High-resolution tomographic P wave, S wave, and VP/VS velocity structure models are derived for Mammoth Mountain, California, using phase data from the Northern California Seismic Network and a temporary deployment of broadband seismometers. An anomalous volume (5.1 × 109 to 5.9 × 1010m3) of low P and low S wave velocities is imaged beneath Mammoth Mountain, extending from near the surface to a depth of ∼2 km below sea level. We infer that the reduction in seismic wave velocities is due to the presence of CO2 distributed in oblate spheroid pores with mean aspect ratio α = 1.6 × 10−3 to 7.9 × 10−3 (crack-like pores) and mean gas volume fraction ϕ = 8.1 × 10−4 to 3.4 × 10−3. The pore density parameter κ = 3ϕ/(4πα) = na3=0.11, where n is the number of pores per cubic meter and a is the mean pore equatorial radius. The total mass of CO2 is estimated to be 4.6 × 109 to 1.9 × 1011 kg. The local geological structure indicates that the CO2 contained in the pores is delivered to the surface through fractures controlled by faults and remnant foliation of the bedrock beneath Mammoth Mountain. The total volume of CO2 contained in the reservoir suggests that given an emission rate of 500 tons day−1, the reservoir could supply the emission of CO2 for ∼25–1040 years before depletion. Continued supply of CO2 from an underlying magmatic system would significantly prolong the existence of the reservoir.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB012537","usgsCitation":"Dawson, P.B., Chouet, B.A., and Pitt, A., 2016, Tomographic image of a seismically active volcano: Mammoth Mountain, California: Journal of Geophysical Research B: Solid Earth, v. 121, no. 1, p. 114-133, https://doi.org/10.1002/2015JB012537.","productDescription":"20 p.","startPage":"114","endPage":"133","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069204","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb012537","text":"Publisher Index Page"},{"id":318020,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.06021118164062,\n 37.68083151896963\n ],\n [\n -119.03205871582031,\n 37.68137494751297\n ],\n [\n -118.99291992187499,\n 37.678386041261184\n ],\n [\n -118.9651107788086,\n 37.67213612088675\n ],\n [\n -118.94588470458984,\n 37.65528588731532\n ],\n [\n -118.9434814453125,\n 37.639519302998295\n ],\n [\n -118.96751403808594,\n 37.62021427322739\n ],\n [\n -118.98983001708984,\n 37.60498423376982\n ],\n [\n -119.03480529785156,\n 37.604440246103636\n ],\n [\n -119.06570434570312,\n 37.60716014465307\n ],\n [\n -119.0869903564453,\n 37.61831068887273\n ],\n [\n -119.08939361572266,\n 37.63734433906192\n ],\n [\n -119.08493041992186,\n 37.655557695625056\n ],\n [\n -119.08802032470703,\n 37.6756687492631\n ],\n [\n -119.0701675415039,\n 37.68246179265685\n ],\n [\n -119.06021118164062,\n 37.68083151896963\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"121","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-16","publicationStatus":"PW","scienceBaseUri":"56c304e0e4b0946c6520881d","contributors":{"authors":[{"text":"Dawson, Phillip B. dawson@usgs.gov","contributorId":2751,"corporation":false,"usgs":true,"family":"Dawson","given":"Phillip","email":"dawson@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":620200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chouet, Bernard A. 0000-0001-5527-0532 chouet@usgs.gov","orcid":"https://orcid.org/0000-0001-5527-0532","contributorId":3304,"corporation":false,"usgs":true,"family":"Chouet","given":"Bernard","email":"chouet@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":620201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pitt, Andrew M. pitt@usgs.gov","contributorId":3893,"corporation":false,"usgs":true,"family":"Pitt","given":"Andrew M.","email":"pitt@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":620202,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170872,"text":"70170872 - 2016 - Radiocarbon dating of silica sinter deposits in shallow drill cores from the Upper Geyser Basin, Yellowstone National Park","interactions":[],"lastModifiedDate":"2016-05-06T13:39:31","indexId":"70170872","displayToPublicDate":"2016-01-15T14:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Radiocarbon dating of silica sinter deposits in shallow drill cores from the Upper Geyser Basin, Yellowstone National Park","docAbstract":"To explore the timing of hydrothermal activity at the Upper Geyser Basin (UGB) in Yellowstone National Park, we obtained seven new accelerator mass spectrometry (AMS) radiocarbon 14C ages of carbonaceous material trapped within siliceous sinter. Five samples came from depths of 15–152 cm within the Y-1 well, and two samples were from well Y-7 (depths of 24 cm and 122 cm). These two wells, at Black Sand and Biscuit Basins, respectively, were drilled in 1967 as part of a scientific drilling program by the U.S. Geological Survey (White et al., 1975). Even with samples as small as 15 g, we obtained sufficient carbonaceous material (a mixture of thermophilic mats, pollen, and charcoal) for the 14C analyses. Apparent time of deposition ranged from 3775 ± 25 and 2910 ± 30 14C years BP at the top of the cores to about 8000 years BP at the bottom. The dates are consistent with variable rates of sinter formation at individual sites within the UGB over the Holocene. On a basin-wide scale, though, these and other existing 14C dates hint that hydrothermal activity at the UGB may have been continuous throughout the Holocene.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jvolgeores.2015.12.005","usgsCitation":"Lowenstern, J.B., Hurwitz, S., and McGeehin, J., 2016, Radiocarbon dating of silica sinter deposits in shallow drill cores from the Upper Geyser Basin, Yellowstone National Park: Journal of Volcanology and Geothermal Research, v. 310, p. 132-136, https://doi.org/10.1016/j.jvolgeores.2015.12.005.","productDescription":"5 p.","startPage":"132","endPage":"136","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069775","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":321025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Upper Geyser Basin, Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Center","active":true,"usgs":true}],"preferred":true,"id":628878,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159603,"text":"ofr20151215 - 2016 - Hydrologic conditions in the South Coast aquifer, Puerto Rico, 2010–15","interactions":[],"lastModifiedDate":"2016-01-15T13:39:04","indexId":"ofr20151215","displayToPublicDate":"2016-01-15T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1215","title":"Hydrologic conditions in the South Coast aquifer, Puerto Rico, 2010–15","docAbstract":"In 1958, the U.S. Geological Survey began documenting hydrologic conditions, including groundwater levels, groundwater withdrawals for agricultural irrigation and public water supply, and water quality, in the South Coast aquifer, Puerto Rico. This information has improved the understanding of the water resources of the region. The hydrologic data indicate that (1) groundwater levels declined as much as 40 feet in the Salinas area and 11 feet in the Guayama area during 2012–14; (2) groundwater withdrawals for agricultural irrigation increased from 6.0 to 10.5 million gallons per day, or 75 percent, from 2010 to 2012; and (3) total groundwater withdrawals decreased from 29.3 to 23.8 million gallons per day from 2010 to 2014. The quantity and quality of water in the aquifer is primarily affected by variations in aquifer recharge as a result of changing rainfall or modes of irrigation; however, the spatial patterns and magnitude of water withdrawals for all uses have a secondary impact on the quantity and quality of water in the aquifer.
\nNational Oceanic and Atmospheric Administration data from climatological stations indicate that the 30-year normal precipitation for the period 1991–2010 in the South Coastal and Southern Slopes climatological regions was about 37.74 and 61.61 inches, respectively; the 30-year moving average precipitation for the period 1985–2014 was 37.94 and 61.80 inches, respectively, for these regions. The mean annual precipitation during 2012–14 was 13 percent below the 30-year moving average for the South Coastal climatological region and 7.7 percent below for the Southern Slopes climatological region. When rainfall is below the 30-year moving average, recharge is diminished and groundwater levels decline. Annual precipitation in the South Coast aquifer, which includes a large part of the South Coastal and Southern Slopes climatological regions, was 39.42, 37.25, and 34.89 inches per year for 2012, 2013, and 2014, respectively.
\nWater level declines reduce the thickness of freshwater in the unconfined parts of the South Coast aquifer. Additionally, the pumping-induced migration of poor-quality water from deep or seaward areas of the aquifer can contribute to reductions in the thickness of freshwater in the aquifer. The reduction in the freshwater saturated thickness of the aquifer in areas near Ponce, Juana Díaz, Salinas, and Guayama is of particular concern because the total saturated thickness of the aquifer is thinner in these areas. Total dissolved solids concentration in groundwater samples indicates a small positive trend in Ponce, Santa Isabel, Salinas, and Guayama. Diminished aquifer recharge during 2012 to 2015 and, to a lesser extent, increased groundwater withdrawals have resulted in a reduction in the freshwater saturated thickness of the aquifer. The reduction in freshwater saturated thickness of the aquifer may affect freshwater resources available for agriculture and public water supply. A prolonged time period with reduced aquifer recharge may have substantial implications for groundwater levels and fresh groundwater availability.
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Lake sediment oxygen isotope records (calcium carbonate-δ18O) in the western North American Cordillera developed during the past decade provide substantial evidence of Pacific ocean–atmosphere forcing of hydroclimatic variability during the Holocene. Here we present an overview of 18 lake sediment δ18O records along with a new compilation of lake water δ18O and δ2H that are used to characterize lake sediment sensitivity to precipitation-δ18O in contrast to fractionation by evaporation. Of the 18 records, 14 have substantial sensitivity to evaporation. Two records reflect precipitation-δ18O since the middle Holocene, Jellybean and Bison Lakes, and are geographically positioned in the northern and southern regions of the study area. Their comparative analysis indicates a sequence of time-varying north–south precipitation-δ18O patterns that is evidence for a highly non-stationary influence by Pacific ocean–atmosphere processes on the hydroclimate of western North America. These observations are discussed within the context of previous research on North Pacific precipitation-δ18O based on empirical and modeling methods. The Jellybean and Bison Lake records indicate that a prominent precipitation-δ18O dipole (enriched-north and depleted-south) was sustained between ~ 3.5 and 1.5 ka, which contrasts with earlier Holocene patterns, and appears to indicate the onset of a dominant tropical control on North Pacific ocean–atmosphere dynamics. This remains the state of the system today. Higher frequency reversals of the north–south precipitation-δ18O dipole between ~ 2.5 and 1.5 ka, and during the Medieval Climate Anomaly and the Little Ice Age, also suggest more varieties of Pacific ocean–atmosphere modes than a single Pacific Decadal Oscillation (PDO) type analogue. Results indicate that further investigation of precipitation-δ18O patterns on short (observational) and long (Holocene) time scales is needed to improve our understanding of the processes that drive regional precipitation-δ18O responses to Pacific ocean–atmosphere variability, which in turn, will lead to a better understanding of internal Pacific ocean–atmosphere variability and its response to external climate forcing mechanisms.
