Groundwater levels were offset in bedrock observation wells, measured by the U.S. Geological Survey or others, as far as 553 km from the Mw 5.8 Mineral, Virginia (USA), earthquake on 23 August 2011. Water levels dropped as much as 0.47 m in 34 wells and rose as much as 0.15 m in 12 others. In some wells, which are as much as 213 m deep, the water levels recovered from these deviations in hours to days, but in others the water-level offset may have persisted. The groundwater-level offsets occurred in locations where the earthquake was at least weakly felt, and the maximum water-level excursion increased with felt intensity, independent of epicentral distance. Coseismic static strain from the earthquake was too small and localized to have contributed significantly to the groundwater-level offsets. The relation with intensity is consistent with ground motion from seismic waves leading to the water-level offsets. Examination of the hydrographs indicates that short-period ground motion most likely affected the permeability of the bedrock aquifers monitored by the wells.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2509(07)","usgsCitation":"Roeloffs, E.A., Nelms, D.L., and Sheets, R., 2015, Widespread groundwater-level offsets caused by the Mw 5.8 Mineral, Virginia, earthquake of 23 August 2011: GSA Special Papers, v. 509, p. 117-136, https://doi.org/10.1130/2014.2509(07).","productDescription":"20 p.","startPage":"117","endPage":"136","ipdsId":"IP-050835","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342196,"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 -84,\n 34\n ],\n [\n -72,\n 34\n ],\n [\n -72,\n 43.3333\n ],\n [\n -84,\n 43.3333\n ],\n [\n -84,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"509","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910afe4b0764e6c5e8881","contributors":{"authors":[{"text":"Roeloffs, Evelyn A. 0000-0002-4761-0469 evelynr@usgs.gov","orcid":"https://orcid.org/0000-0002-4761-0469","contributorId":2680,"corporation":false,"usgs":true,"family":"Roeloffs","given":"Evelyn","email":"evelynr@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697369,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheets, Rodney A. rasheets@usgs.gov","contributorId":1848,"corporation":false,"usgs":true,"family":"Sheets","given":"Rodney A.","email":"rasheets@usgs.gov","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697370,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157348,"text":"70157348 - 2015 - A comparison of estimates of basin-scale soil-moisture evapotranspiration and estimates of riparian groundwater evapotranspiration with implications for water budgets in the Verde Valley, Central Arizona, USA","interactions":[],"lastModifiedDate":"2022-11-03T14:59:40.000811","indexId":"70157348","displayToPublicDate":"2015-09-20T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of estimates of basin-scale soil-moisture evapotranspiration and estimates of riparian groundwater evapotranspiration with implications for water budgets in the Verde Valley, Central Arizona, USA","docAbstract":"Population growth in the Verde Valley in Arizona has led to efforts to better understand water availability in the watershed. Evapotranspiration (ET) is a substantial component of the water budget and a critical factor in estimating groundwater recharge in the area. In this study, four estimates of ET are compared and discussed with applications to the Verde Valley. Higher potential ET (PET) rates from the soil-water balance (SWB) recharge model resulted in an average annual ET volume about 17% greater than for ET from the basin characteristics (BCM) recharge model. Annual BCM PET volume, however, was greater by about a factor of 2 or more than SWB actual ET (AET) estimates, which are used in the SWB model to estimate groundwater recharge. ET also was estimated using a method that combines MODIS-EVI remote sensing data and geospatial information and by the MODFLOW-EVT ET package as part of a regional groundwater-flow model that includes the study area. Annual ET volumes were about same for upper-bound MODIS-EVI ET for perennial streams as for the MODFLOW ET estimates, with the small differences between the two methods having minimal impact on annual or longer groundwater budgets for the study area.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2015.09.005","usgsCitation":"Tillman, F.D., Wiele, S.M., and Pool, D.R., 2015, A comparison of estimates of basin-scale soil-moisture evapotranspiration and estimates of riparian groundwater evapotranspiration with implications for water budgets in the Verde Valley, Central Arizona, USA: Journal of Arid Environments, v. 124, p. 278-291, https://doi.org/10.1016/j.jaridenv.2015.09.005.","productDescription":"14 p.","startPage":"278","endPage":"291","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062528","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471782,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jaridenv.2015.09.005","text":"Publisher Index Page"},{"id":308335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.43291497881991,\n 35.18255355174023\n ],\n [\n -112.43291497881991,\n 34.55130008916785\n ],\n [\n -110.95736033278712,\n 34.55130008916785\n ],\n [\n -110.95736033278712,\n 35.18255355174023\n ],\n [\n -112.43291497881991,\n 35.18255355174023\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"124","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56012a34e4b03bc34f5443ea","chorus":{"doi":"10.1016/j.jaridenv.2015.09.005","url":"http://dx.doi.org/10.1016/j.jaridenv.2015.09.005","publisher":"Elsevier BV","authors":"Tillman F.D, Wiele S.M., Pool D.R.","journalName":"Journal of Arid Environments","publicationDate":"1/2016"},"contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiele, Stephen M. smwiele@usgs.gov","contributorId":2199,"corporation":false,"usgs":true,"family":"Wiele","given":"Stephen","email":"smwiele@usgs.gov","middleInitial":"M.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572775,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215738,"text":"70215738 - 2015 - Metagenomic analysis of planktonic microbial consortia from a non-tidal urban-impacted segment of James River","interactions":[],"lastModifiedDate":"2020-10-28T12:55:07.626365","indexId":"70215738","displayToPublicDate":"2015-09-19T07:49:37","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7182,"text":"Standards in Genomic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Metagenomic analysis of planktonic microbial consortia from a non-tidal urban-impacted segment of James River","docAbstract":"Knowledge of the diversity and ecological function of the microbial consortia of James River in Virginia, USA, is essential to developing a more complete understanding of the ecology of this model river system. Metagenomic analysis of James River's planktonic microbial community was performed for the first time using an unamplified genomic library and a 16S rDNA amplicon library prepared and sequenced by Ion PGM and MiSeq, respectively. From the 0.46-Gb WGS library (GenBank:SRR1146621; MG-RAST:4532156.3), 4 × 106 reads revealed >3 × 106 genes, 240 families of prokaryotes, and 155 families of eukaryotes. From the 0.68-Gb 16S library (GenBank:SRR2124995; MG-RAST:4631271.3; EMB:2184), 4 × 106 reads revealed 259 families of eubacteria. Results of the WGS and 16S analyses were highly consistent and indicated that more than half of the bacterial sequences were Proteobacteria, predominantly Comamonadaceae. The most numerous genera in this group were Acidovorax (including iron oxidizers, nitrotolulene degraders, and plant pathogens), which accounted for 10 % of assigned bacterial reads. Polaromonas were another 6 % of all bacterial reads, with many assignments to groups capable of degrading polycyclic aromatic hydrocarbons. Albidiferax (iron reducers) and Variovorax (biodegraders of a variety of natural biogenic compounds as well as anthropogenic contaminants such as polycyclic aromatic hydrocarbons and endocrine disruptors) each accounted for an additional 3 % of bacterial reads. Comparison of these data to other publically-available aquatic metagenomes revealed that this stretch of James River is highly similar to the upper Mississippi River, and that these river systems are more similar to aquaculture and sludge ecosystems than they are to lakes or to a pristine section of the upper Amazon River. Taken together, these analyses exposed previously unknown aspects of microbial biodiversity, documented the ecological responses of microbes to urban effects, and revealed the noteworthy presence of 22 human-pathogenic bacterial genera (e.g., Enterobacteriaceae, pathogenic Pseudomonadaceae, and ‘Vibrionales') and 6 pathogenic eukaryotic genera (e.g., Trypanosomatidae and Vahlkampfiidae). This information about pathogen diversity may be used to promote human epidemiological studies, enhance existing water quality monitoring efforts, and increase awareness of the possible health risks associated with recreational use of James River.
The water resources of Deep Creek Valley were assessed during 2012–13 with an emphasis on better understanding the groundwater flow system and groundwater budget. Surface-water resources are limited in Deep Creek Valley and are generally used for agriculture. Groundwater is the predominant water source for most other uses and to supplement irrigation. Most groundwater withdrawal in Deep Creek Valley occurs from the unconsolidated basin-fill deposits, in which conditions are generally unconfined near the mountain front and confined in the lower-altitude parts of the valley. Productive aquifers are also present in fractured bedrock that occurs along the valley margins and beneath the basin-fill deposits. The consolidated-rock and basin-fill aquifers are hydraulically connected in many areas with much of the recharge occurring in the consolidated-rock mountain blocks and most of the discharge occurring from the lower-altitude basin-fill deposits.
\nAverage annual recharge to the Deep Creek Valley hydrographic area was estimated to be between 19,000 and 29,000 acre-feet. Groundwater recharge occurs mostly from the infiltration of precipitation and snowmelt at high altitudes. Additional, but limited recharge occurs from the infiltration of runoff from precipitation near the mountain front, infiltration along stream channels, and possible subsurface inflow from adjacent hydrographic areas. Groundwater moves from areas of recharge to springs and streams in the mountains, and to evapotranspiration areas, springs, streams, and wells in the basins. Discharge may also occur as subsurface groundwater outflow to adjacent hydrographic areas. Average annual discharge from the Deep Creek Valley hydrographic area was estimated to be between 21,000 and 22,000 acre-feet, with the largest portion of discharge occurring as evapotranspiration.
\nGroundwater samples were collected from 10 sites for geochemical analysis. Dissolved-solids concentrations ranged from 126 to 475 milligrams per liter, and none of the sites sampled during this study had dissolved-solids concentrations that exceeded the Environmental Protection Agency secondary standard for drinking water of 500 milligrams per liter. Tritium concentrations from 1.6 to 10.1 tritium units at 3 of the 10 sample sites indicate the presence of modern (less than 60 years old) groundwater, and apparent tritium/helium-3 ages calculated for these sites ranged from 7 to 29 years. The other seven sample sites had tritium concentrations less than or equal to 0.4 tritium units and are assumed to be pre-modern. Adjusted minimum radiocarbon ages of these seven pre-modern water samples ranged from 1,000 to 8,000 years with the ages of at least four of the samples being more than 3,000 years. Noble-gas recharge temperatures indicate that groundwater sampled along the valley axis recharged at both mountain and valley altitudes, providing evidence for both mountain-block and mountain-front recharge.
