{"pageNumber":"579","pageRowStart":"14450","pageSize":"25","recordCount":40783,"records":[{"id":70155223,"text":"70155223 - 2014 - Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (<i>Ovis canadensis</i>)","interactions":[],"lastModifiedDate":"2015-08-19T10:10:42","indexId":"70155223","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (<i>Ovis canadensis</i>)","docAbstract":"<p><span>Group living facilitates pathogen transmission among social hosts, yet temporally stable host social organizations can actually limit transmission of some pathogens. When there are few between-subpopulation contacts for the duration of a disease event, transmission becomes localized to subpopulations. The number of&nbsp;</span><i>per capita</i><span>&nbsp;infectious contacts approaches the subpopulation size as pathogen infectiousness increases. Here, we illustrate that this is the case during epidemics of highly infectious pneumonia in bighorn lambs (</span><i>Ovis canadensis</i><span>). We classified individually marked bighorn ewes into disjoint seasonal subpopulations, and decomposed the variance in lamb survival to weaning into components associated with individual ewes, subpopulations, populations and years. During epidemics, lamb survival varied substantially more between ewe-subpopulations than across populations or years, suggesting localized pathogen transmission. This pattern of lamb survival was not observed during years when disease was absent. Additionally, group sizes in ewe-subpopulations were independent of population size, but the number of ewe-subpopulations increased with population size. Consequently, although one might reasonably assume that force of infection for this highly communicable disease scales with population size, in fact, host social behaviour modulates transmission such that disease is frequency-dependent within populations, and some groups remain protected during epidemic events.</span></p>","language":"English","publisher":"Royal Society","publisherLocation":"London","doi":"10.1098/rspb.2014.2331","usgsCitation":"Manlove, K.R., Cassirer, E.F., Cross, P.C., Plowright, R., and Hudson, P., 2014, Costs and benefits of group living with disease: a case study of pneumonia in bighorn lambs (<i>Ovis canadensis</i>): Proceedings of the Royal Society B, v. 281, no. 1797, art20142331, https://doi.org/10.1098/rspb.2014.2331.","productDescription":"art20142331","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058080","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472851,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2014.2331","text":"Publisher Index Page"},{"id":306916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"281","issue":"1797","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-22","publicationStatus":"PW","scienceBaseUri":"55d5a8ade4b0518e3546a4b5","contributors":{"authors":[{"text":"Manlove, Kezia R.","contributorId":74651,"corporation":false,"usgs":true,"family":"Manlove","given":"Kezia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":565166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cassirer, E. Frances","contributorId":23404,"corporation":false,"usgs":true,"family":"Cassirer","given":"E.","email":"","middleInitial":"Frances","affiliations":[],"preferred":false,"id":565167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565165,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plowright, Raina K.","contributorId":23038,"corporation":false,"usgs":true,"family":"Plowright","given":"Raina K.","affiliations":[],"preferred":false,"id":565168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hudson, Peter J.","contributorId":85056,"corporation":false,"usgs":true,"family":"Hudson","given":"Peter J.","affiliations":[],"preferred":false,"id":565169,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70147344,"text":"70147344 - 2014 - Analysis of projected water availability with current basin management plan, Pajaro Valley, California","interactions":[],"lastModifiedDate":"2015-04-30T10:49:52","indexId":"70147344","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of projected water availability with current basin management plan, Pajaro Valley, California","docAbstract":"<p id=\"sp0010\">The projection and analysis of the Pajaro Valley Hydrologic Model (PVHM) 34&nbsp;years into the future using MODFLOW with the Farm Process (MF-FMP) facilitates assessment of potential future water availability. The projection is facilitated by the integrated hydrologic model, MF-FMP that fully couples the simulation of the use and movement of water from precipitation, streamflow, runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. MF-FMP allows for more complete analysis of conjunctive-use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface-water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within &ldquo;water-balance subregions&rdquo; (WBS) comprised of one or more model cells that can represent a single farm, a group of farms, watersheds, or other hydrologic or geopolitical entities. Analysis of conjunctive use would be difficult without embedding the fully coupled supply-and-demand into a fully coupled simulation, and are difficult to estimate a priori.</p>\n<p id=\"sp0015\">The analysis of projected supply and demand for the Pajaro Valley indicate that the current water supply facilities constructed to provide alternative local sources of supplemental water to replace coastal groundwater pumpage, but may not completely eliminate additional overdraft. The simulation of the coastal distribution system (CDS) replicates: 20 miles of conveyance pipeline, managed aquifer recharge and recovery (MARR) system that captures local runoff, and recycled-water treatment facility (RWF) from urban wastewater, along with the use of other blend water supplies, provide partial relief and substitution for coastal pumpage (aka in-lieu recharge). The effects of these Basin Management Plan (BMP) projects were analyzed subject to historical climate variations and assumptions of 2009 urban water demand and land use. Water supplied directly from precipitation, and indirectly from reuse, captured local runoff, and groundwater is necessary but inadequate to satisfy agricultural demand without coastal and regional storage depletion that facilitates seawater intrusion. These facilities reduce potential seawater intrusion by about 45% with groundwater levels in the four regions served by the CDS projected to recover to levels a few feet above sea level. The projected recoveries are not high enough to prevent additional seawater intrusion during dry-year periods or in the deeper aquifers where pumpage is greater. While these facilities could reduce coastal pumpage by about 55% of the historical 2000&ndash;2009 pumpage for these regions, and some of the water is delivered in excess of demand, other coastal regions continue to create demands on coastal pumpage that will need to be replaced to reduce seawater intrusion. In addition, inland urban and agricultural demands continue to sustain water levels below sea level causing regional landward gradients that also drive seawater intrusion. Seawater intrusion is reduced by about 45% but it supplies about 55% of the recovery of groundwater levels in the coastal regions served by the CDS. If economically feasible, water from summer agricultural runoff and tile-drain returnflows could be another potential local source of water that, if captured and reused, could offset the imbalance between supply and demand as well as reducing discharge of agricultural runoff into the National Marine Sanctuary of Monterey Bay. A BMP update (2012) identifies projects and programs that will fund a conservation program and will provide additional, alternative water sources to reduce or replace coastal and inland pumpage, and to replenish the aquifers with managed aquifer recharge in an inland portion of the Pajaro Valley.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.07.005","usgsCitation":"Hanson, R.T., Lockwood, B., and Schmid, W., 2014, Analysis of projected water availability with current basin management plan, Pajaro Valley, California: Journal of Hydrology: Regional Studies, v. 519, no. A, p. 131-147, https://doi.org/10.1016/j.jhydrol.2014.07.005.","productDescription":"17 p.","startPage":"131","endPage":"147","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041544","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":299982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pajaro Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.84112548828125,\n              36.797739040981085\n            ],\n            [\n              -121.84112548828125,\n              36.89005557519409\n            ],\n            [\n              -121.70654296874999,\n              36.89005557519409\n            ],\n            [\n              -121.70654296874999,\n              36.797739040981085\n            ],\n            [\n              -121.84112548828125,\n              36.797739040981085\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"519","issue":"A","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55435229e4b0a658d794149f","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockwood, Brian","contributorId":80202,"corporation":false,"usgs":true,"family":"Lockwood","given":"Brian","email":"","affiliations":[],"preferred":false,"id":545831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmid, Wolfgang","contributorId":84020,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","affiliations":[{"id":13040,"text":"Department of Hydrology and Water Resources, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":545832,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70146957,"text":"70146957 - 2014 - Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States","interactions":[],"lastModifiedDate":"2015-04-24T10:45:15","indexId":"70146957","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States","docAbstract":"<p><span>Forest ecosystems play a critical role in mitigating greenhouse gas emissions. Forest carbon (C) is stored through photosynthesis and released via decomposition and combustion. Relative to C fixation in biomass, much less is known about C depletion through decomposition of woody debris, particularly under a changing climate. It is assumed that the increased temperatures and longer growing seasons associated with projected climate change will increase the decomposition rates (i.e., more rapid C cycling) of downed woody debris (DWD); however, the magnitude of this increase has not been previously addressed. Using DWD measurements collected from a national forest inventory of the eastern United States, we show that the residence time of DWD may decrease (i.e., more rapid decomposition) by as much as 13% over the next 200 years, depending on various future climate change scenarios and forest types. Although existing dynamic global vegetation models account for the decomposition process, they typically do not include the effect of a changing climate on DWD decomposition rates. We expect that an increased understanding of decomposition rates, as presented in this current work, will be needed to adequately quantify the fate of woody detritus in future forests. Furthermore, we hope these results will lead to improved models that incorporate climate change scenarios for depicting future dead wood dynamics in addition to a traditional emphasis on live-tree demographics.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-11-6417-2014","usgsCitation":"Russell, M.B., Woodall, C.W., D’Amato, A.W., Fraver, S., and Bradford, J.B., 2014, Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States: Biogeosciences, v. 11, p. 6417-6425, https://doi.org/10.5194/bg-11-6417-2014.","productDescription":"9 p.","startPage":"6417","endPage":"6425","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056891","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472675,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-11-6417-2014","text":"Publisher Index Page"},{"id":299861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -97.20703125,\n              28.613459424004414\n            ],\n            [\n              -97.20703125,\n              49.61070993807422\n            ],\n            [\n              -66.796875,\n              49.61070993807422\n            ],\n            [\n              -66.796875,\n              28.613459424004414\n            ],\n            [\n              -97.20703125,\n              28.613459424004414\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-26","publicationStatus":"PW","scienceBaseUri":"553b6960e4b0a658d79371d1","contributors":{"authors":[{"text":"Russell, Matthew B.","contributorId":140407,"corporation":false,"usgs":false,"family":"Russell","given":"Matthew","email":"","middleInitial":"B.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false}],"preferred":false,"id":545523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woodall, Christopher W.","contributorId":53696,"corporation":false,"usgs":false,"family":"Woodall","given":"Christopher","email":"","middleInitial":"W.","affiliations":[{"id":7264,"text":"USDA Forest Service, Northern Research Station, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":545524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Amato, Anthony W.","contributorId":28140,"corporation":false,"usgs":false,"family":"D’Amato","given":"Anthony","email":"","middleInitial":"W.","affiliations":[{"id":13478,"text":"Department of Forest Resources, University of Minnesota, St. Paul, Minnesota (Correspondence to: russellm@umn.edu)","active":true,"usgs":false},{"id":6735,"text":"University of Vermont, Rubenstein School of Environment and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":545526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fraver, Shawn","contributorId":91379,"corporation":false,"usgs":false,"family":"Fraver","given":"Shawn","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":545525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":545522,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191714,"text":"70191714 - 2014 - A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest","interactions":[],"lastModifiedDate":"2017-11-08T17:06:40","indexId":"70191714","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest","docAbstract":"<p><span>Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring.</span></p>","language":"English","doi":"10.1109/TGRS.2014.2313558","usgsCitation":"Li, L., Schwartz, M., Wang, Z., Gao, F., Schaaf, C.B., Bin Tan, Morisette, J.T., and Zhang, X., 2014, A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest: IEEE Transactions on Geoscience and Remote Sensing, v. 52, no. 12, p. 7513-7526, https://doi.org/10.1109/TGRS.2014.2313558.","productDescription":"14 p.","startPage":"7513","endPage":"7526","ipdsId":"IP-053376","costCenters":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"links":[{"id":348521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Chequamegon–Nicolet National Forest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.35362243652344,\n              45.83501885571072\n            ],\n            [\n              -90.10711669921875,\n              45.83501885571072\n            ],\n            [\n              -90.10711669921875,\n              45.98217232489232\n            ],\n            [\n              -90.35362243652344,\n              45.98217232489232\n            ],\n            [\n              -90.35362243652344,\n              45.83501885571072\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"52","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425c6e4b0dc0b45b4541e","contributors":{"authors":[{"text":"Li, Li 0000-0002-1641-3710","orcid":"https://orcid.org/0000-0002-1641-3710","contributorId":197290,"corporation":false,"usgs":false,"family":"Li","given":"Li","affiliations":[],"preferred":false,"id":713151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwartz, Mark D.","contributorId":11092,"corporation":false,"usgs":true,"family":"Schwartz","given":"Mark D.","affiliations":[],"preferred":false,"id":713152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Zhuosen","contributorId":197296,"corporation":false,"usgs":false,"family":"Wang","given":"Zhuosen","email":"","affiliations":[],"preferred":false,"id":713153,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gao, Feng 0000-0002-1865-2846","orcid":"https://orcid.org/0000-0002-1865-2846","contributorId":70671,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","email":"","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":713154,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaaf, Crystal B.","contributorId":149538,"corporation":false,"usgs":false,"family":"Schaaf","given":"Crystal","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":713155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bin Tan","contributorId":197299,"corporation":false,"usgs":false,"family":"Bin Tan","affiliations":[],"preferred":false,"id":713156,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":713150,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhang, Xiaoyang","contributorId":197726,"corporation":false,"usgs":false,"family":"Zhang","given":"Xiaoyang","email":"","affiliations":[],"preferred":false,"id":713157,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70188041,"text":"70188041 - 2014 - A suggestion for computing objective function in model calibration","interactions":[],"lastModifiedDate":"2017-05-30T15:57:15","indexId":"70188041","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"A suggestion for computing objective function in model calibration","docAbstract":"<p><span>A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2014.08.002","usgsCitation":"Wu, Y., and Liu, S., 2014, A suggestion for computing objective function in model calibration: Ecological Informatics, v. 24, p. 107-111, https://doi.org/10.1016/j.ecoinf.2014.08.002.","productDescription":"5 p.","startPage":"107","endPage":"111","ipdsId":"IP-058778","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472664,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2014.08.002","text":"Publisher Index Page"},{"id":341882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c2e4b092b266f10d75","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696521,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70188047,"text":"70188047 - 2014 - Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using <sup>137</sup>Cs in two U.S. Midwest agricultural fields","interactions":[],"lastModifiedDate":"2017-05-30T16:01:43","indexId":"70188047","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using <sup>137</sup>Cs in two U.S. Midwest agricultural fields","docAbstract":"<p><span>Cultivated lands in the U.S. Midwest have been affected by soil erosion, causing soil organic carbon (SOC) redistribution in the landscape and other environmental and agricultural problems. The importance of SOC redistribution on soil productivity and crop yield, however, is still uncertain. In this study, we used a model framework, which includes the Unit Stream Power-based Erosion Deposition (USPED) and the Tillage Erosion Prediction (TEP) models, to understand the soil and SOC redistribution caused by water and tillage erosion in two agricultural fields in the U.S. Midwest. This model framework was evaluated for different digital elevation model (DEM) spatial resolutions (10-m, 24-m, 30-m, and 56-m) and topographic exponents (</span><i>m</i><span>&nbsp;=&nbsp;1.0–1.6 and </span><i>n</i><span>&nbsp;=&nbsp;1.0–1.3) using soil redistribution rates from </span><sup>137</sup><span>Cs measurements. The results showed that the aggregated 24-m DEM, </span><i>m</i><span>&nbsp;=&nbsp;1.4 and </span><i>n</i><span>&nbsp;=&nbsp;1.0 for rill erosion, and </span><i>m</i><span>&nbsp;=&nbsp;1.0 and </span><i>n</i><span>&nbsp;=&nbsp;1.0 for sheet erosion, provided the best fit with the observation data at both sites. Moreover, estimated average SOC redistributions were 1.3&nbsp;±&nbsp;9.8&nbsp;g C&nbsp;m</span><sup>−&nbsp;2</sup><span>&nbsp;yr</span><sup>−&nbsp;1</sup><span> in field site 1 and 3.6&nbsp;±&nbsp;14.3&nbsp;g C&nbsp;m</span><sup>−&nbsp;2</sup><span>&nbsp;yr</span><sup>−&nbsp;1</sup><span> in field site 2. Spatial distribution patterns showed SOC loss (negative values) in the eroded areas and SOC gain (positive value) in the deposition areas. This study demonstrated the importance of the spatial resolution and the topographic exponents to estimate and map soil redistribution and the SOC dynamics throughout the landscape, helping to identify places where erosion and deposition from water and tillage are occurring at high rates. Additional research is needed to improve the application of the model framework for use in local and regional studies where rainfall erosivity and cover management factors vary. Therefore, using this model framework can help to improve the information about the spatial distribution of soil erosion across agricultural landscapes and to gain a better understanding of SOC dynamics within eroding and previously eroded fields.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2014.05.019","usgsCitation":"Young, C.J., Liu, S., Schumacher, J.A., Schumacher, T.E., Kaspar, T.C., McCarty, G.W., Napton, D., and Jaynes, D.B., 2014, Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using <sup>137</sup>Cs in two U.S. Midwest agricultural fields: Geoderma, v. 232-234, p. 437-448, https://doi.org/10.1016/j.geoderma.2014.05.019.","productDescription":"12 p.","startPage":"437","endPage":"448","ipdsId":"IP-051307","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","volume":"232-234","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c1e4b092b266f10d71","contributors":{"authors":[{"text":"Young, Claudia J. 0000-0002-0859-7206 cyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":2770,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"cyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schumacher, Joseph A.","contributorId":192364,"corporation":false,"usgs":false,"family":"Schumacher","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":696314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schumacher, Thomas E.","contributorId":192365,"corporation":false,"usgs":false,"family":"Schumacher","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":696315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kaspar, Thomas C.","contributorId":192366,"corporation":false,"usgs":false,"family":"Kaspar","given":"Thomas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":696316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":696317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Napton, Darrell","contributorId":176288,"corporation":false,"usgs":false,"family":"Napton","given":"Darrell","affiliations":[],"preferred":false,"id":696318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jaynes, Dan B.","contributorId":192368,"corporation":false,"usgs":false,"family":"Jaynes","given":"Dan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":696319,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70178372,"text":"70178372 - 2014 - Transcriptomic analysis of the mussel <i>Elliptio complanata</i> identifies candidate stress-response genes and an abundance of novel or noncoding transcripts","interactions":[],"lastModifiedDate":"2017-07-24T10:35:24","indexId":"70178372","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Transcriptomic analysis of the mussel <i>Elliptio complanata</i> identifies candidate stress-response genes and an abundance of novel or noncoding transcripts","docAbstract":"<p><span>Mussels are useful indicator species of environmental stress and degradation, and the global decline in freshwater mussel diversity and abundance is of conservation concern. </span><i>Elliptio complanata</i><span> is a common freshwater mussel of eastern North America that can serve both as an indicator and as an experimental model for understanding mussel physiology and genetics. To support genetic components of these research goals, we assembled transcriptome contigs from Illumina paired-end reads. Despite efforts to collapse similar contigs, the final assembly was in excess of 136,000 contigs with an N50 of 982 bp. Even so, comparisons to the CEGMA database of conserved eukaryotic genes indicated that ∼20% of genes remain unrepresented. However, numerous candidate stress-response genes were present, and we identified lineage-specific patterns of diversification among molluscs for cytochrome P450 detoxification genes and two saccharide-modifying enzymes: 1,3 beta-galactosyltransferase and fucosyltransferase. Less than a quarter of contigs had protein-level similarity based on modest BLAST and Hmmer3 statistical thresholds. These results add comparative genomic resources for molluscs and suggest a wealth of novel proteins and noncoding transcripts.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0112420","usgsCitation":"Cornman, R.S., Robertson, L.S., Galbraith, H.S., and Blakeslee, C.J., 2014, Transcriptomic analysis of the mussel <i>Elliptio complanata</i> identifies candidate stress-response genes and an abundance of novel or noncoding transcripts: PLoS ONE, v. 9, no. 11, e112420; 10 p., https://doi.org/10.1371/journal.pone.0112420.","productDescription":"e112420; 10 p.","ipdsId":"IP-060559","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":472676,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0112420","text":"Publisher Index Page"},{"id":330996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-11-06","publicationStatus":"PW","scienceBaseUri":"582c2ce6e4b0c253be072c0c","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":653795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Laura S. lrobertson@usgs.gov","contributorId":2288,"corporation":false,"usgs":true,"family":"Robertson","given":"Laura","email":"lrobertson@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":653796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Galbraith, Heather S. 0000-0003-3704-3517 hgalbraith@usgs.gov","orcid":"https://orcid.org/0000-0003-3704-3517","contributorId":4519,"corporation":false,"usgs":true,"family":"Galbraith","given":"Heather","email":"hgalbraith@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":653797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":653798,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188050,"text":"70188050 - 2014 - Understanding the hydrologic sources and sinks in the Nile Basin using multisource climate and remote sensing data sets","interactions":[],"lastModifiedDate":"2017-05-30T15:10:08","indexId":"70188050","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the hydrologic sources and sinks in the Nile Basin using multisource climate and remote sensing data sets","docAbstract":"<p><span>In this study, we integrated satellite-drived precipitation and modeled evapotranspiration data (2000–2012) to describe spatial variability of hydrologic sources and sinks in the Nile Basin. Over 2000–2012 period, 4 out of 11 countries (Ethiopia, Tanzania, Kenya, and Uganda) in the Nile Basin showed a positive water balance while three downstream countries (South Sudan, Sudan, and Egypt) showed a negative balance. Gravity Recovery and Climate Experiment (GRACE) mass deviation in storage data analysis showed that at annual timescales, the Nile Basin storage change is substantial while over longer time periods, it is minimal (&lt;1% of basin precipitation). We also used long-term gridded runoff and river discharge data (1869–1984) to understand the discrepancy in the observed and expected flow along the Nile River. The top three countries that contribute most to the flow are Ethiopia, Tanzania, and Kenya. The study revealed that ∼85% of the runoff generated in the equatorial region is lost in an interstation basin that includes the Sudd wetlands in South Sudan; this proportion is higher than the literature reported loss of 50% at the Sudd wetlands alone. The loss in runoff and flow volume at different sections of the river tend to be more than what can be explained by evaporation losses, suggesting a potential recharge to deeper aquifers that are not connected to the Nile channel systems. On the other hand, we also found that the expected average annual Nile flow at Aswan is greater (97 km</span><sup>3</sup><span>) than the reported amount (84 km</span><sup>3</sup><span>). Due to the large variations of the reported Nile flow at different locations and time periods, the study results indicate the need for increased hydrometeorological instrumentation of the basin. The study also helped improve our understanding of the spatial dynamics of water sources and sinks in the Nile Basin and identified emerging hydrologic questions that require further attention.