Plumes of buoyant river water spread in the ocean from river mouths, and these plumes influence water quality, sediment dispersal, primary productivity, and circulation along the world’s coasts. Most investigations of river plumes have focused on large rivers in a coastal region, for which the physical spreading of the plume is assumed to be independent from the influence of other buoyant plumes. Here we provide new understanding of the spreading patterns of multiple plumes interacting along simplified coastal settings by investigating: (i) the relative likelihood of plume-to-plume interactions at different settings using geophysical scaling, (ii) the diversity of plume frontal collision types and the effects of these collisions on spreading patterns of plume waters using a two-dimensional hydrodynamic model, and (iii) the fundamental differences in plume spreading patterns between coasts with single and multiple rivers using a three-dimensional hydrodynamic model. Geophysical scaling suggests that coastal margins with numerous small rivers (watershed areas < 10,000 km2), such as found along most active geologic coastal margins, were much more likely to have river plumes that collide and interact than coastal settings with large rivers (watershed areas > 100,000 km2). When two plume fronts meet, several types of collision attributes were found, including refection, subduction and occlusion. We found that the relative differences in pre-collision plume densities and thicknesses strongly influenced the resulting collision types. The three-dimensional spreading of buoyant plumes was found to be influenced by the presence of additional rivers for all modeled scenarios, including those with and without Coriolis and wind. Combined, these results suggest that plume-to-plume interactions are common phenomena for coastal regions offshore of the world’s smaller rivers and for coastal settings with multiple river mouths in close proximity, and that the spreading and fate of river waters in these settings will be strongly influenced by these interactions. We conclude that new investigations are needed to characterize how plumes interact offshore of river mouths to better understand the transport and fate of terrestrial sources of pollution, nutrients and other materials in the ocean.
A comprehensive inventory of ecosystem services across the entire Great Lakes basin is currently lacking and is needed to make informed management decisions. A greater appreciation and understanding of ecosystem services, including both use and non-use services, may have avoided misguided resource management decisions in the past that resulted in negative legacies inherited by future generations. Given the interest in ecosystem services and lack of a coherent approach to addressing this topic in the Great Lakes, a summit was convened involving 28 experts working on various aspects of ecosystem services in the Great Lakes. The invited attendees spanned a variety of social and natural sciences. Given the unique status of the Great Lakes as the world's largest collective repository of surface freshwater, and the numerous stressors threatening this valuable resource, timing was propitious to examine ecosystem services. Several themes and recommendations emerged from the summit. There was general consensus that: 1) a comprehensive inventory of ecosystem services throughout the Great Lakes is a desirable goal but would require considerable resources; 2) more spatially and temporally intensive data are needed to overcome our data gaps, but the arrangement of data networks and observatories must be well-coordinated; 3) trade-offs must be considered as part of ecosystem services analyses; and 4) formation of a Great Lakes Institute for Ecosystem Services, to provide a hub for research, meetings, and training is desirable. Several challenges also emerged during the summit, which are discussed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2017.02.004","usgsCitation":"Steinman, A.D., Cardinale, B.J., Munns, W.R., Ogdahl, M.E., Allan, D.J., Angadi, T., Bartlett, S., Brauman, K.A., Byappanahalli, M., Doss, M., Dupont, D., Johns, A., Kashian, D., Lupi, F., McIntyre, P.B., Miller, T., Moore, M.P., Muenich, R.L., Poudel, R., Price, J., Provencher, B., Rea, A., Read, J., Renzetti, S., Sohngen, B., and Washburn, E., 2017, Ecosystem services in the Great Lakes: Journal of Great Lakes Research, v. 43, no. 3, p. 161-168, https://doi.org/10.1016/j.jglr.2017.02.004.","productDescription":"8 p.","startPage":"161","endPage":"168","ipdsId":"IP-082813","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469948,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2017.02.004","text":"Publisher Index Page"},{"id":339137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","volume":"43","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e4b0b0e4b09da67999776a","contributors":{"authors":[{"text":"Steinman, Alan D.","contributorId":190417,"corporation":false,"usgs":false,"family":"Steinman","given":"Alan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":688394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cardinale, Bradley J.","contributorId":190418,"corporation":false,"usgs":false,"family":"Cardinale","given":"Bradley","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munns, Wayne R. Jr.","contributorId":190419,"corporation":false,"usgs":false,"family":"Munns","given":"Wayne","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":688396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogdahl, Mary E.","contributorId":152664,"corporation":false,"usgs":false,"family":"Ogdahl","given":"Mary","email":"","middleInitial":"E.","affiliations":[{"id":18955,"text":"Annis Water Resources Institute-GVSU","active":true,"usgs":false}],"preferred":false,"id":688397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allan, David J.","contributorId":190420,"corporation":false,"usgs":false,"family":"Allan","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angadi, Ted","contributorId":190421,"corporation":false,"usgs":false,"family":"Angadi","given":"Ted","email":"","affiliations":[],"preferred":false,"id":688399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bartlett, Sarah","contributorId":190422,"corporation":false,"usgs":false,"family":"Bartlett","given":"Sarah","affiliations":[],"preferred":false,"id":688400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brauman, Kate A.","contributorId":190423,"corporation":false,"usgs":false,"family":"Brauman","given":"Kate","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":688401,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science 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Donna","contributorId":190427,"corporation":false,"usgs":false,"family":"Kashian","given":"Donna","affiliations":[],"preferred":false,"id":688405,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lupi, Frank","contributorId":190428,"corporation":false,"usgs":false,"family":"Lupi","given":"Frank","email":"","affiliations":[],"preferred":false,"id":688406,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McIntyre, Peter B.","contributorId":166828,"corporation":false,"usgs":false,"family":"McIntyre","given":"Peter","email":"","middleInitial":"B.","affiliations":[{"id":24540,"text":"Center