The removal of dams has recently increased over historical levels due to aging infrastructure, changing societal needs, and modern safety standards rendering some dams obsolete. Where possibilities for river restoration, or improved safety, exceed the benefits of retaining a dam, removal is more often being considered as a viable option. Yet, as this is a relatively new development in the history of river management, science is just beginning to guide our understanding of the physical and ecological implications of dam removal. Ultimately, the “lessons learned” from previous scientific studies on the outcomes dam removal could inform future scientific understanding of ecosystem outcomes, as well as aid in decision-making by stakeholders. We created a database visualization tool, the Dam Removal Information Portal (DRIP), to display map-based, interactive information about the scientific studies associated with dam removals. Serving both as a bibliographic source as well as a link to other existing databases like the National Hydrography Dataset, the derived National Dam Removal Science Database serves as the foundation for a Web-based application that synthesizes the existing scientific studies associated with dam removals. Thus, using the DRIP application, users can explore information about completed dam removal projects (for example, their location, height, and date removed), as well as discover sources and details of associated of scientific studies. As such, DRIP is intended to be a dynamic collection of scientific information related to dams that have been removed in the United States and elsewhere. This report describes the architecture and concepts of this “metaknowledge” database and the DRIP visualization tool.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161132","usgsCitation":"Duda, J.J., Wieferich, D.J., Bristol, R.S., Bellmore, J.R., Hutchison, V.B., Vittum, K.M., Craig, Laura, and Warrick, J.A., 2016, Dam Removal Information Portal (DRIP)—A map-based resource linking scientific studies and associated geospatial information about dam removals: U.S. Geological Survey Open-File Report 2016-1132, 14 p., https://dx.doi.org/10.3133/ofr20161132.","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076705","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":326867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1132/coverthb.jpg"},{"id":326868,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1132/ofr20161132.pdf","text":"Report","size":"441 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1132"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Information about groundwater-flow paths and locations where groundwater discharges at and near Puget Sound Naval Shipyard is necessary for understanding the potential migration of subsurface contaminants by groundwater at the shipyard. The design of some remediation alternatives would be aided by knowledge of whether groundwater flowing at specific locations beneath the shipyard will eventually discharge directly to Sinclair Inlet of Puget Sound, or if it will discharge to the drainage system of one of the six dry docks located in the shipyard. A 1997 numerical (finite difference) groundwater-flow model of the shipyard and surrounding area was constructed to help evaluate the potential for groundwater discharge to Puget Sound. That steady-state, multilayer numerical model with homogeneous hydraulic characteristics indicated that groundwater flowing beneath nearly all of the shipyard discharges to the dry-dock drainage systems, and only shallow groundwater flowing beneath the western end of the shipyard discharges directly to Sinclair Inlet.
Updated information from a 2016 regional groundwater-flow model constructed for the greater Kitsap Peninsula was used to update the 1997 groundwater model of the Puget Sound Naval Shipyard. That information included a new interpretation of the hydrogeologic units underlying the area, as well as improved recharge estimates. Other updates to the 1997 model included finer discretization of the finite-difference model grid into more layers, rows, and columns, all with reduced dimensions. This updated Puget Sound Naval Shipyard model was calibrated to 2001–2005 measured water levels, and hydraulic characteristics of the model layers representing different hydrogeologic units were estimated with the aid of state-of-the-art parameter optimization techniques.
The flow directions and discharge locations predicted by this updated model generally match the 1997 model despite refinements and other changes. In the updated model, most groundwater discharge recharged within the boundaries of the shipyard is to the dry docks; only at the western end of the shipyard does groundwater discharge directly to Puget Sound. Particle tracking for the existing long-term monitoring well network suggests that only a few wells intercept groundwater that originates as recharge within the shipyard boundary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161135","collaboration":"Prepared in cooperation with the Naval Facilities Engineering Command-Northwest","usgsCitation":"Jones, J.L., Johnson, K.H., and Frans, L.M., 2016, Numerical simulation of groundwater flow at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington: U.S. Geological Survey Open-File Report 2016-1135, 35 p., https://dx.doi.org/10.3133/ofr20161135.","productDescription":"Report:","startPage":"1","endPage":"35","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076467","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":438574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94FCYGV","text":"USGS data release","linkHelpText":"MODFLOW-NWT model to simulate the groundwater flow system at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington"},{"id":326832,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1135/coverthb.jpg"},{"id":326833,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1135/ofr20161135.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1135"}],"country":"United States","state":"Washington","city":"Bremerton","otherGeospatial":"Puget Sound Naval Shipyard, Naval Base Kitsap,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6953125,\n 47.529488341715265\n ],\n [\n -122.67230987548828,\n 47.53899190311993\n ],\n [\n -122.67093658447266,\n 47.54432241518175\n ],\n [\n -122.65960693359374,\n 47.55150616084034\n ],\n [\n -122.6513671875,\n 47.55382328811835\n ],\n [\n -122.63866424560547,\n 47.556603705614094\n ],\n [\n -122.63248443603514,\n 47.5586889219186\n ],\n [\n -122.62390136718749,\n 47.5610057315948\n ],\n [\n -122.62115478515625,\n 47.569808674020344\n ],\n [\n -122.62493133544922,\n 47.575136052077276\n ],\n [\n -122.64038085937499,\n 47.58023129789275\n ],\n [\n -122.64896392822264,\n 47.584168193691696\n ],\n [\n -122.65445709228516,\n 47.58903100916583\n ],\n [\n -122.65926361083984,\n 47.5996813120644\n ],\n [\n -122.66578674316406,\n 47.60384823184624\n ],\n [\n -122.67162322998047,\n 47.604774168947614\n ],\n [\n -122.68054962158202,\n 47.593198777144636\n ],\n [\n -122.68466949462892,\n 47.58301031389572\n ],\n [\n -122.68260955810545,\n 47.5714301073211\n ],\n [\n -122.69359588623047,\n 47.557067094186735\n ],\n [\n -122.70973205566406,\n 47.54663986006874\n ],\n [\n -122.6953125,\n 47.529488341715265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Acoustic technologies have the potential to be used as a surrogate for measuring suspended-sediment concentration (SSC). This potential was examined in a fine-grained (97-100 percent fines) riverine system in central Illinois by way of installation of an acoustic instrument. Acoustic data were collected continuously over the span of 5.5 years. Acoustic parameters were regressed against SSC data to determine the accuracy of using acoustic technology as a surrogate for measuring SSC in a fine-grained riverine system. The resulting regressions for SSC and sediment acoustic parameters had coefficients of determination ranging from 0.75 to 0.97 for various events and configurations. The overall Nash-Sutcliffe model-fit efficiency was 0.95 for the 132 observed and predicted SSC values determined using the sediment acoustic parameter regressions. The study of using acoustic technologies as a surrogate for measuring SSC in fine-grained riverine systems is ongoing. The results at this site are promising in the realm of surrogate technology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161117","collaboration":"Prepared in cooperation with the Illinois Environmental Protection Agency and the Federal Interagency Sedimentation Project","usgsCitation":"Manaster, A.D, Domanski, M.M., Straub, T.D., and Boldt, J.A., 2016, Estimating suspended sediment using acoustics in a fine-grained riverine system on Kickapoo Creek at Bloomington, Illinois: U.S. Geological Survey Open-File Report 2016–1117, 42 p., https://dx.doi.org/10.3133/ofr20161117.","productDescription":"viii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074002","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":326412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1117/coverthb.jpg"},{"id":326413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1117/ofr20161117.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1117"}],"country":"United States","state":"Illinois","city":"Bloomington","otherGeospatial":"Kickapoo Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.02952575683594,\n 40.57432635193039\n ],\n [\n -90.02952575683594,\n 40.875103022165824\n ],\n [\n -89.6978759765625,\n 40.875103022165824\n ],\n [\n -89.6978759765625,\n 40.57432635193039\n ],\n [\n -90.02952575683594,\n 40.57432635193039\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov
Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean.
First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem.
Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing vulnerability. Use of the HCCVI approach comprised “Phase II” of the assessment. This approach uses summaries of GIS data and models to develop a series of numeric indices for components of vulnerability. We incorporated many of the data sources used in Phase I, but added the results of several other data sources, including climate envelope modeling and vegetation dynamics modeling. The results of Phase II were high and low numeric vulnerability ratings for mid-century and the end of century for each ecosystem. The high and low ratings represented the potential range of vulnerability scores owing to uncertainties in future climate conditions and ecosystem effects.