\nWater-level altitude contours and groundwater ages indicate the potential for a long flow path from southwest to northeast between northern Spring and Deep Creek Valleys through Tippett Valley. Although information gathered during this study is insufficient to conclude whether or not groundwater travels along this interbasin flow path, dissolved sulfate and chloride data indicate that a small fraction of the lower altitude, northern Deep Creek Valley discharge may be sourced from these areas. Despite the uncertainty due to limited data collection points, a hydraulic connection between northern Spring Valley, Tippett Valley, and Deep Creek Valley appears likely, and potential regional effects resulting from future groundwater withdrawals in northern Spring Valley warrant ongoing monitoring of groundwater levels across this area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155097","collaboration":"Prepared in cooperation with the Bureau of Indian Affairs","usgsCitation":"Gardner, P.M., and Masbruch, M.D., 2015, Hydrogeologic and geochemical characterization of groundwater resources in Deep Creek Valley and adjacent areas, Juab and Tooele Counties, Utah, and Elko and White Pine Counties, Nevada: U.S. Geological Survey Scientific Investigations Report 2015–5097, 53 p., https://dx.doi.org/10.3133/sir20155097.","productDescription":"viii, 54 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-037371","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":308275,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5097/coverthb.jpg"},{"id":308276,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5097/sir20155097.pdf","text":"Report","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5097 PDF"}],"country":"United States","state":"Nevada, Utah","county":"Elko County, Juab County, Tooele County, White Pine County","otherGeospatial":"Deep Creek Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.59564208984374,\n 39.35766163717121\n ],\n [\n -114.59564208984374,\n 40.49918094806632\n ],\n [\n -113.72222900390625,\n 40.49918094806632\n ],\n [\n -113.72222900390625,\n 39.35766163717121\n ],\n [\n -114.59564208984374,\n 39.35766163717121\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Utah Water Science Center
U.S. Geological Survey
2329 Orton Circle
Salt Lake City, Utah 84119-2047
http://ut.water.usgs.gov
High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV <15%). Satellite imagery may be an effective monitoring tool in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.596","usgsCitation":"LaRue, M.A., Stapleton, S.P., Porter, C., Atkinson, S.N., Atwood, T.C., Dyck, M., and Lecomte, N., 2015, Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution: Wildlife Society Bulletin, v. 39, no. 4, p. 772-779, https://doi.org/10.1002/wsb.596.","productDescription":"7 p.","startPage":"772","endPage":"779","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063293","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":500053,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/52601c9e182c489182032129672f748f","text":"External Repository"},{"id":326931,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Rowley Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.44238281249999,\n 69.21525256928653\n ],\n [\n -78.3544921875,\n 69.18404149599671\n ],\n [\n -78.2391357421875,\n 69.2425255645653\n ],\n [\n -78.1842041015625,\n 69.3086176331298\n ],\n [\n -78.1787109375,\n 69.35127582255352\n ],\n [\n -78.2830810546875,\n 69.3899830007604\n ],\n [\n -78.44238281249999,\n 69.39964894620636\n ],\n [\n -78.519287109375,\n 69.40931055535233\n ],\n [\n -78.64562988281249,\n 69.39191653683379\n ],\n [\n -78.7884521484375,\n 69.34740128319982\n ],\n [\n -78.717041015625,\n 69.29114227947211\n ],\n [\n -78.782958984375,\n 69.26976435077849\n ],\n [\n -78.8818359375,\n 69.20940390181205\n ],\n [\n -78.9312744140625,\n 69.15083065920365\n ],\n [\n -78.9422607421875,\n 69.12344255014861\n ],\n [\n -79.0411376953125,\n 69.13518451752405\n ],\n [\n -79.07958984375,\n 69.12148494192485\n ],\n [\n -79.21142578125,\n 69.12148494192485\n ],\n [\n -79.43115234375,\n 68.932736060549\n ],\n [\n -79.4146728515625,\n 68.83180177092166\n ],\n [\n -79.189453125,\n 68.81394200526994\n ],\n [\n -78.9093017578125,\n 68.87341871078524\n ],\n [\n -78.760986328125,\n 68.932736060549\n ],\n [\n -78.6016845703125,\n 69.03321086259241\n ],\n [\n -78.49731445312499,\n 69.08621799303475\n ],\n [\n -78.49731445312499,\n 69.12735724054714\n ],\n [\n -78.4259033203125,\n 69.17037257214531\n ],\n [\n -78.44238281249999,\n 69.21525256928653\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"57b82dece4b03fd6b7da3a22","contributors":{"authors":[{"text":"LaRue, Michelle A.","contributorId":20634,"corporation":false,"usgs":true,"family":"LaRue","given":"Michelle","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":646378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapleton, Seth P. sstapleton@usgs.gov","contributorId":3979,"corporation":false,"usgs":true,"family":"Stapleton","given":"Seth","email":"sstapleton@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Porter, Claire","contributorId":131120,"corporation":false,"usgs":false,"family":"Porter","given":"Claire","email":"","affiliations":[],"preferred":false,"id":646380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Stephen N.","contributorId":12365,"corporation":false,"usgs":false,"family":"Atkinson","given":"Stephen","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":646381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":646343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dyck, Markus","contributorId":173868,"corporation":false,"usgs":false,"family":"Dyck","given":"Markus","affiliations":[],"preferred":false,"id":646382,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lecomte, Nicolas","contributorId":131119,"corporation":false,"usgs":false,"family":"Lecomte","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":646383,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157350,"text":"70157350 - 2015 - Suitability of Lake Erie for bigheaded carps based on bioenergetic models and remote sensing","interactions":[],"lastModifiedDate":"2021-06-04T16:17:05.542032","indexId":"70157350","displayToPublicDate":"2015-09-18T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Suitability of Lake Erie for bigheaded carps based on bioenergetic models and remote sensing","docAbstract":"Algal blooms in the Great Lakes are a potential food source for silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis; together bigheaded carps). Understanding these blooms thus plays an important role in understanding the invasion potential of bigheaded carps. We used remote sensing imagery, temperatures, and improved species specific bioenergetics models to determine algal concentrations sufficient for adult bigheaded carps. Depending on water temperature we found that bigheaded carp require between 2 and 7 μg/L chlorophyll or between 0.3 and 1.26 × 105cells/mL Microcystis to maintain body weight. Algal concentrations in the western basin and shoreline were found to be commonly several times greater than the concentrations required for weight maintenance. The remote sensing images show that area of sufficient algal foods commonly encompassed several hundred square kilometers to several thousands of square kilometers when blooms form. From 2002 to 2011, mean algal concentrations increased 273%–411%. This indicates Lake Erie provides increasingly adequate planktonic algal food for bigheaded carps. The water temperatures and algal concentrations detected in Lake Erie from 2008 to 2012 support positive growth rates such that a 4 kg silver carp could gain between 19 and 57% of its body weight in a year. A 5 kg bighead carp modeled at the same water temperatures could gain 20–81% of their body weight in the same period. The remote sensing imagery and bioenergetic models suggest that bigheaded carps would not be food limited if they invaded Lake Erie.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2015.03.029","usgsCitation":"Anderson, K.R., Chapman, D., Wynne, T., Masagounder, K., and Paukert, C.P., 2015, Suitability of Lake Erie for bigheaded carps based on bioenergetic models and remote sensing: Journal of Great Lakes Research, v. 41, no. 2, p. 358-366, https://doi.org/10.1016/j.jglr.2015.03.029.","productDescription":"9 p.","startPage":"358","endPage":"366","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056785","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":308312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie, Lake St. Clair","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n 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Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C12","title":"Approaches in highly parameterized inversion—PEST++ Version 3, a Parameter ESTimation and uncertainty analysis software suite optimized for large environmental models","docAbstract":"The PEST++ Version 1 object-oriented parameter estimation code is here extended to Version 3 to incorporate additional algorithms and tools to further improve support for large and complex environmental modeling problems. PEST++ Version 3 includes the Gauss-Marquardt-Levenberg (GML) algorithm for nonlinear parameter estimation, Tikhonov regularization, integrated linear-based uncertainty quantification, options of integrated TCP/IP based parallel run management or external independent run management by use of a Version 2 update of the GENIE Version 1 software code, and utilities for global sensitivity analyses. The Version 3 code design is consistent with PEST++ Version 1 and continues to be designed to lower the barriers of entry for users as well as developers while providing efficient and optimized algorithms capable of accommodating large, highly parameterized inverse problems. As such, this effort continues the original focus of (1) implementing the most popular and powerful features of the PEST software suite in a fashion that is easy for novice or experienced modelers to use and (2) developing a software framework that is easy to extend.
