The relative importance of predation and food availability as contributors to larval cisco (Coregonus artedi) mortality in Lake Superior were investigated using a visual foraging model to evaluate potential predation pressure by rainbow smelt (Osmerus mordax) and a bioenergetic model to evaluate potential starvation risk. The models were informed by observations of rainbow smelt, larval cisco, and zooplankton abundance at three Lake Superior locations during the period of spring larval cisco emergence and surface-oriented foraging. Predation risk was highest at Black Bay, ON, where average rainbow smelt densities in the uppermost 10 m of the water column were >1000 ha−1. Turbid conditions at the Twin Ports, WI-MN, affected larval cisco predation risk because rainbow smelt remained suspended in the upper water column during daylight, placing them alongside larval cisco during both day and night hours. Predation risk was low at Cornucopia, WI, owing to low smelt densities (<400 ha−1) and deep light penetration, which kept rainbow smelt near the lakebed and far from larvae during daylight. In situ zooplankton density estimates were low compared to the values used to develop the larval coregonid bioenergetics model, leading to predictions of negative growth rates for 10 mm larvae at all three locations. The model predicted that 15 mm larvae were capable of attaining positive growth at Cornucopia and the Twin Ports where low water temperatures (2–6 °C) decreased their metabolic costs. Larval prey resources were highest at Black Bay but warmer water temperatures there offset the benefit of increased prey availability. A sensitivity analysis performed on the rainbow smelt visual foraging model showed that it was relatively insensitive, while the coregonid bioenergetics model showed that the absolute growth rate predictions were highly sensitive to input parameters (i.e., 20% parameter perturbation led to order of magnitude differences in model estimates). Our modelling indicated that rainbow smelt predation may limit larval cisco survival at Black Bay and to a lesser extent at Twin Ports, and that starvation may be a major source of mortality at all three locations. The framework we describe has the potential to further our understanding of the relative importance of starvation and predation on larval fish survivorship, provided information on prey resources available to larvae are measured at sufficiently fine spatial scales and the models provide a realistic depiction of the dynamic processes that the larvae experience.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.09.009","usgsCitation":"Myers, J.T., Yule, D., Jones, M., Quinlan, H.R., and Berglund, E.K., 2014, Foraging and predation risk for larval cisco (Coregonus artedi) in Lake Superior: A modelling synthesis of empirical survey data: Ecological Modelling, v. 294, p. 71-83, https://doi.org/10.1016/j.ecolmodel.2014.09.009.","productDescription":"13 p.","startPage":"71","endPage":"83","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054122","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":296791,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.13134765625,\n 46.51351558059737\n ],\n [\n -92.13134765625,\n 49.023461463214126\n ],\n [\n -84.375,\n 49.023461463214126\n ],\n [\n -84.375,\n 46.51351558059737\n ],\n [\n -92.13134765625,\n 46.51351558059737\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"294","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ba2e4b08de9379b3440","contributors":{"authors":[{"text":"Myers, Jared T. 0009-0004-9362-8792","orcid":"https://orcid.org/0009-0004-9362-8792","contributorId":119508,"corporation":false,"usgs":false,"family":"Myers","given":"Jared","email":"","middleInitial":"T.","affiliations":[{"id":6600,"text":"Qauntitative Fisheries Center, Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":519556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yule, Daniel L. dyule@usgs.gov","contributorId":2502,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","email":"dyule@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":519553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Michael L.","contributorId":119922,"corporation":false,"usgs":false,"family":"Jones","given":"Michael L.","affiliations":[{"id":6600,"text":"Qauntitative Fisheries Center, Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":519557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quinlan, Henry R.","contributorId":117465,"corporation":false,"usgs":false,"family":"Quinlan","given":"Henry","email":"","middleInitial":"R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":519555,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berglund, Eric K.","contributorId":115926,"corporation":false,"usgs":false,"family":"Berglund","given":"Eric","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":519554,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70098199,"text":"70098199 - 2014 - Geopressure gradient maps of Southern Louisiana, state, and vicinity","interactions":[],"lastModifiedDate":"2018-12-21T10:28:05","indexId":"70098199","displayToPublicDate":"2014-12-20T16:08:42","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Geopressure gradient maps of Southern Louisiana, state, and vicinity","docAbstract":"This series of five maps characterizes the subsurface pressure system of southern Louisiana, including the associated State and Federal waters. These maps were generated using the U.S. Geological Survey’s (USGS) comprehensive geopressure-gradient model (Burke et al., 2012b, 2013) that delineates the regional pressure system spanning the onshore and offshore Gulf of Mexico basin, USA. Previously, the model was used to generate ten regional-scale maps (Burke et al., 2012a): five contour maps characterized the depth to the surface defined by the first occurrence of regional isopressure gradients ranging from 0.60 psi/ft to 1.00 psi/ft, in 0.10-psi/ft increments; and five supporting maps displayed the spatial density of the data used to construct the regional contour maps. Explanation of generalized geopressure gradients and pressure-regime nomenclature is given here.\n\nThe five contour maps in this series characterize the depth to the surface defined by the first occurrence of isopressure gradients ranging from 0.60 psi/ft to 1.00 psi/ft, in 0.10-psi/ft increments. The geographical extent of this geopressure-gradient model is delineated on the maps, which encompass one of the most densely drilled regions of southern Louisiana and adjacent areas. The boundary of the model represents the area of greatest well density to maintain accurate contouring to the edge of the model. The pressure data were obtained from the IHS database (IHS Energy Group, 2011) and geologic folios (Dodge and Posey, 1981; Bebout and Gutiérrez, 1982; 1983; Eversull, 1984; Foote et al., 1990), which were compiled and digitally archived (Burke et al., 2011). Data quality analysis, linear-pressure interpolation calculations, and contouring algorithms defining the geopressure-gradient model are described by Burke et al. (2012b, 2013).\n\nThe isopressure-gradient trends depicted on these maps are not intended for detailed interpretation at specific locations.","language":"English","publisher":"American Association of Petroleum Geologists","usgsCitation":"Burke, L., Kinney, S.A., Dubiel, R.F., and Pitman, J.K., 2014, Geopressure gradient maps of Southern Louisiana, state, and vicinity, Zip File.","productDescription":"Zip File","ipdsId":"IP-046034","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":360664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284110,"type":{"id":15,"text":"Index Page"},"url":"https://datapages.com/gis-map-publishing-program/gis-open-files/geographic/geopressure-gradient-maps-of-southern-louisiana-state-and-vicinity"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.779296875,\n 29.065772888415406\n ],\n [\n -88.83544921874999,\n 29.065772888415406\n ],\n [\n -88.83544921874999,\n 30.968189296794247\n ],\n [\n -93.779296875,\n 30.968189296794247\n ],\n [\n -93.779296875,\n 29.065772888415406\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1e0a32e4b0708288cb0227","contributors":{"authors":[{"text":"Burke, Lauri 0000-0002-2035-8048","orcid":"https://orcid.org/0000-0002-2035-8048","contributorId":44891,"corporation":false,"usgs":true,"family":"Burke","given":"Lauri","affiliations":[],"preferred":false,"id":518610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinney, Scott A 0000-0001-5008-5813","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":118487,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":518612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dubiel, Russell F 0000-0002-1280-0350","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":119070,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":518613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":518611,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70134871,"text":"sir20145222 - 2014 - Simulated effects of increased groundwater withdrawals in the Cave Springs area, Hixson, Tennessee","interactions":[],"lastModifiedDate":"2014-12-19T14:47:17","indexId":"sir20145222","displayToPublicDate":"2014-12-19T14:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5222","title":"Simulated effects of increased groundwater withdrawals in the Cave Springs area, Hixson, Tennessee","docAbstract":"Concern for future water supplies in Tennessee has grown in recent years as a result of increased awareness of competing needs, the impact of droughts, and the need for more water to support growing populations. The U.S. Geological Survey conducts investigations to improve the knowledge about interactions of geology, climate, humans, and ecosystems with the water cycle, which is critical to understanding and optimizing water availability. The Hixson Utility District in Hamilton County, Tennessee, uses groundwater resources in the Cave Springs area as a water supply, withdrawing water from two well fields located at Cave Springs and Walkers Corner. Historically, Hixson Utility District has withdrawn about 5 million gallons per day (Mgal/d) at the Cave Springs well field and between 2 and 3 Mgal/d at the Walkers Corner well field. To assess the capacity of the groundwater resources in the Cave Springs area to meet future demands, four different scenarios of increased groundwater withdrawals were analyzed using computer model simulations.
\n\n
In the study area, groundwater is present in both regolith and bedrock. Groundwater flow in the regolith occurs as diffuse flow as recharge from precipitation moves through the regolith to discharge to streams and springs or to the underlying bedrock. Most of the bedrock in the study area has low primary porosity and permeability; however, fracturing and dissolution have produced substantial secondary porosity and permeability. Groundwater flow through the bedrock occurs as both diffuse and conduit flow. Recharge to the aquifer is from two distinct sources: direct infiltration of precipitation and losing streams. A major source of recharge to the aquifer that supplies Cave Springs is surface water that is lost from North Chickamauga Creek as it flows from the Cumberland Plateau onto the Newman Limestone. Average annual streamflow loss (groundwater recharge) from this reach of North Chickamauga Creek for the period November 2000 through June 2006 is about 18 cubic feet per second (ft3/s). Groundwater leaves the aquifer as either discharge to North Chickamauga Creek, Poe Branch, and Lick Branch; discharge to Chickamauga Lake; spring flow to Cave Springs or Rogers Spring; or withdrawals at the Cave Springs or Walkers Corner well fields.
\n\n
Using computer model simulations, four scenarios of increased groundwater withdrawals were analyzed. Each of these four scenarios are compared to a base-case simulation that uses groundwater withdrawal rates from 2012 of 5.1 Mgal/d from the Cave Springs well field and 2.7 Mgal/d from the Walkers Corner well field. Under scenarios A and B, pumpage is increased at Cave Springs by 2 Mgal/d and 5 Mgal/d, respectively, while pumpage at Walkers Corner remains unchanged. Under scenarios C and D, pumpage is increased at Walkers Corner by 2.6 Mgal/d and 4.5 Mgal/d, respectively, while pumpage at Cave Springs remains unchanged. The effects of the increased withdrawals were analyzed by comparing water budget changes of the groundwater discharges to Chickamauga Lake, North Chickamauga Creek, Cave Springs, Poe Branch, and Lick Branch/Rogers Spring for each of the scenarios and evaluating changes in groundwater levels at the well fields.