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/2013WR015231","usgsCitation":"Senay, G., Velpuri, N.M., Bohms, S., Demissie, Y., and Gebremichael, M., 2014, Understanding the hydrologic sources and sinks in the Nile Basin using multisource climate and remote sensing data sets: Water Resources Research, v. 50, no. 11, p. 8625-8650, https://doi.org/10.1002/2013WR015231.","productDescription":"26 p.","startPage":"8625","endPage":"8650","ipdsId":"IP-054002","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013wr015231","text":"Publisher Index Page"},{"id":341873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Nile Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              23.818359375,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              -3.688855143147035\n            ],\n            [\n              37.6171875,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              31.57853542647338\n            ],\n            [\n              23.818359375,\n              -3.688855143147035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"50","issue":"11","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-11","publicationStatus":"PW","scienceBaseUri":"592e84c0e4b092b266f10d6d","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"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},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":166813,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Demissie, Yonas","contributorId":192369,"corporation":false,"usgs":false,"family":"Demissie","given":"Yonas","email":"","affiliations":[],"preferred":false,"id":696325,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gebremichael, Mekonnen","contributorId":147882,"corporation":false,"usgs":false,"family":"Gebremichael","given":"Mekonnen","email":"","affiliations":[],"preferred":false,"id":696326,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70120714,"text":"70120714 - 2014 - Holocene earthquakes and right-lateral slip on the left-lateral Darrington-Devils Mountain fault zone, northern Puget Sound, Washington","interactions":[],"lastModifiedDate":"2015-01-26T13:33:58","indexId":"70120714","displayToPublicDate":"2014-11-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Holocene earthquakes and right-lateral slip on the left-lateral Darrington-Devils Mountain fault zone, northern Puget Sound, Washington","docAbstract":"<p><span>Sources of seismic hazard in the Puget Sound region of northwestern Washington include deep earthquakes associated with the Cascadia subduction zone, and shallow earthquakes associated with some of the numerous crustal (upper-plate) faults that crisscross the region. Our paleoseismic investigations on one of the more prominent crustal faults, the Darrington&ndash;Devils Mountain fault zone, included trenching of fault scarps developed on latest Pleistocene glacial sediments and analysis of cores from an adjacent wetland near Lake Creek, 14 km southeast of Mount Vernon, Washington. Trench excavations revealed evidence of a single earthquake, radiocarbon dated to ca. 2 ka, but extensive burrowing and root mixing of sediments within 50&ndash;100 cm of the ground surface may have destroyed evidence of other earthquakes. Cores in a small wetland adjacent to our trench site provided stratigraphic evidence (formation of a laterally extensive, prograding wedge of hillslope colluvium) of an earthquake ca. 2 ka, which we interpret to be the same earthquake documented in the trenches. A similar colluvial wedge lower in the wetland section provides possible evidence for a second earthquake dated to ca. 8 ka. Three-dimensional trenching techniques revealed evidence for 2.2 &plusmn; 1.1 m of right-lateral offset of a glacial outwash channel margin, and 45&ndash;70 cm of north-side-up vertical separation across the fault zone. These offsets indicate a net slip vector of 2.3 &plusmn; 1.1 m, plunging 14&deg; west on a 286&deg;-striking, 90&deg;-dipping fault plane. The dominant right-lateral sense of slip is supported by the presence of numerous Riedel R shears preserved in two of our trenches, and probable right-lateral offset of a distinctive bedrock fault zone in a third trench. Holocene north-side-up, right-lateral oblique slip is opposite the south-side-up, left-lateral oblique sense of slip inferred from geologic mapping of Eocene and older rocks along the fault zone. The cause of this slip reversal is unknown but may be related to clockwise rotation of the Darrington&ndash;Devils Mountain fault zone into a position more favorable to right-lateral slip in the modern N-S compressional stress field.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01067.1","usgsCitation":"Personius, S.F., Briggs, R.W., Nelson, A.R., Schermer, E.R., Maharrey, J.Z., Sherrod, B.L., Spaulding, S.A., and Bradley, L., 2014, Holocene earthquakes and right-lateral slip on the left-lateral Darrington-Devils Mountain fault zone, northern Puget Sound, Washington: Geosphere, v. 10, no. 6, p. 1482-1500, https://doi.org/10.1130/GES01067.1.","productDescription":"19 p.","startPage":"1482","endPage":"1500","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059226","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":472667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01067.1","text":"Publisher Index Page"},{"id":297530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.46435546875,\n              48.93693495409401\n            ],\n            [\n              -122.10205078125,\n              48.90805939965008\n            ],\n            [\n              -122.14599609375001,\n              47.27922900257082\n            ],\n            [\n              -123.02490234375,\n              47.2195681123155\n            ],\n            [\n              -123.46435546875,\n              48.93693495409401\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2bc6e4b08de9379b34c0","contributors":{"authors":[{"text":"Personius, Stephen F. personius@usgs.gov","contributorId":1214,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","middleInitial":"F.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":519229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":519231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":519226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schermer, Elizabeth R","contributorId":115146,"corporation":false,"usgs":true,"family":"Schermer","given":"Elizabeth","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":519232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maharrey, J. Zebulon","contributorId":116234,"corporation":false,"usgs":true,"family":"Maharrey","given":"J.","email":"","middleInitial":"Zebulon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":519233,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":519230,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spaulding, Sarah A. 0000-0002-9787-7743 sspaulding@usgs.gov","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":1157,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","email":"sspaulding@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":519228,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bradley, Lee-Ann bradley@usgs.gov","contributorId":1141,"corporation":false,"usgs":true,"family":"Bradley","given":"Lee-Ann","email":"bradley@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":519227,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70122403,"text":"sir20145149 - 2014 - Aquifers of Arkansas: protection, management, and hydrologic and geochemical characteristics of groundwater resources in Arkansas","interactions":[],"lastModifiedDate":"2015-04-09T09:29:28","indexId":"sir20145149","displayToPublicDate":"2014-10-31T15:30:00","publicationYear":"2014","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":"2014-5149","title":"Aquifers of Arkansas: protection, management, and hydrologic and geochemical characteristics of groundwater resources in Arkansas","docAbstract":"<p>Sixteen aquifers in Arkansas that currently serve or have served as sources of water supply are described with respect to existing groundwater protection and management programs, geology, hydrologic characteristics, water use, water levels, deductive analysis, projections of hydrologic conditions, and water quality. State and Federal protection and management programs are described according to regulatory oversight, management strategies, and ambient groundwater-monitoring programs that currently (2013) are in place for assessing and protecting groundwater resources throughout the State.</p>\n<p>&nbsp;</p>\n<p>Physical attributes, groundwater geochemistry, and groundwater quality are described for each of the 16 aquifers of the State. Information in regard to the hydrology and geochemistry of each of the aquifers is summarized from about 550 historical and recent publications. Additionally, more than 8,000 sites with groundwater-quality data were obtained from the U.S. Geological Survey National Water Information System and the Arkansas Department of Environmental Quality databases and entered into a spatial database to investigate distribution and trends in chemical constituents for each of the aquifers.</p>\n<p>&nbsp;</p>\n<p>The 16 aquifers of the State were divided into two major physiographic regions of the State: the Coastal Plain Province (referred to as Coastal Plain) of eastern and southern Arkansas, which includes 11 of the 16 aquifers, and the Interior Highlands Division (referred to as Interior Highlands) of western Arkansas, which includes the remaining 5 aquifers. The 11 aquifers in the Coastal Plain consist of various geologic units that are Cenozoic in age and consist primarily of Cretaceous, Tertiary, and Quaternary sands, gravels, silts, and clays. Groundwater in the Coastal Plain represents one of the most valuable natural resources in the State, driving the economic engines of agriculture, while also supplying abundant water for commercial, industrial, and public-supply use. In terms of age from youngest to oldest, the aquifers of the Coastal Plain include Quaternary alluvial aquifers, including the Mississippi River Valley alluvial aquifer (the most important aquifer in Arkansas in terms of volume of use and economic benefits), the Jackson Group (a regional confining unit that served for decades as an important source of domestic supply), and the Cockfield, Sparta, Cane River, Carrizo, Wilcox, Nacatoch, Ozan, Tokio, and Trinity aquifers. The Mississippi River Valley alluvial aquifer accounts for approximately 94 percent of all groundwater used in the State, and the aquifer is used primarily for irrigation purposes. The Sparta aquifer is the second most important aquifer in terms of use, and the aquifer was used in the past dominantly as a source of public and industrial supply, although increasing irrigation use is occurring because of critically declining water levels in the Mississippi River Valley alluvial aquifer. Other aquifers of the Coastal Plain generally are used as important local sources of domestic, industrial, and public supply, in addition to other minor uses. Water quality generally is good for all aquifers of the Coastal Plain, except for elevated iron concentrations and localized areas of high salinity. The high salinity results from intrusion from underlying formations, evapotranspiration processes in areas of low recharge, and inadequate flushing in downgradient areas of residual salinity from deposition in marine environments. Trends in the spatial distribution of individual chemical constituents are related to position along the flow path for most aquifers of the Coastal Plain. These trends include elevated iron and nitrate concentrations with lower pH values and dissolved solids in groundwater from the outcrop areas, transitioning to lower iron and nitrate (related to changes in redox) and higher pH and dissolved solids (dominantly from the dissolution of carbonate minerals) in groundwater downgradient from outcrop areas. Groundwater generally trended from a calcium- to a sodium-bicarbonate water type with increasing cation exchange along the flow path.