\nThe PEST++ Version 3 software suite can be compiled for Microsoft Windows®4 and Linux®5 operating systems; the source code is available in a Microsoft Visual Studio®6 2013 solution; Linux Makefiles are also provided. PEST++ Version 3 continues to build a foundation for an open-source framework capable of producing robust and efficient parameter estimation tools for large environmental models.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section C: Computer programs in Book 7 Automated Data Processing and Computations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C12","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency,Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, Wisconsin 53562-3586
http://wi.water.usgs.gov/
The involvement of prokaryotes in the redox reactions of arsenic occurring between its +5 [arsenate; As(V)] and +3 [arsenite; As(III)] oxidation states has been well established. Most research to date has focused upon circum-neutral pH environments (e.g., freshwater or estuarine sediments) or arsenic-rich “extreme” environments like hot springs and soda lakes. In contrast, relatively little work has been conducted in acidic environments. With this in mind we conducted experiments with sediments taken from the Herman Pit, an acid mine drainage impoundment of a former mercury (cinnabar) mine. Due to the large adsorptive capacity of the abundant Fe(III)-rich minerals, we were unable to initially detect in solution either As(V) or As(III) added to the aqueous phase of live sediment slurries or autoclaved controls, although the former consumed added electron donors (i.e., lactate, acetate, hydrogen), while the latter did not. This prompted us to conduct further experiments with diluted slurries using the live materials from the first incubation as inoculum. In these experiments we observed reduction of As(V) to As(III) under anoxic conditions and reduction rates were enhanced by addition of electron donors. We also observed oxidation of As(III) to As(V) in oxic slurries as well as in anoxic slurries amended with nitrate. We noted an acid-tolerant trend for sediment slurries in the cases of As(III) oxidation (aerobic and anaerobic) as well as for anaerobic As(V) reduction. These observations indicate the presence of a viable microbial arsenic redox cycle in the sediments of this extreme environment, a result reinforced by the successful amplification of arsenic functional genes (aioA, and arrA) from these materials.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/01490451.2015.1080323","usgsCitation":"Blum, J.S., McCann, S., Bennett, S., Miller, L., Stolz, J.R., Stoneburner, B., Saltikov, C., and Oremland, R.S., 2015, A microbial arsenic cycle in sediments of an acidic mine impoundment: Herman Pit, Clear Lake, California: Geomicrobiology Journal, p. 1-13, https://doi.org/10.1080/01490451.2015.1080323.","productDescription":"14 p.","startPage":"1","endPage":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066520","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":488824,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/dataset/A_microbial_arsenic_cycle_in_sediments_of_an_acidic_mine_impoundment_Herman_Pit_Clear_Lake_California_/1569057","text":"External Repository"},{"id":325714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake State Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.80363082885741,\n 39.01958379846303\n ],\n [\n -122.80929565429688,\n 39.02345139405932\n ],\n [\n -122.81719207763672,\n 39.02625193465452\n ],\n [\n -122.8226852416992,\n 39.026518647020076\n ],\n [\n -122.82302856445312,\n 39.01998390437055\n ],\n [\n -122.82234191894531,\n 39.00984719020561\n ],\n [\n -122.81839370727539,\n 39.00251050399366\n ],\n [\n -122.81770706176758,\n 38.99717425427704\n ],\n [\n -122.80586242675781,\n 38.99117049229764\n ],\n [\n -122.79830932617186,\n 38.99170418065391\n ],\n [\n -122.79041290283202,\n 38.99650719476513\n ],\n [\n -122.78715133666991,\n 39.0026439050801\n ],\n [\n -122.79178619384764,\n 39.00998057745704\n ],\n [\n -122.79573440551756,\n 39.01624949451788\n ],\n [\n -122.80363082885741,\n 39.01958379846303\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-12","publicationStatus":"PW","scienceBaseUri":"5799db2fe4b0589fa1c7e674","contributors":{"authors":[{"text":"Blum, Jodi S. jsblum@usgs.gov","contributorId":4263,"corporation":false,"usgs":true,"family":"Blum","given":"Jodi","email":"jsblum@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":643655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCann, Shelley 0000-0002-9753-7968 smccann@usgs.gov","orcid":"https://orcid.org/0000-0002-9753-7968","contributorId":149902,"corporation":false,"usgs":true,"family":"McCann","given":"Shelley","email":"smccann@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":643649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, S. 0000-0002-9772-4122","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":29230,"corporation":false,"usgs":true,"family":"Bennett","given":"S.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":643650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Laurence G. 0000-0002-7807-3475 lgmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-7807-3475","contributorId":2460,"corporation":false,"usgs":true,"family":"Miller","given":"Laurence G.","email":"lgmiller@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":643651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stolz, J. R.","contributorId":173201,"corporation":false,"usgs":false,"family":"Stolz","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":27189,"text":"Department of Biological Sciences, Duquesne University, Pittsburgh, PA 15282","active":true,"usgs":false}],"preferred":false,"id":643652,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stoneburner, B.","contributorId":173202,"corporation":false,"usgs":false,"family":"Stoneburner","given":"B.","email":"","affiliations":[{"id":27190,"text":"Department of Microbiology and Ecotoxicology, University of California at Santa Cruz, Santa","active":true,"usgs":false}],"preferred":false,"id":643653,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Saltikov, C.","contributorId":77722,"corporation":false,"usgs":true,"family":"Saltikov","given":"C.","email":"","affiliations":[],"preferred":false,"id":643654,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":643648,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70157090,"text":"ofr20151170 - 2015 - Agricultural irrigated land-use inventory for Jackson, Calhoun, and Gadsden Counties in Florida, and Houston County in Alabama, 2014","interactions":[],"lastModifiedDate":"2015-09-18T12:03:01","indexId":"ofr20151170","displayToPublicDate":"2015-09-18T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1170","title":"Agricultural irrigated land-use inventory for Jackson, Calhoun, and Gadsden Counties in Florida, and Houston County in Alabama, 2014","docAbstract":"A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to accurately estimate water use or to project future water demands in many Florida counties. This report provides a detailed digital map and summary of irrigated areas for 2014 within Jackson, Calhoun, and Gadsden Counties in Florida, and Houston County in Alabama. The irrigated areas were delineated using land-use data and orthoimagery that were then field verified between June and November 2014. Selected attribute data were collected for the irrigated areas, including crop type, primary water source, and type of irrigation system. Results of the 2014 study indicate that an estimated 31,608 acres were irrigated in Jackson County during 2014. This estimate includes 25,733 acres of field crops, 1,534 acres of ornamentals and grasses (including pasture), and 420 acres of orchards. Specific irrigated crops include cotton (11,759 acres), peanuts (9,909 acres), field corn (2,444 acres), and 3,235 acres of various vegetable (row) crops. The vegetable acreage includes 1,714 acres of which 857 acres were planted with both a spring and fall crop on the same field (double cropped). Overall, groundwater was used to irrigate 98.6 percent of the total irrigated acreage in Jackson County during 2014, whereas surface water and wastewater were used to irrigate the remaining 1.4 percent.
\nIrrigated cropland totaled 3,060 acres in Calhoun County; 4,547 acres in Gadsden County; and 10,333 acres in Houston County. In Calhoun County, sod accounted for the largest irrigated acreage (1,145 acres) followed by peanuts (886 acres). In Gadsden County, ornamentals accounted for the largest irrigated acreage (1,104 acres) followed by cotton (977 acres). In Houston County, cotton accounted for the largest irrigated acreage (4,310 acres) followed by peanuts (2,493 acres). Overall, an estimated 49,548 acres of land were irrigated during 2014 in the four counties inventoried. About 45,052 acres were irrigated by a center pivot, permanent or solid overhead fixtures, or a portable or traveling gun. In all, 650 center pivot irrigation systems were identified, and the calculated acreage under these pivots totaled 43,070 acres. There were 405 center pivot irrigation systems counted in Jackson County during the 2014 field verification followed by Houston with 197, Gadsden with 48, and Calhoun with 10. An estimated 35,087 acres of field corn, cotton, peanuts, and sorghum were irrigated by center pivot systems during 2014 in these four counties combined. Vegetable acreage for the four counties combined totaled 6,699 acres, with 54 percent being irrigated by a drip irrigation system and the remaining 46 percent irrigated by a center pivot or traveling gun.
\nThe irrigated acreage estimated for Jackson County in 2014 (31,608) is about 47 percent higher than the 2012 estimated acreage published by the USDA (21,508 acres). The estimates of irrigated acreage field verified during 2014 for Calhoun and Gadsden Counties are also higher than those published by the USDA for 2012 (86 percent and 71 percent, respectively). In Calhoun County the USDA reported 1,647 irrigated acres while the current study estimated 3,060 acres, and in Gadsden County the USDA reported 2,650 acres while the current study estimated 4,547 acres. For Houston County the USDA-reported value of 9,138 acres in 2012 was 13 percent below the 10,333 acres field verified in the current study. Differences between the USDA 2012 values and 2014 field verified estimates in these two datasets may occur because (1) irrigated acreage for some specific crops increased or decreased substantially during the 2-year interval due to commodity prices or economic changes, (2) irrigated acreage calculated for the current study may be estimated high because irrigation was assumed if an irrigation system was present and therefore the acreage was counted as irrigated, when in fact that may not have been the case as some farmers may not have used their irrigation systems during this growing period even if they had a crop in the field, or (3) the amount of irrigated acreages published by the USDA for selected crops may be underestimated in some cases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151170","collaboration":"Prepared in cooperation with the Florida Department of Agriculture and Consumer Services","usgsCitation":"Marella, R.L., and Dixon, J.F., 2015, Agricultural irrigated land-use inventory for Jackson, Calhoun, and Gadsden Counties in Florida, and Houston County in Alabama, 2014: U.S. Geological Survey Open-File Report 2015–1170, 14 p., https://dx.doi.org/10.3133/ofr20151170.","productDescription":"Report: 14 p.; Appendix; GIS Shape Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062523","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":308269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1170/coverthb.jpg"},{"id":308270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1170/ofr20151170.pdf","text":"Report","size":"2.78 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Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
http://fl.water.usgs.gov
Historically, the city of Palmdale and vicinity have relied on groundwater as the primary source of water, owing, in large part, to the scarcity of surface water in the region. Despite recent importing of surface water, groundwater withdrawal for municipal, industrial, and agricultural use has resulted in groundwater-level declines near the city of Palmdale in excess of 200 feet since the early 1900s. To meet the growing water demand in the area, the city of Palmdale has proposed the Amargosa Creek Recharge Project (ACRP), which has a footprint of about 150 acres along the Amargosa Creek 2 miles west of Palmdale, California. The objective of this study was to evaluate the long-term feasibility of recharging the Antelope Valley aquifer system by using infiltration of imported surface water from the California State Water Project in percolation basins at the ACRP.
\nThree monitoring sites were constructed, and geophysical surveys (gravity, seismic, and resistivity) were completed to define the thickness of valley-fill deposits, depth to water, and location of faults that could influence groundwater flow. Data collected at the monitoring sites, and results from the geophysical surveys, were used to identify three northwest-southeast trending faults in the vicinity of the proposed recharge facility; these faults are probably related to the nearby San Andreas fault zone. Water levels collected from wells at the monitoring sites showed water-level altitude differences as much as 230 feet between the upgradient and downgradient sides of the faults, indicating that these faults are barriers to groundwater flow. Lithologic and geophysical logs indicated the presence of a coarse gravel and sand unit extending from land surface to about 150 feet below land surface that did not appear to be disrupted by faulting.
\nWater samples collected from the monitoring wells were analyzed for major ions, nutrients, trace elements, dissolved organic carbon, volatile organic compounds, stable isotopes of oxygen (oxygen-18) and hydrogen (hydrogen-2, or deuterium), and the radioactive isotopes of hydrogen (hydrogen-3, or tritium) and carbon (carbon-14, or 14C) to determine the water quality of the aquifer system and to help determine the source and age of the groundwater. Results of the water-quality analysis indicated that the source of natural recharge is Amargosa Creek near the ACRP, but that the creek does not provide modern-day recharge downstream of the ACRP.
\nPotential effects of artificial recharge at the ACRP were evaluated by using a local-scale model of groundwater flow. On the basis of geologic samples collected during drilling, the hydraulic conductivity of the sand and gravel unit in the upper 150 feet was assumed to range from 10 to 100 feet per day. To address the goal of minimizing the potential for liquefaction during an earthquake from water-table rise associated with groundwater recharge at the ACRP, simulated water levels were constrained to remain at least 50 feet below land surface, except beneath the proposed artificial-recharge facility.