\n\n
Under scenarios A and B, the largest change in the water budget occurs for flow to Cave Springs with decreases of 1.9 and 4.7 ft3/s, respectively. Similarly, groundwater discharge to North Chickamauga Creek decreases by 1.0 ft3/s and 2.6 ft33/s, respectively. Under scenarios C and D, the largest change in the water budget occurs for flow to Chickamauga Lake with decreases of 1.3 ft3/s and 2.3 ft3/s, respectively. Similarly, groundwater discharge to North Chickamauga Creek decreases by 1.1 ft3/s and 2.1 ft3/s, respectively. Changes in groundwater levels at the well fields were also analyzed. At the Cave Springs well field, maximum declines in groundwater levels due to additional pumpage are less than 1 foot for all scenarios. Groundwater level changes at the Cave Springs well field are small due to the highly transmissive nature of the aquifer in this location. Maximum groundwater-level declines at Walkers Corner are less than 1 foot for scenarios A and B and about 52 feet and 82 feet for scenarios C and D, respectively. Under scenarios C and D, the regional potentiometric surface shows a large cone of depression centered on the Walkers Corner well field and elongated along geologic strike.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145222","collaboration":"Prepared in cooperation with the Hixson Utility District","usgsCitation":"Haugh, C.J., 2014, Simulated effects of increased groundwater withdrawals in the Cave Springs area, Hixson, Tennessee: U.S. Geological Survey Scientific Investigations Report 2014-5222, v, 28 p., https://doi.org/10.3133/sir20145222.","productDescription":"v, 28 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055468","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":296826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145222.jpg"},{"id":296825,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5222/pdf/sir2014-5222.pdf","size":"4.52 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296824,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5222/"}],"scale":"100000","country":"United States","state":"Tennessee","city":"Chattanooga","otherGeospatial":"Cave Springs, Hixson","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.37063598632812,\n 35.206355445199605\n ],\n [\n -85.37063598632812,\n 35.570214567965984\n ],\n [\n -84.90234375,\n 35.570214567965984\n ],\n [\n -84.90234375,\n 35.206355445199605\n ],\n [\n -85.37063598632812,\n 35.206355445199605\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2ab3e4b08de9379b318e","contributors":{"authors":[{"text":"Haugh, Connor J. 0000-0002-5204-8271 cjhaugh@usgs.gov","orcid":"https://orcid.org/0000-0002-5204-8271","contributorId":3932,"corporation":false,"usgs":true,"family":"Haugh","given":"Connor","email":"cjhaugh@usgs.gov","middleInitial":"J.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537031,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70134240,"text":"sir20145214 - 2014 - Analysis of floods, including the tropical storm Irene inundation, of the Ottauquechee River in Woodstock, Bridgewater, and Killington and of Reservoir Brook in Bridgewater and Plymouth, Vermont","interactions":[],"lastModifiedDate":"2014-12-18T15:26:24","indexId":"sir20145214","displayToPublicDate":"2014-12-18T16:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5214","title":"Analysis of floods, including the tropical storm Irene inundation, of the Ottauquechee River in Woodstock, Bridgewater, and Killington and of Reservoir Brook in Bridgewater and Plymouth, Vermont","docAbstract":"Digital flood-inundation maps were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, New York District for a 25-mile reach of the Ottauquechee River and a 2-mile reach of Reservoir Brook in Vermont. The reach of the Ottauquechee River that was studied extends from River Road Bridge in Killington, Vt., to the Taftsville Dam in the village of Taftsville, in the town of Woodstock, Vt., and the reach of Reservoir Brook extends from a location downstream from the Woodward Reservoir in Plymouth, Vt., to its confluence with the Ottauquechee River in Bridgewater, Vt. The inundation maps depict estimates of the areal extent of flooding corresponding to the 1-percent annual exceedance probability (AEP) flood (also referred to as the 100-year flood) and the peak of the tropical storm Irene flood of August 28, 2011, which was greater than the 0.2-percent AEP flood (also referred to as the 500-year flood), as referenced to the USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900).
\n\n
In addition to the two digital flood inundation maps, flood profiles were created that depict the study reach flood elevation of tropical storm Irene of August 2011 and the 10-, 2-, 1-, and 0.2-percent AEP floods, also known as the 10-, 50-, 100-, and 500-year floods, respectively. The 10-, 2-, 1-, and 0.2-percent AEP flood discharges were determined using annual peak flow data from the USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). Flood profiles were computed for the Ottauquechee River and Reservoir Brook by means of a one-dimensional step-backwater model. The model was calibrated using documented high-water marks of the peak of the tropical storm Irene flood of August 2011 as well as stage discharge data as determined for USGS Ottauquechee River near West Bridgewater, Vt. streamgage (station 01150900). The simulated water-surface profiles were combined with a digital elevation model within a geographic information system to delineate the areas flooded during tropical storm Irene and for the 1-percent AEP water-surface profile. The digital elevation model data were derived from light detection and ranging (lidar) data obtained for a 3,281-foot (1,000-meter) corridor along the Ottauquechee River study reach and were augmented with 33-foot (10- meter) contour interval data in the modeled flood-inundation areas outside the lidar corridor. The 33-foot (10-meter) contour interval USGS 15-minute quadrangle topographic digital raster graphics map used to augment lidar data was produced at a scale of 1:24,000. The digital flood inundation maps and flood profiles along with information regarding current stage from USGS streamgages on the Internet provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145214","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Flynn, R.H., 2014, Analysis of floods, including the tropical storm Irene inundation, of the Ottauquechee River in Woodstock, Bridgewater, and Killington and of Reservoir Brook in Bridgewater and Plymouth, Vermont: U.S. Geological Survey Scientific Investigations Report 2014-5214, Report: vii, 11 p.; Readme; 5 Appendixes, https://doi.org/10.3133/sir20145214.","productDescription":"Report: vii, 11 p.; Readme; 5 Appendixes","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055865","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":296815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145214.jpg"},{"id":296807,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5214/"},{"id":296808,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5214/pdf/sir2014-5214.pdf","size":"2.25 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296809,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_app-readme.txt","text":"Appendix 1-5 Readme","size":"14 kB"},{"id":296810,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend01.pdf","text":"Appendix 1","size":"7.71 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296811,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend02.pdf","text":"Appendix 2","size":"172 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296812,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend03.pdf","text":"Appendix 3","size":"140 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":296813,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend04.pdf","text":"Appendix 4","size":"59 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":296814,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5214/appendix/sir2014-5214_apend05.pdf","text":"Appendix 5","size":"55.3 kB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Vermont","otherGeospatial":"Ottauquechee River, Reservoir Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.74871826171875,\n 43.511708955963776\n ],\n [\n -72.74871826171875,\n 43.7572088788494\n ],\n [\n -72.23236083984375,\n 43.7572088788494\n ],\n [\n -72.23236083984375,\n 43.511708955963776\n ],\n [\n -72.74871826171875,\n 43.511708955963776\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2a54e4b08de9379b2fe6","contributors":{"authors":[{"text":"Flynn, Robert H. rflynn@usgs.gov","contributorId":2137,"corporation":false,"usgs":true,"family":"Flynn","given":"Robert","email":"rflynn@usgs.gov","middleInitial":"H.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":525746,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70134861,"text":"fs20143121 - 2014 - The Caloosahatchee River Estuary: a monitoring partnership between Federal, State, and local governments, 2007-13","interactions":[],"lastModifiedDate":"2014-12-18T14:55:44","indexId":"fs20143121","displayToPublicDate":"2014-12-18T15:45:00","publicationYear":"2014","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":"2014-3121","title":"The Caloosahatchee River Estuary: a monitoring partnership between Federal, State, and local governments, 2007-13","docAbstract":"The tidal Caloosahatchee River and downstream estuaries have substantial environmental, recreational, and economic value for southwest Florida residents and visitors. Modifications to the Caloosahatchee River watershed have altered the predevelopment hydrology, thereby threatening the environmental health of estuaries in the area. Hydrologic monitoring of the freshwater contributions from tributaries to the tidal Caloosahatchee River and its estuaries is necessary to adequately describe the total freshwater inflow and constituent loads to the delicate estuarine system.
\n\n
From 2007 to 2013, the U.S. Geological Survey (USGS), in cooperation with the Florida Department of Environmental Protection (FDEP) and the South Florida Water Management District (SFWMD), operated a flow and salinity monitoring network at tributaries flowing into and at key locations within the tidal Caloosahatchee River. This network was designed to supplement existing long-term monitoring stations, such as W.P. Franklin Lock, also known as S–79, which are operated by the USGS in cooperation with the U.S. Army Corps of Engineers, Lee County, and the City of Cape Coral. Additionally, a monitoring station was operated on Sanibel Island from 2010 to 2013 as part of the USGS Greater Everglades Priority Ecosystem Science initiative and in partnership with U.S. Fish and Wildlife Service (J.N. Ding Darling National Wildlife Refuge). Moving boat water-quality surveys throughout the tidal Caloosahatchee River and downstream estuaries began in 2011 and are ongoing. Information generated by these monitoring networks has proved valuable to the FDEP for developing total maximum daily load criteria, and to the SFWMD for calibrating and verifying a hydrodynamic model. The information also supports the Caloosahatchee River Watershed Protection Plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143121","collaboration":"Prepared in cooperation with the Florida Department of Environmental Protection and the South Florida Water Management District","usgsCitation":"Patino, E., 2014, The Caloosahatchee River Estuary: a monitoring partnership between Federal, State, and local governments, 2007-13: U.S. Geological Survey Fact Sheet 2014-3121, 4 p., https://doi.org/10.3133/fs20143121.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2007-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-056907","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":296806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143121.jpg"},{"id":296803,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3121/"},{"id":296804,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3121/pdf/fs2014-3121.pdf","size":"760 kB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River Estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.15713500976562,\n 26.394329964650204\n ],\n [\n -82.15713500976562,\n 26.713720362159552\n ],\n [\n -81.66000366210938,\n 26.713720362159552\n ],\n [\n -81.66000366210938,\n 26.394329964650204\n ],\n [\n -82.15713500976562,\n 26.394329964650204\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2abee4b08de9379b31c4","contributors":{"authors":[{"text":"Patino, Eduardo 0000-0003-1016-3658 epatino@usgs.gov","orcid":"https://orcid.org/0000-0003-1016-3658","contributorId":1743,"corporation":false,"usgs":true,"family":"Patino","given":"Eduardo","email":"epatino@usgs.gov","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"preferred":true,"id":526631,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70135050,"text":"70135050 - 2014 - Understanding the magnitude dependence of PGA and PGV in NGA-West 2 data","interactions":[],"lastModifiedDate":"2017-05-16T10:54:45","indexId":"70135050","displayToPublicDate":"2014-12-18T11:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the magnitude dependence of PGA and PGV in NGA-West 2 data","docAbstract":"The Next Generation Attenuation‐West 2 (NGA‐West 2) 2014 ground‐motion prediction equations (GMPEs) model ground motions as a function of magnitude and distance, using empirically derived coefficients (e.g., Bozorgniaet al., 2014); as such, these GMPEs do not clearly employ earthquake source parameters beyond moment magnitude (M) and focal mechanism. To better understand the magnitude‐dependent trends in the GMPEs, we build a comprehensive earthquake source‐based model to explain the magnitude dependence of peak ground acceleration and peak ground velocity in the NGA‐West 2 ground‐motion databases and GMPEs. Our model employs existing models (Hanks and McGuire, 1981; Boore, 1983, 1986; Anderson and Hough, 1984) that incorporate a point‐source Brune model, including a constant stress drop and the high‐frequency attenuation parameter κ0, random vibration theory, and a finite‐fault assumption at the large magnitudes to describe the data from magnitudes 3 to 8. We partition this range into four different magnitude regions, each of which has different functional dependences on M. Use of the four magnitude partitions separately allows greater understanding of what happens in any one subrange, as well as the limiting conditions between the subranges. This model provides a remarkably good fit to the NGA data for magnitudes from 3<M<8 at close rupture distances (Rrup≤20 km). We explore the trade‐offs between Δσ and κ0 in ground‐motion models and data, which play an important role in understanding small‐magnitude data, for which the corner frequency is masked by the attenuation of high frequencies. That this simple, source‐based model matches the NGA‐West 2 GMPEs and data so well suggests that considerable simplicity underlies the parametrically complex NGA GMPEs.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130283","usgsCitation":"Baltay Sundstrom, A.S., and Hanks, T.C., 2014, Understanding the magnitude dependence of PGA and PGV in NGA-West 2 data: Bulletin of the Seismological Society of America, v. 104, no. 6, p. 2851-2865, https://doi.org/10.1785/0120130283.","productDescription":"15 p.","startPage":"2851","endPage":"2865","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052324","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":296788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-10-21","publicationStatus":"PW","scienceBaseUri":"54dd2ac6e4b08de9379b31fb","contributors":{"authors":[{"text":"Baltay Sundstrom, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":526749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Thomas C. 0000-0003-0928-0056 thanks@usgs.gov","orcid":"https://orcid.org/0000-0003-0928-0056","contributorId":3065,"corporation":false,"usgs":true,"family":"Hanks","given":"Thomas","email":"thanks@usgs.gov","middleInitial":"C.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":526750,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70111439,"text":"sir20145089 - 2014 - Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota","interactions":[],"lastModifiedDate":"2017-10-12T20:06:13","indexId":"sir20145089","displayToPublicDate":"2014-12-18T06:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5089","title":"Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota","docAbstract":"Two karst aquifers, the Edwards aquifer in the Balcones Escarpment region of south-central Texas and the Madison aquifer in the Black Hills of western South Dakota, were evaluated for hydrologic response to projected climate change through 2050. Edwards aquifer sites include Barton Springs, the Bexar County Index Well, and Comal Springs. Madison aquifer sites include Spearfish Creek and Rhoads Fork Spring. Climate projections at sites were based on output from the Community Climate System Model of global climate, linked to the Weather Research and Forecasting (WRF) model of regional climate. The WRF model output was bias adjusted to match means for 1981–2010 from records at weather stations near Madison and Edwards aquifer sites, including Boerne, Texas, and Custer and Lead, South Dakota. Hydrologic response at spring and well sites was based on the Rainfall-Response Aquifer and Watershed Flow (RRAWFLOW) model. The WRF model climate projections for 2011–50 indicate a significant upward trend in annual air temperature for all three weather stations and a significant downward trend in annual precipitation for the Boerne weather station. Annual springflow simulated by the RRAWFLOW model had a significant downward trend for Edwards aquifer sites and no trend for Madison aquifer sites.
