The city of Sioux Falls is the fastest growing community in South Dakota. In response to this continued growth and planning for future development, Sioux Falls requires a sustainable supply of municipal water. Planning and managing sustainable groundwater supplies requires a thorough understanding of local groundwater resources. The Big Sioux aquifer consists of glacial outwash sands and gravels and is hydraulically connected to the Big Sioux River, which provided about 90 percent of the city’s source-water production in 2015. Managing sustainable groundwater supplies also requires an understanding of groundwater availability. An effective mechanism to inform water management decisions is the development and utilization of a groundwater-flow model. A groundwater-flow model provides a quantitative framework for synthesizing field information and conceptualizing hydrogeologic processes. These groundwater-flow models can support decision making processes by mapping and characterizing the aquifer. Accordingly, the city of Sioux Falls partnered with the U.S. Geological Survey to construct a groundwater-flow model. Model inputs will include data from advanced geophysical techniques, specifically airborne electromagnetic methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163075","collaboration":"Prepared in cooperation with the City of Sioux Falls","usgsCitation":"Valder, J.F., Delzer, G.C., Carter, J.M., Smith, B.D., and Smith, D.V., 2016, Construction of a groundwater-flow model for the Big Sioux aquifer using airborne electromagnetic methods, Sioux Falls, South Dakota: U.S. Geological Survey Fact Sheet 2016–3075, 4 p., https://dx.doi.org/10.3133/fs20163075.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-079092","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":328947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3075/fs20163075.pdf","text":"Fact Sheet","size":"4.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3075"},{"id":328946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3075/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Sioux Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.79023742675781,\n 43.56098868633536\n ],\n [\n -96.79023742675781,\n 43.823133635349556\n ],\n [\n -96.69136047363281,\n 43.823133635349556\n ],\n [\n -96.69136047363281,\n 43.56098868633536\n ],\n [\n -96.79023742675781,\n 43.56098868633536\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
Potential sources of analytical bias and error associated with laboratory analyses for selected trace elements where concentrations were greater in filtered samples than in paired unfiltered samples were evaluated by U.S. Geological Survey (USGS) Water Quality Specialists in collaboration with the USGS National Water Quality Laboratory (NWQL) and the Branch of Quality Systems (BQS).
Causes for trace-element concentrations in filtered samples to exceed those in associated unfiltered samples have been attributed to variability in analytical measurements, analytical bias, sample contamination either in the field or laboratory, and (or) sample-matrix chemistry. These issues have not only been attributed to data generated by the USGS NWQL but have been observed in data generated by other laboratories. This study continues the evaluation of potential analytical bias and error resulting from matrix chemistry and instrument variability by evaluating the performance of seven selected trace elements in paired filtered and unfiltered surface-water and groundwater samples collected from 23 sampling sites of varying chemistries from six States, matrix spike recoveries, and standard reference materials.
Filtered and unfiltered samples have been routinely analyzed on separate inductively coupled plasma-mass spectrometry instruments. Unfiltered samples are treated with hydrochloric acid (HCl) during an in-bottle digestion procedure; filtered samples are not routinely treated with HCl as part of the laboratory analytical procedure. To evaluate the influence of HCl on different sample matrices, an aliquot of the filtered samples was treated with HCl. The addition of HCl did little to differentiate the analytical results between filtered samples treated with HCl from those samples left untreated; however, there was a small, but noticeable, decrease in the number of instances where a particular trace-element concentration was greater in a filtered sample than in the associated unfiltered sample for all trace elements except selenium. Accounting for the small dilution effect (2 percent) from the addition of HCl, as required for the in-bottle digestion procedure for unfiltered samples, may be one step toward decreasing the number of instances where trace-element concentrations are greater in filtered samples than in paired unfiltered samples.
The laboratory analyses of arsenic, cadmium, lead, and zinc did not appear to be influenced by instrument biases. These trace elements showed similar results on both instruments used to analyze filtered and unfiltered samples. The results for aluminum and molybdenum tended to be higher on the instrument designated to analyze unfiltered samples; the results for selenium tended to be lower. The matrices used to prepare calibration standards were different for the two instruments. The instrument designated for the analysis of unfiltered samples was calibrated using standards prepared in a nitric:hydrochloric acid (HNO3:HCl) matrix. The instrument designated for the analysis of filtered samples was calibrated using standards prepared in a matrix acidified only with HNO3. Matrix chemistry may have influenced the responses of aluminum, molybdenum, and selenium on the two instruments. The best analytical practice is to calibrate instruments using calibration standards prepared in matrices that reasonably match those of the samples being analyzed.
Filtered and unfiltered samples were spiked over a range of trace-element concentrations from less than 1 to 58 times ambient concentrations. The greater the magnitude of the trace-element spike concentration relative to the ambient concentration, the greater the likelihood spike recoveries will be within data control guidelines (80–120 percent). Greater variability in spike recoveries occurred when trace elements were spiked at concentrations less than 10 times the ambient concentration. Spike recoveries that were considerably lower than 90 percent often were associated with spiked concentrations substantially lower than what was present in the ambient sample. Because the main purpose of spiking natural water samples with known quantities of a particular analyte is to assess possible matrix effects on analytical results, the results of this study stress the importance of spiking samples at concentrations that are reasonably close to what is expected but sufficiently high to exceed analytical variability. Generally, differences in spike recovery results between paired filtered and unfiltered samples were minimal when samples were analyzed on the same instrument.
Analytical results for trace-element concentrations in ambient filtered and unfiltered samples greater than 10 and 40 μg/L, respectively, were within the data-quality objective for precision of ±25 percent. Ambient trace-element concentrations in filtered samples greater than the long-term method detection limits but less than 10 μg/L failed to meet the data-quality objective for precision for at least one trace element in about 54 percent of the samples. Similarly, trace-element concentrations in unfiltered samples greater than the long-term method detection limits but less than 40 μg/L failed to meet this data-quality objective for at least one trace-element analysis in about 58 percent of the samples. Although, aluminum and zinc were particularly problematic, limited re-analyses of filtered and unfiltered samples appeared to improve otherwise failed analytical precision.
The evaluation of analytical bias using standard reference materials indicate a slight low bias for results for arsenic, cadmium, selenium, and zinc. Aluminum and molybdenum show signs of high bias. There was no observed bias, as determined using the standard reference materials, during the analysis of lead.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165135","usgsCitation":"Paul, A.P., Garbarino, J.R., Olsen, L.D., Rosen, M.R., Mebane, C.A., and Struzeski, T.M., 2016, Potential sources of analytical bias and error in selected trace-element data quality analyses: U.S. Geological Survey Scientific Investigations Report 2016–5135, 58 p., https://dx.doi.org/10.3133/sir20165135.","productDescription":"vi, 58 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-074836","costCenters":[{"id":5066,"text":"Office of the Director USGS","active":true,"usgs":true}],"links":[{"id":329081,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5135/sir20165135.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5138"},{"id":329080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5135/coverthb.jpg"}],"contact":"Chief, Water Science Field Team
U.S. Geological Survey
520 North Park Avenue
Tucson, Arizona 85721
http://az.water.usgs.gov/
Assessments of streamflow (discharge) parameters, water quality, physical habitat, and biological communities were completed between May and September 2014 as part of a monitoring program in the Big Wood River watershed of south-central Idaho. The sampling was conducted by the U.S. Geological Survey in cooperation with Blaine County, Trout Unlimited, the Nature Conservancy, and the Wood River Land Trust to help identify the status of aquatic resources at selected locations in the watershed. Information in this report provides a basis with which to evaluate and monitor the long-term health of the Big Wood River and its major tributaries. Sampling sites were co-located with existing U.S. Geological Survey streamgaging stations: three on the main stem Big Wood River and four on the North Fork Big Wood River (North Fork), Warm Springs Creek (Warm Sp), Trail Creek (Trail Ck), and East Fork Big Wood River (East Fork) tributaries.
The analytical results and quality-assurance information for water quality, physical habitat, and biological community samples collected at study sites during 2 weeks in September 2014 are summarized. Water-quality data include concentrations of major nutrients, suspended sediment, dissolved oxygen, and fecal-coliform bacteria. To assess the potential effects of nutrient enrichment on algal growth, concentrations of periphyton biomass (chlorophyll-a and ash free dry weight) in riffle habitats were determined at each site. Physical habitat parameters include stream channel morphology, habitat volume, instream structure, substrate composition, and riparian vegetative cover. Biological data include taxa richness, abundance, and stream-health indicator metrics for macroinvertebrate and fish communities. Statistical summaries of the water-quality, habitat, and biological data are provided along with discussion of how these findings relate to the health of aquatic resources in the Big Wood River watershed.
Seasonal discharge patterns using statistical summaries of daily discharge from selected sites are reported for water years 2012–15. Results showed that annual average daily mean discharge increased from the Big Wood River near Ketchum, ID (BW Ketchum) downstream to the Big Wood River at Hailey, ID (BW Hailey), but decreased by nearly 50 percent from BW Hailey downstream to Big Wood River at Stanton Crossing near Bellevue, ID (BW Stanton). Annual variability in daily mean discharge among main-stem sites was highest at BW Stanton, suggesting that this part of the river may be subject to some level of flow alteration.
Hydrologic alterations resulting in flow reduction can contribute to higher water temperature, especially during the summer months when conditions are often most stressful to fish and other stream organisms. Daily water temperature and water temperature trends from June to September 2014 are reported for select tributary and main-stem sites on the Big Wood River and can be used to assess the potential for biological impairment based on aquatic life temperature criteria for cold-water streams. The State of Idaho maximum temperature criteria for protection of cold-water aquatic life of 22 °C was exceeded at Warm Sp and BW Stanton during summer 2014, but at none of the other main-stem or tributary sites. The 13 °C critical temperature criterion for salmonid spawning was exceeded in early July 2014 at BW Ketchum and BW Hailey near the end of the rainbow trout critical spawning and rearing period. Temperature exceedances were most frequent at BW Stanton, where exceedances for rainbow trout and brown trout occurred from May through early July 2014 during most of the critical spawning and rearing period.
Water quality and habitat availability did not seem to be limiting for fish or other aquatic organisms at most sites in the Big Wood River watershed. Water quality assessments in September 2014 determined no exceedances of total maximum daily load target levels. The availability and quality of habitat was limited at BW Stanton, where shallow-water habitat conditions prevailed.
Macroinvertebrate community diversity was high at all sites except for BW Stanton, where low community diversity was attributed to low species richness and high abundances of a few tolerant taxa. Presence of low species diversity and high macroinvertebrate tolerance values at BW Stanton indicates that benthic community condition and stream health were reduced at that location.
Fish surveys done in September 2014 did not indicate any significant reductions in native fish communities in the Big Wood River or its tributaries. Native rainbow trout (Oncorhynchus mykiss) and Wood River sculpin (Cottus leiopomus) were the dominant fish species in the drainage and were found at all tributary and main-stem sites. Non-native brown (Salmo trutta) and brook trout (Salvelinus fontinalis) were limited to lower drainage sites on the Big Wood River (BW Hailey and BW Stanton), and occurred in relatively low numbers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165128","collaboration":"Prepared in cooperation with Blaine County, Trout Unlimited, The Nature Conservancy, and the Wood River Land Trust","usgsCitation":"MacCoy, D.E., and Short, T.M., 2016, Aquatic biological communities and associated habitats at selected sites in the Big Wood River watershed, south-central Idaho, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5128, 37 p., https://dx.doi.org/10.3133/sir20165128.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-061251","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":329075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5128/sir20165128.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5128"},{"id":329074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5128/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Wood River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.58465576171875,\n 43.2622061978402\n ],\n [\n -114.58465576171875,\n 43.81471121600004\n ],\n [\n -114.01473999023438,\n 43.81471121600004\n ],\n [\n -114.01473999023438,\n 43.2622061978402\n ],\n [\n -114.58465576171875,\n 43.2622061978402\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Warm Mineral Springs, located in southern Sarasota County, Florida, is a warm, highly mineralized, inland spring. Since 1946, a bathing spa has been in operation at the spring, attracting vacationers and health enthusiasts. During the winter months, the warm water attracts manatees to the adjoining spring run and provides vital habitat for these mammals. Well-preserved late Pleistocene to early Holocene-age human and animal bones, artifacts, and plant remains have been found in and around the spring, and indicate the surrounding sinkhole formed more than 12,000 years ago. The spring is a multiuse resource of hydrologic importance, ecological and archeological significance, and economic value to the community.
The pool of Warm Mineral Springs has a circular shape that reflects its origin as a sinkhole. The pool measures about 240 feet in diameter at the surface and has a maximum depth of about 205 feet. The sinkhole developed in the sand, clay, and dolostone of the Arcadia Formation of the Miocene-age to Oligocene-age Hawthorn Group. Underlying the Hawthorn Group are Oligocene-age to Eocene-age limestones and dolostones, including the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. Mineralized groundwater, under artesian pressure in the underlying aquifers, fills the remnant sink, and the overflow discharges into Warm Mineral Springs Creek, to Salt Creek, and subsequently into the Myakka River. Aquifers described in the vicinity of Warm Mineral Springs include the surficial aquifer system, the intermediate aquifer system within the Hawthorn Group, and the Upper Floridan aquifer in the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. The Hawthorn Group acts as an upper confining unit of the Upper Floridan aquifer.
Groundwater flow paths are inferred from the configuration of the potentiometric surface of the Upper Floridan aquifer for September 2010. Groundwater flow models indicate the downward flow of water into the Upper Floridan aquifer in inland areas, and upward flow toward the surface in coastal areas, such as at Warm Mineral Springs. Warm Mineral Springs is located in a discharge area. Changes in water use in the region have affected the potentiometric surface of the Upper Floridan aquifer. Historical increase in groundwater withdrawals resulted in a 10- to 20-foot regional decline in the potentiometric surface of the Upper Floridan aquifer by May 1975 relative to predevelopment levels and remained at approximately that level in May 2007 in the area of Warm Mineral Springs. Discharge measurements at Warm Mineral Springs (1942–2014) decreased from about 11–12 cubic feet per second in the 1940s to about 6–9 cubic feet per second in the 1970s and remained at about that level for the remainder of the period of record. Similarity of changes in regional water use and discharge at Warm Mineral Springs indicates that basin-scale changes to the groundwater system have affected discharge at Warm Mineral Springs. Water temperature had no significant trend in temperature over the period of record, 1943–2015, and outliers were identified in the data that might indicate inconsistencies in measurement methods or locations.
Within the regional groundwater basin, Warm Mineral Springs is influenced by deep Upper Floridan aquifer flow paths that discharge toward the coast. Associated with these flow paths, the groundwater temperatures increase with depth and toward the coast. Multiple lines of evidence indicate that a source of warm groundwater to Warm Mineral Springs is likely the permeable zone of the Avon Park Formation within the Upper Floridan aquifer at a depth of about 1,400 to 1,600 feet, or deeper sources. The permeable zone contains saline groundwater with water temperatures of at least 95 degrees Fahrenheit.
