Recent assessments indicate the emergence of naturally produced lake trout (Salvelinus namaycush) recruitment throughout Lake Huron in the North American Laurentian Great Lakes (>50% of fish <7 years). Because naturally produced fish derived from different stocked hatchery strains are unmarked, managers cannot distinguish strains contributing to natural recruitment. We used 15 microsatellite loci to identify strains of naturally produced lake trout (N= 1567) collected in assessment fisheries during early (2002–2004) and late (2009–2012) sampling periods. Individuals from 13 American and Canadian hatchery strains (N = 1143) were genotyped to develop standardized baseline information. Strain contributions were estimated using a Bayesian inferential approach. Deviance information criteria were used to compare models evaluating strain contributions at different spatial and temporal scales. The best performing models were the most complex models, suggesting that hatchery strain contributions to naturally produced lake trout varied spatially among management districts and temporally between time periods. Contributions of Seneca strain lake trout were consistently high across most management districts, with contributions increasing from early to late time periods (estimates ranged from 52% to 94% for the late period across 8 of 9 districts). Strain contributions deviated from expectations based on historical stocking levels, indicating strains differed with respect to survival, reproductive success, and/or dispersal. Knowledge of recruitment levels of strains stocked in different management districts, and how strain-specific recruitment varies temporally, spatially, and as a function of local or regional stocking is important to prioritize strains for future stocking and management of the transition process from primarily hatchery to naturally produced stocks.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/jhered/esy029","usgsCitation":"Scribner, K.T., Tsehaye, I., Brenden, T.O., Stott, W., Kanefsky, J., and Bence, J., 2018, Hatchery strain contributions to emerging wild lake trout populations in Lake Huron: Journal of Heredity, v. 109, no. 24, p. 675-688, https://doi.org/10.1093/jhered/esy029.","productDescription":"14 p.","startPage":"675","endPage":"688","ipdsId":"IP-094972","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":468482,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/esy029","text":"Publisher Index Page"},{"id":357288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","issue":"24","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-19","publicationStatus":"PW","scienceBaseUri":"5bc02fb3e4b0fc368eb53958","contributors":{"authors":[{"text":"Scribner, Kim T.","contributorId":146113,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","email":"","middleInitial":"T.","affiliations":[{"id":135,"text":"Biological Resources Division","active":false,"usgs":true},{"id":16582,"text":"Department of Fisheries and Wildlife and Department of Zoology, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":744818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tsehaye, Iyob","contributorId":106801,"corporation":false,"usgs":true,"family":"Tsehaye","given":"Iyob","email":"","affiliations":[],"preferred":false,"id":744819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brenden, Travis O.","contributorId":13876,"corporation":false,"usgs":true,"family":"Brenden","given":"Travis","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":744820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stott, Wendylee 0000-0002-5252-4901 wstott@usgs.gov","orcid":"https://orcid.org/0000-0002-5252-4901","contributorId":191249,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","email":"wstott@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":744817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kanefsky, Jeannette","contributorId":72213,"corporation":false,"usgs":true,"family":"Kanefsky","given":"Jeannette","email":"","affiliations":[],"preferred":false,"id":744821,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":744822,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197576,"text":"ofr20181085 - 2018 - Development of an aerial population survey method for elk (Cervus elaphus) in Rocky Mountain National Park, Colorado","interactions":[],"lastModifiedDate":"2018-08-28T11:15:56","indexId":"ofr20181085","displayToPublicDate":"2018-08-24T10:50:00","publicationYear":"2018","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":"2018-1085","displayTitle":"Development of an aerial population survey method for elk (Cervus elaphus) in Rocky Mountain National Park, Colorado","title":"Development of an aerial population survey method for elk (Cervus elaphus) in Rocky Mountain National Park, Colorado","docAbstract":"Since the early 1990s, substantial effort and funding have been expended to conduct research to guide development of a 20-year Elk and Vegetation Management Plan for Rocky Mountain National Park (RMNP) in Colorado. One goal of the plan is to maintain the elk (Cervus elaphus) population size at the lower end of the natural range of variation. To implement management actions called for in the plan, accurate and reliable population estimates are needed, as well as a better understanding of the spatial and temporal distribution of elk. The previous aerial survey protocol and population estimation model used by the park had not been updated since the model’s initial calibration more than 15 years ago and the model was developed with an insufficient number (n=44) of observations. Thus we initiated research to reevaluate, update, and improve elk population estimation protocols for RMNP.
We considered several alternative survey and analysis methods, and concluded that a hybrid population-estimation model using a simultaneous double-observer technique with sighting covariates was the most appropriate and effective aerial survey methodology for this population and the environmental conditions in RMNP. Instructional protocols for conducting these surveys in the future, along with datasheets, are provided in this report’s appendixes.
To develop an improved method for aerial elk surveys, we used elk radio-collar location data from our study and other studies, and applied geographic information system analyses to define the survey area and develop effective, repeatable survey transect lines. We used telemetry data from radio-collared elk to inform our understanding of the temporal and spatial scale of elk movements across the park boundary, elk use of tree cover during potential survey hours, and elk use of different elevations within their range. Determining where elk were during surveys helped to fine-tune a survey design that improved spatial cover-age and decreased costs where possible, while standardizing the method to make it repeatable from year to year. We conducted aerial helicopter surveys to test our methodology in an adaptive, iterative process during three winters: 2007–2008, 2008–2009, and 2009–2010. We gained new information on each survey and used results to refine subsequent surveys.
Our results confirm that elk movements were highly dynamic with respect to park boundary crossings; an average of six round trips from the park to Estes Park, Colorado, and back per month were taken by global positioning system-collared bull elk. We observed a strong diurnal temporal pattern of bull elk use of trees; elk were found in dense tree cover from 15:00−22:00 but not as often during morning and early afternoon hours when surveys were conducted. We used information on elk use of different altitudes to refine and establish a more efficient survey area.