\nFlora and fauna that rely on springflow from Edwards and Madison aquifer sites were assessed for vulnerability to projected climate change on the basis of the Climate Change Vulnerability Index (CCVI). The CCVI is determined by the exposure of a species to climate, the sensitivity of the species, and the ability of the species to cope with climate change. Sixteen species associated with springs and groundwater were assessed in the Balcones Escarpment region. The Barton Springs salamander (Eurycea sosorum) was scored as highly vulnerable with moderate confidence. Nine species—three salamanders, a fountain darter (Etheostoma fonticola), three insects, and two amphipods—were scored as moderately vulnerable. The remaining six species—four vascular plants, the Barton cavesnail (Stygopyrgus bartonensis), and a cave shrimp—were scored as not vulnerable/presumed stable (not vulnerable and evidence does not support change in abundance or range of the species). Vulnerability of eight species associated with streams that receive springflow from the Madison aquifer in the Black Hills was assessed. Of these, the American dipper (Cinclus mexicanus) and the lesser yellow lady’s slipper (Cypripedium parviflorum) were scored as moderately vulernable with high confidence. The dwarf scouringrush (Equisetum scirpoides) and autumn willow (Salix serissima) were also scored as moderately vulnerable with moderate to low confidence, respectively. Other species were assessed as not vulnerable/presumed stable or not vulnerable/increase likely (not vulnerable and evidence supporting an increase in abundance or range of the species). Lower vulnerability scores for the Black Hills species in comparison to the Balcones Escarpment species reflect lower endemicity, higher projected springflow than in the historical period, and high thermal tolerance of many of the species for the Black Hills. Importantly, climate change vulnerability scores differed substantially for Edwards aquifer species when RRAWFLOW model projections were included, resulting in increased vulnerability scores for 12 of the 16 species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145089","collaboration":"Prepared in cooperation with the Department of Interior South-Central Climate Science Center","usgsCitation":"Stamm, J.F., Poteet, M.F., Symstad, A.J., Musgrove, MaryLynn, Long, A.J., Mahler, B.J., and Norton, P.A., 2015, Historical and projected climate (1901–2050) and hydrologic response of karst aquifers, and species vulnerability in south-central Texas and western South Dakota: U.S. Geological Survey Scientific Investigations Report 2014–5089, 59 p., plus supplements, https://dx.doi.org/10.3133/sir20145089.","productDescription":"Report: viii, 61 p.; 3 Supplements","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046230","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":312182,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sir/2014/5089/downloads/","text":"Supplement 1-3","linkFileType":{"id":5,"text":"html"},"description":"Supplement 1-3"},{"id":312140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2014/5089/coverthb.jpg"},{"id":312141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5089/sir20145089.pdf","text":"Report","size":"4.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2014-5089"}],"country":"United States","state":"South Dakota, Texas","otherGeospatial":"Barton Springs, Bexar County Index Well, Comal Springs, Rhoads Fork Spring, Spearfish Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.5,\n 43\n ],\n [\n -104.5,\n 44.5\n ],\n [\n -103,\n 44.5\n ],\n [\n -103,\n 43\n ],\n [\n -104.5,\n 43\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100,\n 29\n ],\n [\n -100,\n 31.5\n ],\n [\n -97,\n 31.5\n ],\n [\n -97,\n 29\n ],\n [\n -100,\n 29\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
1608 Mountain View Road
Rapid City, SD 57702
http://sd.water.usgs.gov/
In July 2011, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed a geophysical survey using electrical resistivity along an approximately 6-mile reach of the lower American River in Sacramento, California, to map near-surface lithological variations. This survey is a part of a manifold and comprehensive study of river-flow dynamics and geologic boundary-property knowledge necessary to estimate scour potential and levee erosion risk. Data were acquired on the left (south or west) bank between river mile 5 and 10.7 as well as a short section on the right bank from river mile 5.4 to 6. Thirteen direct-current resistivity profiles and approximately 8.3 miles of capacitively coupled resisistivity data were acquired along accessible areas of the floodplain between the levee and river bank. Capacitively coupled resistivity was used as a reconnaissance tool, because it allowed for greater spatial coverage of data but with lower resolution and depth of investigation than the DC resistivity method. The study area contains Pleistocene-age alluvial deposits, dominated by gravels, sands, silts, and clays, that vary in both lateral extent and depth. Several generations of lithologic logs were used to help interpret resistivity variations observed in the resistivity models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141242","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Burton, B.L., Powers, M.H., and Ball, L.B., 2014, Characterization of subsurface stratigraphy along the lower American River floodplain using electrical resistivity, Sacramento, California, 2011: U.S. Geological Survey Open-File Report 2014-1242, Report: iv, 62 p.; Direct-current resistivity data; Capacitively coupled resistivity data, https://doi.org/10.3133/ofr20141242.","productDescription":"Report: iv, 62 p.; Direct-current resistivity data; Capacitively coupled resistivity data","numberOfPages":"66","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-055799","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":296766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141242.jpg"},{"id":296763,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1242/pdf/ofr2014-1242.pdf","text":"Report","size":"19.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":296764,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1242/App3/AmRiv_DCres_stg.zip","text":"Direct-current resistivity data","size":"592 kB","description":"Digital Data"},{"id":296762,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1242/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":296765,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1242/App3/AmRiv_CCres_BIN.zip","text":"Capacitively coupled resistivity data","size":"284 kB","description":"Digital Data"}],"projection":"California State Plane projection, zone 2","datum":"North American Datum of 1983","country":"United States","state":"California","city":"Sacramento","otherGeospatial":"American River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a92ee4b00eda8915acf3","contributors":{"authors":[{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":138925,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany","email":"blburton@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":758621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":536902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":536903,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134071,"text":"ofr20141119A - 2014 - Geologic map of metallic and nonmetallic mineral deposits, Badakhshan Province, Afghanistan, modified from the 1967 original map compilation of G.G. Semenov and others","interactions":[],"lastModifiedDate":"2014-12-18T09:01:27","indexId":"ofr20141119A","displayToPublicDate":"2014-12-17T11:00:00","publicationYear":"2014","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":"2014-1119","chapter":"A","title":"Geologic map of metallic and nonmetallic mineral deposits, Badakhshan Province, Afghanistan, modified from the 1967 original map compilation of G.G. Semenov and others","docAbstract":"This geologic map of central Badakhshan Province, Afghanistan, is a combined, redrafted, and modified version of the Geological map of central Badakhshan, scale 1:200,000 (sheet 217), and Map of minerals of central Badakhshan, scale 1:200,000 (also sheet 217) from Semenov and others (1967) (Soviet report no. R0815). That unpublished Soviet report contains the original maps and cross sections, which were prepared in cooperation with the Ministry of Mines and Industries of the Republic of Afghanistan in 1967 under contract no. 1378 (Technoexport, USSR). This USGS publication also includes the gold metallogeny summarized in Abdullah and others (1977) and Peters and others (2007, 2011), and additional compilations from Guguev and others (1967).