The water quality of Warm Mineral Springs, when compared with other springs in Florida had the highest temperature and the greatest mineralized content. Warm Mineral Springs water is characterized by a slight-green color, with varying water clarity, low dissolved oxygen (indicative of deep groundwater), and a hydrogen sulfide odor. Water-quality samples detected ammonium-nitrogen and nitrates, but at low concentrations. The drinking water standard for nitrate adopted by the U.S. Environmental Protection Agency is 10 milligrams per liter, measured as nitrogen. Water samples collected at spring vents by divers on April 29, 2015, had concentrations of 0.9 milligram per liter nitrate-nitrogen at vent A and 0.04–0.05 milligram per liter at vents B, C, and D. Typically, the water clarity is highest in the morning (about 30 feet Secchi depth) and often decreases throughout the day.
Analysis of existing data provided some insight into the hydrologic processes affecting Warm Mineral Springs; however, data have been sparsely and discontinuously collected since the 1940s. Continuous monitoring of hydrologic characteristics such as discharge, water temperature, specific conductance, and water-quality indicators, such as nitrate and turbidity (water clarity), would be valuable for monitoring and development of models of spring discharge and water quality. In addition, water samples could be analyzed for isotopic tracers, such as strontium, and the results used to identify and quantify the sources of groundwater that discharge at Warm Mineral Springs. Groundwater flow/transport models could be used to evaluate the sensitivity of the quality and quantity of water flowing from Warm Mineral Springs to changes in climate, aquifer levels, and water use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161166","collaboration":"Prepared in cooperation with the City of North Port and Sarasota County ","usgsCitation":"Metz, P.A., 2016, Discharge, water temperature, and water quality of Warm Mineral Springs, Sarasota County, Florida: A retrospective analysis: U.S. Geological Survey Open-File Report 2016–1166, 31 p., https://dx.doi.org/10.3133/ofr20161166.","productDescription":"vi, 31 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-066216","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":328877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1166/coverthb2.jpg"},{"id":328878,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1166/ofr20161166.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1166"}],"country":"United States","state":"Florida","county":"Sarasota County","otherGeospatial":"Warm Mineral Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.26177334785461,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.058867814427533\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
(813) 498-5000
Or visit the Caribbean-Florida Water Science Center Web page at
http://fl.water.usgs.gov
Resource nationalism encompasses a broad range of political and economic actions taken by Governments to regulate the extraction of natural resources within their borders. Policies such as increased tariffs or export restrictions can have far-reaching economic effects on international trade. As the Governments of several developing countries consider enacting nationalistic policies, an examination of the 2014 mineral export ban in Indonesia provides an instructive example of the possible impacts of resource nationalism. Significant changes in the production and trade of unprocessed (that is, ores and concentrates) and processed (that is, refined metal) aluminum, copper, and nickel before and after the export ban form the basis of this study.
The U.S. Geological Survey (USGS) National Minerals Information Center (NMIC) tracks production and trade of mineral commodities between producer and consumer countries. Materials flow studies clarify the effects of an export ban on different mineral commodities by assessing changes in production, processing capacity, and trade. Using extensive data collection and monitoring procedures, the USGS NMIC investigated the effects of resource nationalism on the flow of mineral commodities from Indonesia to the global economy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163072","usgsCitation":"Lederer, G.W., 2016, Resource nationalism in Indonesia—Effects of the 2014 mineral export ban: U.S. Geological Survey Fact Sheet 2016-3072, 6 p., https://dx.doi.org/10.3133/fs20163072.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077240","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":328797,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3072/fs20163072.pdf","text":"Report","size":"302 KB","description":"FS 2016-3072"},{"id":328796,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3072/coverthb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 94.921875,\n 5.528510525692801\n ],\n [\n 95.361328125,\n 2.28455066023697\n ],\n [\n 98.96484375,\n -3.074695072369682\n ],\n [\n 103.271484375,\n -7.623886853120036\n ],\n [\n 106.69921875,\n -8.928487062665504\n ],\n [\n 111.09374999999999,\n -9.709057068618208\n ],\n [\n 114.697265625,\n -10.574222078332806\n ],\n [\n 117.861328125,\n -10.833305983642491\n ],\n [\n 122.16796875,\n -11.60919340793894\n ],\n [\n 124.71679687499999,\n -11.264612212504428\n ],\n [\n 127.17773437499999,\n -10.487811882056683\n ],\n [\n 132.099609375,\n -8.667918002363107\n ],\n [\n 134.560546875,\n -8.320212289522944\n ],\n [\n 135.791015625,\n -6.577303118123875\n ],\n [\n 133.9453125,\n -4.477856485570586\n ],\n [\n 132.71484375,\n -5.615985819155327\n ],\n [\n 130.869140625,\n -6.926426847059551\n ],\n [\n 127.705078125,\n -6.664607562172573\n ],\n [\n 123.74999999999999,\n -7.449624260197804\n ],\n [\n 122.607421875,\n -7.972197714386866\n ],\n [\n 121.55273437499999,\n -7.972197714386866\n ],\n [\n 119.70703125,\n -8.059229627200192\n ],\n [\n 118.38867187500001,\n -7.885147283424331\n ],\n [\n 117.42187500000001,\n -7.885147283424331\n ],\n [\n 115.04882812499999,\n -8.146242825034385\n ],\n [\n 114.43359375,\n -7.449624260197804\n ],\n [\n 114.521484375,\n -6.839169626342808\n ],\n [\n 113.203125,\n -6.839169626342808\n ],\n [\n 112.67578124999999,\n -6.664607562172573\n ],\n [\n 112.06054687499999,\n -6.664607562172573\n ],\n [\n 110.74218749999999,\n -6.577303118123875\n ],\n [\n 108.19335937499999,\n -5.703447982149503\n ],\n [\n 107.138671875,\n -5.353521355337321\n ],\n [\n 106.69921875,\n -5.0909441750333855\n ],\n [\n 106.875,\n -3.425691524418062\n ],\n [\n 108.896484375,\n -2.811371193331128\n ],\n [\n 107.666015625,\n -2.1967272417616583\n ],\n [\n 106.34765625,\n -1.4061088354351594\n ],\n [\n 103.974609375,\n -0.5273363048115043\n ],\n [\n 102.568359375,\n 1.2303741774326145\n ],\n [\n 101.689453125,\n 2.0210651187669897\n ],\n [\n 99.755859375,\n 3.6888551431470478\n ],\n [\n 97.998046875,\n 5.353521355337334\n ],\n [\n 94.921875,\n 5.528510525692801\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 109.64355468749999,\n 1.845383988573187\n ],\n [\n 109.423828125,\n 2.064982495867117\n ],\n [\n 109.0283203125,\n 1.625758360412755\n ],\n [\n 108.80859375,\n 1.1864386394452024\n ],\n [\n 108.80859375,\n 0.4833927027896987\n ],\n [\n 108.896484375,\n -0.04394530819134536\n ],\n [\n 109.0283203125,\n -0.6591651462894504\n ],\n [\n 109.3798828125,\n -0.9667509997666298\n ],\n [\n 109.5556640625,\n -1.2743089918452106\n ],\n [\n 109.951171875,\n -1.625758360412755\n ],\n [\n 110.0390625,\n -2.108898659243126\n ],\n [\n 110.21484375,\n -2.5479878714713835\n ],\n [\n 110.5224609375,\n -2.986927393334863\n ],\n [\n 111.09374999999999,\n -3.118576216781991\n ],\n [\n 111.533203125,\n -3.118576216781991\n ],\n [\n 112.1044921875,\n -3.6449998008920375\n ],\n [\n 112.3681640625,\n -3.6449998008920375\n ],\n [\n 112.763671875,\n -3.513421045640032\n ],\n [\n 113.115234375,\n -3.2940822283128046\n ],\n [\n 113.466796875,\n -3.425691524418062\n ],\n [\n 113.90625,\n -3.5572827265412794\n ],\n [\n 114.43359375,\n -3.7327083213358336\n ],\n [\n 114.6533203125,\n -4.127285323245357\n ],\n [\n 114.9169921875,\n -4.127285323245357\n ],\n [\n 115.13671875,\n -3.9957805129630253\n ],\n [\n 115.75195312499999,\n -3.90809888189411\n ],\n [\n 116.1474609375,\n -3.90809888189411\n ],\n [\n 116.49902343749999,\n -3.6449998008920375\n ],\n [\n 116.3671875,\n -3.2502085616531686\n ],\n [\n 116.54296874999999,\n -2.7235830833483856\n ],\n [\n 116.6748046875,\n -2.3723687086440504\n ],\n [\n 116.4111328125,\n -2.108898659243126\n ],\n [\n 116.4111328125,\n -1.845383988573187\n ],\n [\n 116.76269531249999,\n -1.4939713066293112\n ],\n [\n 117.0703125,\n -1.098565496040652\n ],\n [\n 117.50976562499999,\n -0.7470491450051796\n ],\n [\n 117.861328125,\n -0.5712795966325395\n ],\n [\n 117.46582031249999,\n -0.2636709443366629\n ],\n [\n 117.5537109375,\n 0.13183582116662096\n ],\n [\n 117.861328125,\n 0.6591651462894632\n ],\n [\n 118.30078125,\n 0.6591651462894632\n ],\n [\n 118.87207031250001,\n 0.7470491450051796\n ],\n [\n 118.6083984375,\n 1.3182430568620136\n ],\n [\n 118.30078125,\n 1.537901237431487\n ],\n [\n 118.037109375,\n 1.9332268264771233\n ],\n [\n 118.037109375,\n 2.1967272417616712\n ],\n [\n 117.99316406249999,\n 2.767477951092084\n ],\n [\n 117.5537109375,\n 3.118576216781991\n ],\n [\n 117.8173828125,\n 3.425691524418062\n ],\n [\n 117.8173828125,\n 3.8642546157214084\n ],\n [\n 117.46582031249999,\n 4.171115454867424\n ],\n [\n 117.02636718749999,\n 4.302591077119676\n ],\n [\n 116.5869140625,\n 4.302591077119676\n ],\n [\n 116.1474609375,\n 4.214943141390651\n ],\n [\n 115.75195312499999,\n 3.9519408561575946\n ],\n [\n 115.48828125000001,\n 3.469557303061473\n ],\n [\n 115.3564453125,\n 3.118576216781991\n ],\n [\n 115.1806640625,\n 2.767477951092084\n ],\n [\n 114.6533203125,\n 2.4601811810210052\n ],\n [\n 114.60937499999999,\n 1.9332268264771233\n ],\n [\n 114.3896484375,\n 1.5818302639606454\n ],\n [\n 113.7744140625,\n 1.3182430568620136\n ],\n [\n 113.5986328125,\n 1.3621763466641712\n ],\n [\n 113.2470703125,\n 1.4500404973608074\n ],\n [\n 112.8515625,\n 1.537901237431487\n ],\n [\n 112.412109375,\n 1.4939713066293239\n ],\n [\n 112.0166015625,\n 1.2303741774326145\n ],\n [\n 111.6650390625,\n 1.0546279422758869\n ],\n [\n 111.26953125,\n 1.0546279422758869\n ],\n [\n 110.6982421875,\n 0.9228116626857066\n ],\n [\n 110.0830078125,\n 1.0106897682409128\n ],\n [\n 109.64355468749999,\n 1.845383988573187\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 119.55322265624999,\n -0.9008417889908868\n ],\n [\n 119.42138671875,\n -0.9337965488500171\n ],\n [\n 119.28955078124999,\n -1.1644706071806057\n ],\n [\n 119.24560546875001,\n -1.3621763466641585\n ],\n [\n 119.21264648437499,\n -1.6147764249054963\n ],\n [\n 119.234619140625,\n -1.8783255723852057\n ],\n [\n 119.124755859375,\n -2.0430239574220272\n ],\n [\n 119.080810546875,\n -2.284550660236957\n ],\n [\n 119.080810546875,\n -2.460181181020993\n ],\n [\n 118.83911132812499,\n -2.4821334037305633\n ],\n [\n 118.72924804687499,\n -2.778451415046852\n ],\n [\n 118.72924804687499,\n -3.0966358718415505\n ],\n [\n 118.80615234374999,\n -3.3050503438610943\n ],\n [\n 118.861083984375,\n -3.568247821628616\n ],\n [\n 119.39941406249999,\n -3.743671274749705\n ],\n [\n 119.4873046875,\n -3.897138029219278\n ],\n [\n 119.58618164062499,\n -4.105369348495166\n ],\n [\n 119.608154296875,\n -4.247812286342593\n ],\n [\n 119.58618164062499,\n -4.510714125698484\n ],\n [\n 119.4873046875,\n -4.729726554568902\n ],\n [\n 119.53125,\n -4.882994243904852\n ],\n [\n 119.53125,\n -5.058114374355702\n ],\n [\n 119.388427734375,\n -5.178482088522876\n ],\n [\n 119.344482421875,\n -5.28788741401132\n ],\n [\n 119.20166015625,\n -6.413566092994113\n ],\n [\n 119.300537109375,\n -6.566388979822327\n ],\n [\n 119.73999023437499,\n -6.664607562172573\n ],\n [\n 119.981689453125,\n -6.697342732664385\n ],\n [\n 120.43212890625,\n -6.719164960283201\n ],\n [\n 120.904541015625,\n -6.719164960283201\n ],\n [\n 121.47583007812501,\n -6.664607562172573\n ],\n [\n 121.9482421875,\n -6.522730037335407\n ],\n [\n 122.431640625,\n -6.479067290763031\n ],\n [\n 122.662353515625,\n -6.446317749457633\n ],\n [\n 123.12377929687499,\n -5.736242866880139\n ],\n [\n 123.28857421875,\n -5.539445648546757\n ],\n [\n 123.3544921875,\n -5.058114374355702\n ],\n [\n 123.33251953125,\n -4.740675384778361\n ],\n [\n 123.37646484374999,\n -4.3135463640685145\n ],\n [\n 123.20068359374999,\n -3.480523430587774\n ],\n [\n 122.44262695312501,\n -3.743671274749705\n ],\n [\n 122.44262695312501,\n -3.480523430587774\n ],\n [\n 122.288818359375,\n -3.184394492338734\n ],\n [\n 122.200927734375,\n -3.0527538215744703\n ],\n [\n 122.04711914062499,\n -2.997898741103057\n ],\n [\n 121.95922851562501,\n -2.9320690181896394\n ],\n [\n 121.871337890625,\n -2.85526278436657\n ],\n [\n 121.78344726562499,\n -2.7565043855432503\n ],\n [\n 121.78344726562499,\n -2.64676323074096\n ],\n [\n 121.62963867187499,\n -2.515061053188806\n ],\n [\n 121.497802734375,\n -2.3943223575350774\n ],\n [\n 121.30004882812499,\n -2.3613917533090936\n ],\n [\n 121.201171875,\n -2.33943758287141\n ],\n [\n 121.058349609375,\n -2.2516174965491453\n ],\n [\n 120.89355468749999,\n -2.1857489471296665\n ],\n [\n 120.69580078125001,\n -2.218683588558448\n ],\n [\n 120.531005859375,\n -2.0320445754194307\n ],\n [\n 120.377197265625,\n -1.911266535096585\n ],\n [\n 120.355224609375,\n -2.0430239574220272\n ],\n [\n 120.25634765624999,\n -2.0430239574220272\n ],\n [\n 120.10253906249999,\n -1.9332268264771106\n ],\n [\n 119.88281249999999,\n -2.0540032643721338\n ],\n [\n 119.80590820312499,\n -1.8673451129219134\n ],\n [\n 119.761962890625,\n -1.6367402361776067\n ],\n [\n 119.64111328125,\n -1.504953872694194\n ],\n [\n 119.44335937499999,\n -1.3292264529974207\n ],\n [\n 119.564208984375,\n -1.2303741774326018\n ],\n [\n 119.64111328125,\n -1.1534865266428445\n ],\n [\n 119.55322265624999,\n -0.9008417889908868\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 126.80419921874999,\n -1.9551868337565106\n ],\n [\n 129.39697265625,\n -1.9551868337565106\n ],\n [\n 129.39697265625,\n 2.833317196855306\n ],\n [\n 126.80419921874999,\n 2.833317196855306\n ],\n [\n 126.80419921874999,\n -1.9551868337565106\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 125.41992187499999,\n -4.455950571647079\n ],\n [\n 131.396484375,\n -4.455950571647079\n ],\n [\n 131.396484375,\n -2.67968661580376\n ],\n [\n 125.41992187499999,\n -2.67968661580376\n ],\n [\n 125.41992187499999,\n -4.455950571647079\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 124.25537109375,\n -2.5260367521718274\n ],\n [\n 126.5625,\n -2.5260367521718274\n ],\n [\n 126.5625,\n -1.3841426927920029\n ],\n [\n 124.25537109375,\n -1.3841426927920029\n ],\n [\n 124.25537109375,\n -2.5260367521718274\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 121.35498046875,\n 0.4833927027896987\n ],\n [\n 121.59667968749999,\n 0.4614207935306211\n ],\n [\n 121.871337890625,\n 0.37353251022880474\n ],\n [\n 122.18994140624999,\n 0.4614207935306211\n ],\n [\n 122.6513671875,\n 0.4724067568442892\n ],\n [\n 122.958984375,\n 0.4833927027896987\n ],\n [\n 123.15673828124999,\n 0.39550467153201946\n ],\n [\n 123.48632812499999,\n 0.2746571512146894\n ],\n [\n 123.8818359375,\n 0.2856433479945185\n ],\n [\n 124.222412109375,\n 0.39550467153201946\n ],\n [\n 124.45312499999999,\n 0.4614207935306211\n ],\n [\n 125.23315429687501,\n 0.9228116626857066\n ],\n [\n 125.584716796875,\n 1.7575368113083254\n ],\n [\n 125.90332031249999,\n 2.668712251961311\n ],\n [\n 125.9912109375,\n 3.261177158186781\n ],\n [\n 127.15576171875,\n 3.6449998008920375\n ],\n [\n 127.13378906249999,\n 4.23685605976896\n ],\n [\n 126.7822265625,\n 4.718777551249855\n ],\n [\n 125.31005859374999,\n 3.7655967694198504\n ],\n [\n 124.62890625,\n 1.5818302639606454\n ],\n [\n 124.332275390625,\n 1.2852925793638545\n ],\n [\n 124.04663085937499,\n 1.0546279422758869\n ],\n [\n 123.55224609375,\n 1.0656123898763876\n ],\n [\n 122.55249023437501,\n 0.9557662177941483\n ],\n [\n 122.310791015625,\n 0.9008417889908868\n ],\n [\n 122.10205078125,\n 0.9008417889908868\n ],\n [\n 121.981201171875,\n 0.8898568022677679\n ],\n [\n 121.81640624999999,\n 0.8898568022677679\n ],\n [\n 121.607666015625,\n 0.856901647439813\n ],\n [\n 121.497802734375,\n 0.8239462091017685\n ],\n [\n 121.35498046875,\n 0.8459165322899798\n ],\n [\n 121.212158203125,\n 0.8129610018708315\n ],\n [\n 121.17919921875001,\n 0.7140928403610857\n ],\n [\n 121.26708984374999,\n 0.5932511181408705\n ],\n [\n 121.35498046875,\n 0.4833927027896987\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at: http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-27","noUsgsAuthors":false,"publicationDate":"2016-09-27","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c84c","contributors":{"authors":[{"text":"Lederer, Graham