for Limnology, University of Wisconsin, Madison, Wisconsin, 53706, USA.","active":true,"usgs":false}],"preferred":false,"id":688407,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Miller, Todd","contributorId":190429,"corporation":false,"usgs":false,"family":"Miller","given":"Todd","email":"","affiliations":[],"preferred":false,"id":688408,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Moore, Michael P.","contributorId":176155,"corporation":false,"usgs":false,"family":"Moore","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":688409,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Muenich, Rebecca Logsdon","contributorId":169555,"corporation":false,"usgs":false,"family":"Muenich","given":"Rebecca","email":"","middleInitial":"Logsdon","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":688410,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Poudel, Rajendra","contributorId":190430,"corporation":false,"usgs":false,"family":"Poudel","given":"Rajendra","email":"","affiliations":[],"preferred":false,"id":688411,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Price, James","contributorId":156327,"corporation":false,"usgs":false,"family":"Price","given":"James","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":688412,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Provencher, Bill","contributorId":190431,"corporation":false,"usgs":false,"family":"Provencher","given":"Bill","email":"","affiliations":[],"preferred":false,"id":688413,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Rea, Anne","contributorId":190432,"corporation":false,"usgs":false,"family":"Rea","given":"Anne","email":"","affiliations":[],"preferred":false,"id":688414,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Read, Jennifer","contributorId":140055,"corporation":false,"usgs":false,"family":"Read","given":"Jennifer","email":"","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":688415,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Renzetti, Steven","contributorId":190433,"corporation":false,"usgs":false,"family":"Renzetti","given":"Steven","email":"","affiliations":[],"preferred":false,"id":688416,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Sohngen, Brent","contributorId":190434,"corporation":false,"usgs":false,"family":"Sohngen","given":"Brent","email":"","affiliations":[],"preferred":false,"id":688417,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Washburn, Erica","contributorId":190435,"corporation":false,"usgs":false,"family":"Washburn","given":"Erica","email":"","affiliations":[],"preferred":false,"id":688418,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70186366,"text":"70186366 - 2017 - Fungal and bacterial contributions to nitrogen cycling in cheatgrass-invaded and uninvaded native sagebrush soils of the western USA","interactions":[],"lastModifiedDate":"2017-11-22T17:01:54","indexId":"70186366","displayToPublicDate":"2017-04-04T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3089,"text":"Plant and Soil","active":true,"publicationSubtype":{"id":10}},"title":"Fungal and bacterial contributions to nitrogen cycling in cheatgrass-invaded and uninvaded native sagebrush soils of the western USA","docAbstract":"Aim
There is interest in determining how cheatgrass (Bromus tectorum L.) modifies N cycling in sagebrush (Artemisia tridentata Nutt.) soils of the western USA.
Methods
To gain insight into the roles of fungi and bacteria in N cycling of cheatgrass-invaded and uninvaded sagebrush soils, the fungal protein synthesis inhibitor, cycloheximide (CHX), and the bacteriocidal compound, bronopol (BRO) were combined with a 15NH4+ isotope pool dilution approach.
Results
CHX reduced gross N mineralization to the same rate in both sagebrush and cheatgrass soils indicating a role for fungi in N mineralization in both soil types. In cheatgrass soils BRO completely inhibited gross N mineralization, whereas, in sagebrush soils a BRO-resistant gross N mineralization rate was detected that was slower than CHX sensitive gross N mineralization, suggesting that the microbial drivers of gross N mineralization were different in sagebrush and cheatgrass soils. Net N mineralization was stimulated to a higher rate in sagebrush than in cheatgrass soils by CHX, implying that a CHX inhibited N sink was larger in the former than the latter soils. Initial gross NH4+ consumption rates were reduced significantly by both CHX and BRO in both soil types, yet, consumption rates recovered significantly between 24 and 48 h in CHX-treated sagebrush soils. The recovery of NH4+ consumption in sagebrush soils corresponded with an increase in the rate of net nitrification.
Conclusions
These results suggest that cheatgrass invasion of sagebrush soils of the northern Great Basin reduces the capacity of the fungal N consumption sink, enhances the capacity of a CHX resistant N sink and alters the contributions of bacteria and fungi to gross N mineralization.
The U.S. Geological Survey (USGS), as part of the National Assessment of Storm-Induced Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms. On June 9, 2011, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a Beechcraft BE90 King Air (aircraft) at an altitude of 500 feet (ft) (152 meters (m)) and approximately 1,200 ft (366 m) offshore. This mission was conducted to collect baseline data for assessing incremental changes in the beach and nearshore area and can be used to assess future coastal change.
The photographs in this report are Joint Photographic Experts Group (JPEG) images. These photographs document the state of the barrier islands and other coastal features at the time of the survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1044","usgsCitation":"Morgan, K.L.M., 2017, Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, June 9, 2011: U.S. Geological Survey Data Series 1044, https://doi.org/10.3133/ds1044.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077797","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338169,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1044/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"}},{"id":338168,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1044/coverthb.jpg"}],"country":"United States","state":"Alabama, Louisiana","otherGeospatial":"Breton Island, Dauphin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.16778564453125,\n 29.602118211647333\n ],\n [\n -88.05816650390625,\n 29.602118211647333\n ],\n [\n -88.05816650390625,\n 30.28041626667403\n ],\n [\n -89.16778564453125,\n 30.28041626667403\n ],\n [\n -89.16778564453125,\n 29.602118211647333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/
The U.S. Geological Survey (USGS), as part of the National Assessment of Storm-Induced Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms. On August 31, 2005, the USGS conducted an oblique aerial photographic survey from Panama City, Florida, to Lakeshore, Mississippi, and the Chandeleur Islands, Louisiana, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet and approximately 1,000 feet offshore. This mission was flown to collect post-Hurricane Katrina data, which can be used to assess incremental changes in the beach and nearshore area and can be used to assess future coastal change.