\nThe hydraulic conductivities of faults were estimated on the basis of water-level data and an estimate of natural recharge along Amargosa Creek. With assumed horizontal hydraulic conductivities of 10 and 100 feet per day in the upper 150 feet, the simulated maximum artificial recharge rates to the regional flow system at the ACRP were 3,400 and 9,400 acre-feet per year, respectively. These maximum recharge rates were limited primarily by the horizontal hydraulic conductivity in the upper 150 feet and by the liquefaction constraint. Future monitoring of water-level and soil-water content changes during the proposed project would allow improved estimation of aquifer hydraulic properties, the effect of the faults on groundwater movement, and the overall recharge capacity of the ACRP.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155054","collaboration":"Prepared in cooperation with the city of Palmdale, California","usgsCitation":"Christensen, A.H., Siade, A.J., Martin, Peter, Langeheim, V.E., Catchings, R.D., and Burgess, M.K., 2015, Feasibility and potential effects of the proposed Amargosa Creek recharge project, Palmdale, California: U.S. Geological Survey Scientific Investigations Report 2015–5054, 48 p., https://dx.doi.org/10.3133/SIR20155054.","productDescription":"viii, 48 p.","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-029364","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":307894,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5054/sir20155054.pdf","text":"Report","size":"24.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5054"},{"id":307893,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5054/coverthb.jpg"}],"country":"United States","state":"California","city":"Palmdale","otherGeospatial":"Antelope Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.58779907226561,\n 34.41710628141647\n ],\n [\n -118.58779907226561,\n 34.813803317113155\n ],\n [\n -117.73635864257812,\n 34.813803317113155\n ],\n [\n -117.73635864257812,\n 34.41710628141647\n ],\n [\n -118.58779907226561,\n 34.41710628141647\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95829
http://ca.water.usgs.gov
Methicillin-resistant Staphylococcus aureus (MRSA) are a threat to human health worldwide, and although detected at marine beaches, they have been largely unstudied at freshwater beaches. Genes indicating S. aureus (SA; femA) and methicillin resistance (mecA) were detected at 11 and 12 of 13 US Great Lakes beaches and in 18% or 27% of 287 recreational water samples, respectively. Eight beaches had mecA + femA (potential MRSA) detections. During an intensive study, higher bather numbers, staphylococci concentrations, and femA detections were found in samples collected after noon than before noon. Local population density, beach cloud cover, and beach wave height were significantly correlated with SA or MRSA detection frequency. The Panton-Valentine leukocidin gene, associated with community-acquired MRSA, was detected in 12 out of 27 potential MRSA samples. The femA gene was detected less frequently at beaches that met US enterococci criteria or EU enterococci ‘excellent’ recreational water quality, but was not related to Escherichia coli-defined criteria. Escherichia coli is often the only indicator used to determine water quality at US beaches, given the economic and healthcare burden that can be associated with infections caused by SA and MRSA, monitoring of recreational waters for non-fecal bacteria such as staphylococci and/or SA may be warranted.
","language":"English","publisher":"IWA Publishing","doi":"10.2166/wh.2014.278","usgsCitation":"Fogarty, L.R., Haack, S.K., Johnson, H., Brennan, A., Isaacs, N.M., and Spencer, C., 2015, Staphylococcus aureus and methicillin-resistant S. aureus (MRSA) at ambient freshwater beaches: Journal of Water and Health, v. 13, no. 3, p. 680-692, https://doi.org/10.2166/wh.2014.278.","productDescription":"13 p.","startPage":"680","endPage":"692","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059960","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":308243,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":471786,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2166/wh.2014.278","text":"Publisher Index Page"}],"volume":"13","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-29","publicationStatus":"PW","scienceBaseUri":"55fbd641e4b05d6c4e5028c9","contributors":{"authors":[{"text":"Fogarty, Lisa R. 0000-0003-0329-3251 lrfogart@usgs.gov","orcid":"https://orcid.org/0000-0003-0329-3251","contributorId":2053,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa","email":"lrfogart@usgs.gov","middleInitial":"R.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":572081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haack, Sheridan K. skhaack@usgs.gov","contributorId":1982,"corporation":false,"usgs":true,"family":"Haack","given":"Sheridan","email":"skhaack@usgs.gov","middleInitial":"K.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Heather E.","contributorId":207837,"corporation":false,"usgs":false,"family":"Johnson","given":"Heather E.","affiliations":[{"id":12456,"text":"former USGS scientist","active":true,"usgs":false},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":744850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brennan, Angela K. akbrennan@usgs.gov","contributorId":147588,"corporation":false,"usgs":true,"family":"Brennan","given":"Angela K.","email":"akbrennan@usgs.gov","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":572084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Isaacs, Natasha M. nisaacs@usgs.gov","contributorId":4918,"corporation":false,"usgs":true,"family":"Isaacs","given":"Natasha","email":"nisaacs@usgs.gov","middleInitial":"M.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Chelsea","contributorId":147589,"corporation":false,"usgs":false,"family":"Spencer","given":"Chelsea","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":572086,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157211,"text":"70157211 - 2015 - Climate change and physical disturbance manipulations result in distinct biological soil crust communities","interactions":[],"lastModifiedDate":"2015-10-05T16:06:15","indexId":"70157211","displayToPublicDate":"2015-09-17T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and physical disturbance manipulations result in distinct biological soil crust communities","docAbstract":"Biological soil crusts (biocrusts) colonize plant interspaces in many drylands and are critical to soil nutrient cycling. Multiple climate change and land use factors have been shown to detrimentally impact biocrusts on a macroscopic (i.e., visual) scale. However, the impact of these perturbations on the bacterial components of the biocrusts remain poorly understood. We employed multiple long-term field experiments to assess the impacts of chronic physical (foot trampling) and climatic changes (2 °C soil warming, altered summer precipitation (wetting), and combined warming and wetting) on biocrust bacterial biomass, composition, and metabolic profile. The biocrust bacterial communities adopted distinct states based on the mechanism of disturbance. Chronic trampling decreased biomass and caused small community compositional change. Soil warming had little effect on biocrust biomass or composition, while wetting resulted in an increase in cyanobacterial biomass and altered bacterial composition. Warming combined with wetting dramatically altered bacterial composition and decreased cyanobacteria abundance. Shotgun metagenomic sequencing identified four functional gene categories that differed in relative abundance among the manipulations, suggesting that climate and land use changes affected soil bacterial functional potential. This study illustrates that different types of biocrust disturbance damage biocrusts in macroscopically similar ways, but they differentially impact the resident soil bacterial communities and the community functional profile can differ depending on the disturbance type. Therefore, the nature of the perturbation and the microbial response are important considerations for management and restoration of drylands.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/AEM.01443-15","usgsCitation":"Steven, B., Kuske, C.R., Gallegos-Graves, L., Reed, S.C., and Belnap, J., 2015, Climate change and physical disturbance manipulations result in distinct biological soil crust communities: Applied and Environmental Microbiology, v. 81, no. 21, p. 7448-7459, https://doi.org/10.1128/AEM.01443-15.","productDescription":"12 p.","startPage":"7448","endPage":"7459","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068267","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1128/aem.01443-15","text":"Publisher Index Page"},{"id":308242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Arches National Park, Canyonlands National Park, Castle Valley, Island in the Sky District,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.720458984375,\n 38.59004038021371\n ],\n [\n -109.720458984375,\n 38.80975079723835\n ],\n [\n -109.30984497070312,\n 38.80975079723835\n ],\n [\n -109.30984497070312,\n 38.59004038021371\n ],\n [\n -109.720458984375,\n 38.59004038021371\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.95529174804686,\n 38.306102934215616\n ],\n [\n -109.95529174804686,\n 38.382574703770246\n ],\n [\n -109.77676391601562,\n 38.382574703770246\n ],\n [\n -109.77676391601562,\n 38.306102934215616\n ],\n [\n -109.95529174804686,\n 38.306102934215616\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"21","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fbd63ae4b05d6c4e5028c3","contributors":{"authors":[{"text":"Steven, Blaire","contributorId":48470,"corporation":false,"usgs":true,"family":"Steven","given":"Blaire","affiliations":[],"preferred":false,"id":572274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuske, Cheryl R.","contributorId":81063,"corporation":false,"usgs":false,"family":"Kuske","given":"Cheryl","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":572275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gallegos-Graves, La Verne","contributorId":97408,"corporation":false,"usgs":true,"family":"Gallegos-Graves","given":"La Verne","affiliations":[],"preferred":false,"id":572276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":572277,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157224,"text":"70157224 - 2015 - Age estimations of wild pallid sturgeon (Scaphirhynchus albus, Forbes & Richardson 1905) based on pectoral fin spines, otoliths and bomb radiocarbon: inferences on recruitment in the dam-fragmented Missouri River","interactions":[],"lastModifiedDate":"2015-09-17T11:04:44","indexId":"70157224","displayToPublicDate":"2015-09-17T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2166,"text":"Journal of Applied Ichthyology","active":true,"publicationSubtype":{"id":10}},"title":"Age estimations of wild pallid sturgeon (Scaphirhynchus albus, Forbes & Richardson 1905) based on pectoral fin spines, otoliths and bomb radiocarbon: inferences on recruitment in the dam-fragmented Missouri River","docAbstract":"An extant stock of wild pallid sturgeon Scaphirhynchus albus persists in the fragmented upper Missouri River basin of Montana and North Dakota. Although successful spawning and hatch of embryos has been verified, long-term catch records suggest that recruitment has not occurred for several decades as the extant stock lacks juvenile size classes and is comprised exclusively of large, presumably old individuals. Ages of 11 deceased (death years 1997–2007) wild S. albus (136–166 cm fork length) were estimated based on pectoral fin spines, sagittal otoliths and bomb radiocarbon (14C) assays of otoliths to test the hypothesis that members of this stock are old and to provide inferences on recruitment years that produced the extant stock. Age estimations based on counts of presumed annuli were about 2 years greater for otoliths (mean = 51 years, range = 43–57 years) than spines (mean = 49 years, range = 37–59 years). Based on 14C assays, confirmed birth years for all individuals occurred prior to 1957, thus establishing known longevity of at least 50 years. Estimated age based on presumed otolith annuli for one S. albus was validated to at least age 49. Although 14C assays confirmed pre-1957 birth years for all S. albus, only 56% of estimated ages from spines and 91% of estimated ages from otoliths depicted pre-1957 birth years. Both ageing structures were subject to under-ageing error (up to 15 years). Lack of or severe curtailment of S. albus recruitment in the upper Missouri River basin since the mid-1950s closely parallels the 1953–1957 timeframe when a mainstem reservoir was constructed and started to fill. This reservoir may function as a system-wide stressor to diminish recruitment success of S. albus in the upper Missouri River basin.