Evapotranspiration (ET) is an important component of the water cycle – ET from the land surface returns approximately 60% of the global precipitation back to the atmosphere. ET also plays an important role in energy transport among the biosphere, atmosphere, and hydrosphere. Current regional to global and daily to annual ET estimation relies mainly on surface energy balance (SEB) ET models or statistical and empirical methods driven by remote sensing data and various climatological databases. These models have uncertainties due to inevitable input errors, poorly defined parameters, and inadequate model structures. The eddy covariance measurements on water, energy, and carbon fluxes at the AmeriFlux tower sites provide an opportunity to assess the ET modeling uncertainties. In this study, we focused on uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model for ET estimation at multiple AmeriFlux tower sites with diverse land cover characteristics and climatic conditions. The 8-day composite 1-km MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) was used as input land surface temperature for the SSEBop algorithms. The other input data were taken from the AmeriFlux database. Results of statistical analysis indicated that the SSEBop model performed well in estimating ET with an R2 of 0.86 between estimated ET and eddy covariance measurements at 42 AmeriFlux tower sites during 2001–2007. It was encouraging to see that the best performance was observed for croplands, where R2 was 0.92 with a root mean square error of 13 mm/month. The uncertainties or random errors from input variables and parameters of the SSEBop model led to monthly ET estimates with relative errors less than 20% across multiple flux tower sites distributed across different biomes. This uncertainty of the SSEBop model lies within the error range of other SEB models, suggesting systematic error or bias of the SSEBop model is within the normal range. This finding implies that the simplified parameterization of the SSEBop model did not significantly affect the accuracy of the ET estimate while increasing the ease of model setup for operational applications. The sensitivity analysis indicated that the SSEBop model is most sensitive to input variables, land surface temperature (LST) and reference ET (ETo); and parameters, differential temperature (dT), and maximum ET scalar (Kmax), particularly during the non-growing season and in dry areas. In summary, the uncertainty assessment verifies that the SSEBop model is a reliable and robust method for large-area ET estimation. The SSEBop model estimates can be further improved by reducing errors in two input variables (ETo and LST) and two key parameters (Kmax and dT).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.02.026","usgsCitation":"Chen, M., Senay, G.B., Singh, R.K., and Verdin, J.P., 2016, Uncertainty analysis of the Operational Simplified Surface Energy Balance (SSEBop) model at multiple flux tower sites: Journal of Hydrology, v. 536, p. 384-399, https://doi.org/10.1016/j.jhydrol.2016.02.026.","productDescription":"16 p.","startPage":"384","endPage":"399","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071555","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471180,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.02.026","text":"Publisher Index Page"},{"id":330417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"536","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f3e4b0f497e79a5a7b","chorus":{"doi":"10.1016/j.jhydrol.2016.02.026","url":"http://dx.doi.org/10.1016/j.jhydrol.2016.02.026","publisher":"Elsevier BV","authors":"Chen Mingshi, Senay Gabriel B., Singh Ramesh K., Verdin James P.","journalName":"Journal of Hydrology","publicationDate":"5/2016","auditedOn":"4/1/2016","publiclyAccessibleDate":"2/23/2016"},"contributors":{"authors":[{"text":"Chen, Mingshi mchen@usgs.gov","contributorId":4204,"corporation":false,"usgs":true,"family":"Chen","given":"Mingshi","email":"mchen@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":652026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":652237,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168397,"text":"ds977 - 2016 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014","interactions":[{"subject":{"id":70135103,"text":"ds892 - 2014 - DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge","indexId":"ds892","publicationYear":"2014","noYear":false,"title":"DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge"},"predicate":"SUPERSEDED_BY","object":{"id":70168397,"text":"ds977 - 2016 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014","indexId":"ds977","publicationYear":"2016","noYear":false,"title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014"},"id":1},{"subject":{"id":70168397,"text":"ds977 - 2016 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014","indexId":"ds977","publicationYear":"2016","noYear":false,"title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014"},"predicate":"SUPERSEDED_BY","object":{"id":70176575,"text":"ds1021 - 2017 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015","indexId":"ds1021","publicationYear":"2017","noYear":false,"title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015"},"id":2}],"supersededBy":{"id":70176575,"text":"ds1021 - 2017 - DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015","indexId":"ds1021","publicationYear":"2017","noYear":false,"title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015"},"lastModifiedDate":"2017-02-09T12:51:41","indexId":"ds977","displayToPublicDate":"2016-03-04T10:00:00","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":"977","title":"DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014","docAbstract":"This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2014; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds977","usgsCitation":"Urban, F.E., and Clow, G.D., 2016, DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014: U.S. Geological Survey Data Series 977, https://dx.doi.org/10.3133/ds977.","productDescription":"HTML Document; 17 chapters","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069148","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":318058,"rank":19,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Ikpikpuk/Ikpikpuk.html","text":"Ikpikpuk","description":"DS 977 Ikpikpuk"},{"id":318055,"rank":16,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/DrewPoint/DrewPoint.html","text":"Drew Point","description":"DS 977 Drew Point"},{"id":318045,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Lake145/Lake145.html","text":"Lake 145","description":"DS 977 Lake 145"},{"id":318054,"rank":15,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/CamdenBay/CamdenBay.html","text":"Camden Bay","description":"DS 977 Camden Bay"},{"id":318047,"rank":9,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Niguanak/Niguanak.html","text":"Niguanak","description":"DS 977 Niguanak"},{"id":318051,"rank":13,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Awuna1/Awuna1.html","text":" Awuna1","description":"DS 977 Awuna1"},{"id":318056,"rank":17,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/EastTeshekpuk/EastTeshekpuk.html","text":"East Teshekpuk","description":"DS 977 East Teshekpuk"},{"id":318011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0977/images/coverthb.jpg"},{"id":318042,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Inigok/Inigok.html","text":"Inigok","description":"DS 977 Inigok"},{"id":318046,"rank":8,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/MarshCreek/MarshCreek.html","text":"Marsh Creek","description":"DS 977 Marsh Creek"},{"id":318048,"rank":10,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Piksiksak/Piksiksak.html","text":"Piksiksak","description":"DS 977 Piksiksak"},{"id":318049,"rank":11,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/RedSheepCreek/RedSheepCreek.html","text":"Red Sheep Creek","description":"DS 977 Red Sheep Creek"},{"id":318043,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Koluktak/Koluktak.html","text":"Koluktak","description":"DS 977 Koluktak"},{"id":318053,"rank":14,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Awuna2/Awuna2.html","text":" Awuna2","description":"DS 977 Awuna2"},{"id":318057,"rank":18,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/FishCreek/FishCreek.html","text":"Fish Creek","description":"DS 977 Fish Creek"},{"id":318050,"rank":12,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/SouthMeade/SouthMeade.html","text":"South Meade","description":"DS 977 South Meade"},{"id":318012,"rank":2,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/introduction.html","text":"Introduction","description":"DS 977 Introduction"},{"id":318013,"rank":3,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Tunalik/Tunalik.html","text":"Tunalik","description":"DS 977 Tunalik"},{"id":318014,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://pubs.usgs.gov/ds/0977/Umiat/Umiat.html","text":"Umiat","description":"DS 977 Umiat"}],"country":"Canada, 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 -163.037109375,\n 66.08936427047088\n ],\n [\n -163.037109375,\n 71.66366293141732\n ],\n [\n -140.712890625,\n 71.66366293141732\n ],\n [\n -140.712890625,\n 66.08936427047088\n ],\n [\n -163.037109375,\n 66.08936427047088\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
Mangrove forests grow on saline, periodically flooded soils of the tropical and subtropical coasts. The tree species that comprise the mangrove are halophytes that have suites of traits that confer differing levels of tolerance of salinity, aridity, inundation and extremes of temperature. Here we review how climate change and elevated levels of atmospheric CO2 will influence mangrove forests. Tolerance of salinity and inundation in mangroves is associated with the efficient use of water for photosynthetic carbon gain which unpins anticipated gains in productivity with increasing levels of CO2. We review evidence of increases in productivity with increasing CO2, finding that enhancements in growth appear to be similar to trees in non-mangrove habitats and that gains in productivity with elevated CO2 are likely due to changes in biomass allocation. High levels of trait plasticity are observed in some mangrove species, which potentially facilitates their responses to climate change. Trait plasticity is associated with broad tolerance of salinity, aridity, low temperatures and nutrient availability. Because low temperatures and aridity place strong limits on mangrove growth at the edge of their current distribution, increasing temperatures over time and changing rainfall patterns are likely to have an important influence on the distribution of mangroves. We provide a global analysis based on plant traits and IPCC scenarios of changing temperature and aridity that indicates substantial global potential for mangrove expansion.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tree physiology: Adaptations and responses in a changing environment","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-27422-5_7","usgsCitation":"Lovelock, C.E., Krauss, K.W., Osland, M.J., Reef, R., and Ball, M.C., 2016, The physiology of mangrove trees with changing climate, chap. of Tree physiology: Adaptations and responses in a changing environment, v. 6, p. 149-179, https://doi.org/10.1007/978-3-319-27422-5_7.","productDescription":"31 p.","startPage":"149","endPage":"179","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060844","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":319976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"570e1c37e4b0ef3b7ca24c4c","contributors":{"editors":[{"text":"Meinzer, Frederick C.","contributorId":168571,"corporation":false,"usgs":false,"family":"Meinzer","given":"Frederick","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":626533,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Niinemets, Ulo","contributorId":168572,"corporation":false,"usgs":false,"family":"Niinemets","given":"Ulo","email":"","affiliations":[],"preferred":false,"id":626534,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Lovelock, Catherine E.","contributorId":64787,"corporation":false,"usgs":true,"family":"Lovelock","given":"Catherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":626520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":626518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osland, Michael J. 0000-0001-9902-8692 mosland@usgs.gov","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":3080,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","email":"mosland@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":626519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reef, Ruth","contributorId":44826,"corporation":false,"usgs":true,"family":"Reef","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":626521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ball, Marilyn C.","contributorId":7981,"corporation":false,"usgs":true,"family":"Ball","given":"Marilyn","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":626522,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70164631,"text":"sir20165020 - 2016 - Groundwater quality, age, and susceptibility and vulnerability to nitrate contamination with linkages to land use and groundwater flow, Upper Black Squirrel Creek Basin, Colorado, 2013","interactions":[],"lastModifiedDate":"2016-03-09T17:48:45","indexId":"sir20165020","displayToPublicDate":"2016-03-03T18:00:00","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":"2016-5020","title":"Groundwater quality, age, and susceptibility and vulnerability to nitrate contamination with linkages to land use and groundwater flow, Upper Black Squirrel Creek Basin, Colorado, 2013","docAbstract":"The Upper Black Squirrel Creek Basin is located about 25 kilometers east of Colorado Springs, Colorado. The primary aquifer is a productive section of unconsolidated deposits that overlies bedrock units of the Denver Basin and is a critical resource for local water needs, including irrigation, domestic, and commercial use. The primary aquifer also serves an important regional role by the export of water to nearby communities in the Colorado Springs area. Changes in land use and development over the last decade, which includes substantial growth of subdivisions in the Upper Black Squirrel Creek Basin, have led to uncertainty regarding the potential effects to water quality throughout the basin. In response, the U.S. Geological Survey, in cooperation with Cherokee Metropolitan District, El Paso County, Meridian Service Metropolitan District, Mountain View Electric Association, Upper Black Squirrel Creek Groundwater Management District, Woodmen Hills Metropolitan District, Colorado State Land Board, and Colorado Water Conservation Board, and the stakeholders represented in the Groundwater Quality Study Committee of El Paso County conducted an assessment of groundwater quality and groundwater age with an emphasis on characterizing nitrate in the groundwater.
