshore extents. Maps of interpreted lines of equal concentration or isochlors were manually prepared for nine of the regional aquifers; a map was not prepared for the surficial regional aquifer. The isochlor interpretations include the offshore extent of the nine regional aquifers and are presented on a 1:2,000,000 scale base map. Vertically, the chloride samples and interpretations range from deepest (oldest) to shallowest (youngest)—Potomac-Patuxent, Potomac-Patapsco, Magothy, Matawan, Monmouth-Mount Laurel, Aquia, Piney Point, Lower Chesapeake, and Upper Chesapeake regional aquifers.
\nThe approach of this study maximizes the overall density of chloride information and data by assessing relevant published interpretations, all USGS chloride samples, and all relevant offshore samples in one comprehensive interpretation. Published isochlors, where they were interpreted by regional aquifer, were used as much as possible for this regional isochlor assessment. Publication dates for the isochlors used range from 1982 to 2015, and the scales for the isochlors range from local (county or municipality) to state (sub-regional) to regional. The USGS National Water Information System database provided well sample data for the parts of aquifers that are mainly beneath the land areas and yielded 37,517 water-quality records for 1903 through 2011. Published data reports from four phases of research-related offshore coring (1976, 1993, 1997, 2009) were the main source of water-quality data for the parts of aquifers from the shoreline to the outer edge of the Continental Shelf and yielded samples from multiple depths of each of 13 cores. This study also used interpretations and offshore core data from the last regional chloride assessment (1989) which, in addition to 7 offshore cores, included water-quality data from about 500 wells, and borehole geophysics interpretations from a subset of 11 wells. All published information and data that were used in this study were considered time independent and did not assess the published interpretations or data for temporal trends. The approach used here examined only published interpretations and available chloride data, and did not directly use supplemental techniques that can provide insight into the distribution of saltwater, such as geochemical characterization, borehole geophysical information, and geochronology.
\nIsochlor maps for this study are limited to manual interpretations of the 250-milligram per liter (mg/L) and 10,000-mg/L boundaries developed for 9 of the 10 regional aquifers that constitute the regional hydrogeologic framework of the Northern Atlantic Coastal Plain. For a given aquifer, the approach was to initially consider published isochlor interpretations, where available, then to modify the published interpretations, if necessary, to the extent indicated by the well and core samples. The final step was to interpolate isochlors to the full extent of each aquifer layer in areas with sufficient samples or cited interpretations, or to extrapolate isochlors in areas with no samples or where samples were sparse.
\nThe principal limitation of this study is that, because of its regional extent, data and information density can vary greatly, and thus confidence in interpretations can vary widely for onshore and offshore areas across the study area. In areas of sparse data, some samples of elevated chloride could be misinterpreted as being part of a regional elevated chloride trend, and in other cases, an elevated concentration could be misinterpreted as being of only local importance. The interpretive work of this study was applied to a 1:2,000,000 scale base map. Locations of isochlors, wells, cores, political boundaries, and shorelines are meant to be considered approximate.
\nThe isochlors presented in this study were manually interpreted for each aquifer unit as a conceptual representation of an equal concentration line approximately in the middle of an aquifer’s thickness. Differences in chloride concentration lines between the top and bottom of an aquifer could be substantial, especially for the thick parts of aquifers, but that information is not presented in this regional assessment.
\nAlthough additional offshore chloride data are available compared to 27 years ago (1989), the offshore information remains sparse, resulting in less confidence in the offshore interpretations than in the onshore interpretations. Regionally, the 250- and 10,000-mg/L isochlors tend to map progressively eastward from the deepest to the shallowest aquifers across the Northern Atlantic Coastal Plain aquifer system but with some exceptions. The additional data, conceptual understanding, and interpretations in the vicinity of the buried Chesapeake Bay impact structure in eastern Virginia resulted in substantial refinement of isochlors in that area. Overall, the interpretations in this study are updates of the previous regional study from 1989 but do not comprise major differences in interpretation and do not indicate regional movement of the freshwater-saltwater interface since then.