Of the 12 ecosystems assessed in the first approach, five were rated as having high vulnerability (Caribbean Coastal Mangrove, Caribbean Montane Wet Elfin Forest, East Gulf Coastal Plain Southern Loess Bluff Forest, Edwards Plateau Limestone Shrubland, and Nashville Basin Limestone Glade and Woodland). Six ecosystems had medium vulnerability, and one ecosystem had low vulnerability. For the two ecosystems assessed with both approaches, vulnerability ratings generally agreed. The assessment concluded by comparing the two approaches, identifying critical research needs, and making suggestions for future ecosystem vulnerability assessments in the Southeast and beyond. Research needs include reducing uncertainty in the degree of climate exposure likely in the future, as well as acquiring more information on how climate might affect biotic interactions and hydrologic processes. Ideally, a comprehensive vulnerability assessment would include both the narrative summaries that resulted from the synthesis in Phase I, as well as a numeric index that incorporates uncertainty as in Phase II.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161073","usgsCitation":"Costanza, Jennifer, Beck, Scott, Pyne, Milo, Terando, Adam, Rubino, Matthew, White, Rickie, and Collazo, Jaime, 2016, Assessing climate-sensitive ecosystems in the southeastern United States: U.S. Geological Survey Open-File Report 2016–1073, 278 p., https://dx.doi.org/10.3133/ofr20161073.","productDescription":"v, 278 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064978","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":325860,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/fs20163052","text":"Fact Sheet 2016–3052 -","description":"OFR 2016-1073","linkHelpText":"Ecosystem Vulnerability to Climate Change in the Southeastern United States"},{"id":325861,"rank":4,"type":{"id":7,"text":"Companion 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
3916 Sunset Ridge Rd
Raleigh, N.C. 27607
http://nc.water.usgs.gov/
Water from the Little Arkansas River is used as source water for artificial recharge of the Equus Beds aquifer, one of the primary water-supply sources for the city of Wichita, Kansas. The U.S. Geological Survey has operated two continuous real-time water-quality monitoring stations since 1995 on the Little Arkansas River in Kansas. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest. Site-specific regression models were originally published in 2000 for the near Halstead and near Sedgwick U.S. Geological Survey streamgaging stations and the site-specific regression models were then updated in 2003. This report updates those regression models using discrete and continuous data collected during May 1998 through August 2014. In addition to the constituents listed in the 2003 update, new regression models were developed for total organic carbon. The real-time computations of water-quality concentrations and loads are available at http://nrtwq.usgs.gov. The water-quality information in this report is important to the city of Wichita because water-quality information allows for real-time quantification and characterization of chemicals of concern (including chloride), in addition to nutrients, sediment, bacteria, and atrazine transported in the Little Arkansas River. The water-quality information in this report aids in the decision making for water treatment before artificial recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161057","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Rasmussen, P.P., Eslick, P.J., and Ziegler, A.C., 2016, Relations between continuous real-time physical properties and discrete water-quality constituents in the Little Arkansas River, south-central Kansas, 1998-2014: U.S. Geological Survey Open-File Report 2016–1057, 20 p., https://dx.doi.org/10.3133/ofr20161057.","productDescription":"Report: ii, 16 p.; Appendixes 1-2","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073013","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":326275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057.pdf","text":"Report","size":"783 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057"},{"id":326274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1057/coverthb.jpg"},{"id":326280,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057_appendix2.pdf","text":"Appendix 2","size":"2.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057 Appendix 2"},{"id":326276,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057_appendix1.pdf","text":"Appendix 1","size":"2.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057 Appendix 1"}],"country":"United States","state":"Kansas","otherGeospatial":"Little Arkansas River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.2,\n 37.75\n ],\n [\n -98.2,\n 38.6\n ],\n [\n -97.25,\n 38.6\n ],\n [\n -97.25,\n 37.75\n ],\n [\n -98.2,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Dissolved-selenium loading analyses of data collected at 18 water-quality sites in the lower Gunnison River Basin in Colorado were completed through water year (WY) 2014. A WY is defined as October 1–September 30. Selenium is a trace element that bioaccumulates in aquatic food chains and can cause reproductive failure, deformities, and other harmful effects. This report presents information on the dissolved-selenium loads at 18 sites in the lower Gunnison River Basin for WYs 2011–2014. Annual dissolved-selenium loads were calculated at 5 sites with continuous U.S. Geological Survey (USGS) streamflow gages, whereas instantaneous dissolved-selenium loads were calculated for the remaining 13 sites using water-quality samples that had been collected periodically during WYs 2011–2014. Annual dissolved-selenium loads for WY 2014 ranged from 336 pounds (lb) at Uncompahgre River at Colona to 13,300 lb at Gunnison River near Grand Junction (Whitewater). Most sites in the basin had a median instantaneous dissolved-selenium load of less than 20.0 lb per day. In general, dissolved-selenium loads at Gunnison River main-stem sites showed an increase from upstream to downstream.
The State of Colorado water-quality standard for dissolved selenium of 4.6 micrograms per liter (µg/L) was compared to the 85th percentiles for dissolved selenium at selected water-quality sites. Annual 85th percentiles for dissolved selenium were calculated for the five core USGS sites having streamflow gages using estimated dissolved-selenium concentrations from linear regression models. These annual 85th percentiles in WY 2014 ranged from 0.97 µg/L at Uncompahgre River at Colona to 16.7 µg/L at Uncompahgre River at Delta. Uncompahgre River at Delta and Whitewater were the only core sites where water samples exceeded the State of Colorado water-quality standard for dissolved selenium of 4.6 µg/L.
Instantaneous 85th percentiles for dissolved selenium were calculated for sites with sufficient data using water-quality samples collected during WYs 2011–2014. The instantaneous 85th percentiles for samples for WY 2014 ranged from 1.1 µg/L at Uncompahgre River at Colona to 125 µg/L at Loutzenhizer Arroyo at North River Road.
A trend analysis was completed for Whitewater to determine if dissolved-selenium loads are increasing or decreasing. The trend analysis indicates a decrease of 8,000 lb from WY 1986 to WY 2014, a 34.8 percent reduction during the time period, and an additional 6.2 percent reduction from a reported 28.6 percent reduction during WYs 1986–2008. The trend analysis for WY 1992 to WY 2014 indicates a decrease of 5,800 lb per year, or 27.9 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161129","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Henneberg, M.F., 2016, 2014 annual summary of the lower Gunnison River Basin Selenium Management Program water-quality monitoring, Colorado: U.S. Geological Survey Open-File Report 2016–1129, 25 p., https://dx.doi.org/10.3133/ofr20161129. ","productDescription":"iv, 26 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076878","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":326308,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1129/ofr20161129.pdf","text":"Report","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1129"},{"id":326307,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1129/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39935302734375,\n 39.095962936305504\n ],\n [\n -108.270263671875,\n 39.059716474034666\n ],\n [\n -108.160400390625,\n 39.03838632847038\n ],\n [\n -107.99011230468749,\n 39.06824672852526\n ],\n [\n -107.874755859375,\n 39.095962936305504\n ],\n [\n -107.786865234375,\n 39.089567854849314\n ],\n [\n -107.70172119140624,\n 39.0533181067413\n ],\n [\n -107.6055908203125,\n 38.976492485539424\n ],\n [\n -107.6055908203125,\n 38.805470223177466\n ],\n [\n -107.70721435546875,\n 38.62116234642254\n ],\n [\n -107.808837890625,\n 38.43207668538204\n ],\n [\n -107.841796875,\n 38.28131307922969\n ],\n [\n -107.81982421874999,\n 38.048091067457236\n ],\n [\n -107.81982421874999,\n 37.95286091815649\n ],\n [\n -107.92144775390625,\n 37.91820111976663\n ],\n [\n -108.0120849609375,\n 37.91603433975963\n ],\n [\n -108.15216064453125,\n 37.94203148678865\n ],\n [\n -108.26202392578125,\n 38.07404145941957\n ],\n [\n -108.44329833984374,\n 38.47939467327645\n ],\n [\n -108.5723876953125,\n 38.70908932739828\n ],\n [\n -108.6053466796875,\n 38.83542884007303\n ],\n [\n -108.58612060546875,\n 39.04691915968503\n ],\n [\n -108.49822998046875,\n 39.104488809440475\n ],\n [\n -108.39935302734375,\n 39.095962936305504\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225-0046
The Central Platte River Valley provides breeding habitat for a variety of migratory birds, including federally endangered interior least terns (Sternula antillarum; least tern) and threatened piping plovers (Charadrius melodus). Since 2009, researchers have collected demographic data on both species that span their lifecycle (that is, from egg laying through survival of adults). Demographic data were used to estimate vital rates (for example, nest survival, chick survival, and so on) for both species and assess how these vital rates were related to type and age of nesting habitat. Nest survival of both species was unrelated to the age of the site a nest was initiated on. Piping plover chick survival to fledging age was not related to the age of the site it was hatched at, however, the probability of a least tern chick surviving to fledging was higher at older sites. In general there were fewer piping plover nests than least tern nests found at sites created through either the physical construction of a new site or new vegetation management regimes, during 2009–14.
Mean daily least tern nest survival was 0.9742 (95-percent confidence interval [CI]: 0.9692–0.9783) and cumulative nest survival was 0.59 (95-percent CI: 0.53–0.65). Mean daily least tern chick survival was 0.9602 (95-percent CI: 0.9515–0.9673) and cumulative survival to fledging was 0.54 (95-percent CI = 0.48–0.61). Annual apparent survival rates were estimated at 0.42 (95-percent CI = 0.22–0.64) for adult least terns nesting in the Central Platte River Valley and an apparent survival rate of 0.14 (95-pecent CI = 0.04–0.41) for juvenile least terns. The number of least tern nests present at sites created during 2009–14 was associated with the age of the site; more least tern nests were associated with older sites. During 2009–14, there were four (less than 1 percent of all chicks marked) least tern chicks hatched from the Central Platte River Valley that were subsequently captured on nests as adults. Two of these least terns returned to nest at the same site they had hatched from. Ten instances were documented in which an adult least tern could either switch to nest at a new location or remain at the previous location with the onset of a new year. In five (50 percent) of these instances, least terns returned to nest on the site where they had nested in a previous year.