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Comparison of acoustic backscatter imagery, seismic-reflection profiles, and bathymetry collected in 2011 and in 2014 show that sedimentary structures and depositional patterns moved alongshore to the southwest in water depths up to 30 meters during the 3-year period. The measured lateral offset distances range between about 1 and 450 meters with a mean of 20 meters. The mean distances computed indicate that change tended to decrease with increasing water depth. Comparison of isopach maps of modern sediment thickness show that a series of shoreface-attached sand ridges, which are the dominant sedimentary structures offshore of Fire Island, migrated toward the southwest because of erosion of the ridge crests and northeast-facing flanks as well as deposition on the southwest-facing flanks and in troughs between individual ridges. Statistics computed suggest that the modern sediment volume across the about 81 square kilometers of common sea floor mapped in both surveys decreased by 2.8 million cubic meters, which is a mean change of –0.03 meters, which is smaller than the resolution limit of the mapping systems used.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151238","usgsCitation":"Schwab, W.C., Baldwin, W.E., and Denny, J.F., 2016, Assessing the impact of Hurricanes Irene and Sandy on the morphology and modern sediment thickness on the inner continental shelf offshore of Fire Island, New York: U.S. Geological Survey Open-File Report 2015–1238, 15 p., https://dx.doi.org/10.3133/ofr20151238.","productDescription":"v, 15 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-067754","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":314316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1238/pdf/ofr20151238.pdf","text":"Report","size":"782 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1238"},{"id":314303,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ofr/2015/1238","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1238"},{"id":314315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1238/images/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.32824707031249,\n 40.629587853312174\n ],\n [\n -72.76382446289062,\n 40.777421721005936\n ],\n [\n -72.75283813476562,\n 40.76182096906601\n ],\n [\n -73.08517456054688,\n 40.643135583312805\n ],\n [\n -73.28292846679688,\n 40.60978237983301\n ],\n [\n -73.32824707031249,\n 40.629587853312174\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
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The awareness of insects as pollinators and indicators of environmental quality has grown in recent years, partially in response to declines in honey bee (Apis mellifera) populations. While most pesticide research has focused on honey bees, there has been less work on native bee populations. To determine the exposure of native bees to pesticides, bees were collected from an existing research area in northeastern Colorado from two land cover types: grasslands (2013-2014) and wheat fields (2014). Traps were deployed bi-monthly during the summer at each land cover type and all bees, regardless of species, were composited as whole samples and analyzed for 136 current-use pesticides and degradates. This reconnaissance approach provides a sampling of all species and represents overall pesticide exposure (internal and external). Nineteen pesticides and degradates were detected in 54 composite samples collected. Compounds detected in >10% of the samples included the insecticides thiamethoxam (46%), bifenthrin (28%), clothianidin (24%), chlorpyrifos (17%), and imidacloprid (13%), the fungicides azoxystrobin (17%), and pyraclostrobin (11%), and the herbicide atrazine (19%). Concentrations ranged from 1.1 to 312 ng/g for individual pesticides. Pesticides were detected in samples collected from both grasslands and wheat fields; the location of the sample and the surrounding land cover at the 1000 m buffer influenced the pesticides detected but because of a small number of temporally comparable samples, correlations between pesticide concentration and land cover were not significant. The results show native bees collected in both grasslands and wheat fields are exposed to multiple pesticides, these results can direct future research on routes/timing of pesticide exposure and the design of future conservation efforts for pollinators.
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\nThe Beaver-North Canadian River alluvial aquifer consists of unconsolidated sand, gravel, silt, and clay in varying proportions that underlies the Beaver and North Canadian River Valleys for approximately 175 miles (mi) from the Oklahoma Panhandle to the western edge of Oklahoma City in central Oklahoma. The aquifer as delineated for this study varies from 4 to 12 mi wide and is as thick as 308 feet (ft) in the northwest where the aquifer includes the Ogallala Formation.
\nThere are two distinct but in most areas hydraulically connected alluvial units that compose the Beaver-North Canadian River alluvial aquifer: a Quaternary-age topographically higher terrace deposit and a topographically lower, younger alluvium along the active river channel that includes active and Quaternary-age alluvium. The Beaver River composes the headwaters of the North Canadian River, which begins at the confluence of the Beaver River and Wolf Creek. The aquifer is divided for water management into two geographic areas: Reach I upstream from Canton Dam and Reach II downstream from Canton Dam. Reach I covers an area of approximately 874 square miles (mi2), and Reach II covers an area of approximately 371 mi2. The Beaver-North Canadian River alluvial aquifer crosses several climatic zones, from semiarid in the west to continental subhumid in the east. Mean annual precipitation varies from 23.5 inches (in.) in the western part of this aquifer to 35.7 in. in the east.
\nSurface-water demands were met through numerous temporary and permanent surface-water diversions from the Beaver and North Canadian Rivers during the period of study. During the study period, seven diversions removed a mean annual 2,000 acre-feet (acre-ft) of water from Reach I. There were 14 diversions from Reach II with a mean annual permitted volume of approximately 81,000 acre-ft, including diversion into the Lake Hefner Canal for the Oklahoma City public water supply. During the period of this study, 17 temporary surface-water diversion permits were active in Reach I, with total permitted volumes of 2,000 acre-ft, and 41 diversions were active in Reach II, with total permitted volumes of 38,000 acre-ft. The total water use for each temporary permit was assumed to be taken over the 3-month period allotted to temporary withdrawal permits.
\nThe groundwater-use analysis full period of record, 1967–2011, was divided into two sub-intervals because of varying water use, 1970–80 and 1981–2011. Groundwater use in Reach I and Reach II was substantially greater from 1970 to 1980 compared to the rest of the period, and the sub-period 1981–2011 was used because this period includes recent population growth and modern irrigation methods. The total mean annual groundwater use in Reach I was 15,309 acre-feet per year (acre-ft/yr) during 1967–2011; 20,724 acre-ft/yr during 1970–80, and 13,739 acre-ft/yr during 1981–2011. Total mean annual groundwater use in Reach II was similar but slightly less than in Reach I, with 14,098 acre-ft/yr during 1967–2011; 19,963 acre-ft/yr during 1970–80; and 12,285 acre-ft/yr during 1981–2011.
\nIrrigation composed 72 percent of groundwater use in Reach I and 48 percent of groundwater use in Reach II during the 1967–2011 period. Public water supply was a much smaller proportion of total groundwater use in Reach I (15 percent) than in Reach II (39 percent). The proportion of groundwater use for power was 10 percent in Reach I and 5.2 percent in Reach II. All other water-use categories in Reach I only composed 2.2 percent of groundwater use in Reach I. In Reach II, industrial, mining, and commercial categories combined accounted for 4.4 percent of groundwater use; recreation, fish, and wildlife groundwater use accounted for 2.3 percent; and nonirrigated agriculture accounted for 1.5 percent of groundwater use.
\nPermian-age bedrock underlies the Beaver-North Canadian River alluvial aquifer. In the east, the Dog Creek Shale, the Duncan Sandstone, and the Blaine and Chickasha Formations, none of which are notable sources of groundwater in the study area, underlie the Beaver-North Canadian River alluvial aquifer. In the northwestern part of Reach I, bedrock is composed of the Rush Springs and Marlow Formations, which are productive aquifers in some areas. The Cloud Chief Formation is not a source of groundwater.
\nOne hydrogeological unit was delineated in the Beaver-North Canadian River alluvial aquifer, composed of the terrace deposits and alluvium, with limited flow between this unit and bedrock units. Groundwater in this aquifer generally flows from northwest to southeast and across the aquifer toward the Beaver and North Canadian Rivers.
\nGroundwater recharge from precipitation was estimated for the entire Beaver-North Canadian River alluvial aquifer and then itemized for both reaches by using a soil-water-balance (SWB) model. At two locations in Reach I, a water-table fluctuation method was used to estimate local recharge. Total mean annual groundwater recharge from the soil-water-balance method was estimated to be approximately 136,400 acre-ft in Reach I and 82,400 acre-ft in Reach II; the mean annual recharge for both reaches combined was approximately 218,800 acre-ft. Two sites in Reach I located at observation wells with continuous water-level measurements and nearby streamflow-gaging stations with precipitation gages were used to estimate the percentage of precipitation that becomes groundwater recharge. The Woodward site was located at observation well OW-4 near the Woodward, Okla. (07237500), streamflow-gaging station. Total precipitation and recharge for the Woodward and Seiling sites were calculated for the water year 2013. The Woodward site had a total of 14.18 in. of precipitation and 6.3 in. of recharge was calculated, equaling 44 percent of precipitation. The mean percentage of precipitation that was estimated to become recharge in the SWB model for the period 1980–2011 at that location was 9.2 percent, although adjacent SWB-model cells were as high as 20 percent of precipitation. The Seiling site had a total of 26.84 in. of precipitation during the water year 2013, and a total of 6.9 in. of recharge was estimated, equaling 25.9 percent of precipitation. At the Seiling site, the mean percentage of precipitation that became recharge in the SWB model for the period 1980–2011 was 23.0 percent.
\nThe principal inflow to the Beaver-North Canadian River alluvial aquifer was estimated to be surface recharge from precipitation, and plant evapotranspiration was estimated to be the greatest discharge, followed by stream and lake base flow, groundwater pumping, and flow to seeps and springs along the eastern margin of the aquifer. Reach I also included inflow from the High Plains aquifer as lateral inflow of groundwater, though this flow was estimated to be a very minor component of the total water budget. Most of the Beaver and North Canadian Rivers were determined to be gaining streamflow from groundwater, but several reaches in Reach I upstream from Wolf Creek were determined to be losing streamflow through infiltration to the aquifer.
\nAquifer hydrogeologic characteristics were estimated from borehole lithologic logs, well-construction information, and published aquifer tests and during numerical model calibration. The maximum saturated aquifer thickness in Reach I was estimated to be 308 ft, and the mean thickness was estimated to be 36 ft. The maximum saturated thickness in Reach II was estimated to be 86 ft, and the mean thickness was estimated to be 29 ft. Mean hydraulic conductivity of Reach I was estimated to be 70 feet per day (ft/d) with a range of 7–279 ft/d. Mean hydraulic conductivity in Reach II was estimated to be 92 ft/d with a range of 4–279 ft/d.
\nBoth reach models were calibrated manually by using trial-and-error adjustment of recharge, hydraulic conductivity, specific yield, and conductance of boundary conditions. The Reach I model used 28 head observations during the steady-state period of 1980 and 487 head observations during the transient period of 1981–2011. The root-mean-square error of head residuals (observed minus simulated head) was 3.86 ft, and 83 percent of head residuals were between -5 and 5 ft. The Reach II model was calibrated to 75 steady-state head observations and 134 head observations during the transient period. The root-mean-square error of head residuals for that reach was 3.58 ft, and similar to Reach I, 85 percent of residuals were between -5 and 5 ft.