During the time of our study, a concurrent study in the park deployed 120 very high frequency radio collars on elk cows. We used those collar locations during our flights to increase sample size and to evaluate the level of precision we would gain by using “known fates analysis” (in which elk were known to be in the survey area, out of the survey area, or deceased based on radio-collar locations collected simultaneously during aerial surveys). Using radio-collar locations reduced bias by 1.1–8.8 percent and increased precision (that is, reduced the width of confidence intervals). This report provides final population estimates analyzed with and without radio-collar data to demonstrate what is gained by using marked individuals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181085","collaboration":"Prepared in cooperation with Colorado State University and the National Park Service","usgsCitation":"Schoenecker, K.A., Lubow, B.C., and Johnson, T.L., 2018, Development of an aerial population survey method for elk (Cervus elaphus) in Rocky Mountain National Park, Colorado: U.S. Geological Survey Open–File Report 2018–1085, 45 p., https://doi.org/10.3133/ofr20181085.","productDescription":"vii, 45 p.","onlineOnly":"Y","ipdsId":"IP-053382","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":356646,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1085/ofr20181085.pdf","text":"Report","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1085"},{"id":356645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1085/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Estes Valley, Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 40\n ],\n [\n -105.1667,\n 40\n ],\n [\n -105.1667,\n 40.5833\n ],\n [\n -106,\n 40.5833\n ],\n [\n -106,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Expanding populations of North American midcontinent lesser snow geese (Anser caerulescens caerulescens) have potential to alter ecosystems throughout the Arctic and subarctic where they breed. Efforts to understand origins of harvested lesser snow geese to better inform management decisions have traditionally required mark-recapture approaches, while aerial photographic surveys have typically been used to identify breeding distributions. As a potential alternative, isotopic patterns that are metabolically fixed within newly grown flight feathers following summer molting could provide inferences regarding geographic breeding origin of individuals, without the need for prior capture. Our objective was to assess potential to use four stable isotopes (δ13C, δ15N, δ34S, δ2H) from feather material to determine breeding origins. We obtained newly grown flight feathers from individuals during summer banding at three Arctic and two subarctic breeding colonies in 2014 (n = 56) and 2016 (n = 45). We used linear discriminant analyses to predict breeding origins from models using combinations of stable isotopes as predictors and evaluated model accuracy when predicting colony, subregion, or subpopulation levels. We found a strong inverse relationship between δ2H values and increasing latitude (R2 = 0.83), resulting in differences (F4, 51 = 90.41, P < 0.0001) among sampled colonies. No differences in δ13C or δ15N were detected among colonies, although δ34S in Akimiski Island, Baffin Island, and Karrak Lake were more enriched (F4, 51 = 11.25, P < 0.0001). Using δ2H values as a predictor, discriminant analyses improved accuracy in classification level as precision decreased [model accuracy = 67% (colony), 88% (subregion), 94% (subpopulation)]. Application of the isotopic methods we describe could be used to provide an alternative monitoring method of population metrics, such as overall breeding population distribution, region-specific productivity and migratory connectivity that are informative to management decision makers and provide insight into cross-seasonal effects that may influence migratory behavior.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0203077","usgsCitation":"Fowler, D., Webb, E.B., Baldwin, F.B., Vrtiska, M., and Hobson, K., 2018, A multi-isotope (δ13C, δ15N, δ34S, δ2H) approach to establishing migratory connectivity in lesser snow geese: Tracking an overabundant species: PLoS, v. 13, no. 8, e0203077, 15 p., https://doi.org/10.1371/journal.pone.0203077.","productDescription":"e0203077, 15 p.","ipdsId":"IP-097656","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":482051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0203077","text":"Publisher Index Page"},{"id":481932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada","otherGeospatial":"Baffin Island, Southampton Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.14605880996054,\n 66.52398087003161\n ],\n [\n -89.14605880996054,\n 60.50650251248149\n ],\n [\n -77.36182951496465,\n 60.50650251248149\n ],\n [\n -77.36182951496465,\n 66.52398087003161\n ],\n [\n -89.14605880996054,\n 66.52398087003161\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Fowler, Drew N.","contributorId":274651,"corporation":false,"usgs":false,"family":"Fowler","given":"Drew N.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":926997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":926998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Frank B 0000-0003-4797-5959","orcid":"https://orcid.org/0000-0003-4797-5959","contributorId":329810,"corporation":false,"usgs":false,"family":"Baldwin","given":"Frank","email":"","middleInitial":"B","affiliations":[{"id":12590,"text":"Canadian Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":927040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vrtiska, Mark P.","contributorId":274653,"corporation":false,"usgs":false,"family":"Vrtiska","given":"Mark P.","affiliations":[{"id":17640,"text":"Nebraska Game and Parks Commission","active":true,"usgs":false}],"preferred":false,"id":926999,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hobson, Keith A.","contributorId":279772,"corporation":false,"usgs":false,"family":"Hobson","given":"Keith A.","affiliations":[{"id":33186,"text":"Western University","active":true,"usgs":false}],"preferred":false,"id":927000,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70200893,"text":"70200893 - 2018 - Fish Lake limnology and watershed aqueous geochemistry, Fish Lake Plateau, Utah","interactions":[],"lastModifiedDate":"2019-08-23T14:39:32","indexId":"70200893","displayToPublicDate":"2018-08-23T14:37:54","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"title":"Fish Lake limnology and watershed aqueous geochemistry, Fish Lake Plateau, Utah","docAbstract":"Fish Lake is located at 2696 m elevation on the Fish Lake Plateau with a bedrock geology of Oligocene to Pliocene age volcanics and Cretaceous to Eocene age sedimentary rocks. Lake bathymetry indicates a maximum depth of ~27 m and volume of 2.31 x 108 m3. The lake is dimictic with summer water column temperature declines of 13˚C between 7 to 15 m depth, whereas in spring and fall water column is isothermal. Numerous surface streams flow into the lake and there is one surface outflow stream, Lake Creek, which drains to the northeast into Johnson Valley Reservoir and the Fremont River, which is a tributary of the upper Colorado River. Surface inflow streams and spring waters are generally dilute and ionic compositions are consistent with bedrock geology. Spring and creek water oxygen and hydrogen stable isotope compositions indicate snowmelt is the predominant water source to the lake. High evaporative enrichment is indicated by lake water stable oxygen and hydrogen compositions and conservative ions, which suggest evaporative water loss equal or greater than inflow. The ionic and isotope data combined with preliminary discharge measurements provide a preliminary estimated lake-water residence time between approximately 15 and 30 years, although groundwater flux is currently unknown. Dissolved silica concentrations decline by two orders of magnitude between inflowing waters and summer lake waters, indicating substantial uptake by freshwater diatoms and high biological productivity. During summer, epilimnion pH values of 8.7 contribute to slight oversaturation with respect to calcite/aragonite, which suggests that precipitates could form in minor concentration. Below the thermocline pH is near neutral and carbonate mineral dissolution within the water column is likely.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geofluids of Utah","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Utah Geological Association","isbn":"9780998014210","usgsCitation":"David Marchetti, Anderson, L., Donovan, J.J., Harris, M.S., and Huth, T., 2018, Fish Lake limnology and watershed aqueous geochemistry, Fish Lake Plateau, Utah, chap. of Geofluids of Utah, v. 47, p. 55-74.","startPage":"55","endPage":"74","ipdsId":"IP-096056","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":366871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Fish Lake, Fish Lake Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.785888671875,\n 38.51969800337459\n ],\n [\n -111.60186767578125,\n 38.51969800337459\n ],\n [\n -111.60186767578125,\n 38.65334327823747\n ],\n [\n -111.785888671875,\n 38.65334327823747\n ],\n [\n -111.785888671875,\n 38.51969800337459\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"David Marchetti","contributorId":210600,"corporation":false,"usgs":false,"family":"David Marchetti","affiliations":[{"id":38118,"text":"Western Colorado University","active":true,"usgs":false}],"preferred":false,"id":751086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":751085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Joseph J.","contributorId":210601,"corporation":false,"usgs":false,"family":"Donovan","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":751087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, M. Scott mcharris@usgs.gov","contributorId":210602,"corporation":false,"usgs":false,"family":"Harris","given":"M.","email":"mcharris@usgs.gov","middleInitial":"Scott","affiliations":[{"id":35839,"text":"College of Charleston","active":true,"usgs":false}],"preferred":false,"id":751088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huth, Tyler","contributorId":210603,"corporation":false,"usgs":false,"family":"Huth","given":"Tyler","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":751089,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198477,"text":"ofr20181121 - 2018 - Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data","interactions":[],"lastModifiedDate":"2018-08-29T08:50:10","indexId":"ofr20181121","displayToPublicDate":"2018-08-23T12:15:00","publicationYear":"2018","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":"2018-1121","title":"Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data","docAbstract":"The U.S. Geological Survey Coastal and Marine Geology Program uses three methods to derive a datum-based, mean high water shoreline on open-ocean coasts from light detection and ranging (lidar) elevation surveys. This work compared the shorelines produced by the three methods for two different surveys: one survey with simple beach morphology, and one survey with complex beach morphology. For the survey with simple beach morphology, the three methods gave very similar results. The mean differences were less than 0.1 meter, and the root mean square differences were all less than 1.0 meter. For the survey of a beach with complex morphology, the quality control used in the Profile method and Smoothed Contour/Manual Hybrid method produced cleaner shorelines than the Grid method. Only the Profile method can extrapolate if there is no data around mean high water. The Grid and Profile methods produce a point by point estimate of uncertainty which is needed for some applications. Only the Contour method can be easily transferred to external users.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181121","usgsCitation":"Farris, A.S., Weber, K.M., Doran, K.S., and List, J.H., 2018, Comparing methods used by the U.S. Geological Survey Coastal and Marine Geology Program for deriving shoreline position from lidar data: U.S. Geological Survey Open-File Report 2018–1121, 13 p., https://doi.org/10.3133/ofr20181121.","productDescription":"iv, 13 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097675","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":356712,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1121/coverthb.jpg"},{"id":356713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1121/ofr20181121.pdf","text":"Report","size":"977 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1121"}],"contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
The Winnebago Pool is a chain of four shallow lakes (Lake Poygan, Lake Winneconne, Lake Butte des Morts, and Lake Winnebago) that are fed primarily by the Fox and Wolf Rivers, two large agriculturally dominated rivers in Wisconsin, United States. Because the lakes have received extensive phosphorus inputs from their watershed, they have become highly eutrophic with much phosphorus in the water column as well as trapped in their sediments. Each of the four Winnebago Pool lakes has been included on the Wisconsin Department of Natural Resources impaired waters list because of their high total phosphorus concentrations, water-quality use restrictions, and excess algal growth. The study described in this report is part of a Total Maximum Daily Load investigation to determine what actions are needed to improve the water quality (trophic status) of these lakes and thus be able to be removed from the impaired waters list and restore their designated uses. As part of this study, data were collected to describe the existing water quality of the lakes, detailed phosphorus budgets were developed for each of the lakes to describe the different sources of the phosphorus, and two eutrophication models (BATHTUB and Jensen models) were used to determine how much of the phosphorus being input to the lakes needs to be reduced for the lakes to be removed from the impaired waters list and restore their designated uses.