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Groundwater is the Nation’s principal reserve of freshwater. It provides about half our drinking water, is essential to food production, and facilitates business and industry in developing economic well-being. Groundwater is also an important source of water for sustaining the ecosystem health of rivers, wetlands, and estuaries throughout the country. The decreases in groundwater levels and other effects of pumping that result from large-scale development of groundwater resources have led to concerns about the future availability of groundwater to meet all our Nation’s needs. Assessments of groundwater availability provide the science and information needed by the public and decision makers to manage water resources and use them responsibly.
\nThe U.S. Geological Survey (USGS) is conducting large-scale multidisciplinary regional studies of groundwater availability as part of its ongoing assessments of the principal aquifers of the Nation. These regional studies are intended to provide citizens, communities, and natural resource managers with knowledge of the status of the Nation’s groundwater resources and how changes in land use, water use, and climate have affected and are likely to affect those resources now and in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163046","usgsCitation":"Masterson, J.P., and Pope, J.P., 2016, Sustainability of groundwater supplies in the Northern Atlantic Coastal Plain aquifer system: U.S. Geological Survey Fact Sheet 2016–3046, 6 p., https://dx.doi.org/10.3133/fs20163046.","productDescription":"Report: 6 p.; Data Releases","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-071395","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":326349,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165076","text":"Scientific Investigations Report 2016–5076 -","description":"FS 2016-3046","linkHelpText":"Documentation of a Groundwater Flow Model Developed To Assess Groundwater Availability in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326348,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165034","text":"Scientific Investigations Report 2016–5034 -","description":"FS 2016-3046","linkHelpText":"Regional Chloride Distribution in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326347,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/pp1829","text":"Professional Paper 1829 -","description":"FS 2016-3046","linkHelpText":"Assessment of Groundwater Availability in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326346,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ds996","text":"Data Series 996 -","description":"FS 2016-3046","linkHelpText":"Digital Elevations and Extents of Regional Hydrogeologic Units in the Northern Atlantic Coastal Plain Aquifer System From Long Island, New York, to North Carolina"},{"id":326345,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3046/fs20163046.pdf","text":"Report","size":"2.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3046"},{"id":326344,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3046/coverthb.jpg"},{"id":326845,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7MG7MKR","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-NWT model"},{"id":326846,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F70V89WN","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital elevations and extents of hydrogeologic units"},{"id":327885,"rank":9,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/wausp/","text":"USGS Water Availability and Use Science Program","description":"Project Site"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.71875,\n 41.244772343082104\n ],\n [\n -72.861328125,\n 41.22824901518532\n ],\n [\n -73.93798828125,\n 40.830436877649255\n ],\n [\n -75.78369140625,\n 39.707186656826565\n ],\n [\n -77.080078125,\n 38.94232097947902\n ],\n [\n -77.62939453125,\n 38.39333888832238\n ],\n [\n -77.62939453125,\n 37.56199695314352\n ],\n [\n -77.5634765625,\n 36.82687474287728\n ],\n [\n -78.02490234375,\n 35.88905007936091\n ],\n [\n -75.6298828125,\n 34.63320791137959\n ],\n [\n -74.4873046875,\n 36.06686213257888\n ],\n [\n -71.103515625,\n 40.64730356252251\n ],\n [\n -71.71875,\n 41.244772343082104\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Water Availability and Use Science Program
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No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reintroduction of fish and wildlife populations","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Unviersity of California Press","publisherLocation":"Oakland, CA","isbn":"9780520284616","usgsCitation":"Dunham, J.B., White, R., Allen, C.S., Marcot, B.G., and Shively, D., 2016, The reintroduction landscape: Finding success at the intersection of ecological, social, and institutional dimensions, chap. 5 of Reintroduction of fish and wildlife populations.