The photographs in this report are Joint Photographic Experts Group (JPEG) images. These photographs document the state of the barrier islands and other coastal features at the time of the survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1033","usgsCitation":"Morgan, K.L.M., and DeWitt, N.T., 2017, Post-Hurricane Katrina coastal oblique aerial photographs collected from Panama City, Florida, to Lakeshore, Mississippi, and the Chandeleur Islands, Louisiana, August 31, 2005: U.S. Geological Survey Data Series 1033, https://doi.org/10.3133/ds1033.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079893","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1033/coverthb.jpg"},{"id":338245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1033/index.html","text":"Report HTML"}],"country":"United States","state":"Florida","city":"Panama City","otherGeospatial":"Pensacola Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.20672607421875,\n 30.337324394179017\n ],\n [\n -87.19024658203124,\n 30.30176068632071\n ],\n [\n -86.87713623046875,\n 30.36102635890718\n ],\n [\n -86.59423828125,\n 30.372875188118016\n ],\n [\n -86.3140869140625,\n 30.351546261929034\n ],\n [\n -86.143798828125,\n 30.29701788337205\n ],\n [\n -85.94879150390625,\n 30.225848323247707\n ],\n [\n -85.7537841796875,\n 30.107117887092357\n ],\n [\n -85.6988525390625,\n 30.1380015549519\n ],\n [\n -85.98724365234375,\n 30.28990324883237\n ],\n [\n -86.2591552734375,\n 30.372875188118016\n ],\n [\n -86.46514892578124,\n 30.401306519203583\n ],\n [\n -86.77276611328125,\n 30.413150465068853\n ],\n [\n -86.96502685546875,\n 30.391830328088137\n ],\n [\n -87.20672607421875,\n 30.337324394179017\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/
Investigations of coastal change at Fire Island, New York (N.Y.), sought to characterize sediment budgets and determine geologic framework controls on coastal processes. Nearshore sediment thickness is critical for assessing coastal system sediment availability, but it is largely unquantified due to the difficulty of conducting geological or geophysical surveys across the nearshore. This study used an amphibious vessel to acquire chirp subbottom profiles. These profiles were used to characterize nearshore geology and provide an assessment of nearshore sediment volume. Two resulting sediment-thickness maps are provided: total Holocene sediment thickness and the thickness of the active shoreface. The Holocene sediment section represents deposition above the maximum flooding surface that is related to the most recent marine transgression. The active shoreface section is the uppermost Holocene sediment, which is interpreted to represent the portion of the shoreface thought to contribute to present and future coastal behavior. The sediment distribution patterns correspond to previously defined zones of erosion, accretion, and stability along the island, demonstrating the importance of sediment availability in the coastal response to storms and seasonal variability. The eastern zone has a thin nearshore sediment thickness, except for an ebb-tidal deposit at the wilderness breach caused by Hurricane Sandy. Thicker sediment is found along a central zone that includes shoreface-attached sand ridges, which is consistent with a stable or accretional coastline in this area. The thickest overall Holocene section is found in the western zone of the study, where a thicker lower section of Holocene sediment appears related to the westward migration of Fire Island Inlet over several hundred years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171024","usgsCitation":"Locker, S.D., Miselis, J.L., Buster, N.A., Hapke, C.J., Wadman, H.M., McNinch, J.E., Forde, A.S., and Stalk, C.A., 2017, Nearshore sediment thickness, Fire Island, New York: U.S. Geological Survey Open-File Report 2017–1024, 21 p., https://doi.org/10.3133/ofr20171024.","productDescription":"vii, 21 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079609","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1024/ofr20171024.pdf","text":"Report","size":"6.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1024"},{"id":338702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1024/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.87986755371094,\n 40.77534183237267\n ],\n [\n -72.87986755371094,\n 40.77534183237267\n ],\n [\n -72.87986755371094,\n 40.77534183237267\n ],\n [\n -72.87986755371094,\n 40.77534183237267\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.87574768066406,\n 40.77534183237267\n ],\n [\n -73.27743530273438,\n 40.65563874006118\n ],\n [\n -73.24447631835938,\n 40.59674926086908\n ],\n [\n -72.84210205078125,\n 40.7202010588415\n ],\n [\n -72.87574768066406,\n 40.77534183237267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/
We compared total mercury (Hg) concentrations in whole blood of harlequin ducks (Histrionicus histrionicus) sampled within and among two geographically distinct locations and across three years in southwest Alaska. Blue mussels were collected to assess correlation between Hg concentrations in locally available forage and birds. Mercury concentrations in harlequin duck blood were significantly higher at Unalaska Island (0.31 ± 0.19 mean ± SD, μg/g blood) than Kodiak Island (0.04 ± 0.02 mean ± SD, μg/g blood). We found no evidence for annual variation in blood Hg concentration between years at Unalaska Island. However, blood Hg concentration did vary among specific sampling locations (i.e., bays) at Unalaska Island. Findings from this study demonstrate harlequin ducks are exposed to environmental sources of Hg, and whole blood Hg concentrations are associated with their local food source.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2017.01.084","usgsCitation":"Savoy, L., Flint, P.L., Zwiefelhofer, D., Brant, H., Perkins, C.R., Taylor, R.J., Lane, O.P., Hall, J.S., Evers, D.C., and Schamber, J., 2017, Geographic and temporal patterns of variation in total mercury concentrations in blood of harlequin ducks and blue mussels from Alaska: Marine Pollution Bulletin, v. 117, no. 1-2, p. 178-183, https://doi.org/10.1016/j.marpolbul.2017.01.084.","productDescription":"6 p.","startPage":"178","endPage":"183","ipdsId":"IP-078778","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":339076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kodiak Island, Unalaska Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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An international working group (including statutory agencies, NGO representatives and experts) agreed on objectives and actions to maintain the population in favourable conservation status, while accounting for biodiversity, economic and recreational interests. Agreements include setting a population target to reduce agricultural conflicts and avoid tundra degradation, and using hunting in some range states to maintain stable population size. As part of the adaptive management procedures, adjustment to harvest is made annually subject to population status. This has required streamlining of monitoring and assessment activities. Three years after implementation, indicators suggest the attainment of management results. Dialogue, consensus-building and engagement among stakeholders represent the major process achievements.