\nGroundwater-quality samples were collected from 50 randomly selected wells between May and June 2013. The samples were analyzed for major ions, nutrients, dissolved gases, tritium (3H), chlorofluorocarbons (CFC-11, CFC-12, and CFC-113), and fuel products (such as benzene, toluene, ethylbenzene, and xylenes). None of the groundwater samples exceeded the U.S. Environmental Protection Agency (EPA) National Primary Drinking Water Regulations for primary maximum contaminant levels (MCL) for major ions. Secondary maximum contaminant levels, which are not health concerns and affect mainly taste, color, or odor of the water, were observed in rare instances for pH (2 samples), chloride (1 sample), iron (3 samples), and manganese (8 samples). The secondary maximum contaminant level for total dissolved solids was also exceeded for two samples.
\nNitrate (nitrite plus nitrate as nitrogen in groundwater) was elevated above the estimated background concentration of natural recharge waters of 1 milligram per liter (mg/L) in 44 of the 50 wells sampled and showed a median concentration of 5.4 mg/L. Nitrate concentrations were above the MCL of 10 mg/L in 5 of the 50 wells sampled and above half of the EPA MCL (5 mg/L) in 27 of the 50 wells sampled, which included samples above the MCL. Dissolved-oxygen concentrations exceeded 0.5 mg/L in 95 percent of reported values (40 of 42 samples) and exceeded 2.0 mg/L in 90 percent of reported values (38 of 42 samples). The oxidized conditions observed in most areas indicate that nitrate from fertilizers and animal or human waste was geochemically stable and could persist in the groundwater for decades or perhaps longer. A historical analysis of median nitrate concentrations over nearly three decades showed an increase in nitrate of approximately 1 mg/L from 4.3 to 5.4 mg/L, although the increase was not determined to be significantly different using nonparametric statistical methods.
\nMajor-ion data indicate that groundwater representative of the primary aquifer was classified as calcium-sodium bicarbonate type water. Other water samples from wells located mainly along the periphery of the primary aquifer had cation-anion compositions consistent with distinct water sources, including groundwater contributions from the underlying bedrock aquifers. The areas with differentiable water sources were located mainly where alluvial deposits were thin and geologic contacts to the underlying bedrock aquifers were relatively shallow.
\nNitrate concentrations in the groundwater were evaluated for relations to land use. An agricultural region was defined using a sequence of land satellite imagery. Groundwater flow directions interpreted from median water-table elevations measured from 2000 to 2013 were used in conjunction with cropland locations to define the agricultural region boundaries by encompassing potential pathways of nitrate transport in the groundwater from nitrogen-based fertilizers. A statistically significant higher median nitrate concentration was observed for areas inside the agricultural region (6.7 mg/L) compared to areas outside the agricultural region (2.3 mg/L), although median concentrations in both areas were below the MCL (10 mg/L). Median nitrate concentration was also significantly greater in land parcels with septic use (4.9 mg/L) compared to nonseptic parcels (1.7 mg/L). In general, agriculture or septic use was identified as the primary source of nitrate, depending on location, while commercial, county, grazing, and residential land uses were generally secondary sources of nitrate.
\nApparent groundwater ages were estimated from chlorofluorocarbons (CFC-11, CFC-12, and CFC-113) and tritium (3H) data using models that assumed piston flow and binary mixing (dilution of a young component with old, tracer-free water). The mean and median groundwater ages were about 30 years and the standard deviation was 6 years, indicating that most groundwater in the primary aquifer was “young” water that had recharged to the aquifer over the last few decades (post-1950s). The median fraction of young water was about 71 percent, and the standard deviation was 29 percent. The remaining water predated the 1950s, which may have originated from deeper geologic formations or may represent slow moving groundwater within the primary aquifer. Some of the oldest groundwater ages (older than 30 years) were observed in the upper reaches of the aquifer to the northwest where the primary aquifer is thin and intersects bedrock, supporting the hypothesis of geochemically distinct groundwater entering the primary aquifer from below. Groundwater that had reached the central part of the aquifer from upgradient areas of the basin was variable in age because of differences in flow paths and travel velocities. The groundwater age analysis showed that current (2013) land-use practices could affect water quality over decades to come, and that responses to remedial actions could be slow, especially for constituents, such as nitrate, that are stable under oxidized conditions.
\nFuel products (including acetone, benzene, diisopropyl ether, ethylbenzene, methyl acetate, methyl tertiary butyl ether (MTBE), methyl tert-pentyl ether, m- + p-xylene, o-xylene, tert-amyl alcohol, tert-butyl alcohol, tert-butyl ethyl ether, and toluene) were analyzed in groundwater from 49 of the 50 wells. Water from seven sites had detections for fuel compounds; all concentrations were below MCL. The results provided assurance of water quality and a valuable baseline to evaluate future trends of fuel constituents as the region is further developed.
\nProbability maps were developed from logistic regression models to examine the likelihood that nitrate concentrations in groundwater exceeded specified levels. Susceptibility analysis examined relations between mid-level (5.0 mg/L) nitrate concentrations and climatic, hydrologic, and geologic variables; the significant variables were identified as depth to groundwater, soil organic matter, and soil water storage to 25-centimeter (cm) depth. The vulnerability assessments included natural factors driving susceptibility but also human factors related to land use and septic use. Vulnerability to low-level (2.5 mg/L) nitrate was related to depth to groundwater, septic zoning, and soil organic matter. The results highlighted that septic zoning affected low-level nitrate concentrations. Vulnerability to mid-level (5.0 mg/L) nitrate was examined using all 50 samples and also with two data outliers removed, which showed relatively high nitrate concentrations but also anomalous water chemistry or were located beyond the primary study area. Vulnerability to mid-level (5.0 mg/L) nitrate using all 50 samples was related to depth to groundwater, land use, septic use within a 500-meter (m) radius, soil water storage to a 25-cm depth, soil organic matter, and whether a location was within the agricultural region. The mid-level (5.0 mg/L) vulnerability model using 48 samples (two outliers removed) produced the best overall fit and was related to the same variables as when using all samples except septic use. The results for mid-level vulnerability provided additional support that septic use was associated with low levels of nitrate in the groundwater. Soil properties and land use were identified as the main drivers of moderate nitrate concentrations. Probabilities of exceeding low-level nitrate concentrations were high in most areas with the lowest probabilities usually to the northwest along thin geologic deposits in the upper part of the basin.
\nThe results of this investigation offer the foundational information needed for developing best management practices to mitigate nitrate contamination, basic concepts on water quality to aid public education, and information to guide regulatory measures if policy makers determine this is warranted. Science-based decision making will require continued monitoring and analysis of water quality in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165020","collaboration":"Prepared in cooperation with Cherokee Metropolitan District, El Paso County, Meridian Service Metropolitan District, Mountain View Electric Association, Upper Black Squirrel Creek Groundwater Management District, Woodmen Hills Metropolitan District, Colorado State Land Board, Colorado Water Conservation Board, and the stakeholders represented in the Groundwater Quality Study Committee of El Paso County","usgsCitation":"Wellman, T.P., and Rupert, M.G., 2016, Groundwater quality, age, and susceptibility and vulnerability to nitrate contamination with linkages to land use and groundwater flow, Upper Black Squirrel Creek Basin, Colorado, 2013: U.S. Geological Survey Scientific Investigations Report, 2016–5020, 78 p., https://dx.doi.org/10.3133/sir20165020.","productDescription":"viii, 77 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068864","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":318534,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5020/coverthb.jpg"},{"id":318535,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5020/sir20165020.pdf","text":"Report","size":"63.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5020"}],"country":"United States","state":"Colorado","county":"El Paso","otherGeospatial":"Black Squirrel Management District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.67361450195312,\n 38.91668153637508\n ],\n [\n -104.7271728515625,\n 38.971154274048345\n ],\n [\n -104.74090576171875,\n 39.02345139405932\n ],\n [\n -104.75875854492188,\n 39.07784203269269\n ],\n [\n -104.77111816406249,\n 39.12579898118164\n ],\n [\n -104.79034423828125,\n 39.172658670429946\n ],\n [\n -104.73953247070311,\n 39.20459056764483\n ],\n [\n -104.69284057617186,\n 39.218423217141485\n ],\n [\n -104.61868286132812,\n 39.23757161784572\n ],\n [\n -104.53628540039062,\n 39.23863526469436\n ],\n [\n -104.49508666992188,\n 39.198205348894795\n ],\n [\n -104.42642211914062,\n 39.196076813671695\n ],\n [\n -104.34951782226561,\n 39.17052936145295\n ],\n [\n -104.32479858398438,\n 39.135386455771076\n ],\n [\n -104.32342529296875,\n 39.08423817730926\n ],\n [\n -104.32754516601562,\n 39.05651736286005\n ],\n [\n -104.27261352539062,\n 39.04158626095001\n ],\n [\n -104.24102783203124,\n 39.01811672409787\n ],\n [\n -104.23278808593749,\n 38.95940879245423\n ],\n [\n -104.22866821289062,\n 38.9177500315307\n ],\n [\n -104.26437377929686,\n 38.882481197550774\n ],\n [\n -104.33441162109374,\n 38.87179021382536\n ],\n [\n -104.40170288085938,\n 38.87499767781738\n ],\n [\n -104.403076171875,\n 38.72623322072787\n ],\n [\n -104.42092895507812,\n 38.6833657775237\n ],\n [\n -104.45663452148438,\n 38.65227081329621\n ],\n [\n -104.51431274414062,\n 38.65334327823747\n ],\n [\n -104.52804565429688,\n 38.67907761983558\n ],\n [\n -104.53216552734375,\n 38.71873327340352\n ],\n [\n -104.56787109374999,\n 38.749799358878526\n ],\n [\n -104.59945678710936,\n 38.805470223177466\n ],\n [\n -104.62554931640625,\n 38.841846903808985\n ],\n [\n -104.67636108398438,\n 38.922023851268925\n ],\n [\n -104.67361450195312,\n 38.91668153637508\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
The Sauvie Island 7.5' quadrangle is situated in the Puget-Willamette Lowland northwest of downtown Portland, Oreg. This lowland, which extends from Puget Sound to west-central Oregon, is a complex structural and topographic trough between the Coast Range and the Cascade Range. Since late Eocene time, the Cascade Range has been the locus of a discontinuously active volcanic arc associated with underthrusting of oceanic lithosphere beneath the North American continent along the Cascadia Subduction Zone. The Coast Range, which occupies the fore-arc position within the Cascadia arc-trench system, consists of a complex assemblage of Eocene to Miocene volcanic and marine sedimentary rocks.