W. glederer@usgs.gov","contributorId":174731,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham W.","email":"glederer@usgs.gov","affiliations":[],"preferred":false,"id":649129,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70176630,"text":"70176630 - 2016 - Influence of demography and environment on persistence in toad populations","interactions":[],"lastModifiedDate":"2016-09-27T09:40:23","indexId":"70176630","displayToPublicDate":"2016-09-27T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Influence of demography and environment on persistence in toad populations","docAbstract":"Effective conservation of rare species requires an understanding of how potential threats affect population dynamics. Unfortunately, information about population demographics prior to threats (i.e., baseline data) is lacking for many species. Perturbations, caused by climate change, disease, or other stressors can lead to population declines and heightened conservation concerns. Boreal toads (Anaxyrus boreas boreas) have undergone rangewide declines due mostly to the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd), with only a few sizable populations remaining in the southern Rocky Mountains, USA, that are disease-free. Despite the apparent region-wide occurrence of Bd, our focal populations in central Colorado were disease free over a 14-year capture-mark-recapture study until the recent discovery of Bd at one of the sites. We used recapture data and the Pradel reverse-time model to assess the influence of environmental and site-specific conditions on survival and recruitment. We then forecast changes in the toad populations with 2 growth models; one using an average lambda value to initiate the projection, and one using the most recent value to capture potential effects of the incursion of disease into the system. Adult survival was consistently high at the 3 sites, whereas recruitment was more variable and markedly low at 1 site. We found that active season moisture, active season length, and breeding shallows were important factors in estimating recruitment. Population growth models indicated a slight increase at 1 site but decreasing trends at the 2 other sites, possibly influenced by low recruitment. Insight into declining species management can be gained from information on survival and recruitment and how site-specific environmental factors influence these demographic parameters. Our data are particularly useful because they provide baseline data on demographics in populations before a disease outbreak and enhance our ability to detect changes in population parameters potentially caused by the disease.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21118","usgsCitation":"Lambert, B.A., Schorr, R.A., Schneider, S.C., and Muths, E.L., 2016, Influence of demography and environment on persistence in toad populations: Journal of Wildlife Management, v. 80, no. 7, p. 1256-1266, https://doi.org/10.1002/jwmg.21118.","productDescription":"11 p.","startPage":"1256","endPage":"1266","ipdsId":"IP-068989","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":329017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c84e","contributors":{"authors":[{"text":"Lambert, Brad A.","contributorId":173020,"corporation":false,"usgs":false,"family":"Lambert","given":"Brad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":649431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schorr, Robert A.","contributorId":105239,"corporation":false,"usgs":true,"family":"Schorr","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":649432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schneider, Scott C.","contributorId":174943,"corporation":false,"usgs":false,"family":"Schneider","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":649727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":649430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70175721,"text":"sir20165098 - 2016 - Water pressure and ground vibrations induced by water guns at a backwater pond on the Illinois River near Morris, Illinois","interactions":[],"lastModifiedDate":"2016-09-28T09:15:13","indexId":"sir20165098","displayToPublicDate":"2016-09-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5098","title":"Water pressure and ground vibrations induced by water guns at a backwater pond on the Illinois River near Morris, Illinois","docAbstract":"Three different geophysical sensor types were used to characterize the underwater pressure waves and ground velocities generated by the underwater firing of seismic water guns. These studies evaluated the use of water guns as a tool to alter the movement of Asian carp. Asian carp are aquatic invasive species that threaten to move into the Great Lakes Basin from the Mississippi River Basin. Previous studies have identified a threshold of approximately 5 pounds per square inch (lb/in2) for behavioral modification and for structural limitation of a water gun barrier.
Two studies were completed during August 2014 and May 2015 in a backwater pond connected to the Illinois River at a sand and gravel quarry near Morris, Illinois. The August 2014 study evaluated the performance of two 80-cubic-inch (in3) water guns. Data from the 80-in3 water guns showed that the pressure field had the highest pressures and greatest extent of the 5-lb/in2 target value at a depth of 5 feet (ft). The maximum recorded pressure was 13.7 lb/in2, approximately 25 ft from the guns. The produced pressure field took the shape of a north-south-oriented elongated sphere with the 5-lb/in2 target value extending across the entire study area at a depth of 5 ft. Ground velocities were consistent over time, at 0.0067 inches per second (in/s) in the transverse direction, 0.031 in/s in the longitudinal direction, and 0.013 in/s in the vertical direction.
The May 2015 study evaluated the performance of one and two 100-in3 water guns. Data from the 100-in3 water guns, fired both individually and simultaneously, showed that the pressure field had the highest pressures and greatest extent of the 5-lb/in2 target value at a depth of 5 ft. The maximum pressure was 57.4 lb/in2, recorded at the underwater blast sensor closest to the water guns (at a horizontal distance of approximately 3 ft), as two guns fired simultaneously. Pressures and extent of the 5-lb/in2 target value decrease above and below this 5-ft depth, producing a relatively north-south-oriented pressure field shaped like an elongated sphere.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165098","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency as part of the Great Lakes Restoration Initiative","usgsCitation":"Koebel, C.M., and Egly, R.M., 2016, Water pressure and ground vibrations induced by water guns at a backwater pond on the Illinois River near Morris, Illinois: U.S. Geological Survey Scientific Investigations Report 2016–5098, 29 p., https://dx.doi.org/10.3133/sir20165098.","productDescription":"Report: v, 29 p.; Dataset","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-072620","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":328926,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2016/5098/sir20165098_morris_seismic_data.zip","text":"Seismic Data","size":"890.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5098 Seismic Data"},{"id":328934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5098/coverthb.jpg"},{"id":328935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5098/sir20165098.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5098"}],"country":"United States","state":"Illinois","city":"Morris","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.50388526916504,\n 41.32726186584144\n ],\n [\n -88.50388526916504,\n 41.334738165428035\n ],\n [\n -88.46534729003906,\n 41.334738165428035\n ],\n [\n -88.46534729003906,\n 41.32726186584144\n ],\n [\n -88.50388526916504,\n 41.32726186584144\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Illinois-Iowa Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov
This study provides an independent estimate of the areal and volumetric extent of groundwater contaminant plumes which are affected by waste disposal in the 100-K and 100-N Areas (study area) along the Columbia River Corridor of the Hanford Site. The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past.
All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER®data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER®, along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards.
A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3).
Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors.
The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161161","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Hanford Natural Resource Trustee Council","usgsCitation":"Johnson, K.H., 2016, Groundwater contaminant plume maps and volumes, 100-K and 100–N Areas, Hanford Site, Washington: U.S. Geological Survey Open-File Report 2016–1161, 64 p., https://dx.doi.org/10.3133/ofr20161161.","productDescription":"Report: vi, 64 p.; Appendix A","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-071546","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1161/coverthb.jpg"},{"id":329029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1161/ofr20161161.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1161"},{"id":329030,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1161/ofr20161161_appendixa.xlsx","text":"Appendix A","size":"2.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1161 Appendix A"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.83886718750001,\n 46.25204849722291\n ],\n [\n -119.83886718750001,\n 46.82637528602131\n ],\n [\n -119.19616699218749,\n 46.82637528602131\n ],\n [\n -119.19616699218749,\n 46.25204849722291\n ],\n [\n -119.83886718750001,\n 46.25204849722291\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
Scientists and technical support staff from the U.S. Geological Survey measured suspended-sediment concentrations, currents, pressure, and water temperature in two tidal creeks, Reedy Creek and Dinner Creek, in Barnegat Bay, New Jersey, from August 11, 2014, to July 10, 2015 as part of the Estuarine Physical Response to Storms project (GS2–2D). The oceanographic and water-quality data quantify suspended-sediment transport in Reedy Creek and Dinner Creek, which are part of a tidal marsh wetland complex in the Edwin B. Forsythe National Wildlife Refuge. All deployed instruments were removed between January 7, 2015, and April 14, 2015, to avoid damage by ice.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161149","usgsCitation":"Suttles, S.E., Ganju, N.K, Montgomery, E.T., Dickhudt, P.J., Borden, Jonathan., Brosnahan, S.M., and Martini, M.A., 2016, Summary of oceanographic and water-quality measurements in Barnegat Bay, New Jersey, 2014–15: U.S. Geological Survey Open-File Report 2016–1149, 22 p., https://dx.doi.org/10.3133/ofr20161149.","productDescription":"Report: vii, 22 p.; Appendix: 1-2","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076598","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328800,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1149/appendix/downloads/adcptransects","text":"Appendix 2 ","description":"OFR 2016-1149","linkHelpText":"- Acoustic Doppler Current Profiler Transect Data, August 2014 and May 2015 for Reedy and Dinner Creeks"},{"id":328792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1149/coverthb.jpg"},{"id":328793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1149/ofr20161149.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1149"},{"id":328794,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1149/appendix/downloads/watersamples/ofr20161149_appendix1.zip","text":"Appendix 1","size":"40.4 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1149","linkHelpText":"- Water Sample Data, August 2014 to January 2015 and April to July 2015"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.55184936523438,\n 39.36190883564925\n ],\n [\n -74.55184936523438,\n 40.08752795413118\n ],\n [\n -74.02450561523438,\n 40.08752795413118\n ],\n [\n -74.02450561523438,\n 39.36190883564925\n ],\n [\n -74.55184936523438,\n 39.36190883564925\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
http://woodshole.er.usgs.gov/
Occurrence models that account for imperfect detection of species are increasingly used for estimating geographical range, for determining species-landscape relations and to prioritize conservation actions worldwide. In 2010, we conducted a large-scale survey in Río Muni, the mainland territory of Equatorial Guinea, which aimed to estimate the probabilities of occurrence and detection of threatened mammals based on environmental covariates, and to identify priority areas for conservation. Interviews with hunters were designed to record presence/absence data of seven species (golden cat, leopard, forest elephant, forest buffalo, western gorilla, chimpanzee and mandrill) in 225 sites throughout the region. We fitted single season occupancy models and recently developed models which also include false positive errors (i.e. species detected in places where it actually does not occur), which should provide more accurate estimates for most species, which are susceptible to mis-identification. Golden cat and leopard had the lowest occurrence rates in the region, whereas primates had the highest rates. All species, except gorilla, were affected negatively by human settlements. The southern half of Río Muni showed the highest occurrence of the species studied, and conservation strategies for ensuring the persistence of threatened mammals should be focused on this area.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep33838","usgsCitation":"Martinez-Marti, C., Jimenez-Franco, M.V., Royle, J., Palazon, J.A., and Calvo, J.F., 2016, Integrating occurrence and detectability patterns based on interview data: a case study for threatened mammals in Equatorial Guinea: Scientific Reports, v. 6, 33838; 9 p., https://doi.org/10.1038/srep33838.","productDescription":"33838; 9 p.","ipdsId":"IP-078834","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470554,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep33838","text":"Publisher Index Page"},{"id":329485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Equatorial Guinea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 9.8162841796875,\n 2.3668802418421357\n ],\n [\n 9.84375,\n 2.3394375828714224\n ],\n [\n 9.832763671875,\n 2.311994386907854\n ],\n [\n 9.832763671875,\n 2.28455066023697\n ],\n [\n 9.8822021484375,\n 2.2406396093827334\n ],\n [\n 9.9151611328125,\n 2.2077054557054083\n ],\n [\n 9.942626953125,\n 2.20221635884472\n ],\n [\n 10.0140380859375,\n 2.180259769681356\n ],\n [\n 10.074462890625,\n 2.169281354771587\n ],\n [\n 10.140380859375,\n 2.169281354771587\n ],\n [\n 10.1788330078125,\n 2.1747705722118864\n ],\n [\n 10.2777099609375,\n 2.180259769681356\n ],\n [\n 11.35986328125,\n 2.1857489471296665\n ],\n [\n 11.348876953125,\n 0.9997051308419692\n ],\n [\n 9.7833251953125,\n 0.9997051308419692\n ],\n [\n 9.73388671875,\n 1.0656123898763876\n ],\n [\n 9.6734619140625,\n 1.0711045990129324\n ],\n [\n 9.569091796875,\n 1.016182073033441\n ],\n [\n 9.5526123046875,\n 1.0601201709472332\n ],\n [\n 9.5086669921875,\n 1.1150419135172274\n ],\n [\n 9.437255859375,\n 1.1095497845377595\n ],\n [\n 9.3878173828125,\n 1.087581167162357\n ],\n [\n 9.3328857421875,\n 1.1479944704491494\n ],\n [\n 9.327392578125,\n 1.2138984340943106\n ],\n [\n 9.3768310546875,\n 1.257833522873487\n ],\n [\n 9.3988037109375,\n 1.323734761011294\n ],\n [\n 9.437255859375,\n 1.3402098002785028\n ],\n [\n 9.4482421875,\n 1.417091829441639\n ],\n [\n 9.51416015625,\n 1.4720060101903352\n ],\n [\n 9.569091796875,\n 1.554374729735434\n ],\n [\n 9.5855712890625,\n 1.6202674001017445\n ],\n [\n 9.5965576171875,\n 1.6861579269987979\n ],\n [\n 9.667968749999998,\n 1.7520462233579808\n ],\n [\n 9.7119140625,\n 1.812441794538039\n ],\n [\n 9.7393798828125,\n 1.8893059628373186\n ],\n [\n 9.7943115234375,\n 1.9277367801405985\n ],\n [\n 9.7393798828125,\n 2.070472083193102\n ],\n [\n 9.766845703125,\n 2.180259769681356\n ],\n [\n 9.766845703125,\n 2.273573022378629\n ],\n [\n 9.7503662109375,\n 2.3504147112508176\n ],\n [\n 9.8162841796875,\n 2.3668802418421357\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-26","publicationStatus":"PW","scienceBaseUri":"57fe679ee4b0824b2d14370f","contributors":{"authors":[{"text":"Martinez-Marti, Chele","contributorId":175261,"corporation":false,"usgs":false,"family":"Martinez-Marti","given":"Chele","email":"","affiliations":[{"id":27549,"text":"Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jimenez-Franco, Maria