For piping plovers, mean daily apparent nest survival was 0.9880 (95-pecent CI: 0.9836–0.9912) and cumulative nest survival was 0.66 (95-pecent CI: 0.57–0.74). Mean daily piping plover chick survival was 0.9621 (95-pecent CI: 0.9514–0.9706) and cumulative survival to fledging was 0.46 (95-pecent CI = 0.37– 0.56). The annual apparent survival estimate for adult piping plovers nesting in the Central Platte River Valley was 0.76 (95-pecent CI = 0.65–0.85) and was 0.20 (95-pecent CI = 0.14–0.29) for juvenile piping plovers. The number of piping plover nests present at sites created through either the physical construction of a new site or new vegetation management regimes was also associated with site age, with more piping plover nests associated with older sites; however, in general there were fewer piping plover nests found at created sites than least tern nests. Only first-year adult piping plovers were observed on sites in the first year of availability, whereas older sites had a higher proportion of after-first-year adult piping plovers than first-year adult piping plovers. Twelve piping plover chicks (approximately 3 percent of all chicks marked) hatched from the Central Platte River Valley and were subsequently documented on nests as adults. All piping plovers returned to nest on different sites from the one on which they hatched. A total of 45 instances were documented in which an adult plover could either switch to nest at a new location or remain at the previous location with the onset of a new year. In 39 instances (87 percent), the adult nested on the same site as its prior documented nesting attempt and in 6 of these instances the adult switched to a new nesting location between years. There were 13 of 75 uniquely identifiable piping plovers observed to renest (that is, initiate more than one nest in a season) during 2009–14; no renests were observed among uniquely identifiable least terns. In all but one case, piping plover renests were found at the same site as the first nest initiated that season. For birds that renested, the mean initiation date of the first nest was May 6 and the mean initiation date of the second nest was June 8. On average, renests were initiated 7.5 days plus or minus 7.3 (SD [standard deviation]) following the date the initial nesting attempt was ‘fated’ (considered either failed or hatched).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161061","usgsCitation":"Roche, E.A., Sherfy, M.H., Ring, M.M., Shaffer, T.L., Anteau, M.J., and Stucker, J.H., 2016, Demographics and movements of least terns and piping plovers in the Central Platte River Valley, Nebraska: U.S. Geological Survey Open-File Report 2016–1061, 27 p., https://dx.doi.org/10.3133/ofr20161061.","productDescription":"vi, 27 p.","startPage":"1","endPage":"27","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066073","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":326293,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1061/ofr20161061.pdf","text":"Report","size":"2.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1061"},{"id":326292,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1061/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Central Platte River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.69680786132812,\n 40.81588791441588\n ],\n [\n -99.78195190429688,\n 40.66813955408042\n ],\n [\n -99.71466064453125,\n 40.63896734381723\n ],\n [\n -99.60617065429688,\n 40.62437645591559\n ],\n [\n -99.49905395507812,\n 40.622291783092706\n ],\n [\n -99.39743041992188,\n 40.629587853312174\n ],\n [\n -99.36309814453125,\n 40.629587853312174\n ],\n [\n -99.283447265625,\n 40.61186744303007\n ],\n [\n -99.217529296875,\n 40.61082491956405\n ],\n [\n -99.07470703125,\n 40.60456943720527\n ],\n [\n -98.95660400390625,\n 40.606654663050485\n ],\n [\n -98.81927490234375,\n 40.614994915836924\n ],\n [\n -98.75198364257811,\n 40.637925243274374\n ],\n [\n -98.6956787109375,\n 40.65355504328842\n ],\n [\n -98.60641479492188,\n 40.67126439151552\n ],\n [\n -98.51852416992186,\n 40.70042247927178\n ],\n [\n -98.44436645507812,\n 40.713955826286046\n ],\n [\n -98.349609375,\n 40.751418432997454\n ],\n [\n -98.3056640625,\n 40.7743018636372\n ],\n [\n -98.2342529296875,\n 40.831475967182925\n ],\n [\n -98.16146850585938,\n 40.898981853950986\n ],\n [\n -98.09005737304688,\n 40.95915977213492\n ],\n [\n -98.00216674804688,\n 40.99959341455489\n ],\n [\n -97.943115234375,\n 41.036894775104436\n ],\n [\n -98.06121826171875,\n 41.12695250600846\n ],\n [\n -98.09692382812499,\n 41.088667173210624\n ],\n [\n -98.16421508789062,\n 41.05243077390835\n ],\n [\n -98.25759887695312,\n 41.01099329360268\n ],\n [\n -98.34686279296874,\n 40.977824533189526\n ],\n [\n -98.37844848632811,\n 40.95189982816191\n ],\n [\n -98.43475341796875,\n 40.90313381465847\n ],\n [\n -98.4814453125,\n 40.861602479810266\n ],\n [\n -98.54461669921875,\n 40.83667117059108\n ],\n [\n -98.63662719726562,\n 40.80861223601287\n ],\n [\n -98.70529174804686,\n 40.78054143186031\n ],\n [\n -98.75885009765625,\n 40.771181859756496\n ],\n [\n -98.84124755859375,\n 40.758700379161034\n ],\n [\n -98.93600463867188,\n 40.74725696280421\n ],\n [\n -99.01702880859374,\n 40.72956780913899\n ],\n [\n -99.11590576171875,\n 40.73268976628568\n ],\n [\n -99.22027587890624,\n 40.73268976628568\n ],\n [\n -99.32327270507812,\n 40.74309523218185\n ],\n [\n -99.40155029296875,\n 40.75245875985305\n ],\n [\n -99.49081420898438,\n 40.75557964275591\n ],\n [\n -99.62677001953125,\n 40.77846164090355\n ],\n [\n -99.69680786132812,\n 40.81588791441588\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401
The study described in this report represents the first time that a satellite model has been used to identify potential Southwestern Willow Flycatcher (Empidonax traillii extimus) (hereinafter referred to as “flycatcher”) breeding habitat rangewide for 2013–15. Fifty-seven Landsat scenes were required to map the entire range of the flycatcher, encompassing parts of six States and more than 1 billion 30-meter pixels. Predicted flycatcher habitat was summarized in a hierarchical fashion from largest to smallest: regionwide, State, U.S. Fish and Wildlife Service (FWS) management unit, 7.5-minute quadrangle, and critical-habitat reach. The term “predicted habitat” is used throughout this report to distinguish areas the satellite model predicts as suitable flycatcher habitat from what may actually exist on the ground. A rangewide accuracy assessment was done with 758 territories collected in 2014, and change detection was done with yearly habitat maps to identify how and where habitat changed over time. Additionally, effects of tamarisk leaf beetles (Diorhabda spp.) on flycatcher habitat were summarized for the lower Virgin River from 2010 to 2015, and simulations of how tamarisk leaf beetles may affect flycatcher habitat in the lower Colorado and upper Gila Rivers were done for 2015. Model results indicated that the largest areas of predicted flycatcher habitat at elevations below 1,524 meters were in New Mexico and Arizona, areas followed in descending order by California, Texas, Nevada, Utah, and Colorado. By FWS management unit, the largest area of flycatcher habitat during all 3 years were the Middle Rio Grande (New Mexico), followed by the Upper Gila (Arizona and New Mexico) and Middle Gila/San Pedro (Arizona) management units. The area of predicted flycatcher habitat varied considerably in 7.5-minute quadrangles, ranging from 0 to1,398 hectares (ha). Averaged across 3 years, the top three producing quadrangles were Paraje Well (New Mexico), San Marcial (New Mexico), and San Carlos Reservoir (Arizona). The top three FWS critical-habitat reaches in 2015 were Rio Grande-middle (9,544 ha), San Pedro River (1,779 ha), and Gila River-mid San Carlos (1,356 ha); this ranking did not change in 2013 or 2014. Change detection among years showed a large shift in predicted flycatcher habitat influenced by drought patterns, with California habitat decreasing and New Mexico habitat increasing. An accuracy assessment indicated that 88 percent of territories were correctly classified at a 40 percent probability threshold, with an exponential relationship between territory densities and five probability classes. A spatially explicit analysis indicated that beetles decreased predicted flycatcher habitat 94.2 percent from 2010 to 2015 along the lower Virgin River, with only 5.8 percent persisting. In contrast, beetle simulations indicated that 64.1 percent of habitat will persist along the lower Colorado River and 45 percent will persist along the upper Gila River. This project shows that the satellite model adequately predicts flycatcher habitat rangewide, but it lacks the ability to predict which patches will be occupied in a given year. The next logical step is the development of an occupancy model that ties the habitat predictions of the satellite model to patch occupancy so managers can better allocate their resources for survey and restoration activities. Finally, the methods presented in this report seem well suited for automated mapping applications and cloud-based resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161120","usgsCitation":"Hatten, J.R., 2016, A satellite model of Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat and a simulation of potential effects of tamarisk leaf beetles (Diorhabda spp.), Southwestern United States: U.S. Geological Survey Open-File Report 2016–1120, 88 p., https://dx.doi.org/10.3133/ofr20161120.","productDescription":"vi, 88 p.","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074418","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":326223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1120/coverthb.jpg"},{"id":326224,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1120/ofr20161120.pdf","text":"Report","size":"13.6 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U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