\nThe Sauvie Island quadrangle lies along the southwest margin of the Portland Basin, a 2,000-km2 topographic and structural depression. The basin boundary is an abrupt topographic break at the base of the Tualatin Mountains, which separates the Portland and Tualatin Basins. The Tualatin Mountains are underlain by lava flows of the Miocene Columbia River Basalt Group that have been folded into an asymmetric anticline. Oligocene marine sedimentary rocks, not exposed at the surface, are inferred to underlie the basalt flows. The abrupt basin boundary marks the location of the northwest-striking Portland Hills Fault Zone, which is probably an active structure.
\nThe Columbia River flows west and north through the Portland Basin at nearly sea level. The Willamette River enters the Columbia near the southeast corner of the map area. Seismic-reflection profiles and lithologic logs of water wells show as much as 550 m of late Miocene and younger sediments in the deepest part of the basin east of the quadrangle. Deposits exposed at the surface consist chiefly of Holocene and late Pleistocene fluvial and eolian sediments and man-made fill.
\nThis map contributes to a U.S. Geological Survey program to improve the geologic database for the Portland region of the Pacific Northwest urban corridor. The map and ancillary data will support assessments of seismic risk, ground-failure hazards, and resource availability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3349","usgsCitation":"Evarts, R.C., O'Connor, J.E., and Cannon, C.M., 2016, Geologic map of the Sauvie Island quadrangle, Multnomah and Columbia Counties, Oregon, and Clark County, Washington: U.S. Geological Survey Scientific Investigations Map 3349, scale 1:24,000, pamphlet 34 p., https://dx.doi.org/10.3133/sim3349.","productDescription":"Pamphlet: iv, 34 p.; 1 Plate: 40.00 x 34.00 inches; Database; Metadata; Read Me; Shape Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049408","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":318448,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_db.zip","size":"4.8 MB","linkFileType":{"id":6,"text":"zip"}},{"id":318443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3349/coverthb.jpg"},{"id":318449,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3349/metadata/"},{"id":318447,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_shp.zip","text":"Shape Files","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"}},{"id":318445,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_pamphlet.pdf","text":"Pamphlet","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3349 Pamphlet PDF"},{"id":318446,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_readme.pdf","size":"177 KB","linkFileType":{"id":2,"text":"txt"}},{"id":318444,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3349/sim3349_sheet1.pdf","text":"Sheet 1","size":"74 MB","description":"SIM 3349 Map PDF"},{"id":399013,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_104040.htm"}],"scale":"24000","country":"United States","state":"Oregon, Washington","county":"Clark County, Columbia County, Multnomah County","otherGeospatial":"Sauvie Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.875,\n 45.625\n ],\n [\n -122.875,\n 45.75\n ],\n [\n -122.75,\n 45.75\n ],\n [\n -122.75,\n 45.625\n ],\n [\n -122.875,\n 45.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
http://geomaps.wr.usgs.gov/gmeg/
The Landscape Conservation Cooperatives (LCCs) are a network of partnerships throughout North America that are tasked with integrating science and management to support more effective delivery of conservation at a landscape scale. In order to achieve this integration, some LCCs have adopted the approach of providing their partners with better scientific information in an effort to facilitate more effective and coordinated conservation decisions. Taking this approach has led many LCCs to begin funding research to provide the information for improved decision making. To ensure that funding goes to research projects with the highest likelihood of leading to more integrated broad scale conservation, some LCCs have also developed approaches for prioritizing which information needs will be of most benefit to their partnerships. We describe two case studies in which decision analytic tools were used to quantitatively assess the relative importance of information for decisions made by partners in the Plains and Prairie Potholes LCC. The results of the case studies point toward a few valuable lessons in terms of using these tools with LCCs. Decision analytic tools tend to help shift focus away from research oriented discussions and toward discussions about how information is used in making better decisions. However, many technical experts do not have enough knowledge about decision making contexts to fully inform the latter type of discussion. When assessed in the right decision context, however, decision analyses can point out where uncertainties actually affect optimal decisions and where they do not. This helps technical experts understand that not all research is valuable in improving decision making. But perhaps most importantly, our results suggest that decision analytic tools may be more useful for LCCs as way of developing integrated objectives for coordinating partner decisions across the landscape, rather than simply ranking research priorities.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington, D.C.","doi":"10.3996/032015-JFWM-023","usgsCitation":"Post van der Burg, M., Cullinane Thomas, C., Holcombe, T.R., and Nelson, R., 2016, Benefits and limitations of using decision analytic tools to assess uncertainty and prioritize Landscape Conservation Cooperative information needs: Journal of Fish and Wildlife Management, v. 7, no. 1, p. 280-290, https://doi.org/10.3996/032015-JFWM-023.","productDescription":"11 p.","startPage":"280","endPage":"290","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064346","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471181,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/032015-jfwm-023","text":"Publisher Index Page"},{"id":319622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56fceacae4b0a6037df29cdf","contributors":{"authors":[{"text":"Post van der Burg, Max 0000-0002-3943-4194 maxpostvanderburg@usgs.gov","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":4947,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","email":"maxpostvanderburg@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":625611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cullinane Thomas, Catherine 0000-0001-8168-1271 ccullinanethomas@usgs.gov","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":141097,"corporation":false,"usgs":true,"family":"Cullinane Thomas","given":"Catherine","email":"ccullinanethomas@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":625612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":625613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Richard D.","contributorId":55338,"corporation":false,"usgs":true,"family":"Nelson","given":"Richard D.","affiliations":[],"preferred":false,"id":625614,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160030,"text":"cir1419 - 2016 - Get your science used—Six guidelines to improve your products","interactions":[],"lastModifiedDate":"2016-03-04T08:27:06","indexId":"cir1419","displayToPublicDate":"2016-03-03T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1419","title":"Get your science used—Six guidelines to improve your products","docAbstract":"Natural scientists, like many other experts, face challenges when communicating to people outside their fields of expertise. This is especially true when they try to communicate to those whose background, knowledge, and experience are far distant from that field of expertise.
\nAt a recent workshop, experts in risk communication offered insights into the communication challenges of probabilistic hazard products, suggested tips, and shared their strategies for making products that a targeted audience can understand and use. Although the workshop was held to broaden the understanding and use of the U.S. Geological Survey (USGS) National Seismic Hazard Maps (NSHM), the workshop outcomes presented in this report can benefit anyone who develops products based on technical information.
\nOn the basis of research and practice into how people think, use tools, make decisions, and understand scientific/technical information, the social and behavioral scientists, marketers, and social-impact designers at the NSHM workshop provided remarkably consistent guidelines to develop successful science products, such as text, maps, and other products. In this report the guidelines are numbered for clarity, but they can be applied repeatedly, piecemeal, or out of order to fit each project and your resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1419","usgsCitation":"Perry, S.C., Blanpied, M.L., Burkett, E.R., Campbell, N.M., Carlson, A., Cox, D.A., Driedger, C.L., Eisenman, D.P., Fox-Glassman, K.T., Hoffman, S., Hoffman, S.M., Jaiswal, K.S., Jones, L.M., Luco, N., Marx, S.M., McGowan, S.M., Mileti, D.S., Moschetti, M.P., Ozman, D., Pastor, E., Petersen, M.D., Porter, K.A., Ramsey, D.W., Ritchie, L.A., Fitzpatrick, J.K., Rukstales, K.S., Sellnow, T.S., Vaughon, W.L., Wald, D.J., Wald, L.A., Wein, A., and Zarcadoolas, C., 2016, Get your science used—Six guidelines to improve your products: U.S. Geological Survey Circular 1419, 37 p., https://dx.doi.org/10.3133/cir1419.","productDescription":"iv, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064533","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":318527,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1419/coverthb.jpg"},{"id":318528,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1419/c1419.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1419"}],"contact":"Staff, Science Application for Risk Reduction (SAFRR)
U.S. Geological Survey
525 S. Wilson Avenue
Pasadena, CA 91106
http://www.usgs.gov/natural_hazards/safrr/
A model for preferential flow in macropores is based on the short-range spatial distribution of soil matrix infiltrability. It uses elementary areas at two different scales. One is the traditional representative elementary area (REA), which includes a sufficient heterogeneity to typify larger areas, as for measuring field-scale infiltrability. The other, called an elementary matrix area (EMA), is smaller, but large enough to represent the local infiltrability of soil matrix material, between macropores. When water is applied to the land surface, each EMA absorbs water up to the rate of its matrix infiltrability. Excess water flows into a macropore, becoming preferential flow. The land surface then can be represented by a mesoscale (EMA-scale) distribution of matrix infiltrabilities. Total preferential flow at a given depth is the sum of contributions from all EMAs. Applying the model, one case study with multi-year field measurements of both preferential and diffuse fluxes at a specific depth was used to obtain parameter values by inverse calculation. The results quantify the preferential–diffuse partition of flow from individual storms that differed in rainfall amount, intensity, antecedent soil water, and other factors. Another case study provided measured values of matrix infiltrability to estimate parameter values for comparison and illustrative predictions. These examples give a self-consistent picture from the combination of parameter values, directions of sensitivities, and magnitudes of differences caused by different variables. One major practical use of this model is to calculate the dependence of preferential flow on climate-related factors, such as varying soil wetness and rainfall intensity.
","language":"English","publisher":"ACSESS","doi":"10.2136/vzj2015.05.0079","usgsCitation":"Nimmo, J.R., 2016, Quantitative framework for preferential flow initiation and partitioning: Vadose Zone Journal, v. 15, no. 2, https://doi.org/10.2136/vzj2015.05.0079.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069590","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":318537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-08","publicationStatus":"PW","scienceBaseUri":"56d96034e4b015c306f726de","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":621772,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70168794,"text":"70168794 - 2016 - Annual grass invasion in sagebrush-steppe: The relative importance of climate, soil properties and biotic interactions","interactions":[],"lastModifiedDate":"2016-05-19T10:27:29","indexId":"70168794","displayToPublicDate":"2016-03-03T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Annual grass invasion in sagebrush-steppe: The relative importance of climate, soil properties and biotic interactions","docAbstract":"The invasion by winter-annual grasses (AGs) such as Bromus tectorum into sagebrush steppe throughout the western USA is a classic example of a biological invasion with multiple, interacting climate, soil and biotic factors driving the invasion, although few studies have examined all components together. Across a 6000-km2 area of the northern Great Basin, we conducted a field assessment of 100 climate, soil, and biotic (functional group abundances, diversity) factors at each of 90 sites that spanned an invasion gradient ranging from 0 to 100 % AG cover. We first determined which biotic and abiotic factors had the strongest correlative relationships with AGs and each resident functional group. We then used regression and structural equation modeling to explore how multiple ecological factors interact to influence AG abundance. Among biotic interactions, we observed negative relationships between AGs and biodiversity, perennial grass cover, resident species richness, biological soil crust cover and shrub density, whereas perennial and annual forb cover, tree cover and soil microbial biomass had no direct linkage to AG. Among abiotic factors, AG cover was strongly related to climate (increasing cover with increasing temperature and aridity), but had weak relationships with soil factors. Our structural equation model showed negative effects of perennial grasses and biodiversity on AG cover while integrating the negative effects of warmer climate and positive influence of belowground processes on resident functional groups. Our findings illustrate the relative importance of biotic interactions and climate on invasive abundance, while soil properties appear to have stronger relationships with resident biota than with invasives.