V.","contributorId":175262,"corporation":false,"usgs":false,"family":"Jimenez-Franco","given":"Maria","email":"","middleInitial":"V.","affiliations":[{"id":27549,"text":"Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":138865,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":650626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palazon, Jose A.","contributorId":175263,"corporation":false,"usgs":false,"family":"Palazon","given":"Jose","email":"","middleInitial":"A.","affiliations":[{"id":27550,"text":"1Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Calvo, Jose F.","contributorId":175264,"corporation":false,"usgs":false,"family":"Calvo","given":"Jose","email":"","middleInitial":"F.","affiliations":[{"id":27550,"text":"1Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650630,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176627,"text":"70176627 - 2016 - Encounters with Pinyon-Juniper influence riskier movements in Greater Sage-Grouse across the Great Basin","interactions":[],"lastModifiedDate":"2016-09-26T17:21:40","indexId":"70176627","displayToPublicDate":"2016-09-25T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Encounters with Pinyon-Juniper influence riskier movements in Greater Sage-Grouse across the Great Basin","docAbstract":"Fine-scale spatiotemporal studies can better identify relationships between individual survival and habitat fragmentation so that mechanistic interpretations can be made at the population level. Recent advances in Global Positioning System (GPS) technology and statistical models capable of deconstructing high-frequency location data have facilitated interpretation of animal movement within a behaviorally mechanistic framework. Habitat fragmentation due to singleleaf pinyon (Pinus monophylla; hereafter pinyon) and Utah juniper (Juniperus osteosperma; hereafter juniper) encroachment into sagebrush (Artemisia spp.) communities is a commonly implicated perturbation that can adversely influence greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) demographic rates. Using an extensive GPS data set (233 birds and 282,954 locations) across 12 study sites within the Great Basin, we conducted a behavioral change point analysis and subsequently constructed Brownian bridge movement models from each behaviorally homogenous section. We found a positive relationship between modeled movement rate and probability of encountering pinyon-juniper with significant variation among age classes. The probability of encountering pinyon-juniper among adults was two and three times greater than that of yearlings and juveniles, respectively. However, the movement rate in response to the probability of encountering pinyon-juniper trees was 1.5 times greater for juveniles. We then assessed the risk of mortality associated with an interaction between movement rate and the probability of encountering pinyon-juniper using shared frailty models. During pinyon-juniper encounters, on average, juvenile, yearling, and adult birds experienced a 10.4%, 0.2%, and 0.3% reduction in annual survival probabilities. Populations that used pinyon-juniper habitats with a frequency ≥ 3.8 times the overall mean experienced decreases in annual survival probabilities of 71.1%, 0.9%, and 0.9%. This analytical framework identifies a likely behavioral mechanism behind how pinyon-juniper encroachment decreases habitat suitability for sage-grouse, whereby encountering pinyon-juniper stimulates faster yet riskier movements that may make sage-grouse more vulnerable to visually acute predators.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rama.2016.07.004","collaboration":"FWS, BLM, NDOW, FS","usgsCitation":"Prochazka, B.G., Coates, P.S., Ricca, M.A., Casazza, M.L., Gustafson, K.B., and Hull, J.M., 2016, Encounters with Pinyon-Juniper influence riskier movements in Greater Sage-Grouse across the Great Basin: Rangeland Ecology and Management, https://doi.org/10.1016/j.rama.2016.07.004.","onlineOnly":"Y","ipdsId":"IP-074788","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470556,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2016.07.004","text":"Publisher Index Page"},{"id":329009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c854","contributors":{"authors":[{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649423,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustafson, K. Benjamin 0000-0003-3530-0372 kgustafson@usgs.gov","orcid":"https://orcid.org/0000-0003-3530-0372","contributorId":166818,"corporation":false,"usgs":true,"family":"Gustafson","given":"K.","email":"kgustafson@usgs.gov","middleInitial":"Benjamin","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hull, Josh M.","contributorId":174840,"corporation":false,"usgs":false,"family":"Hull","given":"Josh","email":"","middleInitial":"M.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":649425,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176637,"text":"70176637 - 2016 - First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful","interactions":[],"lastModifiedDate":"2021-08-24T15:36:59.792178","indexId":"70176637","displayToPublicDate":"2016-09-23T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful","title":"First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful","docAbstract":"In an era of shrinking budgets yet increasing demands for conservation, the value of existing (i.e., historical) data are elevated. Lengthy time series on common, or previously common, species are particularly valuable and may be available only through the use of historical information. We provide first estimates of the probability of survival and longevity (0.67–0.79 and 5–7 years, respectively) for a subalpine population of a small-bodied, ostensibly common amphibian, the Boreal Chorus Frog (Pseudacris maculata (Agassiz, 1850)), using historical data and contemporary, hypothesis-driven information–theoretic analyses. We also test a priori hypotheses about the effects of color morph (as suggested by early reports) and of drought (as suggested by recent climate predictions) on survival. Using robust mark–recapture models, we find some support for early hypotheses regarding the effect of color on survival, but we find no effect of drought. The congruence between early findings and our analyses highlights the usefulness of historical information in providing raw data for contemporary analyses and context for conservation and management decisions.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjz-2016-0024","usgsCitation":"Muths, E.L., Scherer, R.D., Amburgey, S.M., Matthews, T., Spencer, A.W., and Corn, P., 2016, First estimates of the probability of survival in a small-bodied, high-elevation frog (Boreal Chorus Frog, Pseudacris maculata), or how historical data can be useful: Canadian Journal of Zoology, v. 94, no. 9, p. 599-606, https://doi.org/10.1139/cjz-2016-0024.","productDescription":"8 p.","startPage":"599","endPage":"606","ipdsId":"IP-064683","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488529,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1807/73513","text":"External Repository"},{"id":328941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c856","contributors":{"authors":[{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":649575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scherer, R. D.","contributorId":8061,"corporation":false,"usgs":false,"family":"Scherer","given":"R.","email":"","middleInitial":"D.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":649576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amburgey, S. M.","contributorId":174896,"corporation":false,"usgs":false,"family":"Amburgey","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":649577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matthews, T.","contributorId":174897,"corporation":false,"usgs":false,"family":"Matthews","given":"T.","email":"","affiliations":[],"preferred":false,"id":649578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spencer, A. W.","contributorId":174898,"corporation":false,"usgs":false,"family":"Spencer","given":"A.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":649579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corn, P.S.","contributorId":63751,"corporation":false,"usgs":true,"family":"Corn","given":"P.S.","affiliations":[],"preferred":false,"id":649580,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176105,"text":"ds1017 - 2016 - Digital geologic map data for the Ozark National Scenic Riverways and adjacent areas along the Current River and Jacks Fork, Missouri","interactions":[],"lastModifiedDate":"2016-09-23T10:27:59","indexId":"ds1017","displayToPublicDate":"2016-09-23T09:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1017","title":"Digital geologic map data for the Ozark National Scenic Riverways and adjacent areas along the Current River and Jacks Fork, Missouri","docAbstract":"The geology of the Ozark National Scenic Riverways (ONSR) in southern Missouri has been mapped at 1:24,000 scale. This endeavor was achieved through the combined efforts of U.S. Geological Survey and Missouri Geological Survey individual quadrangle mapping and additional fieldwork by the authors of this report. Geologic data covering the area of the ONSR and a 1-mile (1.6-kilometer) buffer zone surrounding the park, as well as geologic data from a few key adjoining areas, have been compiled into a single, seamless geographic information system database. The intent is to provide base geologic information for natural science research and land management in the park and surrounding areas. The data are served online at ScienceBase (https://www.sciencebase.gov/catalog/), where they are provided in Environmental Systems Research Institute (ESRI) file geodatabase format, and are accompanied by metadata files. These data can be accessed at: http://dx.doi.org/10.5066/F7CJ8BKB. Additional detailed geologic information about the ONSR and surrounding areas is available in the separate 1:24,000-scale quadrangle maps and in a 1:100,000-scale map and report on the regional geology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1017","usgsCitation":"Weary, D.J., Orndorff, R.C., Harrison, R.W., and Weems, R.E., 2016, Digital geologic map data for the Ozark National Scenic Riverways and adjacent areas along the Current River and Jacks Fork, Missouri: U.S. Geological Survey Data Series 1017, 14 p., https://dx.doi.org/10.3133/ds1017.","productDescription":"Report: iv, 14 p., Data Release","startPage":"1","endPage":"14","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055549","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":438545,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CJ8BKB","text":"USGS data release","linkHelpText":"Digital geologic map data for the Ozark National Scenic Riverways and adjacent areas along the Current River and Jacks Fork, Missouri"},{"id":328530,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1017/coverthb2.jpg"},{"id":328531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1017/ds1017.pdf","text":"Report","size":"3.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1017"},{"id":328532,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7CJ8BKB","text":"USGS data release","description":"USGS data release","linkHelpText":"Digital geologic map data for the Ozark National Scenic Riverways and adjacent areas along the Current River and Jacks Fork, Missouri"}],"country":"United States","state":"Missouri","otherGeospatial":"Current River, Jacks Fork","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.2769889831543,\n 37.19286918883309\n ],\n [\n -91.2802505493164,\n 37.19533058280065\n ],\n [\n -91.28677368164062,\n 37.192048706345375\n ],\n [\n -91.29192352294922,\n 37.19601428910628\n ],\n [\n -91.29518508911131,\n 37.19997966357578\n ],\n [\n -91.30170822143555,\n 37.200253129999126\n ],\n [\n -91.30805969238281,\n 37.19765515897727\n ],\n [\n -91.31269454956055,\n 37.20230409659462\n ],\n [\n -91.3154411315918,\n 37.20736290925367\n ],\n [\n -91.31904602050781,\n 37.21324164386899\n ],\n [\n -91.32059097290039,\n 37.216659302277314\n ],\n [\n -91.31458282470702,\n 37.22158045838652\n ],\n [\n -91.31303787231445,\n 37.22650129343409\n ],\n [\n -91.30823135375977,\n 37.22759476873106\n ],\n [\n -91.30428314208984,\n 37.229918351090596\n ],\n [\n -91.30531311035156,\n 37.231968511359014\n ],\n [\n -91.29827499389648,\n 37.23401861588193\n ],\n [\n -91.2944984436035,\n 37.2375719983302\n ],\n [\n -91.29226684570312,\n 37.24098855426871\n ],\n [\n -91.29329681396484,\n 37.25014416051375\n ],\n [\n -91.29484176635741,\n 37.256019560567275\n ],\n [\n -91.30342483520508,\n 37.25342351006726\n ],\n [\n -91.30239486694335,\n 37.242218476496625\n ],\n [\n -91.30908966064453,\n 37.234155287534705\n ],\n [\n -91.31750106811523,\n 37.22937163227105\n ],\n [\n -91.31956100463867,\n 37.22240061985746\n ],\n [\n -91.32711410522461,\n 37.21994010868952\n ],\n [\n -91.32179260253905,\n 37.20777306839136\n ],\n [\n -91.3180160522461,\n 37.20394482974588\n ],\n [\n -91.31011962890625,\n 37.19163846175808\n ],\n [\n -91.29999160766602,\n 37.1956040660659\n ],\n [\n -91.29072189331055,\n 37.187262380805564\n ],\n [\n -91.28042221069336,\n 37.190544465294934\n ],\n [\n -91.28042221069336,\n 37.186441837394554\n ],\n [\n -91.28334045410155,\n 37.1834331019458\n ],\n [\n -91.29364013671875,\n 37.18493748465265\n ],\n [\n -91.29913330078124,\n 37.17933008772031\n ],\n [\n -91.29621505737305,\n 37.17467973550966\n ],\n [\n -91.29810333251953,\n 37.173859055404826\n ],\n [\n -91.30239486694335,\n 37.17632106897632\n ],\n [\n -91.30685806274414,\n 37.17591073895253\n ],\n [\n -91.31114959716797,\n 37.174542956111225\n ],\n [\n -91.31338119506836,\n 37.17221766845256\n ],\n [\n -91.31767272949219,\n 37.173722274520685\n ],\n [\n -91.32299423217773,\n 37.17126017626408\n ],\n [\n -91.32608413696288,\n 37.16770367048253\n ],\n [\n -91.329345703125,\n 37.16633573907469\n ],\n [\n -91.33157730102539,\n 37.17071303242321\n ],\n [\n -91.33810043334961,\n 37.17303836638578\n ],\n [\n -91.34393692016602,\n 37.16770367048253\n ],\n [\n -91.33878707885742,\n 37.160590156787244\n ],\n [\n -91.33604049682617,\n 37.16428379553819\n ],\n [\n -91.33466720581055,\n 37.16209499436255\n ],\n [\n -91.32642745971678,\n 37.16072696144112\n ],\n [\n -91.3235092163086,\n 37.16346300252506\n ],\n [\n -91.32230758666992,\n 37.165514968345214\n ],\n [\n -91.31904602050781,\n 37.16866120773569\n ],\n [\n -91.31372451782227,\n 37.16852441744235\n ],\n [\n -91.31046295166016,\n 37.17057624584397\n ],\n [\n -91.30651473999023,\n 37.17303836638578\n ],\n [\n -91.30016326904297,\n 37.1696187328562\n ],\n [\n -91.29484176635741,\n 37.170302671942636\n ],\n [\n -91.29175186157227,\n 37.17139696160527\n ],\n [\n -91.28900527954102,\n 37.17317514850797\n ],\n [\n -91.28969192504883,\n 37.177141722338035\n ],\n [\n -91.29003524780273,\n 37.18165515647851\n ],\n [\n -91.28488540649414,\n 37.17933008772031\n ],\n [\n -91.27973556518553,\n 37.180834552147516\n ],\n [\n -91.27681732177734,\n 37.183296338395685\n ],\n [\n -91.27578735351561,\n 37.18657859524883\n ],\n [\n -91.27424240112305,\n 37.18849317920571\n ],\n [\n -91.26480102539062,\n 37.18315957459794\n ],\n [\n -91.25398635864258,\n 37.17878300231781\n ],\n [\n -91.2495231628418,\n 37.1800139389017\n ],\n [\n -91.24643325805664,\n 37.177688819626646\n ],\n [\n -91.24385833740233,\n 37.17358549338895\n ],\n [\n -91.23355865478516,\n 37.17344871200958\n ],\n [\n -91.22325897216797,\n 37.17467973550966\n ],\n [\n -91.2224006652832,\n 37.177278497031615\n ],\n [\n -91.21879577636719,\n 37.17563718436526\n ],\n [\n -91.20454788208008,\n 37.173859055404826\n ],\n [\n -91.20025634765625,\n 37.17659462108739\n ],\n [\n -91.19596481323242,\n 37.18261251693054\n ],\n [\n -91.1920166015625,\n 37.18616832094302\n ],\n [\n -91.19527816772461,\n 37.190270963702574\n ],\n [\n -91.2000846862793,\n 37.18739913717396\n ],\n [\n -91.20918273925781,\n 37.18165515647851\n ],\n [\n -91.21038436889648,\n 37.1785094581308\n ],\n [\n -91.21604919433594,\n 37.1785094581308\n ],\n [\n -91.21896743774414,\n 37.179877169160704\n ],\n [\n -91.2246322631836,\n 37.18028747764086\n ],\n [\n -91.22978210449219,\n 37.17809913999305\n ],\n [\n -91.23991012573241,\n 37.177141722338035\n ],\n [\n -91.24265670776367,\n 37.18165515647851\n ],\n [\n -91.25484466552734,\n 37.18384339111027\n ],\n [\n -91.26256942749023,\n 37.18849317920571\n ],\n [\n -91.26840591430664,\n 37.192048706345375\n ],\n [\n -91.2769889831543,\n 37.19286918883309\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://geology.er.usgs.gov/egpsc/
Melting occurred during stick-slip faulting of granite blocks sheared at room-dry, room-temperature conditions in a triaxial apparatus at 200–400 megapascals (MPa) confining pressure. Petrographic examinations of melt textures focused largely on the 400-MPa run products. This report presents an overview of the petrographic data collected on those samples, followed by brief descriptions of annotated versions of all the images.
