Reactive nitrogen (Nr) from anthropogenic sources has been altering ecosystem function in lakes of the Rocky Mountains, other regions of western North America, and the Arctic over recent decades. The response of biota in shallow lakes to atmospheric deposition of Nr, however, has not been considered. Benthic algae are dominant in shallow, high-elevation lakes and are less sensitive to nutrient inputs than planktonic algae. Because the benthos is typically more nutrient rich than the water column, shallow lakes are not expected to show evidence of anthropogenic Nr. In this study, we assessed sedimentary evidence for regional Nr deposition, sediment chronology, and the nature of algal community response in five shallow, high-elevation lakes in Grand Teton National Park (GRTE). Over 140 diatom taxa were identified from the sediments, with a relatively high species richness of taxa characteristic of oligotrophic conditions. The diatom assemblages were dominated by benthic taxa, especially motile taxa. The GRTE lakes demonstrate assemblage-wide shifts in diatoms, including 1) synchronous and significant assemblage changes centered on ~1960 AD; 2) pre-1960 assemblages differed significantly from post-1960 assemblages; 3) pre-1960 diatom assemblages fluctuated randomly, whereas post- 1960 assemblages showed directional change; 4) changes in δ15N signatures were correlated with diatom community composition. These results demonstrate recent changes in shallow high18 elevation lakes that are most correlated with anthropogenic Nr. It is also possible, however, that the combined effect of Nr deposition and warming is accelerating species shifts in benthic diatoms. While uncertainties remain about the potential synergy of Nr deposition and warming, this study adds shallow lakes to the growing list of impacted high-elevation localities in western North America.
","language":"English","publisher":"Institute of Arctic and Alpine Research","doi":"10.1657/AAAR0015-008","usgsCitation":"Spaulding, S.A., Otu, M.K., Wolfe, A.P., and Baron, J., 2015, Paleolimnological records of nitrogen deposition in shallow, high-elevation lakes of Grand Teton National Park, Wyoming, USA: Arctic, Antarctic, and Alpine Research, v. 47, no. 4, p. 703-717, https://doi.org/10.1657/AAAR0015-008.","productDescription":"15 p.","startPage":"703","endPage":"717","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062936","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":471806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1657/aaar0015-008","text":"Publisher Index Page"},{"id":307955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Grand Teton National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.89324951171875,\n 43.56447158721811\n ],\n [\n -110.89324951171875,\n 43.84245116699036\n ],\n [\n -110.67901611328125,\n 43.84245116699036\n ],\n [\n -110.67901611328125,\n 43.56447158721811\n ],\n [\n -110.89324951171875,\n 43.56447158721811\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-05","publicationStatus":"PW","scienceBaseUri":"55eff8a8e4b0dacf699e9fd7","contributors":{"authors":[{"text":"Spaulding, Sarah A. 0000-0002-9787-7743 sspaulding@usgs.gov","orcid":"https://orcid.org/0000-0002-9787-7743","contributorId":1157,"corporation":false,"usgs":true,"family":"Spaulding","given":"Sarah","email":"sspaulding@usgs.gov","middleInitial":"A.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":571511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otu, Megan K.","contributorId":147387,"corporation":false,"usgs":false,"family":"Otu","given":"Megan","email":"","middleInitial":"K.","affiliations":[{"id":16833,"text":"INSTAAR, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":571513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolfe, Alexander P.","contributorId":147388,"corporation":false,"usgs":false,"family":"Wolfe","given":"Alexander","email":"","middleInitial":"P.","affiliations":[{"id":12799,"text":"University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":571514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":571512,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157080,"text":"70157080 - 2015 - The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys","interactions":[],"lastModifiedDate":"2015-09-08T13:34:42","indexId":"70157080","displayToPublicDate":"2015-09-08T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys","docAbstract":"The Palos Verdes Fault (PVF) is one of few active faults in Southern California that crosses the shoreline and can be studied using both terrestrial and subaqueous methodologies. To characterize the near-seafloor fault morphology, tectonic influences on continental slope sedimentary processes and late Pleistocene to present slip rate, a grid of high-resolution multibeam bathymetric data, and chirp subbottom profiles were acquired with an autonomous underwater vehicle (AUV) along the main trace of PVF in water depths between 250 and 600 m. Radiocarbon dates were obtained from vibracores collected using a remotely operated vehicle (ROV) and ship-based gravity cores. The PVF is expressed as a well-defined seafloor lineation marked by subtle along-strike bends. Right-stepping transtensional bends exert first-order control on sediment flow dynamics and the spatial distribution of Holocene depocenters; deformed strata within a small pull-apart basin record punctuated growth faulting associated with at least three Holocene surface ruptures. An upper (shallower) landslide scarp, a buried sedimentary mound, and a deeper scarp have been right-laterally offset across the PVF by 55 ± 5, 52 ± 4 , and 39 ± 8 m, respectively. The ages of the upper scarp and buried mound are approximately 31 ka; the age of the deeper scarp is bracketed to 17–24 ka. These three piercing points bracket the late Pleistocene to present slip rate to 1.3–2.8 mm/yr and provide a best estimate of 1.6–1.9 mm/yr. The deformation observed along the PVF is characteristic of strike-slip faulting and accounts for 20–30% of the total right-lateral slip budget accommodated offshore Southern California.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011938","usgsCitation":"Brothers, D., Conrad, J.E., Maier, K., Paull, C.K., McGann, M., and Caress, D.W., 2015, The Palos Verdes Fault offshore southern California: late Pleistocene to present tectonic geomorphology, seascape evolution and slip rate estimate based on AUV and ROV surveys: Journal of Geophysical Research B: Solid Earth, v. 120, no. 7, p. 4734-4758, https://doi.org/10.1002/2015JB011938.","productDescription":"25 p.","startPage":"4734","endPage":"4758","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063656","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":307951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Palos Verdes Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.39691162109375,\n 33.30987251398259\n ],\n [\n -118.39691162109375,\n 33.8430453147447\n ],\n [\n -117.75421142578125,\n 33.8430453147447\n ],\n [\n -117.75421142578125,\n 33.30987251398259\n ],\n [\n -118.39691162109375,\n 33.30987251398259\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-30","publicationStatus":"PW","scienceBaseUri":"55eff8a9e4b0dacf699e9fe2","chorus":{"doi":"10.1002/2015jb011938","url":"http://dx.doi.org/10.1002/2015jb011938","publisher":"Wiley-Blackwell","authors":"Brothers Daniel S., Conrad James E., Maier Katherine L., Paull Charles K., McGann Mary, Caress David W.","journalName":"Journal of Geophysical Research: Solid Earth","publicationDate":"7/2015"},"contributors":{"authors":[{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":140096,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":571527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":571528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":571529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paull, Charles K. 0000-0001-5940-3443","orcid":"https://orcid.org/0000-0001-5940-3443","contributorId":55825,"corporation":false,"usgs":false,"family":"Paull","given":"Charles","email":"","middleInitial":"K.","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":true,"id":571530,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGann, Mary L. 0000-0002-3057-2945 mmcgann@usgs.gov","orcid":"https://orcid.org/0000-0002-3057-2945","contributorId":147188,"corporation":false,"usgs":true,"family":"McGann","given":"Mary L.","email":"mmcgann@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":571531,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Caress, David W.","contributorId":147392,"corporation":false,"usgs":false,"family":"Caress","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":16837,"text":"MBARI","active":true,"usgs":false}],"preferred":false,"id":571532,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70156560,"text":"ofr20101083Q - 2015 - Seismicity of the Earth 1900‒2013 Mediterranean Sea and vicinity","interactions":[],"lastModifiedDate":"2015-09-09T08:54:41","indexId":"ofr20101083Q","displayToPublicDate":"2015-09-08T14:15:00","publicationYear":"2015","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":"2010-1083","chapter":"Q","title":"Seismicity of the Earth 1900‒2013 Mediterranean Sea and vicinity","docAbstract":"The Mediterranean region is seismically active due to the convergence of the Africa Plate with the Eurasia plate. Present day Africa-Eurasia motion ranges from ~4 millimeters per year (mm/yr) in a northwest-southeast direction in the western Mediterranean to ~10 mm/yr (north-south) in the eastern Mediterranean. The Africa-Eurasia plate boundary is complex, and includes extensional and translational zones in addition to the dominant convergent regimes characterized by subduction and continental collision. This convergence began at approximately 50 million years ago and was associated with the closure of the Tethys Sea; the Mediterranean Sea is all that remains of the Tethys. The highest rates of seismicity in the Mediterranean region are found along the Hellenic subduction zone of southern Greece and the North Anatolian Fault Zone of northwestern Turkey, but significant rates of current seismicity and large historical earthquakes have occurred throughout the region spanning the Mediterranean Sea.