\n\n
Badakhshan Province consists of volcanic, sedimentary, and metamorphic rocks of various ages from late Proterozoic to Cenozoic. The rocks are intensively dislocated and cut by intrusions of magmatic rocks. Primary gold occurrences are distinguished in shear zones with hydrothermal alterations or in contact-metasomatic rocks near magmatic intrusions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141119A","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense","usgsCitation":"Peters, S., Stettner, W.R., Mathieux, D.P., Masonic, L., and Moran, T.W., 2014, Geologic map of metallic and nonmetallic mineral deposits, Badakhshan Province, Afghanistan, modified from the 1967 original map compilation of G.G. Semenov and others: U.S. Geological Survey Open-File Report 2014-1119, Report: 39.50 x 55.00 inches, https://doi.org/10.3133/ofr20141119A.","productDescription":"Report: 39.50 x 55.00 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-034815","costCenters":[],"links":[{"id":296747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141119A.jpg"},{"id":296746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1119/A/pdf/ofr2014-1119a.pdf","size":"96.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296745,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1119/A/"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"World Geodetic System 1984 Datum","country":"Afghanistan","state":"Badakhshan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 69.2578125,\n 36.474306755095206\n ],\n [\n 69.2578125,\n 37.96152331396616\n ],\n [\n 71.2353515625,\n 37.96152331396616\n ],\n [\n 71.2353515625,\n 36.474306755095206\n ],\n [\n 69.2578125,\n 36.474306755095206\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a933e4b00eda8915acfb","contributors":{"authors":[{"text":"Peters, Stephen G. speters@usgs.gov","contributorId":2793,"corporation":false,"usgs":true,"family":"Peters","given":"Stephen G.","email":"speters@usgs.gov","affiliations":[{"id":596,"text":"U.S. Geological Survey National Center","active":false,"usgs":true}],"preferred":false,"id":525671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stettner, Will R. wstettne@usgs.gov","contributorId":4021,"corporation":false,"usgs":true,"family":"Stettner","given":"Will","email":"wstettne@usgs.gov","middleInitial":"R.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":525672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mathieux, Donald P. dmathieu@usgs.gov","contributorId":3295,"corporation":false,"usgs":true,"family":"Mathieux","given":"Donald","email":"dmathieu@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":525670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masonic, Linda M. lmasonic@usgs.gov","contributorId":1418,"corporation":false,"usgs":true,"family":"Masonic","given":"Linda M.","email":"lmasonic@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"preferred":false,"id":536931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Thomas W.","contributorId":127557,"corporation":false,"usgs":false,"family":"Moran","given":"Thomas","email":"","middleInitial":"W.","affiliations":[{"id":7050,"text":"Contractor, ETI","active":true,"usgs":false}],"preferred":false,"id":525673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70134072,"text":"ofr20141119B - 2014 - Geologic map of the Weka Dur gold deposit, Badakhshan Province, Afghanistan, modified from the 1967 original map compilation of M.P. Guguev and others","interactions":[],"lastModifiedDate":"2014-12-18T08:58:16","indexId":"ofr20141119B","displayToPublicDate":"2014-12-17T11:00:00","publicationYear":"2014","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":"2014-1119","chapter":"B","title":"Geologic map of the Weka Dur gold deposit, Badakhshan Province, Afghanistan, modified from the 1967 original map compilation of M.P. Guguev and others","docAbstract":"This geologic map of the Weka Dur gold deposit located in Badakhshan Province, Afghanistan, is a redrafted and modified version of the Geological map of the Weka Dur area, scale 1:10,000 and Geological map of the Weka Dur deposit, scale 1:2,000 from Guguev and others (1967) (Soviet report no. R1584). That unpublished Soviet report contains the original maps and cross sections, which were prepared in cooperation with the Ministry of Mines and Industries of the Republic of Afghanistan in 1967 under contract no. 1378 (Technoexport, USSR). This USGS publication not only reproduces the geology of the original Soviet maps and cross sections, but also illustrates a mapped adit with reported gold concentrations from sampling within the adit, and shows the location of Soviet trenches along the Weka Dur gold deposit.
\n\n
The Weka Dur gold deposit lies in a cluster of other gold deposits in Badakhshan Province (Ragh district), such as the Kadar, Nesheb Dur, and Rishaw gold occurrences. These gold occurrences lie within a zone of late Hercynian folding and are most likely related to fluids that originated from orogenic processes. The Weka Dur deposit is the largest recorded gold occurrence in Afghanistan and is hosted in Proterozoic mica schist and amphibolite that is intruded by diabase dikes and other intrusive rocks. The tabular orebody is 350 meters (m) long and 2 m wide and can be traced downdip for 110 m. Mineralization consists of ochreous, brecciated schists containing high gold concentrations along gently and steeply dipping fissures. The brecciated rocks grade to 46.7 grams per ton (g/t) silver and contain arsenopyrite, galena, chalcopyrite, and scheelite. Trenches and adits were constructed, mapped, and sampled during the 1960s. Calculated resources are 958.3 kilograms of gold, averaging 4.1 g/t gold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141119B","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense","usgsCitation":"Peters, S., Stettner, W.R., and Masonic, L., 2014, Geologic map of the Weka Dur gold deposit, Badakhshan Province, Afghanistan, modified from the 1967 original map compilation of M.P. Guguev and others: U.S. Geological Survey Open-File Report 2014-1119, Map: 48 inches x 39 inches, https://doi.org/10.3133/ofr20141119B.","productDescription":"Map: 48 inches x 39 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-042822","costCenters":[],"links":[{"id":296751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141119b.jpg"},{"id":296749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1119/B/pdf/ofr2014-1119b.pdf","text":"Report","size":"85.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296750,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1119/A/","text":"OFR 2014-1119-A"},{"id":296748,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1119/B/"}],"country":"Afghanistan","otherGeospatial":"Badakhshan Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 69.9609375,\n 38.41055825094609\n ],\n [\n 75.146484375,\n 38.20365531807149\n ],\n [\n 74.35546875,\n 35.60371874069731\n ],\n [\n 69.697265625,\n 35.817813158696616\n ],\n [\n 69.9609375,\n 38.41055825094609\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a933e4b00eda8915acf9","contributors":{"authors":[{"text":"Peters, Stephen G. speters@usgs.gov","contributorId":2793,"corporation":false,"usgs":true,"family":"Peters","given":"Stephen G.","email":"speters@usgs.gov","affiliations":[{"id":596,"text":"U.S. Geological Survey National Center","active":false,"usgs":true}],"preferred":false,"id":525675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stettner, Will R. wstettne@usgs.gov","contributorId":4021,"corporation":false,"usgs":true,"family":"Stettner","given":"Will","email":"wstettne@usgs.gov","middleInitial":"R.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":525676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masonic, Linda M. lmasonic@usgs.gov","contributorId":1418,"corporation":false,"usgs":true,"family":"Masonic","given":"Linda M.","email":"lmasonic@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"preferred":false,"id":525674,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70135665,"text":"70135665 - 2014 - Waterfowl populations of conservation concern: learning from diverse challenges, models, and conservation strategies","interactions":[],"lastModifiedDate":"2014-12-17T09:36:24","indexId":"70135665","displayToPublicDate":"2014-12-17T10:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3764,"text":"Wildfowl","onlineIssn":"2052-6458","printIssn":"0954-6324","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl populations of conservation concern: learning from diverse challenges, models, and conservation strategies","docAbstract":"There are 30 threatened or endangered species of waterfowl worldwide, and several sub-populations are also threatened. Some of these species occur in North America, and others there are also of conservation concern due to declining population trends and their importance to hunters. Here we review conservation initiatives being undertaken for several of these latter species, along with conservation measures in place in Europe, to seek common themes and approaches that could be useful in developing broad conservation guidelines. While focal species may vary in their life histories, population threats and geopolitical context, most conservation efforts have used a systematic approach to understand factors limiting populations and o identify possible management or policy actions. This approach generally includes a priori identification of plausible hypotheses about population declines or status, incorporation of hypotheses into conceptual or quantitative planning models, and the use of some form of structured decision making and adaptive management to develop and implement conservation actions in the face of many uncertainties. A climate of collaboration among jurisdictions sharing these birds is important to the success of a conservation or management programme. The structured conservation approach exemplified herein provides an opportunity to involve stakeholders at all planning stages, allows for all views to be examined and incorporated into model structures, and yields a format for improved communication, cooperation and learning, which may ultimately be one of the greatest benefits of this strategy.
","language":"English","publisher":"Wildfowl & Wetlands Trust","usgsCitation":"Austin, J.E., Slattery, S., and Clark, R.G., 2014, Waterfowl populations of conservation concern: learning from diverse challenges, models, and conservation strategies: Wildfowl, v. 2014, no. Special Issue 4, p. 470-497.","productDescription":"28 p.","startPage":"470","endPage":"497","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053628","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":296742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296688,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2617"}],"volume":"2014","issue":"Special Issue 4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a937e4b00eda8915ad01","contributors":{"authors":[{"text":"Austin, Jane E. jaustin@usgs.gov","contributorId":2839,"corporation":false,"usgs":true,"family":"Austin","given":"Jane","email":"jaustin@usgs.gov","middleInitial":"E.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":536714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slattery, Stuart","contributorId":130965,"corporation":false,"usgs":false,"family":"Slattery","given":"Stuart","affiliations":[{"id":7182,"text":"Ducks Unlimited Canada","active":true,"usgs":false}],"preferred":false,"id":536715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Robert G.","contributorId":33781,"corporation":false,"usgs":false,"family":"Clark","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":536716,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134073,"text":"ofr20141199 - 2014 - Geologic map of the Ahankashan-Rakhna basin, Badghis, Ghor, and Herat Provinces, Afghanistan, modified from the 1974 original map compilation of Y.I. Shcherbina and others","interactions":[],"lastModifiedDate":"2014-12-17T09:41:37","indexId":"ofr20141199","displayToPublicDate":"2014-12-17T10:30:00","publicationYear":"2014","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":"2014-1199","title":"Geologic map of the Ahankashan-Rakhna basin, Badghis, Ghor, and Herat Provinces, Afghanistan, modified from the 1974 original map compilation of Y.I. Shcherbina and others","docAbstract":"This geologic map of the Ahankashan-Rakhna basin, Afghanistan, is a redrafted and modified version of the Geological map of the area of Ahankashan-Rakhna basin, scale 1:50,000 and Geological map of the Ahankashan area with data on mineral resources, scale 1:12,000 from Shcherbina and others (1974) (Soviet report no. 0822). That unpublished Soviet report contains the original maps and cross sections, which were prepared in cooperation with the Ministry of Mines and Industries of the Republic of Afghanistan in Kabul during 1974 under contract no. 50728 (Technoexport, USSR). The redrafted maps and cross sections in this USGS publication illustrate the geology of the Ahankashan and Rakhna basins, located within Badghis, Ghor, and Herat Provinces.