Scanning electron microscope (SEM) images of the starting materials and the three examined 400-MPa samples are presented in this report. Secondary-electron (SE) and backscattered-electron (BSE) imaging techniques were used on different samples. The SE images look down on the sawcut surfaces, yielding topographic and three-dimensional textural information. The BSE imaging was done on samples cut to provide cross-sectional views of the glass-filled shear band (or zone) that developed along the sawcut. Brightness in the BSE images increases with increasing mean atomic number of the material. Additional chemical information about the quenched melt and adjoining minerals was obtained using the energy dispersive system of the SEM during BSE examinations. However, the very narrow shear-band thicknesses and common occurrence of very fine lamellar compositional layering limited the usefulness of this technique for estimating melt chemistry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161059","usgsCitation":"Moore, D.E., Lockner, D.A., Kilgore, B.D., and Beeler, N.M., 2016, Gallery of melt textures developed in Westerly Granite during high-pressure triaxial friction experiments: U.S. Geological Survey Open-File Report 2016–1059, 75 p., https://dx.doi.org/10.3133/ofr20161059.","productDescription":"iv, 75 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-073957","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":328890,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1059/ofr20161059.pdf","text":"Report","size":"81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1059"},{"id":328889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1059/coverthb.jpg"}],"contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, are experiencing long-term declines in abundance. Upper Klamath Lake populations are decreasing because adult mortality, which is relatively low, is not being balanced by recruitment of young adult suckers into known adult spawning aggregations. Previous sampling for juvenile suckers indicated that most juvenile sucker mortality in Upper Klamath Lake likely occurs within the first year of life. The importance of juvenile sucker mortality to the dynamics of Clear Lake Reservoir populations is less clear, and factors other than juvenile mortality (such as access to spawning habitat) play a substantial role. For example, production of age-0 juvenile suckers, as determined by fin ray annuli and fin development, has not been detected since 2013 in Clear Lake Reservoir, whereas it is detected annually in Upper Klamath Lake.
\nWe initiated a long-term juvenile sucker monitoring program in 2015 designed to track cohorts through seasons and among years in both Upper Klamath Lake and Clear Lake Reservoir. Specifically, our goals are to track annual variability in age-0 sucker production, juvenile sucker survival, growth, and condition. In this first year of the monitoring program, we assessed assumptions that sampled fish were representative of populations of suckers in each lake. The size, age, and species composition of suckers were similar between randomly determined sites and fixed sites in each lake. We captured a wide size and age range of suckers using similar gear, indicating our gear did not exclude older and larger fish. We identified improvements that could be made in the monitoring program including increasing the number of randomly determined sample sites in both lakes, evaluation of gear-size selectivity, and validation of aging methods for juvenile Lost River and shortnose suckers.
\nDiffering age composition of juvenile suckers between lakes in our 2015 catches and as reported in previous studies indicate that juvenile suckers are produced in relatively larger numbers each year in Upper Klamath Lake than in Clear Lake Reservoir. Most (96.6 percent) of suckers captured in Upper Klamath Lake in 2015 were age-0, whereas age-0 or age-1 suckers were not captured in Clear Lake Reservoir. Despite ample effort, age-0 suckers have not been captured in Clear Lake Reservoir since 2013. Estimated ages of suckers captured in 2015 in Clear Lake Reservoir ranged from 2 to 6 years. Low flow during spawning seasons in the only known spawning tributary to Clear Lake Reservoir (Willow Creek) appears to explain the lack of age-0 sucker production in recent years.
\nJuvenile sucker mortality is relatively higher in Upper Klamath Lake than in Clear Lake Reservoir. We compared data collected in 2015 to previously published catch rates to produce an index of annual juvenile sucker survival for these species. We calculated indices of annual apparent survival of juvenile sucker ages 0–5 years old in Clear Lake Reservoir to be between 0.37 (±0.86 standard error [SE]) and 0.44 (±0.84 SE). This is the first time indices of annual apparent survival for Lost River and shortnose suckers have been calculated. This estimate has the limitation of being non-species specific because not all individuals were identified to species in previous years, and suckers that were identified included both taxa. In contrast, catch rates decreased by 89 percent for juvenile Lost River suckers and decreased 50 percent for juvenile shortnose suckers in Upper Klamath Lake between August and September 2015. Very low catch rates of age-1 and older suckers in Upper Klamath Lake indicate that annual juvenile sucker survival rates are near zero.
\nCondition of suckers was assessed in 2015 based on age-0 sucker growth rates in Upper Klamath Lake and the prevalence of externally observable afflictions on suckers from both lakes. Age-0 Lost River suckers grew an average (± standard deviation [SD]) of 0.72 (±0.01) millimeters [mm] standard length [SL] per day, and age-0 shortnose suckers grew an average of 0.57 (±0.04) mm SL per day in 2015. This growth rate was similar to growth rates reported for these species in Upper Klamath Lake in previous years. Opercular deformities, skin hemorrhages, black-spot causing parasites, and Lernaea spp. parasitism were the most common afflictions observed on suckers. Observed afflictions were primarily on suckers from Upper Klamath Lake, with the exception of Lernaea spp., which occurred more frequently on suckers from Clear Lake Reservoir. Opercular deformities and black-spot causing parasites were each observed on 5 percent of age-0 suckers from Upper Klamath Lake. Petechial hemorrhaging of the skin was observed on 43 percent of age-0 Lost River suckers, 38 percent of age-0 suckers of undetermined taxa, and only 24 percent of age-0 shortnose suckers from Upper Klamath Lake. Petechial hemorrhaging of the skin was only observed on a single shortnose sucker from Clear Lake Reservoir. Within Upper Klamath Lake, the prevalence of these hemorrhages was exactly twice as high as was reported in 2014.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161164","usgsCitation":"Burdick, S.M., Ostberg, C.O., Hereford, M.E., and Hoy, M.S., 2016, Juvenile sucker cohort tracking data summary and assessment of monitoring program, 2015: U.S. Geological Survey Open-File Report 2016–1164, 30 p., https://dx.doi.org/10.3133/ofr20161164.","productDescription":"Report: iv, 30 p.","startPage":"1","endPage":"30","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079633","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":328862,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1164/coverthb.jpg"},{"id":328863,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1164/ofr20161164.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1164"}],"country":"United States","state":"Oregon","county":"Klamath County","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 43.06086137134326\n ],\n [\n -121.13525390625,\n 42.706659563510385\n ],\n [\n -120.750732421875,\n 41.68932225997044\n ],\n [\n -121.761474609375,\n 41.492120839687786\n ],\n [\n -122.58544921875,\n 41.3025710943056\n ],\n [\n -123.50830078125,\n 40.48873742102282\n ],\n [\n -124.288330078125,\n 40.85537053192496\n ],\n [\n -123.870849609375,\n 42.00848901572399\n ],\n [\n -123.431396484375,\n 41.902277040963696\n ],\n [\n -123.277587890625,\n 42.04113400940809\n ],\n [\n -122.29980468749999,\n 43.06086137134326\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/
Understanding karst aquifers, for purposes of their management and protection, poses unique challenges. Karst aquifers are characterized by groundwater flow through conduits (tertiary porosity), and (or) layers with interconnected pores (secondary porosity) and through intergranular porosity (primary or matrix porosity). Since the late 1960s, advances have been made in the development of numerical computer codes and the use of mathematical model applications towards the understanding of dual (primary [matrix] and secondary [fractures and conduits]) porosity groundwater flow processes, as well as characterization and management of karst aquifers. The Floridan aquifer system (FAS) in Florida and parts of Alabama, Georgia, and South Carolina is composed of a thick sequence of predominantly carbonate rocks. Karst features are present over much of its area, especially in Florida where more than 30 first-magnitude springs occur, numerous sinkholes and submerged conduits have been mapped, and numerous circular lakes within sinkhole depressions are present. Different types of mathematical models have been applied for simulation of the FAS. Most of these models are distributed parameter models based on the assumption that, like a sponge, water flows through connected pores within the aquifer system and can be simulated with the same mathematical methods applied to flow through sand and gravel aquifers; these models are usually referred to as porous-equivalent media models. The partial differential equation solved for groundwater flow is the potential flow equation of fluid mechanics, which is used when flow is dominated by potential energy and has been applied for many fluid problems in which kinetic energy terms are dropped from the differential equation solved. In many groundwater model codes (basic MODFLOW), it is assumed that the water has a constant temperature and density and that flow is laminar, such that kinetic energy has minimal impact on flow. Some models have been developed that incorporate the submerged conduits as a one-dimensional pipe network within the aquifer rather than as discrete, extremely transmissive features in a porous-equivalent medium; these submerged conduit models are usually referred to as hybrid models and may include the capability to simulate both laminar and turbulent flow in the one-dimensional pipe network. Comparisons of the application of a porous-equivalent media model with and without turbulence (MODFLOW-Conduit Flow Process mode 2 and basic MODFLOW, respectively) and a hybrid (MODFLOW-Conduit Flow Process mode 1) model to the Woodville Karst Plain near Tallahassee, Florida, indicated that for annual, monthly, or seasonal average hydrologic conditions, all methods met calibration criteria (matched observed groundwater levels and average flows). Thus, the increased effort required, such as the collection of data on conduit location, to develop a hybrid model and its increased computational burden, is not necessary for simulation of average hydrologic conditions (non-laminar flow effects on simulated head and spring discharge were minimal). However, simulation of a large storm event in the Woodville Karst Plain with daily stress periods indicated that turbulence is important for matching daily springflow hydrographs. Thus, if matching streamflow hydrographs over a storm event is required, the simulation of non-laminar flow and the location of conduits are required. The main challenge in application of the methods and approaches for developing hybrid models relates to the difficulty of mapping conduit networks or having high-quality datasets to calibrate these models. Additionally, hybrid models have long simulation times, which can preclude the use of parameter estimation for calibration. Simulation of contaminant transport that does not account for preferential flow through conduits or extremely permeable zones in any approach is ill-advised. Simulation results in other karst aquifers or other parts of the FAS may differ from the comparison demonstrated herein.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165116","collaboration":"A product of the Water Use and Availability Science Program","usgsCitation":"Kuniansky, E.L., 2016, Simulating groundwater flow in karst aquifers with distributed parameter models—Comparison of porous-equivalent media and hybrid flow approaches: U.S. Geological Survey Scientific Investigations Report 2016–5116, 14 p., https://dx.doi.org/10.3133/sir20165116.","productDescription":"Report: v, 14 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-071317","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":328727,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5116/sir20165116.pdf","text":"Report","size":"3.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5116"},{"id":328833,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7PK0D87","text":"USGS data release - MODFLOW and MODFLOW Conduit Flow Process data sets for simulation experiments of the Woodville Karst Plain, near Tallahassee, Florida with three different approaches and different stress periods","description":"SIR 2016–5116 Data Release"},{"id":328726,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5116/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Woodville Karst Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.4903564453125,\n 30.04532159026885\n ],\n [\n -84.4903564453125,\n 30.456368670179007\n ],\n [\n -84.06875610351562,\n 30.456368670179007\n ],\n [\n -84.06875610351562,\n 30.04532159026885\n ],\n [\n -84.4903564453125,\n 30.04532159026885\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Chief, Caribbean-Florida Water Science Center-Florida
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559–6302
Critically endangered species that have undergone severe population bottlenecks often have little remaining genetic variation, making it difficult to reconstruct population histories to apply in reintroduction and recovery strategies. By using ancient DNA techniques, it is possible to combine genetic evidence from the historical population with contemporary samples to provide a more complete picture of a species' genetic variation across its historical range and through time. Applying this approach, we examined changes in the mitochondrial DNA (mtDNA) control region (526 base pairs) of the endangered California Condor (Gymnogyps californianus). Results showed a >80% reduction in unique haplotypes over the past 2 centuries. We found no spatial sorting of haplotypes in the historical population; the periphery of the range contained haplotypes that were common throughout the historical range. Direct examination of mtDNA from California Condor museum specimens provided a new window into historical population connectivity and genetic diversity showing: (1) a substantial loss of haplotypes, which is consistent with the hypothesis that condors were relatively abundant in the nineteenth century, but declined rapidly as a result of human-caused mortality; and (2) no evidence of historical population segregation, meaning that the available genetic data offer no cause to avoid releasing condors in unoccupied portions of their historical range.