","language":"English","publisher":"Springer","doi":"10.1007/s00442-016-3583-8","usgsCitation":"Bansal, S., and Sheley, R.L., 2016, Annual grass invasion in sagebrush-steppe: The relative importance of climate, soil properties and biotic interactions: Oecologia, v. 181, no. 2, p. 543-557, https://doi.org/10.1007/s00442-016-3583-8.","productDescription":"15 p.","startPage":"543","endPage":"557","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070148","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":318536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.53125,\n 43.14909399920127\n ],\n [\n -119.53125,\n 43.77109381775651\n ],\n [\n -118.5205078125,\n 43.77109381775651\n ],\n [\n -118.5205078125,\n 43.14909399920127\n ],\n [\n -119.53125,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"181","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-26","publicationStatus":"PW","scienceBaseUri":"56d9602ce4b015c306f726b4","contributors":{"authors":[{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":621776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheley, Roger L.","contributorId":167296,"corporation":false,"usgs":false,"family":"Sheley","given":"Roger","email":"","middleInitial":"L.","affiliations":[{"id":24676,"text":"USDA-ARS, Burns Oregon","active":true,"usgs":false}],"preferred":false,"id":621777,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168798,"text":"70168798 - 2016 - A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags","interactions":[],"lastModifiedDate":"2017-01-12T11:06:16","indexId":"70168798","displayToPublicDate":"2016-03-03T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags","docAbstract":"Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.1727","usgsCitation":"Letcher, B., Hocking, D., O'Neil, K., Whiteley, A.R., Nislow, K., and O’Donnell, M., 2016, A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags: PeerJ, v. 4, e1727: 26 p., https://doi.org/10.7717/peerj.1727.","productDescription":"e1727: 26 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072906","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":471182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.1727","text":"Publisher Index Page"},{"id":318531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-29","publicationStatus":"PW","scienceBaseUri":"56d96027e4b015c306f726ad","contributors":{"authors":[{"text":"Letcher, Benjamin H. 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":167313,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin H.","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":621791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hocking, Daniel 0000-0003-1889-9184 dhocking@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-9184","contributorId":149618,"corporation":false,"usgs":true,"family":"Hocking","given":"Daniel","email":"dhocking@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Neil, Kyle","contributorId":82491,"corporation":false,"usgs":true,"family":"O'Neil","given":"Kyle","affiliations":[],"preferred":false,"id":621793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":621794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nislow, Keith H.","contributorId":60106,"corporation":false,"usgs":true,"family":"Nislow","given":"Keith H.","affiliations":[],"preferred":false,"id":621795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Matthew 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":167315,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":621796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174238,"text":"70174238 - 2016 - Mountain building on Io driven by deep faulting","interactions":[],"lastModifiedDate":"2016-07-06T14:10:22","indexId":"70174238","displayToPublicDate":"2016-03-03T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Mountain building on Io driven by deep faulting","docAbstract":"Jupiter’s volcanic moon Io possesses some of the highest relief in the Solar System: massive, isolated mountain blocks that tower up to 17 km above the surrounding plains. These mountains are likely to result from pervasive compressive stresses induced by subsidence of the surface beneath the near-continual emplacement of volcanic material. The stress state that results from subsidence and warming of Io’s lithosphere has been investigated in detail1, 2, 3, 4; however, the mechanism of orogenesis itself and its effect on regional tectonism and volcanism has not been firmly established. Here we present viscoelastic–plastic finite element simulations demonstrating that Io’s mountains form along deep-seated thrust faults that initiate at the base of the lithosphere and propagate upward. We show that faulting fundamentally alters the stress state of Io’s lithosphere by relieving the large volcanism-induced subsidence stresses. Notably, in the upper portion of the lithosphere, stresses become tensile (near-zero differential stress). A number of processes are therefore altered post-faulting, including magma transport through the lithosphere, interactions with tidal stresses and potentially the localization of mountain formation by thermoelastic stresses. We conclude that Io’s mountains form by a unique orogenic mechanism, compared with tectonic processes operating elsewhere in the Solar System.
","language":"English","publisher":"Nature Pub. Group","doi":"10.1038/ngeo2711","usgsCitation":"Bland, M.T., and McKinnon, W., 2016, Mountain building on Io driven by deep faulting: Nature Geoscience, v. 9, p. 429-432, https://doi.org/10.1038/ngeo2711.","productDescription":"4 p.","startPage":"429","endPage":"432","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068183","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":324762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-16","publicationStatus":"PW","scienceBaseUri":"577e2bb1e4b0ef4d2f445a2d","contributors":{"authors":[{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":641566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKinnon, William B.","contributorId":146288,"corporation":false,"usgs":false,"family":"McKinnon","given":"William B.","affiliations":[{"id":16661,"text":"Washington University in Saint Louis","active":true,"usgs":false}],"preferred":false,"id":641567,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168796,"text":"70168796 - 2016 - First documented case of snake fungal disease in a free-ranging wild snake in Louisiana","interactions":[],"lastModifiedDate":"2020-12-21T16:07:36.50284","indexId":"70168796","displayToPublicDate":"2016-03-03T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"First documented case of snake fungal disease in a free-ranging wild snake in Louisiana","docAbstract":"Snake fungal disease (SFD) is a recently documented mycotic disease characterized by scabs or crusty scales, subcutaneous nodules, abnormal molting, cloudiness of the eyes (not associated with molting), and localized thickening or crusting of the skin. SFD has been documented in many species in the Eastern and Midwestern United States within the last decade. SFD has proven lethal in many snakes, and the disease is recognized as an emerging threat to wild snake populations. Here, we describe the first documented case of SFD in Louisiana in a free-ranging wild snake.
","language":"English","publisher":"Eagle Hill Publications","doi":"10.1656/058.015.0111","usgsCitation":"Glorioso, B.M., Waddle, J., Green, D.E., and Lorch, J.M., 2016, First documented case of snake fungal disease in a free-ranging wild snake in Louisiana: Southeastern Naturalist, v. 15, no. 1, p. 4-6, https://doi.org/10.1656/058.015.0111.","productDescription":"3 p.","startPage":"4","endPage":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067103","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":318530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Cypress Island Preserve, Lake Martin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.9251823425293,\n 30.200778435288452\n ],\n [\n -91.9251823425293,\n 30.23089119743091\n ],\n [\n -91.88827514648438,\n 30.23089119743091\n ],\n [\n -91.88827514648438,\n 30.200778435288452\n ],\n [\n -91.9251823425293,\n 30.200778435288452\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56d96030e4b015c306f726ba","contributors":{"authors":[{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":621781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133 waddleh@usgs.gov","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":149048,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","email":"waddleh@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":621782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Green, David E. 0000-0002-7663-1832 degreen@usgs.gov","orcid":"https://orcid.org/0000-0002-7663-1832","contributorId":3715,"corporation":false,"usgs":true,"family":"Green","given":"David","email":"degreen@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":621783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252 jlorch@usgs.gov","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":5565,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey","email":"jlorch@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":621784,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178106,"text":"70178106 - 2016 - Circumpolar biodiversity monitoring program (CBMP): Coastal expert workshop meeting report","interactions":[],"lastModifiedDate":"2016-12-14T13:39:46","indexId":"70178106","displayToPublicDate":"2016-03-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Circumpolar biodiversity monitoring program (CBMP): Coastal expert workshop meeting report","docAbstract":"The Coastal Expert Workshop, which took place in Ottawa, Canada from March 1 to 3, 2016, initiated the development of the Arctic Coastal Biodiversity Monitoring Plan (Coastal Plan). Meeting participants, including northern residents, representatives from industry, non-governmental organisations (NGOs), academia, and government regulators and agencies from across the circumpolar Arctic, discussed current biodiversity monitoring efforts, key issues facing biodiversity in Arctic coastal areas, and collectively identified monitoring indicators, or Focal Ecosystem Components (FECs). On February 29, the day before the workshop, a full day was allocated to Traditional Knowledge (TK) holders to meet and elucidate how this important knowledge can be included in the process of building the Coastal Plan and monitoring biodiversity in Arctic coastal areas, along with scientific data and variables.
This document provides 1) background information about the Circumpolar Biodiversity Monitoring Programme and the Coastal Expert Monitoring Group, 2) overviews on workshop presentations and breakout sessions, and 3) details regarding outcomes of the workshop that will inform the drafting of the Coastal Plan.