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","language":"English","publisher":"Society for Mining, Metallurgy, and Exploration","publisherLocation":"Littleton, CO","usgsCitation":"Karl, N., and Wilburn, D.R., 2017, Global nonfuel mineral exploration trends 2001-2015: Mining Engineering, v. 69, no. 4, p. 30-30.","productDescription":"1 p.","startPage":"30","endPage":"30","ipdsId":"IP-081144","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":338999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":338998,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://me.smenet.org/abstract.cfm?preview=1&articleID=7496&page=30"}],"otherGeospatial":"Earth","volume":"69","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e35f7ee4b09da67997eca7","contributors":{"authors":[{"text":"Karl, Nick 0000-0003-2858-2498 nkarl@usgs.gov","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":178317,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"nkarl@usgs.gov","affiliations":[],"preferred":true,"id":658481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":658480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199853,"text":"70199853 - 2017 - Erosion of refugia in the Sierra Nevada meadows network with climate change","interactions":[],"lastModifiedDate":"2018-10-01T15:43:15","indexId":"70199853","displayToPublicDate":"2017-04-01T15:43:02","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Erosion of refugia in the Sierra Nevada meadows network with climate change","docAbstract":"Climate refugia management has been proposed as a climate adaptation strategy in the face of global change. Key to this strategy is identification of these areas as well as an understanding of how they are connected on the landscape. Focusing on meadows of the Sierra Nevada in California, we examined multiple factors affecting connectivity using circuit theory, and determined how patches have been and are expected to be affected by climate change. Connectivity surfaces varied depending upon the underlying hypothesis, although meadow area and elevation were important features for higher connectivity. Climate refugia that would promote population persistence were identified from downscaled climate layers, based on locations with minimal climatic change from historical conditions. This approach was agnostic to specific species, yielding a broad perspective about changes and localized habitats. Connectivity was not a consistent predictor of refugial status in the 20th century, but expected future climate refugia tended to have higher connectivity than those that recently deviated from historical conditions. Climate change is projected to reduce the number of refugial meadows on a variety of climate axes, resulting in a sparser network of potential refugia across elevations. Our approach provides a straightforward method that can be used as a tool to prioritize places for climate adaptation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1673","usgsCitation":"Maher, S.P., Morelli, T.L., Hershey, M., Flint, A.L., Flint, L.E., Moritz, C., and Beissinger, S.R., 2017, Erosion of refugia in the Sierra Nevada meadows network with climate change: Ecosphere, v. 8, no. 4, p. 1-17, https://doi.org/10.1002/ecs2.1673.","productDescription":"e01673; 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-070741","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":469954,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1673","text":"Publisher Index Page"},{"id":357990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 36\n ],\n [\n -118,\n 36\n ],\n [\n -118,\n 42\n ],\n [\n -122,\n 42\n ],\n [\n -122,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"4","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-20","publicationStatus":"PW","scienceBaseUri":"5bc031aae4b0fc368eb53a3e","contributors":{"authors":[{"text":"Maher, Sean P.","contributorId":7998,"corporation":false,"usgs":true,"family":"Maher","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":746905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":746904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hershey, Michelle","contributorId":208379,"corporation":false,"usgs":false,"family":"Hershey","given":"Michelle","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":746909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746906,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746903,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moritz, Craig","contributorId":149462,"corporation":false,"usgs":false,"family":"Moritz","given":"Craig","email":"","affiliations":[{"id":17742,"text":"Research School of Biology, The Australian Nat'l U, Acton, Australia","active":true,"usgs":false}],"preferred":false,"id":746908,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beissinger, Steven R.","contributorId":100534,"corporation":false,"usgs":true,"family":"Beissinger","given":"Steven","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":746907,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70199835,"text":"70199835 - 2017 - An integrated population model for bird monitoring in North America","interactions":[],"lastModifiedDate":"2018-10-01T14:34:33","indexId":"70199835","displayToPublicDate":"2017-04-01T14:34:23","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"An integrated population model for bird monitoring in North America","docAbstract":"Integrated population models (IPMs) provide a unified framework for simultaneously analyzing data sets of different types to estimate vital rates, population size, and dynamics; assess contributions of demographic parameters to population changes; and assess population viability. Strengths of an IPM include the ability to estimate latent parameters and improve the precision of parameter estimates. We present a hierarchical IPM that combines two broad‐scale avian monitoring data sets: count data from the North American Breeding Bird Survey (BBS) and capture–recapture data from the Monitoring Avian Productivity and Survivorship (MAPS) program. These data sets are characterized by large numbers of sample sites and observers, factors capable of inducing error in the sampling and observation processes. The IPM integrates the data sets by modeling the population abundance as a first‐order autoregressive function of the previous year's population abundance and vital rates. BBS counts were modeled as a log‐linear function of the annual index of population abundance, observation effects (observer identity and first survey year), and overdispersion. Vital