","language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-16-35.1","usgsCitation":"D'Elia, J., Haig, S.M., Mullins, T.D., and Miller, M.P., 2016, Ancient DNA reveals substantial genetic diversity in the California Condor (Gymnogyps californianus) prior to a population bottleneck: The Condor, v. 118, no. 4, p. 703-714, https://doi.org/10.1650/CONDOR-16-35.1.","productDescription":"12 p.","startPage":"703","endPage":"714","ipdsId":"IP-061910","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":470559,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-16-35.1","text":"Publisher Index Page"},{"id":328843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"118","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c870","contributors":{"authors":[{"text":"D'Elia, Jesse","contributorId":63152,"corporation":false,"usgs":true,"family":"D'Elia","given":"Jesse","affiliations":[],"preferred":false,"id":649271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":649272,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D. 0000-0001-8948-9604 tom_mullins@usgs.gov","orcid":"https://orcid.org/0000-0001-8948-9604","contributorId":3615,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas","email":"tom_mullins@usgs.gov","middleInitial":"D.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":649273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":649274,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176534,"text":"70176534 - 2016 - Eurytemora carolleeae in the Laurentian Great Lakes revealed by phylogenetic and morphological analysis","interactions":[],"lastModifiedDate":"2021-08-25T14:48:38.912795","indexId":"70176534","displayToPublicDate":"2016-09-20T17:35:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Eurytemora carolleeae in the Laurentian Great Lakes revealed by phylogenetic and morphological analysis","title":"Eurytemora carolleeae in the Laurentian Great Lakes revealed by phylogenetic and morphological analysis","docAbstract":"In the Laurentian Great Lakes, specimens of Eurytemora have been reported asEurytemora affinis since its invasion in the late 1950s. During an intensive collection of aquatic invertebrates for morphological and molecular identification in Western Lake Erie in 2012-2013, several specimens of Eurytemora were collected. Analysis of these specimens identified them as the recently described species Eurytemora carolleeaeAlekseev and Souissi 2011. This result led us to assess E. carolleeae’s identifying features, geographic distribution and historical presence in the Laurentian Great Lakes in view of its recent description in 2011. Cytochrome oxidase I (COI) DNA sequences ofEurytemora specimens were identified as closer (2 - 4% different) to recently describedE. carolleeae than to most E. affinis sequences (14% different). Eurytemora from other areas of the Great Lakes and from North American rivers as far west as South Dakota (Missouri River) and east to Delaware (Christina River) also keyed to E. carolleeae. Morphological analysis of archival specimens from 1962 and from all the Great Lakes was identified as E. carolleeae. Additionally, Eurytemora drawings in previous publications were reassessed to determine if the species was E. carolleeae and are reported here. Additional morphological characters that may distinguish North AmericanE. carolleeae from other taxa are also described. We conclude that E. carolleeae is the correct name for the species of Eurytemora that has inhabited the Great Lakes since its invasion, as established by both morphological and COI sequence comparisons to reference keys and sequence databases in present and archival specimens.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2016.04.001","usgsCitation":"Vasquez, A., Hudson, P.L., Fujimoto, M., Keeler, K.M., Dieter, P.M., and Ram, J.L., 2016, Eurytemora carolleeae in the Laurentian Great Lakes revealed by phylogenetic and morphological analysis: Journal of Great Lakes Research, v. 42, no. 4, p. 802-811, https://doi.org/10.1016/j.jglr.2016.04.001.","productDescription":"10 p.","startPage":"802","endPage":"811","ipdsId":"IP-071264","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":462077,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5047287","text":"External Repository"},{"id":328782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.9814453125,\n 44.43377984606822\n ],\n [\n -78.0029296875,\n 44.15068115978094\n ],\n [\n -79.4970703125,\n 44.902577996288876\n ],\n [\n -82.0458984375,\n 46.5286346952717\n ],\n [\n -83.935546875,\n 46.37725420510028\n ],\n [\n -84.55078125,\n 47.635783590864854\n ],\n [\n -84.8583984375,\n 48.10743118848039\n ],\n [\n -85.78125,\n 48.16608541901253\n ],\n [\n -86.30859375,\n 48.8936153614802\n ],\n [\n -88.06640625,\n 49.1242192485914\n ],\n [\n -90.7470703125,\n 47.90161354142077\n ],\n [\n -92.46093749999999,\n 46.76996843356982\n ],\n [\n -90.9228515625,\n 46.73986059969267\n ],\n [\n -90.9228515625,\n 46.437856895024204\n ],\n [\n -88.2861328125,\n 47.15984001304432\n ],\n [\n -88.505859375,\n 46.70973594407157\n ],\n [\n -86.66015624999999,\n 46.40756396630067\n ],\n [\n -85.1220703125,\n 46.58906908309182\n ],\n [\n -84.0234375,\n 46.07323062540835\n ],\n [\n -84.638671875,\n 46.07323062540835\n ],\n [\n -86.0888671875,\n 46.07323062540835\n ],\n [\n -87.5830078125,\n 45.767522962149876\n ],\n [\n -88.154296875,\n 44.49650533109348\n ],\n [\n -87.2314453125,\n 44.933696389694674\n ],\n [\n -87.7587890625,\n 43.8028187190472\n ],\n [\n -88.11035156249999,\n 43.229195113965005\n ],\n [\n -87.71484375,\n 41.73852846935917\n ],\n [\n -86.923828125,\n 41.57436130598913\n ],\n [\n -86.0888671875,\n 42.71473218539458\n ],\n [\n -86.3525390625,\n 43.83452678223682\n ],\n [\n -85.78125,\n 44.96479793033101\n ],\n [\n -84.8583984375,\n 45.644768217751924\n ],\n [\n -83.4521484375,\n 45.120052841530544\n ],\n [\n -83.3203125,\n 44.276671273775186\n ],\n [\n -83.8916015625,\n 43.70759350405294\n ],\n [\n -83.8916015625,\n 43.51668853502906\n ],\n [\n -83.0126953125,\n 44.02442151965934\n ],\n [\n -82.705078125,\n 43.32517767999296\n ],\n [\n -82.4853515625,\n 42.74701217318067\n ],\n [\n -81.6943359375,\n 43.197167282501276\n ],\n [\n -81.2548828125,\n 44.43377984606822\n ],\n [\n -81.38671875,\n 44.84029065139799\n ],\n [\n -80.37597656249999,\n 44.37098696297173\n ],\n [\n -79.98046875,\n 44.37098696297173\n ],\n [\n -78.662109375,\n 44.02442151965934\n ],\n [\n -79.6728515625,\n 43.42100882994726\n ],\n [\n -78.9697265625,\n 42.87596410238256\n ],\n [\n -81.03515625,\n 42.5530802889558\n ],\n [\n -82.6611328125,\n 42.00032514831621\n ],\n [\n -83.27636718749999,\n 42.032974332441405\n ],\n [\n -83.408203125,\n 41.44272637767212\n ],\n [\n -82.177734375,\n 41.343824581185686\n ],\n [\n -79.6728515625,\n 42.261049162113856\n ],\n [\n -79.013671875,\n 42.65012181368022\n ],\n [\n -78.8818359375,\n 43.26120612479979\n ],\n [\n -77.080078125,\n 43.26120612479979\n ],\n [\n -76.1572265625,\n 43.51668853502906\n ],\n [\n -75.9814453125,\n 44.43377984606822\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c876","contributors":{"authors":[{"text":"Vasquez, Adrian A.","contributorId":174735,"corporation":false,"usgs":false,"family":"Vasquez","given":"Adrian A.","affiliations":[],"preferred":false,"id":649140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudson, Patrick L. 0000-0002-7646-443X phudson@usgs.gov","orcid":"https://orcid.org/0000-0002-7646-443X","contributorId":5616,"corporation":false,"usgs":true,"family":"Hudson","given":"Patrick","email":"phudson@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujimoto, Masanori","contributorId":151003,"corporation":false,"usgs":false,"family":"Fujimoto","given":"Masanori","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":649142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeler, Kevin M. 0000-0002-8118-0060 kkeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-8118-0060","contributorId":4377,"corporation":false,"usgs":true,"family":"Keeler","given":"Kevin","email":"kkeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dieter, Patricia M. 0000-0003-1686-2679 parmenio@usgs.gov","orcid":"https://orcid.org/0000-0003-1686-2679","contributorId":5289,"corporation":false,"usgs":true,"family":"Dieter","given":"Patricia","email":"parmenio@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":649144,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ram, Jeffrey L.","contributorId":33659,"corporation":false,"usgs":true,"family":"Ram","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":649145,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70175981,"text":"ds1016 - 2016 - Toxicity of bed sediments from the Niagara River Area of Concern and tributaries, New York, to Chironomus dilutus and Hyalella azteca, 2014-15","interactions":[],"lastModifiedDate":"2016-09-20T09:44:30","indexId":"ds1016","displayToPublicDate":"2016-09-20T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1016","title":"Toxicity of bed sediments from the Niagara River Area of Concern and tributaries, New York, to Chironomus dilutus and Hyalella azteca, 2014-15","docAbstract":"The Niagara River was designated as an Area of Concern in 1987 on both the United States and Canadian sides of the international boundary line because past industrial discharges and hazardous waste sites had caused extensive degradation of aquatic habitats. The degradation of the “benthos”, or the benthic macroinvertebrate community, was identified as one of seven beneficial use impairments caused by contaminated bed sediments. The U.S. Geological Survey and the New York State Department of Environmental Conservation, in cooperation with the U.S. Environmental Protection Agency, conducted a study in 2014 and 2015 to gather more extensive data on (a) the toxicity of bed sediments and (b) the status of macroinvertebrate communities on the main stem and tributaries of the Niagara River. This report addresses the first component of that study (toxicity of bed sediments), and summarizes results from laboratory toxicity tests that compare the survival and growth of two macroinvertebrate species between bed sediments from study sites and laboratory controls. Sediment toxicity was negligible at most sites, however poor performance of one or both test species in bed sediments from several tributary sites suggests that the quality of sediments may be adversely affecting benthic macroinvertebrate communities in some tributaries to the Niagara River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1016","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the New York State Department of Environmental Conservation","usgsCitation":"George, S.D., Baldigo, B.P., and Duffy, B.T., 2016, Toxicity of bed sediments from the Niagara River Area of Concern and tributaries, New York, to Chironomus dilutus and Hyalella azteca, 2014–15: U.S. Geological Survey Data Series 1016, 8 p., https://dx.doi.org/10.3133/ds1016.","productDescription":"Report: iv, 8 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074812","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":438546,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FB5129","text":"USGS data release","linkHelpText":"Data from 10-day sediment toxicity tests of bed sediments from the Niagara River Area of Concern and tributaries, New York, with Chironomus dilutus and Hyalella azteca, 201415"},{"id":328719,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7FB5129","text":"USGS data release ","description":"USGS data release ","linkHelpText":"Data from 10-day sediment toxicity tests of bed sediments from the Niagara River Area of Concern and tributaries, New York, with Chironomus dilutus and Hyalella azteca, 2014-15 "},{"id":328717,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1016/coverthb.jpg"},{"id":328718,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1016/ds1016.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1016"}],"country":"United States","state":"New York","otherGeospatial":"Niagara River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.22927856445312,\n 42.8054768278603\n ],\n [\n -79.22927856445312,\n 43.29320031385282\n ],\n [\n -78.72665405273438,\n 43.29320031385282\n ],\n [\n -78.72665405273438,\n 42.8054768278603\n ],\n [\n -79.22927856445312,\n 42.8054768278603\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
(518) 285-5602
Or visit our Website at:
http://ny.water.usgs.gov
An investigation into the magnitude and frequency of floods in Washington State computed the annual exceedance probability (AEP) statistics for 648 U.S. Geological Survey unregulated streamgages in and near the borders of Washington using the recorded annual peak flows through water year 2014. This is an updated report from a previous report published in 1998 that used annual peak flows through the water year 1996. New in this report, a regional skew coefficient was developed for the Pacific Northwest region that includes areas in Oregon, Washington, Idaho and western Montana within the Columbia River drainage basin south of the United States-Canada border, the coastal areas of Oregon and western Washington, and watersheds draining into Puget Sound, Washington. The skew coefficient is an important term in the Log Pearson Type III equation used to define the distribution of the log-transformed annual peaks. The Expected Moments Algorithm was used to fit historical and censored peak-flow data to the log Pearson Type III distribution. A Multiple Grubb-Beck test was employed to censor low outliers of annual peak flows to improve on the frequency distribution. This investigation also includes a section on observed trends in annual peak flows that showed significant trends (p-value < 0.05) in 21 of 83 long-term sites, but with small magnitude Kendall tau values suggesting a limited monotonic trend in the time series of annual peaks. Most of the sites with a significant trend in western Washington were positive and all the sites with significant trends (three sites) in eastern Washington were negative.
Multivariate regression analysis with measured basin characteristics and the AEP statistics at long-term, unregulated, and un-urbanized (defined as drainage basins with less than 5 percent impervious land cover for this investigation) streamgages within Washington and some in Idaho and Oregon that are near the Washington border was used to develop equations to estimate AEP statistics at ungaged basins. Washington was divided into four regions to improve the accuracy of the regression equations; a set of equations for eight selected AEPs and for each region were constructed. Selected AEP statistics included the annual peak flows that equaled or exceeded 50, 20, 10, 4, 2, 1, 0.5 and 0.2 percent of the time equivalent to peak flows for peaks with a 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. Annual precipitation and drainage area were the significant basin characteristics in the regression equations for all four regression regions in Washington and forest cover was significant for the two regression regions in eastern Washington. Average standard error of prediction for the regional regression equations ranged from 70.19 to 125.72 percent for Regression Regions 1 and 2 on the eastern side of the Cascade Mountains and from 43.22 to 58.04 percent for Regression Regions 3 and 4 on the western side of the Cascade Mountains. The pseudo coefficient of determination (where a value of 100 signifies a perfect regression model) ranged from 68.39 to 90.68 for Regression Regions 1 and 2, and 92.35 to 95.44 for Regions 3 and 4.