","conferenceTitle":"Circumpolar biodiversity monitoring program (CBMP) coastal expert workshop meeting","conferenceDate":"Feb. 29- March 3, 2016","conferenceLocation":"Ottawa, Canada","language":"English","publisher":"Conservation of Arctic Flora and Fauna (CAFF)","usgsCitation":"Anderson, R., McLennan, D., Thomson, L., Wegeberg, S., Pettersvik Arvnes, M., Sergienko, L., Behe, C., Moss-Davies, P., Fritz, S., Christensen, T.K., and Price, C., 2016, Circumpolar biodiversity monitoring program (CBMP): Coastal expert workshop meeting report, Circumpolar biodiversity monitoring program (CBMP) coastal expert workshop meeting, Ottawa, Canada, Feb. 29- March 3, 2016, p. 1-52.","productDescription":"53 p.","startPage":"1","endPage":"52","ipdsId":"IP-080363","costCenters":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"links":[{"id":330673,"type":{"id":15,"text":"Index Page"},"url":"https://caff.is/coastal/coastal-monitoring-publications/388-circumpolar-biodiversity-monitoring-program-cbmp-coastal-expert-workshop-meeting"},{"id":332130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585268e2e4b0e2663625ec86","contributors":{"authors":[{"text":"Anderson, Rebecca 0000-0001-6988-6311 rdanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-6988-6311","contributorId":5925,"corporation":false,"usgs":true,"family":"Anderson","given":"Rebecca","email":"rdanderson@usgs.gov","affiliations":[{"id":113,"text":"Alaska Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":652776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLennan, Donald","contributorId":176567,"corporation":false,"usgs":false,"family":"McLennan","given":"Donald","email":"","affiliations":[],"preferred":false,"id":652777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomson, Laura","contributorId":176568,"corporation":false,"usgs":false,"family":"Thomson","given":"Laura","email":"","affiliations":[],"preferred":false,"id":652778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wegeberg, Susse","contributorId":176569,"corporation":false,"usgs":false,"family":"Wegeberg","given":"Susse","email":"","affiliations":[],"preferred":false,"id":652779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pettersvik Arvnes, Maria","contributorId":176570,"corporation":false,"usgs":false,"family":"Pettersvik Arvnes","given":"Maria","email":"","affiliations":[],"preferred":false,"id":652780,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sergienko, Liudmila","contributorId":176571,"corporation":false,"usgs":false,"family":"Sergienko","given":"Liudmila","email":"","affiliations":[],"preferred":false,"id":652781,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Behe, Carolina","contributorId":176572,"corporation":false,"usgs":false,"family":"Behe","given":"Carolina","email":"","affiliations":[],"preferred":false,"id":652782,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moss-Davies, Pitseolak","contributorId":176573,"corporation":false,"usgs":false,"family":"Moss-Davies","given":"Pitseolak","email":"","affiliations":[],"preferred":false,"id":652783,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fritz, Stacey","contributorId":176574,"corporation":false,"usgs":false,"family":"Fritz","given":"Stacey","email":"","affiliations":[],"preferred":false,"id":652784,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Christensen, Thomas K.","contributorId":69381,"corporation":false,"usgs":false,"family":"Christensen","given":"Thomas","email":"","middleInitial":"K.","affiliations":[{"id":6963,"text":"Department of Bioscience, Aarhus University","active":true,"usgs":false}],"preferred":false,"id":652785,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Price, Courtney","contributorId":176575,"corporation":false,"usgs":false,"family":"Price","given":"Courtney","email":"","affiliations":[],"preferred":false,"id":652786,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70176640,"text":"70176640 - 2016 - Assessment of canyon wall failure process from multibeam bathymetry and Remotely Operated Vehicle (ROV) observations, U.S. Atlantic continental margin","interactions":[],"lastModifiedDate":"2021-02-17T22:43:18.006221","indexId":"70176640","displayToPublicDate":"2016-03-03T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Assessment of canyon wall failure process from multibeam bathymetry and Remotely Operated Vehicle (ROV) observations, U.S. Atlantic continental margin","docAbstract":"Over the last few years, canyons along the northern U.S. Atlantic continental margin have been the focus of intensive research examining canyon evolution, submarine geohazards, benthic ecology and deep-sea coral habitat. New high-resolution multibeam bathymetry and Remotely Operated Vehicle (ROV) dives in the major shelf-breaching and minor slope canyons, provided the opportunity to investigate the size of, and processes responsible for, canyon wall failures. The canyons cut through thick Late Cretaceous to Recent mixed siliciclastic and carbonate-rich lithologies which impart a primary control on the style of failures observed. Broad-scale canyon morphology across much of the margin can be correlated to the exposed lithology. Near vertical walls, sedimented benches, talus slopes, and canyon floor debris aprons were present in most canyons. The extent of these features depends on canyon wall cohesion and level of internal fracturing, and resistance to biological and chemical erosion. Evidence of brittle failure over different spatial and temporal scales, physical abrasion by downslope moving flows, and bioerosion, in the form of burrows and surficial scrape marks provide insight into the modification processes active in these canyons. The presence of sessile fauna, including long-lived, slow growing corals and sponges, on canyon walls, especially those affected by failure provide a critical, but as yet, poorly understood chronological record of geologic processes within these systems.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Submarine mass movements and their consequences: 7th international symposium part II","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-20979-1_10","usgsCitation":"Chaytor, J., Demopoulos, A., ten Brink, U., Baxter, C.D., Quattrini, A.M., and Brothers, D., 2016, Assessment of canyon wall failure process from multibeam bathymetry and Remotely Operated Vehicle (ROV) observations, U.S. Atlantic continental margin, chap. 10 of Submarine mass movements and their consequences: 7th international symposium part II, p. 103-113, https://doi.org/10.1007/978-3-319-20979-1_10.","productDescription":"11 p.","startPage":"103","endPage":"113","ipdsId":"IP-063805","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488132,"rank":0,"type":{"id":41,"text":"Open Access 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A recovery factor represents the percentage of an oil reservoir’s original oil in place estimated to be recoverable by the application of a miscible CO2-EOR method. The USGS estimates were calculated for 2,018 clastic and 1,681 carbonate candidate reservoirs in the “Significant Oil and Gas Fields of the United States Database” prepared by Nehring Associates, Inc. (2012).
\nThis report presents distributions of estimated recovery factors organized by plays in seven U.S. regions. The distributional parameters for plays containing at least three candidate reservoirs are presented in tables, and parameters for plays containing at least six candidate reservoirs are presented in boxplots. Over all the reservoirs evaluated, 90 percent of the recovery-factor estimates for clastic reservoirs fell within the range from 8.7 to 16.2 percent, and the median value of the distribution was 9.5 percent. Similarly, 90 percent of the recovery-factor estimates for carbonate reservoirs were within the range from 11.8 to 27.5 percent, and the median value of the distribution was 13.6 percent. Both distributions were right skewed.
\nThe retention factor is the percentage of injected CO2 that is naturally retained in the reservoir. Retention factors were also estimated in this study. For clastic reservoirs, 90 percent of the estimated retention factors were between 21.7 and 32.1 percent, and for carbonate reservoirs, 90 percent were between 23.7 and 38.2 percent. The respective median values were 22.9 for clastic reservoirs and 26.1 for carbonate reservoirs. Both distributions were right skewed. The recovery and retention factors that were calculated are consistent with the corresponding factors reported in the literature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151239","usgsCitation":"Attanasi, E.D., and Freeman, P.A., 2016, Play-level distributions of estimates of recovery factors for a miscible carbon dioxide enhanced oil recovery method used in oil reservoirs in the conterminous United States: U.S. Geological Survey Open-File Report 2015–1239, 36 p., https://dx.doi.org/10.3133/ofr20151239.","productDescription":"vii, 36 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067608","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":318493,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1239/ofr20151239.pdf","text":"Report","size":"2.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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\"}}]}\n","contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
MS 956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Availability of water is an important issue in northeastern Arizona because of continued water requirements for industrial and municipal use by a growing population and because of low precipitation in the arid climate of the Black Mesa area. Precipitation in the area typically is between 6 and 14 inches per year.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from January 2012 to September 2013. The monitoring program includes measurements of (1) groundwater withdrawals, (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry.
In calendar year 2012, total groundwater withdrawals were 4,010 acre-ft, industrial withdrawals were 1,370 acre-ft, and municipal withdrawals were 2,640 acre-ft. Total withdrawals during 2012 were about 45 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline. From 2011 to 2012 total withdrawals decreased by 10 percent; industrial withdrawals decreased by approximately 1 percent, and total municipal withdrawals decreased by 15 percent.
From 2012 to 2013, annually measured water levels in the Black Mesa area declined in 6 of 16 wells that were available for comparison in the unconfined areas of the N aquifer, and the median change was 0.8 feet. Water levels declined in 5 of 16 wells measured in the confined area of the aquifer. The median change for the confined area of the aquifer was 0.3 feet. From the prestress period (prior to 1965) to 2013, the median water-level change for 34 wells in both the confined and unconfined areas was -13.5 feet; the median water-level changes were -0.8 feet for 16 wells measured in the unconfined areas and -51.0 feet for 16 wells measured in the confined area.
Spring flow was measured at four springs in 2013; Burro, Unnamed Spring near Dennehotso, Moenkopi School, and Pasture Canyon Springs. Flow fluctuated during the period of record for Burro and Unnamed Springs near Dennehotso, but a decreasing trend was apparent at Moenkopi School Spring and Pasture Canyon Spring. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Unnamed Spring near Dennehotso has fluctuated for the period of record at each spring. Trend analysis for discharge at Moenkopi School and Pasture Canyon Springs showed a decreasing trend.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2013), Dinnebito Wash near Sand Springs 09401110 (1993 to 2013), Polacca Wash near Second Mesa 09400568 (1994 to 2013), and Pasture Canyon Springs 09401265 (2004 to 2013). Median winter flows (November through February) from these sites for each water year were used as an index of the amount of groundwater discharge. For the period of record of each streamflow-gaging station, the median winter flows have generally remained constant, which suggests no change in groundwater discharge.
In 2013, water samples collected from 12 wells and 4 springs in the Black Mesa area were analyzed for selected chemical constituents, and the results were compared with previous analyses. Concentrations of dissolved solids, chloride, and sulfate have varied at all 12 wells for the period of record, but neither increasing nor decreasing trends over time were found. Dissolved solids, chloride, and sulfate concentrations increased at Moenkopi School Spring during the more than 13 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly since the early 1980s. Concentrations of dissolved solids, chloride, and sulfate at Burro Spring and Unnamed Spring near Dennehotso have varied for the period of record with no increasing or decreasing trend in the data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151221","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs and the Arizona Department of Water Resources","usgsCitation":"Macy, J.P., and Truini, Margot, 2016, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2012–2013: U.S. Geological Survey Open-File Report 2015–1221, 43 p., https://dx.doi.org/10.3133/ofr20151221.","productDescription":"vi, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-01-01","ipdsId":"IP-059312","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":318423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1221/coverthb.jpg"},{"id":318424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1221/ofr20151221.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1221 PDF"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3,\n 35.3\n ],\n [\n -111.3,\n 37\n ],\n [\n -109.3,\n 37\n ],\n [\n -109.3,\n 35.3\n ],\n [\n -111.3,\n 35.3\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Sexually size-dimorphic species must show some difference between the sexes in growth rate and/or length of growing period. Such differences in growth parameters can cause the sexes to be impacted by environmental variability in different ways, and understanding these differences allows a better understanding of patterns in productivity between individuals and populations. We investigated differences in growth rate and diet between male and female Adélie Penguin (Pygoscelis adeliae) chicks during two breeding seasons at Cape Crozier, Ross Island, Antarctica. Adélie Penguins are a slightly dimorphic species, with adult males averaging larger than adult females in mass (~11%) as well as bill (~8%) and flipper length (~3%). We measured mass and length of flipper, bill, tibiotarsus, and foot at 5-day intervals for 45 male and 40 female individually-marked chicks. Chick sex was molecularly determined from feathers. We used linear mixed effects models to estimate daily growth rate as a function of chick sex, while controlling for hatching order, brood size, year, and potential variation in breeding quality between pairs of parents. Accounting for season and hatching order, male chicks gained mass an average of 15.6 g d-1 faster than females. Similarly, growth in bill length was faster for males, and the calculated bill size difference at fledging was similar to that observed in adults. There was no evidence for sex-based differences in growth of other morphological features. Adélie diet at Ross Island is composed almost entirely of two species—one krill (Euphausia crystallorophias) and one fish (Pleuragramma antarctica), with fish having a higher caloric value. Using isotopic analyses of feather samples, we also determined that male chicks were fed a higher proportion of fish than female chicks. The related differences in provisioning and growth rates of male and female offspring provides a greater understanding of the ways in which ecological factors may impact the two sexes differently.