\nSeveral analyses were performed by using the numeric groundwater-flow models as predictive tools, including estimating the EPS pumping rate for both reaches. The EPS is defined by the Oklahoma Water Resources Board as an annual per-acre groundwater-pumping rate that will reduce saturated thickness in half of the aquifer to 5 ft or less over a period of 20 years; additional estimates were made for periods of 40 and 50 years. Other analyses included using models to estimate the effects of groundwater pumping and a prolonged drought on groundwater in storage and streamflow and lake storage of water.
\nThe EPS pumping rate was found to be approximately 0.57 acre-feet per acre per year ([acre-ft/acre]/yr) in Reach I and 0.73 (acre-ft/acre)/yr in Reach II for a 20-year period. For a 40-year period, the annual EPS pumping rate was determined to be 0.54 (acre-ft/acre)/yr in Reach I and 0.61 (acre-ft/acre)/yr in Reach II. For a 50-year period, the EPS pumping rate was determined to be 0.53 (acre-ft/acre)/yr in Reach I and 0.61 (acre-ft/acre)/yr in Reach II.
\nGroundwater pumping at the 2011 rate for 50 years resulted in a 3.6-percent decrease in the amount of water in groundwater storage in Reach I and a decrease of 2.5 percent in the amount of groundwater in storage in Reach II. A cumulative 32-percent increase in pumping greater than the 2011 rate over a period of 50 years caused a decrease in groundwater storage of 4.0 percent in Reach I and 3.3 percent in Reach II.
\nA hypothetical severe drought was simulated by using aquifer recharge flow rates during the drought year of 2011 for a period of 10 years. All other flows including evapotranspiration and groundwater pumping were set at estimated 2011 rates. The hypothetical drought caused a decrease in water in aquifer storage by about 7 percent in Reach I and 7 percent in Reach II. Another analysis of the effects of hypothetical drought estimated the effects of drought on streamflow and lake storage. The hypothetical drought was simulated by decreasing recharge by 75 percent for a selected 10-year period (1994–2004) during the 1980–2011 simulation. In Reach I, the amounts of water stored in Canton Lake and streamflow at the Seiling, Okla., streamflow-gaging station were analyzed. Streamflow at the Seiling station decreased by a mean of 75 percent and was still diminished by 10 percent after 2011. In Reach II, the effect of drought on the streamflow at the Yukon, Okla., streamflow-gaging station was examined. The greatest mean streamflow decrease was approximately 60 percent during the simulated drought, and after 2011, the mean decrease in streamflow was still about 5 percent. Canton Lake storage decreased by as much as 83 percent during the simulated drought and did not recover by 2011.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155183","collaboration":"Prepared in cooperation with the Oklahoma Water Resources Board","usgsCitation":"Ryter, D.W., and Correll, J.S., 2016, Hydrogeological framework, numerical simulation of groundwater flow, and effects of projected water use and drought for the Beaver-North Canadian River alluvial aquifer, northwestern Oklahoma (ver.1.1, February 2016): U.S. Geological Survey Scientific Investigations Report 2015–5183, 63 p., https://dx.doi.org/10.3133/sir20155183.","productDescription":"xi, 63 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056873","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":314354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5183/coverthb2.jpg"},{"id":314355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5183/sir20155183.pdf","text":"Report","size":"4.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5183"},{"id":318346,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5183/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5183"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Beaver-North Canadian River alluvial aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 35\n ],\n [\n -100,\n 37\n ],\n [\n -97.5,\n 37\n ],\n [\n -97.5,\n 35\n ],\n [\n -100,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted January 14, 2016; Version 1.1: February 24, 2016","contact":"Director, Oklahoma Water Science Center
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Oklahoma City, OK
http://ok.water.usgs.gov/
Process dynamics in fluvial-based dryland environments are highly complex with fluvial, aeolian, and alluvial processes all contributing to landscape change. When anthropogenic activities such as dam-building affect fluvial processes, the complexity in local response can be further increased by flood- and sediment-limiting flows. Understanding these complexities is key to predicting landscape behavior in drylands and has important scientific and management implications, including for studies related to paleoclimatology, landscape ecology evolution, and archaeological site context and preservation. Here we use multi-temporal LiDAR surveys, local weather data, and geomorphological observations to identify trends in site change throughout the 446-km-long semi-arid Colorado River corridor in Grand Canyon, Arizona, USA, where archaeological site degradation related to the effects of upstream dam operation is a concern. Using several site case studies, we show the range of landscape responses that might be expected from concomitant occurrence of dam-controlled fluvial sand bar deposition, aeolian sand transport, and rainfall-induced erosion. Empirical rainfall-erosion threshold analyses coupled with a numerical rainfall–runoff–soil erosion model indicate that infiltration-excess overland flow and gullying govern large-scale (centimeter- to decimeter-scale) landscape changes, but that aeolian deposition can in some cases mitigate gully erosion. Whereas threshold analyses identify the normalized rainfall intensity (defined as the ratio of rainfall intensity to hydraulic conductivity) as the primary factor governing hydrologic-driven erosion, assessment of false positives and false negatives in the dataset highlight topographic slope as the next most important parameter governing site response. Analysis of 4+ years of high resolution (four-minute) weather data and 75+ years of low resolution (daily) climate records indicates that dryland erosion is dependent on short-term, storm-driven rainfall intensity rather than cumulative rainfall, and that erosion can occur outside of wet seasons and even wet years. These results can apply to other similar semi-arid landscapes where process complexity may not be fully understood.
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- Cannibalistic-morph Tiger Salamanders in unexpected ecological contexts","interactions":[],"lastModifiedDate":"2016-01-14T10:29:10","indexId":"70162004","displayToPublicDate":"2016-01-14T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Cannibalistic-morph Tiger Salamanders in unexpected ecological contexts","docAbstract":"Barred tiger salamanders [Ambystoma mavortium (Baird, 1850)] exhibit two trophic morphologies; a typical and a cannibalistic morph. Cannibalistic morphs, distinguished by enlarged vomerine teeth, wide heads, slender bodies, and cannibalistic tendencies, are often found where conspecifics occur at high density. During 2012 and 2013, 162 North Dakota wetlands and lakes were sampled for salamanders. Fifty-one contained A. mavortium populations; four of these contained cannibalistic morph individuals. Two populations with cannibalistic morphs occurred at sites with high abundances of conspecifics. However, the other two populations occurred at sites with unexpectedly low conspecific but high fathead minnow [Pimephales promelas (Rafinesque, 1820)] abundances. Further, no typical morphs were observed in either of these later two populations, contrasting with earlier research suggesting cannibalistic morphs only occur at low frequencies in salamander populations. Another anomaly of all four populations was the occurrence of cannibalistic morphs in permanent water sites, suggesting their presence was due to factors other than faster growth allowing them to occupy ephemeral habitats. Therefore, our findings suggest environmental factors inducing the cannibalistic morphism may be more complex than previously thought.
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Dakota\",\"nation\":\"USA \"}}]}","volume":"175","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5698c6abe4b0fbd3f7fa4bd6","contributors":{"authors":[{"text":"McLean, Kyle I.","contributorId":63316,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle I.","affiliations":[],"preferred":false,"id":588310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockwell, Craig A.","contributorId":55257,"corporation":false,"usgs":true,"family":"Stockwell","given":"Craig A.","affiliations":[],"preferred":false,"id":588311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":588309,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70162073,"text":"70162073 - 2016 - Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States","interactions":[],"lastModifiedDate":"2017-01-18T09:24:56","indexId":"70162073","displayToPublicDate":"2016-01-14T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States","docAbstract":"The development of different energy balance models has allowed users to choose a model based on its suitability in a region. We compared four commonly used models—Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model, Surface Energy Balance Algorithm for Land (SEBAL) model, Surface Energy Balance System (SEBS) model, and the Operational Simplified Surface Energy Balance (SSEBop) model—using Landsat images to estimate evapotranspiration (ET) in the Midwestern United States. Our models validation using three AmeriFlux cropland sites at Mead, Nebraska, showed that all four models captured the spatial and temporal variation of ET reasonably well with an R2 of more than 0.81. Both the METRIC and SSEBop models showed a low root mean square error (<0.93 mm·day−1) and a high Nash–Sutcliffe coefficient of efficiency (>0.80), whereas the SEBAL and SEBS models resulted in relatively higher bias for estimating daily ET. The empirical equation of daily average net radiation used in the SEBAL and SEBS models for upscaling instantaneous ET to daily ET resulted in underestimation of daily ET, particularly when the daily average net radiation was more than 100 W·m−2. Estimated daily ET for both cropland and grassland had some degree of linearity with METRIC, SEBAL, and SEBS, but linearity was stronger for evaporative fraction. Thus, these ET models have strengths and limitations for applications in water resource management.