The calculated AEP statistics for the streamgages and the regional regression equations are expected to be incorporated into StreamStats after the publication of this report. StreamStats is the interactive Web-based map tool created by the U.S. Geological Survey to allow the user to choose a streamgage and obtain published statistics or choose ungaged locations where the program automatically applies the regional regression equations and computes the estimates of the AEP statistics.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165118","collaboration":"Prepared in cooperation with the Washington State Department of Transportation and the Washington State Department of Ecology","usgsCitation":"Mastin, M.C., Konrad, C.P., Veilleux, A.G., and Tecca, A.E., 2016, Magnitude, frequency, and trends of floods at gaged and ungaged sites in Washington, based on data through water year 2014 (ver 1.2, November 2017): U.S. Geological Survey Scientific Investigations Report 2016–5118, 70 p., https://dx.doi.org/10.3133/sir20165118.","productDescription":"Report: vi, 69 p.; 3 Tables","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075256","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329272,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5118/versionHist.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5118 Version History"},{"id":328745,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5118/sir20165118.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5118"},{"id":328747,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5118/sir20165118_table5.xlsx","text":"Table 5","size":"220 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5118 Table 5"},{"id":328746,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5118/sir20165118_table2.xlsx","text":"Table 2","size":"105 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5118 Table 2"},{"id":328776,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2016/5118/sir20165118_floodqtools.xlsm","text":"Flood Q Tools","size":"880 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5118 Flood Q Tools"},{"id":328748,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5118/sir20165118_table8.xlsx","text":"Table 8","size":"458 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5118 Table 8"},{"id":328744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5118/coverthb2.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-122.519535,48.288314],[-122.551793,48.281512],[-122.584086,48.297987],[-122.618466,48.294159],[-122.626757,48.288991],[-122.620748,48.282961],[-122.623779,48.269431],[-122.652639,48.265081],[-122.66921,48.240614],[-122.668385,48.223967],[-122.628352,48.222467],[-122.606406,48.208262],[-122.588138,48.18594],[-122.558205,48.119579],[-122.571853,48.102143],[-122.54512,48.05255],[-122.513994,48.059077],[-122.511081,48.075301],[-122.525422,48.096537],[-122.513276,48.097538],[-122.491104,48.094242],[-122.431266,48.045001],[-122.376259,48.034457],[-122.373263,48.000791],[-122.353611,47.981433],[-122.349597,47.958796],[-122.358812,47.93742],[-122.376837,47.923703],[-122.380497,47.904023],[-122.397349,47.912401],[-122.431035,47.914732],[-122.445519,47.930226],[-122.44076,47.951845],[-122.446682,47.963155],[-122.47266,47.988449],[-122.501257,47.987089],[-122.521219,47.972997],[-122.546824,47.967215],[-122.552053,47.973644],[-122.542924,47.996404],[-122.58178,48.010386],[-122.607342,48.030992],[-122.593621,48.0472],[-122.594922,48.056318],[-122.614028,48.072788],[-122.598301,48.110616],[-122.609568,48.15186],[-122.633167,48.163281],[-122.677337,48.154587],[-122.693084,48.181509],[-122.763042,48.215342],[-122.770045,48.224395],[-122.752563,48.260061],[-122.732022,48.279425],[-122.72259,48.304268],[-122.673731,48.354683],[-122.664928,48.374823],[-122.664659,48.401508],[-122.634991,48.404244],[-122.63582,48.395128],[-122.609715,48.411565],[-122.60198,48.409907],[-122.595351,48.3972],[-122.585038,48.395166],[-122.585162,48.353304],[-122.551334,48.342138],[-122.506568,48.310041],[-122.505828,48.297677],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.452399,47.503471],[-122.460027,47.48686],[-122.433385,47.46643],[-122.439415,47.458633],[-122.437656,47.407424],[-122.395054,47.399277],[-122.373628,47.388718],[-122.437809,47.365606],[-122.453997,47.343337],[-122.469702,47.344623],[-122.493122,47.330253],[-122.51885,47.33332],[-122.528128,47.345542],[-122.517797,47.368678],[-122.526733,47.398581],[-122.514703,47.414048],[-122.513328,47.449106],[-122.497862,47.475915],[-122.482739,47.483133],[-122.474684,47.511068]]],[[[-122.695907,48.737273],[-122.663259,48.697077],[-122.644901,48.691389],[-122.618225,48.670721],[-122.609576,48.645018],[-122.635299,48.651846],[-122.673538,48.680809],[-122.691795,48.711498],[-122.718833,48.716818],[-122.722262,48.731624],[-122.715709,48.748672],[-122.695907,48.737273]]],[[[-123.035393,49.002154],[-123.021459,48.977299],[-123.028091,48.973943],[-123.083834,48.976139],[-123.090546,49.001976],[-123.035393,49.002154]]],[[[-122.800217,48.60169],[-122.804869,48.595932],[-122.801096,48.585425],[-122.770349,48.558106],[-122.788503,48.530393],[-122.787347,48.523012],[-122.777467,48.517799],[-122.779124,48.508911],[-122.817912,48.483888],[-122.81973,48.458843],[-122.803521,48.428748],[-122.812208,48.422326],[-122.874135,48.418196],[-122.893646,48.422655],[-122.889016,48.435947],[-122.913888,48.443231],[-122.928004,48.439966],[-122.91646,48.453263],[-122.926901,48.460874],[-122.962009,48.451161],[-123.039156,48.460003],[-123.067675,48.479497],[-123.119451,48.492576],[-123.141478,48.505291],[-123.163234,48.529544],[-123.16147,48.547618],[-123.176266,48.562131],[-123.173061,48.579086],[-123.184941,48.58697],[-123.197754,48.586216],[-123.203026,48.596178],[-123.178425,48.622115],[-123.107362,48.622451],[-123.098462,48.612834],[-123.101552,48.59782],[-123.074611,48.591816],[-123.048403,48.569216],[-123.015046,48.560821],[-122.987296,48.561895],[-122.98611,48.569984],[-122.995026,48.578162],[-123.016647,48.580244],[-123.034101,48.591767],[-123.023433,48.599477],[-123.04653,48.61149],[-123.048652,48.621002],[-123.023495,48.634001],[-123.009924,48.655064],[-122.949116,48.693398],[-122.942367,48.706723],[-122.894599,48.71503],[-122.833124,48.698173],[-122.800267,48.67962],[-122.743049,48.661991],[-122.755031,48.649512],[-122.792147,48.633502],[-122.809622,48.619035],[-122.800217,48.60169]]],[[[-123.197953,48.68466],[-123.186076,48.684917],[-123.14799,48.668001],[-123.106165,48.633473],[-123.134956,48.63724],[-123.215917,48.669352],[-123.237148,48.683466],[-123.236567,48.68895],[-123.212892,48.689713],[-123.197953,48.68466]]],[[[-123.025486,48.717966],[-123.007511,48.718863],[-123.005086,48.694342],[-123.021215,48.681416],[-123.042337,48.675663],[-123.03636,48.69008],[-123.070427,48.699971],[-123.040179,48.717296],[-123.025486,48.717966]]],[[[-122.649405,48.588457],[-122.610841,48.561146],[-122.578856,48.54813],[-122.572967,48.529028],[-122.599948,48.536904],[-122.635738,48.526021],[-122.649256,48.528769],[-122.654342,48.537956],[-122.649405,48.588457]]],[[[-122.714512,48.60878],[-122.694672,48.596602],[-122.670638,48.568812],[-122.68944,48.543903],[-122.722407,48.540606],[-122.73048,48.565602],[-122.73944,48.573893],[-122.739898,48.583949],[-122.714512,48.60878]]],[[[-122.699266,48.621115],[-122.674173,48.629944],[-122.657016,48.609891],[-122.676796,48.610055],[-122.699266,48.621115]]],[[[-122.334524,48.018916],[-122.321721,48.019977],[-122.303455,48.005603],[-122.326115,48.010295],[-122.334524,48.018916]]],[[[-122.418268,47.320614],[-122.324833,47.348521],[-122.328434,47.400621],[-122.348035,47.415921],[-122.355135,47.441921],[-122.383136,47.450521],[-122.368036,47.459221],[-122.361336,47.481421],[-122.396538,47.51522],[-122.398338,47.55012],[-122.421139,47.57602],[-122.387139,47.59572],[-122.370167,47.583087],[-122.342937,47.59122],[-122.339513,47.599113],[-122.344937,47.60912],[-122.367819,47.624213],[-122.414645,47.639766],[-122.429841,47.658919],[-122.393248,47.701602],[-122.38044,47.709119],[-122.37314,47.729219],[-122.382641,47.749119],[-122.380241,47.758519],[-122.396422,47.777927],[-122.394944,47.803318],[-122.33595,47.852306],[-122.328546,47.897917],[-122.311927,47.923703],[-122.307048,47.949117],[-122.249007,47.959507],[-122.230046,47.970917],[-122.226346,47.976417],[-122.232391,47.987713],[-122.224979,48.016626],[-122.231761,48.029876],[-122.281087,48.049793],[-122.326119,48.092877],[-122.343241,48.097631],[-122.363842,48.12393],[-122.370253,48.164809],[-122.362044,48.187568],[-122.372492,48.193022],[-122.395499,48.228551],[-122.433767,48.23655],[-122.449605,48.232598],[-122.45371,48.228859],[-122.449513,48.214736],[-122.441731,48.211776],[-122.45493,48.196639],[-122.478535,48.188087],[-122.479008,48.175703],[-122.442383,48.130841],[-122.379481,48.087384],[-122.358375,48.056133],[-122.377114,48.057568],[-122.400692,48.085255],[-122.4675,48.130353],[-122.489986,48.120617],[-122.512031,48.133931],[-122.53722,48.183745],[-122.538916,48.209683],[-122.530996,48.249821],[-122.503786,48.257045],[-122.480925,48.251706],[-122.463962,48.270541],[-122.406516,48.25183],[-122.395328,48.257187],[-122.392058,48.269628],[-122.371693,48.287839],[-122.408718,48.326413],[-122.442678,48.337934],[-122.475529,48.359912],[-122.507437,48.364666],[-122.533452,48.383409],[-122.539449,48.39719],[-122.554536,48.40604],[-122.558403,48.426758],[-122.551221,48.439465],[-122.557298,48.444438],[-122.575254,48.443333],[-122.581607,48.429244],[-122.61448,48.41488],[-122.649839,48.408526],[-122.674158,48.424726],[-122.678928,48.439466],[-122.654844,48.454087],[-122.657753,48.47294],[-122.664623,48.478128],[-122.689121,48.476849],[-122.700603,48.457632],[-122.712322,48.464143],[-122.712981,48.47879],[-122.701644,48.497622],[-122.684521,48.509123],[-122.671386,48.50398],[-122.606961,48.522152],[-122.599951,48.520946],[-122.598469,48.512169],[-122.568071,48.50821],[-122.537355,48.466749],[-122.500721,48.460887],[-122.471832,48.470724],[-122.46967,48.474975],[-122.483501,48.49243],[-122.485288,48.528106],[-122.498463,48.556206],[-122.504428,48.564775],[-122.531978,48.568644],[-122.534719,48.574246],[-122.495904,48.575927],[-122.478431,48.559303],[-122.44456,48.570115],[-122.425271,48.599522],[-122.448702,48.622624],[-122.46425,48.625717],[-122.500308,48.656163],[-122.519172,48.713095],[-122.495301,48.737328],[-122.490401,48.751128],[-122.510902,48.757728],[-122.535803,48.776128],[-122.567498,48.779185],[-122.596844,48.771492],[-122.637146,48.735708],[-122.626287,48.72093],[-122.612562,48.714932],[-122.605733,48.701066],[-122.615169,48.693839],[-122.630422,48.696625],[-122.673472,48.733082],[-122.647443,48.773998],[-122.646777,48.785011],[-122.693683,48.804475],[-122.699303,48.789063],[-122.709815,48.786205],[-122.709169,48.817829],[-122.717073,48.84719],[-122.793175,48.892927],[-122.751289,48.911239],[-122.746596,48.930731],[-122.766096,48.941955],[-122.787539,48.931702],[-122.821631,48.941369],[-122.817226,48.95597],[-122.774276,48.991038],[-122.756318,48.996881],[-122.75802,49.002357],[-121.751252,48.997399],[-117.032351,48.999188],[-117.042623,47.761223],[-117.039813,46.425425],[-117.034696,46.418318],[-117.046915,46.379577],[-117.062785,46.365287],[-117.062748,46.353624],[-117.055983,46.345531],[-117.023844,46.335976],[-117.020663,46.314793],[-116.986688,46.296662],[-116.991134,46.276342],[-116.966742,46.256923],[-116.955264,46.23088],[-116.965841,46.203417],[-116.92187,46.167808],[-116.950276,46.123464],[-116.955263,46.102237],[-116.976957,46.09667],[-116.982479,46.089389],[-116.978938,46.080007],[-116.957372,46.075449],[-116.942656,46.061],[-116.91718,45.996575],[-118.987129,45.999855],[-119.027056,45.969134],[-119.12612,45.932859],[-119.19553,45.92787],[-119.25715,45.939926],[-119.322509,45.933183],[-119.364396,45.921605],[-119.450256,45.917354],[-119.487829,45.906307],[-119.524632,45.908605],[-119.571584,45.925456],[-119.600549,45.919581],[-119.623393,45.905639],[-119.669877,45.856867],[-119.772927,45.845578],[-119.802655,45.84753],[-119.907461,45.828135],[-119.965744,45.824365],[-120.07015,45.785152],[-120.141352,45.773152],[-120.170453,45.761951],[-120.210754,45.725951],[-120.282156,45.72125],[-120.40396,45.699249],[-120.482362,45.694449],[-120.505863,45.700048],[-120.559465,45.738348],[-120.591166,45.746547],[-120.634968,45.745847],[-120.68937,45.715847],[-120.855674,45.671545],[-120.895575,45.642945],[-120.913476,45.640045],[-120.943977,45.656445],[-120.983478,45.648344],[-121.06437,45.652549],[-121.084933,45.647893],[-121.120064,45.623134],[-121.117052,45.618117],[-121.145534,45.607886],[-121.183841,45.606441],[-121.196556,45.616689],[-121.200367,45.649829],[-121.215779,45.671238],[-121.33777,45.704949],[-121.372574,45.703111],[-121.401739,45.692887],[-121.423592,45.69399],[-121.462849,45.701367],[-121.499153,45.720846],[-121.533106,45.726541],[-121.631167,45.704657],[-121.668362,45.705082],[-121.707358,45.694809],[-121.735104,45.694039],[-121.811304,45.706761],[-121.867167,45.693277],[-121.901855,45.670716],[-121.900858,45.662009],[-121.908267,45.654399],[-121.935149,45.644169],[-121.955734,45.643559],[-121.963547,45.632784],[-121.983038,45.622812],[-122.044374,45.609516],[-122.101675,45.583516],[-122.183695,45.577696],[-122.2017,45.564141],[-122.266701,45.543841],[-122.331502,45.548241],[-122.352802,45.569441],[-122.380302,45.575941],[-122.438674,45.563585],[-122.548149,45.596768],[-122.675008,45.618039],[-122.76381,45.657138],[-122.774511,45.680437],[-122.760108,45.734413],[-122.761451,45.759163],[-122.769532,45.780583],[-122.795605,45.81],[-122.785026,45.867699],[-122.81151,45.912725],[-122.806193,45.932416],[-122.813998,45.960984],[-122.837638,45.98082],[-122.856158,46.014469],[-122.878092,46.031281],[-122.884478,46.06028],[-122.904119,46.083734],[-122.962681,46.104817],[-123.004233,46.133823],[-123.041297,46.146351],[-123