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101083Q","usgsCitation":"Herman, M.W., Hayes, G.P., Smoczyk, G.M., Turner, Rebecca, Turner, Bethan, Jenkins, Jennifer, Davies, Sian, Parker, Amy, Sinclair, Allison, Benz, H.M., Furlong, K.P., and Villaseñor, Antonio, 2015, Seismicity of the Earth 1900–2013, Mediterranean Sea and vicinity: U.S. Geological Survey Open-File Report 2010–1083-Q, scale 1:10,000,000, https://dx.doi.org/10.3133/ofr20101083Q.","productDescription":"1 p.","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065794","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":307744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2010/1083/q/coverthb.jpg"},{"id":307745,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2010/1083/q/ofr20101083q.pdf","text":"Report","size":"78.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2010-1083-Q"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -18.45703125,\n 22.431340156360594\n ],\n [\n -18.45703125,\n 57.040729838360875\n ],\n [\n 51.328125,\n 57.040729838360875\n ],\n [\n 51.328125,\n 22.431340156360594\n ],\n [\n -18.45703125,\n 22.431340156360594\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
http://geohazards.cr.usgs.gov/
Subglacial discharge influences glacier basal motion and erodes and redeposits sediment. At tidewater glacier termini, discharge drives submarine terminus melting, affects fjord circulation, and is a central component of proglacial marine ecosystems. However, our present inability to track subglacial discharge and its variability significantly hinders our understanding of these processes. Here we report observations of hourly to seasonal variations in 1.5–10 Hz seismic tremor that strongly correlate with subglacial discharge but not with basal motion, weather, or discrete icequakes. Our data demonstrate that vigorous discharge occurs from tidewater glaciers during summer, in spite of fast basal motion that could limit the formation of subglacial conduits, and then abates during winter. Furthermore, tremor observations and a melt model demonstrate that drainage efficiency of tidewater glaciers evolves seasonally. Glaciohydraulic tremor provides a means by which to quantify subglacial discharge variations and offers a promising window into otherwise obscured glacierized environments.
","language":"English","publisher":"Wiley","doi":"10.1002/2015GL064590","usgsCitation":"Bartholomaus, T.C., Amundson, J.M., Walter, J., O’Neel, S., West, M.E., and Larsen, C.F., 2015, Subglacial discharge at tidewater glaciers revealed by seismic tremor: Geophysical Research Letters, v. 42, no. 15, p. 6391-6398, https://doi.org/10.1002/2015GL064590.","productDescription":"8 p.","startPage":"6391","endPage":"6398","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060356","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":471808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl064590","text":"Publisher Index Page"},{"id":307956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland, United States","state":"Alaska","otherGeospatial":"Columbia Glacier, Hubbard Glacier, Jakobshavn Isbræ, Mendenhall Glacier, 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Most studies attribute this purely to underlying physical templates, such as groundwater salinity gradients caused by tidal flux and topography. However, a few recent studies hypothesize that self-reinforcing feedback between vegetation and vadose zone salinity are also involved and create a bistable situation in which either halophytic dominated habitat or freshwater plant communities may dominate as alternative stable states. Here, we revisit the bistability hypothesis and demonstrate the mechanisms that result in bistability. We demonstrate with remote sensing imagery the sharp boundaries between freshwater hardwood hammock communities in southern Florida and halophytic communities such as buttonwood hammocks and mangroves. We further document from the literature how transpiration of mangroves and freshwater plants respond differently to vadose zone salinity, thus altering the salinity through feedback. Using mathematical models, we show how the self-reinforcing feedback, together with physical template, controls the ecotones between halophytic and freshwater communities. Regions of bistability along environmental gradients of salinity have the potential for large-scale vegetation shifts following pulse disturbances such as hurricane tidal surges in Florida, or tsunamis in other regions. The size of the region of bistability can be large for low-lying coastal habitat due to the saline water table, which extends inland due to salinity intrusion. We suggest coupling ecological and hydrologic processes as a framework for future studies.
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We defined the minimum stover requirement (MSR) to maintain current soil organic carbon levels and then estimated current and future soil carbon (C), nitrogen (N), phosphorus (P), and potassium (K) budgets for various stover harvest scenarios. Analyses for 2006 through 2010 across the entire Corn Belt indicated that currently, 28 Tg or 1.6 Mg ha−1 of stover could be sustainably harvested from 17.95 million hectares (Mha) with N, P, and K removal of 113, 26, and 47 kg ha−1, respectively, and C removal for that period was estimated to be 4.55 Mg C ha−1. Assuming continued yield increases and a planted area of 26.74 Mha in 2050, 77.4 Tg stover (or 2.4 Mg ha−1) could be sustainably harvested with N, P, and K removal of 177, 37, and 72 kg ha−1, respectively, along with C removal of ∼6.57 Mg C ha−1. Although there would be significant variation across the region, harvesting only the excess over the MSR under current fertilization rates would result in a small depletion of soil N (−5 ± 27 kg ha−1) and K (−20 ± 31 kg ha−1) and a moderate surplus of P (36 ± 18 kg ha−1). Our 2050 projections based on continuing to keep the MSR, but having higher yields indicate that soil N and K deficits would become larger, thus emphasize the importance of balancing soil nutrient supply with crop residue removal.
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The methods include a physics‐based model by Hartzell et al. (1999, 2005), a stochastic source‐based model by Boore (2009), and a stochastic site‐based model by Rezaeian and Der Kiureghian (2010, 2012). The ground‐motion dataset consists of 40 stations within 600 km of the epicenter. Several metrics are used to validate the simulations: (1) overall bias of response spectra and Fourier spectra (from 0.1 to 10 Hz); (2) spatial distribution of residuals for GMRotI50 peak ground acceleration (PGA), peak ground velocity, and pseudospectral acceleration (PSA) at various periods; (3) comparison with ground‐motion prediction equations (GMPEs) for the eastern United States. Our results show that (1) the physics‐based model provides satisfactory overall bias from 0.1 to 10 Hz and produces more realistic synthetic waveforms; (2) the stochastic site‐based model also yields more realistic synthetic waveforms and performs superiorly for frequencies greater than about 1 Hz; (3) the stochastic source‐based model has larger bias at lower frequencies (<0.5 Hz) and cannot reproduce the varying frequency content in the time domain. The spatial distribution of GMRotI50 residuals shows that there is no obvious pattern with distance in the simulation bias, but there is some azimuthal variability. The comparison between synthetics and GMPEs shows similar fall‐off with distance for all three models, comparable PGA and PSA amplitudes for the physics‐based and stochastic site‐based models, and systematic lower amplitudes for the stochastic source‐based model at lower frequencies (<0.5 Hz).