The coastal region of California supports a wealth of ecosystem services including habitat provision for wildlife and fisheries. Tidal marshes, mudflats, and shallow bays within coastal estuaries link marine, freshwater and terrestrial habitats, and provide economic and recreational benefits to local communities. Climate change effects such as sea-level rise (SLR) are altering these habitats, but we know little about how these areas will change over the next 50–100 years. Our study examined the projected effects of three recent SLR scenarios produced for the West Coast of North America on tidal marshes in California. We compiled physical and biological data, including coastal topography, tidal inundation, plant composition, and sediment accretion to project how SLR may alter these ecosystems in the future. The goal of our research was to provide results that support coastal management and conservation efforts across California. Under a low SLR scenario, all study sites remained vegetated tidal wetlands, with most sites showing little elevation and vegetation change relative to sea level. At most sites, mid SLR projections led to increases in low marsh habitat at the expense of middle and high marsh habitat. Marshes at Morro Bay and Tijuana River Estuary were the most vulnerable to mid SLR with many areas becoming intertidal mudflat. Under a high SLR scenario, most sites were projected to lose vegetated habitat, eventually converting to intertidal mudflats. Our results suggest that California marshes are vulnerable to major habitat shifts under mid or high rates of SLR, especially in the latter part of the century. Loss of vegetated tidal marshes in California due to SLR is expected to impact ecosystem services that are dependent on coastal wetlands such as wildlife habitat, carbon sequestration, improved water quality, and coastal protection from storms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161125","collaboration":"Prepared in cooperation with the Southwest Climate Science Center","usgsCitation":"Thorne, K.M., MacDonald, G.M., Ambrose, R.F., Buffington, K.J., Freeman, C.M., Janousek, C.N., Brown, L.N., Holmquist, J.R., Guntenspergen, G.R., Powelson, K.W., Barnard, P.L., and Takekawa, J.Y., 2016, Effects of climate change on tidal marshes along a latitudinal gradient in California: U.S. Geological Survey Open-File Report 2016-1125, 75 p., https://dx.doi.org/10.3133/ofr20161125.","productDescription":"Report: viii, 75 p.; Appendixes","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075871","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":326133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1125/coverthb.jpg"},{"id":326134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1125/ofr20161125.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1125 Report PDF"},{"id":326135,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1125/ofr20161125_appendixes.pdf","text":"Appendixes","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1125 Appendixes PDF"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.91455078125,\n 40.94671366508002\n ],\n [\n -122.51953124999999,\n 35.99578538642032\n ],\n [\n -120.52001953124999,\n 33.61461929233378\n ],\n [\n -117.92724609375,\n 32.41706632846282\n ],\n [\n -116.05957031249999,\n 32.657875736955305\n ],\n [\n -118.65234374999999,\n 34.63320791137959\n ],\n [\n -120.65185546875,\n 36.58024660149866\n ],\n [\n -122.98095703125,\n 41.0130657870063\n ],\n [\n -124.91455078125,\n 40.94671366508002\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
In 2014 and 2015, the U.S. Geological Survey (USGS) sampled water wells in the Los Angeles Basin and southern San Joaquin Valley, California, and oil wells in the San Joaquin Valley for analysis of multiple chemical, isotopic, and groundwater-age tracers. The purpose of this reconnaissance sampling was to evaluate the utility of tracers for assessing the effects of oil and gas production activities on groundwater quality in California. The study was done in cooperation with the California State Water Resources Control Board. Results of the study are intended to help design a regional groundwater-monitoring program to be implemented as part of California Senate Bill 4 (SB 4 statutes of 2013). The regional monitoring program plans to assess the effects of oil and gas production activities on groundwater quality and to provide a regional context for local monitoring of the groundwater-quality effects from well-stimulation treatments, which are techniques used to improve oil and gas production by increasing their rate of flow to the well. California SB 4 mandates that this local monitoring is to be done by oil-well operators in accordance with monitoring criteria established by the State Water Board.
\nThis report evaluates the utility of the chemical, isotopic, and groundwater-age tracers for assessing sources of salinity, methane, and petroleum hydrocarbons in groundwater overlying or near several California oil fields. Tracers of dissolved organic carbon in
oil-field-formation water are also discussed. Tracer data for samples collected from 51 water wells and 4 oil wells are examined.
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
Characterizing bathymetric change in coastal environments is an important component in understanding shoreline evolution, especially along barrier island platforms. Bathymetric change is a function of the regional sediment budget, long-term wave and current patterns, and episodic impact from high-energy events such as storms. Human modifications may also cause changes in seafloor elevation. This study, conducted by the U.S. Geological Survey in collaboration with the U.S. Fish and Wildlife Service, evaluates bathymetric and volumetric change and sediment characteristics around Breton Island and Gosier Shoals located offshore of the Mississippi River Delta in Louisiana. This area has been affected by significant storm events such as Hurricane Katrina in 2005. Sedimentation patterns at Breton Island and offshore have also been modified by the excavation of a shipping channel north of the island. Four time periods are considered that encompass these episodes and include long-term change and short-term storm recovery: 1869–2014, 1869–1920, 1920–2014, and 2007–2014. Finally, sediment characteristics are reported in the context of seafloor elevation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161069","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Flocks, J.G., and Terrano, J.F., 2016, Analysis of seafloor change at Breton Island, Gosier Shoals, and surrounding waters, 1869–2014, Breton National Wildlife Refuge, Louisiana: U.S. Geological Survey Open-File Report 2016–1069, 27 p., https://dx.doi.org/10.3133/ofr20161069.","productDescription":"Report: vi, 27 p.; Data Releases","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073884","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324961,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/ds1005","text":"Data Series 1005","description":"OFR 2016-1069","linkHelpText":"Archive of Bathymetry and Backscatter Data Collected in 2014 Nearshore Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana"},{"id":324963,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7XS5SGM","text":"USGS data release - A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for Breton Island, Louisiana: 1869–2014","description":"OFR 2016-1069"},{"id":324960,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.3133/ofr20161039","text":"Open-File Report 2016–1039","description":"OFR 2016-1069","linkHelpText":"Analysis of shoreline and geomorphic change for Breton Island, Louisiana, from 1869 to 2014"},{"id":324962,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F70G3H6G","text":"USGS data release - Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014","description":"OFR 2016-1069"},{"id":324958,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1069/coverthb.jpg"},{"id":324959,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1069/ofr20161069.pdf","text":"Report","size":"7.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1069"}],"country":"United States","state":"Louisana","otherGeospatial":"Breton Island, Breton National Wildlife Refuge, Gosier Shoals","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.07234191894531,\n 29.471883455244765\n ],\n [\n -88.98994445800781,\n 29.538216607905866\n ],\n [\n -89.07096862792969,\n 29.614057949691468\n ],\n [\n -89.31060791015624,\n 29.44438130948883\n ],\n [\n -89.22477722167967,\n 29.361231724636678\n ],\n [\n -89.19525146484375,\n 29.38576493113888\n ],\n [\n -89.14581298828125,\n 29.387559811639232\n ],\n [\n -89.10804748535155,\n 29.352254684201622\n ],\n [\n -89.0826416015625,\n 29.369011186354562\n ],\n [\n -89.07920837402344,\n 29.39952487234379\n ],\n [\n -89.05654907226562,\n 29.4186660412453\n ],\n [\n -89.05517578125,\n 29.44916482692468\n ],\n [\n -89.07234191894531,\n 29.471883455244765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
Boreal soils play an important role in the global carbon cycle owing to the large amount of carbon stored within this northern region. To understand how carbon and nitrogen storage varied among different ecosystems, a vegetation gradient was established in the Bonanza Creek Long Term Ecological Research (LTER) site, located in interior Alaska. The ecosystems represented are a black spruce (Picea mariana)–feather moss (for example, Hylocomium sp.) forest ecosystem, a shrub-dominated ecosystem, a tussock-grass-dominated ecosystem, a sedge-dominated ecosystem, and a rich fen ecosystem. Here, we report the physical, chemical, and descriptive properties for the soil cores collected at these sites. These data have been used to calculate carbon and nitrogen accumulation rates on a long-term (decadal and century) basis (Manies and others, in press).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161034","usgsCitation":"Manies, K.L., Harden, J.W., Fuller, C.C., Xu, Xiaomei, and McGeehin, J.P., 2016, Soil data for a vegetation gradient located at Bonanza Creek Long Term Ecological Research Site, interior Alaska: U.S. Geological Survey Open-File Report 2016–1034, 10 p., https://dx.doi.org/10.3133/ofr20161034.","productDescription":"Report: iv, 10 p.; Data Files","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072809","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":325710,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1034/coverthb.jpg"},{"id":325738,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1034/ofr20161034_appendix.zip","text":"Data Files","size":"120 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1034"},{"id":325737,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1034/ofr20161034.pdf","text":"Report","size":"393 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1034"}],"contact":"Contact Information