","language":"English","publisher":"MDPI","doi":"10.3390/w8010009","usgsCitation":"Singh, R.K., and Senay, G., 2016, Comparison of four different energy balance models for estimating evapotranspiration in the Midwestern United States: Water, v. 8, no. 1, art9: 19 p., https://doi.org/10.3390/w8010009.","productDescription":"art9: 19 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071106","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8010009","text":"Publisher Index Page"},{"id":314323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","city":"Mead","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.580810546875,\n 41.16030461996852\n ],\n [\n -96.580810546875,\n 41.28219255498905\n ],\n [\n -96.3717269897461,\n 41.28219255498905\n ],\n [\n -96.3717269897461,\n 41.16030461996852\n ],\n [\n -96.580810546875,\n 41.16030461996852\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-26","publicationStatus":"PW","scienceBaseUri":"5698c6b0e4b0fbd3f7fa4bda","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":588468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. senay@usgs.gov","contributorId":150062,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[],"preferred":false,"id":588469,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162098,"text":"70162098 - 2016 - Larval dispersal underlies demographically important inter-system connectivity in a Great Lakes yellow perch (Perca flavescens) population","interactions":[],"lastModifiedDate":"2016-03-03T11:15:28","indexId":"70162098","displayToPublicDate":"2016-01-14T10:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Larval dispersal underlies demographically important inter-system connectivity in a Great Lakes yellow perch (Perca flavescens) population","docAbstract":"Ability to quantify connectivity among spawning subpopulations and their relative contribution of recruits to the broader population is a critical fisheries management need. By combining microsatellite and age information from larval yellow perch (Perca flavescens) collected in the Lake St. Clair – Detroit River system (SC-DRS) and western Lake Erie with a hydrodynamic backtracking approach, we quantified subpopulation structure, connectivity, and contributions of recruits to the juvenile stage in western Lake Erie during 2006-2007. After finding weak (yet stable) genetic structure between the SC-DRS and two western Lake Erie subpopulations, microsatellites also revealed measurable recruitment of SC-DRS larvae to the juvenile stage in western Lake Erie (17-21% during 2006-2007). Consideration of pre-collection larval dispersal trajectories, using hydrodynamic backtracking, increased estimated contributions to 65% in 2006 and 57% in 2007. Our findings highlight the value of complementing subpopulation discrimination methods with hydrodynamic predictions of larval dispersal by revealing the SC-DRS as a source of recruits to western Lake Erie and also showing that connectivity through larval dispersal can affect the structure and dynamics of large-lake fish populations.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0161","usgsCitation":"Brodnik, R.M., Fraker, M.E., Anderson, E., Carreon-Martinez, L., DeVanna, K.M., Heath, D.D., Reichert, J.M., Roseman, E., and Ludsin, S.A., 2016, Larval dispersal underlies demographically important inter-system connectivity in a Great Lakes yellow perch (Perca flavescens) population: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 3, p. 416-426, https://doi.org/10.1139/cjfas-2015-0161.","productDescription":"11 p.","startPage":"416","endPage":"426","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051105","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471329,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/52708","text":"External Repository"},{"id":314319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie, Lake St. Clair-Detroit River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.56201171875,\n 41.35207214451295\n ],\n [\n -83.56201171875,\n 43.01268088642034\n ],\n [\n -78.804931640625,\n 43.01268088642034\n ],\n [\n -78.804931640625,\n 41.35207214451295\n ],\n [\n -83.56201171875,\n 41.35207214451295\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"73","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5698c6b2e4b0fbd3f7fa4be2","contributors":{"authors":[{"text":"Brodnik, Reed M.","contributorId":152212,"corporation":false,"usgs":false,"family":"Brodnik","given":"Reed","email":"","middleInitial":"M.","affiliations":[{"id":18882,"text":"aDepartment of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, 43212","active":true,"usgs":false}],"preferred":false,"id":588503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fraker, Michael E. 0000-0002-1813-706X","orcid":"https://orcid.org/0000-0002-1813-706X","contributorId":150962,"corporation":false,"usgs":false,"family":"Fraker","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":588504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Eric J.","contributorId":89434,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric J.","affiliations":[],"preferred":false,"id":588511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carreon-Martinez, Lucia","contributorId":152213,"corporation":false,"usgs":false,"family":"Carreon-Martinez","given":"Lucia","email":"","affiliations":[{"id":18883,"text":"Department of Biology, The University of Texas at Brownsville, Brownsville, TX, 78520","active":true,"usgs":false}],"preferred":false,"id":588506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeVanna, Kristen M.","contributorId":64991,"corporation":false,"usgs":true,"family":"DeVanna","given":"Kristen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":588505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Heath, Dan D.","contributorId":152214,"corporation":false,"usgs":false,"family":"Heath","given":"Dan","email":"","middleInitial":"D.","affiliations":[{"id":18884,"text":"GLIER, The University of Windsor, Windsor, ON, N9B 3P4, Canada","active":true,"usgs":false}],"preferred":false,"id":588507,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reichert, Julie M.","contributorId":152216,"corporation":false,"usgs":false,"family":"Reichert","given":"Julie","email":"","middleInitial":"M.","affiliations":[{"id":18884,"text":"GLIER, The University of Windsor, Windsor, ON, N9B 3P4, Canada","active":true,"usgs":false}],"preferred":false,"id":588509,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roseman, Edward F. eroseman@usgs.gov","contributorId":147266,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","email":"eroseman@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":588502,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ludsin, Stuart A.","contributorId":96978,"corporation":false,"usgs":true,"family":"Ludsin","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":588510,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70160050,"text":"70160050 - 2016 - The effects of heterospecifics and climatic conditions on incubation behavior within a mixed-species colony","interactions":[],"lastModifiedDate":"2016-06-02T10:45:19","indexId":"70160050","displayToPublicDate":"2016-01-14T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of heterospecifics and climatic conditions on incubation behavior within a mixed-species colony","docAbstract":"Parental incubation behavior largely influences nest survival, a critical demographic process in avian population dynamics, and behaviors vary across species with different life history breeding strategies. Although research has identified nest survival advantages of mixing colonies, behavioral mechanisms that might explain these effects is largely lacking. We examined parental incubation behavior using video-monitoring techniques on Alcatraz Island, California, of black-crowned night-heron Nycticorax nycticorax(hereinafter, night-heron) in a mixed-species colony with California gulls Larus californicus and western gulls L. occidentalis. We first quantified general nesting behaviors (i.e. incubation constancy, and nest attendance), and a suite of specific nesting behaviors (i.e. inactivity, vigilance, preening, and nest maintenance) with respect to six different daily time periods. We employed linear mixed effects models to investigate environmental and temporal factors as sources of variation in incubation constancy and nest attendance using 211 nest days across three nesting seasons (2010–2012). We found incubation constancy (percent of time on the eggs) and nest attendance (percent of time at the nest) were lower for nests that were located < 3 m from one or more gull nest, which indirectly supports the predator protection hypothesis, whereby heterospecifics provide protection allowing more time for foraging and other self-maintenance activities. To our knowledge, this is the first empirical evidence of the influence of one nesting species on the incubation behavior of another. We also identified distinct differences between incubation constancy and nest attentiveness, indicating that these biparental incubating species do not share similar energetic constraints as those that are observed for uniparental species. Additionally, we found that variation in incubation behavior was a function of temperature and precipitation, where the strength of these effects was dependent on the time of day. Overall, these findings strengthen our understanding of incubation behavior and nest ecology of a colonial-nesting species.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.00900","usgsCitation":"Coates, P.S., Brussee, B.E., Hothem, R.L., Howe, K.H., Casazza, M.L., and Eadie, J.M., 2016, The effects of heterospecifics and climatic conditions on incubation behavior within a mixed-species colony: Journal of Avian Biology, v. 47, no. 3, p. 399-408, https://doi.org/10.1111/jav.00900.","productDescription":"10 p.","startPage":"399","endPage":"408","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066910","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":314313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Alcatraz Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.42599725723267,\n 37.8248194145315\n ],\n [\n -122.42599725723267,\n 37.82863288343018\n ],\n [\n -122.42013931274413,\n 37.82863288343018\n ],\n [\n -122.42013931274413,\n 37.8248194145315\n ],\n [\n -122.42599725723267,\n 37.8248194145315\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-29","publicationStatus":"PW","scienceBaseUri":"5698c6b2e4b0fbd3f7fa4be6","contributors":{"authors":[{"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":581717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":581718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hothem, Roger L. roger_hothem@usgs.gov","contributorId":1721,"corporation":false,"usgs":true,"family":"Hothem","given":"Roger","email":"roger_hothem@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":581719,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howe, Kristy H. khowe@usgs.gov","contributorId":147803,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy","email":"khowe@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":581720,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":581721,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eadie, John M.","contributorId":34067,"corporation":false,"usgs":false,"family":"Eadie","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":6961,"text":"Department of Wildlife, Fish & Conservation Biology, University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":581722,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70162125,"text":"70162125 - 2016 - Tradeoff between assessment and control of aquatic invasive species: A case study of sea lamprey management in the St. Marys River","interactions":[],"lastModifiedDate":"2016-06-08T09:53:57","indexId":"70162125","displayToPublicDate":"2016-01-14T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Tradeoff between assessment and control of aquatic invasive species: A case study of sea lamprey management in the St. Marys River","docAbstract":"Allocating resources between the gathering of information to guide management actions and implementing those actions presents an inherent tradeoff. This tradeoff is evident for control of the Sea Lamprey Petromyzon marinus in the St. Marys River, connecting Lakes Huron and Superior and a major source of parasitic Sea Lampreys to Lake Huron and northern Lake Michigan. Larval Sea Lampreys in the St. Marys River are controlled through the application of Bayluscide, which is applied to areas of high larval density. Bayluscide applications are guided with an annual deepwater electrofishing survey to estimate larval Sea Lamprey density at relatively fine spatial scales. We took a resampling approach to describe the effect of sampling intensity on the success of the larval Sea Lamprey management program and explicitly incorporated the economic tradeoff between assessment and control efforts to maximize numbers of larvae killed in the St. Marys River. When no tradeoff between assessment and control was incorporated, increasing assessment always led to more larvae killed for the same treatment budget. When the tradeoff was incorporated, the sampling intensity that maximized the number of larvae killed depended on the overall budget available. Increased sampling intensities maximized effectiveness under medium to large budgets (US \\$0.4 to \\$2.0 million), and intermediate sampling intensities maximized effectiveness under low budgets. Sea Lamprey control actions based on assessment information outperformed those that were implemented with no assessment under all budget scenarios.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2015.1103822","usgsCitation":"Robinson, J.M., Wilberg, M.J., Adams, J.V., and Jones, M., 2016, Tradeoff between assessment and control of aquatic invasive species: A case study of sea lamprey management in the St. Marys River: North American Journal of Fisheries Management, v. 36, no. 1, p. 11-20, https://doi.org/10.1080/02755947.2015.1103822.","productDescription":"10 p.","startPage":"11","endPage":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056034","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":314310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"St. Marys River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.37705993652344,\n 46.44069599413034\n ],\n [\n -84.37705993652344,\n 46.533830919250846\n ],\n [\n -84.20333862304688,\n 46.533830919250846\n ],\n [\n -84.20333862304688,\n 46.44069599413034\n ],\n [\n -84.37705993652344,\n 46.44069599413034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-13","publicationStatus":"PW","scienceBaseUri":"5698c6b2e4b0fbd3f7fa4be8","contributors":{"authors":[{"text":"Robinson, Jason M.","contributorId":42866,"corporation":false,"usgs":true,"family":"Robinson","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":588618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilberg, Michael J.","contributorId":36494,"corporation":false,"usgs":true,"family":"Wilberg","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":588619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588617,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Michael L.","contributorId":7219,"corporation":false,"usgs":false,"family":"Jones","given":"Michael L.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":588620,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160881,"text":"ofr20161001 - 2016 - Identify potential lock treatment options to prevent movement of aquatic invasive species through the Chicago Area Waterways System (CAWS)","interactions":[],"lastModifiedDate":"2016-01-14T08:51:12","indexId":"ofr20161001","displayToPublicDate":"2016-01-14T08:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1001","title":"Identify potential lock treatment options to prevent movement of aquatic invasive species through the Chicago Area Waterways System (CAWS)","docAbstract":"The Illinois River is a primary tributary of the Mississippi River, connecting with the Mississippi at Grafton, Illinois. The headwaters of the river are at the confluence of the Des Plaines and Kankakee Rivers in eastern Grundy County, Illinois. Approximately 273 miles long, it runs through the heart of Illinois and is the connection between the Mississippi River and Lake Michigan in the Great Lakes basin. Because of this connection, there is concern about the potential for introduced aquatic species in one basin to migrate through this connection into the other basin. A prime example of this are the Asian carps, which were introduced into commercial fishing ponds in Arkansas in the 1970s and, following escape, are now making their way up the Mississippi, Illinois, and Missouri Rivers. Options are being investigated to minimize or prevent non-native aquatic species from invading either basin through the Illinois River connection and eventually having detrimental impacts on the basin into which they migrate.