\n\n
The Ahankashan and Rakhna prospect area is one of several gold and copper deposits within west-central Afghanistan. Here, various felsic to intermediate igneous porphyries intrude Lower Triassic to lower Paleogene sedimentary rocks, producing mineral and ore-bearing zones related to hydrothermal alteration, skarns, silicification, and crushing (brecciation). Mineralized skarns contain assemblages such as magnetite, magnetite-hematite, epidote-hematite, and epidote-garnet, as well as disseminations of chalcopyrite, covellite, chalcocite, cuprite, malachite, and azurite. Gold mineralization is mainly associated with zones of crushing along faults, and with small silicified igneous veins within granite and quartz porphyry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141199","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense","usgsCitation":"Tucker, R.D., Stettner, W.R., Masonic, L., and Bogdanow, A.K., 2014, Geologic map of the Ahankashan-Rakhna basin, Badghis, Ghor, and Herat Provinces, Afghanistan, modified from the 1974 original map compilation of Y.I. Shcherbina and others: U.S. Geological Survey Open-File Report 2014-1199, Report: 51.00 x 41.00 inches, https://doi.org/10.3133/ofr20141199.","productDescription":"Report: 51.00 x 41.00 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056911","costCenters":[{"id":497,"text":"Office of International Programs","active":false,"usgs":true}],"links":[{"id":296743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141199.jpg"},{"id":296739,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1199/"},{"id":296740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1199/pdf/ofr2014-1199.pdf","size":"76.5 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"500000","projection":"Universal Transverse Mercator projection","datum":"World Geodetic System 1984 Datum","country":"Afghanistan","state":"Badghis, Ghor, Herat","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 63.369140625,\n 33.797408767572485\n ],\n [\n 63.369140625,\n 35.371135022800985\n ],\n [\n 65.58837890625,\n 35.371135022800985\n ],\n [\n 65.58837890625,\n 33.797408767572485\n ],\n [\n 63.369140625,\n 33.797408767572485\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a936e4b00eda8915acfd","contributors":{"authors":[{"text":"Tucker, Robert D. 0000-0001-8463-4358 rtucker@usgs.gov","orcid":"https://orcid.org/0000-0001-8463-4358","contributorId":2007,"corporation":false,"usgs":true,"family":"Tucker","given":"Robert","email":"rtucker@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":525677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stettner, Will R. wstettne@usgs.gov","contributorId":4021,"corporation":false,"usgs":true,"family":"Stettner","given":"Will","email":"wstettne@usgs.gov","middleInitial":"R.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":525678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masonic, Linda M. lmasonic@usgs.gov","contributorId":1418,"corporation":false,"usgs":true,"family":"Masonic","given":"Linda M.","email":"lmasonic@usgs.gov","affiliations":[{"id":5072,"text":"Office of Communication and Publishing","active":true,"usgs":true}],"preferred":false,"id":525679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bogdanow, Anya K. abogdanow@usgs.gov","contributorId":5406,"corporation":false,"usgs":true,"family":"Bogdanow","given":"Anya","email":"abogdanow@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":525680,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70135738,"text":"70135738 - 2014 - Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population","interactions":[],"lastModifiedDate":"2018-08-19T21:52:56","indexId":"70135738","displayToPublicDate":"2014-12-17T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population","docAbstract":"Context: The potential for research methods to affect wildlife is an increasing concern among both scientists and the public. This topic has a particular urgency for polar bears because additional research is needed to monitor and understand population responses to rapid loss of sea ice habitat.
Aims: This study used data collected from polar bears sampled in the Alaska portion of the southern Beaufort Sea to investigate the potential for capture to adversely affect behaviour and vital rates. We evaluated the extent to which capture, collaring and handling may influence activity and movement days to weeks post-capture, and body mass, body condition, reproduction and survival over 6 months or more.
Methods: We compared post-capture activity and movement rates, and relationships between prior capture history and body mass, body condition and reproductive success. We also summarised data on capture-related mortality.
Key results: Individual-based estimates of activity and movement rates reached near-normal levels within 2–3 days and fully normal levels within 5 days post-capture. Models of activity and movement rates among all bears had poor fit, but suggested potential for prolonged, lower-level rate reductions. Repeated captures was not related to negative effects on body condition, reproduction or cub growth or survival. Capture-related mortality was substantially reduced after 1986, when immobilisation drugs were changed, with only 3 mortalities in 2517 captures from 1987–2013.
Conclusions: Polar bears in the southern Beaufort Sea exhibited the greatest reductions in activity and movement rates 3.5 days post-capture. These shorter-term, post-capture effects do not appear to have translated into any long-term effects on body condition, reproduction, or cub survival. Additionally, collaring had no effect on polar bear recovery rates, body condition, reproduction or cub survival.
Implications: This study provides empirical evidence that current capture-based research methods do not have long-term implications, and are not contributing to observed changes in body condition, reproduction or survival in the southern Beaufort Sea. Continued refinement of capture protocols, such as the use of low-impact dart rifles and reversible drug combinations, might improve polar bear response to capture and abate short-term reductions in activity and movement post-capture.
","language":"English","publisher":"Csiro Publishing","doi":"10.1071/WR13225","usgsCitation":"Rode, K.D., Pagano, A.M., Bromaghin, J.F., Atwood, T.C., Durner, G.M., Simac, K.S., and Amstrup, S.C., 2014, Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population: Wildlife Research, v. 41, no. 4, p. 311-322, https://doi.org/10.1071/WR13225.","productDescription":"12 p.","startPage":"311","endPage":"322","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053304","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":296741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.3359375,\n 74.4964131169431\n ],\n [\n -123.662109375,\n 74.56673621013677\n ],\n [\n -127.529296875,\n 69.83962194067463\n ],\n [\n -136.7578125,\n 69.00567519658819\n ],\n [\n -157.5,\n 71.27259471233448\n ],\n [\n -154.3359375,\n 74.4964131169431\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5492a931e4b00eda8915acf7","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536771,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536863,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536864,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Simac, Kristin S. 0000-0002-4072-1940 ksimac@usgs.gov","orcid":"https://orcid.org/0000-0002-4072-1940","contributorId":131096,"corporation":false,"usgs":true,"family":"Simac","given":"Kristin","email":"ksimac@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":536865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amstrup, Steven C.","contributorId":67034,"corporation":false,"usgs":false,"family":"Amstrup","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":13182,"text":"Polar Bears International","active":true,"usgs":false}],"preferred":false,"id":536866,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70135739,"text":"70135739 - 2014 - Identifying polar bear resource selection patterns to inform offshore development in a dynamic and changing Arctic","interactions":[],"lastModifiedDate":"2014-12-18T09:06:36","indexId":"70135739","displayToPublicDate":"2014-12-17T10:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Identifying polar bear resource selection patterns to inform offshore development in a dynamic and changing Arctic","docAbstract":"Although sea ice loss is the primary threat to polar bears (Ursus maritimus), little can be done to mitigate its effects without global efforts to reduce greenhouse gas emissions. Other factors, however, could exacerbate the impacts of sea ice loss on polar bears, such as exposure to increased industrial activity. The Arctic Ocean has enormous oil and gas potential, and its development is expected to increase in the coming decades. Estimates of polar bear resource selection will inform managers how bears use areas slated for oil development and to help guide conservation planning. We estimated temporally-varying resource selection patterns for non-denning adult female polar bears in the Chukchi Sea population (2008–2012) at two scales (i.e., home range and weekly steps) to identify factors predictive of polar bear use throughout the year, before any offshore development. From the best models at each scale, we estimated scale-integrated resource selection functions to predict polar bear space use across the population's range and determined when bears were most likely to use the region where offshore oil and gas development in the United States is slated to occur. Polar bears exhibited significant intra-annual variation in selection patterns at both scales but the strength and annual patterns of selection differed between scales for most variables. Bears were most likely to use the offshore oil and gas planning area during ice retreat and growth with the highest predicted use occurring in the southern portion of the planning area. The average proportion of predicted high-value habitat in the planning area was >15% of the total high-value habitat for the population during sea ice retreat and growth and reached a high of 50% during November 2010. Our results provide a baseline on which to judge future changes to non-denning adult female polar bear resource selection in the Chukchi Sea and help guide offshore development in the region. Lastly, our study provides a framework for assessing potential impacts of offshore oil and gas development to other polar bear populations around the Arctic.
This report describes the construction, calibration, evaluation, and results of a steady-state numerical groundwater flow model of the Great Basin carbonate and alluvial aquifer system that was developed as part of the U.S. Geological Survey National Water Census Initiative to evaluate the nation’s groundwater availability. The study area spans 110,000 square miles across five states. The numerical model uses MODFLOW-2005, and incorporates and tests complex hydrogeologic and hydrologic elements of a conceptual understanding of an interconnected groundwater system throughout the region, including mountains, basins, consolidated rocks, and basin fill. The level of discretization in this model has not been previously available throughout the study area.
\nObservations used to calibrate the model are those of water levels and discharge to evapotranspiration, springs, rivers, and lakes. Composite scaled sensitivities indicate the simulated values of discharge to springs, rivers, and lakes provide as much information about model parameters as do simulated water-level values. The model has 176 parameters and little parameter correlation. The simulated equivalents to observations provide enough information to constrain most parameters to smaller ranges than the conceptual constraints, and most parameter values are within reasonable ranges.
\nModel fit to observations, comparison of simulated to conceptual water-level contours, and comparison of simulated to conceptual water budgets indicate this model provides a reasonable representation of the regional groundwater system. Eighty-six percent of the simulated values of water levels in wells are within 119 feet (one standard deviation of the error) of the observed values. Ninety percent of the simulated discharges are within 30 percent of the observed values. Total simulated recharge in the study area is within 10 percent of the conceptual amount; total simulated discharge is the same as conceptual discharge. Comparison of simulated hydraulic heads with the conceptual potentiometric surface indicates that the model accurately depicts major features of the hydraulic-head distribution. The incorporation of new recharge estimates and of mountain springs and streams as model observations creates higher simulated recharge mounds under many mountain ranges and highlights that in many cases, the regional flow paths go around, not through (or under) mountain ranges. Results from the model show that much of the flow in the groundwater system occurs in deeper layers, even though about 86 percent of the discharge occurs in layer 1. Over 95 percent of the recharge moves down from layer 1, and about 25 percent moves down to layer 8.
\nThe model was used to delineate six simulated groundwater flow regions that connect recharge areas to discharge areas. The eastern Great Salt Lake and Great Salt Lake Desert model regions contain 75 percent of the groundwater budget, but only 42 percent of the study area. In contrast, the more southern Death Valley and Colorado model regions contain only 12 percent of the groundwater budget, but 37 percent of the study area.