","language":"English","publisher":"Crossmark","doi":"10.1371/journal.pone.0149090","usgsCitation":"Jennings, S., Varsani, A., Dugger, K., Ballard, G., and Ainley, D.G., 2016, Sex-based differences in Adelie penguin (Pygoscelis adeliae) chick growth rates.: PLoS ONE, v. 11, no. 3, p. 1-13, https://doi.org/10.1371/journal.pone.0149090.","productDescription":"13 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061214","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0149090","text":"Publisher Index Page"},{"id":323452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ross Island, Antarctica","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 165.19592285156247,\n -78.07788665318229\n ],\n [\n 165.19592285156247,\n -77.06157599262296\n ],\n [\n 170.4913330078125,\n -77.06157599262296\n ],\n [\n 170.4913330078125,\n -78.07788665318229\n ],\n [\n 165.19592285156247,\n -78.07788665318229\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-02","publicationStatus":"PW","scienceBaseUri":"575be4ade4b04f417c27f548","contributors":{"authors":[{"text":"Jennings, Scott","contributorId":171721,"corporation":false,"usgs":false,"family":"Jennings","given":"Scott","email":"","affiliations":[],"preferred":false,"id":638415,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varsani, Arvind","contributorId":171722,"corporation":false,"usgs":false,"family":"Varsani","given":"Arvind","email":"","affiliations":[],"preferred":false,"id":638416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":638377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ballard, Grant","contributorId":40499,"corporation":false,"usgs":true,"family":"Ballard","given":"Grant","affiliations":[],"preferred":false,"id":638417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ainley, David G.","contributorId":32039,"corporation":false,"usgs":false,"family":"Ainley","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":34154,"text":"Point Reyes Bird Observatory, Stinson Beach, CA","active":true,"usgs":false}],"preferred":false,"id":638418,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168744,"text":"70168744 - 2016 - Influence of species, size and relative abundance on the outcomes of competitive interactions between brook trout and juvenile coho salmon","interactions":[],"lastModifiedDate":"2017-02-15T14:14:48","indexId":"70168744","displayToPublicDate":"2016-03-02T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1590,"text":"Ethology Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Influence of species, size and relative abundance on the outcomes of competitive interactions between brook trout and juvenile coho salmon","docAbstract":"Resource competition between animals is influenced by a number of factors including the species, size and relative abundance of competing individuals. Stream-dwelling animals often experience variably available food resources, and some employ territorial behaviors to increase their access to food. We investigated the factors that affect dominance between resident, non-native brook trout and recolonizing juvenile coho salmon in the Elwha River, WA, USA, to see if brook trout are likely to disrupt coho salmon recolonization via interference competition. During dyadic laboratory feeding trials, we hypothesized that fish size, not species, would determine which individuals consumed the most food items, and that species would have no effect. We found that species, not size, played a significant role in dominance; coho salmon won 95% of trials, even when only 52% the length of their brook trout competitors. As the pairs of competing fish spent more time together during a trial sequence, coho salmon began to consume more food, and brook trout began to lose more, suggesting that the results of early trials influenced fish performance later. In group trials, we hypothesized that group composition and species would not influence fish foraging success. In single species groups, coho salmon consumed more than brook trout, but the ranges overlapped. Brook trout consumption remained constant through all treatments, but coho salmon consumed more food in treatments with fewer coho salmon, suggesting that coho salmon experienced more intra- than inter-specific competition and that brook trout do not pose a substantial challenge. Based on our results, we think it is unlikely that competition from brook trout will disrupt Elwha River recolonization by coho salmon.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/03949370.2015.1125393","usgsCitation":"Thornton, E.J., Duda, J.J., and Quinn, T.P., 2016, Influence of species, size and relative abundance on the outcomes of competitive interactions between brook trout and juvenile coho salmon: Ethology Ecology and Evolution, v. 29, no. 2, p. 157-169, https://doi.org/10.1080/03949370.2015.1125393.","productDescription":"13 p.","startPage":"157","endPage":"169","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065073","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":318502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.6181640625,\n 47.70144425833169\n ],\n [\n -123.6181640625,\n 48.15509285476017\n ],\n [\n -123.44650268554688,\n 48.15509285476017\n ],\n [\n -123.44650268554688,\n 47.70144425833169\n ],\n [\n -123.6181640625,\n 47.70144425833169\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-29","publicationStatus":"PW","scienceBaseUri":"56d80eafe4b015c306f5ea05","contributors":{"authors":[{"text":"Thornton, Emily J","contributorId":167271,"corporation":false,"usgs":false,"family":"Thornton","given":"Emily","email":"","middleInitial":"J","affiliations":[{"id":24670,"text":"School of Aquatic and Fishery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":621589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":621588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Quinn, Thomas P.","contributorId":167272,"corporation":false,"usgs":false,"family":"Quinn","given":"Thomas","email":"","middleInitial":"P.","affiliations":[{"id":24671,"text":"School of Aquatic and Fsiery Sciences, UW, Box 355020, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":621590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70168750,"text":"70168750 - 2016 - Quantifying fish swimming behavior in response to acute exposure of aqueous copper using computer assisted video and digital image analysis","interactions":[],"lastModifiedDate":"2018-08-09T12:11:03","indexId":"70168750","displayToPublicDate":"2016-03-02T12:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying fish swimming behavior in response to acute exposure of aqueous copper using computer assisted video and digital image analysis","docAbstract":"Behavioral responses of aquatic organisms to environmental contaminants can be precursors of other effects such as survival, growth, or reproduction. However, these responses may be subtle, and measurement can be challenging. Using juvenile white sturgeon (Acipenser transmontanus) with copper exposures, this paper illustrates techniques used for quantifying behavioral responses using computer assisted video and digital image analysis. In previous studies severe impairments in swimming behavior were observed among early life stage white sturgeon during acute and chronic exposures to copper. Sturgeon behavior was rapidly impaired and to the extent that survival in the field would be jeopardized, as fish would be swept downstream, or readily captured by predators. The objectives of this investigation were to illustrate protocols to quantify swimming activity during a series of acute copper exposures to determine time to effect during early lifestage development, and to understand the significance of these responses relative to survival of these vulnerable early lifestage fish. With mortality being on a time continuum, determining when copper first affects swimming ability helps us to understand the implications for population level effects. The techniques used are readily adaptable to experimental designs with other organisms and stressors.
","language":"English","publisher":"JoVE","doi":"10.3791/53477","usgsCitation":"Calfee, R.D., Puglis, H.J., Little, E.E., Brumbaugh, W.G., and Mebane, C.A., 2016, Quantifying fish swimming behavior in response to acute exposure of aqueous copper using computer assisted video and digital image analysis: Journal of Visualized Experiments, v. 108, e53477, https://doi.org/10.3791/53477.","productDescription":"e53477","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064597","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471184,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3791/53477","text":"Publisher Index Page"},{"id":318499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-26","publicationStatus":"PW","scienceBaseUri":"56d80eb2e4b015c306f5ea12","contributors":{"authors":[{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":621632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":621633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Little, Edward E. 0000-0003-0034-3639 elittle@usgs.gov","orcid":"https://orcid.org/0000-0003-0034-3639","contributorId":1746,"corporation":false,"usgs":true,"family":"Little","given":"Edward","email":"elittle@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":621634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":621635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mebane, Christopher A. 0000-0002-9089-0267 cmebane@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-0267","contributorId":110,"corporation":false,"usgs":true,"family":"Mebane","given":"Christopher","email":"cmebane@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":621636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168782,"text":"70168782 - 2016 - The “Anthropocene” epoch: Scientific decision or political statement?","interactions":[],"lastModifiedDate":"2016-03-02T10:57:27","indexId":"70168782","displayToPublicDate":"2016-03-02T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1728,"text":"GSA Today","active":true,"publicationSubtype":{"id":10}},"title":"The “Anthropocene” epoch: Scientific decision or political statement?","docAbstract":"The proposal for the “Anthropocene” epoch as a formal unit of the geologic time scale has received extensive attention in scientific and public media. However, most articles on the Anthropocene misrepresent the nature of the units of the International Chronostratigraphic Chart, which is produced by the International Commission on Stratigraphy (ICS) and serves as the basis for the geologic time scale. The stratigraphic record of the Anthropocene is minimal, especially with its recently proposed beginning in 1945; it is that of a human lifespan, and that definition relegates considerable anthropogenic change to a “pre-Anthropocene.” The utility of the Anthropocene requires careful consideration by its various potential users. Its concept is fundamentally different from the chronostratigraphic units that are established by ICS in that the documentation and study of the human impact on the Earth system are based more on direct human observation than on a stratigraphic record. The drive to officially recognize the Anthropocene may, in fact, be political rather than scientific.