In-lake water-quality data indicated that each of the lakes had extensive vertical mixing that resulted in their water quality deteriorating throughout summer. Each of the lakes had mean summer total phosphorus concentrations exceeding 0.088 milligram per liter (mg/L), well above the 0.040 mg/L criterion for the lakes. Detailed phosphorus budgets for the lakes indicated that the primary sources of phosphorus were from their tributaries (for the most upstream lake in the Winnebago Pool–Lake Poygan) or from a combination of input from the upstream lakes and phosphorus release from the bottom sediment when only the summer months were considered (for the other three lakes).
Model simulations with the BATHTUB and Jensen models indicated that (1) the lakes should have almost linear response in their total phosphorus concentrations to changes in their phosphorus inputs; (2) phosphorus inputs need to be reduced by about 60 percent to the Upper Pool Lakes and 69–73 percent to Lake Winnebago to reduce their mean summer total phosphorus concentrations to 0.040 mg/L; and (3) if all the anthropogenic phosphorus inputs to the lakes could be eliminated, their best possible mean summer total phosphorus concentrations should decrease to about 0.022–0.028 mg/L in the Upper Pool Lakes and to 0.032–0.033 mg/L in Lake Winnebago. The effects of any reduction in phosphorus loading will take many years (50 to more than 75 years) to be fully realized in lake water quality because of phosphorus release from the lake sediments. The effects of nutrient reductions in the watershed of a chain of lakes, such as the Winnebago Pool, gradually cascades down the chain, which has beneficial and detrimental effects. Any action made in the watershed of upstream lakes to reduce phosphorus inputs should improve the water quality of all downstream lakes; however, the upstream lakes delay the response in the downstream lakes, especially in lakes where internal phosphorus loading is important.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185099","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Robertson, D.M., Siebers, B.J., Diebel, M.W., and Somor, A.J., 2018, Water-quality response to changes in phosphorus loading of the Winnebago Pool Lakes, Wisconsin, with special emphasis on the effects of internal loading in a chain of shallow lakes: U.S. Geological Survey Scientific Investigations Report 2018–5099, 58 p., https://doi.org/10.3133/sir20185099.","productDescription":"Report: ix, 58 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-094896","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":356707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5099/coverthb.jpg"},{"id":356708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5099/sir20185099.pdf","text":"Report","size":"3.70 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5099"},{"id":356709,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y8BE4H","text":"USGS data release","description":"USGS data release","linkHelpText":"Eutrophication water-quality models and supporting water-quality and phosphorus load data used to simulate changes in the water quality of the Winnebago Pool Lakes, Wisconsin, in response to change in phosphorus loading"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Winnebago Pool Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90,\n 43.5\n ],\n [\n -88.25,\n 43.5\n ],\n [\n -88.25,\n 45.75\n ],\n [\n -90,\n 45.75\n ],\n [\n -90,\n 43.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Seismic hazard models are important for society, feeding into building codes and hazard mitigation efforts. These models, however, rest on many uncertain assumptions and are difficult to test observationally because of the long recurrence times of large earthquakes. Physics-based earthquake simulators offer a potentially helpful tool, but they face a vast range of fundamental scientific uncertainties. We compare a physics-based earthquake simulator against the latest seismic hazard model for California. Using only uniform parameters in the simulator, we find strikingly good agreement of the long-term shaking hazard compared with the California model. This ability to replicate statistically based seismic hazard estimates by a physics-based model cross-validates standard methods and provides a new alternative approach needing fewer inputs and assumptions for estimating hazard.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.aau0688","usgsCitation":"Shaw, B.E., Milner, K.R., Field, E., Richards-Dinger, K.B., Gilchrist, J.J., Dieterich, J.H., and Jordan, T.H., 2018, A physics-based earthquake simulator replicates seismic hazard statistics across California: Science Advances, v. 4, no. 8, p. 1-9, https://doi.org/10.1126/sciadv.aau0688.","productDescription":"eaau0688; 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-098977","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468484,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aau0688","text":"Publisher Index Page"},{"id":357666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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H.","contributorId":198156,"corporation":false,"usgs":false,"family":"Dieterich","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":745984,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordan, Thomas H.","contributorId":75055,"corporation":false,"usgs":true,"family":"Jordan","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":745985,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198812,"text":"ofr20181136 - 2018 - Social attraction used to establish Caspian tern (Hydroprogne caspia) nesting colonies on modified islands at the Don Edwards San Francisco Bay National Wildlife Refuge, California—Final report","interactions":[],"lastModifiedDate":"2018-08-27T10:51:56","indexId":"ofr20181136","displayToPublicDate":"2018-08-22T09:02:22","publicationYear":"2018","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":"2018-1136","displayTitle":"Social attraction used to establish Caspian tern (Hydroprogne caspia) nesting colonies on modified islands at the Don Edwards San Francisco Bay National Wildlife Refuge, California—Final report","title":"Social attraction used to establish Caspian tern (Hydroprogne caspia) nesting colonies on modified islands at the Don Edwards San Francisco Bay National Wildlife Refuge, California—Final report","docAbstract":"To address the 2008/2010 and Supplemental 2014 National Oceanic and Atmospheric Administration Fisheries Biological Opinion for operation of the Federal Columbia River Power System, the U.S. Army Corps of Engineers (USACE) and the Bureau of Reclamation (Reclamation) developed and began implementation of Caspian tern (Hydroprogne caspia) management plans. This implementation includes redistribution of the Caspian terns in the Columbia River estuary and the mid-Columbia River region to reduce predation on salmonids listed under the Endangered Species Act. Key elements of the plans are (1) reduction of nesting habitat for Caspian terns in the Columbia River estuary and the mid-Columbia River region, and (2) creation or modification of nesting habitat at alternative sites within the Caspian tern breeding range. As part of this effort, USACE and Reclamation developed Caspian tern nesting habitat at the U.S. Fish and Wildlife Service Don Edwards San Francisco Bay National Wildlife Refuge (DENWR), California, prior to the 2015 nesting season. Furthermore, nesting habitat for western snowy plovers (Charadrius alexandrinus nivosus) also was developed to provide separate nesting opportunities in the same managed ponds to reduce potential conflicts with Caspian terns. Specifically, seven recently constructed islands within two managed ponds (Ponds A16 and SF2) of DENWR were modified to provide habitat attractive to nesting Caspian terns (5 islands) and snowy plovers (2 islands). These 7 islands were a subset of 46 islands recently constructed in Ponds A16 and SF2 to provide waterbird nesting habitat as part of the South Bay Salt Pond (SBSP) Restoration Project.