</p>\n<p>&nbsp;</p>\n<p>The Interior Highlands of western Arkansas has less reported groundwater use than other areas of the State, reflecting a combination of factors. These factors include prevalent and increasing use of surface water, less intensive agricultural uses, lower population and industry densities, lesser potential yield of the resource, and lack of detailed reporting. The overall low yields of aquifers of the Interior Highlands result in domestic supply as the dominant use, with minor industrial, public, and commercial-supply use. Where greater volumes are required for growth of population and industry, surface water is the greatest supplier of water needs in the Interior Highlands. The various aquifers of the Interior Highlands generally occur in shallow, fractured, well-indurated, structurally modified bedrock of this mountainous region of the State, as compared to the relatively flat-lying, unconsolidated sediments of the Coastal Plain. In terms of age from youngest to oldest, the aquifers of the Interior Highlands include: the Arkansas River Valley alluvial aquifer, the Ouachita Mountains aquifer, the Western Interior Plains confining system, the Springfield Plateau aquifer, and the Ozark aquifer. Spatial trends in groundwater geochemistry in the Interior Highlands differ greatly from trends noted for aquifers of the Coastal Plain. In the Coastal Plain, the prevalence of long regional flow paths results in regionally predictable and mappable geochemical changes along the flow paths. In the Interior Highlands, short, topographically controlled flow paths (from hilltops to valleys) within small watersheds represent the predominant groundwater-flow system. As such, dense data coverage from numerous wells would be required to effectively characterize these groundwater basins and define small-scale geochemical changes along any given flow path for aquifers of the Interior Highlands. Changes in geochemistry generally were related to rock type and residence time along individual flow paths. Dominant changes in geochemistry for the Ouachita Mountains aquifer and the Western Interior Plains confining system are attributed to rock/water interaction and changes in redox zonation along the flow path. In these areas, groundwater evolves along flow paths from a calcium- to a sodium-bicarbonate water type with increasing reducing conditions resulting in denitrification, elevated iron and manganese concentrations, and production of methane in the more geochemically evolved and strongest reducing conditions. In the Ozark and Springfield Plateau aquifers, rapid influx of surface-derived contaminants, especially nitrogen, coupled with few to no attenuation processes was attributed to the karst landscape developed on Mississippian- and Ordovician-age carbonate rocks of the Ozark Plateaus. Increasing nitrate concentrations are related to increasing agricultural land use, and areas of mature karst development result in higher nitrate concentrations than areas with less karst features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145149","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission","usgsCitation":"Kresse, T.M., Hays, P.D., Merriman, K.R., Gillip, J.A., Fugitt, D., Spellman, J.L., Nottmeier, A.M., Westerman, D.A., Blackstock, J.M., and Battreal, J.L., 2014, Aquifers of Arkansas: protection, management, and hydrologic and geochemical characteristics of groundwater resources in Arkansas: U.S. Geological Survey Scientific Investigations Report 2014-5149, Report: xxi, 334 p.; Report pages 1-111; Report pages 112-221; Report pages 222-235, https://doi.org/10.3133/sir20145149.","productDescription":"Report: xxi, 334 p.; Report pages 1-111; Report pages 112-221; Report pages 222-235","numberOfPages":"360","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-054912","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":295819,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145149.jpg"},{"id":299534,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2014/5149/pdf/sir2014-5149_Aquifers.pdf","text":"Aquifers of the Interior Highlands through Summary","size":"5.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report pages 250-311","linkHelpText":"Report pages 250-311"},{"id":299535,"rank":7,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2014/5149/pdf/sir2014-5149_References.pdf","text":"References","size":"275 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report pages 312-335","linkHelpText":"Report pages 312-335"},{"id":295813,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2014/5149/pdf/sir2014-5149_Contents.pdf","text":"Contents, Conversion Factors, Acronyms","size":"237 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report Front Matter","linkHelpText":"Report Front Matter"},{"id":295814,"rank":4,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2014/5149/pdf/sir2014-5149_Abstract.pdf","text":"Abstract through the Mississippi River Valley Alluvial Aquifer","size":"20.2 MB","description":"Report pages 1-111","linkHelpText":"Report pages 1-111"},{"id":295815,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2014/5149/pdf/sir2014-5149_MinorAlluvial.pdf","text":"Minor Alluvial Aquifers in Coastal Plain through the Trinity Aquifer","size":"23.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report pages 112-249","linkHelpText":"Report pages 112-249"},{"id":295783,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5149/"},{"id":295812,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5149/pdf/sir2014-5149.pdf","size":"54.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Arkasas","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c9bb2e4b0ba8303f709a9","contributors":{"authors":[{"text":"Kresse, Timothy M. 0000-0003-1035-0672 tkresse@usgs.gov","orcid":"https://orcid.org/0000-0003-1035-0672","contributorId":2758,"corporation":false,"usgs":true,"family":"Kresse","given":"Timothy","email":"tkresse@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merriman, Katherine R. 0000-0002-1303-2410 kmerriman@usgs.gov","orcid":"https://orcid.org/0000-0002-1303-2410","contributorId":4973,"corporation":false,"usgs":true,"family":"Merriman","given":"Katherine","email":"kmerriman@usgs.gov","middleInitial":"R.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":522844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gillip, Jonathan A. jgillip@usgs.gov","contributorId":3222,"corporation":false,"usgs":true,"family":"Gillip","given":"Jonathan","email":"jgillip@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fugitt, D. Todd","contributorId":127005,"corporation":false,"usgs":false,"family":"Fugitt","given":"D. Todd","affiliations":[{"id":6759,"text":"Arkansas","active":true,"usgs":false}],"preferred":false,"id":522846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spellman, Jane L.","contributorId":127006,"corporation":false,"usgs":false,"family":"Spellman","given":"Jane","email":"","middleInitial":"L.","affiliations":[{"id":6760,"text":"FTN Associates, Ltd","active":true,"usgs":false}],"preferred":false,"id":522847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Westerman, Drew A. 0000-0002-8522-776X dawester@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-776X","contributorId":4526,"corporation":false,"usgs":true,"family":"Westerman","given":"Drew","email":"dawester@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blackstock, Joshua M. jblackst@usgs.gov","contributorId":5553,"corporation":false,"usgs":true,"family":"Blackstock","given":"Joshua","email":"jblackst@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":522850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Battreal, James L.","contributorId":127019,"corporation":false,"usgs":false,"family":"Battreal","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":6759,"text":"Arkansas","active":true,"usgs":false}],"preferred":false,"id":522898,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70122361,"text":"sir20145166 - 2014 - Groundwater-flow and land-subsidence model of Antelope Valley, California","interactions":[],"lastModifiedDate":"2014-10-31T15:21:38","indexId":"sir20145166","displayToPublicDate":"2014-10-31T14:00:00","publicationYear":"2014","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":"2014-5166","title":"Groundwater-flow and land-subsidence model of Antelope Valley, California","docAbstract":"<p>Antelope Valley, California, is a topographically closed basin in the western part of the Mojave Desert, about 50 miles northeast of Los Angeles. The Antelope Valley groundwater basin is about 940 square miles and is separated from the northern part of Antelope Valley by faults and low-lying hills. Prior to 1972, groundwater provided more than 90 percent of the total water supply in the valley; since 1972, it has provided between 50 and 90 percent. Most groundwater pumping in the valley occurs in the Antelope Valley groundwater basin, which includes the rapidly growing cities of Lancaster and Palmdale. Groundwater-level declines of more than 270 feet in some parts of the groundwater basin have resulted in an increase in pumping lifts, reduced well efficiency, and land subsidence of more than 6 feet in some areas. Future urban growth and limits on the supply of imported water may increase reliance on groundwater.</p>\n<p>&nbsp;</p>\n<p>In 2011, the Los Angeles County Superior Court of California ruled that the Antelope Valley groundwater basin is in overdraft&mdash;groundwater extractions are in excess of the Court-defined safe yield of the groundwater basin. The Court determined that the safe yield of the adjudicated area of the basin was 110,000 acre-feet per year (acre-ft/yr). Natural recharge is an important component of total groundwater recharge in Antelope Valley; however, the exact quantity and distribution of natural recharge, primarily in the form of mountain-front recharge, is uncertain, with total estimates ranging from 30,000 to 160,000 acre-ft/yr. Technical experts, retained by parties to the adjudication, used 60,000 acre-ft/yr to estimate the sustainable yield of the basin, and this value was used in this study. In order to better understand the uncertainty associated with natural recharge and to provide a tool to aid in groundwater management, a numerical model of groundwater flow and land subsidence in the Antelope Valley groundwater basin was developed using old and new geohydrologic information.</p>\n<p>&nbsp;</p>\n<p>The groundwater-flow system consists of three aquifers: the upper, middle, and lower aquifers. The three aquifers, which were identified on the basis of the hydrologic properties, age, and depth of the unconsolidated deposits, consist of gravel, sand, silt, and clay alluvial deposits and clay and silty clay lacustrine deposits. Prior to groundwater development in the valley, recharge was primarily the infiltration of runoff from the surrounding mountains. Groundwater flowed from the recharge areas to discharge areas around the playas where it discharged from the aquifer system as either evapotranspiration or from springs. Partial barriers to horizontal groundwater flow, such as faults, have been identified in the groundwater basin. Water-level declines owing to groundwater development have eliminated the natural sources of discharge, and pumping for agricultural and urban uses have become the primary source of discharge from the groundwater system. Infiltration of return flow from agricultural irrigation has become an important source of recharge to the aquifer system.</p>\n<p>&nbsp;</p>\n<p>The groundwater-flow model of the basin was discretized horizontally into a grid of 130 rows and 118 columns of square cells 1 kilometer (0.621 mile) on a side, and vertically into four layers representing the upper (two layers), middle (one layer), and lower (one layer) aquifers. Faults that were thought to act as horizontal-flow barriers were simulated in the model. The model was calibrated to simulate steady-state conditions, represented by 1915 water levels and transient-state conditions during 1915&ndash;95, by using water-level and subsidence data. Initial estimates of the aquifer-system properties and stresses were obtained from a previously published numerical model of the Antelope Valley groundwater basin; estimates also were obtained from recently collected hydrologic data and from results of simulations of groundwater-flow and land-subsidence models of the Edwards Air Force Base area. Some of these initial estimates were modified during model calibration. Groundwater pumpage for agriculture was estimated on the basis of irrigated crop acreage and crop consumptive-use data. Pumpage for public supply, which is metered, was compiled and entered into a database used for this study. Estimated annual agricultural pumpage peaked at 395,000 acre-feet (acre-ft) in 1951 and then declined because of declining agricultural production. Recharge from irrigation return flows was assumed to be 30 percent of agricultural pumpage; delays associated with return flow moving through the unsaturated zone were also simulated. The annual quantity of mountain-front recharge initially was based on estimates from previous studies. The model was calibrated using the PEST software suite; prior information from the area was incorporated through the use of Tikhonov regularization. During model calibration, the estimated mountain-front recharge was reduced from the previous estimate of 30,300 acre-ft/yr to 29,150 acre-ft/yr.</p>\n<p>&nbsp;</p>\n<p>Results of the simulations using the calibrated model indicate that simulated groundwater pumpage exceeded recharge in most years, resulting in an estimated cumulative depletion in groundwater storage of 8,700,000 acre-ft during the transient-simulation period (1915&ndash;2005). About 15,000,000 acre-ft of cumulative groundwater pumpage was simulated during the transient-simulation period (1915&ndash;2005), reaching a maximum rate of about 400,000 acre-ft/yr in 1951. Groundwater pumpage resulted in simulated hydraulic heads declining by more than 150 feet (ft) compared to 1915 conditions in agricultural areas. The decline in hydraulic head in the groundwater basin is the result of this depletion of groundwater storage. In turn, the simulated decline in hydraulic head in the groundwater basin has resulted in the decrease in natural discharge from the basin and has caused compaction of aquitards, resulting in land subsidence. The areal distribution of total simulated land subsidence for 2005, after about 90 years of groundwater development, indicates that land subsidence occurred throughout almost the entire Lancaster subbasin, with a maximum of about 9.4 ft in the central and eastern parts of the subbasin.</p>\n<p>&nbsp;</p>\n<p>An important objective of this study was to systematically address the uncertainty in estimates of natural recharge and related aquifer parameters by using the groundwater-flow and land-subsidence model with observational data and expert knowledge. After the model was calibrated to the observations and a reasonable parameter set obtained, the parameter null space&mdash;parameter values that do not appreciably affect the model calibration but may have importance for prediction&mdash;was identified. The effect of parameter uncertainty on the estimation of mountain-front recharge was addressed using the Null-Space Monte Carlo method. The Pareto trade-off method of visualizing uncertainty was also used to portray the reasonableness of larger natural-recharge rates. Results indicate that the total mountain-front recharge likely ranges between 28,000 and 44,000 acre-ft/yr, which is appreciably less than published estimates of 60,000 acre-ft/yr. Additionally, expected errors associated with agricultural pumpage estimates used in this study were found to have relatively little effect on the estimates of mountain-front recharge, reflecting the difficulty in increasing recharge through manipulation of other components of the water budget.