\nThe Illinois River has a series of locks and dams that are used to facilitate the navigation of commercial and recreational shipping from Chicago to Beardstown, Illinois. One option under consideration is to develop a lock treatment process that stops aquatic invasive species from entering (and moving through) the Chicago Area Waterway System (CAWS), while at the same time not unduly impeding the movement of barges and other boat traffic between Lake Michigan and the Mississippi River. The purpose this report was to evaluate the feasibility of using chemical and (or) physical treatments to determine if a sufficiently efficacious option could be used to prevent aquatic invasive species from being transported through the locks. Approximately 30 chemical and physical control options were evaluated on the basis of nine factors ranging from viability for use on a large scale, rapid lethality, human health effects, and potential damage to lock structures and vessel hulls.
\nCompatibility of the various options was also evaluated to assess the possibility that options could be combined to enhance efficacy. Engineering requirements were not considered as part of this evaluation. The available information suggests that hot water at 43 °C and ozone are the most feasible options.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161001","usgsCitation":"Hubert, T.D., Boogaard, M.A., and Fredricks, K.T., 2016, Identify potential lock treatment options to prevent movement of aquatic invasive species through the Chicago Area Waterway System (CAWS): U.S. Geological Survey Open-File Report 2016–1001, 16 p., https://dx.doi.org/10.3133/ofr20161001.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071535","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":313866,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1001/ofr20161001.pdf","text":"Report","size":"223 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1001"},{"id":313865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1001/coverthb.jpg"}],"country":"United States","otherGeospatial":"Chicago Area Waterway System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.47015380859375,\n 41.3850519497068\n ],\n [\n -88.47015380859375,\n 42.285437007491545\n ],\n [\n -86.956787109375,\n 42.285437007491545\n ],\n [\n -86.956787109375,\n 41.3850519497068\n ],\n [\n -88.47015380859375,\n 41.3850519497068\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
LaCrosse, WI 54603
http://www.umesc.usgs.gov/
Sex determination of fish species is difficult to assess when sexual dimorphism and gametes are not apparent. For threatened and endangered fish species, noninvasive techniques are needed when determining sex to minimize stress and the potential for mortality. We evaluated the use of a portable ultrasound unit to determine sex of Lake Sturgeon Acipenser fulvescens in the field. Ultrasound images were collected from 9 yellow-egg (F2, F3), 32 black-egg (F4, F5), and 107 fully developed male (M2) Lake Sturgeon. Two readers accurately assigned sex to 88–96% of fish, but accuracy varied in relation to maturity stage. Black-egg females and fully developed males were correctly identified for 89–100% of the fish sampled, while these two readers identified yellow-egg females only 33% and 67% of the time. Time spent collecting images ranged between 2 and 3 min once the user was comfortable with operating procedures. Discriminant analysis revealed the total length : girth ratio was a strong predictor of sex and maturity, correctly classifying 81% of black-egg females and 97% of the fully developed males. However, yellow-egg females were incorrectly classified on all occasions. This study shows the utility of using ultrasonography and a total length : girth ratio for sex determination of Lake Sturgeon in later reproductive stages around the spawning season.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2015.1103823","usgsCitation":"Chiotti, J.A., Boase, J., Hondorp, D.W., and Briggs, A., 2016, Assigning sex and reproductive stage to adult Lake Sturgeon using ultrasonography and common morphological measurements: North American Journal of Fisheries Management, v. 36, no. 1, p. 21-29, https://doi.org/10.1080/02755947.2015.1103823.","productDescription":"9 p.","startPage":"21","endPage":"29","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064995","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":314927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"St. Clair–Detroit River system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.4359130859375,\n 43.004647127794435\n ],\n [\n -82.40020751953125,\n 43.000629854450025\n ],\n [\n -82.40295410156249,\n 42.95441233121331\n ],\n [\n -82.4359130859375,\n 42.91419494510531\n ],\n [\n -82.45788574218749,\n 42.817566071581616\n ],\n [\n -82.45513916015625,\n 42.75306280054229\n ],\n [\n -82.4853515625,\n 42.67839711889057\n ],\n [\n -82.5018310546875,\n 42.601619944327965\n ],\n [\n -82.562255859375,\n 42.53689200787317\n ],\n [\n -82.45513916015625,\n 42.52069952914966\n ],\n [\n -82.3919677734375,\n 42.44778143462245\n ],\n [\n -82.41668701171875,\n 42.356514317057886\n ],\n [\n -82.4798583984375,\n 42.3037216984154\n ],\n [\n -82.56500244140625,\n 42.3037216984154\n ],\n [\n -82.64190673828125,\n 42.29965889253408\n ],\n [\n -82.81219482421875,\n 42.29965889253408\n ],\n [\n -82.935791015625,\n 42.33215399891373\n ],\n [\n -83.056640625,\n 42.3037216984154\n ],\n [\n -83.1005859375,\n 42.26308184299127\n ],\n [\n -83.1005859375,\n 42.18375873465217\n ],\n [\n -83.1060791015625,\n 42.13082130188811\n ],\n [\n -83.1060791015625,\n 42.05337156043361\n ],\n [\n -83.20220947265625,\n 42.02481360781777\n ],\n [\n -83.21319580078125,\n 42.12674735753131\n ],\n [\n -83.15277099609375,\n 42.248851700720955\n ],\n [\n -83.08685302734375,\n 42.32403179535469\n ],\n [\n -82.9852294921875,\n 42.36869093640926\n ],\n [\n -82.913818359375,\n 42.391008609205045\n ],\n [\n -82.88909912109375,\n 42.4417010906216\n ],\n [\n -82.89459228515624,\n 42.49842801732155\n ],\n [\n -82.85064697265625,\n 42.569264372193864\n ],\n [\n -82.81219482421875,\n 42.577354839557856\n ],\n [\n -82.81219482421875,\n 42.593532625649935\n ],\n [\n -82.8314208984375,\n 42.63193804106211\n ],\n [\n -82.80120849609374,\n 42.66224137632745\n ],\n [\n -82.77374267578125,\n 42.65820178455667\n ],\n [\n -82.694091796875,\n 42.69252994883861\n ],\n [\n -82.60620117187499,\n 42.67435857693384\n ],\n [\n -82.60894775390625,\n 42.64002037386321\n ],\n [\n -82.54302978515625,\n 42.627896481020855\n ],\n [\n -82.52105712890625,\n 42.67839711889057\n ],\n [\n -82.496337890625,\n 42.73894375124379\n ],\n [\n -82.48809814453125,\n 42.77322729247907\n ],\n [\n -82.49359130859375,\n 42.81353658623225\n ],\n [\n -82.4798583984375,\n 42.85985981506279\n ],\n [\n -82.47711181640625,\n 42.92827401776912\n ],\n [\n -82.44140625,\n 42.96647242540857\n ],\n [\n -82.44140625,\n 42.994603451901305\n ],\n [\n -82.4359130859375,\n 43.004647127794435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-13","publicationStatus":"PW","scienceBaseUri":"56a9f83ee4b012c193aa3ebc","contributors":{"authors":[{"text":"Chiotti, Justin A.","contributorId":59371,"corporation":false,"usgs":true,"family":"Chiotti","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":589832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boase, James C.","contributorId":72713,"corporation":false,"usgs":true,"family":"Boase","given":"James C.","affiliations":[],"preferred":false,"id":589833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":589831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Andrew S.","contributorId":32796,"corporation":false,"usgs":true,"family":"Briggs","given":"Andrew S.","affiliations":[],"preferred":false,"id":589834,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70162101,"text":"70162101 - 2016 - Diel feeding ecology of Slimy Sculpin in a tributary to Skaneateles Lake, New York","interactions":[],"lastModifiedDate":"2016-01-13T13:20:02","indexId":"70162101","displayToPublicDate":"2016-01-13T14:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Diel feeding ecology of Slimy Sculpin in a tributary to Skaneateles Lake, New York","docAbstract":"Interactions among the benthic community are typically overlooked but play an important role in fish community dynamics. We examined the diel feeding ecology of Slimy Sculpin (Cottus cognatus) from Grout Brook, a tributary to Skaneateles Lake. Of the six time periods examined, Slimy Sculpin consumed the least during the nighttime (2400 h and 0400 h). Chironomids were the major prey consumed during all time periods except for 2400 h when ephemeropterans were the major prey consumed. There was a moderate preference by Slimy Sculpin for food from the benthos (0.59 ± 0.06) with Diptera (Chironomids), Ephemeroptera (Baetidae), and Trichoptera (Brachycentridae) representing the major taxa. Slimy Sculpin appear to be opportunistic feeders selecting what is most available in the brook. Index of fullness was variable and averaged 1.15% across the diel cycle. Daily ration was measured as a function of fish dry body weight and ranged from 0.12 to 0.22. Estimates of daily consumption ranged from 0.007% to 4.0% of body weight, which corresponds to reports for other species. These findings have application in gauging the relative importance of Slimy Sculpin in streams where highly valued salmonid species also occur.