Soil Carbon Research - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 962
Menlo Park, CA 94025
http://carbon.wr.usgs.gov/
http://carbon.wr.usgs.gov/people.html
The U.S. Geological Survey anchored a sediment trap in the northern Gulf of Mexico in January 2008 to collect seasonal time-series data on the flux and assemblage composition of live planktic foraminifers. This report provides an update of the previous time-series data to include continuous results from January 2013 through May 2014. Ten taxa constituted ~95 percent of both the 2013 and 2014 assemblages: Globigerinoides ruber (pink and white varieties), Globigerinoides sacculifer, Globigerina calida, Globigerinella aequilateralis, Globorotalia menardii group [The Gt. menardii group includes Gt. menardii, Gt. tumida, and Gt. ungulata], Orbulina universa, Globorotalia truncatulinoides, Pulleniatina spp., and Neogloboquadrina dutertrei. In 2013, the mean daily flux was 177 tests per square meter per day (m−2 day−1), with maximum fluxes of >1,200 tests m−2 day−1 during the middle of February and minimum fluxes of <13 tests m−2 day−1 during the beginning of November. In 2014, the mean daily flux was 189 tests m−2 day−1, with maximum fluxes of >900 tests m−2 day−1 at the end of January and minimum fluxes of <30 tests m−2 day−1 at the beginning of January. Globorotalia truncatulinoides showed a clear preference for the winter, consistent with data from 2008 to 2012. Globigerinoides ruber (white) flux data for 2012 (average 23 tests m−2 day−1) were consistent with data from 2011 (average 30 tests m−2 day−1) and 2010 (average 29 tests m−2 day−1) and showed a steady threefold increase since 2009 (average 11 tests m−2 day−1) and a tenfold increase from the 2008 flux (3 tests m−2 day−1). The flux data from 2013 (average 15 tests m−2 day−1) and 2014 (average 8 tests m−2 day−1) showed decline from the previous 3 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161115","usgsCitation":"Reynolds, C.E., and Richey, J.N., 2016, Seasonal flux and assemblage composition of planktic foraminifera from the northern Gulf of Mexico, 2008–14: U.S. Geological Survey Open-File Report 2016–1115, 14 p., https://dx.doi.org/10.3133/ofr20161115.","productDescription":"Report: iv, 14 p.; Table","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073887","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":325709,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1115/ofr20161115_table1.xls","text":"Planktic Foraminiferal Flux ","size":"264 KB xls","description":"OFR 2016-1115"},{"id":325708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ofr/2016/1115/ofr20161115.pdf","text":"Report","size":"962 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1115"},{"id":325707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1115/coverthb.jpg"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
A detailed inventory of irrigated crop acreage is not available at the level of resolution needed to accurately estimate agricultural water use or to project future water demands in many Florida counties. A detailed digital map and summary of irrigated acreage during the 2015 growing season was developed for 13 of the 15 counties that compose the Suwannee River Water Management District. The irrigated areas were delineated using land-use data, orthoimagery, and information obtained from the water management district consumptive water-use permits that were then field verified between May and November of 2015. Selected attribute data were collected for the irrigated areas, including crop type, primary water source, and type of irrigation system. Results indicate that an estimated 113,134 acres were either irrigated or had potential for irrigation in all or part of the 13 counties within the Suwannee River Water Management District during 2015. This estimate includes 108,870 acres of field-verified, irrigated crops and 4,264 acres of irrigated land observed as (1) idle (with an irrigation system visible but no crop present at the time of the field-verification visit), (2) acres that could not be verified during field visits, or (3) acres that were located on publicly owned research lands.
\nOf the total field-verified crops, 83,721 acres were field crops; 20,962 acres were vegetable crops (sometimes referred to as row crops); 3,089 acres were in tree nurseries, ornamentals, and sod production; and 1,098 acres were fruit crops. Specific irrigated crops included 32,468 acres of corn (primarily for silage); 28,170 acres of peanuts; and 10,331 acres of hay. About 40 percent of the vegetable acreage (8,340 acres) was double cropped (planted with both a spring and a fall crop on the same field). Beans, carrots, and watermelons were the most commonly grown vegetable crops in these 13 counties in 2015.
\nSprinkler irrigation systems including center pivots, portable or traveling guns, and permanent or solid overhead fixtures accounted for nearly 91 percent (102,874 acres) of the total irrigated acreage in the Suwannee River Water Management District, whereas microirrigation systems including drip irrigation accounted for 9 percent (10,260 acres) of the irrigated acreage. A total of 1,466 center pivots were observed during field verification in 2015 and accounted for 93,093 irrigated acres (which represents 82 percent of the total irrigated acreage). Most center pivots were in use at the time of the field verification, although about 3 percent appeared idle. No flood irrigation systems were observed during field verification in 2015. Overall, groundwater was used to irrigate nearly all of the field-verified acreage (99.8 percent). Dairy wastewater effluent was used on many fields during 2015; however, a quantitative estimate of acreage using effluent could not be determined.
\nIrrigated cropland totaled 26,927 acres in Suwannee County; 16,511 acres in Madison County; 14,862 acres in Hamilton County; and 14,155 acres in Gilchrist County; these four counties accounted for nearly two-thirds (64 percent) of the acres irrigated within the Suwannee River Water Management District during 2015. Corn (primarily for silage) and peanuts were the primary irrigated crops, accounting for 48, 70, and 71 percent, respectively, of the total irrigated acreage in Suwannee, Madison, and Gilchrist Counties; vegetables accounted for 52 percent of the total irrigated acres in Hamilton County. Other counties with substantial irrigated acreage included Levy (10,122 acres), Alachua (9,547 acres), and Lafayette (8,110 acres); these three counties, combined with Suwannee, Madison, Hamilton, and Gilchrist Counties, accounted for 88 percent of the irrigated acreage in the Suwannee River Water Management District.
\nThe irrigated acreage that was field verified in 2015 for the 13 counties in the Suwannee River Water Management District (113,134 acres) is about 6 percent higher than the estimated acreage published by the U.S. Department of Agriculture (107,217 acres) for 2012; however, this 2012 value represents acreage for the entire portion of all 13 counties, not just the Suwannee River Water Management District portion. Differences between the 2015 field-verified acreage totals and those published by the U.S. Department of Agriculture for 2012 may occur because (1) irrigated acreage for some specific crops increased or decreased substantially during the 3-year interval due to commodity prices or economic changes, (2) calculated field-verified irrigated acreage may be an overestimate 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 U.S. Department of Agriculture for selected crops may be underestimated in some cases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161111","collaboration":"Prepared in cooperation with the Florida Department of Agriculture and Consumer Services and the Suwannee River Water Management District","usgsCitation":"Marella, R.L., Dixon, J.F., and Berry, D.R., 2016, Agricultural irrigated land-use inventory for the counties in the Suwannee River Water Management District in Florida, 2015: U.S. Geological Survey Open-File Report 2016–1111, 18 p., https://dx.doi.org/10.3133/ofr20161111.","productDescription":"Report: 18 p.; Appendixes: 1-2; Data Release","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-071711","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":438580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NK3C4V","text":"USGS data release","linkHelpText":"Map, Data, and GIS Files Pertaining to the Agricultural Irrigated Land-use Inventory for the Counties in the Suwannee River Water Management District, 2015"},{"id":325761,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1111/ofr20161111_appendix1.pdf","text":"Appendix 1","size":"9.50 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1111 Appendix 1"},{"id":325760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1111/ofr20161111.pdf","text":"Report","size":"1.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1111"},{"id":325762,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1111/ofr20161111_appendix2.xlsx","text":"Appendix 2","size":"216 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016–1111 Appendix 2"},{"id":325763,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7NK3C4V","text":"USGS data release - GIS Data and Tables Pertaining to the Agricultural Irrigated Land-use Inventory for the Counties in the Suwannee River Water Management District, 2015","description":"USGS data release"},{"id":325759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1111/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Suwannee River Water Management District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.0673828125,\n 30.680439786468128\n ],\n [\n -82.3974609375,\n 30.58117925738696\n ],\n [\n -82.3974609375,\n 30.164126343161097\n ],\n [\n -82.0513916015625,\n 30.149877316442065\n ],\n [\n -82.034912109375,\n 29.3965337391284\n ],\n [\n -82.7435302734375,\n 28.96489485992114\n ],\n [\n -83.0621337890625,\n 29.14736383122664\n ],\n [\n -83.408203125,\n 29.53522956294847\n ],\n [\n -83.583984375,\n 29.783449456820605\n ],\n [\n -84.0838623046875,\n 30.102365696412445\n ],\n [\n -84.0673828125,\n 30.680439786468128\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
12703 Research Parkway
Orlando, FL 32826