We used social attraction methods (decoys and electronic call systems) to attract Caspian terns and snowy plovers to these seven modified islands, and conducted surveys from March to September of 2015, 2016, and 2017 to evaluate nest numbers, nest density, and productivity. Results from the 2015 nesting season, the first year of the study, indicated that island modifications and social attraction measures were successful in establishing Caspian tern breeding colonies at Ponds A16 and SF2 of DENWR. Prior to 2015, there was no history of Caspian terns nesting in either Pond A16 or Pond SF2. The success of 2015 continued in 2016 and 2017. In 2017, the third and final year of the project, Caspian terns initiated at least 664 nests, fledged at least 239 chicks, and had a breeding success rate of 0.36 fledged chicks per breeding pair. This represents a 171 percent increase in the number of breeding pairs and a 41 percent increase in the number of chicks fledged, but a 48 percent decrease in the fledglings produced per breeding pair in 2017 compared to 2015, the first year the colonies were established. The two new large and growing Caspian tern nesting colonies at Ponds A16 and SF2 demonstrate the effectiveness of social attraction measures in helping to establish tern nesting colonies in San Francisco Bay. Social attraction measures similar to those used in this study, but targeting other colonial species such as Forster’s terns (Sterna forsteri) and American avocets (Recurvirostra americana), may help to establish waterbird breeding colonies at wetlands enhanced as part of the SBSP Restoration Project.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181136","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Bureau of Reclamation","usgsCitation":"Hartman, C.A., Ackerman, J.T., Herzog, M.P., Strong, C., Trachtenbarg, D., and Shore, C.A., 2018, Social attraction used to establish Caspian tern (Hydroprogne caspia) nesting colonies on modified islands at the Don Edwards San Francisco Bay National Wildlife Refuge, California—Final report: U.S. Geological Survey Open-File Report 2018-1136, 41 p., https://doi.org/10.3133/ofr20181136.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-096017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":356703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1136/coverthb.jpg"},{"id":356704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1136/ofr20181136.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1136"}],"country":"United States","state":"California","otherGeospatial":"Don Edwards San Francisco Bay National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.30667114257812,\n 37.38488959341307\n ],\n [\n -121.87889099121092,\n 37.38488959341307\n ],\n [\n -121.87889099121092,\n 37.637616213035884\n ],\n [\n -122.30667114257812,\n 37.637616213035884\n ],\n [\n -122.30667114257812,\n 37.38488959341307\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Detailed information on the nutrition of free-ranging mammals contributes to the understanding of life history requirements, yet is often quite limited temporally for most species. Reliable dietary inferences can be made by analyzing the stable carbon (C) and nitrogen (N) isotopic values (δ13C and δ15N) of some consumer tissues; exactly which tissue is utilized dictates the inferential scope. Steller sea lion (SSL) vibrissae are grown continuously without shedding and thus provide a continuous multi-year record of dietary consumption. We applied a novel kernel density approach to compare the δ13C and δ15N values along the length of SSL vibrissae with δ13C and δ15N distributions of potential prey species. This resulted in time-series of proportion estimates of dietary consumption for individual SSL. Substantial overlap in δ13C and δ15N distributions for prey species prevented a discrete species-scale assessment of SSL diets; however, a post hoc correlational analysis of diet proportion estimates revealed grouping by trophic level. Our findings suggest that adult female SSL diets in the western and central Aleutian Islands shift significantly according to season: diets contain a higher proportion of lower trophic level species (Pacific Ocean perch, northern rockfish, Atka mackerel and walleye pollock) in the summer, whereas in the winter SSL consume a much more diverse diet which includes a greater proportion of higher trophic level species (arrowtooth flounder, Kamchatka flounder, darkfin sculpin, Pacific cod, Pacific octopus, rock sole, snailfish, and yellow Irish lord).
","language":"English","publisher":"Springer","doi":"10.1007/s00442-018-4173-8","usgsCitation":"Doll, A.C., Taras, B.D., Stricker, C.A., Rea, L.D., O'Hara, T., Cyr, A., Mcdermott, S., Loomis, T., Fadely, B.S., and Wunder, M., 2018, Temporal records of diet diversity dynamics in individual adult female Steller sea lion (Eumetopias jubatus) vibrissae: Oecologia, v. 188, no. 1, p. 263-275, https://doi.org/10.1007/s00442-018-4173-8.","productDescription":"13 p.","startPage":"263","endPage":"275","ipdsId":"IP-077908","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":356689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"188","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5b98a281e4b0702d0e842f05","contributors":{"authors":[{"text":"Doll, Andrew C.","contributorId":139566,"corporation":false,"usgs":false,"family":"Doll","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":743197,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taras, Brian D.","contributorId":207216,"corporation":false,"usgs":false,"family":"Taras","given":"Brian","email":"","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":743198,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":743196,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rea, Lorrie D.","contributorId":82143,"corporation":false,"usgs":false,"family":"Rea","given":"Lorrie","email":"","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":743199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O'Hara, Todd M.","contributorId":34768,"corporation":false,"usgs":false,"family":"O'Hara","given":"Todd M.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":743200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cyr, Andrew P.","contributorId":207217,"corporation":false,"usgs":false,"family":"Cyr","given":"Andrew P.","affiliations":[{"id":7097,"text":"University of Alaska-Fairbanks","active":true,"usgs":false}],"preferred":false,"id":743201,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mcdermott, S.","contributorId":207218,"corporation":false,"usgs":false,"family":"Mcdermott","given":"S.","email":"","affiliations":[{"id":37482,"text":"National Oceanographic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":743202,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loomis, T.M.","contributorId":207219,"corporation":false,"usgs":false,"family":"Loomis","given":"T.M.","email":"","affiliations":[{"id":37483,"text":"Ocean Peace Inc.","active":true,"usgs":false}],"preferred":false,"id":743203,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fadely, Brian S.","contributorId":184042,"corporation":false,"usgs":false,"family":"Fadely","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":743205,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wunder, Michael B.","contributorId":80599,"corporation":false,"usgs":false,"family":"Wunder","given":"Michael B.","affiliations":[{"id":6674,"text":"Department of Integrative Biology, University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":743204,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198885,"text":"ofr20181128 - 2018 - Evaluation of key scientific issues in the report, “State of the mountain lion—A call to end trophy hunting of America’s lion”","interactions":[],"lastModifiedDate":"2018-08-27T10:44:51","indexId":"ofr20181128","displayToPublicDate":"2018-08-22T08:43:00","publicationYear":"2018","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":"2018-1128","title":"Evaluation of key scientific issues in the report, “State of the mountain lion—A call to end trophy hunting of America’s lion”","docAbstract":"In their recently published report, State of the Mountain Lion: A Call to End Trophy Hunting of America’s Lion, the Humane Society of the United States suggested that mountain lion (Puma concolor) hunting should be abolished in the United States. The report claims this recommendation is based on scientific arguments that demonstrate the overharvest of mountain lions throughout much of their current range in the United States. We reviewed the science presented by the Humane Society to support their call for the cessation of mountain lion hunting. Rather than provide a rigorous assessment of the peer-reviewed scientific literature and available data on mountain lion ecology, population dynamics and management, the report uses a fundamentally unscientific approach that starts with an a priori assumption that hunting is detrimental to the long-term persistence of mountain lion populations, then attempts to use scientific arguments to support this value-based position. The report frequently ignores or selectively interprets relevant peer-reviewed literature, weakening the scientific credibility of the report. The report relies on imprecise and inadequate demographic measures, questionable data, and simplistic methodologies to derive dubious estimates of potential lion densities; it compares these estimates to various measures produced by State agencies (which themselves vary in reliability as estimates of abundance) to purportedly illustrate the detrimental effects of hunting. The approach used in the report to support the predetermined supposition that mountain lion populations are over-hunted fails to serve as a scientifically defensible foundation for management recommendations range-wide or at the State level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181128","usgsCitation":"Cain, J.W., III, and Mitchell, M.S., 2018, Evaluation of key scientific issues in the report, “State of the mountain lion—A call to end trophy hunting of America’s lion”: U.S. Geological Survey Open-File Report 2018-1128, 14 p., https://doi.org/10.3133/ofr20181128.","productDescription":"iv, 14 p.","onlineOnly":"Y","ipdsId":"IP-098716","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":356705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1128/coverthb.jpg"},{"id":356706,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1128/ofr20181128.pdf","text":"Report","size":"5.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1128"}],"contact":"Leader, Washington Cooperative Fish and Wildlife Research Unit