\nExamples of potential use of the model to investigate the groundwater system include (1) the effects of different recharge, (2) different interpretations of the extent or offset of long faults or fault zones, and (3) different conceptual models of the spatial variation of hydraulic properties. The model can also be used to examine the ultimate effects of groundwater withdrawals on a regional scale, to provide boundary conditions for local-scale models, and to guide data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145213","usgsCitation":"Brooks, L.E., Masbruch, M.D., Sweetkind, D.S., and Buto, S.G., 2014, Steady-state numerical groundwater flow model of the Great Basin carbonate and alluvial aquifer system: U.S. Geological Survey Scientific Investigations Report 2014-5213, Report: x, 124 p.; 2 Plates: 16.5 x 22.0 inches; Appendix Tables; Model Files, https://doi.org/10.3133/sir20145213.","productDescription":"Report: x, 124 p.; 2 Plates: 16.5 x 22.0 inches; Appendix Tables; Model Files","numberOfPages":"138","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-037343","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":296686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145213.jpg"},{"id":296683,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5213/downloads/sir2014-5213_plates1and2.zip","text":"Plates 1 and 2","size":"11.6 MB","description":"Plates 1 and 2"},{"id":296681,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5213/"},{"id":296685,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5213/downloads/sir2014-5213_modelfiles.zip","text":"Model Files","size":"143.3 MB","description":"Model Files"},{"id":296684,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5213/downloads/sir2014-5213_appendixexceltables.zip","text":"Appendix Tables","size":"535 kB","description":"Appendix Tables"},{"id":296682,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5213/pdf/sir2014-5213.pdf","size":"32.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Albers Equal Area Conic Projection","datum":"North American Datum 1983","country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.5205078125,\n 35.460669951495305\n ],\n [\n -118.5205078125,\n 42.52069952914966\n ],\n [\n -111.0498046875,\n 42.52069952914966\n ],\n [\n -111.0498046875,\n 35.460669951495305\n ],\n [\n -118.5205078125,\n 35.460669951495305\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Groundwater Resources Program","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54900630e4b020a14785d24a","contributors":{"authors":[{"text":"Brooks, Lynette E. 0000-0002-9074-0939 lebrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-9074-0939","contributorId":2718,"corporation":false,"usgs":true,"family":"Brooks","given":"Lynette","email":"lebrooks@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetkind, Donald S. dsweetkind@usgs.gov","contributorId":127801,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":false,"id":536697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buto, Susan G. 0000-0002-1107-9549 sbuto@usgs.gov","orcid":"https://orcid.org/0000-0002-1107-9549","contributorId":1057,"corporation":false,"usgs":true,"family":"Buto","given":"Susan","email":"sbuto@usgs.gov","middleInitial":"G.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":536696,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160771,"text":"70160771 - 2014 - Acoustic telemetry reveals large-scale migration patterns of walleye in Lake Huron","interactions":[],"lastModifiedDate":"2015-12-30T13:40:16","indexId":"70160771","displayToPublicDate":"2014-12-15T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Acoustic telemetry reveals large-scale migration patterns of walleye in Lake Huron","docAbstract":"Fish migration in large freshwater lacustrine systems such as the Laurentian Great Lakes is not well understood. The walleye (Sander vitreus) is an economically and ecologically important native fish species throughout the Great Lakes. In Lake Huron walleye has recently undergone a population expansion as a result of recovery of the primary stock, stemming from changing food web dynamics. During 2011 and 2012, we used acoustic telemetry to document the timing and spatial scale of walleye migration in Lake Huron and Saginaw Bay. Spawning walleye (n = 199) collected from a tributary of Saginaw Bay were implanted with acoustic tags and their migrations were documented using acoustic receivers (n = 140) deployed throughout U.S. nearshore waters of Lake Huron. Three migration pathways were described using multistate mark-recapture models. Models were evaluated using the Akaike Information Criterion. Fish sex did not influence migratory behavior but did affect migration rate and walleye were detected on all acoustic receiver lines. Most (95%) tagged fish migrated downstream from the riverine tagging and release location to Saginaw Bay, and 37% of these fish emigrated from Saginaw Bay into Lake Huron. Remarkably, 8% of walleye that emigrated from Saginaw Bay were detected at the acoustic receiver line located farthest from the release location more than 350 km away. Most (64%) walleye returned to the Saginaw River in 2012, presumably for spawning. Our findings reveal that fish from this stock use virtually the entirety of U.S. nearshore waters of Lake Huron.
","language":"English","publisher":"PLoS","publisherLocation":"San Francisco","doi":"10.1371/journal.pone.0114833","usgsCitation":"Hayden, T.A., Holbrook, C., Fielder, D.G., Vandergoot, C.S., Bergstedt, R.A., Dettmers, J.M., Krueger, C., and Cooke, S., 2014, Acoustic telemetry reveals large-scale migration patterns of walleye in Lake Huron: PLoS ONE, v. 9, no. 12, p. 1-19, https://doi.org/10.1371/journal.pone.0114833.","productDescription":"19 p.","startPage":"1","endPage":"19","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060215","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0114833","text":"Publisher Index Page"},{"id":313064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan, Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.1715087890625,\n 42.871938424448466\n ],\n [\n -85.1715087890625,\n 45.80965764997408\n ],\n [\n -82.19970703125,\n 45.80965764997408\n ],\n [\n -82.19970703125,\n 42.871938424448466\n ],\n [\n -85.1715087890625,\n 42.871938424448466\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-15","publicationStatus":"PW","scienceBaseUri":"56850e4de4b0a04ef49337be","contributors":{"authors":[{"text":"Hayden, Todd A. 0000-0002-0451-0425 thayden@usgs.gov","orcid":"https://orcid.org/0000-0002-0451-0425","contributorId":5987,"corporation":false,"usgs":true,"family":"Hayden","given":"Todd","email":"thayden@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fielder, David G.","contributorId":127528,"corporation":false,"usgs":false,"family":"Fielder","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":583838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher S.","contributorId":71849,"corporation":false,"usgs":false,"family":"Vandergoot","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":583839,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergstedt, Roger A. rbergstedt@usgs.gov","contributorId":4174,"corporation":false,"usgs":true,"family":"Bergstedt","given":"Roger","email":"rbergstedt@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583840,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettmers, John M.","contributorId":27395,"corporation":false,"usgs":true,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":583841,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Krueger, Charles C.","contributorId":73131,"corporation":false,"usgs":true,"family":"Krueger","given":"Charles C.","affiliations":[],"preferred":false,"id":583842,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":583843,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70135252,"text":"70135252 - 2014 - A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems","interactions":[],"lastModifiedDate":"2014-12-18T09:10:50","indexId":"70135252","displayToPublicDate":"2014-12-15T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":808,"text":"Annual Review of Ecology, Evolution, and Systematics","active":true,"publicationSubtype":{"id":10}},"title":"A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems","docAbstract":"Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-ecolsys-120213-091650","usgsCitation":"Collins, S., Belnap, J., Grimm, N.B., Rudgers, J., Dahm, C., D’Odorico, P., Litvak, M., Natvig, D.O., Peters, D.C., Pockman, W., Sinsabaugh, R.L., and Wolf, B.O., 2014, A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems: Annual Review of Ecology, Evolution, and Systematics, v. 45, p. 397-419, https://doi.org/10.1146/annurev-ecolsys-120213-091650.","productDescription":"23 p.","startPage":"397","endPage":"419","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056887","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":296676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54900627e4b020a14785d244","contributors":{"authors":[{"text":"Collins, Scott L.","contributorId":71307,"corporation":false,"usgs":false,"family":"Collins","given":"Scott L.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":526983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":526982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grimm, N. B.","contributorId":54164,"corporation":false,"usgs":false,"family":"Grimm","given":"N.","email":"","middleInitial":"B.","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":526984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rudgers, J. A.","contributorId":127832,"corporation":false,"usgs":false,"family":"Rudgers","given":"J. A.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":526991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dahm, Clifford N.","contributorId":22730,"corporation":false,"usgs":false,"family":"Dahm","given":"Clifford N.","affiliations":[{"id":7000,"text":"Department of Biology, University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":526985,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"D’Odorico, P.","contributorId":56528,"corporation":false,"usgs":true,"family":"D’Odorico","given":"P.","email":"","affiliations":[],"preferred":false,"id":526992,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Litvak, M.","contributorId":127830,"corporation":false,"usgs":false,"family":"Litvak","given":"M.","email":"","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":526986,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Natvig, D. O.","contributorId":127831,"corporation":false,"usgs":false,"family":"Natvig","given":"D.","email":"","middleInitial":"O.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":526987,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Peters, Douglas C.","contributorId":106797,"corporation":false,"usgs":true,"family":"Peters","given":"Douglas","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":526993,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pockman, W. T.","contributorId":57260,"corporation":false,"usgs":false,"family":"Pockman","given":"W. T.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":526988,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sinsabaugh, R. L.","contributorId":30784,"corporation":false,"usgs":false,"family":"Sinsabaugh","given":"R.","email":"","middleInitial":"L.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":526989,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wolf, B. O.","contributorId":87897,"corporation":false,"usgs":false,"family":"Wolf","given":"B.","email":"","middleInitial":"O.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":526990,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70148179,"text":"70148179 - 2014 - Tree growth and recruitment in a leveed floodplain forest in the Mississippi River Alluvial Valley, USA","interactions":[],"lastModifiedDate":"2015-05-26T10:56:43","indexId":"70148179","displayToPublicDate":"2014-12-15T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Tree growth and recruitment in a leveed floodplain forest in the Mississippi River Alluvial Valley, USA","docAbstract":"Flooding is a defining disturbance in floodplain forests affecting seed germination, seedling establishment, and tree growth. Globally, flood control, including artificial levees, dams, and channelization has altered flood regimes in floodplains. However, a paucity of data are available in regards to the long-term effects of levees on stand establishment and tree growth in floodplain forests. In this study, we used dendrochronological techniques to reconstruct tree recruitment and tree growth over a 90-year period at three stands within a ring levee in the Mississippi River Alluvial Valley (MAV) and to evaluate whether recruitment patterns and tree growth changed following levee construction. We hypothesized that: (1) sugarberry is increasing in dominance and overcup oak (Quercus lyrata) is becoming less dominant since the levee, and that changes in hydrology are playing a greater role than canopy disturbance in these changes in species dominance; and (2) that overcup oak growth has declined following construction of the levee and cessation of overbank flooding whereas that of sugarberry has increased. Recruitment patterns shifted from flood-tolerant overcup oak to flood-intolerant sugarberry (Celtis laevigata) after levee construction. None of the 122 sugarberry trees cored in this study established prior to the levee, but it was the most common species established after the levee. The mechanisms behind the compositional change are unknown, however, the cosmopolitan distribution of overcup oak during the pre-levee period and sugarberry during the post-levee period, the lack of sugarberry establishment in the pre-levee period, and the confinement of overcup oak regeneration to the lowest areas in each stand after harvest in the post-levee period indicate that species-specific responses to flooding and light availability are forcing recruitment patterns. Overcup oak growth was also affected by levee construction, but in contrast to our hypothesis, growth actually increased for several decades before declining during a drought in the late 1990s. We interpret this result as removal of flood stress following levee construction. This finding emphasizes the fact that flooding can be stressful to trees regardless of their flood tolerance and that growth in floodplain trees can be sustained provided adequate soil moisture is present, regardless of the source of soil moisture. However, future research efforts should focus on the long-term effect of hydrologic modification on stand development and on how hydrologic modifications, such as elimination of surface flooding and groundwater declines, affect the vulnerability of floodplain forests to drought.