The microscopic organisms of the Everglades include numerous prokaryotic organisms, including the eubacteria, such as the cyanobacteria and non-photosynthetic bacteria, as well as several eukaryotic algae and protozoa that form the base of the food web. This report is part 1 in a series of reports that describe microscopic organisms encountered during the examination of several hundred samples collected in the southern Everglades. Part 1 describes the cyanobacteria and includes a suite of images and the most current taxonomic treatment of each taxon. The majority of the images are of live organisms, allowing their true color to be represented. A number of potential new species are illustrated; however, corroborating evidence from a genetic analysis of the morphological characteristics is needed to confirm these designations as new species. Part 1 also includes images of eubacteria that resemble cyanobacteria. Additional parts of the report on microscopic organisms of the Everglades are currently underway, such as the green algae and diatoms. The report also serves as the basis for a taxonomic image database that will provide a digital record of the Everglades microscopic flora and fauna. It is anticipated that these images will facilitate current and future ecological studies on the Everglades, such as understanding food-web dynamics, sediment formation and accumulation, the effects of nutrients and flow, and climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161114","usgsCitation":"Rosen, B.H., and Mareš, Jan, Catalog of microscopic organisms of the Everglades, Part 1—The cyanobacteria: U.S. Geological Survey Open-File Report 2016–1114, 108 p., https://dx.doi.org/10.3133/ofr20161114.","productDescription":"Report: x,108 p.","startPage":"1","endPage":"108","numberOfPages":"122","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073349","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":325624,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1114/ofr20161114.pdf","text":"Report","size":"31.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1114"},{"id":325610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1114/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.68359375,\n 25.12539261151203\n ],\n [\n -80.958251953125,\n 25.085598897064777\n ],\n [\n -81.2164306640625,\n 25.199970890386023\n ],\n [\n -81.2274169921875,\n 25.44823489808649\n ],\n [\n -81.375732421875,\n 25.681137335685307\n ],\n [\n -81.7987060546875,\n 25.913585416189797\n ],\n [\n -81.8316650390625,\n 26.091321632191132\n ],\n [\n -81.551513671875,\n 26.254009699865737\n ],\n [\n -81.1614990234375,\n 26.298339726417737\n ],\n [\n -81.0296630859375,\n 26.401710528707707\n ],\n [\n -80.9417724609375,\n 26.519735305660795\n ],\n [\n -80.584716796875,\n 26.45090222367262\n ],\n [\n -80.5023193359375,\n 26.59343927024179\n ],\n [\n -80.4473876953125,\n 26.672004547729433\n ],\n [\n -80.57373046875,\n 26.848578525873275\n ],\n [\n -80.5902099609375,\n 27.103143960595734\n ],\n [\n -80.33203125,\n 27.108033801463115\n ],\n [\n -80.22766113281249,\n 27.103143960595734\n ],\n [\n -80.0518798828125,\n 27.024877476307523\n ],\n [\n -79.9639892578125,\n 26.632728662035912\n ],\n [\n -79.9749755859375,\n 26.170229047478472\n ],\n [\n -80.09033203125,\n 25.750424835909385\n ],\n [\n -80.15625,\n 25.329131707091477\n ],\n [\n -80.68359375,\n 25.12539261151203\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
The Amargosa River Canyon, located in the Mojave Desert of southeastern California, contains the longest perennial reach of the Amargosa River. Because of its diverse flora and fauna, it has been designated as an Area of Critical Environmental Concern and a Wild and Scenic River by the Bureau of Land Management. A survey of fishes conducted in summer 2010 indicated that endemic Amargosa River pupfish (Cyprinodon nevadensis amargosae) and speckled dace (Rhinichthys osculus spp.) were abundant and occurred throughout the Amargosa River Canyon. The 2010 survey reported non-native red swamp crayfish (Procambarus clarkii) and western mosquitofish (Gambusia affinis) captures were significantly higher, whereas pupfish captures were lower, in areas dominated by non-native saltcedar (Tamarix ssp.). Based on the 2010 survey, it was hypothesized that the invasion of saltcedar could result in a decrease in native species. In an effort to maintain and enhance native fish populations, the Bureau of Land Management removed saltcedar from a 1,550 meter reach of stream on the Amargosa River in autumn 2014 and autumn 2015. Prior to the removal of saltcedar, a survey of fishes and crayfish using baited minnow traps was conducted in the treatment reach to serve as a baseline for future comparisons with post-saltcedar removal surveys. During the 2014 survey, 1,073 pupfish and 960 speckled dace were captured within the treatment reach. Catch per unit effort of pupfish and speckled dace in the treatment reach was less in 2014 than in 2010, although differences could be owing to seasonal variation in capture probability. Non-native mosquitofish catch per unit effort decreased from 2010 to 2014; however, the catch per unit effort of crayfish increased from 2010 to 2014. Future monitoring efforts of this reach should be conducted at the same time period to account for potential seasonal fluctuations of abundance and distribution of fishes and crayfish. A more robust study design that accounts for variation in capture probability could be implemented to quantify the effects of habitat modifications on abundance of fishes and crayfish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161112","usgsCitation":"Hereford, M.E., 2016, Relative distribution and abundance of fishes and crayfish in 2010 and 2014 prior to saltcedar (Tamarix ssp.) removal in the Amargosa River Canyon, southeastern California: U.S. Geological Survey Open-File Report 2016–1112, 18 p., https://dx.doi.org/10.3133/ofr20161112.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073284","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":325573,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1112/ofr20161112.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1112 Report PDF"},{"id":325572,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1112/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Amargosa River Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.22719764709473,\n 35.826930045620486\n ],\n [\n -116.22719764709473,\n 35.8405686232225\n ],\n [\n -116.21895790100099,\n 35.8405686232225\n ],\n [\n -116.21895790100099,\n 35.826930045620486\n ],\n [\n -116.22719764709473,\n 35.826930045620486\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Sedimentologic and topographic data from Hurricane Sandy washover deposits were collected from southern Long Beach Island, New Jersey, in order to document changes to the barrier-island beaches, dunes, and coastal wetlands caused by Hurricane Sandy and subsequent storm events. These data will provide a baseline dataset for use in future coastal change descriptive and predictive studies and assessments. The data presented here were collected as part of the U.S. Geological Survey’s Barrier Island and Estuarine Wetland Physical Change Assessment Project (http://coastal.er.usgs.gov/sandy-wetland-assessment/), which aims to assess ecological and societal vulnerability that results from long- and short-term physical changes to barrier islands and coastal wetlands. This report describes data that were collected in April 2015, approximately 2½ years after Hurricane Sandy’s landfall on October 29, 2012. During the field campaign, washover deposits were photographed and described, and sediment cores, sediment samples, and surface-elevation data were collected. Data collected during this study, including sample locations and elevations, core photographs, computed tomography scans, descriptive core logs, sediment grain-size data, and accompanying Federal Geographic Data Committee metadata, are available in the associated U.S. Geological Survey data release (Bishop and others, 2016; http://dx.doi.org/10.5066/F7PK0D7S).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161090","collaboration":"Barrier Island and Estuarine Wetland Physical Change Assessment Project","usgsCitation":"Bishop, J.M., Richmond, B.R., Zaremba, N.J., Lunghino, B.D., and Kane, H.K., 2016, Hurricane Sandy washover deposits on southern Long Beach Island, New Jersey: U.S. Geological Survey Open-File Report 2016–1090, 14 p., https://dx.doi.org/10.3133/ofr20161090.","productDescription":"Report: vi, 21 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073323","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1090/ofr20161090.pdf","text":"Report","size":"5.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1090"},{"id":324813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1090/coverthb.jpg"},{"id":324815,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7PK0D7S","text":"USGS data release - Hurricane Sandy washover deposit data from southern Long Beach Island, New Jersey: Grain-size, elevations, and graphic core logs"}],"country":"United States","state":"New Jersey","otherGeospatial":"Long Beach Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.30912017822266,\n 39.504305605954634\n ],\n [\n -74.3060302734375,\n 39.49874248613119\n ],\n [\n -74.29779052734375,\n 39.49635815560969\n ],\n [\n -74.27684783935547,\n 39.504305605954634\n ],\n [\n -74.26380157470702,\n 39.52072745681898\n ],\n [\n -74.2620849609375,\n 39.526288816558626\n ],\n [\n -74.26654815673828,\n 39.53502719632629\n ],\n [\n -74.2730712890625,\n 39.53449762886045\n ],\n [\n -74.28062438964844,\n 39.526818446639844\n ],\n [\n -74.29847717285156,\n 39.51675478434244\n ],\n [\n -74.30912017822266,\n 39.504305605954634\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, California. This report includes data collected by U.S. Geological Survey (USGS) scientists for the period from January 2015 to December 2015. These data are appended to long-term datasets extending back to 1974, and serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2015, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. In M. petalum, all observed elements showed annual maxima in January–February and minima in April, except for Zn, which was lowest in December. In sediments, annual maxima also occurred in January–February, and minima were measured in June and September. In 2015, metal concentrations in both sediments and clam tissue were among the lowest on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.