","language":"English","publisher":"University of Notre Dame","doi":"10.1674/amid-175-01-37-46.1","usgsCitation":"Chalupnicki, M.A., and Johnson, J.H., 2016, Diel feeding ecology of Slimy Sculpin in a tributary to Skaneateles Lake, New York: American Midland Naturalist, v. 175, no. 1, p. 37-46, https://doi.org/10.1674/amid-175-01-37-46.1.","productDescription":"10 p.","startPage":"37","endPage":"46","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055360","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":314280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Grout Brook, Skaneateles Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.44905090332031,\n 42.76314586689494\n ],\n [\n -76.44905090332031,\n 42.94838139765314\n ],\n [\n -76.26091003417969,\n 42.94838139765314\n ],\n [\n -76.26091003417969,\n 42.76314586689494\n ],\n [\n -76.44905090332031,\n 42.76314586689494\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"175","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5697752ee4b039675d00a6bc","contributors":{"authors":[{"text":"Chalupnicki, Marc A. mchalupnicki@usgs.gov","contributorId":3236,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":588517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588518,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162102,"text":"70162102 - 2016 - Age, growth, and size of Lake Superior Pygmy Whitefish (Prosopium coulterii)","interactions":[],"lastModifiedDate":"2016-01-13T13:36:38","indexId":"70162102","displayToPublicDate":"2016-01-13T14:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":737,"text":"American Midland Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Age, growth, and size of Lake Superior Pygmy Whitefish (Prosopium coulterii)","docAbstract":"Pygmy Whitefish (Prosopium coulterii) are a small, glacial relict species with a disjunct distribution in North America and Siberia. In 2013 we collected Pygmy Whitefish at 28 stations from throughout Lake Superior. Total length was recorded for all fish and weight and sex were recorded and scales and otoliths were collected from a subsample. We compared the precision of estimated ages between readers and between scales and otoliths, estimated von Bertalanffy growth parameters for male and female Pygmy Whitefish, and reported the first weight-length relationship for Pygmy Whitefish. Age estimates between scales and otoliths differed significantly with otolith ages significantly greater for most ages after age-3. Maximum otolith age was nine for females and seven for males, which is older than previously reported for Pygmy Whitefish from Lake Superior. Growth was initially fast but slowed considerably after age-3 for males and age-4 for females, falling to 3–4 mm per year at maximum estimated ages. Females were longer than males after age-3. Our results suggest the size, age, and growth of Pygmy Whitefish in Lake Superior have not changed appreciably since 1953.
","language":"English","publisher":"University of Notre Dame","doi":"10.1674/amid-175-01-24-36.1","usgsCitation":"Stewart, T., Derek Ogle, Gorman, O.T., and Vinson, M., 2016, Age, growth, and size of Lake Superior Pygmy Whitefish (Prosopium coulterii): American Midland Naturalist, v. 175, no. 1, p. 24-36, https://doi.org/10.1674/amid-175-01-24-36.1.","productDescription":"13 p.","startPage":"24","endPage":"36","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062004","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":314281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.2412109375,\n 46.46813299215554\n ],\n [\n -92.2412109375,\n 49.023461463214126\n ],\n [\n -84.3310546875,\n 49.023461463214126\n ],\n [\n -84.3310546875,\n 46.46813299215554\n ],\n [\n -92.2412109375,\n 46.46813299215554\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"175","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5697752be4b039675d00a6b6","contributors":{"authors":[{"text":"Stewart, Taylor trstewart@usgs.gov","contributorId":145494,"corporation":false,"usgs":true,"family":"Stewart","given":"Taylor","email":"trstewart@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Derek Ogle","contributorId":152217,"corporation":false,"usgs":false,"family":"Derek Ogle","affiliations":[{"id":18886,"text":"Northland College","active":true,"usgs":false}],"preferred":false,"id":588522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman, Owen T. 0000-0003-0451-110X otgorman@usgs.gov","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":2888,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"otgorman@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":588519,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204449,"text":"70204449 - 2016 - Integrative modelling reveals mechanisms linking productivity and plant species richness","interactions":[],"lastModifiedDate":"2019-07-24T13:43:37","indexId":"70204449","displayToPublicDate":"2016-01-13T13:03:52","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Integrative modelling reveals mechanisms linking productivity and plant species richness","docAbstract":"How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nature16524","usgsCitation":"Grace, J.B., Anderson, T.M., Seabloom, E.W., Borer, E.T., Adler, P.B., Harpole, W., Hautier, Y., Hillebrand, H., Lind, E.M., Partel, M., Bakker, J.D., Buckley, Y.M., Crawley, M.J., Damschen, E.I., Davies, K.F., Fay, P.A., Firn, J., Gruner, D.S., Hector, A., Knops, J.M., MacDougall, A.S., Melbourne, B.A., Morgan, J.W., Orrock, J., Prober, S.M., and Smith, M., 2016, Integrative modelling reveals mechanisms linking productivity and plant species richness: Nature, v. 529, p. 390-393, https://doi.org/10.1038/nature16524.","productDescription":"4 p.","startPage":"390","endPage":"393","ipdsId":"IP-051258","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471330,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://dspace.library.uu.nl/handle/1874/344413","text":"External Repository"},{"id":365909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"529","noUsgsAuthors":false,"publicationDate":"2016-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":766959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, T. 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Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012","interactions":[],"lastModifiedDate":"2021-07-02T13:50:02.84497","indexId":"sir20155133","displayToPublicDate":"2016-01-13T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5133","title":"Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012","docAbstract":"In the Chesapeake Bay watershed, estimated fluxes of nutrients and sediment from the bay’s nontidal tributaries into the estuary are the foundation of decision making to meet reductions prescribed by the Chesapeake Bay Total Maximum Daily Load (TMDL) and are often the basis for refining scientific understanding of the watershed-scale processes that influence the delivery of these constituents to the bay. Two regression-based flux and trend estimation models, ESTIMATOR and Weighted Regressions on Time, Discharge, and Season (WRTDS), were compared using data from 80 watersheds in the Chesapeake Bay Nontidal Water-Quality Monitoring Network (CBNTN). The watersheds range in size from 62 to 70,189 square kilometers and record lengths range from 6 to 28 years. ESTIMATOR is a constant-parameter model that estimates trends only in concentration; WRTDS uses variable parameters estimated with weighted regression, and estimates trends in both concentration and flux. WRTDS had greater explanatory power than ESTIMATOR, with the greatest degree of improvement evident for records longer than 25 years (30 stations; improvement in median model R2= 0.06 for total nitrogen, 0.08 for total phosphorus, and 0.05 for sediment) and the least degree of improvement for records of less than 10 years, for which the two models performed nearly equally. Flux bias statistics were comparable or lower (more favorable) for WRTDS for any record length; for 30 stations with records longer than 25 years, the greatest degree of improvement was evident for sediment (decrease of 0.17 in median statistic) and total phosphorus (decrease of 0.05). The overall between-station pattern in concentration trend direction and magnitude for all constituents was roughly similar for both models. A detailed case study revealed that trends in concentration estimated by WRTDS can operationally be viewed as a less-constrained equivalent to trends in concentration estimated by ESTIMATOR. Estimates of annual mean flow-adjusted (ESTIMATOR) and flow-normalized (WRTDS) concentration for years initially constituting the end of a water-quality record showed a similar degree of variability as data for additional years were incrementally added and the initial estimates “aged.” On the basis of the results of this broad comparison of the two models, the U.S. Geological Survey is adopting WRTDS as the primary model for estimating constituent fluxes and trends throughout the CBNTN. Nutrient and sediment flux and trend estimates, based on WRTDS, are summarized narratively and tabulated in appendixes for all stations for which fluxes or trends were reported through water year 2012.
\nWRTDS also was used to explore the sensitivity of flux and trend estimates to three data-quality issues common in many large-scale monitoring networks and evident in some of the CBNTN records. The potential effects of inconsistency in annual sampling effort and inconsistency in storm sampling effort were explored by way of a subsampling experiment using eight of the most densely sampled long-term (1985–2012) stations in the CBNTN as baseline datasets. From each dataset, a set of 10 “design guideline” subsamples was selected, consisting of 12 monthly samples and 8 targeted storm samples per year. The selection was conducted in a manner that preserved the overall intensity of storm sampling in the baseline data. These 10 subsamples were further manipulated to create “heterogeneous” subsamples by removing storm samples prior to 2003. The maximum relative difference between flow-normalized flux estimated in a single year from any of the 10 design guideline subsamples and values estimated in the corresponding year from baseline data was smallest for dissolved inorganic nitrogen (median of 8 stations = 6 percent of baseline estimate), but more appreciable for total phosphorus and sediment (medians of 22 and 32 percent, respectively). The maximum relative difference between flow-normalized flux estimated from from the 10 heterogeneous subsamples and values estimated in the corresponding year from baseline data was more pronounced, with medians for 8 stations of 15, 30, and 53 percent of the corresponding baseline estimates for dissolved inorganic nitrogen, total phosphorus, and sediment, respectively. The worst-case maximum relative differences between flow-normalize flux estimated in a single year from the 10 heterogeneous subsamples and values estimated in the corresponding year from baseline data were 25 percent for dissolved inorganic nitrogen, 37 percent for total phosphorus, and 250 percent for sediment. The results for the heterogeneous subsamples indicate that changes in storm sampling frequency can result in appreciable distortion of estimated trends in flow-normalized flux, especially for total phosphorus and sediment. Trend lines estimated from heterogeneous subsamples tended to converge with the trend lines estimated from baseline data after 2003. In contrast, 2003–12 trends based on subsamples truncated by discarding all data prior to the induced heterogeneity in 2003 showed appreciable biases and differences in slope, relative to the corresponding 2003–12 segment of the trend computed from the design guideline subsamples. Overall, the results indicate that for particulate constituents, load and trend estimates computed using long-term records recently converted to CBNTN design guideline sampling protocols will be most reliable if the trend is computed using the entire record, but reported only for the period that design guideline sampling protocols were followed.