","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1016/j.foreco.2014.08.024","collaboration":"Arkansas Game and Fish-Commission; Louisiana Department of Wildlife and Fisheries, U.S. Fish and Wildlife Service; U.S. Geological Survey Louisiana Fish and Wildlife Cooperative Research Unit","usgsCitation":"Gee, H.K., King, S.L., and Keim, R., 2014, Tree growth and recruitment in a leveed floodplain forest in the Mississippi River Alluvial Valley, USA: Forest Ecology and Management, v. 334, p. 85-95, https://doi.org/10.1016/j.foreco.2014.08.024.","productDescription":"11 p.","startPage":"85","endPage":"95","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055252","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300781,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"334","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55659958e4b0d9246a9eb647","contributors":{"authors":[{"text":"Gee, Hugo K.W.","contributorId":140925,"corporation":false,"usgs":false,"family":"Gee","given":"Hugo","email":"","middleInitial":"K.W.","affiliations":[],"preferred":false,"id":547604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547537,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":547605,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70135346,"text":"sim3309 - 2014 - Bedrock geologic and structural map through the western Candor Colles region of Mars","interactions":[],"lastModifiedDate":"2023-03-20T18:07:11.900565","indexId":"sim3309","displayToPublicDate":"2014-12-12T12:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3309","title":"Bedrock geologic and structural map through the western Candor Colles region of Mars","docAbstract":"The Candor Colles are a population of low, conical hills along the southeast flank of Ceti Mensa, in west Candor Chasma, within the Valles Marineris system of Mars (fig. 1). Ceti Mensa and the adjacent Candor Mensa are mounds of layered sedimentary deposits and are the most prominent landforms within west Candor Chasma. Prior to the arrival of the Mars Reconnaissance Orbiter (MRO) in orbit around Mars in 2006 (Zurek and Smrekar, 2007), geologic maps of the area utilized the relatively low resolution Viking Orbiter photomosaics (20–150 m/pixel). Geologic maps covering west Candor Chasma were created at scales of 1:15,000,000 for the western equatorial region of Mars (Scott and Tanaka, 1986), 1:2,000,000 for the Valles Marineris region (Witbeck and others, 1991), and 1:500,000 for the far eastern part of west Candor Chasma (Mars Transverse Mercator quadrangle–05072; Lucchitta, 1999).
\n\n
Previous structural mapping in west Candor Chasma at scales of less than 1:24,000 (Okubo and others, 2008; Okubo, 2010) employed digital terrain models (DTMs), with 1-m post spacings, derived from stereo MRO High Resolution Imaging Science Experiment (HiRISE) imagery (McEwen and others, 2010) and focused on examining the relative timing between deposition of the youngest unit of the layered deposits in this area (unit Avme of Witbeck and others, 1991) relative to regional faulting related to chasma formation. These previous mapping efforts on the southwest flank of Ceti Mensa demonstrated that unit Avme is not deformed by faults attributed to formation of the chasma. Studies of other layered deposits (primarily unit Hvl, but also including units Avme, Avsl, Avsd, and Avfs; Witbeck and others, 1991) exposed along the southeast flank of Ceti Mensa using a High-Resolution Stereo Camera (HRSC) digital terrain model (DTM) (50 m/pixel) refined the local stratigraphy and revealed evidence for syntectonic deposition of these deposits (Fueten and others, 2006, 2008; Jaumann and others, 2007; Birnie and others, 2012).
\n\n
Layered deposits such as those that constitute Ceti Mensa are widespread throughout the interior regions of Valles Marineris (Witbeck and others, 1991). These sedimentary deposits have been variously interpreted as eolian sediments (Nedell and others, 1987), hyaloclastic debris (Chapman and Tanaka, 2001; Komatsu and others, 2004), lacustrine or fluvial sediment (Dromart and others, 2007; Mangold and others, 2008; Metz and others, 2009), pyroclastic deposits (Hynek and others, 2003), evaporites (Mangold and others, 2008; Andrews-Hanna and others, 2010), or various combinations thereof.
\n\n
Recent analysis of data from the MRO Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) shows that these sediments consist primarily of hydrated sulfates (Murchie and others, 2009a,b). Further, hydrologic modeling indicates that spring-fed lakes likely occurred within the chasma (Andrews-Hanna and others, 2010). These recent findings point to a scenario in which the layered deposits accumulated as sequences of evaporites precipitating in hypersaline lakes, with contemporaneous trapping of eolian dust and sand, diagenesis, and iron-cycling, interspersed with periods of eolian and fluvial erosion (Murchie and others, 2009a). Water vapor released from these lakes may have also driven localized precipitation of snow and accumulation of layered deposits on the adjacent plateaus (Kite and others, 2011a,b). This scenario is in contrast to recent alternative interpretations that the layered deposits formed within the chasma through weathering of dust-rich ice deposits (Niles and Michalski, 2009; Michalski and Niles, 2012).
\n
The structure and geology of the layered deposits in the Candor Colles region corresponding to units Avfs, Avme, and Hvl of Witbeck and others (1991) are reevaluated in this 1:18,000-scale map. The objectives herein are to gather high-resolution structural measurements to (1) refine the previous unit boundaries in this area established by Witbeck and others (1991), (2) revise the local stratigraphy where necessary, (3) characterize bed forms to help constrain depositional processes, and (4) determine the styles and extent of deformation to better inform reconstructions of the local post-depositional geologic history.
In the endeavor to assess potential effects to the Gulf of Mexico ecosystem from the Mississippi Canyon 252 incident, referred to as the Deepwater Horizon oil spill, various environmental data have been collected. Whereas initial efforts have included satellite tracking and sediment and water sampling to estimate the geographical scope of oiling, research on biological samples can provide insights into potential physiological responses to oil if it was present in the food web, sediment, or water column. Fish species are ideal model organisms for studying responses to water- and sediment-borne contaminants due to their life history (Jenkins et al. 2014), and several Gulf of Mexico fish species were studied by scientists after this incident. Typical field data collected on fish reflect organism condition and include observations such as fish length, weight, gonad condition, condition factor (weight in relation to length), parasite load, and color of organs (Schmitt and Dethloff 2000). However, if physiological responses occurred due to oil exposure, effects would not be immediately visible using organism-level observations alone. Changes occur first at the organ, tissue, cell, or molecular levels, and these responses can be measured by using biomarker assays (van der Oost et al. 2003).
","largerWorkTitle":"Impacts of oil spill disasters on marine habitats and fisheries in North America","language":"English","publisher":"CRC Press","isbn":"9781466557208 ","usgsCitation":"Olivier, H.M., and Jenkins, J.A., 2014, Proper handling of animal tissues from the field to the laboratory supports reliable biomarker endpoints, chap. of Impacts of oil spill disasters on marine habitats and fisheries in North America, p. 81-93.","productDescription":"13 p.","startPage":"81","endPage":"93","ipdsId":"IP-046164","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":360242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360241,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.crcpress.com/Impacts-of-Oil-Spill-Disasters-on-Marine-Habitats-and-Fisheries-in-North/Alford-Peterson-Green/p/book/9781466557208"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c137dd5e4b006c4f85148a0","contributors":{"editors":[{"text":"Alford, J. B.","contributorId":120313,"corporation":false,"usgs":true,"family":"Alford","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":754140,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Peterson, Mark S.","contributorId":8979,"corporation":false,"usgs":true,"family":"Peterson","given":"Mark","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":754141,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Green, Christopher C.","contributorId":111389,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":754142,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Olivier, Heather M.","contributorId":23245,"corporation":false,"usgs":true,"family":"Olivier","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":754139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":754138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70129575,"text":"fs20143107 - 2014 - The 3D Elevation Program: summary for Michigan","interactions":[],"lastModifiedDate":"2016-08-17T15:17:03","indexId":"fs20143107","displayToPublicDate":"2014-12-11T09:00:00","publicationYear":"2014","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":"2014-3107","title":"The 3D Elevation Program: summary for Michigan","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Michigan, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, water supply and quality, infrastructure and construction management, coastal zone management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation's natural and constructed features. The Michigan Statewide Authoritative Imagery and Lidar (MiSAIL) program provides statewide lidar coordination with local, State, and national groups in support of 3DEP for Michigan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143107","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Michigan (Originally posted December 10, 2014; Version 1.1: January 5, 2015; Version 1.2: June 29, 2015): U.S. Geological Survey Fact Sheet 2014-3107, 2 p., https://doi.org/10.3133/fs20143107.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057034","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":296601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143107.jpg"},{"id":296600,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3107/pdf/fs2014-3107.pdf","text":"Report","size":"351 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":296593,"rank":2,"type":{"id":15,"text":"Index 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Jr. carswell@usgs.gov","contributorId":127609,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":526945,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70135097,"text":"70135097 - 2014 - Quaternary landscape development, alluvial fan chronology and erosion of the Mecca Hills at the southern end of the San Andreas Fault zone","interactions":[],"lastModifiedDate":"2014-12-10T15:07:43","indexId":"70135097","displayToPublicDate":"2014-12-10T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Quaternary landscape development, alluvial fan chronology and erosion of the Mecca Hills at the southern end of the San Andreas Fault zone","docAbstract":"Quantitative geomorphic analysis combined with cosmogenic nuclide 10Be-based geochronology and denudation rates have been used to further the understanding of the Quaternary landscape development of the Mecca Hills, a zone of transpressional uplift along the southern end of the San Andreas Fault, in southern California. The similar timing of convergent uplifts along the San Andreas Fault with the initiation of the sub-parallel San Jacinto Fault suggest a possible link between the two tectonic events. The ages of alluvial fans and the rates of catchment-wide denudation have been integrated to assess the relative influence of climate and tectonic uplift on the development of catchments within the Mecca Hills. Ages for major geomorphic surfaces based on 10Be surface exposure dating of boulders and 10Be depth profiles define the timing of surface stabilization to 2.6 +5.6/–1.3 ka (Qyf1 surface), 67.2 ± 5.3 ka (Qvof2 surface), and 280 ± 24 ka (Qvof1 surface). Comparison of 10Be measurements from active channel deposits (Qac) and fluvial terraces (Qt) illustrate a complex history of erosion, sediment storage, and sediment transport in this environment. Beryllium-10 catchment-wide denudation rates range from 19.9 ± 3.2 to 149 ± 22.5 m/Ma and demonstrate strong correlations with mean catchment slope and with total active fault length normalized by catchment area. The lack of strong correlation with other geomorphic variables suggests that tectonic uplift and rock weakening have the greatest control. The currently measured topography and denudation rates across the Mecca Hills may be most consistent with a model of radial topographic growth in contrast to a model based on the rapid uplift and advection of crust.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2014.09.009","usgsCitation":"Gray, H.J., Owen, L.A., Dietsch, C., Beck, R., Caffee, M.A., Finkelman, R., and Mahan, S., 2014, Quaternary landscape development, alluvial fan chronology and erosion of the Mecca Hills at the southern end of the San Andreas Fault zone: Quaternary Science Reviews, v. 105, p. 66-85, https://doi.org/10.1016/j.quascirev.2014.09.009.","productDescription":"20 p.","startPage":"66","endPage":"85","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054894","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":472579,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2014.09.009","text":"Publisher Index Page"},{"id":296595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.51904296875,\n 42.00032514831621\n ],\n [\n -119.77294921874999,\n 42.00032514831621\n ],\n [\n -119.86083984375,\n 38.94232097947902\n ],\n [\n -113.64257812499999,\n 34.34343606848294\n ],\n [\n -114.521484375,\n 32.75032260780972\n ],\n [\n -117.333984375,\n 32.56533316084101\n ],\n [\n -121.4208984375,\n 34.63320791137959\n ],\n [\n -124.71679687499999,\n 40.54720023441049\n ],\n [\n -124.51904296875,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb7e4b027aeab781288","contributors":{"authors":[{"text":"Gray, Harrison J. 0000-0002-4555-7473 hgray@usgs.gov","orcid":"https://orcid.org/0000-0002-4555-7473","contributorId":4991,"corporation":false,"usgs":true,"family":"Gray","given":"Harrison","email":"hgray@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":526815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Owen, Lewis A.","contributorId":127798,"corporation":false,"usgs":false,"family":"Owen","given":"Lewis","email":"","middleInitial":"A.","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":526816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dietsch, Craig","contributorId":127799,"corporation":false,"usgs":false,"family":"Dietsch","given":"Craig","email":"","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":526817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Richard A.","contributorId":49202,"corporation":false,"usgs":false,"family":"Beck","given":"Richard A.","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":526818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caffee, Marc A.","contributorId":36048,"corporation":false,"usgs":false,"family":"Caffee","given":"Marc","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":526819,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finkelman, Robert B.","contributorId":38138,"corporation":false,"usgs":false,"family":"Finkelman","given":"Robert B.","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":526820,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mahan, Shannon 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":1215,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":526814,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70135184,"text":"sir20145211 - 2014 - Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010","interactions":[],"lastModifiedDate":"2014-12-10T13:28:26","indexId":"sir20145211","displayToPublicDate":"2014-12-10T14:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5211","title":"Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010","docAbstract":"Flooding is among the worst natural disasters responsible for loss of life and property in Arizona, underscoring the importance of accurate estimation of flood magnitude for proper structural design and floodplain mapping. Twenty-four years of additional peak-flow data have been recorded since the last comprehensive regional flood frequency analysis conducted in Arizona. Periodically, flood frequency estimates and regional regression equations must be revised to maintain the accurate estimation of flood frequency and magnitude.