\nAnalyses of the benthic community structure at the same mudflat over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2015), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2015. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed an increase in dominance, concurrent with the decrease in Ag and Cu concentrations, and in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 abundance in 2015. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like M. petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2015 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous (live-birth) species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2015 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161118","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Crauder, Jeff, Parchaso, Francis, Stewart, Robin, Turner, Mathew, Hornberger, M.I., and Luoma, S.N., 2016, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015: U.S. Geological Survey Open-File Report 2016–1118, 78 p., https://dx.doi.org/10.3133/ofr20161118.","productDescription":"vii, 78 p.","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076608","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":416191,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416190,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416189,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416188,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416187,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20171135","text":"Open-File Report 2017-1135","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016"},{"id":325514,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1118/coverthb.jpg"},{"id":325515,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1118/ofr20161118.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1118"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14530944824217,\n 37.40452830389465\n ],\n [\n -122.14530944824217,\n 37.52443079581378\n ],\n [\n -121.91871643066406,\n 37.52443079581378\n ],\n [\n -121.91871643066406,\n 37.40452830389465\n ],\n [\n -122.14530944824217,\n 37.40452830389465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
The Florida Keys reef tract (FKRT) is the largest coral-reef ecosystem in the continental United States. The modern FKRT extends for 362 kilometers along the coast of South Florida from Dry Tortugas National Park in the southwest, through the Florida Keys National Marine Sanctuary (FKNMS), to Fowey Rocks reef in Biscayne National Park in the northeast. Most reefs along the FKRT are sheltered by the exposed islands of the Florida Keys; however, large channels are located between the islands of the Middle Keys. These openings allow for tidal transport of water from Florida Bay onto reefs in the area. The characteristics of the water masses coming from Florida Bay, which can experience broad swings in temperature, salinity, nutrients, and turbidity over short periods of time, are generally unfavorable or “inimical” to coral growth and reef development.
Although reef habitats are ubiquitous throughout most of the Upper and Lower Keys, relatively few modern reefs exist in the Middle Keys most likely because of the impacts of inimical waters from Florida Bay. The reefs that are present in the Middle Keys generally are poorly developed compared with reefs elsewhere in the region. For example, Acropora palmata has been the dominant coral on shallow-water reefs in the Caribbean over the last 1.5 million years until populations of the coral declined throughout the region in recent decades. Although A. palmata was historically abundant in the Florida Keys, it was conspicuously absent from reefs in the Middle Keys. Instead, contemporary reefs in the Middle Keys have been dominated by occasional massive (that is, boulder or head) corals and, more often, small, non-reef-building corals.
Holocene reef cores have been collected from many locations along the FKRT; however, despite the potential importance of the history of reefs in the Middle Florida Keys to our understanding of the environmental controls on reef development throughout the FKRT, there are currently no published records of the Holocene history of reefs in the region. The objectives of the present study were to (1) provide general descriptions of unpublished core records from Alligator Reef and (2) collect and describe new Holocene reef cores from two additional locations in the Middle Keys: Sombrero and Tennessee Reefs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161074","usgsCitation":"Toth, L.T., Stathakopoulos, Anastasios, and Kuffner, I.B., 2016, The structure and composition of Holocene coral reefs in the Middle Florida Keys: U.S. Geological Survey Open-File Report 2016–1074, 27 p., https://dx.doi.org/10.3133/ofr20161074.","productDescription":"v, 27 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074381","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":325513,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1074/ofr20161074.pdf","text":"Report","size":"5.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1074"},{"id":325512,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1074/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.32080078125,\n 24.58459276519208\n ],\n [\n -81.32080078125,\n 25.013439812256372\n ],\n [\n -80.43365478515625,\n 25.013439812256372\n ],\n [\n -80.43365478515625,\n 24.58459276519208\n ],\n [\n -81.32080078125,\n 24.58459276519208\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
6000 4th Street South
St. Petersburg, FL 33701
(727) 502-8068
http://coastal.er.usgs.gov/
Walruses are large benthic predators that rest out of water between foraging bouts. Coastal “haulouts” (places where walruses rest) are formed by adult males in summer and sometimes by females and young when sea ice is absent, and are often used repeatedly across seasons and years. Understanding the geography and historical use of haulouts provides a context for conservation efforts. We summarize information on Pacific walrus haulouts from available reports (n =151), interviews with coastal residents and aviators, and personal observations of the authors. We provide this in the form of a georeferenced database that can be queried and displayed with standard geographic information system and database management software. The database contains 150 records of Pacific walrus haulouts, with a summary of basic characteristics on maximum haulout aggregation size, age-sex composition, season of use, and decade of most recent use. Citations to reports are provided in the appendix and as a bibliographic database. Haulouts were distributed across the coasts of the Pacific walrus range; however, the largest (maximum >10,000 walruses) of the haulouts reported in the recent 4 decades (n=19) were concentrated on the Russian shores in regions near the Bering Strait and northward into the western Chukchi Sea (n=17). Haulouts of adult female and young walruses primarily occurred in the Bering Strait region and areas northward, with others occurring in the central Bering Sea, Gulf of Anadyr, and Saint Lawrence Island regions. The Gulf of Anadyr was the only region to contain female and young walrus haulouts, which formed after the northward spring migration and prior to autumn ice formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161108","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and Chukot-TINRO and Institute of Biological Problems of the North Far East Branch of Russian Academy of Sciences","usgsCitation":"Fischbach, A.S., Kochnev, A.A., Garlich-Miller, J.L., and Jay, C.V., 2016, Pacific walrus coastal haulout database, 1852-2016— Background report: U.S. Geological Survey Open-File Report 2016-1108, Report: iv, 27 p.; Data Release, https://doi.org/10.3133/ofr20161108.","productDescription":"Report: iv, 27 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076335","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":325339,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7RX994P","text":"USGS data release","description":"USGS data release","linkHelpText":"Pacific Walrus Coastal Haulout Database, 1852-2016"},{"id":438584,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VD6WK5","text":"USGS data release","linkHelpText":"ArcGIS Mapping Service for Pacific Walrus Coastal Haulouts"},{"id":438583,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RX994P","text":"USGS data release","linkHelpText":"Pacific Walrus Coastal Haulout Database 1852-2016"},{"id":325338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1108/ofr20161108.pdf","text":"Report","size":"1.3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1108 Report PDF"},{"id":325337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1108/coverthb.jpg"}],"country":"Russia, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -203.642578125,\n 50.12057809796008\n ],\n [\n -203.642578125,\n 72.18180355624855\n ],\n [\n -149.765625,\n 72.18180355624855\n ],\n [\n -149.765625,\n 50.12057809796008\n ],\n [\n -203.642578125,\n 50.12057809796008\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
In 2015, the U.S. Geological Survey (USGS) released an updated assessment of undiscovered, technically recoverable shale gas and shale oil resources of the Mississippian Barnett Shale in north-central Texas (Marra and others, 2015). The Barnett Shale was assessed using the standard continuous (unconventional) methodology established by the USGS for two assessment units (AUs): (1) Barnett Continuous Gas AU, and (2) Barnett Mixed Continuous Gas and Oil AU. A third assessment unit, the Western Barnett Continuous Oil AU, was also defined but was not quantitatively assessed because of limited data within the extent of the AU. The purpose of this report is to provide supplemental documentation of the quantitative input parameters applied in the Barnett Shale assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20161097","usgsCitation":"Marra, K.R., Charpentier, R.R., Schenk, C.J., Lewan, M.D., Leathers-Miller, H.M., Klett, T.R., Gaswirth, S.B., Le, P.A., Mercier, T.J., Pitman, J.K., and Tennyson, M.E., 2016, Input-form data for the U.S. Geological Survey assessment of the Mississippian Barnett Shale of the Bend Arch–Fort Worth Basin Province, 2015: U.S. Geological Survey Open-File Report 2016-1097, 31 p., https://dx.doi.org/10.3133/ofr20161097.","productDescription":"iii, 34 p.","startPage":"1","endPage":"31","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073625","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":325066,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1097/ofr20161097.pdf","text":"Report","size":"212 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1097"},{"id":325065,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1097/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Mississippian Barnett Shale","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.6297607421875,\n 33.4039312002347\n ],\n [\n -98.33862304687499,\n 32.10118973232094\n ],\n [\n -97.81677246093749,\n 31.85889704445453\n ],\n [\n -96.932373046875,\n 31.840232667909365\n ],\n [\n -96.12487792968749,\n 32.040676557717454\n ],\n [\n -95.6854248046875,\n 32.7872745269555\n ],\n [\n -95.6854248046875,\n 33.408516828002675\n ],\n [\n -95.97656249999999,\n 33.75174787568194\n ],\n [\n -96.558837890625,\n 33.61461929233378\n ],\n [\n -97.0037841796875,\n 33.578014746143985\n ],\n [\n -97.833251953125,\n 33.68321092658007\n ],\n [\n -98.250732421875,\n 34.07086232376631\n ],\n [\n -98.6187744140625,\n 33.710632271492095\n ],\n [\n -98.6297607421875,\n 33.4039312002347\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS 939
Denver Federal Center
Denver, CO 80225-0046
An ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina is important for the protection and preservation of the State’s water resources. Information concerning the low-flow characteristics of streams is especially important during critical flow periods, such as during the historic droughts that South Carolina has experienced in the past few decades.
In 2008, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, initiated a study to update low-flow statistics at continuous-record streamgaging stations operated by the U.S. Geological Survey in South Carolina. This report presents the low-flow statistics for 28 selected streamgaging stations in the Savannah and Salkehatchie River Basins in South Carolina. The low-flow statistics include daily mean flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance and the annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day mean flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years, depending on the length of record available at the streamgaging station. The low-flow statistics were computed from records available through March 31, 2014.