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062356","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":328097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328096,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520284616"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7f1afe4b0f2f0cebf11b9","contributors":{"editors":[{"text":"Jachowski, David S.","contributorId":82966,"corporation":false,"usgs":true,"family":"Jachowski","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":647706,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Millspaugh, Joshua J.","contributorId":22082,"corporation":false,"usgs":true,"family":"Millspaugh","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":647707,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Angermeier, Paul L. biota@usgs.gov","contributorId":1432,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":613,"text":"Virginia Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":647708,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Slotow, Rob","contributorId":174198,"corporation":false,"usgs":false,"family":"Slotow","given":"Rob","email":"","affiliations":[],"preferred":false,"id":647709,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"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":646994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Rollie","contributorId":174030,"corporation":false,"usgs":false,"family":"White","given":"Rollie","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":646995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Chris S","contributorId":174031,"corporation":false,"usgs":false,"family":"Allen","given":"Chris","email":"","middleInitial":"S","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":646996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marcot, Bruce G.","contributorId":152612,"corporation":false,"usgs":false,"family":"Marcot","given":"Bruce","email":"","middleInitial":"G.","affiliations":[{"id":18944,"text":"Pacific Northwest Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":646997,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shively, Dan","contributorId":42341,"corporation":false,"usgs":true,"family":"Shively","given":"Dan","email":"","affiliations":[],"preferred":false,"id":646998,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176143,"text":"70176143 - 2016 - Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2016-08-31T10:13:26","indexId":"70176143","displayToPublicDate":"2016-08-31T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico","docAbstract":"We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JC011482","usgsCitation":"Plant, N.G., Wahl, T., and Long, J.W., 2016, Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico: Journal of Geophysical Research C: Oceans, v. 121, no. 5, p. 3029-3043, https://doi.org/10.1002/2015JC011482.","productDescription":"15 p.","startPage":"3029","endPage":"3043","ipdsId":"IP-070871","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470631,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://eprints.soton.ac.uk/393754/2/pdf","text":"External Repository"},{"id":328093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"5","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"57c7f1abe4b0f2f0cebf11ad","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":647454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, Thomas","contributorId":141017,"corporation":false,"usgs":false,"family":"Wahl","given":"Thomas","email":"","affiliations":[{"id":13653,"text":"University South Florida","active":true,"usgs":false}],"preferred":false,"id":647455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647456,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176157,"text":"70176157 - 2016 - Model calibration criteria for estimating ecological flow characteristics","interactions":[],"lastModifiedDate":"2018-04-02T15:27:59","indexId":"70176157","displayToPublicDate":"2016-08-31T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Model calibration criteria for estimating ecological flow characteristics","docAbstract":"Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those envisioned by the modelers. While the estimation of model parameters for ungauged catchments is a challenging research task in itself, it is important to evaluate whether simulated time series preserve critical aspects of the streamflow hydrograph. To address this question, seven calibration objective functions were evaluated for their ability to preserve ecologically relevant streamflow characteristics of the average annual hydrograph using a runoff model, HBV-light, at 27 catchments in the southeastern United States. Calibration trials were repeated 100 times to reduce parameter uncertainty effects on the results, and 12 ecological flow characteristics were computed for comparison. Our results showed that the most suitable calibration strategy varied according to streamflow characteristic. Combined objective functions generally gave the best results, though a clear underprediction bias was observed. The occurrence of low prediction errors for certain combinations of objective function and flow characteristic suggests that (1) incorporating multiple ecological flow characteristics into a single objective function would increase model accuracy, potentially benefitting decision-making processes; and (2) there may be a need to have different objective functions available to address specific applications of the predicted time series.