</p>\n<p>&nbsp;</p>\n<p>The calibrated model was used to simulate the response of the aquifer to potential future pumping scenarios: (1) no change in the distribution of pumpage, or status quo; (2) redistribution of pumpage; and (3) artificial recharge. All three of these scenarios specify a total pumpage throughout the Antelope Valley of 110,000 acre-ft/yr according to the safe yield value ruled by the Los Angeles County Superior Court of California. This reduction in groundwater pumpage is assumed uniform throughout the basin, based on a 10-percent reduction of the total pumpage in 2005 to achieve the 110,000 acre-ft/yr level. The calibrated Antelope Valley groundwater-flow and land-subsidence model was used to simulate the hydrologic effects of the three groundwater-management scenarios during a 50-year period by using the reduced, temporally constant, pumpage distribution.</p>\n<p>&nbsp;</p>\n<p>Results from the first scenario indicated that the total drawdown observed since predevelopment would continue, with values exceeding 325 ft near Palmdale; consequently, land subsidence would also continue, with additional subsidence (since 2005) exceeding 3 ft in the central part of the Lancaster subbasin. The second scenario evaluated redistributing pumpage from areas in the Lancaster subbasin where simulated hydraulic-head declines were the greatest to areas where declines were smallest. Neither a formal optimization algorithm nor water-rights allocations were considered when redistributing the pumpage. Results indicated that hydraulic heads near Palmdale, where the pumpage was reduced, would recover by about 200 ft compared to 2005 conditions, with only 30 ft of additional drawdown in the northwestern part of the Lancaster subbasin, where the pumpage was increased. The magnitude of the simulated additional land subsidence decreased slightly compared to the first, status quo, scenario but land subsidence continued to be simulated throughout most of the northern part of the Lancaster subbasin. The third scenario consisted of two artificial-recharge simulations along the Upper Amargosa Creek channel and at a site located north of Antelope Buttes. Results indicate that applying artificial recharge at these sites would yield continued drawdowns and associated land subsidence. However, the magnitudes of drawdown and subsidence would be smaller than those simulated in the status quo scenario, indicating that artificial-recharge operations in the Antelope Valley could be expected to reduce the magnitude and extent of continued water-level declines and associated land subsidence.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145166","collaboration":"Prepared in cooperation with the Los Angeles County Department of Public Works, Antelope Valley-East Kern Water Agency, Palmdale Water District, and Edwards Air Force Base","usgsCitation":"Siade, A.J., Nishikawa, T., Rewis, D.L., Martin, P., and Phillips, S.P., 2014, Groundwater-flow and land-subsidence model of Antelope Valley, California: U.S. Geological Survey Scientific Investigations Report 2014-5166, Report: xiv, 138 p.; 5 Appendix Tables, https://doi.org/10.3133/sir20145166.","productDescription":"Report: xiv, 138 p.; 5 Appendix Tables","numberOfPages":"154","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-023623","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":295810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145166.jpg"},{"id":295798,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5166/pdf/sir2014-5166.pdf","size":"13.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295799,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_2_table_1.xlsx","text":"Appendix 2 Table 1","size":"1.5 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295800,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_3_table_1_and_2.xlsx","text":"Appendix 3 Tables 1 and 2","size":"259 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295801,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_4_table_1.xlsx","text":"Appendix 4 Table 1","size":"222 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295802,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendix_7_table_1.xlsx","text":"Appendix 7 Table 1","size":"238 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295803,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5166/downloads/sir2014-5166_appendixtables.xlsx","text":"Appendix Tables","size":"1.3 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":295777,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5166/"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5454968ee4b0dc7793747c72","contributors":{"authors":[{"text":"Siade, Adam J. asiade@usgs.gov","contributorId":1533,"corporation":false,"usgs":true,"family":"Siade","given":"Adam","email":"asiade@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nishikawa, Tracy 0000-0002-7348-3838 tnish@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-3838","contributorId":1515,"corporation":false,"usgs":true,"family":"Nishikawa","given":"Tracy","email":"tnish@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rewis, Diane L. dlrewis@usgs.gov","contributorId":1511,"corporation":false,"usgs":true,"family":"Rewis","given":"Diane","email":"dlrewis@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522822,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phillips, Steven P. 0000-0002-5107-868X sphillip@usgs.gov","orcid":"https://orcid.org/0000-0002-5107-868X","contributorId":1506,"corporation":false,"usgs":true,"family":"Phillips","given":"Steven","email":"sphillip@usgs.gov","middleInitial":"P.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":522879,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70128580,"text":"ds842 - 2014 - Database for the geologic map of upper Eocene to Holocene volcanic and related rocks in the Cascade Range, Washington","interactions":[],"lastModifiedDate":"2019-02-25T13:39:41","indexId":"ds842","displayToPublicDate":"2014-10-31T12:00:00","publicationYear":"2014","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":"842","title":"Database for the geologic map of upper Eocene to Holocene volcanic and related rocks in the Cascade Range, Washington","docAbstract":"<p>This geospatial database for a geologic map of the Cascades Range in Washington state is one of a series of maps that shows Cascade Range geology by fitting published and unpublished mapping into a province-wide scheme of lithostratigraphic units. Geologic maps of the Eocene to Holocene Cascade Range in California and Oregon complete the series, providing a comprehensive geologic map of the entire Cascade Range that incorporates modern field studies and that has a unified and internally consistent explanantion. The complete series will be useful for regional studies of volcanic hazards, volcanology, and tectonics.</p>\n<p>&nbsp;</p>\n<p>Originally a project supported by the Geothermal Research Program of the U.S. Geological Survey, the maps emphasize Quaternary volcanic rocks, because large igneous-related hydrothermal systems that have high temperatures are associated with Quaternary volcanic fields. Rocks older than a few million years are also included on the maps as they help to unravel geologic puzzles of the present-day Cascade Range. The deeply eroded older volcanoes found in the Western Cascades physiographic subprovince are analogues of today's snow-covered shield volcanoes and stratovolcanoes. The fossil hydrothermal systems of the Eocene to Pliocene vents now exposed provide clues to processes active today beneath the Pleistocene and Holocene volcanic peaks along the present-day crest of the Cascade Range. Study of these older rocks can aid in developing models of geothermal systems. These rocks also give insight into the origins of volcanic-hosted mineral deposits and even to future volcanic hazards.</p>\n<p>&nbsp;</p>\n<p>This digital database contains information used to produce the geologic map published as Sheet 1 in U.S. Geological Survey Miscellaneous Investigations Series Map I-2005. (Sheet 2 of Map I-2005 shows sources of geologic data used in the compilation and is available separately). Sheet 1 of Map I-2005 shows the distribution and relations of volcanic and related rock units in the Cascade Range of Washington at a scale of 1:500,000. This digital release is produced from stable materials originally compiled at 1:250,000 scale that were used to publish Sheet 1. The database therefore contains more detailed geologic information than is portrayed on Sheet 1. This is most noticeable in the database as expanded polygons of surficial units and the presence of additional strands of concealed faults. No stable compilation materials exist for Sheet 1 at 1:500,000 scale. The main component of this digital release is a spatial database prepared using geographic information systems (GIS) applications. This release also contains links to files to view or print the map sheet, main report text, and accompanying mapping reference sheet from Map I-2005. For more information on volcanoes in the Cascade Range in Washington, Oregon, or California, please refer to the U.S. Geological Survey Volcano Hazards Program website.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds842","usgsCitation":"Barron, A.D., Ramsey, D.W., and Smith, J.G., 2014, Database for the geologic map of upper Eocene to Holocene volcanic and related rocks in the Cascade Range, Washington: U.S. Geological Survey Data Series 842, Report: HTML Document; Readme; Metadata; Database, https://doi.org/10.3133/ds842.","productDescription":"Report: HTML Document; Readme; Metadata; Database","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-048871","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":295795,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds842.JPG"},{"id":295785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0842/downloads/ds842_index.html","linkFileType":{"id":5,"text":"html"}},{"id":295786,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/0842/downloads/ds842_README.txt","size":"2 kB","linkFileType":{"id":2,"text":"txt"}},{"id":295775,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0842/"},{"id":295787,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0842/downloads/ds842_metadata-geo.txt","size":"27 kB","linkFileType":{"id":2,"text":"txt"}},{"id":295788,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/ds/0842/downloads/DS-842/ds842.zip","size":"18.2 MB"}],"country":"United States","state":"Washington","otherGeospatial":"Cascade Range","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5454968de4b0dc7793747c62","contributors":{"authors":[{"text":"Barron, Andrew D.","contributorId":28628,"corporation":false,"usgs":true,"family":"Barron","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":522818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramsey, David W. 0000-0003-1698-2523 dramsey@usgs.gov","orcid":"https://orcid.org/0000-0003-1698-2523","contributorId":3819,"corporation":false,"usgs":true,"family":"Ramsey","given":"David","email":"dramsey@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":522817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, James G.","contributorId":127003,"corporation":false,"usgs":false,"family":"Smith","given":"James","email":"","middleInitial":"G.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address:  TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":522819,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70138823,"text":"70138823 - 2014 - Using vertical Fourier transforms to invert potential-field data to magnetization or density models in the presence of topography","interactions":[],"lastModifiedDate":"2018-05-03T16:30:57","indexId":"70138823","displayToPublicDate":"2014-10-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Using vertical Fourier transforms to invert potential-field data to magnetization or density models in the presence of topography","docAbstract":"<p><span>A physical property inversion approach based on the use of 3D (or 2D) Fourier transforms to calculate the potential-field within a 3D (or 2D) volume from a known physical property distribution within the volume is described. Topographic surfaces and observations at arbitrary locations are easily accommodated. The limitations of the approach and applications to real data are considered.</span><span></span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Society of Exploration Geophysicists, 2014 Technical Program Expanded Abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2014 SEG Annual Meeting","conferenceDate":"October 26-31, 2014","conferenceLocation":"Denver, CO","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/segam2014-0226.1","usgsCitation":"Phillips, J., 2014, Using vertical Fourier transforms to invert potential-field data to magnetization or density models in the presence of topography, <i>in</i> Society of Exploration Geophysicists, 2014 Technical Program Expanded Abstracts, Denver, CO, October 26-31, 2014, p. 1339-1343, https://doi.org/10.1190/segam2014-0226.1.","productDescription":"5 p.","startPage":"1339","endPage":"1343","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055541","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":310631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-05","publicationStatus":"PW","scienceBaseUri":"562f4ebce4b093cee780a2b6","contributors":{"authors":[{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":538972,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70141779,"text":"70141779 - 2014 - Influence of fuels, weather and the built environment on the exposure of property to wildfire","interactions":[],"lastModifiedDate":"2015-02-20T16:17:06","indexId":"70141779","displayToPublicDate":"2014-10-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Influence of fuels, weather and the built environment on the exposure of property to wildfire","docAbstract":"<p><span>Wildfires can pose a significant risk to people and property. Billions of dollars are spent investing in fire management actions in an attempt to reduce the risk of loss. One of the key areas where money is spent is through fuel treatment &ndash; either fuel reduction (prescribed fire) or fuel removal (fuel breaks). Individual treatments can influence fire size and the maximum distance travelled from the ignition and presumably risk, but few studies have examined the landscape level effectiveness of these treatments. Here we use a Bayesian Network model to examine the relative influence of the built and natural environment, weather, fuel and fuel treatments in determining the risk posed from wildfire to the wildland-urban interface. Fire size and distance travelled was influenced most strongly by weather, with exposure to fires most sensitive to changes in the built environment and fire parameters. Natural environment variables and fuel load all had minor influences on fire size, distance travelled and exposure of assets. These results suggest that management of fuels provided minimal reductions in risk to assets and adequate planning of the changes in the built environment to cope with the expansion of human populations is going to be vital for managing risk from fire under future climates.