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.12873","collaboration":"Fisheries and Oceans Canada; Montana Fish, Wildlife and Parks; Wisconsin Department of Natural Resources; U. S. Fish and Wildlife Service","usgsCitation":"Braaten, P., Campana, S.E., Fuller, D.B., Lott, R.D., Bruch, R.M., and Jordan, G.R., 2015, Age estimations of wild pallid sturgeon (Scaphirhynchus albus, Forbes & Richardson 1905) based on pectoral fin spines, otoliths and bomb radiocarbon: inferences on recruitment in the dam-fragmented Missouri River: Journal of Applied Ichthyology, v. 31, no. 5, p. 821-829, https://doi.org/10.1111/jai.12873.","productDescription":"9 p.","startPage":"821","endPage":"829","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060218","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":471788,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jai.12873","text":"Publisher Index Page"},{"id":308241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.973876953125,\n 46.20264638061019\n ],\n [\n -106.973876953125,\n 48.180738507303836\n ],\n [\n -100.887451171875,\n 48.180738507303836\n ],\n [\n -100.887451171875,\n 46.20264638061019\n ],\n [\n -106.973876953125,\n 46.20264638061019\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-08","publicationStatus":"PW","scienceBaseUri":"55fbd636e4b05d6c4e5028c1","contributors":{"authors":[{"text":"Braaten, P. J. pbraaten@usgs.gov","contributorId":2724,"corporation":false,"usgs":true,"family":"Braaten","given":"P. J.","email":"pbraaten@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":572297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campana, S. E.","contributorId":147671,"corporation":false,"usgs":false,"family":"Campana","given":"S.","email":"","middleInitial":"E.","affiliations":[{"id":16891,"text":"Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada","active":true,"usgs":false}],"preferred":false,"id":572298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, D. B.","contributorId":58196,"corporation":false,"usgs":true,"family":"Fuller","given":"D.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":572299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lott, R. D.","contributorId":147672,"corporation":false,"usgs":false,"family":"Lott","given":"R.","email":"","middleInitial":"D.","affiliations":[{"id":16892,"text":"Montana Fish, Wildlife and Parks, Fort Peck, Montana","active":true,"usgs":false}],"preferred":false,"id":572300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bruch, R. M.","contributorId":147673,"corporation":false,"usgs":false,"family":"Bruch","given":"R.","email":"","middleInitial":"M.","affiliations":[{"id":16893,"text":"Wisconsin Department of Natural Resources, Oshkosh, Wisconsin","active":true,"usgs":false}],"preferred":false,"id":572301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jordan, G. R.","contributorId":147674,"corporation":false,"usgs":false,"family":"Jordan","given":"G.","email":"","middleInitial":"R.","affiliations":[{"id":16894,"text":"U. S. Fish and Wildlife Service, Billings, Montana","active":true,"usgs":false}],"preferred":false,"id":572302,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157271,"text":"70157271 - 2015 - Developing analytical approaches to explore the connection between endocrine-active pharmaceuticals in water to effects in fish","interactions":[],"lastModifiedDate":"2018-09-04T16:23:57","indexId":"70157271","displayToPublicDate":"2015-09-17T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":764,"text":"Analytical and Bioanalytical Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Developing analytical approaches to explore the connection between endocrine-active pharmaceuticals in water to effects in fish","docAbstract":"The emphasis of this research project was to develop and optimize a solid-phase extraction method and highperformance liquid chromatography-electrospray ionizationmass spectrometry method, such that a linkage between the detection of endocrine-active pharmaceuticals (EAPs) in the aquatic environment and subsequent effects on fish populations could eventually be studied. Four EAPs were studied: tamoxifen (TAM), exemestane (EXE), letrozole (LET), anastrozole (ANA); and three TAM metabolites: 4- hydroxytamoxifen, e/z endoxifen, and n-desmethyl tamoxifen. In aqueous matrices, the use of isotopically labeled standards for the EAPs allowed for the generation of good recoveries, greater than 80 %, and low relative standard deviations (% RSDs) (3 to 27 %). TAM metabolites had lower recoveries in the spiked water matrices: 35 to 93 % in waste/source water compared to 58 to 110 % in DI water. The precision in DI water was acceptable ranging from 8 to 38 % RSD. However, the precision in real environmental wastewaters could be poor, ranging from 15 to 120 % RSD, dependent upon unique matrix effects. In plasma, the overall recoveries of the EAPs were acceptable: 88 to 110 %, with %RSDs of 6 to 18 % (Table 3). The spiked recoveries of the TAM metabolites from plasma were good, ranging from 77 to 120 %, with %RSDs ranging from 27 to 32 %. Two of the TAM metabolites, 4- hydroxytamoxifen and n-desmethyl tamoxifen, were confirmed in most of the environmental aqueous samples. The discovery of TAM metabolites demonstrates that the source of the TAM metabolites, TAM, is constant, introducing a pseudo-persistence of this chemical into the environment.
","language":"English","publisher":"Springer","doi":"10.1007/s00216-015-8813-0","collaboration":"U.S. Environmental Protection Agency","usgsCitation":"Jones-Lepp, T.L., Taniguchi-Fu, R., Morgan, J., Nance, T., Ward, M., Alvarez, D., and Mills, L., 2015, Developing analytical approaches to explore the connection between endocrine-active pharmaceuticals in water to effects in fish: Analytical and Bioanalytical Chemistry, v. 407, no. 21, p. 6481-6492, https://doi.org/10.1007/s00216-015-8813-0.","productDescription":"12 p.","startPage":"6481","endPage":"6492","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063155","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":308239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"407","issue":"21","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-16","publicationStatus":"PW","scienceBaseUri":"55fbd63be4b05d6c4e5028c5","contributors":{"authors":[{"text":"Jones-Lepp, Tammy L.","contributorId":103132,"corporation":false,"usgs":true,"family":"Jones-Lepp","given":"Tammy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":572523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taniguchi-Fu, Randi L.","contributorId":147746,"corporation":false,"usgs":false,"family":"Taniguchi-Fu","given":"Randi L.","affiliations":[{"id":16920,"text":"US Environmental Protection Agency, National Exposure Research Laboratory, Office of Research and Development, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":572524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgan, Jade","contributorId":147747,"corporation":false,"usgs":false,"family":"Morgan","given":"Jade","email":"","affiliations":[{"id":16920,"text":"US Environmental Protection Agency, National Exposure Research Laboratory, Office of Research and Development, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":572525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nance, Trevor","contributorId":147748,"corporation":false,"usgs":false,"family":"Nance","given":"Trevor","email":"","affiliations":[{"id":16920,"text":"US Environmental Protection Agency, National Exposure Research Laboratory, Office of Research and Development, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":572526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ward, Matthew","contributorId":147749,"corporation":false,"usgs":false,"family":"Ward","given":"Matthew","affiliations":[{"id":16920,"text":"US Environmental Protection Agency, National Exposure Research Laboratory, Office of Research and Development, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":572527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alvarez, David A. dalvarez@usgs.gov","contributorId":139231,"corporation":false,"usgs":true,"family":"Alvarez","given":"David A.","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":572522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mills, Lesley","contributorId":147750,"corporation":false,"usgs":false,"family":"Mills","given":"Lesley","email":"","affiliations":[{"id":16921,"text":"US Environmental Protection Agency, National Human Health and Exposure Research Laboratory, Office of Research and Development, Narragansett, RI","active":true,"usgs":false}],"preferred":false,"id":572528,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157107,"text":"ofr20151175 - 2015 - Geology of Joshua Tree National Park geodatabase","interactions":[],"lastModifiedDate":"2015-09-17T10:04:18","indexId":"ofr20151175","displayToPublicDate":"2015-09-16T19:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1175","title":"Geology of Joshua Tree National Park geodatabase","docAbstract":"The database in this Open-File Report describes the geology of Joshua Tree National Park and was completed in support of the National Cooperative Geologic Mapping Program of the U.S. Geological Survey (USGS) and in cooperation with the National Park Service (NPS). The geologic observations and interpretations represented in the database are relevant to both the ongoing scientific interests of the USGS in southern California and the management requirements of NPS, specifically of Joshua Tree National Park (JOTR).
Joshua Tree National Park is situated within the eastern part of California’s Transverse Ranges province and straddles the transition between the Mojave and Sonoran deserts. The geologically diverse terrain that underlies JOTR reveals a rich and varied geologic evolution, one that spans nearly two billion years of Earth history. The Park’s landscape is the current expression of this evolution, its varied landforms reflecting the differing origins of underlying rock types and their differing responses to subsequent geologic events. Crystalline basement in the Park consists of Proterozoic plutonic and metamorphic rocks intruded by a composite Mesozoic batholith of Triassic through Late Cretaceous plutons arrayed in northwest-trending lithodemic belts. The basement was exhumed during the Cenozoic and underwent differential deep weathering beneath a low-relief erosion surface, with the deepest weathering profiles forming on quartz-rich, biotite-bearing granitoid rocks. Disruption of the basement terrain by faults of the San Andreas system began ca. 20 Ma and the JOTR sinistral domain, preceded by basalt eruptions, began perhaps as early as ca. 7 Ma, but no later than 5 Ma. Uplift of the mountain blocks during this interval led to erosional stripping of the thick zones of weathered quartz-rich granitoid rocks to form etchplains dotted by bouldery tors—the iconic landscape of the Park. The stripped debris filled basins along the fault zones.
Mountain ranges and basins in the Park exhibit an east-west physiographic grain controlled by left-lateral fault zones that form a sinistral domain within the broad zone of dextral shear along the transform boundary between the North American and Pacific plates. Geologic and geophysical evidence reveal that movement on the sinistral faults zones has resulted in left steps along the zones, resulting in the development of sub-basins beneath Pinto Basin and Shavers and Chuckwalla Valleys. The sinistral fault zones connect the Mojave Desert dextral faults of the Eastern California Shear Zone to the north and east with the Coachella Valley strands of the southern San Andreas Fault Zone to the west.
Quaternary surficial deposits accumulated in alluvial washes and playas and lakes along the valley floors; in alluvial fans, washes, and sheet wash aprons along piedmonts flanking the mountain ranges; and in eolian dunes and sand sheets that span the transition from valley floor to piedmont slope. Sequences of Quaternary pediments are planed into piedmonts flanking valley-floor and upland basins, each pediment in turn overlain by successively younger residual and alluvial surficial deposits.
GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center—Tucson, Arizona
U.S. Geological Survey, c/o University of Arizona
ENRB Bldg, 520 N. Park Ave, Rm 355
Tucson, Arizona 85719-5035
http://geomaps.wr.usgs.gov/
This study focused on the importance of the colmation layer in the removal of cyanobacteria, viruses, and dissolved organic carbon (DOC) during natural bank filtration. Injection-and-recovery studies were performed at two shallow (0.5 m deep), sandy, near-shore sites at the southern end of Ashumet Pond, a waste-impacted, kettle pond on Cape Cod, MA, that is subject to periodic blooms of cyanobacteria and continuously recharges a sole-source drinking-water aquifer. The experiment involved assessing the transport behaviors of bromide (conservative tracer), Synechococcus sp. IU625 (cyanobacterium, 2.6 ± 0.2 µm), AS-1 (tailed cyanophage, 110 nm long), MS2 (coliphage, 26 nm diameter), and carboxylate-modified microspheres (1.7 µm diameter) introduced to the colmation layer using a bag-and-barrel (Lee-type) seepage meter. The injectate constituents were tracked as they were advected across the pond water–groundwater interface and through the underlying aquifer sediments under natural-gradient conditions past push-point samplers placed at ∼30-cm intervals along a 1.2-m-long, diagonally downward flow path. More than 99% of the microspheres, IU625, MS2, AS-1, and ∼44% of the pond DOC were removed in the colmation layer (upper 25 cm of poorly sorted bottom sediments) at two test locations characterized by dissimilar seepage rates (1.7 vs. 0.26 m d−1). Retention profiles in recovered core material indicated that >82% of the attached IU625 were in the top 3 cm of bottom sediments. The colmation layer was also responsible for rapid changes in the character of the DOC and was more effective (by three orders of magnitude) at removing microspheres than was the underlying 20-cm-thick segment of sediment.
","language":"English","publisher":"American Society of Agronomy","publisherLocation":"Madison, WI","doi":"10.2134/jeq2015.03.0151","usgsCitation":"Harvey, R.W., Metge, D.W., LeBlanc, D.R., Underwood, J., Aiken, G.R., Butler, K.D., McCobb, T.D., and Jasperse, J., 2015, Importance of the colmation layer in the transport and removal of cyanobacteria, viruses, and dissolved organic carbon during natural lake-bank filtration: Journal of Environmental Quality, v. 44, no. 5, p. 1413-1423, https://doi.org/10.2134/jeq2015.03.0151.","productDescription":"11 p.","startPage":"1413","endPage":"1423","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066009","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central 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Central Branch","active":true,"usgs":true}],"preferred":true,"id":626922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Metge, David W. dwmetge@usgs.gov","contributorId":663,"corporation":false,"usgs":true,"family":"Metge","given":"David","email":"dwmetge@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":626923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628 dleblanc@usgs.gov","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":1696,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"dleblanc@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Underwood, Jennifer C. jcunder@usgs.gov","contributorId":4680,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer C.","email":"jcunder@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":626925,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":626926,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":626927,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCobb, Timothy D. 0000-0003-1533-847X tmccobb@usgs.gov","orcid":"https://orcid.org/0000-0003-1533-847X","contributorId":2012,"corporation":false,"usgs":true,"family":"McCobb","given":"Timothy","email":"tmccobb@usgs.gov","middleInitial":"D.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626928,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jasperse, Jay","contributorId":168661,"corporation":false,"usgs":false,"family":"Jasperse","given":"Jay","affiliations":[{"id":17863,"text":"Sonoma County Water Agency","active":true,"usgs":false}],"preferred":false,"id":626929,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70156394,"text":"sir20155112 - 2015 - Trace-metal and organic constituent concentrations in bed sediment at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas—Comparisons to sediment-quality guidelines and indications for timing of exposure","interactions":[],"lastModifiedDate":"2015-09-17T09:49:41","indexId":"sir20155112","displayToPublicDate":"2015-09-16T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5112","title":"Trace-metal and organic constituent concentrations in bed sediment at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas—Comparisons to sediment-quality guidelines and indications for timing of exposure","docAbstract":"This report compares concentrations for a wide range of inorganic and organic constituents in bed sediment from Big Base Lake and Little Base Lake, which are located on Little Rock Air Force Base, Arkansas, to sediment-quality guidelines. This report also compares trace-metal concentrations in a bed-sediment core sample to sediment age to determine when the highest concentrations of trace metals were deposited in Big Base Lake.
\nTrace-metal results often were higher than background concentrations in the surrounding Pulaski County area, and concentrations of arsenic, cadmium, cobalt, copper, lead, manganese, mercury, nickel, and zinc at one or more of three study sites were higher than median concentrations for a study involving 98 urban streams in seven metropolitan areas of the United States. Concentrations for most polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and organochlorine pesticides in all three bed-sediment samples were less than the laboratory reporting limit or were detected at low concentrations.
\nSome contaminants were detected at concentrations that are potentially toxic to sediment-dwelling biota; however, in general, the analyses suggest that the risk of sediment toxicity may be relatively low. Threshold effect concentrations were exceeded for 14 constituents—arsenic, copper, lead, nickel, and zinc, five polycyclic aromatic hydrocarbons compounds, chlordane, and all three dichlorodiphenyltrichloroethane (DDT) congeners—which suggests potential toxicity to some sediment-dwelling biota. Only two constituents had concentrations that exceeded published probable effect concentrations—arsenic (at the deepest site in Big Base Lake, NS6) and p,p’-dichlorodiphenyldichloroethylene (p,p’-DDE; at both sites in Big Base Lake, NS5 and NS6).
\nRegarding highest concentrations and associated timing of exposure, trace metals analyzed in the sediment core seem to indicate three fairly distinct exposure patterns. For 11 trace metals that had the highest concentration measured in the shallowest and most recently deposited sediment, the most likely explanation is recent exposure by anthropogenic activities. Most of the 11 trace metals with highest concentrations in shallow sediment are relatively innocuous; however, arsenic, copper, selenium, and zinc are among the U.S. Environmental Protection Agency’s 126 priority pollutants. For three trace metals (cadmium, lead, and mercury), for which concentrations were highest in sediments that were 16–20 centimeters down the core, it is likely that a source associated with those contaminants during the period when those sediments were deposited, was reduced or eliminated. The eight remaining trace metals, for which concentrations were highest in sediments that were just below the prereservoir surface, likely had sources that were eliminated soon after lake construction or occurred at relatively high background concentrations in soils in the area around Little Rock Air Force Base.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155112","collaboration":"Prepared in cooperation with Little Rock Air Force Base","usgsCitation":"Justus, B.G., Hays, P.D., and Hart, R.M., 2015, Trace-metal and organic constituent concentrations in bed sediment at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas—Comparisons to sediment-quality guidelines and indications for timing of exposure: U.S. Geological Survey Scientific Investigations Report 2015–5112, 17 p., https://dx.doi.org/10.3133/sir20155112.","productDescription":"vi, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065235","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":308110,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5112/coverthb.jpg"},{"id":308111,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5112/sir20155112.pdf","text":"Report","size":"526 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5112"}],"country":"United States","state":"Arkansas","otherGeospatial":"Big Base Lake, Little Base Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.16859817504881,\n 34.89230245992801\n ],\n [\n -92.16859817504881,\n 34.89849749646823\n ],\n [\n -92.16068029403685,\n 34.89849749646823\n ],\n [\n -92.16068029403685,\n 34.89230245992801\n ],\n [\n -92.16859817504881,\n 34.89230245992801\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, Arkansas 72211–3528
http://ar.water.usgs.gov/
Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic C-H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jag.2015.01.010","collaboration":"Andrew K. Skidmore, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands","usgsCitation":"Kokaly, R., and Skidmore, A.K., 2015, Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm: International Journal of Applied Earth Observation and Geoinformation, v. 43, p. 55-83, https://doi.org/10.1016/j.jag.2015.01.010.","productDescription":"29 p.","startPage":"55","endPage":"83","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059901","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":471790,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jag.2015.01.010","text":"Publisher Index Page"},{"id":308209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa849ce4b05d6c4e501a27","contributors":{"authors":[{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":139570,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","email":"raymond@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":572501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skidmore, Andrew K","contributorId":147736,"corporation":false,"usgs":false,"family":"Skidmore","given":"Andrew","email":"","middleInitial":"K","affiliations":[{"id":16918,"text":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":572502,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157235,"text":"70157235 - 2015 - Too hot to trot? evaluating the effects of wildfire on patterns of occupancy and abundance for a climate-sensitive habitat-specialist","interactions":[],"lastModifiedDate":"2015-10-19T12:36:45","indexId":"70157235","displayToPublicDate":"2015-09-16T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Too hot to trot? evaluating the effects of wildfire on patterns of occupancy and abundance for a climate-sensitive habitat-specialist","docAbstract":"Wildfires are increasing in frequency and severity as a result of climate change in many ecosystems; however, effects of altered disturbance regimes on wildlife remain poorly quantified. Here, we leverage an unexpected opportunity to investigate how fire affects the occupancy and abundance of a climate-sensitive habitat specialist, the American pika (Ochotona princeps). We determine the effects of a fire on microclimates within talus and explore habitat factors promoting persistence and abundance in fire-affected habitat. During the fire, temperatures in talus interstices remained below 19°C, suggesting that animals could have survived in situ. Within 2 years, pikas were widely distributed throughout burned areas and did not appear to be physiologically stressed at severely burned sites. Furthermore, pika densities were better predicted by topographic variables known to affect this species than by metrics of fire severity. This widespread distribution may reflect quick vegetation recovery and the fact that the fire did not alter the talus microclimates in the following years. Together, these results highlight the value of talus as a thermal refuge for small animals during and after fire. They also underscore the importance of further study in individual species’ responses to typical and altered disturbance regimes.