U.S. Geological Survey
Fishery Sciences Building, Box 355020
University of Washington
Seattle, Washington, 98195
The Castle Rock quadrangle is in the northeast corner of Chemehuevi Valley, California and Arizona. It includes the Colorado River’s entrance to the valley at the mouth of Topock Gorge and the northern outskirts of Lake Havasu City, Arizona, and the Chemehuevi Indian Tribe community of Havasu Lake, California. The map includes large parts of the Chemehuevi Indian Reservation and the Havasu National Wildlife Refuge. Upon its exit through the mouth of Topock Gorge, the Colorado River enters Chemehuevi Valley where its floodplain (now submerged under Lake Havasu) is flanked by alluvial piedmonts of the Chemehuevi and Mohave Mountains to the west and east, respectively. This abrupt transition offers a useful perspective into the structural evolution of the Colorado River extensional corridor and of the Colorado River itself. It contains key structural and stratigraphic elements recording a complex history of Cretaceous plutonism and deformation, significant tectonic extension, volcanism, and sedimentation in the Miocene, and, ultimately, the evolution of the Colorado River from the latest Miocene to the present. Lake Havasu submerged the axis of Chemehuevi Valley following the completion of Parker Dam in 1938, and the Colorado River now feeds a verdant delta marsh that composes part of the map. Important bedrock units include the Cretaceous Chemehuevi Mountains Plutonic Suite, the 18.78 Ma Peach Spring Tuff, and thick overlying sequences of interlayered Miocene megabreccia and fanglomerate. The exposure of these units is closely linked to extension along the Chemehuevi-Whipple Mountains detachment fault system. The complex bedrock geologic framework serves as the structural and topographic foundation for the key strata chronicling the evolution of the lower Colorado River. Important stratigraphic units that bear on its evolution to the present day include the Bouse Formation, the Bullhead Alluvium, and the Chemehuevi Formation. The map area also contains the river’s modern delta at the head of Lake Havasu.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3411","usgsCitation":"House, P.K., John, B.E., Malmon, D.V., Block, D., Beard, L.S., Felger, T.J., Crow, R.S., Schwing, J.E., and Cassidy, C.E., 2018, Geologic map of the Castle Rock 7.5' quadrangle, Arizona and California: U.S. Geological Survey Scientific Investigations Map 3411, scale 1:24,000, pamphlet 15 p., https://doi.org/10.3133/sim3411.","productDescription":"Pamphlet: iii, 15 p.; 1 Sheet: 41.0 x 30.0 inches; Database; Metadata; Read Me","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078411","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":399120,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_107707.htm"},{"id":356669,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3411/sim3411_readme.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3411"},{"id":356668,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3411/sim3411_database.zip","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3411"},{"id":356667,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3411/sim3411_metadata","text":"Metadata folder","description":"SIM 3411"},{"id":356664,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3411/coverthb.jpg"},{"id":356666,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3411/sim3411_map.pdf","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3411"},{"id":356665,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3411/sim3411_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3411"}],"country":"United States","state":"Arizona, California","otherGeospatial":"Castle Rock 7.5' quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.5,\n 34.5\n ],\n [\n -114.375,\n 34.5\n ],\n [\n -114.375,\n 34.625\n ],\n [\n -114.5,\n 34.625\n ],\n [\n -114.5,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Flagstaff, Arizona
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001-1600
Climate change will affect stream systems in numerous ways over the coming century. Globally, streams are expected to experience changes in temperature and flow regime. Previous work has indicated that these changes will likely affect fish distributions, but little work has been conducted examining population level effects of climate change on warmwater fish at the warmest portion of their range. We model several potential climate change-related stressors and the resulting effects on smallmouth bass Micropterus dolomieu populations in the Buffalo National River, Arkansas, USA, located near the southern extent of smallmouth bass range. Smallmouth bass are a popular recreational fish in the region and angler harvest likely contributes substantially to annual mortality. We created a simulation model parameterized with data collected from the Buffalo National River to evaluate the relative importance of climate stressors and angler harvest on smallmouth bass populations. Our simulations suggest that increases in springtime temperature and reductions in river discharge during the spawning period could increase recruitment, resulting in increases in adult abundance (8% higher). However, when increased flooding and drought probabilities are considered, our model indicates the Buffalo National River could experience large reductions in adult smallmouth bass abundance (≥50% decline) and increased probability of extinction compared to present levels. Simulations showed that harvest reduction could be a viable strategy to reduce the negative effects of climate change, but that even with complete closure of harvest, smallmouth bass population levels would still be well below present abundance (46% lower than present). Efforts to reduce flooding and drought effects related to climate change in the Buffalo National River could help offset the predicted reduction in the smallmouth bass population.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0202737","usgsCitation":"Middaugh, C.R., and Magoulick, D.D., 2018, Forecasting effects of angler harvest and climate change on smallmouth bass abundance at the southern edge of their range: PLoS ONE, v. 13, no. 8, p. 1-18, https://doi.org/10.1371/journal.pone.0202737.","productDescription":"e0202737; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-090536","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468487,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0202737","text":"Publisher Index Page"},{"id":357857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Buffalo National River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93,\n 35.75\n ],\n [\n -92.33,\n 35.75\n ],\n [\n -92.33,\n 36.33\n ],\n [\n -93,\n 36.33\n ],\n [\n -93,\n 35.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-20","publicationStatus":"PW","scienceBaseUri":"5bc02fb3e4b0fc368eb5395c","contributors":{"authors":[{"text":"Middaugh, Christopher R.","contributorId":177019,"corporation":false,"usgs":false,"family":"Middaugh","given":"Christopher","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":746547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":746546,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197361,"text":"ofr20181089 - 2018 - Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey","interactions":[],"lastModifiedDate":"2018-08-24T12:37:46","indexId":"ofr20181089","displayToPublicDate":"2018-08-20T14:30:00","publicationYear":"2018","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":"2018-1089","title":"Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey","docAbstract":"The U.S. Geological Survey (USGS) uses Maintenance of Variance Extension Type 1 (MOVE.1) regression to transfer streamflows measured at long-term continuous-record streamgaging stations to partial-record (PR) streamgaging stations where intermittent base-flow measurements are available. MOVE.1 regression is used widely throughout the hydrologic community to extend historic low flows and low-flow statistics at continuous-record streamgaging stations to streamgaging stations that have access to only a partial record of low flows. The method correlates base-flow measurements at PR streamgaging stations with daily mean streamflows measured at index stations that exhibit similar streamflow characteristics.