</span></p>","language":"English","publisher":"PLOS One","doi":"10.1371/journal.pone.0111414","usgsCitation":"Penman, T.D., Collins, L.S., Syphard, A.D., Keeley, J.E., and Bradstock, R.A., 2014, Influence of fuels, weather and the built environment on the exposure of property to wildfire: PLoS ONE, v. 9, no. 10, e111414; 9 p., https://doi.org/10.1371/journal.pone.0111414.","productDescription":"e111414; 9 p.","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056457","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":472678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0111414","text":"Publisher Index Page"},{"id":298077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-31","publicationStatus":"PW","scienceBaseUri":"54e868bee4b02d776a67c5c9","contributors":{"authors":[{"text":"Penman, Trent D.","contributorId":139403,"corporation":false,"usgs":false,"family":"Penman","given":"Trent","email":"","middleInitial":"D.","affiliations":[{"id":12769,"text":"Centre for Environmental Rist Management of Bushfires, U of Wollongong, Australia","active":true,"usgs":false}],"preferred":false,"id":541089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Luke S.","contributorId":76108,"corporation":false,"usgs":false,"family":"Collins","given":"Luke","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":541090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":541091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradstock, Ross A.","contributorId":42826,"corporation":false,"usgs":false,"family":"Bradstock","given":"Ross","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":541093,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70148350,"text":"70148350 - 2014 - Optimally managing water resources in large river basins for an uncertain future","interactions":[],"lastModifiedDate":"2015-05-29T11:16:24","indexId":"70148350","displayToPublicDate":"2014-10-31T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Optimally managing water resources in large river basins for an uncertain future","docAbstract":"<p>Managers of large river basins face conflicting needs for water resources such as wildlife habitat, water supply, wastewater assimilative capacity, flood control, hydroelectricity, and recreation. The Savannah River Basin for example, has experienced three major droughts since 2000 that resulted in record low water levels in its reservoirs, impacting local economies for years. The Savannah River Basin&rsquo;s coastal area contains municipal water intakes and the ecologically sensitive freshwater tidal marshes of the Savannah National Wildlife Refuge. The Port of Savannah is the fourth busiest in the United States, and modifications to the harbor have caused saltwater to migrate upstream, reducing the freshwater marsh&rsquo;s acreage more than 50 percent since the 1970s. There is a planned deepening of the harbor that includes flow-alteration features to minimize further migration of salinity. The effectiveness of the flow-alteration features will only be known after they are constructed.</p>\n<p>One of the challenges of basin management is the optimization of water use through ongoing regional economic development, droughts, and climate change. This paper describes a model of the Savannah River Basin designed to continuously optimize regulated flow to meet prioritized objectives set by resource managers and stakeholders. The model was developed from historical data by using machine learning, making it more accurate and adaptable to changing conditions than traditional models. The model is coupled to an optimization routine that computes the daily flow needed to most efficiently meet the water-resource management objectives. The model and optimization routine are packaged in a decision support system that makes it easy for managers and stakeholders to use. Simulation results show that flow can be regulated to substantially reduce salinity intrusions in the Savannah National Wildlife Refuge while conserving more water in the reservoirs. A method for using the model to assess the effectiveness of the flow-alteration features after the deepening also is demonstrated.</p>","largerWorkTitle":"Proceedings of the 2014 South Carolina Water Resources Conference","conferenceTitle":"2014 South Carolina Water Resources Conference","conferenceDate":"October 15-16, 2014","conferenceLocation":"Columbia, SC","language":"English","usgsCitation":"Roehl, E.A., and Conrads, P., 2014, Optimally managing water resources in large river basins for an uncertain future, <i>in</i> Proceedings of the 2014 South Carolina Water Resources Conference, Columbia, SC, October 15-16, 2014, 6 p.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065989","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":300919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":300918,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://tigerprints.clemson.edu/scwrc/2014/2014policy/3/"}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"lower Savannah River, Savannah National Wildlife Refuge, Savannah River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.90057373046875,\n              32.0383483283312\n            ],\n            [\n              -80.9033203125,\n              32.02146689475617\n            ],\n            [\n              -81.02005004882812,\n              32.088392208449804\n            ],\n            [\n              -81.05369567871094,\n              32.07850198496867\n            ],\n            [\n              -81.07635498046875,\n              32.07850198496867\n            ],\n            [\n              -81.12579345703125,\n              32.10758782193262\n            ],\n            [\n              -81.15669250488281,\n              32.156431175120495\n            ],\n            [\n              -81.15669250488281,\n              32.22151494505975\n            ],\n            [\n              -81.18175506591797,\n              32.25491040237429\n            ],\n            [\n              -81.13849639892578,\n              32.33123819794542\n            ],\n            [\n              -81.11858367919922,\n              32.32427558887655\n            ],\n            [\n              -81.11858367919922,\n              32.28568142693891\n            ],\n            [\n              -81.14433288574219,\n              32.21919132617101\n            ],\n            [\n              -81.11686706542967,\n              32.19537080888963\n            ],\n            [\n              -81.1117172241211,\n              32.149455154523984\n            ],\n            [\n              -81.07086181640625,\n              32.09799051942507\n            ],\n            [\n              -81.00288391113281,\n              32.103225536729\n            ],\n            [\n              -80.90057373046875,\n              32.0383483283312\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55698dede4b0d9246a9f64af","contributors":{"authors":[{"text":"Roehl, Edwin A. Jr.","contributorId":108083,"corporation":false,"usgs":false,"family":"Roehl","given":"Edwin","suffix":"Jr.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":547797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","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":547796,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70131481,"text":"70131481 - 2014 - Dual-domain mass-transfer parameters from electrical hysteresis: Theory and analytical approach applied to laboratory, synthetic streambed, and groundwater experiments","interactions":[],"lastModifiedDate":"2021-04-05T11:58:18.201575","indexId":"70131481","displayToPublicDate":"2014-10-29T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Dual-domain mass-transfer parameters from electrical hysteresis: Theory and analytical approach applied to laboratory, synthetic streambed, and groundwater experiments","docAbstract":"<p><span>Models of dual‐domain mass transfer (DDMT) are used to explain anomalous aquifer transport behavior such as the slow release of contamination and solute tracer tailing. Traditional tracer experiments to characterize DDMT are performed at the flow path scale (meters), which inherently incorporates heterogeneous exchange processes; hence, estimated “effective” parameters are sensitive to experimental design (i.e., duration and injection velocity). Recently, electrical geophysical methods have been used to aid in the inference of DDMT parameters because, unlike traditional fluid sampling, electrical methods can directly sense less‐mobile solute dynamics and can target specific points along subsurface flow paths. Here we propose an analytical framework for graphical parameter inference based on a simple petrophysical model explaining the hysteretic relation between measurements of bulk and fluid conductivity arising in the presence of DDMT at the local scale. Analysis is graphical and involves visual inspection of hysteresis patterns to (1) determine the size of paired mobile and less‐mobile porosities and (2) identify the exchange rate coefficient through simple curve fitting. We demonstrate the approach using laboratory column experimental data, synthetic streambed experimental data, and field tracer‐test data. Results from the analytical approach compare favorably with results from calibration of numerical models and also independent measurements of mobile and less‐mobile porosity. We show that localized electrical hysteresis patterns resulting from diffusive exchange are independent of injection velocity, indicating that repeatable parameters can be extracted under varied experimental designs, and these parameters represent the true intrinsic properties of specific volumes of porous media of aquifers and hyporheic zones.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/2014WR015880","usgsCitation":"Briggs, M.A., Day-Lewis, F.D., Ong, J.B., Harvey, J.W., and Lane, J.W., 2014, Dual-domain mass-transfer parameters from electrical hysteresis: Theory and analytical approach applied to laboratory, synthetic streambed, and groundwater experiments: Water Resources Research, v. 50, no. 10, p. 8281-8299, https://doi.org/10.1002/2014WR015880.","productDescription":"19 p.","startPage":"8281","endPage":"8299","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059884","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472679,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr015880","text":"Publisher Index Page"},{"id":296079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-10-29","publicationStatus":"PW","scienceBaseUri":"5465d632e4b04d4b7dbd65c5","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":521236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":521237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ong, John B. jbong@usgs.gov","contributorId":5190,"corporation":false,"usgs":true,"family":"Ong","given":"John","email":"jbong@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":521238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":521239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":521240,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70176470,"text":"70176470 - 2014 - The potential for sea-level-rise-induced barrier island loss: Insights from the Chandeleur Islands, Louisiana, USA","interactions":[],"lastModifiedDate":"2016-09-16T13:49:36","indexId":"70176470","displayToPublicDate":"2014-10-28T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"The potential for sea-level-rise-induced barrier island loss: Insights from the Chandeleur Islands, Louisiana, USA","docAbstract":"<p><span>As sea level rises and hurricanes become more intense, barrier islands around the world become increasingly vulnerable to conversion from self-sustaining migrating landforms to submerging or subaqueous sand bodies. To explore the mechanism by which such state changes occur and to assess the factors leading to island disintegration, we develop a suite of numerical simulations for the Chandeleur Islands in Louisiana, U.S.A., which appear to be on the verge of this transition. Our results suggest that the Chandeleurs are likely poised to change state, leading to their demise, within decades depending on future storm history. Contributing factors include high rates of relative sea level rise, limited sediment supply, muddy substrate, current island position relative to former Mississippi River distributary channels, and the effects of changes in island morphology on sediment transport pathways. Although deltaic barrier islands are most sensitive to disintegration because of their muddy substrate, the importance of relative sea level rise rate in determining the timing of threshold crossing suggests that the conceptual models for deltaic barrier island formation and disintegration may apply more broadly in the future.