","language":"English","publisher":"International Association of Wildland Fire","doi":"10.1071/WF15038","usgsCitation":"Varner, J., Lambert, M.S., Horns, J.J., Laverty, S., Dizney, L., Beever, E., and Dearing, M.D., 2015, Too hot to trot? evaluating the effects of wildfire on patterns of occupancy and abundance for a climate-sensitive habitat-specialist: International Journal of Wildland Fire, v. 24, no. 7, p. 921-932, https://doi.org/10.1071/WF15038.","productDescription":"12 p.","startPage":"921","endPage":"932","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-063302","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":308208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Mt. Hood","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.7889404296875,\n 45.30773430004869\n ],\n [\n -121.7889404296875,\n 45.42255200704734\n ],\n [\n -121.60903930664062,\n 45.42255200704734\n ],\n [\n -121.60903930664062,\n 45.30773430004869\n ],\n [\n -121.7889404296875,\n 45.30773430004869\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa849de4b05d6c4e501a2d","contributors":{"authors":[{"text":"Varner, Johanna","contributorId":147700,"corporation":false,"usgs":false,"family":"Varner","given":"Johanna","email":"","affiliations":[{"id":16911,"text":"Dept. of Biology, University of Utah, Salt Lake City, UT","active":true,"usgs":false}],"preferred":false,"id":572356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lambert, Mallory S.","contributorId":147701,"corporation":false,"usgs":false,"family":"Lambert","given":"Mallory","email":"","middleInitial":"S.","affiliations":[{"id":16911,"text":"Dept. of Biology, University of Utah, Salt Lake City, UT","active":true,"usgs":false}],"preferred":false,"id":572357,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horns, Joshua J.","contributorId":147702,"corporation":false,"usgs":false,"family":"Horns","given":"Joshua","email":"","middleInitial":"J.","affiliations":[{"id":16911,"text":"Dept. of Biology, University of Utah, Salt Lake City, UT","active":true,"usgs":false}],"preferred":false,"id":572358,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laverty, Sean","contributorId":147703,"corporation":false,"usgs":false,"family":"Laverty","given":"Sean","email":"","affiliations":[{"id":16912,"text":"University of Central Oklahoma, Department of Mathematics, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":572359,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dizney, Laurie","contributorId":147704,"corporation":false,"usgs":false,"family":"Dizney","given":"Laurie","email":"","affiliations":[{"id":16913,"text":"University of Portland, Department of Biology, Portland, OR","active":true,"usgs":false}],"preferred":false,"id":572360,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beever, Erik A. 0000-0002-9369-486X ebeever@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-486X","contributorId":147685,"corporation":false,"usgs":true,"family":"Beever","given":"Erik A.","email":"ebeever@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":572355,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dearing, M. Denise","contributorId":147705,"corporation":false,"usgs":false,"family":"Dearing","given":"M.","email":"","middleInitial":"Denise","affiliations":[{"id":16911,"text":"Dept. of Biology, University of Utah, Salt Lake City, UT","active":true,"usgs":false}],"preferred":false,"id":572361,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70157264,"text":"70157264 - 2015 - Landscape structure affects specialists but not generalists in naturally fragmented grasslands","interactions":[],"lastModifiedDate":"2016-01-04T10:37:26","indexId":"70157264","displayToPublicDate":"2015-09-16T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape structure affects specialists but not generalists in naturally fragmented grasslands","docAbstract":"Understanding how biotic communities respond to landscape spatial structure is critically important for conservation management as natural landscapes become increasingly fragmented. However, empirical studies of the effects of spatial structure on plant species richness have found inconsistent results, suggesting that more comprehensive approaches are needed. In this study, we asked how landscape structure affects total plant species richness and the richness of a guild of specialized plants in a multivariate context. We sampled herbaceous plant communities at 56 dolomite glades (insular, fire-adapted grasslands) across the Missouri Ozarks, and used structural equation modeling (SEM) to analyze the relative importance of landscape structure, soil resource availability, and fire history for plant communities. We found that landscape spatial structure-defined as the area-weighted proximity of glade habitat surrounding study sites (proximity index)-had a significant effect on total plant species richness, but only after we controlled for environmental covariates. Richness of specialist species, but not generalists, was positively related to landscape spatial structure. Our results highlight that local environmental filters must be considered to understand the influence of landscape structure on communities, and that unique species guilds may respond differently to landscape structure than the community as a whole. These findings suggest that both local environment and landscape context should be considered when developing management strategies for species of conservation concern in fragmented habitats.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Brooklyn, NY","doi":"10.1890/15-0245.1","collaboration":"Jesse E. D. Miller, University of Wisconsin\nEllen I. Damschen, University of Wisconsin\nSusan P. Harrison, University of California - Davis","usgsCitation":"Miller, J., Damschen, E.I., Harrison, S.P., and Grace, J.B., 2015, Landscape structure affects specialists but not generalists in naturally fragmented grasslands: Ecology, v. 96, no. 12, p. 3323-3331, https://doi.org/10.1890/15-0245.1.","productDescription":"9 p.","startPage":"3323","endPage":"3331","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063314","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":308206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"96","issue":"12","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa849ce4b05d6c4e501a25","contributors":{"authors":[{"text":"Miller, Jesse","contributorId":147734,"corporation":false,"usgs":false,"family":"Miller","given":"Jesse","email":"","affiliations":[{"id":16916,"text":"Dept. of Zoology, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":572496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Damschen, Ellen Ingman","contributorId":6177,"corporation":false,"usgs":false,"family":"Damschen","given":"Ellen","email":"","middleInitial":"Ingman","affiliations":[{"id":16916,"text":"Dept. of Zoology, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":572497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harrison, Susan P.","contributorId":147735,"corporation":false,"usgs":false,"family":"Harrison","given":"Susan","email":"","middleInitial":"P.","affiliations":[{"id":16917,"text":"Dept. of Env. Sci. and Policy, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":572498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":572495,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157265,"text":"70157265 - 2015 - Polymorphic mountain whitefish (Prosopium williamsoni) in a coastal riverscape: size class assemblages, distribution, and habitat associations","interactions":[],"lastModifiedDate":"2017-11-22T17:47:24","indexId":"70157265","displayToPublicDate":"2015-09-16T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Polymorphic mountain whitefish (Prosopium williamsoni) in a coastal riverscape: size class assemblages, distribution, and habitat associations","docAbstract":"We compared the assemblage structure, spatial distributions, and habitat associations of mountain whitefish (Prosopium williamsoni) morphotypes and size classes. We hypothesised that morphotypes would have different spatial distributions and would be associated with different habitat features based on feeding behaviour and diet. Spatially continuous sampling was conducted over a broad extent (29 km) in the Calawah River, WA (USA). Whitefish were enumerated via snorkelling in three size classes: small (10–29 cm), medium (30–49 cm), and large (≥50 cm). We identified morphotypes based on head and snout morphology: a pinocchio form that had an elongated snout and a normal form with a blunted snout. Large size classes of both morphotypes were distributed downstream of small and medium size classes, and normal whitefish were distributed downstream of pinocchio whitefish. Ordination of whitefish assemblages with nonmetric multidimensional scaling revealed that normal whitefish size classes were associated with higher gradient and depth, whereas pinocchio whitefish size classes were positively associated with pool area, distance upstream, and depth. Reach-scale generalised additive models indicated that normal whitefish relative density was associated with larger substrate size in downstream reaches (R2 = 0.64), and pinocchio whitefish were associated with greater stream depth in the reaches farther upstream (R2 = 0.87). These results suggest broad-scale spatial segregation (1–10 km), particularly between larger and more phenotypically extreme individuals. These results provide the first perspective on spatial distributions and habitat relationships of polymorphic mountain whitefish.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12163","usgsCitation":"Starr, J.C., and Torgersen, C.E., 2015, Polymorphic mountain whitefish (Prosopium williamsoni) in a coastal riverscape: size class assemblages, distribution, and habitat associations: Ecology of Freshwater Fish, v. 24, no. 4, p. 505-518, https://doi.org/10.1111/eff.12163.","productDescription":"14 p.","startPage":"505","endPage":"518","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055420","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":308205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Calawah River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.43870544433595,\n 47.93566683402829\n ],\n [\n -124.43870544433595,\n 47.98027031431345\n ],\n [\n -124.20318603515624,\n 47.98027031431345\n ],\n [\n -124.20318603515624,\n 47.93566683402829\n ],\n [\n -124.43870544433595,\n 47.93566683402829\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-18","publicationStatus":"PW","scienceBaseUri":"55fa849de4b05d6c4e501a29","contributors":{"authors":[{"text":"Starr, James C. jstarr@usgs.gov","contributorId":5854,"corporation":false,"usgs":true,"family":"Starr","given":"James","email":"jstarr@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":572499,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157267,"text":"70157267 - 2015 - Will a warmer and wetter future cause extinction of native Hawaiian forest birds?","interactions":[],"lastModifiedDate":"2015-09-16T13:41:14","indexId":"70157267","displayToPublicDate":"2015-09-16T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Will a warmer and wetter future cause extinction of native Hawaiian forest birds?","docAbstract":"Isolation of the Hawaiian archipelago produced a highly endemic and unique avifauna. Avian malaria (Plasmodium relictum), an introduced mosquito-borne pathogen, is a primary cause of extinctions and declines of these endemic honeycreepers. Our research assesses how global climate change will affect future malaria risk and native bird populations. We used an epidemiological model to evaluate future bird-mosquito-malaria dynamics in response to alternative climate projections from the Coupled Model Intercomparison Project (CMIP). Climate changes during the second half of the century accelerate malaria transmission and cause a dramatic decline in bird abundance. Different temperature and precipitation patterns produce divergent trajectories where native birds persist with low malaria infection under a warmer and dryer projection (RCP4.5), but suffer high malaria infection and severe reductions under hot and dry (RCP8.5) or warm and wet (A1B) futures. We conclude that future global climate change will cause significant decreases in the abundance and diversity of remaining Hawaiian bird communities. Because these effects appear unlikely before mid-century, natural resource managers have time to implement conservation strategies to protect this unique avifauna from further decimation. Similar climatic drivers for avian and human malaria suggest that mitigation strategies for Hawai'i have broad application to human health.