rates modeled included adult apparent survival, estimated from a transient Cormack‐Jolly‐Seber model using MAPS data, and recruitment (surviving hatched birds from the previous season + dispersing adults) estimated as a latent parameter. An assessment of the IPM demonstrated it could recover true parameter values from 200 simulated data sets. The IPM was applied to data sets (1992–2008) of two bird species, Gray Catbird (Dumetella carolinensis) and Wood Thrush (Hylocichla mustelina) in the New England/Mid‐Atlantic coastal Bird Conservation Region of the United States. The Gray Catbird population was relatively stable (trend +0.4% per yr), while the Wood Thrush population nearly halved (trend −4.5% per yr) over the 17‐yr study period. IPM estimates of population growth rates, adult survival, and detection and residency probabilities were similar and as precise as estimates from the stand‐alone BBS and CJS models. A benefit of using the IPM was its ability to estimate the latent recruitment parameter. Annual growth rates for both species correlated more with recruitment than survival, and the relationship for Wood Thrush was stronger than for Gray Catbird. The IPM's unified modeling framework facilitates integration of these important data sets.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1493","usgsCitation":"Ahrestani, F.S., Saracco, J.F., Sauer, J.R., Pardieck, K.L., and Royle, J.A., 2017, An integrated population model for bird monitoring in North America: Ecological Applications, v. 27, no. 3, p. 916-924, https://doi.org/10.1002/eap.1493.","productDescription":"9 p.","startPage":"916","endPage":"924","ipdsId":"IP-080990","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":357969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"5bc031aae4b0fc368eb53a40","contributors":{"authors":[{"text":"Ahrestani, Farshid S.","contributorId":208349,"corporation":false,"usgs":false,"family":"Ahrestani","given":"Farshid","email":"","middleInitial":"S.","affiliations":[{"id":37785,"text":"The Institute of Bird Populations","active":true,"usgs":false}],"preferred":false,"id":746840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saracco, James F.","contributorId":208350,"corporation":false,"usgs":false,"family":"Saracco","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":37785,"text":"The Institute of Bird Populations","active":true,"usgs":false}],"preferred":false,"id":746841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746842,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":139626,"corporation":false,"usgs":true,"family":"Royle","given":"J.","email":"aroyle@usgs.gov","middleInitial":"Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":746843,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70181997,"text":"70181997 - 2017 - Trends in snowmelt-related streamflow timing in the conterminous United States","interactions":[],"lastModifiedDate":"2018-08-07T14:33:22","indexId":"70181997","displayToPublicDate":"2017-04-01T14:33:14","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Trends in snowmelt-related streamflow timing in the conterminous United States","docAbstract":"Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940–2014 and 1960–2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940–2014, 0.9 days/decade) and 3.4 days (1960–2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940–2014, 0.5 days/decade) and 5.2 days (1960–2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February–May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.01.051","usgsCitation":"Dudley, R.W., Hodgkins, G.A., McHale, M., Kolian, M., and Renard, B., 2017, Trends in snowmelt-related streamflow timing in the conterminous United States: Journal of Hydrology, v. 547, p. 208-221, https://doi.org/10.1016/j.jhydrol.2017.01.051.","productDescription":"14 p.","startPage":"208","endPage":"221","ipdsId":"IP-076605","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":469955,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.01.051","text":"Publisher Index Page"},{"id":356297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"547","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc6f5e4b0f5d57878ebad","contributors":{"authors":[{"text":"Dudley, Robert W. 0000-0002-0934-0568 rwdudley@usgs.gov","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":2223,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","email":"rwdudley@usgs.gov","middleInitial":"W.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolian, Michael J.","contributorId":177290,"corporation":false,"usgs":false,"family":"Kolian","given":"Michael J.","affiliations":[],"preferred":false,"id":669223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Renard, Benjamin","contributorId":177291,"corporation":false,"usgs":false,"family":"Renard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":669224,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198633,"text":"70198633 - 2017 - Geometry, mass balance and thinning at Eklutna Glacier, Alaska: an altitude-mass-balance feedback with implications for water resources","interactions":[],"lastModifiedDate":"2018-08-14T13:36:15","indexId":"70198633","displayToPublicDate":"2017-04-01T13:36:07","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Geometry, mass balance and thinning at Eklutna Glacier, Alaska: an altitude-mass-balance feedback with implications for water resources","docAbstract":"We analyzed glacier surface elevations (1957, 2010 and 2015) and surface mass-balance measurements (2008–2015) on the 30 km2 Eklutna Glacier, in the Chugach Mountains of southcentral Alaska. The geodetic mass balances from 1957 to 2010 and 2010 to 2015 are −0.52 ± 0.46 and −0.74 ± 0.10 m w.e. a−1, respectively. The glaciological mass balance of −0.73 m w.e. a−1 from 2010 to 2015 is indistinguishable from the geodetic value. Even after accounting for loss of firn in the accumulation zone, we found most of the mass loss over both time periods was from a broad, low-slope basin that includes much of the accumulation zone of the main branch. Ice-equivalent surface elevation changes in the basin were −1.0 ± 0.8 m a−1 from 1957 to 2010, and −0.6 ± 0.1 m a−1 from 2010 to 2015, shifting the glacier hypsometry downward and resulting in more negative mass balances: an altitude-mass-balance feedback. Net mass loss from Eklutna Glacier accounts for 7 ± 1% of the average inflow to Eklutna Reservoir, which is entirely used for water and power by Anchorage, Alaska's largest city. If the altitude-mass-balance feedback continues, this ‘deglaciation discharge dividend’ is likely to increase over the short-term before it eventually decreases due to diminishing glacier area.