</span></p>","language":"English","publisher":"Elsevier Scientific Pub. Co.","publisherLocation":"Amsterdam","doi":"10.1016/j.margeo.2014.05.022","usgsCitation":"Moore, L.J., Patsch, K., List, J., and Williams, S.J., 2014, The potential for sea-level-rise-induced barrier island loss: Insights from the Chandeleur Islands, Louisiana, USA: Marine Geology, v. 355, p. 244-259, https://doi.org/10.1016/j.margeo.2014.05.022.","startPage":"244","endPage":"259","numberOfPages":"16","ipdsId":"IP-033509","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana, Mississippi","otherGeospatial":"North Chandeleur Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89,\n              29.866667\n            ],\n            [\n              -89,\n              29.966667\n            ],\n            [\n              -88.35,\n              29.966667\n            ],\n            [\n              -88.35,\n              29.866667\n            ],\n            [\n              -89,\n              29.866667\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"355","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7efd6e4b0bc0bec09f39e","contributors":{"authors":[{"text":"Moore, Laura J.","contributorId":39452,"corporation":false,"usgs":true,"family":"Moore","given":"Laura","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":648870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patsch, Kiki","contributorId":174649,"corporation":false,"usgs":false,"family":"Patsch","given":"Kiki","email":"","affiliations":[{"id":13014,"text":"Department of Environmental Sciences, University of Virginia","active":true,"usgs":false}],"preferred":false,"id":648871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"List, Jeffrey H. jlist@usgs.gov","contributorId":127596,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey H.","email":"jlist@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, S. Jeffress 0000-0002-1326-7420 jwilliams@usgs.gov","orcid":"https://orcid.org/0000-0002-1326-7420","contributorId":2063,"corporation":false,"usgs":true,"family":"Williams","given":"S.","email":"jwilliams@usgs.gov","middleInitial":"Jeffress","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70123235,"text":"ofr20141185 - 2014 - Water-quality modeling of Klamath Straits Drain recirculation, a Klamath River wetland, and 2011 conditions for the Link River to Keno Dam reach of the Klamath River, Oregon","interactions":[],"lastModifiedDate":"2014-10-24T15:40:24","indexId":"ofr20141185","displayToPublicDate":"2014-10-24T15:34:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1185","title":"Water-quality modeling of Klamath Straits Drain recirculation, a Klamath River wetland, and 2011 conditions for the Link River to Keno Dam reach of the Klamath River, Oregon","docAbstract":"<p>The upper Klamath River and adjacent Lost River are interconnected basins in south-central Oregon and northern California. Both basins have impaired water quality with Total Maximum Daily Loads (TMDLs) in progress or approved. In cooperation with the Bureau of Reclamation, the U.S. Geological Survey (USGS) and Watercourse Engineering, Inc., have conducted modeling and research to inform management of these basins for multiple purposes, including agriculture, endangered species protection, wildlife refuges, and adjacent and downstream water users. A water-quality and hydrodynamic model (CE-QUAL-W2) of the Link River to Keno Dam reach of the Klamath River for 2006–09 is one of the tools used in this work. The model can simulate stage, flow, water velocity, ice cover, water temperature, specific conductance, suspended sediment, nutrients, organic matter in bed sediment and the water column, three algal groups, three macrophyte groups, dissolved oxygen, and pH.</p>\n<br>\n<p>This report documents two model scenarios and a test of the existing model applied to year 2011, which had exceptional water quality. The first scenario examined the water-quality effects of recirculating Klamath Straits Drain flows into the Ady Canal, to conserve water and to decrease flows from the Klamath Straits Drain to the Klamath River. The second scenario explicitly incorporated a 2.73×10<sup>6</sup> m<sup>2</sup> (675 acre) off-channel connected wetland into the CE-QUAL-W2 framework, with the wetland operating from May 1 through October 31. The wetland represented a managed treatment feature to decrease organic matter loads and process nutrients. Finally, the summer of 2011 showed substantially higher dissolved-oxygen concentrations in the Link-Keno reach than in other recent years, so the Link-Keno model (originally developed for 2006–09) was run with 2011 data as a test of model parameters and rates and to develop insights regarding the reasons for the improved water-quality conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141185","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A., Sogutlugil, I., Deas, M.L., and Rounds, S.A., 2014, Water-quality modeling of Klamath Straits Drain recirculation, a Klamath River wetland, and 2011 conditions for the Link River to Keno Dam reach of the Klamath River, Oregon: U.S. Geological Survey Open-File Report 2014-1185, viii, 75 p., https://doi.org/10.3133/ofr20141185.","productDescription":"viii, 75 p.","numberOfPages":"88","onlineOnly":"Y","ipdsId":"IP-056254","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":295752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141185.jpg"},{"id":295750,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1185/"},{"id":295751,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1185/pdf/ofr2014-1185.pdf"}],"country":"United States","state":"Oregon","otherGeospatial":"Klamath River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"544b5c07e4b03653c63fb1be","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":79821,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett B.","email":"annett@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":499955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sogutlugil, I. Ertugrul","contributorId":23867,"corporation":false,"usgs":true,"family":"Sogutlugil","given":"I. Ertugrul","affiliations":[],"preferred":false,"id":499953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deas, Michael L.","contributorId":61359,"corporation":false,"usgs":true,"family":"Deas","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":499954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":499952,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70127554,"text":"ds887 - 2014 - EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013","interactions":[],"lastModifiedDate":"2014-10-24T10:55:21","indexId":"ds887","displayToPublicDate":"2014-10-24T10:41:00","publicationYear":"2014","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":"887","title":"EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013","docAbstract":"<p>These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.</p>\n<br>\n<p>This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired post-Hurricane Sandy on November 1, 5, 16, 20, and 30, 2012; December 5, 6, and 21, 2012; and January 10, 2013. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.</p>\n<br>\n<p>Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the \"bare earth\" under vegetation from a point cloud of last return elevations.</p>\n<br>\n<p>For more information about similar projects, please visit the <a href=\"http://coastal.er.usgs.gov/lsrm/\" target=\"_blank\"> Lidar for Science and Resource Management Web site</a>.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds887","usgsCitation":"Wright, C., Troche, R.J., Kranenburg, C., Klipp, E.S., Fredericks, X., and Nagle, D.B., 2014, EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013: U.S. Geological Survey Data Series 887, HTML Document, https://doi.org/10.3133/ds887.","productDescription":"HTML Document","onlineOnly":"Y","temporalStart":"2012-11-01","temporalEnd":"2013-01-10","ipdsId":"IP-055647","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds887.jpg"},{"id":295713,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0887/home.html"},{"id":295715,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0887/"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"544b5c05e4b03653c63fb1b8","contributors":{"authors":[{"text":"Wright, C. Wayne","contributorId":52097,"corporation":false,"usgs":true,"family":"Wright","given":"C. Wayne","affiliations":[],"preferred":false,"id":502398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":502396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kranenburg, Christine J.","contributorId":7211,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","affiliations":[],"preferred":false,"id":502397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":502394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan","contributorId":73520,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","affiliations":[],"preferred":false,"id":502399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":502395,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70168485,"text":"70168485 - 2014 - Latitudinal and photic effects on diel foraging and predation risk in freshwater pelagic ecosystems","interactions":[],"lastModifiedDate":"2016-02-16T13:11:58","indexId":"70168485","displayToPublicDate":"2014-10-24T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Latitudinal and photic effects on diel foraging and predation risk in freshwater pelagic ecosystems","docAbstract":"<div class=\"page\" title=\"Page 1\">\n<div class=\"layoutArea\">\n<p class=\"column\"><span>1. </span><span>Clark &amp; Levy </span><span>(</span><span>American Naturalist</span><span>, </span><span>131</span><span>, 1988, 271&ndash;290) described an antipredation window for smaller planktivorous fish during crepuscular periods when light permits feeding on zooplankton, but limits visual detection by piscivores. Yet, how the window is influenced by the interaction between light regime, turbidity and cloud cover over a broad latitudinal gradi- ent remains unexplored.</span></p>\n<div class=\"column\">\n<p><span>2. </span><span>We evaluated how latitudinal and seasonal shifts in diel light regimes alter the foraging- risk environment for visually feeding planktivores and piscivores across a natural range of turbidities and cloud covers. Pairing a model of aquatic visual feeding with a model of sun and moon illuminance, we estimated foraging rates of an idealized planktivore and piscivore over depth and time across factorial combinations of latitude (0</span><span>&ndash;</span><span>70</span><span>&deg;</span><span>), turbidity (0</span><span>\u0010</span><span>1</span><span>&ndash;</span><span>5 NTU) and cloud cover (clear to overcast skies) during the summer solstice and autumnal equinox. We evaluated the foraging-risk environment based on changes in the magnitude, duration and peak timing of the antipredation window. </span></p>\n<p><span>3. </span><span>The model scenarios generated up to 10-fold shifts in magnitude, 24-fold shifts in duration and 5</span><span>\u0010</span><span>5-h shifts in timing of the peak antipredation window. The size of the window increased with latitude. This pattern was strongest during the solstice. In clear water at low turbidity (0</span><span>\u0010</span><span>1</span><span>&ndash;</span><span>0</span><span>\u0010</span><span>5 NTU), peaks in the magnitude and duration of the window formed at 57</span><span>&ndash;</span><span>60</span><span>&deg; </span><span>latitude, before falling to near zero as surface waters became saturated with light under a midnight sun and clear skies at latitudes near 70</span><span>&deg;</span><span>. Overcast dampened the midnight sun enough to allow larger windows to form in clear water at high latitudes. Conversely, at turbidities </span><span>&ge;</span><span>2 NTU, greater reductions in the visual range of piscivores than planktivores created a window for long periods at high latitudes. Latitudinal dependencies were essentially lost during the equinox, indicating a progressive compression of the window from early summer into autumn. </span></p>\n<p><span>4. </span><span>Model results show that diel-seasonal foraging and predation risk in freshwater pelagic ecosystems changes considerably with latitude, turbidity and cloud cover. These changes alter the structure of pelagic predator</span><span>&ndash;</span><span>prey interactions, and in turn, the broader role of pelagic consumers in habitat coupling in lakes.&nbsp;</span></p>\n</div>\n</div>\n</div>","language":"English","publisher":"University Press","publisherLocation":"Cambridge, UK","doi":"10.1111/1365-2656.12295","usgsCitation":"Hansen, A., and Beauchamp, D.A., 2014, Latitudinal and photic effects on diel foraging and predation risk in freshwater pelagic ecosystems: Journal of Animal Ecology, v. 84, no. 2, p. 532-544, https://doi.org/10.1111/1365-2656.12295.","productDescription":"13 p.","startPage":"532","endPage":"544","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055038","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":318075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-24","publicationStatus":"PW","scienceBaseUri":"56c4564ae4b0946c65218563","contributors":{"authors":[{"text":"Hansen, Adam G.","contributorId":103947,"corporation":false,"usgs":true,"family":"Hansen","given":"Adam G.","affiliations":[],"preferred":false,"id":620504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, David A. 0000-0002-3592-8381 fadave@usgs.gov","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":4205,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","email":"fadave@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":620503,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70129433,"text":"70129433 - 2014 - Adaptive management and the value of information: learning via intervention in epidemiology","interactions":[],"lastModifiedDate":"2014-10-23T09:01:56","indexId":"70129433","displayToPublicDate":"2014-10-22T14:05:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"Adaptive management and the value of information: learning via intervention in epidemiology","docAbstract":"Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pbio.1001970","usgsCitation":"Shea, K., Tildesley, M., Runge, M.C., Fonnesbeck, C.J., and Ferrari, M.J., 2014, Adaptive management and the value of information: learning via intervention in epidemiology: PLoS Biology, v. 12, no. 10, e1001970; 11 p., https://doi.org/10.1371/journal.pbio.1001970.","productDescription":"e1001970; 11 p.","numberOfPages":"11","ipdsId":"IP-057442","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pbio.1001970","text":"Publisher Index