Following changes in the computing platform for storing, processing, retrieving, and publishing National Water Information System (NWIS) hydrologic data, legacy Statistical Analysis System (SAS) code developed by the USGS to implement the MOVE.1 regression was no longer suitable for reading and processing NWIS streamflow data. To migrate the MOVE.1 program so that it could continue to read streamflow data using the new hydrologic data platform, the SAS code was re-written in R, an open source programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The work described in this report was performed in a study conducted by USGS in cooperation with the New Jersey Department of Environmental Protection.
During migration from SAS to R, graphical and tabular output generated by the R script was compared to output produced by the legacy SAS code to ensure that equations used to perform the MOVE.1 regression remained the same. An option to perform censored MOVE.1 regression was added to extend the MOVE.1 methodology to cases where one or more measured continuous-record or PR streamgaging station flows are zero valued. In addition to permitting censored regression, the new R script includes an option to perform piecewise MOVE.1 regression when the relation between PR station and index station low flows varies significantly across the range of index station streamflows.
Together with traditional MOVE.1 regression, censored, and piecewise MOVE.1 regression methods implemented by the R script offer less biased estimates than ordinary least squares regression for the annual 7-day 10-year and other low-flow statistics at PR stations for a range of base-flow conditions. The R script is used to implement the MOVE.1 regression methods across a variety of computing platforms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181089","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Colarullo, S.J., Sullivan, S.L., and McHugh, A.R., 2018, Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey: U.S. Geological Survey Open-File Report 2018–1089, 20 p., https://doi.org/10.3133/ofr20181089.","productDescription":"v, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-089567","costCenters":[{"id":470,"text":"New Jersey Water Science 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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The maps and graphs in this summary describe national streamflow conditions for water year 2017 (October 1, 2016, to September 30, 2017) in the context of streamflow ranks relative to the 88-year period of 1930–2017, unless otherwise noted. The illustrations are based on observed data from the U.S. Geological Survey (USGS) National Streamflow Network (U.S. Geological Survey, 2018a). The period of 1930–2017 was used because the number of streamgages before 1930 was too small to provide representative data for computing statistics for most regions of the country.
In the summary, reference is made to the term “runoff,” which is the depth to which a river basin, State, or other geographic area would be covered with water if all the streamflow within the area during a specified period was uniformly distributed on it. The value of runoff quantifies the magnitude of water flowing through the Nation’s rivers and streams in measurement units that can be compared from one area to another. In this summary, runoff for a specified period and geographic area is computed from all streamgages with complete record in the geographic area.
In all the graphics, a rank of 1 indicates the highest annual flow of all years analyzed and 88 indicates the lowest annual flow of all years. Rankings of streamflow are grouped into much below normal, below normal, normal, above normal, and much above normal based on percentiles of flow (less than 10 percent, 10–24 percent, 25–75 percent, 76–90 percent, and greater than 90 percent, respectively; U.S. Geological Survey, 2018b). States or water-resources regions are presented in the text in order of ranking; a highest or lowest rank is not shown when there are ties in the rankings. Some of the data used to produce the maps and graphs are provisional and subject to change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183056","usgsCitation":"Jian, X., Wolock, D.M., Brady, S.J., and Lins, H.F., 2018, Streamflow—Water year 2017: U.S. Geological Survey Fact Sheet 2018–3056, 6 p., https://doi.org/10.3133/fs20183056.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-098559","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":356612,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3056/fs20183056.pdf","text":"Report","size":"622 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3056"},{"id":356611,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3056/coverthb.jpg"}],"country":"United States","contact":"U.S. Geological Survey
MS 415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Detection represents an important limitation of accurately estimating population size, abundance, and habitat suitability for wildlife, which can be especially true for cryptic animals. Moreover, for reptiles, juveniles are often less likely to be detected than later life stages. In the case of invasive species, preventing false negatives early in the invasion process can be critical for improving outcomes of control measures. We evaluated habitat structure in relation to catch per unit effort (CPUE) and mean size of trapped invasive brown treesnakes (Boiga irregularis) on Guam. We used a 5‐ha enclosure containing a known, closed population of brown treesnakes to identify key habitat variables that related to CPUE and mean size of trapped snakes over six years. We then tested the relationship of those variables to CPUE and mean size of trapped snakes at three sites with suppressed snake populations as a proxy for low‐density populations anticipated to occur during early detection of invasive populations. We found that a coarse measure of habitat structure represented by three forest types correlated with trap detections, as well as finer measures of habitat structure, such as distance to nearest branch and the type of trap support structure used. On average, smaller snakes were captured in traps placed higher in the tree canopy. Some, but not all, habitat variables identified as predictive of CPUE and mean size within the enclosed population pre‐suppression were also predictive at the snake‐suppressed (low‐density proxy) sites. Habitat structure around the sampling unit (a trap) affected detection probability and the size of detected individuals independently of the demographic structure of the population. Measuring wildlife‐habitat relationships of invaders in their novel environments may be one method to improve early detection during invasive species management.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2339","usgsCitation":"Nafus, M.G., Yackel Adams, A.A., Klug, P.E., and Rodda, G.H., 2018, Habitat type and structure affect trap capture success of an invasive snake across variable densities: Ecosphere, v. 9, no. 8, p. 1-14, https://doi.org/10.1002/ecs2.2339.","productDescription":"e02339; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-092718","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468488,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2339","text":"Publisher Index Page"},{"id":437780,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93OMPVO","text":"USGS data release","linkHelpText":"Habitat characterization around standard brown treesnake traps on Guam, 2004 - 2017"},{"id":358816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-20","publicationStatus":"PW","scienceBaseUri":"5c10a953e4b034bf6a7e514d","contributors":{"authors":[{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klug, Page E.","contributorId":210065,"corporation":false,"usgs":false,"family":"Klug","given":"Page","email":"","middleInitial":"E.","affiliations":[{"id":38064,"text":"USDA WS NWRC","active":true,"usgs":false}],"preferred":false,"id":749742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodda, Gordon H. 0000-0002-6696-7308 roddag@usgs.gov","orcid":"https://orcid.org/0000-0002-6696-7308","contributorId":210066,"corporation":false,"usgs":true,"family":"Rodda","given":"Gordon","email":"roddag@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":749743,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197992,"text":"fs20183028 - 2018 - Assessment of undiscovered oil and gas resources in the Midlands area, England, 2018","interactions":[],"lastModifiedDate":"2018-08-21T22:01:39","indexId":"fs20183028","displayToPublicDate":"2018-08-20T12:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3028","title":"Assessment of undiscovered oil and gas resources in the Midlands area, England, 2018","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered, technically recoverable resources of 319 million barrels of oil and 8.3 trillion cubic feet of gas in the Midlands area of England.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183028","usgsCitation":"Schenk, C.J., Tennyson, M.E., Mercier, T.J., Woodall, C.A., Finn, T.M., Gaswirth, S.B., Le, P.A., Brownfield, M.E., Marra, K.R., and Leathers-Miller, H.M., 2018, Assessment of undiscovered oil and gas resources in the Midlands area, England, 2018 (ver. 1.1, August 2018): U.S. Geological Survey Fact Sheet 2018–3028, 4 p., https://doi.org/10.3133/fs20183028.","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-095693","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":355492,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3028/fs20183028.pdf","text":"Report","size":"3.