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GSATG270A.1","usgsCitation":"Finney, S.C., and Edwards, L.E., 2016, The “Anthropocene” epoch: Scientific decision or political statement?: GSA Today, v. 26, no. 3, p. 3-4, https://doi.org/10.1130/GSATG270A.1.","productDescription":"2 p.","startPage":"3","endPage":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070876","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":318494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"56d80eb6e4b015c306f5ea26","contributors":{"authors":[{"text":"Finney, Stanley C.","contributorId":167284,"corporation":false,"usgs":false,"family":"Finney","given":"Stanley","email":"","middleInitial":"C.","affiliations":[{"id":24675,"text":"California State University at Long Beach","active":true,"usgs":false}],"preferred":false,"id":621740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":621739,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168775,"text":"70168775 - 2016 - The evolution of a thermokarst-lake landscape: Late Quaternary permafrost degradation and stabilization in interior Alaska","interactions":[],"lastModifiedDate":"2016-06-02T11:00:48","indexId":"70168775","displayToPublicDate":"2016-03-02T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3368,"text":"Sedimentary Geology","active":true,"publicationSubtype":{"id":10}},"title":"The evolution of a thermokarst-lake landscape: Late Quaternary permafrost degradation and stabilization in interior Alaska","docAbstract":"Thermokarst processes characterize a variety of ice-rich permafrost terrains and often lead to lake formation. The long-term evolution of thermokarst landscapes and the stability and longevity of lakes depend upon climate, vegetation and ground conditions, including the volume of excess ground ice and its distribution. The current lake status of thermokarst-lake landscapes and their future trajectories under climate warming are better understood in the light of their long-term development. We studied the lake-rich southern marginal upland of the Yukon Flats (northern interior Alaska) using dated lake-sediment cores, observations of river-cut exposures, and remotely-sensed data. The region features thick (up to 40 m) Quaternary deposits (mainly loess) that contain massive ground ice. Two of three studied lakes formed ~ 11,000–12,000 cal yr BP through inferred thermokarst processes, and fire may have played a role in initiating thermokarst development. From ~ 9000 cal yr BP, all lakes exhibited steady sedimentation, and pollen stratigraphies are consistent with regional patterns. The current lake expansion rates are low (0 to < 7 cm yr− 1 shoreline retreat) compared with other regions (~ 30 cm yr− 1 or more). This thermokarst lake-rich region does not show evidence of extensive landscape lowering by lake drainage, nor of multiple lake generations within a basin. However, LiDAR images reveal linear “corrugations” (> 5 m amplitude), deep thermo-erosional gullies, and features resembling lake drainage channels, suggesting that highly dynamic surface processes have previously shaped the landscape. Evidently, widespread early Holocene permafrost degradation and thermokarst lake initiation were followed by lake longevity and landscape stabilization, the latter possibly related to establishment of dense forest cover. Partial or complete drainage of three lakes in 2013 reveals that there is some contemporary landscape dynamism. Holocene landscape evolution in the study area differs from that described from other thermokarst-affected regions; regional responses to future environmental change may be equally individualistic.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.sedgeo.2016.01.018","usgsCitation":"Edwards, M., Grosse, G., Jones, B.M., and McDowell, P.F., 2016, The evolution of a thermokarst-lake landscape: Late Quaternary permafrost degradation and stabilization in interior Alaska: Sedimentary Geology, v. 340, p. 3-14, https://doi.org/10.1016/j.sedgeo.2016.01.018.","productDescription":"12 p.","startPage":"3","endPage":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068641","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":471185,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://epic.awi.de/id/eprint/41740/","text":"External Repository"},{"id":318496,"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 -150.084228515625,\n 65.0025821781929\n ],\n [\n -150.084228515625,\n 67.51277075847912\n ],\n [\n -141.207275390625,\n 67.51277075847912\n ],\n [\n -141.207275390625,\n 65.0025821781929\n ],\n [\n -150.084228515625,\n 65.0025821781929\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"340","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56d80eb2e4b015c306f5ea18","contributors":{"authors":[{"text":"Edwards, Mary E.","contributorId":103490,"corporation":false,"usgs":true,"family":"Edwards","given":"Mary E.","affiliations":[],"preferred":false,"id":621678,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":621679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":621677,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDowell, Patricia F.","contributorId":116892,"corporation":false,"usgs":false,"family":"McDowell","given":"Patricia","email":"","middleInitial":"F.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":621680,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168769,"text":"70168769 - 2016 - The geologic history of Margaritifer basin, Mars","interactions":[],"lastModifiedDate":"2016-04-21T11:04:07","indexId":"70168769","displayToPublicDate":"2016-03-02T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"The geologic history of Margaritifer basin, Mars","docAbstract":"In this study, we investigate the fluvial, sedimentary, and volcanic history of Margaritifer basin and the Uzboi-Ladon-Morava (ULM) outflow channel system. This network of valleys and basins spans more than 8000 km in length, linking the fluvially dissected southern highlands and Argyre Basin with the northern lowlands via Ares Vallis. Compositionally, thermophysically, and morphologically distinct geologic units are identified and are used to place critical relative stratigraphic constraints on the timing of geologic processes in Margaritifer basin. Our analyses show that fluvial activity was separated in time by significant episodes of geologic activity, including the widespread volcanic resurfacing of Margaritifer basin and the formation of chaos terrain. The most recent fluvial activity within Margaritifer basin appears to terminate at a region of chaos terrain, suggesting possible communication between surface and subsurface water reservoirs. We conclude with a discussion of the implications of these observations on our current knowledge of Martian hydrologic evolution in this important region.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JE004938","usgsCitation":"Salvatore, M.R., Kraft, M.D., Edwards, C., and Christensen, P.R., 2016, The geologic history of Margaritifer basin, Mars: Journal of Geophysical Research E: Planets, v. 121, no. 3, p. 273-295, https://doi.org/10.1002/2015JE004938.","productDescription":"23 p.","startPage":"273","endPage":"295","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069142","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":471186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015je004938","text":"Publisher Index Page"},{"id":318497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-05","publicationStatus":"PW","scienceBaseUri":"56d80eb5e4b015c306f5ea20","contributors":{"authors":[{"text":"Salvatore, M. R.","contributorId":167279,"corporation":false,"usgs":false,"family":"Salvatore","given":"M.","email":"","middleInitial":"R.","affiliations":[{"id":24673,"text":"University of Michigan-Dearborne","active":true,"usgs":false}],"preferred":false,"id":621666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraft, M. D.","contributorId":167280,"corporation":false,"usgs":false,"family":"Kraft","given":"M.","email":"","middleInitial":"D.","affiliations":[{"id":24674,"text":"Arizona State University; Western Washington University","active":true,"usgs":false}],"preferred":false,"id":621667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Christopher cedwards@usgs.gov","contributorId":147768,"corporation":false,"usgs":true,"family":"Edwards","given":"Christopher","email":"cedwards@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":621665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, P. R.","contributorId":7819,"corporation":false,"usgs":false,"family":"Christensen","given":"P.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":621668,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168783,"text":"70168783 - 2016 - Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan","interactions":[],"lastModifiedDate":"2021-08-24T15:54:40.292443","indexId":"70168783","displayToPublicDate":"2016-03-02T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan","title":"Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan","docAbstract":"Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term “tracer” transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5b05378","usgsCitation":"Safaie, A., Wendzel, A., Ge, Z., Nevers, M., Whitman, R.L., Corsi, S., and Phanikumar, M., 2016, Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan: Environmental Science & Technology, v. 50, no. 5, p. 2442-2449, https://doi.org/10.1021/acs.est.5b05378.","productDescription":"8 p.","startPage":"2442","endPage":"2449","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069953","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":318495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan, Ogden Dunes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1,\n 41.5\n ],\n [\n -87.1,\n 41.75\n ],\n [\n -87.25,\n 41.75\n ],\n [\n -87.25,\n 41.5\n ],\n [\n -87.1,\n 41.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-15","publicationStatus":"PW","scienceBaseUri":"56d80ea9e4b015c306f5e9ec","chorus":{"doi":"10.1021/acs.est.5b05378","url":"http://dx.doi.org/10.1021/acs.est.5b05378","publisher":"American Chemical Society (ACS)","authors":"Safaie Ammar, Wendzel Aaron, Ge Zhongfu, Nevers Meredith B., Whitman Richard L., Corsi Steven R., Phanikumar Mantha S.","journalName":"Environmental Science & Technology","publicationDate":"3/2016"},"contributors":{"authors":[{"text":"Safaie, Ammar","contributorId":167285,"corporation":false,"usgs":false,"family":"Safaie","given":"Ammar","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":621744,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wendzel, Aaron","contributorId":167286,"corporation":false,"usgs":false,"family":"Wendzel","given":"Aaron","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":621745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ge, Zhongfu","contributorId":139463,"corporation":false,"usgs":false,"family":"Ge","given":"Zhongfu","email":"","affiliations":[{"id":12773,"text":"American Bureau of Shipping, Corporate Marine Technology","active":true,"usgs":false}],"preferred":false,"id":621746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nevers, Meredith 0000-0001-6963-6734 mnevers@usgs.gov","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":2013,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith","email":"mnevers@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":621743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitman, Richard L. rwhitman@usgs.gov","contributorId":542,"corporation":false,"usgs":true,"family":"Whitman","given":"Richard","email":"rwhitman@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":621747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corsi, Steven R. srcorsi@usgs.gov","contributorId":150657,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":621749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":621748,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169107,"text":"70169107 - 2016 - Effect of wastewater treatment facility closure on endocrine disrupting chemicals in a Coastal Plain stream","interactions":[],"lastModifiedDate":"2018-08-10T10:05:13","indexId":"70169107","displayToPublicDate":"2016-03-02T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3249,"text":"Remediation Journal","active":true,"publicationSubtype":{"id":10}},"title":"Effect of wastewater treatment facility closure on endocrine disrupting chemicals in a Coastal Plain stream","docAbstract":"Wastewater treatment facility (WWTF) closures are rare environmental remediation events; offering unique insight into contaminant persistence, long-term wastewater impacts, and ecosystem recovery processes. The U.S. Geological Survey assessed the fate of select endocrine disrupting chemicals (EDC) in surface water and streambed sediment one year before and one year after closure of a long-term WWTF located within the Spirit Creek watershed at Fort Gordon, Georgia. Sample sites included a WWTF-effluent control located upstream from the outfall, three downstream effluent-impacted sites located between the outfall and Spirit Lake, and one downstream from the lake's outfall. Prior to closure, the 2.2-km stream segment downstream from the WWTF outfall was characterized by EDC concentrations significantly higher (α = 0.05) than at the control site; indicating substantial downstream transport and limited in-stream attenuation of EDC, including pharmaceuticals, estrogens, alkylphenol ethoxylate (APE) metabolites, and organophosphate flame retardants (OPFR). Wastewater-derived pharmaceutical, APE metabolites, and OPFR compounds were also detected in the outflow of Spirit Lake, indicating the potential for EDC transport to aquatic ecosystems downstream of Fort Gordon under effluent discharge conditions. After the WWTF closure, no significant differences in concentrations or numbers of detected EDC compounds were observed between control and downstream locations. The results indicated EDC pseudo-persistence under preclosure, continuous supply conditions, with rapid attenuation following WWTF closure. Low concentrations of EDC at the control site throughout the study and comparable concentrations in downstream locations after WWTF closure indicated additional, continuing, upstream contaminant sources within the Spirit Creek watershed.