Page"},{"id":295611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295610,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pbio.1001970"}],"volume":"12","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-10-21","publicationStatus":"PW","scienceBaseUri":"5448b909e4b0f888a81b879b","contributors":{"authors":[{"text":"Shea, Katriona","contributorId":8783,"corporation":false,"usgs":true,"family":"Shea","given":"Katriona","affiliations":[],"preferred":false,"id":503713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tildesley, Michael J.","contributorId":100772,"corporation":false,"usgs":true,"family":"Tildesley","given":"Michael J.","affiliations":[],"preferred":false,"id":503715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":503712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fonnesbeck, Christopher J.","contributorId":83047,"corporation":false,"usgs":true,"family":"Fonnesbeck","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":503714,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferrari, Matthew J.","contributorId":103205,"corporation":false,"usgs":true,"family":"Ferrari","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":503716,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259726,"text":"70259726 - 2014 - InSAR imaging of aleutian volcanoes: Monitoring a volcanic arc from space","interactions":[],"lastModifiedDate":"2024-10-22T10:59:57.832685","indexId":"70259726","displayToPublicDate":"2014-10-22T05:54:29","publicationYear":"2014","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"displayTitle":"InSAR Imaging of Aleutian Volcanoes: Monitoring a Volcanic Arc from Space","title":"InSAR imaging of aleutian volcanoes: Monitoring a volcanic arc from space","docAbstract":"<p>Interferometric synthetic aperture radar (InSAR) is a relatively new remote sensing tool that is capable of measuring ground-surface deformation with centimeter-to-subcentimeter precision at a spatial resolution of tens of meters over an area of hundreds to thousands of square kilometers. With its global coverage and all-weather imaging capability, InSAR has become an increasingly important technique for studying volcanoes in remote regions such as the Aleutian Islands. The spatial distribution of surface deformation data derived from InSAR images enables the construction of detailed mechanical models to enhance the study of magmatic processes.</p>","language":"English","publisher":"Springer","doi":"https://doi.org/10.1007/978-3-642-00348-6","usgsCitation":"Lu, Z., and Dzurisin, D., 2014, InSAR imaging of aleutian volcanoes: Monitoring a volcanic arc from space, xxix, 390 p., https://doi.org/https://doi.org/10.1007/978-3-642-00348-6.","productDescription":"xxix, 390 p.","ipdsId":"IP-043967","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":463069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":916468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":916469,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70074697,"text":"70074697 - 2014 - An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: Combining index and demographic data","interactions":[],"lastModifiedDate":"2020-12-28T12:43:57.68989","indexId":"70074697","displayToPublicDate":"2014-10-21T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: Combining index and demographic data","docAbstract":"<p><span>Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large‐scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short‐term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (</span><i>λ</i><span>) for Gunnison sage‐grouse (</span><i>Centrocercus minimus</i><span>). The long‐term population index data available for Gunnison sage‐grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage‐grouse to be variable and slightly declining over the past 16&nbsp;years.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1290","usgsCitation":"Davis, A.J., Hooten, M., Phillips, M.L., and Doherty, P.F., 2014, An integrated modeling approach to estimating Gunnison Sage-Grouse population dynamics: Combining index and demographic data: Ecology and Evolution, v. 4, no. 22, p. 4247-2457, https://doi.org/10.1002/ece3.1290.","productDescription":"11 p.","startPage":"4247","endPage":"2457","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045802","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1290","text":"Publisher Index Page"},{"id":311317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.68701171875,\n              37.00255267215955\n            ],\n            [\n              -111.68701171875,\n              39.487084981687495\n            ],\n            [\n              -106.9189453125,\n              39.487084981687495\n            ],\n            [\n              -106.9189453125,\n              37.00255267215955\n            ],\n            [\n              -111.68701171875,\n              37.00255267215955\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"22","noUsgsAuthors":false,"publicationDate":"2014-10-22","publicationStatus":"PW","scienceBaseUri":"564717bde4b0e2669b3130ff","contributors":{"authors":[{"text":"Davis, Amy J.","contributorId":149854,"corporation":false,"usgs":false,"family":"Davis","given":"Amy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":579809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin B. 0000-0002-1614-723X","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":119998,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin B.","affiliations":[],"preferred":false,"id":518511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Michael L.","contributorId":149855,"corporation":false,"usgs":false,"family":"Phillips","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":579810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doherty, Paul F. Jr.","contributorId":37636,"corporation":false,"usgs":false,"family":"Doherty","given":"Paul","suffix":"Jr.","email":"","middleInitial":"F.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":579811,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70133144,"text":"70133144 - 2014 - A multi-scale assessment of animal aggregation patterns to understand increasing pathogen seroprevalence","interactions":[],"lastModifiedDate":"2017-04-03T12:42:56","indexId":"70133144","displayToPublicDate":"2014-10-21T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A multi-scale assessment of animal aggregation patterns to understand increasing pathogen seroprevalence","docAbstract":"<p><span>Understanding how animal density is related to pathogen transmission is important to develop effective disease control strategies, but requires measuring density at a scale relevant to transmission. However, this is not straightforward or well-studied among large mammals with group sizes that range several orders of magnitude or aggregation patterns that vary across space and time. To address this issue, we examined spatial variation in elk (</span><i>Cervus canadensis</i><span>) aggregation patterns and brucellosis across 10 regions in the Greater Yellowstone Area where previous studies suggest the disease may be increasing. We hypothesized that rates of increasing brucellosis would be better related to the frequency of large groups than mean group size or population density, but we examined whether other measures of density would also explain rising seroprevalence. To do this, we measured wintering elk density and group size across multiple spatial and temporal scales from monthly aerial surveys. We used Bayesian hierarchical models and 20 years of serologic data to estimate rates of increase in brucellosis within the 10 regions, and to examine the linear relationships between these estimated rates of increase and multiple measures of aggregation. Brucellosis seroprevalence increased over time in eight regions (one region showed an estimated increase from 0.015 in 1991 to 0.26 in 2011), and these rates of increase were positively related to all measures of aggregation. The relationships were weaker when the analysis was restricted to areas where brucellosis was present for at least two years, potentially because aggregation was related to disease-establishment within a population. Our findings suggest that (1) group size did not explain brucellosis increases any better than population density and (2) some elk populations may have high densities with small groups or lower densities with large groups, but brucellosis is likely to increase in either scenario. In this case, any one control method such as reducing population density or group size may not be sufficient to reduce transmission. This study highlights the importance of examining the density-transmission relationship at multiple scales and across populations before broadly applying disease control strategies.</span></p>","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/ES14-00181.1","usgsCitation":"Brennan, A.K., Cross, P.C., Higgs, M.D., Edwards, W.H., Scurlock, B.M., and Creel, S., 2014, A multi-scale assessment of animal aggregation patterns to understand increasing pathogen seroprevalence: Ecosphere, v. 5, no. 10, art138: 25 p., https://doi.org/10.1890/ES14-00181.1.","productDescription":"art138: 25 p.","ipdsId":"IP-053350","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":472686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es14-00181.1","text":"Publisher Index Page"},{"id":339041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -109.896240234375,\n              41.393294288784865\n            ],\n            [\n              -106.50146484374999,\n              41.393294288784865\n            ],\n            [\n              -106.50146484374999,\n              44.98811302615805\n            ],\n            [\n              -109.896240234375,\n              44.98811302615805\n            ],\n            [\n              -109.896240234375,\n              41.393294288784865\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"5","issue":"10","noUsgsAuthors":false,"publicationDate":"2014-10-31","publicationStatus":"PW","scienceBaseUri":"58e35f80e4b09da67997ecb5","contributors":{"authors":[{"text":"Brennan, Angela K. akbrennan@usgs.gov","contributorId":4892,"corporation":false,"usgs":true,"family":"Brennan","given":"Angela","email":"akbrennan@usgs.gov","middleInitial":"K.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":524802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":524801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgs, Megan D.","contributorId":127365,"corporation":false,"usgs":false,"family":"Higgs","given":"Megan","email":"","middleInitial":"D.","affiliations":[{"id":6916,"text":"Department of Mathematical Sciences, Montana State University, Bozeman, USA","active":true,"usgs":false}],"preferred":false,"id":524803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, W. Henry","contributorId":127366,"corporation":false,"usgs":false,"family":"Edwards","given":"W.","email":"","middleInitial":"Henry","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":688074,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scurlock, Brandon M.","contributorId":93788,"corporation":false,"usgs":false,"family":"Scurlock","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":6917,"text":"Wyoming Game and Fish Department, Laramie, USA","active":true,"usgs":false}],"preferred":false,"id":524805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creel, Scott","contributorId":15089,"corporation":false,"usgs":true,"family":"Creel","given":"Scott","affiliations":[],"preferred":false,"id":524806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70141361,"text":"70141361 - 2014 - 210Pb dating","interactions":[],"lastModifiedDate":"2015-03-06T11:15:00","indexId":"70141361","displayToPublicDate":"2014-10-21T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"210Pb dating","docAbstract":"<p>Roughly fifty years ago, a small group of scientists from Belgium and the United States, trying to better constrain ice sheet accumulation rates, attempted to apply what was then know about environmental lead as a potential geochronometer. Thus Goldberg (1963) developed the first principles of the <sup>210</sup>Pb dating method, which was soon followed by a paper by Crozaz et al. (1964), who examined accumulation history of Antarctic snow using <sup>210</sup>Pb. Shortly thereafter, Koide et al. (1972, 1973) adapted this technique to unravel sediment deposition and accumulation records in deep-sea environments. Serendipitously, they chose to work in a deep basin off California, where an independent and robust age model had already been developed. Krishanswami et al. (1971) extended the use of this technique to lacustrine deposits to reconstruct depositional histories of lake sediment, and maybe more importantly, contaminant inputs and burial. Thus, the powerful tool for dating recent (up to about one century old) sediment deposits was established and soon widely adopted. Today almost all oceanographic or limnologic studies that address recent depositional reconstructions employ <sup>210</sup>Pb as one of several possible geochronometers (Andrews et al., 2009; Gale, 2009; Baskaran, 2011; Persson and Helms, 2011). This paper presents a short overview of the principles of <sup>210</sup>Pb dating and provides a few examples that illustrate the utility of this tracer in contrasting depositional systems. Potential caveats and uncertainties (Appleby et al., 1986; Binford, 1990; Binford et al., 1993; Smith, 2001; Hancock et al., 2002) inherent to the use and interpretation of <sup>210</sup>Pb-derived age-models are also introduced. Recommendations as to best practices for most reliable uses and reporting are presented in the summary.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Scientific Dating Methods","language":"English","publisher":"Springer Netherlands","doi":"10.1007/978-94-007-6326-5_236-1","usgsCitation":"Swarzenski, P.W., 2014, 210Pb dating, chap. <i>of</i> Encyclopedia of Scientific Dating Methods, 11 p., https://doi.org/10.1007/978-94-007-6326-5_236-1.","productDescription":"11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060526","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":298327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-21","publicationStatus":"PW","scienceBaseUri":"54faddb9e4b02419550db6cd","contributors":{"authors":[{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":540728,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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