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","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Catalog of type specimens of recent mammals: Orders Carnivora, Perissodactyla, Artiodactyla, and Cetacea in the National Museum of Natural History: Smithsonian Contributions to Zoology No. 646","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Smithsonian Institution","publisherLocation":"Washington, D.C.","doi":"10.5479/si.19436696.646","usgsCitation":"Reynolds, R., and Helgen, K.M., 2016, Forward, chap. of Catalog of type specimens of recent mammals: Orders Carnivora, Perissodactyla, Artiodactyla, and Cetacea in the National Museum of Natural History: Smithsonian Contributions to Zoology No. 646, v. 646, p. 1-2, https://doi.org/10.5479/si.19436696.646.","productDescription":"2 p.","startPage":"1","endPage":"2","ipdsId":"IP-068591","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":462107,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5479/si.19436696.646","text":"Publisher Index Page"},{"id":328095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"646","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"57c7f1a9e4b0f2f0cebf11a7","contributors":{"editors":[{"text":"Fisher, Robert D. 0000-0002-2956-3240 rdfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":3913,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rdfisher@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":647596,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Ludwig, Craig A.","contributorId":19045,"corporation":false,"usgs":true,"family":"Ludwig","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":647597,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Reynolds, Robert rpreynolds@usgs.gov","contributorId":174065,"corporation":false,"usgs":true,"family":"Reynolds","given":"Robert","email":"rpreynolds@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":647128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helgen, Kristopher M.","contributorId":174066,"corporation":false,"usgs":false,"family":"Helgen","given":"Kristopher","email":"","middleInitial":"M.","affiliations":[{"id":27353,"text":"Division of Mammals, National Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":647129,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176162,"text":"70176162 - 2016 - Temperature is better than precipitation as a predictor of plant community assembly across a dryland region","interactions":[],"lastModifiedDate":"2016-09-16T16:21:53","indexId":"70176162","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Temperature is better than precipitation as a predictor of plant community assembly across a dryland region","docAbstract":"How closely do plant communities track climate? Research suggests that plant species converge toward similar environmental tolerances relative to the environments that they experience. Whether these patterns apply to severe environments or scale up to plant community-level patterns of relative climatic tolerances is poorly understood. Using estimates of species' climatic tolerances acquired from occurrence records, we determined the contributions of individual species' climatic niche breadths and environmental filtering to the relationships between community-average climatic tolerances and the local climates experienced by those communities.
Southwestern United States drylands.
Interspecific variation in niche breadth was assessed as a function of species' climatic optima (median climatic niche value). The relationships between climatic optima and tolerances were used as null expectations for the relationship between abundance-weighted mean climatic tolerances of communities and the local climate of that community. Deviations from this null expectation indicate that species with greater or lesser climatic tolerances are favoured relative to co-occurring species. The intensity of environmental filtering was estimated by comparing the range of climatic tolerances within each community to a null distribution generated from a random assembly algorithm.
The temperature niches of species were consistently symmetrical and of similar breadths, regardless of their temperature optima. In contrast, precipitation niches were skewed toward wetter conditions, and niche breadth increased with increasing precipitation optima. At the community level, relationships with climate were much stronger for temperature than for precipitation. Furthermore, cold and heat were stronger assembly filters than drought or precipitation, with the intensity of environmental filtering increasing at both ends of climatic gradients. Community-average climatic tolerances did deviate significantly from null expectations, indicating that species with higher or lower relative climatic tolerances were favoured under certain conditions.
Despite strong water limitation of plant performance in dryland ecosystems, communities tracked variation in temperature much more closely, intimating strong responses to anticipated temperature increases. Furthermore, abundance distributions were biased toward species with higher or lower relative climatic tolerances under different climatic conditions, but predictably so, indicating the need for assembly models that include processes other than simple environmental filtering.