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3028"},{"id":355491,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3028/coverthb2.jpg"},{"id":356596,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2018/3028/versionHist.txt","size":"4.00 kB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"}],"country":"England","otherGeospatial":"Midlands Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -3.5,\n 52.7\n ],\n [\n 0,\n 52.7\n ],\n [\n 0,\n 54.5\n ],\n [\n -3.5,\n 54.5\n ],\n [\n -3.5,\n 52.7\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0 (July 2018); Version 1.1 (August 2018)","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The availability of cold-water refugia during summertime river-water temperature maximums is important for cold-water fish species including Endangered Species Act listed salmonids since water temperature influences metabolism, growth, and phenology. The U.S. Geological Survey monitored water temperature at 10 sites approximately evenly-spaced along the lower Quinault River on the Olympic Peninsula, Washington, from June 2016 to August 2017 to assess thermal conditions in the lower river. During this 15-month period, there was a near-continuous, 15-minute record at 7 of the sites; complications with thermistors at 3 of the 10 sites limited the temperature dataset to include only summer 2016. In addition, near-streambed and water-surface temperatures were measured along the lower river during a longitudinal survey from August 9 to 12, 2016, during summer baseflow conditions to potentially identify cold or cooler water regions. Measured August water temperatures were warmer than model-predicted August temperatures for the period, 1993–2011. Summertime (July–September) daily minimum temperatures exceeded established salmon habitat threshold temperatures of 16 °C (core summer season) and 17.5 °C (spawning, rearing, and migration periods) for 122 and 65 days, respectively, on average at all monitoring sites with a complete 15-month record that included two summer baseflow periods. Summertime water temperatures at those sites were generally cooler in the downstream direction along the lower Quinault River but became warmer in the downstream direction during the rest of the year, suggesting the river was influenced by diffuse discharge of groundwater with a relatively constant annual temperature. The August longitudinal temperature survey did not detect cold-water refugia (features more than 3 °C cooler than ambient stream water), although it did identify 11 cooler water features (CWF) approximately 100–800 m in length that were 0.1 °C cooler than adjacent upstream or downstream water. The CWFs appeared to correspond to local geomorphic conditions. In August 2017, 10 of the 11 CWFs were field surveyed, and 5 appeared to be influenced by shading from solar radiation by riparian vegetation or steep cliff banks. In addition, field observations suggest that finer scale (that is, less than 10 m) CWFs, specifically individual side pools associated with large, in-channel wood, increased in frequency in the downstream direction along the lower Quinault River. However, this study did not quantify the density or water temperatures associated with these fine-scale features that may serve as cool- or cold-water pockets or patches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181129","collaboration":"Prepared in cooperation with the Quinault Indian Nation","usgsCitation":"Jaeger, K.L., Curran, C.A., Wulfkuhle, E.J., and Opatz, C.O., 2018, Water temperature in the lower Quinault River, Olympic Peninsula, Washington, June 2016–August 2017: U.S. Geological Survey Open-File Report 2018-1129, 24 p., https://doi.org/10.3133/ofr20181129.","productDescription":"Report: iv, 24 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-094010","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":356563,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1129/ofr20181129.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 20181129"},{"id":356562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1129/coverthb.jpg"},{"id":363267,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7C53J2D","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water temperature and depth data for the lower Quinault River during summer baseflow, Washington, August 2016 and 2017"}],"country":"United States","state":"Washington","otherGeospatial":"Lower Quinault RIver, Olympic Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.35,\n 47.55\n ],\n [\n -123.5,\n 47.55\n ],\n [\n -123.5,\n 47.25\n ],\n [\n -124.35,\n 47.25\n ],\n [\n -124.35,\n 47.55\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Data sets with increased spatial and temporal resolution can help researchers and resource managers quantify representative distributional patterns of mobile sportfish. In this research, first, we illustrate patterns of sportfish distribution using individual (percent of population, residence time, number of movements) and combined distributional metrics. Second, we apply these metrics to one highly mobile fish species, the blue catfish (Ictalurus furcatus), across a range of spatial (whole reservoir, region, site) and temporal (year, month, diel period) scales. Specifically, we tracked 123 acoustically tagged blue catfish with a 20-receiver array in Milford Reservoir, KS, USA. When we integrated metrics, four site-specific distributional patterns emerged: (a) a large, active multi-site fish aggregation, (b) localised site fidelity, (c) transitional sites and (d) rarely used locations. These patterns would not have been detected using a single metric as each measurement revealed a different piece of the distribution story. For example, if we had only quantified percent of population, we could identify fish location, but not whether individual fish spent time at a location or were just passing through. Our examination of multiple scales also provided a novel context for interpreting site-specific patterns. As an illustration of this insight, using conventional approaches, we would have observed heterogeneity, but we would not have detected fish aggregations, in which individual fish either remained or repeatedly returned to a site. In summary, our results show the advantage of setting the entire ecosystem as the study boundary to integrate multiple responses using a spatially and temporally extensive data set.
","language":"English","publisher":"Wiley-Blackwell","doi":"10.1111/eff.12438","usgsCitation":"Gerber, K.M., Mather, M.E., Smith, J., and Peterson, Z.J., 2018, Multiple metrics provide context for the distribution of a highly mobile fish predator, the blue catfish: Ecology of Freshwater Fish, v. 28, no. 1, p. 141-155, https://doi.org/10.1111/eff.12438.","productDescription":"15 p.","startPage":"141","endPage":"155","ipdsId":"IP-090557","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488963,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12438","text":"Publisher Index Page"},{"id":395065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Milford Reservoir, Republican River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Unit","active":true,"usgs":false}],"preferred":false,"id":832015,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210260,"text":"70210260 - 2018 - Spatial and temporal variability of pCO2, carbon fluxes and saturation state on the West Florida Shelf","interactions":[],"lastModifiedDate":"2020-05-27T14:06:17.700553","indexId":"70210260","displayToPublicDate":"2018-08-20T09:02:47","publicationYear":"2018","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":"Spatial and temporal variability of pCO2, carbon fluxes and saturation state on the West Florida Shelf","docAbstract":"The West Florida Shelf (WFS) is a source of uncertainty for the Gulf of Mexico carbon budget. Data from the synthesis of approximately 135,000 pCO2 values from over 96 cruises from the WFS show that the shelf waters fluctuate between being a weak source to a weak sink of carbon with the atmosphere. Overall, the shelf acts as a weak source of CO2 at 0.32 ± 1.5 mol m-2 yr-1. Subregions, however, reveal slightly different trends, where surface waters associated with 40 m – 200 m isobaths in the northern and southern WFS are generally weak sinks all year, except for summer when they act as sources of CO2. Conversely, nearshore waters (< 40 m) are a source of CO2 are a source all year round, particularly the southern shallow waters. The pCO2 of seawater has been increasing at a rate of approximately 5.26 µatm yr-1 as compared to atmospheric pCO2 which has increased at a rate of about 1.7 µatm yr-1 from 1996 to 2016. The pCO2 and CO2 flux on the shelf from 1996 - 2016 have increased about 49 µatm, and 1.08 mol m-2, respectively. The WFS is emitting 9.23 Tg C yr-1, with the southern nearshore region emitting the most at 9.01 Tg C yr-1 and the northern region acting as a sink of -1.96 Tg C yr-1.