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/jog.2016.146","usgsCitation":"Sass, L., Loso, M.G., Geck, J., Thoms, E., and Mcgrath, D., 2017, Geometry, mass balance and thinning at Eklutna Glacier, Alaska: an altitude-mass-balance feedback with implications for water resources: Journal of Glaciology, v. 63, no. 238, p. 343-354, https://doi.org/10.1017/jog.2016.146.","productDescription":"12 p.","startPage":"343","endPage":"354","ipdsId":"IP-075520","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":469956,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/jog.2016.146","text":"Publisher Index Page"},{"id":438399,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MP51CB","text":"USGS data release","linkHelpText":"Point Measurements of Surface Mass Balance, Eklutna Glacier, Alaska, 2008-2015"},{"id":356437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Eklutna Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.07485961914062,\n 61.16824528169757\n ],\n [\n -148.91006469726562,\n 61.16824528169757\n ],\n [\n -148.91006469726562,\n 61.28425704516601\n ],\n [\n -149.07485961914062,\n 61.28425704516601\n ],\n [\n -149.07485961914062,\n 61.16824528169757\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"63","issue":"238","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-25","publicationStatus":"PW","scienceBaseUri":"5b98a463e4b0702d0e84307f","contributors":{"authors":[{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":742299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loso, Michael G.","contributorId":146361,"corporation":false,"usgs":false,"family":"Loso","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":742300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geck, Jason","contributorId":177441,"corporation":false,"usgs":false,"family":"Geck","given":"Jason","email":"","affiliations":[],"preferred":false,"id":742301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thoms, Evan 0000-0002-8945-613X ethoms@usgs.gov","orcid":"https://orcid.org/0000-0002-8945-613X","contributorId":206949,"corporation":false,"usgs":true,"family":"Thoms","given":"Evan","email":"ethoms@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":742302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mcgrath, Daniel 0000-0002-9462-6842 dmcgrath@usgs.gov","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":145635,"corporation":false,"usgs":true,"family":"Mcgrath","given":"Daniel","email":"dmcgrath@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":742303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261469,"text":"70261469 - 2017 - Global nonfuel mineral exploration trends 2001-2015","interactions":[],"lastModifiedDate":"2024-12-11T17:05:53.664076","indexId":"70261469","displayToPublicDate":"2017-04-01T11:03:06","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2755,"text":"Mining Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Global nonfuel mineral exploration trends 2001-2015","docAbstract":"This review summarizes significant exploration trends related to active sites and budgets, mineral commodities and regional factors for the years 2001-2015. Data were compiled by specialists in the USGS-NMIC, and reported annually in the USGS-NMIC Minerals Yearbook series and in the May issue of Mining Engineering magazine. External data for these analyses were derived from industry sources, published literature, and SNL Metals & Mining, an offering of S&P Global Market Intelligence (New York, NY).","language":"English","publisher":"Society for Mining, Metallurgy, & Exploration","usgsCitation":"Karl, N.A., and Wilburn, D.R., 2017, Global nonfuel mineral exploration trends 2001-2015: Mining Engineering, v. 69, no. 4, p. 30-37.","productDescription":"8 p.","startPage":"30","endPage":"37","ipdsId":"IP-081372","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":464991,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://me.smenet.org/abstract.cfm?preview=1&articleID=7496&page=30"},{"id":465022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"69","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Karl, Nick A 0000-0003-2858-2498","orcid":"https://orcid.org/0000-0003-2858-2498","contributorId":246006,"corporation":false,"usgs":true,"family":"Karl","given":"Nick","email":"","middleInitial":"A","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":920666,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193709,"text":"70193709 - 2017 - Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation","interactions":[],"lastModifiedDate":"2017-11-29T16:10:58","indexId":"70193709","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2776,"text":"Molecular Ecology Resources","active":true,"publicationSubtype":{"id":10}},"title":"Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation","docAbstract":"Environmental DNA (eDNA) can be used as an assessment tool to detect populations of threatened species and provide fine-scale data required to make management decisions. The objectives of this project were to use quantitative PCR (qPCR) to: (i) detect spiked salamander DNA in soil, (ii) quantify eDNA degradation over time, (iii) determine detectability of salamander eDNA in a terrestrial environment using soil, faeces, and skin swabs, (iv) detect salamander eDNA in a mesocosm experiment. Salamander eDNA was positively detected in 100% of skin swabs and 66% of faecal samples and concentrations did not differ between the two sources. However, eDNA was not detected in soil samples collected from directly underneath wild-caught living salamanders. Salamander genomic DNA (gDNA) was detected in all qPCR reactions when spiked into soil at 10.0, 5.0, and 1.0 ng/g soil and spike concentration had a significant effect on detected concentrations. Only 33% of samples showed recoverable eDNA when spiked with 0.25 ng/g soil, which was the low end of eDNA detection. To determine the rate of eDNA degradation, gDNA (1 ng/g soil) was spiked into soil and quantified over seven days. Salamander eDNA concentrations decreased across days, but eDNA was still amplifiable at day 7. Salamander eDNA was detected in two of 182 mesocosm soil samples over 12 weeks (n = 52 control samples; n = 65 presence samples; n = 65 eviction samples). The discrepancy in detection success between experiments indicates the potential challenges for this method to be used as a monitoring technique for small-bodied wild terrestrial salamander populations.