\n\n
Annual peak-flow data collected through water year 2010 were compiled from 448 unregulated streamflow-gaging stations, hereafter referred to as streamgages, in Arizona having a minimum of 10 years of record. Flood frequency estimates were first computed with station (or at-site) skew using the Expected Moments Algorithm with a multiple Grubbs-Beck test to identify multiple potentially influential low flows to fit a Pearson Type III distribution. Next, a multiple step Bayesian least-squares-regression approach was used to determine a new statewide regional skew of −0.09. No basin characteristics analyzed were statistically significant in explaining the variation in skew and as a result, the constant model was chosen as the best regional skew model for the Arizona study area. The mean square error used in Bulletin 17B (B17B) of the Interagency Advisory Committee on Water Data is used to describe the precision of the regional skew. The constant model had a mean square error equal to 0.08, which corresponds to an effective record length of 85 years. This is a marked improvement over a previous Arizona regional skew analysis, with a reported mean square error of 0.31, for a corresponding effective record length of around 17 years. Thus the new regional model had almost five times the information content (as measured by effective record length) of that calculated in USGS Water Supply Paper 2433, published in 1997, or the value of 0.302 reported in the B17B generalized skew map. The flood frequency estimates were recalculated using a weighted skew of the station and regional skew. Station flood frequency estimates for each streamgage are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities.
\n\n
Geographical information systems were used to compute basin characteristic information for each streamgage for the purpose of developing regional equations to estimate flood statistics at ungaged basins. Five hydrologic flood regions in Arizona were defined in a multivariate regionalization process based on mean basin elevation, mean annual precipitation, and soil permeability. A regional generalized least-squares-regression analysis was used to develop five sets of equations from 344 nonredundant streamgages, corresponding to five regions, for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities at ungaged basins in Arizona. The regression equations developed for these five regions were based on one or more of the statistically significant explanatory variables: drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression regions for the five regions ranged from 27 to 122 percent and the pseudo-coefficients of determination (pseudo-R2), a measure of the proportion of peak-flow variation that is explained by the basin characteristics, ranged from 68 to 98 percent. Regression equations for Central Highlands (region 4) had the lowest model error and the greatest pseudo-R2 metrics. The equations for Colorado Plateau (region 2) regression equations generally had greater model error and lower pseudo-R2 metrics. The improvement of regional regression equation model error and pseudo-R2 metrics was related to higher numbers of streamgages, longer period of record, and even spatial coverage within a region.
\n\n
The regional regression equations were integrated into the U.S. Geological Survey’s StreamStats program. The StreamStats program is a national map-based web application that allows the public to easily access published flood frequency and basin characteristic statistics. The interactive web application allows a user to select a point within a watershed (gaged or ungaged) and retrieve flood-frequency estimates derived from the current regional regression equations and geographic information system data within the selected basin. StreamStats provides users with an efficient and accurate means for retrieving the most up to date flood frequency and basin characteristic data. StreamStats is intended to provide consistent statistics, minimize user error, and reduce the need for large datasets and costly geographic information system software.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145211","collaboration":"Prepared in cooperation with the Flood Control Districts of Maricopa County, Pima County, Pinal County, Yavapai County, Mohave County, Cochise County, Navajo County, Greenlee County, and Salt River Project, U.S. Forest Service, and Bureau of Reclamation.","usgsCitation":"Paretti, N., Kennedy, J.R., Turney, L.A., and Veilleux, A.G., 2014, Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010: U.S. Geological Survey Scientific Investigations Report 2014-5211, Report: vii, 61 p.; 16 Tables, https://doi.org/10.3133/sir20145211.","productDescription":"Report: vii, 61 p.; 16 Tables","numberOfPages":"73","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040579","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":296591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145211.gif"},{"id":296589,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5211/downloads/sir2014-5211.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296590,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5211/downloads/SIR2014-5211_tables.xlsx","text":"Tables","size":"650 kB"},{"id":296585,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5211/"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 37.055177106660814\n ],\n [\n -108.984375,\n 31.31610138349565\n ],\n [\n -111.1376953125,\n 31.259769987394286\n ],\n [\n -114.98291015625,\n 32.47269502206151\n ],\n [\n -114.873046875,\n 36.19109202182454\n ],\n [\n -114.14794921875,\n 37.020098201368114\n ],\n [\n -109.00634765625,\n 37.055177106660814\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb5e4b027aeab781282","contributors":{"authors":[{"text":"Paretti, Nicholas V. nparetti@usgs.gov","contributorId":802,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas V.","email":"nparetti@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":526927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":526928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turney, Lovina A. labbott@usgs.gov","contributorId":5744,"corporation":false,"usgs":true,"family":"Turney","given":"Lovina","email":"labbott@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":526929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":526930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70111875,"text":"sir20145109 - 2014 - Methods for estimating magnitude and frequency of 1-, 3-, 7-, 15-, and 30-day flood-duration flows in Arizona","interactions":[],"lastModifiedDate":"2015-04-01T11:41:40","indexId":"sir20145109","displayToPublicDate":"2014-12-10T13:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5109","title":"Methods for estimating magnitude and frequency of 1-, 3-, 7-, 15-, and 30-day flood-duration flows in Arizona","docAbstract":"Large floods have historically caused extensive damage in Arizona. Although peak-flow frequency estimates are required for managing the risk posed by floods, estimates of the frequency of sustained flood flow (flood-duration flow) are also useful for planning and assessing the adequacy of retention and conveyance structures and for water-resource planning. This report presents a flood-duration flow frequency analysis for selected durations (1 day, 3 day, 7 day, 15 day, and 30 day) at 173 streamgaging stations throughout Arizona and in western New Mexico. For each n-day duration, a log-Pearson type III distribution was fitted to the annual series of n-day flood-duration flows using the expected moments algorithm with a multiple Grubbs-Beck low-outlier test. Regional skews were developed independently for each n-day duration using a hybrid weighted least squares/generalized least squares method. No basin characteristics were found to adequately explain variation in skew among stations and a constant statewide skew model was used for all n-day durations. The regional skewness coefficient is negative for all n-day durations and becomes increasingly negative for longer n-day durations. Uncertainty associated with the skewness coefficient is estimated using a Bayesian generalized least squares technique.
\nRegression equations, which allow predictions of n-day flood-duration flows for selected annual exceedance probabilities at ungaged sites, were developed using generalized least-squares regression and flood-duration flow frequency estimates at 56 streamgaging stations within a single, relatively uniform physiographic region in the central part of Arizona, between the Colorado Plateau and Basin and Range Province, called the Transition Zone. Drainage area explained most of the variation in the n-day flood-duration annual exceedance probabilities, but mean annual precipitation and mean elevation were also significant variables in the regression models. Standard error of prediction for the regression equations varies from 28 to 53 percent and generally decreases with increasing n-day duration. Outside the Transition Zone there are insufficient streamgaging stations to develop regression equations, but flood-duration flow frequency estimates are presented at select streamgaging stations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145109","collaboration":"Prepared in cooperation with the Flood Control District of Maricopa County","usgsCitation":"Kennedy, J.R., Paretti, N., and Veilleux, A.G., 2014, Methods for estimating magnitude and frequency of 1-, 3-, 7-, 15-, and 30-day flood-duration flows in Arizona (Version 1.0: December 9, 2014; Version 1.1: April 1, 2015): U.S. Geological Survey Scientific Investigations Report 2014-5109, Report: v, 35 p.; 3 Appendices, https://doi.org/10.3133/sir20145109.","productDescription":"Report: v, 35 p.; 3 Appendices","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-037880","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":299247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145109.gif"},{"id":296576,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5109/"},{"id":296577,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5109/downloads/sir2014-5109.pdf","text":"Report","size":"11.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":296578,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5109/downloads/Appendix_1_station_estimates.xlsx","text":"Appendix 1","size":"152 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1"},{"id":296579,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5109/downloads/Appendix_2_station_variance.xlsx","text":"Appendix 2","size":"140 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2"},{"id":296580,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5109/downloads/Appendix_3.pdf","text":"Appendix 3","size":"267 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 3"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.00634765625,\n 37.055177106660814\n ],\n [\n -108.984375,\n 31.31610138349565\n ],\n [\n -111.1376953125,\n 31.259769987394286\n ],\n [\n -114.98291015625,\n 32.47269502206151\n ],\n [\n -114.873046875,\n 36.19109202182454\n ],\n [\n -114.14794921875,\n 37.020098201368114\n ],\n [\n -109.00634765625,\n 37.055177106660814\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 9, 2014; Version 1.1: April 1, 2015","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54896eb4e4b027aeab781280","contributors":{"authors":[{"text":"Kennedy, Jeffrey R. 0000-0002-3365-6589 jkennedy@usgs.gov","orcid":"https://orcid.org/0000-0002-3365-6589","contributorId":2172,"corporation":false,"usgs":true,"family":"Kennedy","given":"Jeffrey","email":"jkennedy@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paretti, Nicholas V. nparetti@usgs.gov","contributorId":802,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas V.","email":"nparetti@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":false,"id":518928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":518929,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70135156,"text":"70135156 - 2014 - Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling","interactions":[],"lastModifiedDate":"2016-11-22T18:40:45","indexId":"70135156","displayToPublicDate":"2014-12-10T12:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling","docAbstract":"Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.
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