\nInconsistencies related to changing laboratory methods were also examined via two manipulative experiments. In the first experiment, increasing and decreasing “stair-step” patterns of changes in censoring level, overall representing a factor-of-five change in the laboratory reporting limit, were artificially imposed on a 27-year record with no censoring and a period-of-record concentration trend of –68.4 percent. Trends estimated on the basis of the manipulated records were broadly similar to the original trend (–63.6 percent for decreasing censoring levels and –70.3 percent for increasing censoring levels), lending a degree of confidence that the survival regression routines upon which WRTDS is based are generally robust to data censoring. The second experiment considered an abrupt disappearance of low-concentration observations of total phosphorus, associated with a laboratory method change and not reflected through censoring, near the middle of a 28-year record. By process of elimination, an upward shift in the estimated flow-normalize concentration trend line around the same time was identified as a likely artifact resulting from the laboratory method change, although a contemporaneous change in watershed processes cannot be ruled out. Decisions as to how to treat records with potential sampling protocol or laboratory methods-related artifacts should be made on a case-by-case basis, and trend results should be appropriately qualified.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155133","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program","usgsCitation":"Chanat, J.G., Moyer, D.L., Blomquist, J.D., Hyer, K.E., and Langland, M.J., 2016, Application of a weighted regression model for reporting nutrient and sediment concentrations, fluxes, and trends in concentration and flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, results through water year 2012: U.S. Geological Survey Scientific Investigations Report 2015–5133, 76 p., https://dx.doi.org/10.3133/sir20155133.","productDescription":"Report: viii, 74 p.; 5 Appendixes","numberOfPages":"88","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-063310","costCenters":[{"id":614,"text":"Virginia Water Science 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3","size":"452 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2015-5133","linkHelpText":"Table 1 - Annual Results"},{"id":314015,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5133/pdf/sir20155133_app3_intro.pdf","text":"Appendix 3","size":"421 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5133","linkHelpText":"Introduction (Table 1 and 2)"},{"id":314014,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5133/pdf/sir20155133_appendix2.pdf","text":"Appendix 2","size":"211 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5133"},{"id":314013,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5133/pdf/sir20155133_appendix1.pdf","text":"Appendix 1","size":"523 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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http://va.water.usgs.gov/
Bioenergetics modeling was used to determine individual and population consumption by Bloater Coregonus hoyi in Lake Michigan during three time periods with variable Bloater density: 1993–1996 (high), 1998–2002 (intermediate), and 2009–2011 (low). Despite declines in Bloater abundance between 1993 and 2011, our results did not show any density-dependent compensatory response in annual individual consumption, specific consumption, or proportion of maximum consumption consumed. Diporeia spp. accounted for a steadily decreasing fraction of annual consumption, and Bloater were apparently unable to eat enough Mysis diluviana or other prey to account for the loss of Diporeia in the environment. The fraction of production of both Diporeia and Mysis that was consumed by the Bloater population decreased over time so that the consumption-to-production ratio for Diporeia + Mysis was 0.74, 0.26, and 0.14 in 1993–1996, 1998–2002, and 2009–2011, respectively. Although high Bloater numbers in the 1980s to 1990s may have had an influence on populations of Diporeia, Bloater were not the main factor driving Diporeia to a nearly complete disappearance because Diporeia continued to decline when Bloater predation demands were lessening. Thus, there appears to be a decoupling in the inverse relationship between predator and prey abundance in Lake Michigan. Compared with Alewife Alosa pseudoharengus, the other dominant planktivore in the lake, Bloater have a lower specific consumption and higher gross conversion efficiency (GCE), indicating that the lake can support a higher biomass of Bloater than Alewife. However, declines in Bloater GCE since the 1970s and the absence of positive responses in consumption variables following declines in abundance suggest that productivity in Lake Michigan might not be able to support the same biomass of Bloater as in the past.
","language":"English","publisher":"Taylor & Franics","doi":"10.1080/00028487.2015.1094130","usgsCitation":"Pothoven, S.A., and Bunnell, D., 2016, A shift in bloater consumption in Lake Michigan between 1993 and 2011 and its effects on Diporeia and Mysis prey: Transactions of the American Fisheries Society, v. 145, no. 1, p. 59-68, https://doi.org/10.1080/00028487.2015.1094130.","productDescription":"10 p.","startPage":"59","endPage":"68","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065492","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":314263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.08862304687499,\n 41.590796851056005\n ],\n [\n -86.63818359375,\n 41.812267143599804\n ],\n [\n -86.36352539062499,\n 42.13082130188811\n ],\n [\n -86.143798828125,\n 42.60970621339408\n ],\n [\n -86.12182617187499,\n 43.13306116240612\n ],\n [\n -86.396484375,\n 43.56447158721811\n ],\n [\n -86.36352539062499,\n 43.810747313446996\n ],\n [\n -86.37451171875,\n 44.07969327425713\n ],\n [\n -86.099853515625,\n 44.512176171071054\n ],\n [\n -85.902099609375,\n 44.793530904744074\n ],\n [\n -85.6494140625,\n 44.66865287227321\n ],\n [\n -85.308837890625,\n 44.85586880735725\n ],\n [\n -85.25390625,\n 45.158800738352134\n ],\n [\n -85.25390625,\n 45.251688256117646\n ],\n [\n -84.847412109375,\n 45.37530235052552\n ],\n [\n -84.8583984375,\n 45.4986468234261\n ],\n [\n -84.979248046875,\n 45.506346901083425\n ],\n [\n -85.05615234375,\n 45.583289756006316\n ],\n [\n -84.92431640625,\n 45.72152152227954\n ],\n [\n -84.66064453125,\n 45.79050946752472\n ],\n [\n -84.79248046875,\n 45.98169518512228\n ],\n [\n -85.198974609375,\n 46.11894150610708\n ],\n [\n -85.528564453125,\n 46.17222297845542\n ],\n [\n -85.6494140625,\n 46.057985244793024\n ],\n [\n -86.165771484375,\n 46.01985337287634\n ],\n [\n -86.385498046875,\n 45.98169518512228\n ],\n [\n -86.978759765625,\n 45.94351068030587\n ],\n [\n -87.3193359375,\n 45.73685954736049\n ],\n [\n -87.4951171875,\n 45.35214524585177\n ],\n [\n -87.791748046875,\n 45.042478050891546\n ],\n [\n -88.033447265625,\n 44.83249999349062\n ],\n [\n -88.099365234375,\n 44.629573191951046\n ],\n [\n -88.13232421875,\n 44.44162421758805\n ],\n [\n -87.879638671875,\n 44.49650533109348\n ],\n [\n -87.5830078125,\n 44.78573392716592\n ],\n [\n -87.440185546875,\n 44.809121700077355\n ],\n [\n -87.440185546875,\n 44.66865287227321\n ],\n [\n -87.64892578125,\n 44.29240108529005\n ],\n [\n -87.637939453125,\n 44.20583500104184\n ],\n [\n -87.703857421875,\n 44.04811573082351\n ],\n [\n -87.857666015625,\n 43.82660134505384\n ],\n [\n -87.802734375,\n 43.731414013769\n ],\n [\n -87.890625,\n 43.50075243569041\n ],\n [\n -87.978515625,\n 43.15710884095329\n ],\n [\n -87.945556640625,\n 42.90816007196054\n ],\n [\n -87.91259765625,\n 42.72280375732727\n ],\n [\n -87.91259765625,\n 42.382894009614056\n ],\n [\n -87.890625,\n 42.187829010590825\n ],\n [\n -87.7587890625,\n 41.934976500546604\n ],\n [\n -87.681884765625,\n 41.73033005046653\n ],\n [\n -87.4951171875,\n 41.582579601430346\n ],\n [\n -87.08862304687499,\n 41.590796851056005\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-08","publicationStatus":"PW","scienceBaseUri":"56977528e4b039675d00a6b4","contributors":{"authors":[{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":588535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David B. 0000-0003-3521-7747 dbunnell@usgs.gov","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":3139,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":588534,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70162100,"text":"70162100 - 2016 - Use of terrestrial field studies in the derivation of bioaccumulation potential of chemicals","interactions":[],"lastModifiedDate":"2018-08-10T09:54:48","indexId":"70162100","displayToPublicDate":"2016-01-13T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Use of terrestrial field studies in the derivation of bioaccumulation potential of chemicals","docAbstract":"Field-based studies are an essential component of research addressing the behavior of organic chemicals, and a unique line of evidence that can be used to assess bioaccumulation potential in chemical registration programs and aid in development of associated laboratory and modeling efforts. To aid scientific and regulatory discourse on the application of terrestrial field data in this manner, this article provides practical recommendations regarding the generation and interpretation of terrestrial field data. Currently, biota-to-soil-accumulation factors (BSAFs), biomagnification factors (BMFs), and bioaccumulation factors (BAFs) are the most suitable bioaccumulation metrics that are applicable to bioaccumulation assessment evaluations and able to be generated from terrestrial field studies with relatively low uncertainty. Biomagnification factors calculated from field-collected samples of terrestrial carnivores and their prey appear to be particularly robust indicators of bioaccumulation potential. The use of stable isotope ratios for quantification of trophic relationships in terrestrial ecosystems needs to be further developed to resolve uncertainties associated with the calculation of terrestrial trophic magnification factors (TMFs). Sampling efforts for terrestrial field studies should strive for efficiency, and advice on optimization of study sample sizes, practical considerations for obtaining samples, selection of tissues for analysis, and data interpretation is provided. Although there is still much to be learned regarding terrestrial bioaccumulation, these recommendations provide some initial guidance to the present application of terrestrial field data as a line of evidence in the assessment of chemical bioaccumulation potential and a resource to inform laboratory and modeling efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/ieam.1717","usgsCitation":"van den Brink, N.W., Arblaster, J.A., Bowman, S.R., Conder, J.M., Elliott, J., Johnson, M.S., Muir, D.C., Natal-da-Luz, T., Rattner, B.A., Sample, B.E., and Shore, R.F., 2016, Use of terrestrial field studies in the derivation of bioaccumulation potential of chemicals: Integrated Environmental Assessment and Management, v. 12, no. 1, p. 135-145, https://doi.org/10.1002/ieam.1717.","productDescription":"11 p.","startPage":"135","endPage":"145","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068305","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471331,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1717","text":"Publisher Index Page"},{"id":314256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-01","publicationStatus":"PW","scienceBaseUri":"56977530e4b039675d00a6c2","contributors":{"authors":[{"text":"van den Brink, Nico W.","contributorId":39229,"corporation":false,"usgs":true,"family":"van den Brink","given":"Nico","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":588524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arblaster, Jennifer A.","contributorId":152218,"corporation":false,"usgs":false,"family":"Arblaster","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":588525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowman, Sarah R.","contributorId":152219,"corporation":false,"usgs":false,"family":"Bowman","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":588526,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conder, Jason M.","contributorId":81294,"corporation":false,"usgs":true,"family":"Conder","given":"Jason","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":588527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elliott, John E.","contributorId":127368,"corporation":false,"usgs":false,"family":"Elliott","given":"John E.","affiliations":[{"id":6779,"text":"Environment Canada, Burlington, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":588528,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Mark S.","contributorId":86058,"corporation":false,"usgs":true,"family":"Johnson","given":"Mark","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":588529,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muir, Derek C.G.","contributorId":68679,"corporation":false,"usgs":true,"family":"Muir","given":"Derek","email":"","middleInitial":"C.G.","affiliations":[],"preferred":false,"id":588530,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Natal-da-Luz, Tiago","contributorId":152220,"corporation":false,"usgs":false,"family":"Natal-da-Luz","given":"Tiago","email":"","affiliations":[],"preferred":false,"id":588531,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":588516,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sample, Bradley E.","contributorId":61135,"corporation":false,"usgs":true,"family":"Sample","given":"Bradley","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":588532,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shore, Richard F.","contributorId":127369,"corporation":false,"usgs":false,"family":"Shore","given":"Richard","email":"","middleInitial":"F.","affiliations":[{"id":6919,"text":"Natural Environment Research Council, UK","active":true,"usgs":false}],"preferred":false,"id":588533,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70173941,"text":"70173941 - 2016 - Combined effects of projected sea level rise, storm surge, and peak river flows on water levels in the Skagit Floodplain","interactions":[],"lastModifiedDate":"2016-06-21T09:16:38","indexId":"70173941","displayToPublicDate":"2016-01-13T09:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"Combined effects of projected sea level rise, storm surge, and peak river flows on water levels in the Skagit Floodplain","docAbstract":"Current understanding of the combined effects of sea level rise (SLR), storm surge, and changes in river flooding on near-coastal environments is very limited. This project uses a suite of numerical models to examine the combined effects of projected future climate change on flooding in the Skagit floodplain and estuary. Statistically and dynamically downscaled global climate model scenarios from the ECHAM-5 GCM were used as the climate forcings. Unregulated daily river flows were simulated using the VIC hydrology model, and regulated river flows were simulated using the SkagitSim reservoir operations model. Daily tidal anomalies (TA) were calculated using a regression approach based on ENSO and atmospheric pressure forcing simulated by the WRF regional climate model. A 2-D hydrodynamic model was used to estimate water surface elevations in the Skagit floodplain using resampled hourly hydrographs keyed to regulated daily flood flows produced by the reservoir simulation model, and tide predictions adjusted for SLR and TA. Combining peak annual TA with projected sea level rise, the historical (1970–1999) 100-yr peak high water level is exceeded essentially every year by the 2050s. The combination of projected sea level rise and larger floods by the 2080s yields both increased flood inundation area (+ 74%), and increased average water depth (+ 25 cm) in the Skagit floodplain during a 100-year flood. Adding sea level rise to the historical FEMA 100-year flood resulted in a 35% increase in inundation area by the 2040's, compared to a 57% increase when both SLR and projected changes in river flow were combined.