","language":"English","publisher":"Wiley","doi":"10.1111/1755-0998.12667","usgsCitation":"Walker, D.M., Leys, J.E., Dunham, K.E., Oliver, J.C., Schiller, E.E., Stephenson, K.S., Kimrey, J.T., Wooten, J., and Rogers, M.W., 2017, Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation: Molecular Ecology Resources, v. 17, no. 6, p. 1223-1230, https://doi.org/10.1111/1755-0998.12667.","productDescription":"8 p.","startPage":"1223","endPage":"1230","ipdsId":"IP-080810","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-11","publicationStatus":"PW","scienceBaseUri":"5a003150e4b0531197b5a748","contributors":{"authors":[{"text":"Walker, Donald M.","contributorId":39132,"corporation":false,"usgs":false,"family":"Walker","given":"Donald","email":"","middleInitial":"M.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leys, Jacob E.","contributorId":199800,"corporation":false,"usgs":false,"family":"Leys","given":"Jacob","email":"","middleInitial":"E.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Kelly E.","contributorId":169093,"corporation":false,"usgs":false,"family":"Dunham","given":"Kelly","email":"","middleInitial":"E.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Joshua C.","contributorId":199613,"corporation":false,"usgs":false,"family":"Oliver","given":"Joshua","email":"","middleInitial":"C.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schiller, Emily E.","contributorId":145533,"corporation":false,"usgs":false,"family":"Schiller","given":"Emily","email":"","middleInitial":"E.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephenson, Kelsey S.","contributorId":100992,"corporation":false,"usgs":false,"family":"Stephenson","given":"Kelsey","email":"","middleInitial":"S.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720394,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kimrey, John T.","contributorId":199571,"corporation":false,"usgs":false,"family":"Kimrey","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":35244,"text":"Tennessee Technological University","active":true,"usgs":false}],"preferred":false,"id":720395,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wooten, Jessica","contributorId":190940,"corporation":false,"usgs":false,"family":"Wooten","given":"Jessica","email":"","affiliations":[{"id":35654,"text":"Centre College, Danville, KY, USA","active":true,"usgs":false}],"preferred":false,"id":720396,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720397,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70193130,"text":"70193130 - 2017 - Groundwater conditions in Utah, Spring of 2017","interactions":[],"lastModifiedDate":"2019-05-21T13:31:27","indexId":"70193130","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":110,"text":"Cooperative Investigations Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"58","title":"Groundwater conditions in Utah, Spring of 2017","docAbstract":"This is the fifty-fourth in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions.
This report, like the others in the series, contains information on well construction, groundwater withdrawals from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to new wells constructed for withdrawal of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available.
This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2016. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at http://www.waterrights.utah.gov/techinfo/ and http://ut.water.usgs.gov/publications/GW2017.pdf.
Groundwater conditions in Utah for calendar year 2015 are reported in Burden and others (2016) and are available online at http://ut.water.usgs.gov/publications/GW2016.pdf.
","language":"English","publisher":"Utah Department of Natural Resources","usgsCitation":"Burden, C.B., 2017, Groundwater conditions in Utah, Spring of 2017: Cooperative Investigations Report 58, x, 118 p.","productDescription":"x, 118 p.","numberOfPages":"132","ipdsId":"IP-084773","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":350081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364057,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://waterrights.utah.gov/techinfo/wwwpub/GW2017.pdf"}],"country":"United 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\"}}]}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fbeee4b06e28e9c237a6","contributors":{"authors":[{"text":"Burden, Carole B. cburden@usgs.gov","contributorId":852,"corporation":false,"usgs":true,"family":"Burden","given":"Carole","email":"cburden@usgs.gov","middleInitial":"B.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718085,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70194067,"text":"70194067 - 2017 - Multiple models guide strategies for agricultural nutrient reductions","interactions":[],"lastModifiedDate":"2018-02-06T11:48:12","indexId":"70194067","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the 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Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.","language":"English","publisher":"Wiley","doi":"10.1002/fee.1472","usgsCitation":"Scavia, D., Kalcic, M., Muenich, R.L., Read, J., Aloysius, N., Bertani, I., Boles, C., Confesor, R., DePinto, J., Gildow, M., Martin, J., Redder, T., Robertson, D.M., Sowa, S.P., Wang, Y., and Yen, H., 2017, Multiple models guide strategies for agricultural nutrient reductions: Frontiers in Ecology and the Environment, v. 15, no. 3, p. 126-132, https://doi.org/10.1002/fee.1472.","productDescription":"7 p.","startPage":"126","endPage":"132","ipdsId":"IP-075287","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":461665,"rank":0,"type":{"id":41,"text":"Open Access 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Throughout the nesting season, nests are naturally disturbed by newly nesting females, resulting in egg breakage and loss of some nest viability. This environment is ideal for the growth and proliferation of microorganisms. The range of bacterial flora present in beach sand and egg shells was examined, with emphasis on bacteria that may pose a threat to public and animal health. The extent to which the bacterial load and genera on the beach changed throughout the season was also assessed. Twenty-five genera were identified, with Pseudomonas spp. found to be the most predominant environmental bacteria. Four genera identified possess zoonotic potential, while five additional genera are known to be of public and animal health significance. Distinct shifts in the density and distribution of bacteria were observed along the beach from early to peak nesting season. Shifts were seen across heavily traversed zones, thus highlighting the potential exposure threats posed to beach visitors and animals alike. Further studies aimed at speciating this population of bacteria, as well as isolating potential fungal pathogens may mitigate this threat. Identification of bacterial agents that are specifically pathogenic to leatherback turtles, turtle eggs, hatchlings and those who may interact with these animals will serve to enhance and guide efforts to better conserve this species and protect the health of all who visit this ecologically significant site.