.115904,46.185268],[-123.166414,46.188973],[-123.280166,46.144843],[-123.371433,46.146372],[-123.430847,46.181827],[-123.427629,46.229348],[-123.474844,46.267831],[-123.501245,46.271004],[-123.547659,46.259109],[-123.547636,46.265595],[-123.613544,46.259988],[-123.669501,46.266832],[-123.679125,46.272502],[-123.680574,46.296025],[-123.700764,46.305278],[-123.724273,46.301161],[-123.727913,46.289661],[-123.741478,46.290274],[-123.766682,46.273499],[-123.806139,46.283588],[-123.875525,46.239787],[-123.919581,46.251217],[-123.954353,46.277001],[-123.974509,46.303063],[-124.001264,46.31326],[-124.020551,46.315737],[-124.029924,46.308312],[-124.044018,46.275925],[-124.060961,46.278761],[-124.080671,46.267239],[-124.064624,46.326899],[-124.057425,46.409315],[-124.057024,46.493338],[-124.068655,46.634879],[-124.062715,46.642582],[-124.048444,46.645827],[-124.035874,46.630822],[-124.052708,46.622796],[-124.050842,46.617421],[-124.023566,46.582559],[-124.031737,46.496375],[-124.026032,46.462978],[-123.990615,46.463019],[-123.99268,46.488617],[-123.983688,46.498542],[-123.968044,46.473497],[-123.943667,46.477197],[-123.921192,46.507731],[-123.896703,46.522665],[-123.894254,46.537028],[-123.920247,46.567343],[-123.928861,46.588875],[-123.955556,46.60357],[-123.960642,46.636364],[-123.921913,46.650262],[-123.923269,46.672708],[-123.851356,46.70256],[-123.84621,46.716795],[-123.87668,46.730657],[-123.898641,46.750205],[-123.916371,46.741322],[-123.91285,46.730647],[-123.916874,46.726739],[-123.948683,46.725369],[-123.968564,46.736106],[-123.974994,46.733391],[-123.979655,46.724658],[-123.966886,46.705184],[-123.994242,46.707929],[-124.003458,46.702337],[-124.063117,46.733664],[-124.092176,46.741624],[-124.108078,46.836388],[-124.138225,46.905534],[-124.110641,46.91252],[-124.093392,46.901168],[-124.089286,46.867716],[-124.073113,46.861493],[-124.055085,46.870429],[-124.046344,46.893972],[-124.01366,46.90363],[-123.985082,46.921916],[-123.957493,46.921261],[-123.86018,46.948556],[-123.898245,46.971927],[-123.939214,46.969739],[-123.959185,46.981759],[-124.012218,46.985176],[-124.019727,46.991189],[-124.005248,47.003915],[-124.017035,47.011717],[-124.026345,47.030187],[-124.065856,47.04114],[-124.122057,47.04165],[-124.141517,47.035142],[-124.151288,47.021112],[-124.138035,46.970959],[-124.124386,46.94387],[-124.180111,46.926357],[-124.169113,46.994508],[-124.182802,47.134041],[-124.236349,47.287287],[-124.25359,47.30248],[-124.271193,47.305025],[-124.299943,47.34836],[-124.319379,47.355559],[-124.336724,47.415996],[-124.355955,47.545698],[-124.382215,47.632302],[-124.412106,47.691199],[-124.425195,47.738434],[-124.453927,47.765334],[-124.47657,47.769671],[-124.489737,47.816988],[-124.539927,47.836967],[-124.562363,47.866216],[-124.625512,47.887963],[-124.645442,47.935338],[-124.672427,47.964414],[-124.67083,47.982366],[-124.682157,48.035987],[-124.696542,48.069274],[-124.695114,48.087096],[-124.687101,48.098657],[-124.733174,48.163393],[-124.731746,48.169997],[-124.704153,48.184422],[-124.696111,48.198599],[-124.690389,48.219745],[-124.705031,48.238774],[-124.684677,48.255228],[-124.676319,48.295143],[-124.665908,48.299324],[-124.65894,48.331057],[-124.670072,48.341341],[-124.696703,48.349748],[-124.727022,48.371101],[-124.731828,48.381157],[-124.716947,48.389776],[-124.653243,48.390691],[-124.631108,48.376522],[-124.599278,48.381035],[-124.395593,48.288772],[-124.361351,48.287582],[-124.272017,48.25441],[-124.250882,48.264773],[-124.238582,48.262471],[-124.101773,48.216883],[-124.107215,48.200082],[-124.050734,48.177747],[-123.981032,48.164761],[-123.880068,48.160621],[-123.858821,48.154273],[-123.778122,48.155466],[-123.728736,48.1628],[-123.71835,48.158713],[-123.702743,48.166783],[-123.651408,48.156952],[-123.628819,48.139279],[-123.590839,48.134949],[-123.551131,48.151382],[-123.507235,48.131807],[-123.440128,48.142014],[-123.441972,48.124259],[-123.424668,48.118065],[-123.332699,48.11297],[-123.288265,48.121036],[-123.239129,48.118217],[-123.21719,48.127203],[-123.1644,48.165894],[-123.133445,48.177276],[-123.143229,48.156633],[-123.116479,48.150208],[-123.085154,48.127137],[-123.06621,48.120469],[-123.038727,48.081138],[-122.979413,48.09594],[-122.929095,48.096244],[-122.917942,48.091535],[-122.927975,48.06665],[-122.918602,48.058238],[-122.877641,48.047025],[-122.849273,48.053808],[-122.857727,48.065774],[-122.878255,48.076072],[-122.882013,48.100779],[-122.876282,48.110877],[-122.833173,48.134406],[-122.760448,48.14324],[-122.748911,48.117026],[-122.778466,48.106135],[-122.801399,48.087561],[-122.766648,48.04429],[-122.74229,48.049324],[-122.739271,48.069153],[-122.747389,48.070795],[-122.733257,48.091232],[-122.698465,48.103102],[-122.68724,48.101662],[-122.69222,48.087081],[-122.682264,48.042723],[-122.668942,48.032026],[-122.669868,48.017217],[-122.686898,48.008305],[-122.70184,48.016106],[-122.723374,48.008095],[-122.718082,47.987739],[-122.701294,47.972979],[-122.6788,47.96793],[-122.676215,47.958743],[-122.68445,47.939593],[-122.657722,47.931156],[-122.651063,47.920985],[-122.655085,47.905058],[-122.646494,47.894771],[-122.610341,47.887343],[-122.631857,47.874815],[-122.63636,47.866186],[-122.69376,47.868002],[-122.681602,47.850405],[-122.683742,47.838773],[-122.748061,47.800546],[-122.758498,47.746036],[-122.781682,47.70392],[-122.811929,47.679861],[-122.832139,47.695511],[-122.790619,47.792597],[-122.812616,47.840029],[-122.820178,47.835904],[-122.815027,47.807493],[-122.845612,47.777474],[-122.880462,47.720643],[-122.896524,47.674838],[-122.97244,47.6149],[-123.106486,47.45817],[-123.15598,47.355745],[-123.140169,47.347496],[-123.111298,47.362619],[-123.120234,47.39149],[-122.967284,47.585685],[-122.917103,47.620743],[-122.856611,47.649615],[-122.804498,47.653363],[-122.754186,47.671612],[-122.740159,47.736228],[-122.722686,47.748827],[-122.714801,47.768176],[-122.690562,47.778372],[-122.682015,47.800882],[-122.623192,47.836199],[-122.608105,47.856728],[-122.573672,47.857582],[-122.573098,47.874081],[-122.588235,47.912923],[-122.620316,47.931553],[-122.617022,47.938987],[-122.603861,47.940478],[-122.592184,47.922519],[-122.549072,47.919072],[-122.527593,47.905882],[-122.513986,47.880807],[-122.506122,47.831745],[-122.482529,47.815511],[-122.485214,47.804128],[-122.495346,47.79704],[-122.495458,47.786692],[-122.471402,47.765965],[-122.470333,47.757109],[-122.471844,47.749819],[-122.488491,47.743605],[-122.554454,47.745704],[-122.543161,47.710941],[-122.53094,47.704814],[-122.511196,47.708715],[-122.504604,47.699136],[-122.518277,47.65132],[-122.493205,47.635122],[-122.500357,47.617816],[-122.49824,47.598242],[-122.493933,47.588963],[-122.479089,47.583654],[-122.518367,47.57408],[-122.543118,47.556326],[-122.546611,47.52355],[-122.52305,47.524],[-122.494882,47.510265],[-122.530514,47.469041],[-122.531889,47.428827],[-122.551136,47.394456],[-122.537044,47.375896],[-122.575985,47.32642],[-122.547521,47.285344],[-122.578211,47.254804],[-122.589454,47.227618],[-122.602541,47.217506],[-122.611464,47.2181],[-122.668571,47.270449],[-122.697378,47.283969],[-122.671256,47.343774],[-122.632463,47.376394],[-122.671486,47.366876],[-122.725738,47.33047],[-122.74525,47.297158],[-122.749621,47.276408],[-122.718124,47.250045],[-122.648941,47.214531],[-122.641802,47.205013],[-122.673925,47.174675],[-122.691771,47.141958],[-122.711997,47.127681],[-122.771619,47.167109],[-122.832799,47.243412],[-122.816633,47.276457],[-122.799025,47.289306],[-122.796646,47.341654],[-122.803688,47.355071],[-122.821868,47.363069],[-122.822344,47.319763],[-122.84586,47.298405],[-122.863732,47.270221],[-122.856171,47.233788],[-122.838298,47.208353],[-122.858735,47.167955],[-122.852046,47.164359],[-122.814238,47.179482],[-122.775056,47.123114],[-122.721437,47.103179],[-122.67813,47.103866],[-122.650634,47.132738],[-122.631987,47.140589],[-122.614855,47.169143],[-122.590829,47.178107],[-122.561957,47.244099],[-122.527586,47.291531],[-122.547747,47.316403],[-122.533338,47.31662],[-122.471652,47.277321],[-122.4442,47.266723],[-122.429605,47.269707],[-122.409199,47.288556],[-122.444635,47.300421],[-122.418268,47.320614]]]]},\"properties\":{\"name\":\"Washington\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: Originally post September 20, 2016; Version 1.1: October 4, 2016; Version 1.2: November 2017","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
We present results of population genetic analyses performed on Oregon silverspot butterflies (OSB; Speyeria zerene hippolyta) in western Oregon and northwestern California. We used DNA sequences from a 561-base pair region of the mitochondrial cytochrome oxidase subunit I (COI) gene for a dataset comprised of 112 S. z. hippolyta and 32 S. z. gloriosa individuals collected at 9 locations in western Oregon and northwestern California. The most pertinent findings thus far are summarized as follows:
Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Data acquired by Harris Corporation’s (Melbourne, FL, USA) Geiger-mode IntelliEarth™ sensor and Sigma Space Corporation’s (Lanham-Seabrook, MD, USA) Single Photon HRQLS sensor were evaluated and compared to accepted 3D Elevation Program (3DEP) data and survey ground control to assess the suitability of these new technologies for the 3DEP. While not able to collect data currently to meet USGS lidar base specification, this is partially due to the fact that the specification was written for linear-mode systems specifically. With little effort on part of the manufacturers of the new lidar systems and the USGS Lidar specifications team, data from these systems could soon serve the 3DEP program and its users. Many of the shortcomings noted in this study have been reported to have been corrected or improved upon in the next generation sensors.
","language":"English","publisher":"MDPI","doi":"10.3390/rs8090767","usgsCitation":"Stoker, J.M., Abdullah, Q., Nayegandhi, A., and Winehouse, J., 2016, Evaluation of single photon and Geiger mode Lidar for the 3D Elevation Program: Remote Sensing, v. 8, no. 9, Article 767; 16 p., https://doi.org/10.3390/rs8090767.","productDescription":"Article 767; 16 p.","ipdsId":"IP-077259","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":470564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs8090767","text":"Publisher Index Page"},{"id":328736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"57f7c63de4b0bc0bec09c88e","contributors":{"authors":[{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":649023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abdullah, Qassim","contributorId":174668,"corporation":false,"usgs":false,"family":"Abdullah","given":"Qassim","email":"","affiliations":[{"id":27496,"text":"Woolpert","active":true,"usgs":false}],"preferred":false,"id":649024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":649025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winehouse, Jayna","contributorId":174696,"corporation":false,"usgs":false,"family":"Winehouse","given":"Jayna","email":"","affiliations":[],"preferred":false,"id":649026,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176249,"text":"ds1018 - 2016 - California sea otter (Enhydra lutris nereis) census results, Spring 2016","interactions":[],"lastModifiedDate":"2016-09-19T14:55:04","indexId":"ds1018","displayToPublicDate":"2016-09-19T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1018","title":"California sea otter (Enhydra lutris nereis) census results, Spring 2016","docAbstract":"The 2016 census of southern sea otters Enhydra lutris nereis was conducted in May along the mainland coast of central California and in April at San Nicolas Island in southern California. The 3-year average of combined counts from the mainland range and San Nicolas Island was 3,272. This is the first year that the official index has exceeded 3,090, the Endangered Species Act delisting threshold suggested by the U.S. Fish and Wildlife Service (the threshold would need to be exceeded for 3 consecutive years before delisting consideration). The 5-year average trend in abundance, including both the mainland range and San Nicolas Island populations, is positive at 3.2 percent per year; however, regional trends vary, with localized declines at the southern and northern peripheries of the mainland range. The lack of population growth in the range peripheries over recent years likely explains the cessation of range expansion, with the range limits remaining almost unchanged from the previous 5 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1018","usgsCitation":"Tinker, M.T., and Hatfield, B.B., 2016, California sea otter (Enhydra lutris nereis) census results, spring 2016: U.S. Geological Survey Data Series 1018, 10 p., https://dx.doi.org/10.3133/ds1018.","productDescription":"Report: iv, 9 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-078738","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438547,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7FJ2DWJ","text":"USGS data release","linkHelpText":"Annual California Sea Otter Census: 2016 Spring Census Summary"},{"id":328735,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7FJ2DWJ","text":"USGS data release","linkHelpText":"Annual California Sea Otter Census - 2016 Spring Census Summary"},{"id":328710,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1018/ds1018.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1018 report PDF"},{"id":328709,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1018/coverthb.jpg"}],"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 -122.431640625,\n 33.128351191631566\n ],\n [\n -122.431640625,\n 37.125286284966805\n ],\n [\n -119.388427734375,\n 37.125286284966805\n ],\n [\n -119.388427734375,\n 33.128351191631566\n ],\n [\n -122.431640625,\n 33.128351191631566\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/