","language":"English","publisher":"International Association for Vegetation Science","publisherLocation":"Uppsala, Sweden","doi":"10.1111/jvs.12440","usgsCitation":"Butterfield, B.J., and Munson, S.M., 2016, Temperature is better than precipitation as a predictor of plant community assembly across a dryland region: Journal of Vegetation Science, v. 27, no. 5, p. 938-947, https://doi.org/10.1111/jvs.12440.","productDescription":"10 p.","startPage":"938","endPage":"947","ipdsId":"IP-060796","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":328089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"27","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-04","publicationStatus":"PW","scienceBaseUri":"57c7f1afe4b0f2f0cebf11b7","contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":647521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":647520,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175747,"text":"70175747 - 2016 - Methods for exploring uncertainty in groundwater management predictions","interactions":[],"lastModifiedDate":"2016-09-01T13:13:07","indexId":"70175747","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Methods for exploring uncertainty in groundwater management predictions","docAbstract":"Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Integrated groundwater management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-319-23576-9_28","isbn":"978-3-319-23575-2","usgsCitation":"Guillaume, J.H., Hunt, R.J., Comunian, A., Fu, B., and Blakers, R.S., 2016, Methods for exploring uncertainty in groundwater management predictions, chap. of Integrated groundwater management, p. 711-737, https://doi.org/10.1007/978-3-319-23576-9_28.","productDescription":"27 p.","startPage":"711","endPage":"737","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057337","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":488538,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-319-23576-9_28","text":"Publisher Index Page"},{"id":328111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c7f1a9e4b0f2f0cebf11a9","contributors":{"editors":[{"text":"Jakeman, Anthony J. 0000-0001-5282-2215","orcid":"https://orcid.org/0000-0001-5282-2215","contributorId":173848,"corporation":false,"usgs":false,"family":"Jakeman","given":"Anthony","email":"","middleInitial":"J.","affiliations":[{"id":17939,"text":"The Australian National University","active":true,"usgs":false}],"preferred":false,"id":647604,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Barreteau, Olivier","contributorId":173849,"corporation":false,"usgs":false,"family":"Barreteau","given":"Olivier","email":"","affiliations":[{"id":27301,"text":"IRSTEA - UMR G-EAU (France)","active":true,"usgs":false}],"preferred":false,"id":647605,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647606,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Rinaudo, Jean-Daniel","contributorId":173850,"corporation":false,"usgs":false,"family":"Rinaudo","given":"Jean-Daniel","email":"","affiliations":[{"id":27302,"text":"BRGM (France)","active":true,"usgs":false}],"preferred":false,"id":647607,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Ross, Andrew","contributorId":173851,"corporation":false,"usgs":false,"family":"Ross","given":"Andrew","email":"","affiliations":[{"id":13328,"text":"UNESCO-IHE","active":true,"usgs":false}],"preferred":false,"id":647608,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Guillaume, Joseph H. A.","contributorId":173856,"corporation":false,"usgs":false,"family":"Guillaume","given":"Joseph","email":"","middleInitial":"H. A.","affiliations":[{"id":6718,"text":"Aalto University, Finland","active":true,"usgs":false}],"preferred":false,"id":646295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":646294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Comunian, Alessandro","contributorId":173857,"corporation":false,"usgs":false,"family":"Comunian","given":"Alessandro","email":"","affiliations":[{"id":27304,"text":"University of New South Wales","active":true,"usgs":false}],"preferred":false,"id":646296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fu, Baihua 0000-0003-2494-0518","orcid":"https://orcid.org/0000-0003-2494-0518","contributorId":174165,"corporation":false,"usgs":false,"family":"Fu","given":"Baihua","email":"","affiliations":[],"preferred":false,"id":647603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blakers, Rachel S","contributorId":173858,"corporation":false,"usgs":false,"family":"Blakers","given":"Rachel","email":"","middleInitial":"S","affiliations":[{"id":27305,"text":"Australia National University","active":true,"usgs":false}],"preferred":false,"id":646297,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176280,"text":"70176280 - 2016 - Summer-autumn habitat use of yearling rainbow trout in two streams in the Lake Ontario watershed","interactions":[],"lastModifiedDate":"2016-09-07T12:42:34","indexId":"70176280","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2948,"text":"Open Fish Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Summer-autumn habitat use of yearling rainbow trout in two streams in the Lake Ontario watershed","docAbstract":"Understanding the habitat requirements of salmonids in streams is an important component of fisheries management. We examined the summer and autumn habitat use of yearling Rainbow Trout Oncorhynchus mykiss in relation to available habitat in two streams in the Lake Ontario watershed. Little interstream variation in trout habitat use was observed; the variation that did occur was largely due to differences between streams in available habitat in the autumn. In both streams, yearling Rainbow Trout utilized pool habitat and during periods of high stream discharge were associated with larger substrate that may provide a velocity barrier. These findings may assist resource managers in their efforts to protect and restore habitat for migratory Rainbow Trout in the Lake Ontario watershed.