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Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":541902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":541903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":541904,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156414,"text":"ofr20151158 - 2015 - Range-wide network of priority areas for greater sage-grouse - a design for conserving connected distributions or isolating individual zoos?","interactions":[{"subject":{"id":70156414,"text":"ofr20151158 - 2015 - Range-wide network of priority areas for greater sage-grouse - a design for conserving connected distributions or isolating individual zoos?","indexId":"ofr20151158","publicationYear":"2015","noYear":false,"title":"Range-wide network of priority areas for greater sage-grouse - a design for conserving connected distributions or isolating individual zoos?"},"predicate":"SUPERSEDED_BY","object":{"id":70179852,"text":"70179852 - 2017 - Range-wide connectivity of priority areas for Greater Sage-Grouse: Implications for long-term conservation from graph theory","indexId":"70179852","publicationYear":"2017","noYear":false,"title":"Range-wide connectivity of priority areas for Greater Sage-Grouse: Implications for long-term conservation from graph theory"},"id":1}],"supersededBy":{"id":70179852,"text":"70179852 - 2017 - Range-wide connectivity of priority areas for Greater Sage-Grouse: Implications for long-term conservation from graph theory","indexId":"70179852","publicationYear":"2017","noYear":false,"title":"Range-wide connectivity of priority areas for Greater Sage-Grouse: Implications for long-term conservation from graph theory"},"lastModifiedDate":"2017-11-22T15:50:32","indexId":"ofr20151158","displayToPublicDate":"2015-09-08T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1158","title":"Range-wide network of priority areas for greater sage-grouse - a design for conserving connected distributions or isolating individual zoos?","docAbstract":"The network of areas delineated in 11 Western States for prioritizing management of greater sage-grouse (Centrocercus urophasianus) represents a grand experiment in conservation biology and reserve design. We used centrality metrics from social network theory to gain insights into how this priority area network might function. The network was highly centralized. Twenty of 188 priority areas accounted for 80 percent of the total centrality scores. These priority areas, characterized by large size and a central location in the range-wide distribution, are strongholds for greater sage-grouse populations and also might function as sources. Mid-ranking priority areas may serve as stepping stones because of their location between large central and smaller peripheral priority areas. The current network design and conservation strategy has risks. The contribution of almost one-half (n = 93) of the priority areas combined for less than 1 percent of the cumulative centrality scores for the network. These priority areas individually are likely too small to support viable sage-grouse populations within their boundary. Without habitat corridors to connect small priority areas either to larger priority areas or as a clustered group within the network, their isolation could lead to loss of sage-grouse within these regions of the network.
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777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
The invasive Silver Carp (Hypophthalmichthys molitrix) dominate large regions of the Mississippi River drainage and continue to expand their range northward threatening the Laurentian Great Lakes. This study found that complex broadband sound (0–10 kHz) is effective in altering the behavior of Silver Carp with implications for deterrent barriers or potential control measures (e.g., herding fish into nets). The phonotaxic response of Silver Carp was investigated using controlled experiments in outdoor concrete ponds (10 × 4.9 × 1.2 m). Pure tones (500–2000 Hz) and complex sound (underwater field recordings of outboard motors) were broadcast using underwater speakers. Silver Carp always reacted to the complex sounds by exhibiting negative phonotaxis to the sound source and by alternating speaker location, Silver Carp could be directed consistently, up to 37 consecutive times, to opposite ends of the large outdoor pond. However, fish habituated quickly to pure tones, reacting to only approximately 5 % of these presentations and never showed more than two consecutive responses. Previous studies have demonstrated the success of sound barriers in preventing Silver Carp movement using pure tones and this research suggests that a complex sound stimulus would be an even more effective deterrent.
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Mensinger, 2015, Acoustical deterrence of Silver Carp (Hypophthalmichthys molitrix): Biological Invasions, v. 17, no. 12, p. 3383-3392, https://doi.org/10.1007/s10530-015-0964-6.","productDescription":"10 p.","startPage":"3383","endPage":"3392","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061099","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":307944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"17","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-25","publicationStatus":"PW","scienceBaseUri":"55eff8a6e4b0dacf699e9fcf","contributors":{"authors":[{"text":"Brooke J. Vetter","contributorId":140352,"corporation":false,"usgs":false,"family":"Brooke J. 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Mensinger","contributorId":140354,"corporation":false,"usgs":false,"family":"Allen F. Mensinger","affiliations":[{"id":13467,"text":"Biology Department, University of Minnesota, Duluth","active":true,"usgs":false}],"preferred":false,"id":545327,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70154842,"text":"70154842 - 2015 - Potential direct and indirect effects of climate change on a shallow natural lake fish assemblage","interactions":[],"lastModifiedDate":"2015-10-23T14:45:22","indexId":"70154842","displayToPublicDate":"2015-09-07T15:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Potential direct and indirect effects of climate change on a shallow natural lake fish assemblage","docAbstract":"Much uncertainty exists around how fish communities in shallow lakes will respond to climate change. In this study, we modelled the effects of increased water temperatures on consumption and growth rates of two piscivores (northern pike [Esox lucius] and largemouth bass [Micropterus salmoides]) and examined relative effects of consumption by these predators on two prey species (bluegill [Lepomis macrochirus] and yellow perch [Perca flavescens]). Bioenergetics models were used to simulate the effects of climate change on growth and food consumption using predicted 2040 and 2060 temperatures in a shallow Nebraska Sandhill lake, USA. The patterns and magnitude of daily and cumulative consumption during the growing season (April–October) were generally similar between the two predators. However, growth of northern pike was always reduced (−3 to −45% change) compared to largemouth bass that experienced subtle changes (4 to −6% change) in weight by the end of the growing season. Assuming similar population size structure and numbers of predators in 2040–2060, future consumption of bluegill and yellow perch by northern pike and largemouth bass will likely increase (range: 3–24%), necessitating greater prey biomass to meet future energy demands. The timing of increased predator consumption will likely shift towards spring and fall (compared to summer), when prey species may not be available in the quantities required. Our findings suggest that increased water temperatures may affect species at the edge of their native range (i.e. northern pike) and a potential mismatch between predator and prey could exist.
","language":"English","publisher":"Munksgaard","publisherLocation":"Copenhagen","doi":"10.1111/eff.12248","usgsCitation":"Breeggemann, J.J., Kaemingk, M.A., DeBates, T., Paukert, C.P., Krause, J., Letvin, A.P., Stevens, T.M., Willis, D.W., and Chipps, S.R., 2015, Potential direct and indirect effects of climate change on a shallow natural lake fish assemblage: Ecology of Freshwater Fish, 13 p., https://doi.org/10.1111/eff.12248.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-045842","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":310609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","county":"Cherry","otherGeospatial":"Valentine National Wildlife Refuge","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-102.0829,42.9979],[-102.0007,42.9973],[-101.9652,42.9971],[-101.7528,42.9958],[-101.6775,42.9953],[-101.2277,42.9953],[-100.7509,42.9947],[-100.6721,42.9949],[-100.3938,42.996],[-100.1984,42.997],[-100.1985,42.8461],[-100.1984,42.782],[-100.184,42.7829],[-100.1837,42.4338],[-100.1675,42.4348],[-100.1667,42.0881],[-100.2675,42.0871],[-100.6156,42.0872],[-100.73,42.0885],[-100.8444,42.0896],[-100.9582,42.0897],[-100.9841,42.09],[-101.1016,42.0913],[-101.1926,42.0914],[-101.3094,42.0925],[-101.3323,42.0927],[-101.4097,42.0942],[-101.4251,42.0936],[-101.4492,42.0933],[-101.6861,42.0945],[-101.7733,42.0938],[-101.803,42.0934],[-101.8902,42.0962],[-101.9199,42.0958],[-102.0065,42.0958],[-102.0393,42.0962],[-102.0387,42.1826],[-102.0402,42.4448],[-102.0669,42.4448],[-102.0664,42.5302],[-102.0665,42.7867],[-102.0846,42.7864],[-102.0836,42.9606],[-102.0829,42.9979]]]},\"properties\":{\"name\":\"Cherry\",\"state\":\"NE\"}}]}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-07","publicationStatus":"PW","scienceBaseUri":"562b5a31e4b00162522207dc","contributors":{"authors":[{"text":"Breeggemann, Jason J.","contributorId":149395,"corporation":false,"usgs":false,"family":"Breeggemann","given":"Jason","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":578288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaemingk, Mark A.","contributorId":40510,"corporation":false,"usgs":true,"family":"Kaemingk","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":578289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBates, T.J.","contributorId":57250,"corporation":false,"usgs":true,"family":"DeBates","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":578290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paukert, Craig P. 0000-0002-9369-8545 cpaukert@usgs.gov","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":879,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","email":"cpaukert@usgs.gov","middleInitial":"P.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krause, J.","contributorId":56874,"corporation":false,"usgs":true,"family":"Krause","given":"J.","email":"","affiliations":[],"preferred":false,"id":578291,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Letvin, Alexander P.","contributorId":149396,"corporation":false,"usgs":false,"family":"Letvin","given":"Alexander","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":578292,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stevens, Tanner M.","contributorId":149397,"corporation":false,"usgs":false,"family":"Stevens","given":"Tanner","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":578293,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Willis, David W.","contributorId":55313,"corporation":false,"usgs":true,"family":"Willis","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":578294,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":578295,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70147396,"text":"ofr20151080 - 2015 - Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States","interactions":[],"lastModifiedDate":"2018-04-03T11:36:56","indexId":"ofr20151080","displayToPublicDate":"2015-09-04T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1080","title":"Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States","docAbstract":"Chloride exists as a major ion in most natural waters, but many anthropogenic sources are increasing concentrations of chloride in many receiving waters. Although natural concentrations in continental waters can be as high as 200,000 milligrams per liter, chloride concentrations that are suitable for freshwater ecology, human consumption, and agricultural and industrial water uses commonly are on the order of 10 to 1,000 milligrams per liter. “Road salt” frequently is identified as the sole source of anthropogenic chloride, but only about 30 percent of the salt consumed and released to the environment is used for deicing. Furthermore, several studies in Southern States where the use of deicing salt is minimal also show anthropogenic chloride in rising concentrations and in strong correlation to imperviousness and road density. This is because imperviousness and road density also are strongly correlated to population density. The term “road salt” is a misnomer because deicers applied to parking lots, sidewalks, and driveways can be a substantial source of chloride in some catchments because these land covers are comparable to roadways as a percentage of the total impervious area and commonly receive higher salt application rates than some roadways. Other sources of anthropogenic chloride include wastewater, dust control on unpaved roads, fertilizer, animal waste, irrigation, aquaculture, energy production wastes, and landfill leachates. The assumption that rising chloride concentrations in surface water or groundwater is indicative of contamination by deicing chemicals rather than one or more other potential sources may preclude the identification of toxic, carcinogenic, mutagenic, or endocrine-disrupting contaminants that are associated with many sources of elevated chloride concentrations. Once the sources of anthropogenic chloride in an area of interest have been identified and measured, water and solute budgets can be estimated to guide decisionmakers to identify and apply potential mitigation measures that can reduce the problem.
\nScientists, engineers, regulators, and decisionmakers need information about potential sources of chloride, water and solute budgets, and methods for collecting water-quality data to help identify potential sources. This information is needed to evaluate potential sources of chloride in areas where chloride may have adverse ecological effects or may degrade water supplies used for drinking water, agriculture, or industry. Knowledge of potential sources will help decisionmakers identify the best mitigation measures to reduce the total background chloride load, thereby reducing the potential for water-quality exceedances that occur because of superposition on rising background concentrations. Also, knowledge of potential sources may help decisionmakers identify the potential for the presence of contaminants that have toxic, carcinogenic, mutagenic, or endocrine-disrupting effects at concentrations that are lower by orders of magnitude than the chloride concentrations in the source water. This report is a comprehensive synthesis of relevant information, but it is not the result of an exhaustive search for literature on each topic. The potential adverse effects of chloride on infrastructure and the environment are not discussed in this report because these issues have been extensively documented elsewhere.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151080","collaboration":"Prepared in cooperation with the U.S. Department of Transportation Federal Highway Administration Office of Project Development and Environmental Review","usgsCitation":"Granato, G.E., DeSimone, L.A., Barbaro, J.R., and Jeznach, L.C., 2015, Methods for evaluating potential sources of chloride in surface waters and groundwaters of the conterminous United States: U.S. Geological Survey Open-File Report 2015–1080, 89 p., https://dx.doi.org/10.3133/ofr20151080.","productDescription":"ix, 89 p.","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063136","costCenters":[{"id":376,"text":"Massachusetts Water Science 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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Mount St. Helens began erupting in late 2004 following an 18 year quiescence. Swarms of repeating earthquakes accompanied the extrusion of a mostly solid dacite dome over the next 4 years. In some cases the waveforms from these earthquakes evolved slowly, likely reflecting changes in the properties of the volcano that affect seismic wave propagation. We use coda-wave interferometry to quantify small changes in seismic velocity structure (usually <1%) between two similar earthquakes and employed waveforms from several hundred families of repeating earthquakes together to create a continuous function of velocity change observed at permanent stations operated within 20 km of the volcano. The high rate of earthquakes allowed tracking of velocity changes on an hourly time scale. Changes in velocity were largest near the newly extruding dome and likely related to shallow deformation as magma first worked its way to the surface. We found strong correlation between velocity changes and the inverse of real-time seismic amplitude measurements during the first 3 weeks of activity, suggesting that fluctuations of pressure in the shallow subsurface may have driven both seismicity and velocity changes. Velocity changes during the remainder of the eruption likely result from a complex interplay of multiple effects and are not well explained by any single factor alone, highlighting the need for complementary geophysical data when interpreting velocity changes.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2015JB012101","usgsCitation":"Hotovec-Ellis, A., Vidale, J., Gomberg, J.S., Thelen, W.A., and Moran, S.C., 2015, Changes in seismic velocity during the first 14 months of the 2004–2008 eruption of Mount St. Helens, Washington: Journal of Geophysical Research B: Solid Earth, v. 120, no. 9, p. 6226-6240, https://doi.org/10.1002/2015JB012101.","productDescription":"15 p.","startPage":"6226","endPage":"6240","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067267","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":309373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-04","publicationStatus":"PW","scienceBaseUri":"560d07ade4b058f706e542fb","contributors":{"authors":[{"text":"Hotovec-Ellis, A.J.","contributorId":147946,"corporation":false,"usgs":false,"family":"Hotovec-Ellis","given":"A.J.","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":573396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vidale, J.E.","contributorId":55849,"corporation":false,"usgs":true,"family":"Vidale","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":573397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gomberg, Joan S. 0000-0002-0134-2606 gomberg@usgs.gov","orcid":"https://orcid.org/0000-0002-0134-2606","contributorId":1269,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","email":"gomberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":573395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thelen, Weston A. 0000-0003-2534-5577 wthelen@usgs.gov","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":4126,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","email":"wthelen@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":573398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":573399,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156555,"text":"sir20155117 - 2015 - A conceptual framework and monitoring strategy for movement of saltwater in the coastal plain aquifer system of Virginia","interactions":[],"lastModifiedDate":"2015-09-04T11:18:05","indexId":"sir20155117","displayToPublicDate":"2015-09-04T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5117","title":"A conceptual framework and monitoring strategy for movement of saltwater in the coastal plain aquifer system of Virginia","docAbstract":"A conceptual framework synthesizes previous studies to provide an understanding of conditions, processes, and relations of saltwater to groundwater withdrawal in the Virginia Coastal Plain aquifer system. A strategy for monitoring saltwater movement is based on spatial relations between the saltwater-transition zone and 612 groundwater-production wells that were regulated during 2013 by the Virginia Department of Environmental Quality. The vertical position and lateral distance and direction of the bottom of each production well’s screened interval was calculated relative to previously published groundwater chloride iso-concentration surfaces. Spatial analysis identified 81 production wells completed in the Yorktown-Eastover and Potomac aquifers that are positioned in closest proximity to the 250-milligrams-per-liter chloride surface, and from which chloride concentrations are most likely to increase above the U.S. Environmental Protection Agency’s 250-milligrams-per-liter secondary maximum-contaminant level. Observation wells are specified to distinguish vertical upconing from lateral intrusion among individual production wells. To monitor upconing, an observation well is to be collocated with each production well and completed at about the altitude of the 250-milligrams-per-liter chloride iso-concentration surface. To monitor lateral intrusion, a potential location of an observation well is projected from the bottom of each production well’s screened interval, in the lateral direction to the underlying chloride surface to a distance of 1 mile.
\nMonitoring potential withdrawal-induced movement of saltwater in the Virginia Coastal Plain aquifer system is needed to detect increases in chloride concentration before groundwater-production wells become contaminated. An investigation was undertaken during 2014 by the U.S. Geological Survey in cooperation with the Virginia Department of Environmental Quality, to provide a sound scientific understanding of saltwater movement and guidance to implement a monitoring program. Previous studies have theorized that the saltwater originated primarily from seawater repeatedly emplaced within aquifer sediments during the past about 65 million years. Subsequent flushing by fresh groundwater has been impeded across sediments filling the Chesapeake Bay impact crater. The resulting saltwater-transition zone has been mapped to exhibit a warped and steeply mounded dome shape about centered on the impact crater, and flanked by a nearly level and shallow plateau shape to the southeast. Groundwater chloride concentrations have historically fluctuated during periods of weeks to months, probably as a result of localized vertical upconing beneath individual production wells. Lateral intrusion takes several decades or more to horizontally displace groundwater across distances of about 1 mile toward production wells. Upconing is relatively immediate, but reversible, whereas lateral intrusion under the regionally landward hydraulic gradient may slowly, but permanently reposition the saltwater-transition zone. Upconing coupled with lateral intrusion is theorized to produce composite chloride-concentration trends that vary widely over time in response to changing water demands, and evolve dynamically from hydraulic interactions among multiple neighboring production wells.
\nSome aspects of observation-well construction and sampling are of particular importance to monitoring saltwater movement in the Virginia Coastal Plain aquifer system. Observation wells should feature screened intervals generally of no more than 10 feet that isolate distinct parts of the aquifer, and be thoroughly developed for removal of drilling fluid and introduced water. Presample purging should fully displace stratified saltwater in the well casing upward to the pump. Stable flow should be maintained as field parameters are measured and sample containers are filled with filtered water isolated from the atmosphere and unaffected by surface temperature. Groundwater samples from both upconing and lateral-intrusion observation wells should initially be collected four times per year when wells are newly established, but can be more optimally timed with withdrawal once responses in chloride concentrations can be reliably predicted. Concentrations of major ions (1) determine the dominant chemical composition of groundwater at each well, (2) establish the relative position of the well within the saltwater-transition zone, and (3) provide data quality control by calculation of sample charge balance. For these reasons, samples initially collected for the first year from newly established observation wells should be analyzed for calcium, magnesium, sodium, and potassium cations and chloride, bicarbonate, carbonate, sulfate, fluoride, and bromide anions. Inflection-point titration for alkalinity should be completed in the field. Analysis of chloride and field parameters may be adequate on a long-term basis once the dominant chemical composition at each well is established. Specific conductance may also provide a surrogate for chloride concentration depending on regulatory policy.
\nThe saltwater-movement monitoring strategy is limited and constrained. Relative monitoring needs among groundwater-production wells, and construction of observation wells, depend on the accuracy of previously mapped groundwater chloride iso-concentration surfaces. Production wells in similar proximity to saltwater can differ in aquifer hydraulic conductivity, rates of withdrawal, and screened-interval lengths. Only production wells making withdrawals reported to the Virginia Department of Environmental Quality have been accounted for; undocumented production wells can result in spurious changes in groundwater chloride concentration. Upconing observation wells should be as close as possible to corresponding production wells, so long as production wells are not damaged by borehole deviation. Projected locations of some lateral-intrusion observation wells may be precluded and require adjustment. Depths of upconing and lateral-intrusion observation wells may also require adjustment to be within the same aquifer as their corresponding production wells. Existing unused wells can be adapted as observation wells if differences from specified locations and construction are kept to a minimum and are accounted for. Where multiple production wells are in proximity, a modified monitoring approach may be needed to determine their net effect on changes in chloride concentration, and may require more than one lateral-intrusion observation well depending on the vertical positions of production-well screened intervals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155117","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., 2015, A conceptual framework and monitoring strategy for movement of saltwater in the Coastal Plain aquifer system of Virginia: U.S. Geological Survey Scientific Investigations Report 2015–5117, 30 p., 1 pl., https://dx.doi.org/10.3133/sir20155117.","productDescription":"Report: vi, 30 p.; Plate: 24 x 35 inches; Table","numberOfPages":"40","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-062904","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":307898,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5117/coverthb.jpg"},{"id":307899,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5117/sir20155117.pdf","text":"Report","size":"1.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5117"},{"id":307900,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5117/sir20155117_attachment1.xlsx","text":"Attachment 1","size":"114 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5117","linkHelpText":"Groundwater-production Wells, Vertical Positions and Lateral Distances and Directions Relative to Chloride Iso-concentration Surfaces, and Projected Locations of Lateral-intrusion Observation Wells"},{"id":307901,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5117/sir20155117_plate1.pdf","text":"Plate 1","size":"399 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5117","linkHelpText":"Locations of Groundwater-Production Wells, Projected Locations of Lateral Intrusion Observation Wells, and the Configuration of the 250-Milligrams-Per-Liter Chloride Iso-Concentration Surface"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.24462890625,\n 36.51405119943165\n ],\n [\n -78.24462890625,\n 38.436379603\n ],\n [\n -75.3387451171875,\n 38.436379603\n ],\n [\n -75.3387451171875,\n 36.51405119943165\n ],\n [\n -78.24462890625,\n 36.51405119943165\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
(804) 261-2600
Or visit the Virginia Water Science Center Web site:
http://va.water.usgs.gov/
Arid shrublands are stressful environments, typified by alkaline soils low in organic matter, with biologically-limiting extremes in water availability, temperature, and UV radiation. The widely-spaced plants and interspace biological soil crusts in these regions provide soil nutrients in a localized fashion, creating a mosaic pattern of plant- or crust-associated microhabitats with distinct nutrient composition. With sporadic and limited rainfall, nutrients are primarily retained in the shallow surface soil, patterning biological activity. We examined soil bacterial and fungal community responses to simulated nitrogen (N) deposition in an arid Larrea tridentata-Ambrosia dumosa field experiment in southern Nevada, USA, using high-throughput sequencing of ribosomal RNA genes. To examine potential interactions among the N application, microhabitat and soil depth, we sampled soils associated with shrub canopies and interspace biological crusts at two soil depths (0–0.5 or 0–10 cm) across the N-amendment gradient (0, 7, and 15 kg ha−1 yr−1). We hypothesized that localized compositional differences in soil microbiota would constrain the impacts of N addition to a microhabitat distribution that would reflect highly localized geochemical conditions and microbial community composition. The richness and community composition of both bacterial and fungal communities differed significantly by microhabitat and with soil depth in each microhabitat. Only bacterial communities exhibited significant responses to the N addition. Community composition correlated with microhabitat and depth differences in soil geochemical features. Given the distinct roles of soil bacteria and fungi in major nutrient cycles, the resilience of fungi and sensitivity of bacteria to N amendments suggests that increased N input predicted for many arid ecosystems could shift nutrient cycling toward pathways driven primarily by fungal communities.
The Colorado River and its tributaries supply water to more than 35 million people in the United States and 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about 12 billion kilowatt hours of hydroelectric power annually. The Upper Colorado River Basin, encompassing more than 110,000 square miles (mi2), contains the headwaters of the Colorado River (also known as the River) and is an important source of snowmelt runoff to the River. Groundwater discharge also is an important source of water in the River and its tributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin. Planning for the sustainable management of the Colorado River in future climates requires an understanding of the Upper Colorado River Basin groundwater system. This report documents input datasets for a Soil-Water Balance groundwater recharge model that was developed for the Upper Colorado River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151160","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the USGS Groundwater Resources Program","usgsCitation":"Tillman, F., 2015, Documentation of input datasets for the soil-water balance groundwater recharge model of the Upper Colorado River Basin: U.S. Geological Survey Open-File Report 2015-1160, v, 17 p., https://doi.org/10.3133/ofr20151160.","productDescription":"v, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066684","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":307918,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1160/coverthb.jpg"},{"id":307919,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1160/ofr20151160.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1160 PDF"},{"id":316699,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://water.usgs.gov/lookup/getspatial?ofr_2015_1160_soil-water_balance"}],"country":"Mexico, United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.69937133789062,\n 36.730079507078415\n ],\n [\n -111.68083190917969,\n 36.730079507078415\n ],\n [\n -111.64581298828125,\n 36.72677751526221\n ],\n [\n -111.4068603515625,\n 36.67723060234619\n ],\n [\n -111.181640625,\n 36.54936246839778\n ],\n [\n -110.45654296875,\n 36.46105407505434\n ],\n [\n -109.8687744140625,\n 35.991340960635405\n ],\n [\n -109.5062255859375,\n 35.67068501330236\n ],\n [\n -109.21508789062499,\n 35.48751102385376\n ],\n [\n -108.907470703125,\n 35.34425514918409\n ],\n [\n -107.5286865234375,\n 35.290468565908775\n ],\n [\n -107.2760009765625,\n 35.28150065789119\n ],\n [\n -107.215576171875,\n 35.31736632923788\n ],\n [\n -107.13317871093749,\n 35.460669951495305\n ],\n [\n -106.9793701171875,\n 35.62604706595698\n ],\n [\n -106.94091796875,\n 35.817813158696616\n ],\n [\n -106.875,\n 36.26199220445664\n ],\n [\n -106.842041015625,\n 36.67723060234619\n ],\n [\n -106.864013671875,\n 37.02886944696474\n ],\n [\n -107.0068359375,\n 37.21283151445594\n ],\n [\n -107.33642578124999,\n 37.37015718405753\n ],\n [\n -107.545166015625,\n 37.55328764595765\n ],\n [\n -107.666015625,\n 37.74465712069939\n ],\n [\n -107.42431640625,\n 37.84883250647402\n ],\n [\n -107.07275390625,\n 37.90953361677018\n ],\n [\n -106.6552734375,\n 38.004819966413194\n ],\n [\n -106.666259765625,\n 38.33303882235456\n ],\n [\n -106.69921875,\n 38.685509760012\n ],\n [\n -106.875,\n 39.13006024213511\n ],\n [\n -106.435546875,\n 39.40224434029275\n ],\n [\n -105.9521484375,\n 39.740986355883564\n ],\n [\n -105.908203125,\n 40.34654412118006\n ],\n [\n -105.99609375,\n 40.613952441166596\n ],\n [\n -106.435546875,\n 40.74725696280421\n ],\n [\n -106.69921875,\n 41.64007838467894\n ],\n [\n -107.57812499999999,\n 42.65012181368025\n ],\n [\n -108.10546875,\n 42.84375132629023\n ],\n [\n -108.8525390625,\n 43.13306116240612\n ],\n [\n -109.423828125,\n 43.197167282501276\n ],\n [\n -109.77539062499999,\n 43.42100882994726\n ],\n [\n -109.9072265625,\n 43.67581809328341\n ],\n [\n -110.3466796875,\n 43.83452678223682\n ],\n [\n -110.61035156249999,\n 43.67581809328341\n ],\n [\n -110.74218749999999,\n 43.13306116240612\n ],\n [\n -110.8740234375,\n 42.19596877629178\n ],\n [\n -111.0498046875,\n 41.44272637767212\n ],\n [\n -111.0498046875,\n 41.19518982948959\n ],\n [\n -111.181640625,\n 41.04621681452063\n ],\n [\n -111.37939453125,\n 40.94671366508002\n ],\n [\n -111.533203125,\n 40.613952441166596\n ],\n [\n -111.73095703125,\n 40.245991504199026\n ],\n [\n -111.884765625,\n 39.8928799002948\n ],\n [\n -111.97265625,\n 39.33429742980725\n ],\n [\n -112.2802734375,\n 39.11301365149975\n ],\n [\n -112.43408203124999,\n 38.856820134743636\n ],\n [\n -112.60986328125,\n 38.59970036588819\n ],\n [\n -112.60986328125,\n 38.376115424036016\n ],\n [\n -112.67578124999999,\n 38.22091976683121\n ],\n [\n -112.8955078125,\n 37.87485339352928\n ],\n [\n -113.02734374999999,\n 37.579412513438385\n ],\n [\n -113.02734374999999,\n 37.26530995561875\n ],\n [\n -112.9833984375,\n 37.00255267215955\n ],\n [\n -112.67578124999999,\n 36.756490329505155\n ],\n [\n -112.34619140625,\n 36.5978891330702\n ],\n [\n -111.97265625,\n 36.56260003738548\n ],\n [\n -111.69937133789062,\n 36.730079507078415\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean undiscovered resources of 214 million barrels of oil, 329 billion cubic feet of associated/dissolved natural gas, and 14 million barrels of natural gas liquids in the informal Uteland Butte member of the Green River Formation, Uinta Basin, Utah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153052","collaboration":"Prepared in cooperation with the National and Global Petroleum Assessment","usgsCitation":"Johnson, R.C., Birdwell, J.E., Mercier, T.J., Brownfield, M.E., Charpentier, R.R., Klett, T.R., Leathers, H.M., Schenk, C.J., and Tennyson, M.E., 2015, Assessment of undiscovered oil and gas resources in the Uteland Butte Member of the Eocene Green River Formation, Uinta Basin, Utah: U.S. Geological Survey Fact Sheet 2015–3052, 2 p., https://dx.doi.org/10.3133/fs20153052.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-065844","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":438685,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VT1Q4H","text":"USGS data release","linkHelpText":"USGS National Assessment of Oil and Gas Project - Uteland Butte Assessment Units"},{"id":307707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3052/coverthb.jpg"},{"id":307708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3052/fs20153052.pdf","text":"Report","size":"1.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3052"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.80810546875,\n 41.590796851056005\n ],\n [\n -104.87548828125,\n 41.590796851056005\n ],\n [\n -104.78759765625,\n 37.43997405227057\n ],\n [\n -112.17041015625,\n 37.43997405227057\n ],\n [\n -112.25830078125,\n 41.16211393939692\n ],\n [\n -112.17041015625,\n 41.42625319507272\n ],\n [\n -110.80810546875,\n 41.590796851056005\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
The population of Striped Bass Morone saxatilis in Chesapeake Bay has increased significantly since the 1980s because of management efforts while the relative abundance of some key prey fish has declined since the 1970s. We examined the trophic interactions and prey consumption patterns of Striped Bass in Chesapeake Bay to determine how Striped Bass have responded to changing prey resources. Seasonal diet, growth, and thermal data were collected from 1955 to 1959, 1990 to 1992, and 1998 to 2001; these data were coupled with a bioenergetics model approach to characterize temporal patterns in prey consumption for Striped Bass. The estimates were compared across each period to build a historical prey consumption profile from 1955 to 2001. Prey consumption dynamics for Striped Bass have changed dramatically between 1955 and 2001. In general, Striped Bass in the early and late 1990s consumed less Atlantic Menhaden Brevoortia tyranus and more Bay Anchovy Anchoa mitchilli than during the 1950s. The largest differences in consumption were observed in the younger age-classes. During 1998–2001, age-1 and age-2 Striped Bass consumed, respectively, 15.5 and 11.9 times less Atlantic Menhaden than during the 1950sand 12.2 and 7.2 less than during 1990–1992. Bay Anchovy were almost absent in the diet of bass age 3 and older during the 1950s but were consumed by the age-3+ group during 1990–1992 and to a greater extent during 1998–2001. Age-3+ Striped Bass during 1998–2001, on average, consumed twice as much Bay Anchovy than during 1990–1992. Blue crab Callinectes sappidus were consumed only by age 2 in the 1950s and 1990–1992 and by ages 2 and older in 1998–2001. Age-2 bass consumed 8.8 more blue crab in 1990–1992 and 7.5 times more in 1998–2001 than during the 1950s. The patterns in the consumption of Atlantic Menhaden coincided with increased consumption of Bay Anchovy and blue crab, possibly as a result of the declines in Atlantic Menhaden relative abundance in Chesapeake Bay. The difference in consumption was also evident in the total energy consumed; age-1 and age-6 Striped Bass consumed 1.6 times more energy in 1955–1959 than during 1998–2001. Our research demonstrates how the elements of Striped Bass feeding, including diet composition, amount of food eaten, and consumption rates, are affected by prey resources.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2015.1045989","usgsCitation":"Overton, A.S., Griffin, J., Margraf, F.J., May, E.B., and Hartman, K.J., 2015, Chronicling long-term predator responses to a shifting forage base in Chesapeake Bay: an energetics approach: Transactions of the American Fisheries Society, v. 144, no. 5, p. 956-966, https://doi.org/10.1080/00028487.2015.1045989.","productDescription":"11 p.","startPage":"956","endPage":"966","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1955-01-01","temporalEnd":"2001-12-31","ipdsId":"IP-059482","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":307928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.992431640625,\n 36.910372213522535\n ],\n [\n -75.56396484375,\n 38.00049145082287\n ],\n [\n -75.8221435546875,\n 39.690280594818034\n ],\n [\n -76.7340087890625,\n 39.25352462727606\n ],\n [\n -77.0965576171875,\n 38.06539235133249\n ],\n [\n -77.0965576171875,\n 37.16907157713011\n ],\n [\n -76.5802001953125,\n 36.76969233214548\n ],\n [\n -75.992431640625,\n 36.910372213522535\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"144","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-12","publicationStatus":"PW","scienceBaseUri":"55e96120e4b0dacf699e7855","contributors":{"authors":[{"text":"Overton, Anthony S.","contributorId":147350,"corporation":false,"usgs":false,"family":"Overton","given":"Anthony","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":571416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffin, Jennifer C.","contributorId":147352,"corporation":false,"usgs":false,"family":"Griffin","given":"Jennifer C.","affiliations":[],"preferred":false,"id":571417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Margraf, F. Joseph jmargraf@usgs.gov","contributorId":257,"corporation":false,"usgs":true,"family":"Margraf","given":"F.","email":"jmargraf@usgs.gov","middleInitial":"Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":571039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"May, Eric B.","contributorId":147354,"corporation":false,"usgs":false,"family":"May","given":"Eric","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":571418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, Kyle J.","contributorId":6414,"corporation":false,"usgs":false,"family":"Hartman","given":"Kyle","email":"","middleInitial":"J.","affiliations":[{"id":16210,"text":"Division of Forestry and Natural Resources, West Virginia University","active":true,"usgs":false}],"preferred":false,"id":571419,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155208,"text":"ofr20151130 - 2015 - Geophysical investigation of the pressure field produced by water guns at a pond site in La Crosse, Wisconsin","interactions":[],"lastModifiedDate":"2015-09-03T13:57:53","indexId":"ofr20151130","displayToPublicDate":"2015-09-03T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1130","title":"Geophysical investigation of the pressure field produced by water guns at a pond site in La Crosse, Wisconsin","docAbstract":"Three different geophysical sensor types were used to characterize the underwater pressure waves generated by the underwater firing of a seismic water gun and their suitability for establishing a pressure barrier to potentially direct or prevent the movement of the Asian carps. The sensors used to collect the seismic information were blast rated hydrophones and underwater blast sensors. Specific location information for the water guns and the sensors was obtained using either laser rangefinders or differentially corrected global positioning systems (GPS).
\nTwo separate studies are discussed in this report. The two studies were completed during September 2012 and July 2013. Both of these studies took place in an earthen testing pond on the campus of Upper Midwest Environmental Sciences Center (UMESC) in La Crosse, Wisconsin.
\nPrevious studies had identified 5 pounds per square inch (lb/in2) as a target value for the successful operation of a water gun barrier. The September 2012 study evaluated the performance of 1-cubic-inch (in3) and 80-in3 water guns. Data from the 1-in3 gun showed that it produces a very planar wave with limited effect on the depths above and below its gun ports. The 1-in3 gun did not produce the 5-lb/in2
\ntarget pressure at a sufficient distance to be considered effective. The 80-in3 gun produced a bowl-shaped pressure field with the 5-lb/in2 target radius at the surface extending to 45 feet.
\nThe July 2013 study consisted of three scenarios: fish behavior, single gun assessment, and experimental barrier evaluation. The fish behavior scenario simulated the pond conditions from previous studies. Two 80-in3 water guns were fired in the south end of the testing pond. Pressures essentially doubled from the testing of the single 80-in3 water gun. The single gun assessment scenario sought to replicate the setup of the 80-in3 scenario in September 2012, but with additional sensors to better define the pressure field. The 5-lb/in2 target pressure field continued to show a radius ranging from 40 to 45 feet, dependent on the pressure of the input air. The final scenario, the experimental barrier evaluation, showed that a two-dimensional continuous plane of 5 lb/in2 can be created between two 80-in3 water guns to a separation of 99 feet and a depth of 6.5 feet with 1,500 lb/in2 of input air.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151130","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Adams, R.F., and Morrow, W.S., 2015, Geophysical investigation of the pressure field produced by water guns at a pond site in La Crosse, Wisconsin: U.S. Geological Survey Open-File Report 2015–1130, 24 p., 1 app., https://dx.doi.org/10.3133/ofr20151130.","productDescription":"iv, 56 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-09-01","temporalEnd":"2013-07-31","ipdsId":"IP-053140","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":307792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1130/coverthb.jpg"},{"id":307793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1130/ofr20151130.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1130"}],"country":"United States","state":"Wisconsin","city":"La Crosse","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.25677585601807,\n 43.8665583482127\n ],\n [\n -91.25677585601807,\n 43.86934288877363\n ],\n [\n -91.24935150146484,\n 43.86934288877363\n ],\n [\n -91.24935150146484,\n 43.8665583482127\n ],\n [\n -91.25677585601807,\n 43.8665583482127\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
405 N. Goodwin
Urbana, IL 61801
(217) 328-8747
http://il.water.usgs.gov/
Understanding seasonal distribution and movement patterns of animals that migrate long distances is an essential part of monitoring and conserving their populations. Compared to migratory birds and other more conspicuous migrants, we know very little about the movement patterns of many migratory bats. Hoary bats (Lasiurus cinereus), a cryptic, wide-ranging, long-distance migrant, comprise a substantial proportion of the tens to hundreds of thousands of bat fatalities estimated to occur each year at wind turbines in North America. We created seasonally-dynamic species distribution models (SDMs) from 2,753 museum occurrence records collected over five decades in North America to better understand the seasonal geographic distributions of hoary bats. We used 5 SDM approaches: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy and consolidated outputs to generate ensemble maps. These maps represent the first formal hypotheses for sex- and season-specific hoary bat distributions. Our results suggest that North American hoary bats winter in regions with relatively long growing seasons where temperatures are moderated by proximity to oceans, and then move to the continental interior for the summer. SDMs suggested that hoary bats are most broadly distributed in autumn—the season when they are most susceptible to mortality from wind turbines; this season contains the greatest overlap between potentially suitable habitat and wind energy facilities. Comparing wind-turbine fatality data to model outputs could test many predictions, such as ‘risk from turbines is highest in habitats between hoary bat summering and wintering grounds’. Although future field studies are needed to validate the SDMs, this study generated well-justified and testable hypotheses of hoary bat migration patterns and seasonal distribution.
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Determining the detailed movements of individual animals often requires them to carry tracking devices, but tracking broad-scale movement of small bats (< 30g) has been limited by transmitter technology and long-term attachment methods. This limitation inhibits our understanding of bat dispersal and migration, particularly in the context of emerging conservation issues like fatalities at wind turbines and diseases. 2. We tested a novel method of attaching lightweight global positioning system (GPS) tags and geolocating data loggers to small bats. We used monofilament, synthetic, absorbable sutures to secure GPS tags and data loggers to the skin of anesthetized big brown bats (Eptesicus fuscus) in Colorado and hoary bats (Lasiurus cinereus) in California. 3. GPS tags and data loggers were sutured to 17 bats in this study. Three tagged bats were recaptured seven months after initial deployment, with tags still attached; none of these bats showed ill effects from the tag. No severe injuries were apparent upon recapture of 6 additional bats that carried tags up to 26 days after attachment, however one of the bats exhibited skin chafing. 4. Use of absorbable sutures to affix small tracking devices seems to be a safe, effective method for studying movements of bats over multiple months, although additional testing is warranted. This new attachment method has the potential to quickly advance our understanding of small bats, particularly as more-sophisticated miniature tracking devices (e.g., satellite tags) become available.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1584","collaboration":"Prepared in cooperation with Wildlife Veterinary Consulting; U.S. Forest Service Pacific Southwest Research Station; Bat Conservation International","usgsCitation":"Castle, K.T., Weller, T.J., Cryan, P.M., Hein, C.D., and Schirmacher, M.R., 2015, Using sutures to attach miniature tracking tags to small bats for multimonth movement and behavioral studies: Ecology and Evolution, v. 5, no. 14, p. 2980-2989, https://doi.org/10.1002/ece3.1584.","productDescription":"10 p.","startPage":"2980","endPage":"2989","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2014-08-01","temporalEnd":"2015-05-31","ipdsId":"IP-066197","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471813,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1584","text":"Publisher Index Page"},{"id":307915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-04","publicationStatus":"PW","scienceBaseUri":"55e9612ae4b0dacf699e7863","contributors":{"authors":[{"text":"Castle, Kevin T.","contributorId":90616,"corporation":false,"usgs":true,"family":"Castle","given":"Kevin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":571315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weller, Theodore J.","contributorId":105961,"corporation":false,"usgs":false,"family":"Weller","given":"Theodore","email":"","middleInitial":"J.","affiliations":[{"id":13261,"text":"USDA Forest Service, Pacific Southwest Research Station, Davis, California","active":true,"usgs":false}],"preferred":false,"id":571316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":571314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hein, Cris D.","contributorId":73910,"corporation":false,"usgs":false,"family":"Hein","given":"Cris","email":"","middleInitial":"D.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":571317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schirmacher, Michael R.","contributorId":76635,"corporation":false,"usgs":false,"family":"Schirmacher","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":571318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70157006,"text":"70157006 - 2015 - Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?","interactions":[],"lastModifiedDate":"2015-09-03T13:09:46","indexId":"70157006","displayToPublicDate":"2015-09-03T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":629,"text":"Acta Chiropterologica","active":true,"publicationSubtype":{"id":10}},"title":"Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?","docAbstract":"Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.
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47914 252nd Street
Sioux Falls, SD 57198-0001
Food web productivity in lakes can be limited by dissolved organic carbon (DOC), which reduces fish production by limiting the abundance of their zoobenthic prey. We demonstrate that in a set of 10 small, north temperate lakes spanning a wide DOC gradient, these negative effects of high DOC concentrations on zoobenthos production are driven primarily by availability of warm, well-oxygenated habitat, rather than by light limitation of benthic primary production as previously proposed. There was no significant effect of benthic primary production on zoobenthos production after controlling for oxygen, even though stable isotope analysis indicated that zoobenthos do use this resource. Mean whole-lake zoobenthos production was lower in high-DOC lakes with reduced availability of oxygenated habitat, as was fish biomass. These insights improve understanding of lake food webs and inform management in the face of spatial variability and ongoing temporal change in lake DOC concentrations.
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