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford, England","doi":"10.1111/gcb.13005","usgsCitation":"Liao, W., Timm, O.E., Zhang, C., Atkinson, C.T., LaPointe, D., and Samuel, M.D., 2015, Will a warmer and wetter future cause extinction of native Hawaiian forest birds?: Global Change Biology, 32 p., https://doi.org/10.1111/gcb.13005.","productDescription":"32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059405","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":308224,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.77392578125,\n 21.881889807629282\n ],\n [\n -159.80712890625,\n 22.553147478403194\n ],\n [\n -158.6865234375,\n 22.451648819126216\n ],\n [\n -154.95117187499997,\n 20.52993312517078\n ],\n [\n -154.46777343749997,\n 19.539084135509334\n ],\n [\n -155.54443359374997,\n 18.70869162255995\n ],\n [\n -156.4892578125,\n 19.145168196205297\n ],\n [\n -156.55517578125,\n 19.973348786110602\n ],\n [\n -157.5,\n 20.858811790867687\n ],\n [\n -158.97216796875,\n 21.51440672003028\n ],\n [\n -159.93896484375,\n 21.6778482933475\n ],\n [\n -160.6201171875,\n 21.35078115067975\n ],\n [\n -160.77392578125,\n 21.881889807629282\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-29","publicationStatus":"PW","scienceBaseUri":"55fa849ee4b05d6c4e501a31","chorus":{"doi":"10.1111/gcb.13005","url":"http://dx.doi.org/10.1111/gcb.13005","publisher":"Wiley-Blackwell","authors":"Liao Wei, Elison Timm Oliver, Zhang Chunxi, Atkinson Carter T., LaPointe Dennis A., Samuel Michael D.","journalName":"Global Change Biology","publicationDate":"6/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Liao, Wei","contributorId":147740,"corporation":false,"usgs":false,"family":"Liao","given":"Wei","email":"","affiliations":[{"id":13018,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":572515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Timm, Oliver Elison","contributorId":147741,"corporation":false,"usgs":false,"family":"Timm","given":"Oliver","email":"","middleInitial":"Elison","affiliations":[],"preferred":false,"id":572516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Chunxi","contributorId":147742,"corporation":false,"usgs":false,"family":"Zhang","given":"Chunxi","email":"","affiliations":[],"preferred":false,"id":572517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atkinson, Carter T. 0000-0002-4232-5335 catkinson@usgs.gov","orcid":"https://orcid.org/0000-0002-4232-5335","contributorId":1124,"corporation":false,"usgs":true,"family":"Atkinson","given":"Carter","email":"catkinson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":572518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LaPointe, Dennis dlapointe@usgs.gov","contributorId":2926,"corporation":false,"usgs":true,"family":"LaPointe","given":"Dennis","email":"dlapointe@usgs.gov","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":572519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":572504,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157256,"text":"70157256 - 2015 - Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities","interactions":[],"lastModifiedDate":"2015-09-16T08:56:53","indexId":"70157256","displayToPublicDate":"2015-09-16T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities","docAbstract":"Accurate estimates of species richness are necessary to test predictions of ecological theory and evaluate biodiversity for conservation purposes. However, species richness is difficult to measure in the field because some species will almost always be overlooked due to their cryptic nature or the observer's failure to perceive their cues. Common measures of species richness that assume consistent observability across species are inviting because they may require only single counts of species at survey sites. Single-visit estimation methods ignore spatial and temporal variation in species detection probabilities related to survey or site conditions that may confound estimates of species richness. We used simulated and empirical data to evaluate the bias and precision of raw species counts, the limiting forms of jackknife and Chao estimators, and multi-species occupancy models when estimating species richness to evaluate whether the choice of estimator can affect inferences about the relationships between environmental conditions and community size under variable detection processes. Four simulated scenarios with realistic and variable detection processes were considered. Results of simulations indicated that (1) raw species counts were always biased low, (2) single-visit jackknife and Chao estimators were significantly biased regardless of detection process, (3) multispecies occupancy models were more precise and generally less biased than the jackknife and Chao estimators, and (4) spatial heterogeneity resulting from the effects of a site covariate on species detection probabilities had significant impacts on the inferred relationships between species richness and a spatially explicit environmental condition. For a real dataset of bird observations in northwestern Alaska, the four estimation methods produced different estimates of local species richness, which severely affected inferences about the effects of shrubs on local avian richness. Overall, our results indicate that neglecting the effects of site covariates on species detection probabilities may lead to significant bias in estimation of species richness, as well as the inferred relationships between community size and environmental covariates.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/14-1248.1","collaboration":"Colleen Handel","usgsCitation":"McNew, L.B., and Handel, C.M., 2015, Evaluating species richness: biased ecological inference results from spatial heterogeneity in species detection probabilities: Ecological Applications, v. 25, no. 6, p. 1669-1680, https://doi.org/10.1890/14-1248.1.","productDescription":"12 p.","startPage":"1669","endPage":"1680","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056170","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":438682,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18WS3","text":"USGS data release","linkHelpText":"Avian Habitat Data; Seward Peninsula, Alaska, 2012"},{"id":438681,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JS9NG2","text":"USGS data release","linkHelpText":"Avian Point Transect Survey, Seward Peninsula, Alaska, 2012"},{"id":308145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55fa8499e4b05d6c4e501a21","contributors":{"authors":[{"text":"McNew, Lance B. lmcnew@usgs.gov","contributorId":5086,"corporation":false,"usgs":true,"family":"McNew","given":"Lance","email":"lmcnew@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":572453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Handel, Colleen M. 0000-0002-0267-7408 cmhandel@usgs.gov","orcid":"https://orcid.org/0000-0002-0267-7408","contributorId":3067,"corporation":false,"usgs":true,"family":"Handel","given":"Colleen","email":"cmhandel@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":572454,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155020,"text":"70155020 - 2015 - Landslides and megathrust splay faults captured by the late Holocene sediment record of eastern Prince William Sound, Alaska","interactions":[],"lastModifiedDate":"2015-10-23T15:48:44","indexId":"70155020","displayToPublicDate":"2015-09-15T16:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Landslides and megathrust splay faults captured by the late Holocene sediment record of eastern Prince William Sound, Alaska","docAbstract":"We present new marine seismic‐reflection profiles and bathymetric maps to characterize Holocene depositional patterns, submarine landslides, and active faults beneath eastern and central Prince William Sound (PWS), Alaska, which is the eastern rupture patch of the 1964 Mw 9.2 earthquake. We show evidence that submarine landslides, many of which are likely earthquake triggered, repeatedly released along the southern margin of Orca Bay in eastern PWS. We document motion on reverse faults during the 1964 Great Alaska earthquake and estimate late Holocene slip rates for these growth faults, which splay from the subduction zone megathrust. Regional bathymetric lineations help define the faults that extend 40–70 km in length, some of which show slip rates as great as 3.75 mm/yr. We infer that faults mapped below eastern PWS connect to faults mapped beneath central PWS and possibly onto the Alaska mainland via an en echelon style of faulting. Moderate (Mw>4) upper‐plate earthquakes since 1964 give rise to the possibility that these faults may rupture independently to potentially generate Mw 7–8 earthquakes, and that these earthquakes could damage local infrastructure from ground shaking. Submarine landslides, regardless of the source of initiation, could generate local tsunamis to produce large run‐ups along nearby shorelines. In a more general sense, the PWS area shows that faults that splay from the underlying plate boundary present proximal, perhaps independent seismic sources within the accretionary prism, creating a broad zone of potential surface rupture that can extend inland 150 km or more from subduction zone trenches.
","language":"English","publisher":"The Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120140273","usgsCitation":"Finn, S., Liberty, L.M., Haeussler, P.J., and Pratt, T.L., 2015, Landslides and megathrust splay faults captured by the late Holocene sediment record of eastern Prince William Sound, Alaska: Bulletin of the Seismological Society of America, v. 105, no. 5, p. 2343-2353, https://doi.org/10.1785/0120140273.","productDescription":"11 p.","startPage":"2343","endPage":"2353","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066872","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":310615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.512939453125,\n 59.147769484619786\n ],\n [\n -149.512939453125,\n 61.454521127671924\n ],\n [\n -144.20654296875,\n 61.454521127671924\n ],\n [\n -144.20654296875,\n 59.147769484619786\n ],\n [\n -149.512939453125,\n 59.147769484619786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-15","publicationStatus":"PW","scienceBaseUri":"562b5a30e4b00162522207d6","contributors":{"authors":[{"text":"Finn, S.P.","contributorId":65438,"corporation":false,"usgs":true,"family":"Finn","given":"S.P.","email":"","affiliations":[],"preferred":false,"id":564676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liberty, Lee M.","contributorId":89631,"corporation":false,"usgs":true,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":564677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":564678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pratt, Thomas L. 0000-0003-3131-3141 tpratt@usgs.gov","orcid":"https://orcid.org/0000-0003-3131-3141","contributorId":3279,"corporation":false,"usgs":true,"family":"Pratt","given":"Thomas","email":"tpratt@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":564679,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160791,"text":"70160791 - 2015 - Quantification of 15 bile acids in lake charr feces by ultra-high performance liquid chromatography–tandem mass spectrometry","interactions":[],"lastModifiedDate":"2015-12-30T15:33:17","indexId":"70160791","displayToPublicDate":"2015-09-15T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2215,"text":"Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Quantification of 15 bile acids in lake charr feces by ultra-high performance liquid chromatography–tandem mass spectrometry","docAbstract":"Many fishes are hypothesized to use bile acids (BAs) as chemical cues, yet quantification of BAs in biological samples and the required methods remain limited. Here, we present an UHPLC–MS/MS method for simultaneous, sensitive, and rapid quantification of 15 BAs, including free, taurine, and glycine conjugated BAs, and application of the method to fecal samples from lake charr (Salvelinus namaycush). The analytes were separated on a C18 column with acetonitrile–water (containing 7.5 mM ammonium acetate and 0.1% formic acid) as mobile phase at a flow rate of 0.25 mL/min for 12 min. BAs were monitored with a negative electrospray triple quadrupole mass spectrometer (Xevo TQ-S™). Calibration curves of 15 BAs were linear over the concentration range of 1.00–5,000 ng/mL. Validation revealed that the method was specific, accurate, and precise. The method was applied to quantitative analysis of feces extract of fry lake charr and the food they were eating. The concentrations of analytes CA, TCDCA, TCA, and CDCA were 242.3, 81.2, 60.7, and 36.2 ng/mg, respectively. However, other taurine conjugated BAs, TUDCA, TDCA, and THDCA, were not detected in feces of lake charr. Interestingly, TCA and TCDCA were detected at high concentrations in food pellets, at 71.9 and 38.2 ng/mg, respectively. Application of the method to feces samples from lake charr supported a role of BAs as chemical cues, and will enhance further investigation of BAs as chemical cues in other fish species.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jchromb.2015.07.028","collaboration":"Li, K.; Buchinger, T.J.; Bussy, U.; Fissette, S.D.; Li W.","usgsCitation":"Li, K., Buchinger, T.J., Bussy, U., Fissette, S.D., Johnson, N., and Li, W., 2015, Quantification of 15 bile acids in lake charr feces by ultra-high performance liquid chromatography–tandem mass spectrometry: Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, v. 1001, p. 27-34, https://doi.org/10.1016/j.jchromb.2015.07.028.","productDescription":"8 p.","startPage":"27","endPage":"34","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066854","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1001","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56850ee6e4b0a04ef4933ab9","contributors":{"authors":[{"text":"Li, Ke","contributorId":94959,"corporation":false,"usgs":true,"family":"Li","given":"Ke","affiliations":[],"preferred":false,"id":583910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buchinger, Tyler J.","contributorId":40508,"corporation":false,"usgs":true,"family":"Buchinger","given":"Tyler","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":583911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bussy, Ugo","contributorId":150993,"corporation":false,"usgs":false,"family":"Bussy","given":"Ugo","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fissette, Skye D.","contributorId":150994,"corporation":false,"usgs":false,"family":"Fissette","given":"Skye","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583909,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583914,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}