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JC014195","usgsCitation":"Robbins, L., Daley, K., Barbero, L., Wanninkhof, R., Heathcote, R., Zong, H., Lisle, J.T., Cai, W., and Smith, C., 2018, Spatial and temporal variability of pCO2, carbon fluxes and saturation state on the West Florida Shelf: Journal of Geophysical Research C: Oceans, v. 123, no. 9, p. 6174-6188, https://doi.org/10.1029/2018JC014195.","productDescription":"15 p.","startPage":"6174","endPage":"6188","ipdsId":"IP-098275","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468489,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jc014195","text":"Publisher Index Page"},{"id":375073,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"West Florida shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.078125,\n 28.188243641850313\n ],\n [\n -83.84765625,\n 26.470573022375085\n ],\n [\n -81.9580078125,\n 24.886436490787712\n ],\n [\n -80.5078125,\n 24.846565348219734\n ],\n [\n -80.9912109375,\n 26.43122806450644\n ],\n [\n -82.66113281249999,\n 30.372875188118016\n ],\n [\n -87.275390625,\n 30.334953881988564\n ],\n [\n -85.078125,\n 28.188243641850313\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Robbins, L. 0000-0003-3681-1094","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":224952,"corporation":false,"usgs":false,"family":"Robbins","given":"L.","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":789799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daley, K.","contributorId":224953,"corporation":false,"usgs":false,"family":"Daley","given":"K.","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":789800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbero, L.","contributorId":224954,"corporation":false,"usgs":false,"family":"Barbero","given":"L.","email":"","affiliations":[{"id":41004,"text":"NOAA Atlantic Oceanographic & Meterological Laboratory","active":true,"usgs":false}],"preferred":false,"id":789801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wanninkhof, R.","contributorId":224955,"corporation":false,"usgs":false,"family":"Wanninkhof","given":"R.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":789802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heathcote, R.L.","contributorId":182467,"corporation":false,"usgs":false,"family":"Heathcote","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":789803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zong, H.","contributorId":224956,"corporation":false,"usgs":false,"family":"Zong","given":"H.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":789804,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":789805,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cai, W.-J.","contributorId":211651,"corporation":false,"usgs":false,"family":"Cai","given":"W.-J.","affiliations":[{"id":38298,"text":"College of Earth, Ocean, and the Environment, University of Delaware, Newark, Delaware, USA","active":true,"usgs":false}],"preferred":false,"id":789806,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, C.","contributorId":224957,"corporation":false,"usgs":false,"family":"Smith","given":"C.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":789807,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198669,"text":"70198669 - 2018 - Hydrologic performance of retrofit rain gardens in a residential neighborhood (Cleveland Ohio USA) with a focus on monitoring methods","interactions":[],"lastModifiedDate":"2018-11-19T09:03:51","indexId":"70198669","displayToPublicDate":"2018-08-19T08:29:47","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Hydrologic performance of retrofit rain gardens in a residential neighborhood (Cleveland Ohio USA) with a focus on monitoring methods","docAbstract":"Green infrastructure refers to a range of urban stormwater management tools that can be flexibly implemented. These practices can aid in mitigating the negative impacts of runoff by increasing catchment detention capacity. We studied two engineered rain gardens (Cleveland OH) that were designed to infiltrate and detain direct runoff volume generated from an adjacent roadway, and sheet flow from pervious areas of each catchment area. We also accounted for hydrologic interactions between the engineered and upslope basic (non-engineered) rain gardens. A whole water-cycle monitoring approach was employed to fully assess the role of green infrastructure interventions on performance as inflows captured, duration of outflow drainage (i.e., excess moisture), hydrologic losses (e.g., evapotranspiration), and groundwater table dynamics. We found that these tandem rain gardens had good capacity for runoff inflow volumes over the course of over 100 storm events.The integration of green infrastructure in urban landscapes and long-term monitoring for effectiveness and its key functions produces novel data that can be used by researchers and other interested parties to conduct assessments of urban ecosystem functions and leverage these unique datasets by integrating with other datasets as per good scientific practice. We role model good monitoring practice, discuss unique ways to interpret challenging hydraulic circumstances, and conclude with a discussion of monitoring techniques that scale between the simple, passive and elegant; to full-blown research-grade monitoring infrastructure such as that employed in this study.","language":"English","publisher":"Environmental Protection Agency","usgsCitation":"Shuster, W.D., and Darner, R.A., 2018, Hydrologic performance of retrofit rain gardens in a residential neighborhood (Cleveland Ohio USA) with a focus on monitoring methods, ii, 42 p.","productDescription":"ii, 42 p.","ipdsId":"IP-094111","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":359537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":356439,"type":{"id":15,"text":"Index Page"},"url":"https://cfpub.epa.gov/si/si_public_record_Report.cfm?dirEntryId=341951&Lab=NRMRL"}],"country":"United States","state":"Ohio","city":"Cleveland","otherGeospatial":"Slavic Village","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.63976907730103,\n 41.45917929853694\n ],\n [\n -81.62968397140503,\n 41.45917929853694\n ],\n [\n -81.62968397140503,\n 41.46315921700656\n ],\n [\n -81.63976907730103,\n 41.46315921700656\n ],\n [\n -81.63976907730103,\n 41.45917929853694\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bf3d9f3e4b045bfcae0c9bb","contributors":{"authors":[{"text":"Shuster, William D.","contributorId":139413,"corporation":false,"usgs":false,"family":"Shuster","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":751450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Darner, Robert A. 0000-0003-1333-8265 radarner@usgs.gov","orcid":"https://orcid.org/0000-0003-1333-8265","contributorId":1972,"corporation":false,"usgs":true,"family":"Darner","given":"Robert","email":"radarner@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":751451,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198773,"text":"70198773 - 2018 - Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype","interactions":[],"lastModifiedDate":"2018-08-24T11:34:14","indexId":"70198773","displayToPublicDate":"2018-08-17T16:18:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype","title":"Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype","docAbstract":"Cold-water corals provide critical habitats for a multitude of marine species, but are understudied relative to tropical corals. Primnoa pacifica is a cold-water coral prevalent throughout Alaskan waters, while another species in the genus, Primnoa resedaeformis, is widely distributed in the Atlantic Ocean. This study examined the V4-V5 region of the 16S rRNA gene after amplifying and pyrosequencing bacterial DNA from samples of these species. Key differences between the two species’ microbiomes included a robust presence of bacteria belonging to the Chlamydiales order in most of the P. pacifica samples, whereas no more than 2% of any microbial community from P. resedaeformiscomprised these bacteria. Microbiomes of P. resedaeformis exhibited higher diversity than those of P. pacifica, and the two species largely clustered separately in a principal coordinate analysis. Comparison of P. resedaeformis microbiomes from samples collected in two submarine canyons revealed a significant difference between locations. This finding mirrored significant genetic differences among the P. resedaeformis from the two canyons based upon population genetic analysis of microsatellite loci. This study presents the first report of microbiomes associated with these two coral species.
","language":"English","publisher":"Springer","doi":"10.1038/s41598-018-30901-z","usgsCitation":"Goldsmith, D.B., Kellogg, C.A., Morrison, C.L., Gray, M.A., Stone, R.P., Waller, R.G., Brooke, S.D., and Ross, S., 2018, Comparison of microbiomes of cold-water corals Primnoa pacifica and Primnoa resedaeformis, with possible link between microbiome composition and host genotype: Scientific Reports, v. 8, 12383; 15 p., https://doi.org/10.1038/s41598-018-30901-z.","productDescription":"12383; 15 p.","ipdsId":"IP-091190","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-30901-z","text":"Publisher Index Page"},{"id":356632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-17","publicationStatus":"PW","scienceBaseUri":"5b98a283e4b0702d0e842f13","contributors":{"authors":[{"text":"Goldsmith, Dawn B. 0000-0003-0080-5346 dgoldsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-0080-5346","contributorId":191764,"corporation":false,"usgs":true,"family":"Goldsmith","given":"Dawn","email":"dgoldsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":742920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":742921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":146488,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":742927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gray, Michael A.","contributorId":200715,"corporation":false,"usgs":false,"family":"Gray","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":742922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stone, Robert P.","contributorId":190569,"corporation":false,"usgs":false,"family":"Stone","given":"Robert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":742923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waller, Rhian G.","contributorId":195852,"corporation":false,"usgs":false,"family":"Waller","given":"Rhian","email":"","middleInitial":"G.","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":742924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brooke, Sandra D.","contributorId":196940,"corporation":false,"usgs":false,"family":"Brooke","given":"Sandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":742925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":742926,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}