","language":"English","publisher":"Bentham Science Publishers","doi":"10.2174/1874401X01609010045","usgsCitation":"Johnson, J.H., McKenna, J., and Chalupnicki, M., 2016, Summer-autumn habitat use of yearling rainbow trout in two streams in the Lake Ontario watershed: Open Fish Science Journal, v. 9, p. 45-50, https://doi.org/10.2174/1874401X01609010045.","productDescription":"6 p.","startPage":"45","endPage":"50","ipdsId":"IP-075868","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470634,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2174/1874401x01609010045","text":"Publisher Index Page"},{"id":328311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Grout Brook, Orwell Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.29592895507812,\n 42.71296638907414\n ],\n [\n -76.29592895507812,\n 42.80295793799244\n ],\n [\n -76.23310089111328,\n 42.80295793799244\n ],\n [\n -76.23310089111328,\n 42.71296638907414\n ],\n [\n -76.29592895507812,\n 42.71296638907414\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.02573394775389,\n 43.5107129908437\n ],\n [\n -76.02573394775389,\n 43.611471040985286\n ],\n [\n -75.970458984375,\n 43.611471040985286\n ],\n [\n -75.970458984375,\n 43.5107129908437\n ],\n [\n -76.02573394775389,\n 43.5107129908437\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57d13a40e4b0571647cf8e11","contributors":{"authors":[{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKenna, James E. Jr. 0000-0002-1428-7597 jemckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-1428-7597","contributorId":627,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","suffix":"Jr.","email":"jemckenna@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":648188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalupnicki, Marc 0000-0002-3792-9345 mchalupnicki@usgs.gov","orcid":"https://orcid.org/0000-0002-3792-9345","contributorId":173643,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":648189,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176185,"text":"70176185 - 2016 - Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed","interactions":[],"lastModifiedDate":"2016-08-31T14:46:03","indexId":"70176185","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed","docAbstract":"Estimating streamwater solute loads is a central objective of many water-quality monitoring and research studies, as loads are used to compare with atmospheric inputs, to infer biogeochemical processes, and to assess whether water quality is improving or degrading. In this study, we evaluate loads and associated errors to determine the best load estimation technique among three methods (a period-weighted approach, the regression-model method, and the composite method) based on a solute's concentration dynamics and sampling frequency. We evaluated a broad range of varying concentration dynamics with stream flow and season using four dissolved solutes (sulfate, silica, nitrate, and dissolved organic carbon) at five diverse small watersheds (Sleepers River Research Watershed, VT; Hubbard Brook Experimental Forest, NH; Biscuit Brook Watershed, NY; Panola Mountain Research Watershed, GA; and Río Mameyes Watershed, PR) with fairly high-frequency sampling during a 10- to 11-yr period. Data sets with three different sampling frequencies were derived from the full data set at each site (weekly plus storm/snowmelt events, weekly, and monthly) and errors in loads were assessed for the study period, annually, and monthly. For solutes that had a moderate to strong concentration–discharge relation, the composite method performed best, unless the autocorrelation of the model residuals was <0.2, in which case the regression-model method was most appropriate. For solutes that had a nonexistent or weak concentration–discharge relation (modelR2 < about 0.3), the period-weighted approach was most appropriate. The lowest errors in loads were achieved for solutes with the strongest concentration–discharge relations. Sample and regression model diagnostics could be used to approximate overall accuracies and annual precisions. For the period-weighed approach, errors were lower when the variance in concentrations was lower, the degree of autocorrelation in the concentrations was higher, and sampling frequency was higher. The period-weighted approach was most sensitive to sampling frequency. For the regression-model and composite methods, errors were lower when the variance in model residuals was lower. For the composite method, errors were lower when the autocorrelation in the residuals was higher. Guidelines to determine the best load estimation method based on solute concentration–discharge dynamics and diagnostics are presented, and should be applicable to other studies.