","language":"English","publisher":"Wiley","publisherLocation":"New York, NY","doi":"10.1002/rem.21455","usgsCitation":"Bradley, P.M., Journey, C.A., and Clark, J.M., 2016, Effect of wastewater treatment facility closure on endocrine disrupting chemicals in a Coastal Plain stream: Remediation Journal, v. 26, no. 2, p. 9-24, https://doi.org/10.1002/rem.21455.","productDescription":"16 p.","startPage":"9","endPage":"24","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071584","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Spirit Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.14048385620117,\n 33.37268517076214\n ],\n [\n -82.13722229003906,\n 33.37232677960624\n ],\n [\n -82.13644981384277,\n 33.373330271121596\n ],\n [\n -82.13747978210449,\n 33.37655570115267\n ],\n [\n -82.1389389038086,\n 33.3804977309726\n ],\n [\n -82.14177131652832,\n 33.38142945736583\n ],\n [\n -82.14571952819824,\n 33.382432843855234\n ],\n [\n -82.14923858642578,\n 33.38515626310354\n ],\n [\n -82.15018272399902,\n 33.38644627402568\n ],\n [\n -82.15344429016113,\n 33.38737793667645\n ],\n [\n -82.15524673461914,\n 33.38809459345993\n ],\n [\n -82.15644836425781,\n 33.38981454563582\n ],\n [\n -82.15696334838867,\n 33.39146280120461\n ],\n [\n -82.15696334838867,\n 33.392896041511285\n ],\n [\n -82.15893745422363,\n 33.39389929566411\n ],\n [\n -82.16116905212402,\n 33.39461589868319\n ],\n [\n -82.16176986694336,\n 33.39511751728097\n ],\n [\n -82.16357231140135,\n 33.39511751728097\n ],\n [\n -82.1641731262207,\n 33.39382763503726\n ],\n [\n -82.16297149658203,\n 33.3923227482246\n ],\n [\n -82.16082572937012,\n 33.39153446378123\n ],\n [\n -82.15953826904297,\n 33.38981454563582\n ],\n [\n -82.15902328491211,\n 33.387951262575854\n ],\n [\n -82.15799331665038,\n 33.385944605385994\n ],\n [\n -82.15361595153809,\n 33.38465458702014\n ],\n [\n -82.15198516845703,\n 33.38264785373944\n ],\n [\n -82.15009689331053,\n 33.38071274564174\n ],\n [\n -82.14752197265625,\n 33.379709339303815\n ],\n [\n -82.14503288269043,\n 33.37906428625834\n ],\n [\n -82.14340209960938,\n 33.37727244713804\n ],\n [\n -82.14194297790527,\n 33.37612565072615\n ],\n [\n -82.14168548583984,\n 33.374262074305484\n ],\n [\n -82.14125633239746,\n 33.372900204746884\n ],\n [\n -82.14048385620117,\n 33.37268517076214\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-02","publicationStatus":"PW","scienceBaseUri":"56ed26b0e4b0f59b85db09f4","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":622959,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":622960,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159457,"text":"sir20155159 - 2016 - Application of hydrogeology and groundwater-age estimates to assess the travel time of groundwater at the site of a landfill to the Mahomet Aquifer, near Clinton, Illinois","interactions":[],"lastModifiedDate":"2016-03-02T13:44:50","indexId":"sir20155159","displayToPublicDate":"2016-03-02T10:30:00","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":"2015-5159","title":"Application of hydrogeology and groundwater-age estimates to assess the travel time of groundwater at the site of a landfill to the Mahomet Aquifer, near Clinton, Illinois","docAbstract":"The U.S. Geological Survey used interpretations of hydrogeologic conditions and tritium-based groundwater age estimates to assess the travel time of groundwater at a landfill site near Clinton, Illinois (the “Clinton site”) where a chemical waste unit (CWU) was proposed to be within the Clinton landfill unit #3 (CLU#3). Glacial deposits beneath the CWU consist predominantly of low-permeability silt- and clay-rich till interspersed with thin (typically less than 2 feet in thickness) layers of more permeable deposits, including the Upper and Lower Radnor Till Sands and the Organic Soil unit. These glacial deposits are about 170 feet thick and overlie the Mahomet Sand Member of the Banner Formation. The Mahomet aquifer is composed of the Mahomet Sand Member and is used for water supply in much of east-central Illinois.
Eight tritium analyses of water from seven wells were used to evaluate the overall age of recharge to aquifers beneath the Clinton site. Groundwater samples were collected from six monitoring wells on or adjacent to the CLU#3 that were open to glacial deposits above the Mahomet aquifer (the upper and lower parts of the Radnor Till Member and the Organic Soil unit) and one proximal production well (approximately 0.5 miles from the CLU#3) that is screened in the Mahomet aquifer. The tritium-based age estimates were computed with a simplifying, piston-flow assumption: that groundwater moves in discrete packets to the sampled interval by advection, without hydrodynamic dispersion or mixing.
Tritium concentrations indicate a recharge age of at least 59 years (pre-1953 recharge) for water sampled from deposits below the upper part of the Radnor Till Member at the CLU#3, with older water expected at progressively greater depth in the tills. The largest tritium concentration from a well sampled by this study (well G53S; 0.32 ± 0.10 tritium units) was in groundwater from a sand deposit in the upper part of the Radnor Till Member; the shallowest permeable unit sampled by this study. That result indicated that nearly all groundwater sampled from well G53S entered the aquifer as recharge before 1953. Tritium was detected in a trace concentration in one sample from a second monitoring well open to the upper part of the Radnor Till Member (well G07S; 0.11 ± 0.09 tritium units), and not detected in samples collected from two monitoring wells open to a sand deposit in the lower part of the Radnor Till Member, from two samples collected from two monitoring wells open to the Organic Soil unit, and in two samples collected from a production well screened in the middle of the Mahomet aquifer (a groundwater sample and a sequential replicate sample). The lack of tritium in five of the six groundwater samples collected from the shallow permeable units beneath CLU#3 site and the two samples from the one Mahomet aquifer well indicates an absence of post-1952 recharge. Groundwater-flow paths that could contribute post-1952 recharge to the lower part of the Radnor Till Member, the Organic Soil unit, or the Mahomet aquifer at the CLU#3 are not indicated by these data.
Hypothetical two-part mixtures of tritium-dead, pre-1953 recharge water and decay-corrected tritium concentrations in post-1952 recharge were computed and compared with tritium analyses in groundwater sampled from monitoring wells at the CLU#3 site to evaluate whether tritium concentrations in groundwater could be represented by mixtures involving some post-1952 recharge. Results from the hypothetical two-part mixtures indicate that groundwater from monitoring well (G53S) was predominantly composed of pre-1953 recharge and that if present, younger, post-1955 recharge, contributed less than 2.5 percent to that sample. The hypothetical two-part mixing results also indicated that very small amounts of post-1952 recharge composing less than about 2.5 percent of the sample volume could not be distinguished in groundwater samples with tritium concentrations less than about 0.15 TU.
The piston-flow based age of recharge determined from the tritium concentration in the groundwater sample from monitoring well G53S yielded an estimated maximum vertical velocity from the land surface to the upper part of the Radnor Till Member of 0.85 feet per year or less. This velocity, ifassumed to apply to the remaining glacial till deposits above the Mahomet aquifer, indicates that recharge flows through the 170 feet of glacial deposits between the base of the proposed chemical waste unit and the top of the Mahomet aquifer in a minimum of 200 years or longer. Analysis of hydraulic data from the site, constrained by a tritium-age based maximum groundwater velocity estimate, computed minimum estimates of effective porosity that range from about 0.021 to 0.024 for the predominantly till deposits above the Mahomet aquifer.
Estimated rates of transport of recharge from land surface to the Mahomet aquifer for the CLU#3 site computed using the Darcy velocity equation with site-specific data were about 260 years or longer. The Darcy velocity-based estimates were computed using values that were based on tritium data, estimates of vertical velocity and effective porosity and available site-specific data. Solution of the Darcy velocity equation indicated that maximum vertical groundwater velocities through the deposits above the aquifer were 0.41 or 0.61 feet per year, depending on the site-specific values of vertical hydraulic conductivity (laboratory triaxial test values) and effective porosity used for the computation. The resulting calculated minimum travel times for groundwater to flow from the top of the Berry Clay Member (at the base of the proposed chemical waste unit) to the top of the Mahomet aquifer ranged from about 260 to 370 years, depending on the velocity value used in the calculation. In comparison, plausible travel times calculated using vertical hydraulic conductivity values from a previously published regional groundwater flow model were either slightly less than or longer than those calculated using site data and ranged from 230 to 580 years.
Tritium data from 1996 to 2011 USGS regional sampling of groundwater from domestic wells in the confined part of the Mahomet aquifer—which are 2.5 to about 40 miles from the Clinton site—were compared with site-specific data from a production well at the Clinton site. Tritium-based groundwater-age estimates indicated predominantly pre- 1953 recharge dates for USGS and other prior regional samples of groundwater from domestic wells in the Mahomet aquifer. These results agreed with the tritium-based, pre-1953 recharge age estimated for a groundwater sample and a sequential replicate sample from a production well in the confined part of the Mahomet aquifer beneath the Clinton site.
The regional tritium-based groundwater age estimates also were compared with pesticide detections in samples from distal domestic wells in the USGS regional network that are about 2.5 to 40 miles from the Clinton site to identify whether very small amounts of post-1952 recharge have in places reached confined parts of the Mahomet aquifer at locations other than the Clinton site in an approximately 2,000 square mile area of the Mahomet aquifer. Very small amounts of post-1952 recharge were defined in this analysis as less than about 2.5 percent of the total recharge contributing to a groundwater sample, based on results from the two-part mixing analysis of tritium data from the Clinton site. Pesticide-based groundwater-age estimates based on 22 detections of pesticides (13 of these detections were estimated concentrations), including atrazine, deethylatrazine (2-Chloro-4-isopropylamino-6-amino- s-triazine), cyanazine, diazinon, metolachlor, molinate, prometon, and trifluralin in groundwater samples from 10 domestic wells 2.5 to about 40 miles distant from the Clinton site indicate that very small amounts of post-1956 to post-1992 recharge can in places reach the confined part of the Mahomet aquifer in other parts of central Illinois. The relative lack of tritium in these samples indicate that the amounts of post-1956 to post-1992 recharge contributing to the 10 domestic wells were a very small part of the overall older groundwater sampled from those wells.
The flow process by which very small amounts of pesticide-bearing groundwater reached the screened intervals of the 10 domestic wells could not be distinguished between well-integrity related infiltration and natural hydrogeologic features. Potential explanations include: (1) infiltration through man-made avenues in or along the well, (2) flow of very small amounts of post-1956 to post-1992 recharge through sparsely distributed natural permeable aspects of the glacial till and diluted by mixing with older groundwater, or (3) a combination of both processes.
Presuming the domestic wells sampled by the USGS in 1996–2011 in the regional study of the confined part of the Mahomet aquifer are adequately sealed and produce groundwater that is representative of aquifer conditions, the regional tritium and pesticide-based groundwater-age results indicate substantial heterogeneity in the glacial stratigraphy above the Mahomet aquifer. The pesticide-based groundwater-age estimates from the domestic wells distant from the Clinton site also indicate that parts of the Mahomet aquifer with the pesticide detections can be susceptible to contaminant sources at the land surface. The regional pesticide and tritium results from the domestic wells further indicate that a potential exists for possible contaminants from land surface to be transported through the glacial drift deposits that confine the Mahomet aquifer in other parts of central Illinois at faster rates than those computed for recharge at the Clinton site, including CLU#3. This analysis indicates the potential value of sub-microgram-per-liter level concentrations of land-use derived indicators of modern recharge to indicate the presence of very small amounts of modern, post-1952 age recharge in overall older, pre-1953 age groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155159","usgsCitation":"Kay, R.T., and Buszka, P.M., 2016, Application of hydrogeology and groundwater-age estimates to assess the travel time of groundwater at the site of a landfill to the Mahomet Aquifer, near Clinton, Illinois, with a section on Regional Indications of Recharge to the Mahomet Aquifer from Previously Collected Tritium and Pesticide Data, by Buszka, P.M. and Morrow, W.S.: U.S. Geological Survey Scientific Investigations Report 2015–5159, 54 p., https://dx.doi.org/10.3133/sir20155159.\n","productDescription":"vii, 54 p.","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-038616","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":314192,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5159/coverthb.jpg"},{"id":314193,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5159/sir20155159.pdf","text":"Report","size":"1.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5159"}],"country":"United States","state":"Illinois","city":"Clinton","otherGeospatial":"Mahomet Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.96428108215332,\n 40.107618711896095\n ],\n [\n -88.96428108215332,\n 40.117793139514546\n ],\n [\n -88.94694328308105,\n 40.117793139514546\n ],\n [\n -88.94694328308105,\n 40.107618711896095\n ],\n [\n -88.96428108215332,\n 40.107618711896095\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N. Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov/