A pulse of water was released from Morelos Dam into the dry streambed of the Colorado River in its former delta on March 23, 2014. Although small in relation to delta floods of a century ago, this was the first flow to reach the sea in nearly two decades. The pulse flow was significant in that it resulted from an international agreement, Minute 319, which allowed Colorado River water to be used for environmental restoration. Here we present a historical perspective of channel change and the results of geomorphic and sediment transport monitoring during the pulse flow between Yuma, Arizona and San Luis Rio Colorado, Sonora. This reach is known as the Limitrophe, because the river channel is the legal border between the United States and Mexico. Peak discharge of the pulse flow was 120 m3/s at Morelos Dam, but decreased to 71 m3/s at the southern border because of infiltration losses to the dry streambed. In contrast, flood flows in the 1980s and 1990s peaked above 600 m3/s at the southern border, and high flows above 200 m3/s were common. The sustained high flows in the 1980s caused widening and reworking of the river channel downstream through the delta. In the Limitrophe, flooding in 1993 from the Gila River basin dissected the 1980s flood surfaces, and smaller floods in the late 1990s incised the modern “active” channel within these higher surfaces. Field observations show that most geomorphic change during the pulse flow was confined to this pre-pulse, active channel. Relatively little bank erosion was evident, particularly in upstream reaches where vegetation is most dense, but new sandbars formed in areas of flow expansion. Farther downstream, localized bed scour and deposition ranged from 10s of centimeters to more than a meter, and fluvial dunes aggraded the bed in several locations. Measurable suspended-sediment transport occurred throughout the Limitrophe. Sediment concentrations peaked during the rising limb, and suspended sand concentrations suggest deposition in the lower 7 km of the Limitrophe as the channel gradient decreases by an order of magnitude. The pulse flow was small compared to historic floods, and flood magnitudes greater than the 2014 pulse flow are therefore necessary to significantly rework stable geomorphic surfaces or induce channel widening.
","conferenceTitle":"SEDHYD 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Joint Federal Interagency Conference","usgsCitation":"Mueller, E.R., Schmidt, J.C., Topping, D.J., and Grams, P.E., 2015, Geomorphic change in the Limitrophe reach of the Colorado River in response to the 2014 delta pulse flow, United States and Mexico, SEDHYD 2015, Reno, NV, April 19-23, 2015, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061044","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":311634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":300912,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2015/openconf/modules/request.php?module=oc_program&action=summary.php&id=136"}],"country":"United States","state":"Arizona and California","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.65194702148438,\n 33.43258740206331\n ],\n [\n -114.59564208984374,\n 33.41539481578252\n ],\n [\n -114.68353271484375,\n 33.358061612778876\n ],\n [\n -114.6533203125,\n 33.22260546814777\n ],\n [\n -114.664306640625,\n 33.10419660287101\n ],\n [\n -114.46792602539062,\n 33.02363335727839\n ],\n [\n -114.42672729492188,\n 32.8830470298317\n ],\n [\n -114.48440551757811,\n 32.72721987021932\n ],\n [\n -114.7467041015625,\n 32.49586350791503\n ],\n [\n -114.81536865234374,\n 32.49586350791503\n ],\n [\n -114.79476928710938,\n 32.55491613824475\n ],\n [\n -114.80300903320314,\n 32.604675440554985\n ],\n [\n -114.79476928710938,\n 32.62087018318113\n ],\n [\n -114.72473144531251,\n 32.708733368521585\n ],\n [\n -114.70550537109374,\n 32.76302656020649\n ],\n [\n -114.51324462890625,\n 32.86343938914863\n ],\n [\n -114.5489501953125,\n 32.992539261996946\n ],\n [\n -114.73297119140625,\n 33.04550781490999\n ],\n [\n -114.73983764648439,\n 33.19617852296372\n ],\n [\n -114.75082397460936,\n 33.28232392051035\n ],\n [\n -114.75082397460936,\n 33.39131947587412\n ],\n [\n -114.73159790039062,\n 33.4302952539532\n ],\n [\n -114.67391967773436,\n 33.43831750748322\n ],\n [\n -114.65194702148438,\n 33.43258740206331\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5650524de4b0f162148c5d0c","contributors":{"authors":[{"text":"Mueller, Erich R. 0000-0001-8202-154X emueller@usgs.gov","orcid":"https://orcid.org/0000-0001-8202-154X","contributorId":4930,"corporation":false,"usgs":true,"family":"Mueller","given":"Erich","email":"emueller@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, John C. 0000-0002-2988-3869 jcschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-2988-3869","contributorId":1983,"corporation":false,"usgs":true,"family":"Schmidt","given":"John","email":"jcschmidt@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":140985,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547849,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139643,"text":"70139643 - 2015 - Suspended sediment transport trough a large fluvial-tidal channel network","interactions":[],"lastModifiedDate":"2019-11-12T17:37:36","indexId":"70139643","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Suspended sediment transport trough a large fluvial-tidal channel network","docAbstract":"The confluence of the Sacramento and San Joaquin Rivers, CA, forms a large network of interconnected channels, referred to as the Sacramento-San Joaquin Delta (the Delta). The Delta comprises the transition zone from the fluvial influences of the upstream rivers and tidal influences of San Francisco Bay downstream. Formerly an extensive tidal marsh, the hydrodynamics and geomorphology of Delta have been substantially modified by humans to support agriculture, navigation, and water supply. These modifications, including construction of new channels, diking and draining of tidal wetlands, dredging of navigation channels, and the operation of large pumping facilities for distribution of freshwater from the Delta to other parts of the state, have had a dramatic impact on the physical and ecological processes within the Delta. To better understand the current physical processes, and their linkages to ecological processes, the USGS maintains an extensive network of flow, sediment, and water quality gages in the Delta. Flow gaging is accomplished through use of the index-velocity method, and sediment monitoring uses turbidity as a surrogate for suspended-sediment concentration. Herein, we present analyses of the transport and dispersal of suspended sediment through the complex network of channels in the Delta. The primary source of sediment to the Delta is the Sacramento River, which delivers pulses of sediment primarily during winter and spring runoff events. Upon reaching the Delta, the sediment pulses move through the fluvial-tidal transition while also encountering numerous channel junctions as the Sacramento River branches into several distributary channels. The monitoring network allows us to track these pulses through the network and document the dominant transport pathways for suspended sediment. Further, the flow gaging allows for an assessment of the relative effects of advection (the fluvial signal) and dispersion (from the tides) on the sediment pulses as they move through the system. Herein, we present analyses of the “first flush” sediment pulse that occurred on the Sacramento River in December 2012, documenting the transport pathways as well as the effects of advection and dispersion on the sediment as it moved through the fluvial-tidal transition in the Delta. The analyses identified an important transport pathway through the interior of the Delta toward the large pumping facilities in the south Delta, which has important implications for native fish (because their movements are triggered by sediment/turbidity). The results also reveal the dramatic transition from fluvial-dominated transport (advection) to tidal-dominated transport (dispersion) as the sediment pulse approaches the estuary.
","conferenceTitle":"SEDHYD 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, Nevada","language":"English","usgsCitation":"Wright, S., and Morgan-King, T.L., 2015, Suspended sediment transport trough a large fluvial-tidal channel network, SEDHYD 2015, Reno, Nevada, April 19-23, 2015, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061555","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":311116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311115,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2015/openconf/modules/request.php?module=oc_program&action=summary.php&id=173"}],"country":"United States","state":"California","otherGeospatial":"Sacramento and San Joaquin Rivers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.94549560546875,\n 37.85316995894978\n ],\n [\n -121.47033691406249,\n 37.85316995894978\n ],\n [\n -121.47033691406249,\n 38.31149091244452\n ],\n [\n -121.94549560546875,\n 38.31149091244452\n ],\n [\n -121.94549560546875,\n 37.85316995894978\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5641d1c3e4b0831b7d62e74b","contributors":{"authors":[{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan-King, Tara L. 0000-0001-5632-5232 tamorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-5632-5232","contributorId":554,"corporation":false,"usgs":true,"family":"Morgan-King","given":"Tara","email":"tamorgan@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":539480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148359,"text":"70148359 - 2015 - Large river bed sediment characterization with low-cost sidecan sonar: Case studies from two setting in the Colorado (Arizona) and Penobscot (Maine) Rivers","interactions":[],"lastModifiedDate":"2018-04-23T13:11:33","indexId":"70148359","displayToPublicDate":"2015-04-23T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Large river bed sediment characterization with low-cost sidecan sonar: Case studies from two setting in the Colorado (Arizona) and Penobscot (Maine) Rivers","docAbstract":"Mapping subaqueous riverbed sediment grain size across channels and in nearshore areas typically used by fish and benthic invertebrates is difficult where and when the water flow is too swift or deep to wade yet impractical to access with large boats and instruments. Fluvial characteristics can further constrain sampling options, particularly where flow depth, water column turbidity or channel bottom structure prohibit use of aerial or bottom deployed imaging platforms.\nHere we discuss considerations in the use of sidescan sonar for riverbed sediment classification using examples from two large rivers, the Colorado River below Glen Canyon Dam in Arizona and the Upper Penobscot River in northern Maine (Figure 3). These case studies represent two fluvial systems that differ in recent history, physiography, sediment transport, and fluvial morphologies. The bed of the Colorado River in Glen Canyon National Recreation Area is predominantly graveled with extensive mats of submerged vegetation, and ephemeral surficial sand deposits exist below major tributaries. The bed is imaged periodically to assess the importance of substrate type and variability on rainbow trout spawning and juvenile rearing habitats and controls on aquatic invertebrate population dynamics. The Colorado River bed further below the dam in Grand Canyon National Park is highly dynamic. Tributary inputs of sand, gravel and boulders are spatially variable, and hydraulics of individual pools and eddies vary considerably in space and in response to varying dam operations, including experimental controlled flood releases to rebuild eroding sandbars. The bed encompasses the full range of noncohesive sediments, deposited in complicated spatial patterns. The mobile portion of the Penobscot River is generally more uniform, and consists predominantly of embedded gravels interspersed between bedrock outcrops with small isolated sand patches in sections with modest or low gradients. Patches of large cobbles, boulders and bedrock outcrops are present in the lower reaches of the river near locations of two recent dam removal projects but are of limited extent below the \"head of tide\" on the river. Aggregations of coarse materials often correspond to locations with abrupt bed elevation drops in the Upper Penobscot River.","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the 3rd joint federal interagency conference on sedimentation and hydrologic modeling","conferenceTitle":"5th federal interagency hydrologic modeling conference and the 10th federal interagency sedimentation conference ","conferenceDate":"April 19 – 23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Conference","usgsCitation":"Buscombe, D.D., Grams, P.E., Melis, T., and Smith, S., 2015, Large river bed sediment characterization with low-cost sidecan sonar: Case studies from two setting in the Colorado (Arizona) and Penobscot (Maine) Rivers, in Proceedings of the 3rd joint federal interagency conference on sedimentation and hydrologic modeling, Reno, NV, April 19 – 23, 2015, p. 1273-1277.","productDescription":"5 p. ","startPage":"1273","endPage":"1277","ipdsId":"IP-061222","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":332353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":300908,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2015/openconf/modules/request.php?module=oc_program&action=summary.php&id=77"}],"country":"United States","state":"Arizona, Maine","otherGeospatial":"Colorado River, Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.79638671875,\n 36.13787471840729\n ],\n [\n -113.57666015625,\n 35.97800618085566\n ],\n [\n -113.148193359375,\n 36.32397712011264\n ],\n [\n -112.7197265625,\n 36.465471886798134\n ],\n [\n -112.071533203125,\n 36.27085020723902\n ],\n [\n -111.807861328125,\n 36.712467243386264\n ],\n [\n -111.566162109375,\n 36.94989178681327\n ],\n [\n -111.4453125,\n 36.8708321556463\n ],\n [\n -111.719970703125,\n 36.049098959065645\n ],\n [\n -112.11547851562499,\n 35.96022296929667\n ],\n [\n -112.5,\n 36.1733569352216\n ],\n [\n -113.00537109375,\n 36.10237644873644\n ],\n [\n -113.2470703125,\n 35.62158189955968\n ],\n [\n -113.84033203125,\n 35.7286770448517\n ],\n [\n -113.983154296875,\n 36.09349937380574\n ],\n [\n -113.79638671875,\n 36.13787471840729\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.64257812499999,\n 45.58713413436411\n ],\n [\n -68.4283447265625,\n 45.50249699389715\n ],\n [\n -68.6480712890625,\n 45.37144349133922\n ],\n [\n -68.6920166015625,\n 45.18590859850545\n ],\n [\n -68.73046875,\n 45.01141864227728\n ],\n [\n -68.5711669921875,\n 44.98422783516651\n ],\n [\n -68.587646484375,\n 45.1936513315257\n ],\n [\n -68.45581054687499,\n 45.38301927899065\n ],\n [\n -68.2965087890625,\n 45.487094732298374\n ],\n [\n -68.302001953125,\n 45.56406391514301\n ],\n [\n -68.5162353515625,\n 45.644768217751924\n ],\n [\n -68.64257812499999,\n 45.58713413436411\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51c0e4b01224f329b5f5","contributors":{"authors":[{"text":"Buscombe, Daniel D. 0000-0001-6217-5584 dbuscombe@usgs.gov","orcid":"https://orcid.org/0000-0001-6217-5584","contributorId":5020,"corporation":false,"usgs":false,"family":"Buscombe","given":"Daniel","email":"dbuscombe@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grams, Paul E. 0000-0002-0873-0708 pgrams@usgs.gov","orcid":"https://orcid.org/0000-0002-0873-0708","contributorId":1830,"corporation":false,"usgs":true,"family":"Grams","given":"Paul","email":"pgrams@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547838,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melis, Theodore S. 0000-0003-0473-3968 tmelis@usgs.gov","orcid":"https://orcid.org/0000-0003-0473-3968","contributorId":1829,"corporation":false,"usgs":true,"family":"Melis","given":"Theodore S.","email":"tmelis@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":547839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Sean","contributorId":140986,"corporation":false,"usgs":false,"family":"Smith","given":"Sean","affiliations":[{"id":13637,"text":"School of earth and climate science, Uni. of Maine.","active":true,"usgs":false}],"preferred":false,"id":547840,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70135096,"text":"fs20143101 - 2015 - Rhenium: a rare metal critical in modern transportation","interactions":[],"lastModifiedDate":"2015-04-23T09:30:46","indexId":"fs20143101","displayToPublicDate":"2015-04-22T13:15:00","publicationYear":"2015","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":"2014-3101","title":"Rhenium: a rare metal critical in modern transportation","docAbstract":"Rhenium is a silvery-white, metallic element with an extremely high melting point (3,180 degrees Celsius) and a heat-stable crystalline structure, making it exceptionally resistant to heat and wear. Since the late 1980s, rhenium has been critical for superalloys used in turbine blades and in catalysts used to produce lead-free gasoline.
\nOne of the rarest elements, rhenium has an average abundance of less than one part per billion in the continental crust. Rhenium was the last stable, naturally occurring element discovered. Although its existence was predicted in 1871—Russian chemist Dmitri Mendeleev noted two vacant slots below manganese on the periodic table of elements—rhenium was not isolated until 1925, when German chemists Walker Noddack, Ida Tacke, and Otto Berg detected it in platinum ore.
\nRhenium rarely occurs as a native element or as its own sulfide mineral—rheniite (ReS2)—and often occurs as a substitute for molybdenum in molybdenite (MoS2). Most extracted rhenium is a byproduct of copper mining, with about 80 percent recovered from flue dust during the processing of molybdenite concentrates from porphyry copper deposits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143101","usgsCitation":"John, D.A., 2015, Rhenium: a rare metal critical in modern transportation: U.S. Geological Survey Fact Sheet 2014-3101, 2 p., https://doi.org/10.3133/fs20143101.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054779","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":299820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143101.jpg"},{"id":299816,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3101/"},{"id":299817,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3101/pdf/fs2014-3101.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5538b817e4b02c4db8d20ce6","contributors":{"authors":[{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":526813,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70145880,"text":"70145880 - 2015 - Climate trends and projections for Guam","interactions":[],"lastModifiedDate":"2017-06-09T15:01:06","indexId":"70145880","displayToPublicDate":"2015-04-22T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Climate trends and projections for Guam","docAbstract":"The island of Guam experiences a tropical marine climate, which is warm and humid moderated by seasonal tradewinds and a wet and dry season. The dry season lasts from January to June, while the rainy months are from July to December. Annual rainfall totals 84-116 inches (2133-2946 mm), of which two-thirds fall during the rainy season. Seasonal temperatures and precipitation are also affected by the El-Niño Southern Oscillation (ENSO) and tropical cyclones, which cause the largest deviations from average precipitation. An average of three tropical storms and one typhoon pass within 80 nautical miles of Guam each year, and both flooding and drought can impact freshwater supply management and associated infrastructure.
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trees","interactions":[],"lastModifiedDate":"2015-08-07T15:04:58","indexId":"70155368","displayToPublicDate":"2015-04-21T15:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3562,"text":"The Holocene","active":true,"publicationSubtype":{"id":10}},"title":"Alternative standardization approaches to improving streamflow reconstructions with ring-width indices of riparian trees","docAbstract":"Old, multi-aged populations of riparian trees provide an opportunity to improve reconstructions of streamflow. Here, ring widths of 394 plains cottonwood (Populus deltoids, ssp. monilifera) trees in the North Unit of Theodore Roosevelt National Park, North Dakota, are used to reconstruct streamflow along the Little Missouri River (LMR), North Dakota, US. Different versions of the cottonwood chronology are developed by (1) age-curve standardization (ACS), using age-stratified samples and a single estimated curve of ring width against estimated ring age, and (2) time-curve standardization (TCS), using a subset of longer ring-width series individually detrended with cubic smoothing splines of width against year. The cottonwood chronologies are combined with the first principal component of four upland conifer chronologies developed by conventional methods to investigate the possible value of riparian tree-ring chronologies for streamflow reconstruction of the LMR. Regression modeling indicates that the statistical signal for flow is stronger in the riparian cottonwood than in the upland chronologies. The flow signal from cottonwood complements rather than repeats the signal from upland conifers and is especially strong in young trees (e.g. 5–35 years). Reconstructions using a combination of cottonwoods and upland conifers are found to explain more than 50% of the variance of LMR flow over a 1935–1990 calibration period and to yield reconstruction of flow to 1658. The low-frequency component of reconstructed flow is sensitive to the choice of standardization method for the cottonwood. In contrast to the TCS version, the ACS reconstruction features persistent low flows in the 19th century. Results demonstrate the value to streamflow reconstruction of riparian cottonwood and suggest that more studies are needed to exploit the low-frequency streamflow signal in densely sampled age-stratified stands of riparian trees.
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Forest Service, National Stream and Aquatic Ecology Center","active":true,"usgs":false}],"preferred":false,"id":565574,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70146870,"text":"70146870 - 2015 - Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios","interactions":[],"lastModifiedDate":"2015-11-06T16:43:14","indexId":"70146870","displayToPublicDate":"2015-04-21T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios","docAbstract":"Human land use will increasingly contribute to habitat loss and water shortages in California, given future population projections and associated land-use demand. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km2) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within Mediterranean California ecoregions. Historical land use and land cover (LULC) change estimates were derived from the Farmland Mapping and Monitoring Program dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources. Five future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios A2 and B1 scenarios. Spatial land-use transition outputs across scenarios were combined to reveal scenario agreement and a land conversion threat index was developed to evaluate vulnerability of existing protected areas to proximal land conversion. By 2060, highest LULC conversion threats were projected to impact nearly 10,500 km2 of land area within 10 km of a protected area boundary and over 18,000 km2 of land area within essential habitat connectivity areas. Agricultural water use declined across all scenarios perpetuating historical drought-related land use from 2008-2010 and trends of annual cropland conversion into perennial woody crops. STSM is useful in analyzing land-use related impacts on water resource use as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, LULC change impacts will help to better inform resource management and mitigation strategies.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"AIMS Environmental Science","conferenceTitle":"2nd State-and-Transition Simulation Modeling Conference","conferenceDate":"September 16-18, 2014","conferenceLocation":"Fort Collins, Colorado","language":"English","publisher":"AIMS Press","doi":"10.3934/environsci.2015.2.282","usgsCitation":"Wilson, T., Sleeter, B.M., Sherba, J.T., and Cameron, D., 2015, Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios, in AIMS Environmental Science, v. 2, no. 2, Fort Collins, Colorado, September 16-18, 2014, p. 282-301, https://doi.org/10.3934/environsci.2015.2.282.","productDescription":"20 p.","startPage":"282","endPage":"301","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062790","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":472138,"rank":0,"type":{"id":40,"text":"Open 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PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563ddd42e4b0831b7d6271f0","contributors":{"authors":[{"text":"Wilson, Tamara 0000-0001-7399-7532 tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":545395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research 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Africa","interactions":[],"lastModifiedDate":"2016-12-15T12:13:59","indexId":"70159140","displayToPublicDate":"2015-04-20T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3459,"text":"Special Paper of the Geological Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Organic sedimentation in modern lacustrine systems: A case study from Lake Malawi, East Africa","docAbstract":"This study examines the relationship between depositional environment and sedimentary organic geochemistry in Lake Malawi, East Africa, and evaluates the relative significance of the various processes that control sedimentary organic matter (OM) in lacustrine systems. Total organic carbon (TOC) concentrations in recent sediments from Lake Malawi range from 0.01 to 8.80 wt% and average 2.83 wt% for surface sediments and 2.35 wt% for shallow core sediments. Hydrogen index (HI) values as determined by Rock-Eval pyrolysis range from 0 to 756 mg HC g−1 TOC and average 205 mg HC g−1 TOC for surface sediments and 228 mg HC g−1 TOC for shallow core samples. On average, variations in primary productivity throughout the lake may account for ~33% of the TOC content in Lake Malawi sediments (as much as 1 wt% TOC), and have little or no impact on sedimentary HI values. Similarly, ~33% to 66% of the variation in TOC content in Lake Malawi sediments appears to be controlled by anoxic preservation of OM (~1–2 wt% TOC), although some component of the water depth–TOC relationship may be due to physical sediment transport processes. Furthermore, anoxic preservation has a minimal effect on HI values in Lake Malawi sediments. Dilution of OM by inorganic sediment may account for ~16% of variability in TOC content in Lake Malawi sediments (~0.5 wt% TOC). The effect of inputs of terrestrial sediment on the organic character of surface sediments in these lakes is highly variable, and appears to be more closely related to the local depositional environment than the regional flux of terrestrial OM. Total nitrogen and TOC content in surface sediments collected throughout the lake are found to be highly correlated (r2 = 0.95), indicating a well-homogenized source of OM to the lake bottom. The recurring suspension and deposition of terrestrial sediment may account for significant amounts of OM deposited in offshore regions of the lake. This process effectively separates denser inorganic sediment from less dense OM and allows terrestrial OM to preferentially be transported farther offshore. The conclusion is that for the organic carbon content in these regions to be elevated a mixed terrestrial-lacustrine origin is required. The hydrodynamic separation of mineral and organic constituents is most pronounced in regions with shallow bathymetric gradients, consistent with previous findings from Lake Tanganyika.","language":"English","publisher":"Geological Society of America","doi":"10.1130/2015.2515(02)","usgsCitation":"Ellis, G.S., Katz, B.J., Scholz, C., and Peter K. 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Mature terrestrial sands are dominated by quartz, which is abundant in source lithologies on Earth and is physically and chemically stable under a wide range of conditions. Immature sands, such as those rich in feldspars or mafic minerals, are composed of grains that are easily physically weathered and highly susceptible to chemical weathering. On Mars, which is predominately mafic in composition, terrestrial standards of sediment maturity are not applicable. In addition, the martian climate today is cold, dry and sediments are likely to be heavily influenced by physical weathering rather than chemical weathering. Due to these large differences in weathering processes and composition, martian sediments require an alternate maturity index. Abrason tests have been conducted on a variety of mafic materials and results suggest that mature martian sediments may be composed of well sorted, well rounded, spherical basalt grains. In addition, any volcanic glass present is likely to persist in a mechanical weathering environment while chemically altered products are likely to be winnowed away. A modified sediment maturity index is proposed that can be used in future studies to constrain sediment source, paleoclimate, mechanisms for sediment production, and surface evolution. This maturity index may also provide details about erosional and sediment transport systems and preservation processes of layered deposits.
","language":"English","publisher":"American Astronomical Society","publisherLocation":"San Diego, CA","doi":"10.1016/j.icarus.2015.04.020","usgsCitation":"Cornwall, C., Bandfield, J.L., Titus, T.N., Schreiber, B.C., and Montgomery, D.R., 2015, Physical abrasion of mafic minerals and basalt grains: application to Martian aeolian deposits: Icarus, v. 256, p. 13-21, https://doi.org/10.1016/j.icarus.2015.04.020.","productDescription":"9 p.","startPage":"13","endPage":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059535","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":299789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"256","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55362343e4b0b22a15807aae","contributors":{"authors":[{"text":"Cornwall, Carin","contributorId":140355,"corporation":false,"usgs":false,"family":"Cornwall","given":"Carin","email":"","affiliations":[{"id":13468,"text":"1Department of Earth and Space Sciences, University of Washington, Seattle, Washington, USA.","active":true,"usgs":false}],"preferred":false,"id":545329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bandfield, Joshua L.","contributorId":140356,"corporation":false,"usgs":false,"family":"Bandfield","given":"Joshua","email":"","middleInitial":"L.","affiliations":[{"id":13469,"text":"Space Science Institute, Boulder, Colorado, USA","active":true,"usgs":false}],"preferred":false,"id":545330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":545328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schreiber, B. C.","contributorId":140357,"corporation":false,"usgs":false,"family":"Schreiber","given":"B.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":545332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Montgomery, D. R.","contributorId":41582,"corporation":false,"usgs":false,"family":"Montgomery","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":545331,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70146633,"text":"70146633 - 2015 - Application of the FluEgg model to predict transport of Asian carp eggs in the Saint Joseph River (Great Lakes tributary)","interactions":[],"lastModifiedDate":"2015-06-02T11:28:45","indexId":"70146633","displayToPublicDate":"2015-04-17T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Application of the FluEgg model to predict transport of Asian carp eggs in the Saint Joseph River (Great Lakes tributary)","docAbstract":"The Fluvial Egg Drift Simulator (FluEgg) is a three-dimensional Lagrangian model that simulates the movement and development of Asian carp eggs until hatching based on the physical characteristics of the flow field and the physical and biological characteristics of the eggs. This tool provides information concerning egg development and spawning habitat suitability including: egg plume location, egg vertical and travel time distribution, and egg-hatching risk. A case study of the simulation of Asian carp eggs in the Lower Saint Joseph River, a tributary of Lake Michigan, is presented. The river hydrodynamic input for FluEgg was generated in two ways — using hydroacoustic data and using HEC-RAS model data. The HEC-RAS model hydrodynamic input data were used to simulate 52 scenarios covering a broad range of flows and water temperatures with the eggs at risk of hatching ranging from 0 to 93% depending on river conditions. FluEgg simulations depict the highest percentage of eggs at risk of hatching occurs at the lowest discharge and at peak water temperatures. Analysis of these scenarios illustrates how the interactive relation among river length, hydrodynamics, and water temperature influence egg transport and hatching risk. An improved version of FluEgg, which more realistically simulates dispersion and egg development, is presented. Also presented is a graphical user interface that facilitates the use of FluEgg and provides a set of post-processing analysis tools to support management decision-making regarding the prevention and control of Asian carp reproduction in rivers with or without Asian carp populations.
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Ryan, Garcia Marcelo H.","journalName":"Journal of Great Lakes Research","publicationDate":"6/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Garcia, Tatiana 0000-0002-1979-7246 tgarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-1979-7246","contributorId":140327,"corporation":false,"usgs":true,"family":"Garcia","given":"Tatiana","email":"tgarcia@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":545164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Elizabeth A. emurphy@usgs.gov","contributorId":3250,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","email":"emurphy@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":545162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. 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Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0121655","usgsCitation":"Hunter, M., Oyler-McCance, S.J., Dorazio, R.M., Fike, J.A., Smith, B.J., Hunter, C.T., Reed, R., and Hart, K.M., 2015, Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive Burmese pythons: PLoS ONE, v. 10, no. 4, e0121655; 17 p., https://doi.org/10.1371/journal.pone.0121655.","productDescription":"e0121655; 17 p.","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055221","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0121655","text":"Publisher Index Page"},{"id":299753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 25.07316070640961\n ],\n [\n -81.84814453125,\n 26.509904531413927\n ],\n [\n -80.19195556640625,\n 26.509904531413927\n ],\n [\n -80.19195556640625,\n 25.07316070640961\n ],\n [\n -81.84814453125,\n 25.07316070640961\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-15","publicationStatus":"PW","scienceBaseUri":"553220a0e4b0b22a158063b3","contributors":{"authors":[{"text":"Hunter, Margaret E. 0000-0002-4760-9302 mhunter@usgs.gov","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":140314,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret E.","email":"mhunter@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":545130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":545131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":545132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fike, Jennifer A. fikej@usgs.gov","contributorId":4564,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":545133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Brian J. 0000-0002-0531-0492 bjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-0531-0492","contributorId":899,"corporation":false,"usgs":true,"family":"Smith","given":"Brian","email":"bjsmith@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":545134,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunter, Charles T.","contributorId":140315,"corporation":false,"usgs":false,"family":"Hunter","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":545135,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":140316,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":545136,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hart, Kristen M. 0000-0002-5257-7974 kristen_hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":1966,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","email":"kristen_hart@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":545137,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70146890,"text":"70146890 - 2015 - 11.12 – Tools and techniques: gravitational method","interactions":[],"lastModifiedDate":"2015-12-08T16:43:39","indexId":"70146890","displayToPublicDate":"2015-04-17T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"11.12 – Tools and techniques: gravitational method","docAbstract":"The gravitational method is used to investigate density variations within the subsurface at depths of several meters to tens of meters, as in depth-to-bedrock investigations, or at depths of several kilometers, as in sedimentary basin thickness investigations. This chapter covers fundamental relations, densities of Earth materials, instruments, field procedures, data reduction, filtering, forward modeling, inversion, and field examples. The focus is on near-surface investigations as distinct from the solid Earth studies found elsewhere in this treatise. The gravitational method is often used in conjunction with other geophysical methods, such as the magnetic method or the seismic method, which target similar physical properties at similar depths.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Treatise on Geophysics","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-444-53802-4.00197-4","usgsCitation":"Phillips, J., 2015, 11.12 – Tools and techniques: gravitational method, chap. of Treatise on Geophysics, v. 11, p. 393-418, https://doi.org/10.1016/B978-0-444-53802-4.00197-4.","productDescription":"26 p.","startPage":"393","endPage":"418","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044810","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":312048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","edition":"2nd","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56680d3fe4b06a3ea36c8e1e","contributors":{"authors":[{"text":"Phillips, Jeffrey 0000-0002-6459-2821 jeff@usgs.gov","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":127453,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffrey","email":"jeff@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":545488,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137525,"text":"ofr20141236 - 2015 - Accuracy testing of electric groundwater-level measurement tapes","interactions":[],"lastModifiedDate":"2015-04-16T16:14:45","indexId":"ofr20141236","displayToPublicDate":"2015-04-16T16:30:00","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":"2014-1236","title":"Accuracy testing of electric groundwater-level measurement tapes","docAbstract":"Electric tapes are used to measure groundwater levels and to verify the accuracy of pressure transducers installed in wells. Electric tapes are generally assumed to be accurate to ±0.01 foot (ft), but little information is available from the manufacturers and no accuracy studies have been conducted to confirm this value. This study measured the accuracy of six popular models of electric groundwater tapes.
\nThe tapes tested include models from Durham Geo, Geotech, Heron, In-Situ, Solinst, and Waterline that are commonly used by the U.S.Geological Survey (USGS). The accuracy tests compared the length of each electric tape to a calibrated-steel reference tape and measured each probe’s activation accuracy and displacement volume. The tape-length accuracy combined with the probe-activation accuracy gave the overall measurement accuracy of the tape.
\nThe accuracy tests demonstrated that none of the electric-tape models tested consistently met the suggested USGS accuracy of ±0.01 ft. The test data show that the tape models in the study should give a water-level measurement that is accurate to roughly ±0.05 ft per 100 ft without additional calibration. To meet USGS accuracy guidelines, the electric-tape models tested will need to be individually calibrated. Specific conductance also plays a part in tape accuracy. The probes will not work in water with specific conductance values near zero, and the accuracy of one probe was unreliable in very high conductivity water (10,000 microsiemens per centimeter).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141236","usgsCitation":"Jelinski, J., Clayton, C.S., and Fulford, J.M., 2015, Accuracy testing of electric groundwater-level measurement tapes: U.S. Geological Survey Open-File Report 2014-1236, vi, 27 p., https://doi.org/10.3133/ofr20141236.","productDescription":"vi, 27 p.","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052287","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":299747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141236.jpg"},{"id":299745,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1236/"},{"id":299746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1236/pdf/ofr2014-1236.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5530cf1ae4b0b22a15806131","contributors":{"authors":[{"text":"Jelinski, Jim","contributorId":138570,"corporation":false,"usgs":false,"family":"Jelinski","given":"Jim","email":"","affiliations":[{"id":12443,"text":"U.S. Geological Survey (retired)","active":true,"usgs":false}],"preferred":false,"id":537870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clayton, Christopher S. cclayton@usgs.gov","contributorId":5506,"corporation":false,"usgs":true,"family":"Clayton","given":"Christopher","email":"cclayton@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":537869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fulford, Janice M. jfulford@usgs.gov","contributorId":991,"corporation":false,"usgs":true,"family":"Fulford","given":"Janice","email":"jfulford@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":537871,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173441,"text":"70173441 - 2015 - Is there a single best estimator? selection of home range estimators using area- under- the-curve","interactions":[],"lastModifiedDate":"2016-06-14T15:56:43","indexId":"70173441","displayToPublicDate":"2015-04-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Is there a single best estimator? selection of home range estimators using area- under- the-curve","docAbstract":"Global positioning system (GPS) technology for monitoring home range and movements of wildlife has resulted in prohibitively large sample sizes of locations for traditional estimators of home range. We used area-under-the-curve to explore the fit of 8 estimators of home range to data collected with both GPS and concurrent very high frequency (VHF) technology on a terrestrial mammal, the Florida panther Puma concolor coryi, to evaluate recently developed and traditional estimators.
\nArea-under-the-curve was the highest for Florida panthers equipped with Global Positioning System (GPS) technology compared to VHF technology. For our study animal, estimators of home range that incorporated a temporal component to estimation performed better than traditional first- and second-generation estimators.
\nComparisons of fit of home range contours with locations collected would suggest that use of VHF technology is not as accurate as GPS technology to estimate size of home range for large mammals. Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used. Furthermore, estimators that incorporate a temporal component (third-generation estimators) appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used and in comparison to first- and second-generation estimators. We defined third-generation estimators of home range as any estimator that incorporates time, space, animal-specific parameters, and habitat. Such estimators would include movement-based kernel density, Brownian bridge movement models, and dynamic Brownian bridge movement models among others that have yet to be evaluated.
\nIn an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?
","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.12397","usgsCitation":"Rose, R., Byler, D., Eastman, J.R., Fleishman, E., Geller, G., Goetz, S., Guild, L., Hamilton, H., Hansen, M., Headley, R., Hewson, J., Horning, N., Kaplin, B.A., Laporte, N., Leidner, A., Leimgruber, P., Morisette, J.T., Musinsky, J., Pintea, L., Prados, A., Radeloff, V., Rowen, M., Saatchi, S., Schill, S., Tabor, K., Turner, W., Vodacek, A., Vogelmann, J., Wegmann, M., Wilkie, D., and Wilson, C., 2015, Ten ways remote sensing can contribute to conservation: Conservation Biology, v. 29, no. 2, p. 350-359, https://doi.org/10.1111/cobi.12397.","productDescription":"10 p.","startPage":"350","endPage":"359","ipdsId":"IP-055934","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341863,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-15","publicationStatus":"PW","scienceBaseUri":"592e84bfe4b092b266f10d60","contributors":{"authors":[{"text":"Rose, Robert A.","contributorId":192397,"corporation":false,"usgs":false,"family":"Rose","given":"Robert A.","affiliations":[],"preferred":false,"id":696436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byler, Dirck","contributorId":192398,"corporation":false,"usgs":false,"family":"Byler","given":"Dirck","email":"","affiliations":[],"preferred":false,"id":696437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eastman, J. Ron","contributorId":192399,"corporation":false,"usgs":false,"family":"Eastman","given":"J.","email":"","middleInitial":"Ron","affiliations":[],"preferred":false,"id":696438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleishman, Erica","contributorId":11863,"corporation":false,"usgs":true,"family":"Fleishman","given":"Erica","affiliations":[],"preferred":false,"id":696439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Geller, Gary","contributorId":81395,"corporation":false,"usgs":true,"family":"Geller","given":"Gary","affiliations":[],"preferred":false,"id":696440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goetz, Scott","contributorId":75259,"corporation":false,"usgs":true,"family":"Goetz","given":"Scott","affiliations":[],"preferred":false,"id":696441,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guild, Liane","contributorId":192400,"corporation":false,"usgs":false,"family":"Guild","given":"Liane","affiliations":[],"preferred":false,"id":696442,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hamilton, Healy","contributorId":192401,"corporation":false,"usgs":false,"family":"Hamilton","given":"Healy","email":"","affiliations":[],"preferred":false,"id":696443,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hansen, Matt","contributorId":61330,"corporation":false,"usgs":true,"family":"Hansen","given":"Matt","email":"","affiliations":[],"preferred":false,"id":696444,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Headley, Rachel rheadley@usgs.gov","contributorId":1744,"corporation":false,"usgs":true,"family":"Headley","given":"Rachel","email":"rheadley@usgs.gov","affiliations":[],"preferred":true,"id":696445,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hewson, Jennifer","contributorId":192402,"corporation":false,"usgs":false,"family":"Hewson","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":696446,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Horning, Ned","contributorId":192403,"corporation":false,"usgs":false,"family":"Horning","given":"Ned","email":"","affiliations":[],"preferred":false,"id":696447,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kaplin, Beth A.","contributorId":192404,"corporation":false,"usgs":false,"family":"Kaplin","given":"Beth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":696448,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Laporte, Nadine","contributorId":192405,"corporation":false,"usgs":false,"family":"Laporte","given":"Nadine","email":"","affiliations":[],"preferred":false,"id":696449,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Leidner, Allison K.","contributorId":92909,"corporation":false,"usgs":true,"family":"Leidner","given":"Allison K.","affiliations":[],"preferred":false,"id":696450,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Leimgruber, Peter","contributorId":192406,"corporation":false,"usgs":false,"family":"Leimgruber","given":"Peter","email":"","affiliations":[],"preferred":false,"id":696451,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":696452,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Musinsky, John","contributorId":192407,"corporation":false,"usgs":false,"family":"Musinsky","given":"John","email":"","affiliations":[],"preferred":false,"id":696453,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Pintea, Lilian","contributorId":192408,"corporation":false,"usgs":false,"family":"Pintea","given":"Lilian","email":"","affiliations":[],"preferred":false,"id":696454,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Prados, Ana","contributorId":192409,"corporation":false,"usgs":false,"family":"Prados","given":"Ana","email":"","affiliations":[],"preferred":false,"id":696455,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Radeloff, Volker C.","contributorId":76169,"corporation":false,"usgs":true,"family":"Radeloff","given":"Volker C.","affiliations":[],"preferred":false,"id":696456,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Rowen, Mary","contributorId":192410,"corporation":false,"usgs":false,"family":"Rowen","given":"Mary","email":"","affiliations":[],"preferred":false,"id":696457,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Saatchi, Sassan","contributorId":192411,"corporation":false,"usgs":false,"family":"Saatchi","given":"Sassan","email":"","affiliations":[],"preferred":false,"id":696458,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Schill, Steve","contributorId":26184,"corporation":false,"usgs":true,"family":"Schill","given":"Steve","email":"","affiliations":[],"preferred":false,"id":696459,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Tabor, Karyn","contributorId":192412,"corporation":false,"usgs":false,"family":"Tabor","given":"Karyn","email":"","affiliations":[],"preferred":false,"id":696460,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Turner, Woody","contributorId":149221,"corporation":false,"usgs":false,"family":"Turner","given":"Woody","email":"","affiliations":[{"id":17679,"text":"Earth Science Division, NASA Headquarters, Washington D.C.","active":true,"usgs":false}],"preferred":false,"id":696461,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Vodacek, Anthony","contributorId":192413,"corporation":false,"usgs":false,"family":"Vodacek","given":"Anthony","email":"","affiliations":[],"preferred":false,"id":696462,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":696463,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Wegmann, Martin","contributorId":177540,"corporation":false,"usgs":false,"family":"Wegmann","given":"Martin","email":"","affiliations":[],"preferred":false,"id":696464,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Wilkie, David","contributorId":192414,"corporation":false,"usgs":false,"family":"Wilkie","given":"David","email":"","affiliations":[],"preferred":false,"id":696465,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Wilson, Cara","contributorId":192415,"corporation":false,"usgs":false,"family":"Wilson","given":"Cara","email":"","affiliations":[],"preferred":false,"id":696466,"contributorType":{"id":1,"text":"Authors"},"rank":31}]}} ,{"id":70147593,"text":"70147593 - 2015 - Carbon exchange between the atmosphere and subtropical forested cypress and pine wetlands","interactions":[],"lastModifiedDate":"2016-07-18T22:50:40","indexId":"70147593","displayToPublicDate":"2015-04-16T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Carbon exchange between the atmosphere and subtropical forested cypress and pine wetlands","docAbstract":"Carbon dioxide exchange between the atmosphere and forested subtropical wetlands is largely unknown. Here we report a first step in characterizing this atmospheric–ecosystem carbon (C) exchange, for cypress strands and pine forests in the Greater Everglades of Florida as measured with eddy covariance methods at three locations (Cypress Swamp, Dwarf Cypress and Pine Upland) for 2 years. Links between water and C cycles are also examined at these three sites, as are methane emission measured only at the Dwarf Cypress site. Each forested wetland showed net C uptake from the atmosphere both monthly and annually, as indicated by the net ecosystem exchange (NEE) of carbon dioxide (CO2). For this study, NEE is the difference between photosynthesis and respiration, with negative values representing uptake from the atmosphere that is retained in the ecosystem or transported laterally via overland flow (unmeasured for this study). Atmospheric C uptake (NEE) was greatest at the Cypress Swampp (−900 to −1000 g C m2 yr−1), moderate at the Pine Upland (−650 to −700 g C m2 yr−1) and least at the Dwarf Cypress (−400 to −450 g C m2 yr−1). Changes in NEE were clearly a function of seasonality in solar insolation, air temperature and flooding, which suppressed heterotrophic soil respiration. We also note that changes in the satellite-derived enhanced vegetation index (EVI) served as a useful surrogate for changes in NEE at these forested wetland sites.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-12-2285-2015","usgsCitation":"Shoemaker, W., Anderson, F.E., Barr, J.G., Graham, S.L., and Botkin, D.B., 2015, Carbon exchange between the atmosphere and subtropical forested cypress and pine wetlands: Biogeosciences, v. 12, p. 2285-2300, https://doi.org/10.5194/bg-12-2285-2015.","productDescription":"16 p.","startPage":"2285","endPage":"2300","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056860","costCenters":[{"id":269,"text":"FLWSC-Ft. 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\nAims: The present study aims to detect behavioural effects of researcher handling and winter precipitation on a natural population of desert tortoises in the desert of Southwestern United States, over the period 1997 to 2014, through extensive assessments of capture events during multiple research studies, and capture–mark–recapture survivorship analysis.
\nMethods: Juvenile and adult desert tortoises were repeatedly handled with consistent methodology across 18 years during 10 study seasons. Using a generalised linear mixed-effects model, we assessed the effects of both research manipulation and abiotic conditions on probability of voiding. Additionally, we used a Cormack–Jolly–Seber model to assess the effects of winter precipitation and voiding on long-term apparent survivorship.
\nKey results: Of 1008 total capture events, voiding was recorded on 83 (8.2%) occasions in 42 different individuals. Our top models indicated that increases in handling time led to significantly higher probabilities of voiding for juveniles, females and males. Similarly, increases in precipitation resulted in significantly higher probabilities of voiding for juveniles and females, but not for males. Tortoise capture frequency was negatively correlated with voiding occurrence. Cormack–Jolly–Seber models demonstrated a weak effect of winter precipitation on survivorship, but a negligible effect for both voiding behaviour and sex.
\nConclusions: Handling-induced voiding by desert tortoises may occur during common research activities and years of above average winter precipitation. Increased likelihood of voiding in individuals with relatively low numbers of recaptures suggested that tortoises may have perceived researchers initially as predators, and therefore voided as a defensive strategy. Voiding does not appear to impact long-term survivorship in desert tortoises at this site.
\nImplications: This study has demonstrated that common handling practices on desert tortoise may cause voiding behaviour. These results suggest that in order to minimise undesirable behavioural responses in studied desert tortoise populations, defined procedures or protocols must be followed by the investigators to reduce contact period to the extent feasible.
","language":"English","publisher":"CSIRO Publishing","publisherLocation":"East Melbourne, Australia","doi":"10.1071/WR14196","usgsCitation":"Agha, M., Murphy, M.O., Lovich, J.E., Ennen, J.R., Oldham, C.R., Meyer-Wilkins, K., Bjurlin, C., Austin, M., Madrak, S.V., Loughran, C.L., Tennant, L.A., and Price, S.J., 2015, The effect of research activities and winter precipitation on voiding behaviour of Agassiz’s desert tortoises (Gopherus agassizii): Wildlife Research, v. 41, no. 8, p. 641-649, https://doi.org/10.1071/WR14196.","productDescription":"9 p.","startPage":"641","endPage":"649","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053514","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":319735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"41","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park 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jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":625902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ennen, Joshua R.","contributorId":83858,"corporation":false,"usgs":true,"family":"Ennen","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":625906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oldham, Christian R.","contributorId":168430,"corporation":false,"usgs":false,"family":"Oldham","given":"Christian","email":"","middleInitial":"R.","affiliations":[{"id":25289,"text":"Department of Forestry, University of Kentucky, Lexington, KY 40546, USA","active":true,"usgs":false}],"preferred":false,"id":625907,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meyer-Wilkins, Kathie","contributorId":8742,"corporation":false,"usgs":false,"family":"Meyer-Wilkins","given":"Kathie","affiliations":[],"preferred":false,"id":625905,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bjurlin, Curtis","contributorId":90183,"corporation":false,"usgs":false,"family":"Bjurlin","given":"Curtis","affiliations":[],"preferred":false,"id":625909,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Austin, Meaghan","contributorId":37244,"corporation":false,"usgs":true,"family":"Austin","given":"Meaghan","affiliations":[],"preferred":false,"id":625910,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Madrak, Sheila V.","contributorId":7403,"corporation":false,"usgs":true,"family":"Madrak","given":"Sheila","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":625911,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loughran, Caleb L.","contributorId":26599,"corporation":false,"usgs":true,"family":"Loughran","given":"Caleb","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":625912,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Tennant, Laura A. 0000-0003-0062-7287 ltennant@usgs.gov","orcid":"https://orcid.org/0000-0003-0062-7287","contributorId":5984,"corporation":false,"usgs":true,"family":"Tennant","given":"Laura","email":"ltennant@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":625913,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Price, Steven J. 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Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus urophasianus) habitat models to evaluate the effects of potential climate-induced habitat change. Under the 2050 IPCC A1B scenario, 11.6% of currently identified nesting habitat was lost, and 0.002% of new potential habitat was gained, with 4% of summer habitat lost and 0.039% gained. Our results demonstrate the successful ability of remote sensing based sagebrush components, when coupled with precipitation, to forecast future component response using IPCC precipitation scenarios. Our approach also enables future quantification of greater sage-grouse habitat under different precipitation scenarios, and provides additional capability to identify regional precipitation influence on sagebrush component response.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2015.03.002","usgsCitation":"Homer, C.G., Xian, G.Z., Aldridge, C.L., Meyer, D.K., Loveland, T.R., and O’Donnell, M.S., 2015, Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050: learning from past climate patterns and Landsat imagery to predict the future: Ecological Indicators, v. 55, p. 131-145, https://doi.org/10.1016/j.ecolind.2015.03.002.","productDescription":"15 p.","startPage":"131","endPage":"145","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061116","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472146,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2015.03.002","text":"Publisher Index Page"},{"id":299699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.96240234375,\n 41.48080459927738\n ],\n [\n -110.00473022460938,\n 41.6770148220322\n ],\n [\n -109.69573974609375,\n 42.56926437219384\n ],\n [\n -108.65341186523436,\n 42.37883631647602\n ],\n [\n -108.96240234375,\n 41.48080459927738\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"552f7d9ae4b0b22a158031c7","contributors":{"authors":[{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":544946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":544947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":544948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer, Debra K. 0000-0002-8841-697X dkmeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8841-697X","contributorId":3145,"corporation":false,"usgs":true,"family":"Meyer","given":"Debra","email":"dkmeyer@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":544950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140256,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","middleInitial":"R.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":544949,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":3351,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":544951,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159193,"text":"70159193 - 2015 - The modelling and assessment of whale-watching impacts","interactions":[],"lastModifiedDate":"2015-10-19T10:35:15","indexId":"70159193","displayToPublicDate":"2015-04-15T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"title":"The modelling and assessment of whale-watching impacts","docAbstract":"In recent years there has been significant interest in modelling cumulative effects and the population consequences of individual changes in cetacean behaviour and physiology due to disturbance. One potential source of disturbance that has garnered particular interest is whale-watching. Though perceived as ‘green’ or eco-friendly tourism, there is evidence that whale-watching can result in statistically significant and biologically meaningful changes in cetacean behaviour, raising the question whether whale-watching is in fact a long term sustainable activity. However, an assessment of the impacts of whale-watching on cetaceans requires an understanding of the potential behavioural and physiological effects, data to effectively address the question and suitable modelling techniques. Here, we review the current state of knowledge on the viability of long-term whale-watching, as well as logistical limitations and potential opportunities. We conclude that an integrated, coordinated approach will be needed to further understanding of the possible effects of whale-watching on cetaceans.
","language":"English","publisher":"Elsevier Applied Science","publisherLocation":"Barking, Essex, England","doi":"10.1016/j.ocecoaman.2015.04.006","usgsCitation":"New, L., Hall, A.J., Harcourt, R., Kaufman, G., Parsons, E., Pearson, H.C., Cosentino, A.M., and Schick, R.S., 2015, The modelling and assessment of whale-watching impacts: Ocean and Coastal Management, v. 115, p. 10-16, https://doi.org/10.1016/j.ocecoaman.2015.04.006.","productDescription":"7 p.","startPage":"10","endPage":"16","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-064920","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472147,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocecoaman.2015.04.006","text":"Publisher Index Page"},{"id":310036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56261497e4b0fb9a11dd765d","contributors":{"authors":[{"text":"New, Leslie lnew@usgs.gov","contributorId":145484,"corporation":false,"usgs":true,"family":"New","given":"Leslie","email":"lnew@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":577800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Ailsa J.","contributorId":40915,"corporation":false,"usgs":true,"family":"Hall","given":"Ailsa","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":577801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harcourt, Robert","contributorId":149302,"corporation":false,"usgs":false,"family":"Harcourt","given":"Robert","affiliations":[],"preferred":false,"id":577815,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaufman, Greg","contributorId":149303,"corporation":false,"usgs":false,"family":"Kaufman","given":"Greg","email":"","affiliations":[],"preferred":false,"id":577816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parsons, E.C.M.","contributorId":149304,"corporation":false,"usgs":false,"family":"Parsons","given":"E.C.M.","email":"","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":577817,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearson, Heidi C.","contributorId":149305,"corporation":false,"usgs":false,"family":"Pearson","given":"Heidi","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":577818,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cosentino, A. Mel","contributorId":149306,"corporation":false,"usgs":false,"family":"Cosentino","given":"A.","email":"","middleInitial":"Mel","affiliations":[],"preferred":false,"id":577819,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schick, Robert S","contributorId":149294,"corporation":false,"usgs":false,"family":"Schick","given":"Robert","email":"","middleInitial":"S","affiliations":[{"id":12470,"text":"University of St. Andrews","active":true,"usgs":false}],"preferred":false,"id":577802,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70154768,"text":"70154768 - 2015 - A sea lamprey (Petromyzon marinus) sex pheromone mixture increases trap catch relative to a single synthesized component in specific environments","interactions":[],"lastModifiedDate":"2017-05-18T11:53:08","indexId":"70154768","displayToPublicDate":"2015-04-15T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2205,"text":"Journal of Chemical Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A sea lamprey (Petromyzon marinus) sex pheromone mixture increases trap catch relative to a single synthesized component in specific environments","docAbstract":"Spermiating male sea lamprey (Petromyzon marinus) release a sex pheromone, of which a component, 7α, 12α, 24-trihydoxy-3-one-5α-cholan-24-sulfate (3kPZS), has been identified and shown to induce long distance preference responses in ovulated females. However, other pheromone components exist, and when 3kPZS alone was used to control invasive sea lamprey populations in the Laurentian Great Lakes, trap catch increase was significant, but gains were generally marginal. We hypothesized that free-ranging sea lamprey populations discriminate between a partial and complete pheromone while migrating to spawning grounds and searching for mates at spawning grounds. As a means to test our hypothesis, and to test two possible uses of sex pheromones for sea lamprey control, we asked whether the full sex pheromone mixture released by males (spermiating male washings; SMW) is more effective than 3kPZS in capturing animals in traditional traps (1) en route to spawning grounds and (2) at spawning grounds. At locations where traps target sea lampreys en route to spawning grounds, SMW-baited traps captured significantly more sea lampreys than paired 3kPZS-baited traps (~10 % increase). At spawning grounds, no difference in trap catch was observed between 3kPZS and SMW-baited traps. The lack of an observed difference at spawning grounds may be attributed to increased pheromone competition and possible involvement of other sensory modalities to locate mates. Because fishes often rely on multiple and sometimes redundant sensory modalities for critical life history events, the addition of sex pheromones to traditionally used traps is not likely to work in all circumstances. In the case of the sea lamprey, sex pheromone application may increase catch when applied to specifically designed traps deployed in streams with low adult density and limited spawning habitat.
","language":"English","publisher":"Springer","doi":"10.1007/s10886-015-0561-2","usgsCitation":"Johnson, N.S., Tix, J., Hlina, B.L., Wagner, C.M., Siefkes, M.J., Wang, H., and Li, W., 2015, A sea lamprey (Petromyzon marinus) sex pheromone mixture increases trap catch relative to a single synthesized component in specific environments: Journal of Chemical Ecology, v. 41, no. 3, p. 311-321, https://doi.org/10.1007/s10886-015-0561-2.","productDescription":"11 p.","startPage":"311","endPage":"321","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060452","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":305538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-22","publicationStatus":"PW","scienceBaseUri":"55950f2be4b0b6d21dd6cbd2","contributors":{"authors":[{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":564048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tix, John A.","contributorId":126766,"corporation":false,"usgs":false,"family":"Tix","given":"John A.","affiliations":[{"id":6602,"text":"Great Lakes Science Center, Hammond Bay Biological Station","active":true,"usgs":false}],"preferred":false,"id":564049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hlina, Benjamin L.","contributorId":145441,"corporation":false,"usgs":false,"family":"Hlina","given":"Benjamin","email":"","middleInitial":"L.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":564050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, C. Michael","contributorId":145442,"corporation":false,"usgs":false,"family":"Wagner","given":"C.","email":"","middleInitial":"Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":564051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Siefkes, Michael J.","contributorId":36905,"corporation":false,"usgs":true,"family":"Siefkes","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":564052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Huiyong","contributorId":79007,"corporation":false,"usgs":true,"family":"Wang","given":"Huiyong","affiliations":[],"preferred":false,"id":564053,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Li, Weiming","contributorId":65440,"corporation":false,"usgs":true,"family":"Li","given":"Weiming","affiliations":[],"preferred":false,"id":564054,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190681,"text":"70190681 - 2015 - Sediment contributions from floodplains and legacy sediments to Piedmont streams of Baltimore County, Maryland","interactions":[],"lastModifiedDate":"2017-09-12T11:49:32","indexId":"70190681","displayToPublicDate":"2015-04-15T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Sediment contributions from floodplains and legacy sediments to Piedmont streams of Baltimore County, Maryland","docAbstract":"Disparity between watershed erosion rates and downstream sediment delivery has remained an important theme in geomorphology for many decades, with the role of floodplains in sediment storage as a common focus. In the Piedmont Province of the eastern USA, upland deforestation and agricultural land use following European settlement led to accumulation of thick packages of overbank sediment in valley bottoms, commonly referred to as legacy deposits. Previous authors have argued that legacy deposits represent a potentially important source of modern sediment loads following remobilization by lateral migration and progressive channel widening. This paper seeks to quantify (1) rates of sediment remobilization from Baltimore County floodplains by channel migration and bank erosion, (2) proportions of streambank sediment derived from legacy deposits, and (3) potential contribution of net streambank erosion and legacy sediments to downstream sediment yield within the Mid-Atlantic Piedmont.
We calculated measurable gross erosion and deposition rates within the fluvial corridor along 40 valley segments from 18 watersheds with drainage areas between 0.18 and 155 km2 in Baltimore County, Maryland. We compared stream channel and floodplain morphology from lidar-based digital elevation data collected in 2005 with channel positions recorded on 1:2400 scale topographic maps from 1959–1961 in order to quantify 44–46 years of channel change. Sediment bulk density and particle size distributions were characterized from streambank and channel deposit samples and used for volume to mass conversions and for comparison with other sediment sources.
Average annual lateral migration rates ranged from 0.04 to 0.19 m/y, which represented an annual migration of 2.5% (0.9–4.4%) channel width across all study segments, suggesting that channel dimensions may be used as reasonable predictors of bank erosion rates. Gross bank erosion rates varied from 43 to 310 Mg/km/y (median = 114) and were positively correlated with drainage area. Measured deposition within channels accounted for an average of 46% (28–75%) of gross erosion, with deposition increasingly important in larger drainages. Legacy sediments accounted for 6–90% of bank erosion at individual study segments, represented about 60% of bank height at most exposures, and accounted for 57% (± 16%) of the measured gross erosion. Extrapolated results indicated that first- and second-order streams accounted for 62% (± 38%) of total streambank erosion from 1005 km2 of northern Baltimore County. After accounting for estimated redeposition, extrapolated net streambank sediment yields (72 Mg/km2/y) constituted 70% of estimated average Piedmont watershed yields (104 Mg/km2/y). The results suggest that streambank sediments are a relatively large source of sediment from Piedmont tributaries to the Chesapeake Bay.
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The RTL-W1 fish liver cell line was used to investigate two endpoints (genotoxicity and DNA-repair-capacity impairment) associated with exposure to runoff from asphalt pavement with CTB sealcoat or with an asphalt-based sealcoat hypothesized to contain about 7% CTB sealcoat (AS-blend). Genotoxic potential was assessed by the Formamido pyrimidine glycosylase (Fpg)-modified comet assay for 1:10 and 1:100 dilutions of runoff samples collected from 5 h to 36 d following sealcoat application. DNA-repair capacity was assessed by the base excision repair comet assay for 1:10 dilution of samples collected 26 h and 36 d following application. Both assays were run with and without co-exposure to ultraviolet-A radiation (UVA). With co-exposure to UVA, genotoxic effects were significant for both dilutions of CTB runoff for three of four sample times, and for some samples of AS-blend runoff. Base excision repair was significantly impaired for CTB runoff both with and without UVA exposure, and for AS-blend runoff only in the absence of UVA. This study is the first to investigate the effects of exposure to the complex mixture of chemicals in coal tar on DNA repair capacity. The results indicate that co-exposure to runoff from CT-sealcoated pavement and UVA as much as a month after sealcoat application has the potential to cause genotoxicity and impair DNA repair capacity.
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\nSheet 2: This map is based on data from the Lunar Orbiter Laser Altimeter (LOLA; Smith and others, 2010), an instrument on the National Aeronautics and Space Administration (NASA) Lunar Reconnaissance Orbiter (LRO) spacecraft (Tooley and others, 2010). The image used for the base of this map represents more than 6.5 billion measurements gathered between July 2009 and July 2013, adjusted for consistency in the coordinate system described below, and then converted to lunar radii (Mazarico and others, 2012). For the Mercator portion, these measurements were converted into a digital elevation model (DEM) with a resolution of 0.015625 degrees per pixel, or 64 pixels per degree. In projection, the pixels are 473.8 m in size at the equator. For the polar portion, the LOLA elevation points were used to create a DEM at 240 meters per pixel. A shaded relief map was generated from each DEM with a sun angle of 45° from horizontal, and a sun azimuth of 270°, as measured clockwise from north with no vertical exaggeration. The DEM values were then mapped to a global color look-up table, with each color representing a range of 1 km of elevation. For this map sheet, only larger feature names are shown. For references listed above, please open the full PDF.
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In determining which life history characteristics had the greatest influence on future population dynamics, adult female survival consistently had the highest sensitivity and elasticity and this result was robust across a wide range of life history parameter values. Conversely, retrospective models consistently found that the majority of annual variation in lambda was associate with variation in productivity. Stochastic models that are base on process variation and incorporate correlations among life history parameters are the most useful for visualizing the probability of achieving a desired management outcome. Effective management targets both the mean and the variance parameters and takes advantage of correlations among life history parameters. Example models demonstrate that sea duck species can achieve equal fitness using a variety of survival and productivity combinations. Sea duck populations will tend to have long time largest in terms of responding to management actions. 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