Low-flow statistics are influenced by length of record, hydrologic regime under which the data were collected, analytical techniques used, and other factors, such as urbanization, diversions, and droughts that may have occurred in the basin. To assess changes in the low-flow statistics from the previously published values, a comparison of the low-flow statistics for the annual minimum 7-day average streamflow with a 10-year recurrence interval (7Q10) from this study was made with the most recently published values. Of the 28 streamgaging stations for which recurrence interval computations were made, 14 streamgaging stations were suitable for comparing to low-flow statistics that were previously published in U.S. Geological Survey reports. These comparisons indicated that seven of the streamgaging stations had values lower than the previous values, two streamgaging stations had values higher than the previous values, and two streamgaging stations had values that were unchanged from previous values. The remaining three stations for which previous 7Q10 values were computed, which are located on the main stem of the Savannah River, were not compared with current estimates because of differences in the way the pre-regulation and regulated flow data were analyzed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161101","collaboration":"Prepared in cooperation with the South Carolina Department of Health and Environmental Control","usgsCitation":"Feaster, T.D., and Guimaraes, W.B., 2016, Low-flow frequency and flow duration of selected South Carolina streams in the Savannah and Salkehatchie River Basins through March 2014 (ver. 1.1, November 2016): U.S. Geological Survey Open-File Report 2016–1101, 62 p., https://dx.doi.org/10.3133/ofr20161101.","productDescription":"vi, 62 p.","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074376","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":325181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1101/ofr20161101.pdf","text":"Report","size":"2.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
In the subtropical and tropical Pacific islands, changing climate is predicted to influence precipitation and freshwater availability, and thus is predicted to impact ecosystems goods and services available to ecosystems and human communities. The small size of high Hawaiian Islands, plus their complex microlandscapes, require downscaling of global climate models to provide future projections of greater skill and spatial resolution. Two different climate modeling approaches (physics-based dynamical downscaling and statistics-based downscaling) have produced dissimilar projections. Because of these disparities, natural resource managers and decision makers have low confidence in using the modeling results and are therefore are unwilling to include climate-related projections in their decisions. In September 2015, the Pacific Islands Climate Science Center (PICSC), the Pacific Islands Climate Change Cooperative (PICCC), and the Pacific Regional Integrated Sciences and Assessments (Pacific RISA) program convened a 2-day facilitated workshop in which the two modeling teams, plus key model users and resource managers, were brought together for a comparison of the two approaches, culminating with a discussion of how to provide predictions that are useable by resource managers. The proceedings, discussions, and outcomes of this Workshop are summarized in this Open-File Report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161102","usgsCitation":"Helweg, D.A., Keener, V., and Burgett, J.M., 2016, Report from the workshop on climate downscaling and its application in high Hawaiian Islands, September 16–17, 2015: U.S. Geological Survey Open-File Report 2016–1102, 25 p., https://dx.doi.org/10.3133/ofr20161102.","productDescription":"Report: ix, 38 p. 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Appendix 6. “Estimating Climate-Change Impacts on Groundwater Recharge for the Island of Maui, Hawaiʻi” by Alan Mair","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1102 Appendix 6"},{"id":325050,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1102/ofr20161102_appendix5_ohye_presentation.pdf","text":"Appendix 5. “The Climate Change Conundrum: A Water Resource Management Perspective” by Lenore Ohye","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1102 Appendix 5"},{"id":325049,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1102/ofr20161102_appendix4_wang_presentation.pdf","text":"Appendix 4. “Dynamical Downscaling” by Yuqing Wang","size":"12.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1102 Appendix 4"},{"id":325048,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1102/ofr20161102_appendix3_timm_presentation.pdf","text":"Appendix 3. “Presentation on Statistical Downscaling” by Oliver Elison Timm","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1102 Appendix 3"},{"id":325047,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1102/ofr20161102_appendix2_risa_resource_matrix.xlsx","text":"Appendix 2. “Island Downscaling Resources Matrix” model descriptions","size":"44 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1102 Appendix 2"},{"id":325046,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1102/ofr20161102_appendix1_keener_survey_results.pdf","text":"Appendix 1. “Review of RISA Survey: Insights Learned Through Using Downscaled Climate Products” by Victoria Keener","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1102 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\"}}]}","contact":"David A. Helweg, Director
Department of the Interior Pacific Islands Climate Science Center
U.S. Geological Survey Climate and Land Use Mission Area
https://www.doi.gov/csc/pacific
High-resolution seismic-reflection and refraction images of the 1906 surface rupture zone of the San Andreas Fault near Woodside, California reveal evidence for one or more additional near-surface (within about 3 meters [m] depth) fault strands within about 25 m of the 1906 surface rupture. The 1906 surface rupture above the groundwater table (vadose zone) has been observed in paleoseismic trenches that coincide with our seismic profile and is seismically characterized by a discrete zone of low P-wave velocities (Vp), low S-wave velocities (Vs), high Vp/Vs ratios, and high Poisson’s ratios. A second near-surface fault strand, located about 17 m to the southwest of the 1906 surface rupture, is inferred by similar seismic anomalies. Between these two near-surface fault strands and below 5 m depth, we observed a near-vertical fault strand characterized by a zone of high Vp, low Vs, high Vp/Vs ratios, and high Poisson’s ratios on refraction tomography images and near-vertical diffractions on seismic-reflection images. This prominent subsurface zone of seismic anomalies is laterally offset from the 1906 surface rupture by about 8 m and likely represents the active main (long-term) strand of the San Andreas Fault at 5 to 10 m depth. Geometries of the near-surface and subsurface (about 5 to 10 m depth) fault zone suggest that the 1906 surface rupture dips southwestward to join the main strand of the San Andreas Fault at about 5 to 10 m below the surface. The 1906 surface rupture forms a prominent groundwater barrier in the upper 3 to 5 m, but our interpreted secondary near-surface fault strand to the southwest forms a weaker barrier, suggesting that there has been less or less-recent near-surface slip on that strand. At about 6 m depth, the main strand of the San Andreas Fault consists of water-saturated blue clay (collected from a hand-augered borehole), which is similar to deeply weathered serpentinite observed within the main strand of the San Andreas Fault at nearby sites. Multiple fault strands in the area of the 1906 surface rupture may account for variations in geologic slip rates calculated from several paleoseismic sites along the Peninsula segment of the San Andreas Fault.t.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161063","usgsCitation":"Rosa, C.M., Catchings, R.D., Rymer, M.J., Grove, Karen, and Goldman, M.R., 2016, Structure of the 1906 near-surface rupture zone of the San Andreas Fault, San Francisco Peninsula segment, near Woodside, California: U.S. Geological Survey Open-File Report 2016–1063, 31 p., https://dx.doi.org/10.3133/ofr20161063.","productDescription":"iv, 31 p.","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069256","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":320781,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1063/ofr20161063.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1063 Report PDF"},{"id":320780,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1063/coverthb.jpg"}],"country":"United States","state":"California","city":"Woodside","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4041748046875,\n 37.28716518793855\n ],\n [\n -122.4041748046875,\n 37.67077737288316\n ],\n [\n -122.12677001953124,\n 37.67077737288316\n ],\n [\n -122.12677001953124,\n 37.28716518793855\n ],\n [\n -122.4041748046875,\n 37.28716518793855\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center—Menlo Park, Calif. Office
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Current and future breeding ranges of 15 bird and 16 reptile species were modeled in the Southwestern United States. Rather than taking a broad-scale, vulnerability-assessment approach, we created a species distribution model (SDM) for each focal species incorporating climatic, landscape, and plant variables. Baseline climate (1940–2009) was characterized with Parameter-elevation Regressions on Independent Slopes Model (PRISM) data and future climate with global-circulation-model data under an A1B emission scenario. Climatic variables included monthly and seasonal temperature and precipitation; landscape variables included terrain ruggedness, soil type, and insolation; and plant variables included trees and shrubs commonly associated with a focal species. Not all species-distribution models contained a plant, but if they did, we included a built-in annual migration rate for more accurate plant-range projections in 2039 or 2099. We conducted a group meta-analysis to (1) determine how influential each variable class was when averaged across all species distribution models (birds or reptiles), and (2) identify the correlation among contemporary (2009) habitat fragmentation and biological attributes and future range projections (2039 or 2099). Projected changes in bird and reptile ranges varied widely among species, with one-third of the ranges predicted to expand and two-thirds predicted to contract. A group meta-analysis indicated that climatic variables were the most influential variable class when averaged across all models for both groups, followed by landscape and plant variables (birds), or plant and landscape variables (reptiles), respectively. The second part of the meta-analysis indicated that numerous contemporary habitat-fragmentation (for example, patch isolation) and biological-attribute (for example, clutch size, longevity) variables were significantly correlated with the magnitude of projected range changes for birds and reptiles. Patch isolation was a significant trans-specific driver of projected bird and reptile ranges, suggesting that strategic actions should focus on restoration and enhancement of habitat at local and regional scales to promote landscape connectivity and conservation of core areas.
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U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/