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1298","usgsCitation":"Aulenbach, B.T., Burns, D.A., Shanley, J.B., Yanai, R.D., Bae, K., Wild, A., Yang, Y., and Yi, D., 2016, Approaches to stream solute load estimation for solutes with varying dynamics from five diverse small watershed: Ecosphere, v. 7, no. 6, e01298; 22 p., https://doi.org/10.1002/ecs2.1298.","productDescription":"e01298; 22 p.","ipdsId":"IP-065579","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1298","text":"Publisher Index Page"},{"id":328145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-17","publicationStatus":"PW","scienceBaseUri":"57c7f1a3e4b0f2f0cebf119f","contributors":{"authors":[{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":647651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yanai, Ruth D.","contributorId":59720,"corporation":false,"usgs":true,"family":"Yanai","given":"Ruth","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":647652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bae, Kikang","contributorId":174183,"corporation":false,"usgs":false,"family":"Bae","given":"Kikang","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wild, Adam","contributorId":174184,"corporation":false,"usgs":false,"family":"Wild","given":"Adam","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yang, Yang","contributorId":174185,"corporation":false,"usgs":false,"family":"Yang","given":"Yang","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yi, Dong","contributorId":174186,"corporation":false,"usgs":false,"family":"Yi","given":"Dong","email":"","affiliations":[{"id":27381,"text":"State University of New York, College of Environmental Science and Forestry, Syracuse, NY","active":true,"usgs":false}],"preferred":false,"id":647656,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70176817,"text":"70176817 - 2016 - Spatial distribution of thermokarst terrain in Arctic Alaska","interactions":[],"lastModifiedDate":"2016-10-12T14:10:01","indexId":"70176817","displayToPublicDate":"2016-08-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution of thermokarst terrain in Arctic Alaska","docAbstract":"In landscapes underlain by ice-rich permafrost, the development of thermokarst landforms can have drastic impacts on ecosystem processes and human infrastructure. Here we describe the distribution of thermokarst landforms in the continuous permafrost zone of Arctic Alaska, analyze linkages to the underlying surficial geology, and discuss the vulnerability of different types of landscapes to future thaw. We identified nine major thermokarst landforms and then mapped their distributions in twelve representative study areas totaling 300-km2. These study areas differ in their geologic history, permafrost-ice content, and ground thermal regime. Results show that 63% of the entire study area is occupied by thermokarst landforms and that the distribution of thermokarst landforms and overall landscape complexity varies markedly with surficial geology. Areas underlain by ice-rich marine silt are the most affected by thermokarst (97% of total area), whereas areas underlain by glacial drift are least affected (14%). Drained thermokarst-lake basins are the most widespread thermokarst landforms, covering 33% of the entire study region, with greater prevalence in areas of marine silt (48% coverage), marine sand (47%), and aeolian silt (34%). Thermokarst-lakes are the second most common thermokarst landform, covering 16% of the study region, with highest coverage in areas underlain by marine silt (39% coverage). Thermokarst troughs and pits cover 7% of the study region and are the third most prevalent thermokarst landform. They are most common in areas underlain by deltaic sands and gravels (18% coverage) and marine sand (12%). Alas valleys are widespread in areas of aeolian silt (14%) located in gradually sloping uplands. Areas of marine silt have been particularly vulnerable to thaw in the past because they are ice-rich and have low-gradient topography facilitating the repeated development of thermokarst-lakes. In the future, ice-rich aeolian, upland terrain (yedoma) will be particularly susceptible to thaw because it still contains massive concentrations of ground ice in the form of syngenetic ice-wedges that have remained largely intact since the Pleistocene.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2016.08.007","usgsCitation":"Farquharson, L.M., Mann, D.H., Grosse, G., Jones, B.M., and Romanovsky, V., 2016, Spatial distribution of thermokarst terrain in Arctic Alaska: Geomorphology, v. 273, p. 116-133, https://doi.org/10.1016/j.geomorph.2016.08.007.","productDescription":"18 p.","startPage":"116","endPage":"133","ipdsId":"IP-074641","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":470633,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://epic.awi.de/id/eprint/41744/","text":"Publisher Index Page"},{"id":329491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160,\n 68.5\n ],\n [\n -160,\n 71.5\n ],\n [\n -149,\n 71.5\n ],\n [\n -149,\n 68.5\n ],\n [\n -160,\n 68.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"273","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ff4bf7e4b0824b2d159765","chorus":{"doi":"10.1016/j.geomorph.2016.08.007","url":"http://dx.doi.org/10.1016/j.geomorph.2016.08.007","publisher":"Elsevier BV","authors":"Farquharson L.M., Mann D.H., Grosse G., Jones B.M., Romanovsky V.E.","journalName":"Geomorphology","publicationDate":"11/2016"},"contributors":{"authors":[{"text":"Farquharson, Louise M.","contributorId":175206,"corporation":false,"usgs":false,"family":"Farquharson","given":"Louise","middleInitial":"M.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":650414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mann, Daniel H.","contributorId":175207,"corporation":false,"usgs":false,"family":"Mann","given":"Daniel","middleInitial":"H.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":650415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":650416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":650413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romanovsky, Vladimir","contributorId":175208,"corporation":false,"usgs":false,"family":"Romanovsky","given":"Vladimir","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":650417,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}