","language":"English","publisher":"BioOne","doi":"10.3955/046.090.0106","usgsCitation":"Hamman, J.J., Hamlet, A.F., Fuller, R., and Grossman, E., 2016, Combined effects of projected sea level rise, storm surge, and peak river flows on water levels in the Skagit Floodplain: Northwest Science, v. 90, no. 1, p. 57-78, https://doi.org/10.3955/046.090.0106.","productDescription":"21 p.","startPage":"57","endPage":"78","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063851","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471332,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3955/046.090.0106","text":"Publisher Index Page"},{"id":323967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":323930,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/abs/10.3955/046.090.0106"}],"country":"United States","state":"Washington","county":"Skagit","otherGeospatial":"Skagit Floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.11279296875001,\n 47.56540738772849\n ],\n [\n -123.11279296875001,\n 48.680080770292875\n ],\n [\n -119.4049072265625,\n 48.680080770292875\n ],\n [\n -119.4049072265625,\n 47.56540738772849\n ],\n [\n -123.11279296875001,\n 47.56540738772849\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"90","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576913b4e4b07657d19fefe2","contributors":{"authors":[{"text":"Hamman, Josheph J","contributorId":172118,"corporation":false,"usgs":false,"family":"Hamman","given":"Josheph","email":"","middleInitial":"J","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":639641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hamlet, Alan F.","contributorId":15529,"corporation":false,"usgs":true,"family":"Hamlet","given":"Alan","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":639642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuller, Roger","contributorId":172119,"corporation":false,"usgs":false,"family":"Fuller","given":"Roger","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":639643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":140908,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric E.","email":"egrossman@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":639640,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173995,"text":"70173995 - 2016 - Forcing and variability of nonstationary rip currents","interactions":[],"lastModifiedDate":"2018-03-26T13:51:49","indexId":"70173995","displayToPublicDate":"2016-01-13T04:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Forcing and variability of nonstationary rip currents","docAbstract":"Surface wave transformation and the resulting nearshore circulation along a section of coast with strong alongshore bathymetric gradients outside the surf zone are modeled for a consecutive 4 week time period. The modeled hydrodynamics are compared to in situ measurements of waves and currents collected during the Nearshore Canyon Experiment and indicate that for the entire range of observed conditions, the model performance is similar to other studies along this stretch of coast. Strong alongshore wave height gradients generate rip currents that are observed by remote sensing data and predicted qualitatively well by the numerical model. Previous studies at this site have used idealized scenarios to link the rip current locations to undulations in the offshore bathymetry but do not explain the dichotomy between permanent offshore bathymetric features and intermittent rip current development. Model results from the month‐long simulation are used to track the formation and location of rip currents using hourly statistics, and results show that the direction of the incoming wave energy strongly controls whether rip currents form. In particular, most of the offshore wave spectra were bimodal and we find that the ratio of energy contained in each mode dictates rip current development, and the alongshore rip current position is controlled by the incident wave period. Additionally, model simulations performed with and without updating the nearshore morphology yield no significant change in the accuracy of the predicted surf zone hydrodyanmics indicating that the large‐scale offshore features (e.g., submarine canyon) predominately control the nearshore wave‐circulation system.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JC010990","usgsCitation":"Long, J.W., and Ozkan-Haller, H., 2016, Forcing and variability of nonstationary rip currents: Journal of Geophysical Research C: Oceans, v. 121, no. 1, p. 520-539, https://doi.org/10.1002/2015JC010990.","productDescription":"20 p.","startPage":"520","endPage":"539","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2003-10-01","ipdsId":"IP-065750","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jc010990","text":"Publisher Index Page"},{"id":324145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-14","publicationStatus":"PW","scienceBaseUri":"576a653ae4b07657d1a11da3","contributors":{"authors":[{"text":"Long, Joseph W. 0000-0003-2912-1992 jwlong@usgs.gov","orcid":"https://orcid.org/0000-0003-2912-1992","contributorId":3303,"corporation":false,"usgs":true,"family":"Long","given":"Joseph","email":"jwlong@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":640099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ozkan-Haller, H.T.","contributorId":172266,"corporation":false,"usgs":false,"family":"Ozkan-Haller","given":"H.T.","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":640100,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70173528,"text":"70173528 - 2016 - Global perspectives on the urban stream syndrome","interactions":[],"lastModifiedDate":"2016-06-21T15:11:11","indexId":"70173528","displayToPublicDate":"2016-01-13T02:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Global perspectives on the urban stream syndrome","docAbstract":"Urban streams commonly express degraded physical, chemical, and biological conditions that have been collectively termed the “urban stream syndrome”. The description of the syndrome highlights the broad similarities among these streams relative to their less-impaired counterparts. Awareness of these commonalities has fostered rapid improvements in the management of urban stormwater for the protection of downstream watercourses, but the focus on the similarities among urban streams has obscured meaningful differences among them. Key drivers of stream responses to urbanization can vary greatly among climatological and physiographic regions of the globe, and the differences can be manifested in individual stream channels even through the homogenizing veneer of urban development. We provide examples of differences in natural hydrologic and geologic settings (within similar regions) that can result in different mechanisms of stream ecosystem response to urbanization and, as such, should lead to different management approaches. The idea that all urban streams can be cured using the same treatment is simplistic, but overemphasizing the tremendous differences among natural (or human-altered) systems also can paralyze management. Thoughtful integration of work that recognizes the commonalities of the urban stream syndrome across the globe has benefitted urban stream management. Now we call for a more nuanced understanding of the regional, subregional, and local attributes of any given urban stream and its watershed to advance the physical, chemical, and ecological recovery of these systems.
","language":"English","publisher":"University of Chicago Press","publisherLocation":"Chicago, IL","doi":"10.1086/684940","usgsCitation":"Roy, A.H., Booth, D.B., Capps, K.A., and Smith, B., 2016, Global perspectives on the urban stream syndrome: Freshwater Science, v. 35, no. 1, p. 412-420, https://doi.org/10.1086/684940.","productDescription":"9 p.","startPage":"412","endPage":"420","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063957","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a653be4b07657d1a11dac","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Booth, Derek B.","contributorId":100873,"corporation":false,"usgs":false,"family":"Booth","given":"Derek","email":"","middleInitial":"B.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":640110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capps, Krista A.","contributorId":35456,"corporation":false,"usgs":true,"family":"Capps","given":"Krista","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":640111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Benjamin","contributorId":171838,"corporation":false,"usgs":false,"family":"Smith","given":"Benjamin","affiliations":[],"preferred":false,"id":640112,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157983,"text":"ofr20151190 - 2016 - Reconnaissance sediment budget for selected watersheds of West Maui, Hawai‘i","interactions":[],"lastModifiedDate":"2016-01-13T08:49:08","indexId":"ofr20151190","displayToPublicDate":"2016-01-12T18:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1190","title":"Reconnaissance sediment budget for selected watersheds of West Maui, Hawai‘i","docAbstract":"Episodic runoff brings suspended sediment to the nearshore waters of West Maui, Hawaiʻi. Even small rainfalls create visible plumes over a few hours. We used mapping, field experiments, and analysis of recent (July 19–20, 2014) and historic rainfall to estimate sources of land-based pollution for two watersheds in West Maui: Honolua, and Honokōwai. Former agricultural fields and some unimproved roads are plausible sources for polluted runoff, but have saturated hydraulic conductivities greater than the 10–15 millimeters per hour (mm/hr) rainfalls of July 2014. These fields and roads showed minor evidence for storm runoff, and could not have contributed substantially to July 2014 plume generation. Since 1978, rain at intensities capable of causing runoff from former agricultural fields sustained for 1–2 hours is also rare; such intensities have 2–5 year recurrence rates in the north, and greater than 25 year recurrence rates to the south near Lahaina. Streambanks now eroding into historic terraces of sands, silts, and clays are a more plausible source. Although past large storms contributed to sediment loading, annual plume generation is now caused by smaller rainfalls eroding these near-stream legacy deposits. Treatments of former agricultural fields, roads, and reserve forests are consequently not likely to measurably affect sediment pollution from smaller, more frequent storms. Increased runoff from the development of West Maui has the potential to exacerbate sediment plumes from such storms unless there is an effective strategy to reduce bank erosion. Uncertainties in the extent and erosion rate of historic terraces, however, limit our ability to plan mitigation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151190","usgsCitation":"Stock, J.D., Falinksi, K.A., Callender, T., 2015, Reconnaissance sediment budget for selected watersheds of West Maui, Hawai‘i: U.S. Geological Survey Open-File Report 2015–1190, 42 p., https://www.dx.doi.org/10.3133/ofr20151190.","productDescription":"v, 42 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066158","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":314194,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1190/coverthb.jpg"},{"id":314195,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1190/ofr20151190.pdf","text":"Report","size":"22.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1190"}],"country":"United States","state":"Hawaii","otherGeospatial":"West Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.70074462890625,\n 20.785646688202153\n ],\n [\n -156.70074462890625,\n 21.03804387657284\n ],\n [\n -156.55620574951172,\n 21.03804387657284\n ],\n [\n -156.55620574951172,\n 20.785646688202153\n ],\n [\n -156.70074462890625,\n 20.785646688202153\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center—Flagstaff
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001-1600
http://geomaps.wr.usgs.gov/gmeg/