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Chandrashekhar","contributorId":91788,"corporation":false,"usgs":false,"family":"Unakal","given":"Chandrashekhar","email":"","affiliations":[{"id":35671,"text":"The University of the West Indies","active":true,"usgs":false}],"preferred":false,"id":720568,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dziva, Francis","contributorId":198477,"corporation":false,"usgs":false,"family":"Dziva","given":"Francis","email":"","affiliations":[{"id":35671,"text":"The University of the West Indies","active":true,"usgs":false}],"preferred":false,"id":720567,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Holder, Ridley","contributorId":198495,"corporation":false,"usgs":false,"family":"Holder","given":"Ridley","email":"","affiliations":[{"id":35671,"text":"The University of the West Indies","active":true,"usgs":false}],"preferred":false,"id":720569,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Carthy, Raymond R. 0000-0001-8978-5083 rayc@usgs.gov","orcid":"https://orcid.org/0000-0001-8978-5083","contributorId":3685,"corporation":false,"usgs":true,"family":"Carthy","given":"Raymond","email":"rayc@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720570,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70191950,"text":"70191950 - 2017 - Earning their stripes: The potential of tiger trout and other salmonids as biological controls of forage fishes in a western reservoir","interactions":[],"lastModifiedDate":"2017-10-19T11:32:22","indexId":"70191950","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Earning their stripes: The potential of tiger trout and other salmonids as biological controls of forage fishes in a western reservoir","docAbstract":"Maintaining a balance between predator and prey populations can be an ongoing challenge for fisheries managers, especially in managing artificial ecosystems such as reservoirs. In a high-elevation Utah reservoir, the unintentional introduction of the Utah Chub Gila atraria and its subsequent population expansion prompted managers to experimentally shift from exclusively stocking Rainbow Trout Oncorhynchus mykiss to also stocking tiger trout (female Brown Trout Salmo trutta × male Brook Trout Salvelinus fontinalis) and Bonneville Cutthroat Trout O. clarkii utah (hereafter, Cutthroat Trout) as potential biological control agents. We measured a combination of diet, growth, temperature, and abundance and used bioenergetic simulations to quantify predator demand versus prey supply. Utah Chub were the predominant prey type for tiger trout, contributing up to 80% of the diet depending on the season. Utah Chub represented up to 70% of the total diet consumed by Cutthroat Trout. Although Utah Chub dominated the fish biomass in the reservoir, we still estimated abundances of 238,000 tiger trout, 214,000 Cutthroat Trout, and 55,000 Rainbow Trout. Consequently, when expanded to the population level of each predator, tiger trout and Cutthroat Trout consumed large quantities of Utah Chub on an annual basis: tiger trout consumed 508,000 kg (2,660 g/predator) of the standing prey population, and Cutthroat Trout consumed an estimated 322,000 kg (1,820 g/predator). The estimated combined consumption by Cutthroat Trout and tiger trout exceeded the estimate of Utah Chub annual production. As such, our results suggest that the high rates of piscivory exhibited by Cutthroat Trout and tiger trout in artificial lentic ecosystems are likely sufficient to effectively reduce the overall abundance of forage fishes and to prevent forage fishes from dominating fish assemblages. Collectively, this research provides the first documented findings on tiger trout ecology and performance, which will aid managers in designing and implementing the best stocking strategy to optimize sport fish performance, control undesirable forage fish, and enhance and maintain angler satisfaction.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2016.1264509","usgsCitation":"Winters, L.K., Budy, P., and Thiede, G.P., 2017, Earning their stripes: The potential of tiger trout and other salmonids as biological controls of forage fishes in a western reservoir: North American Journal of Fisheries Management, v. 37, no. 2, p. 380-394, https://doi.org/10.1080/02755947.2016.1264509.","productDescription":"15 p.","startPage":"380","endPage":"394","ipdsId":"IP-074773","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Scofield Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.1952018737793,\n 39.74045836300404\n ],\n [\n -111.11160278320312,\n 39.74045836300404\n ],\n [\n -111.11160278320312,\n 39.819743927696756\n ],\n [\n -111.1952018737793,\n 39.819743927696756\n ],\n [\n -111.1952018737793,\n 39.74045836300404\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-08","publicationStatus":"PW","scienceBaseUri":"59e9b995e4b05fe04cd65c9f","contributors":{"authors":[{"text":"Winters, Lisa K.","contributorId":171640,"corporation":false,"usgs":false,"family":"Winters","given":"Lisa","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":713773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":713772,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thiede, Gary P.","contributorId":9154,"corporation":false,"usgs":true,"family":"Thiede","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":713774,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188346,"text":"70188346 - 2017 - Microbial methane from in situ biodegradation of coal and shale: A review and reevaluation of hydrogen and carbon isotope signatures","interactions":[],"lastModifiedDate":"2017-06-06T16:08:28","indexId":"70188346","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Microbial methane from in situ biodegradation of coal and shale: A review and reevaluation of hydrogen and carbon isotope signatures","docAbstract":"Stable carbon and hydrogen isotope signatures of methane, water, and inorganic carbon are widely utilized in natural gas systems for distinguishing microbial and thermogenic methane and for delineating methanogenic pathways (acetoclastic, hydrogenotrophic, and/or methylotrophic methanogenesis). Recent studies of coal and shale gas systems have characterized in situ microbial communities and provided stable isotope data (δD-CH4, δD-H2O, δ13C-CH4, and δ13C-CO2) from a wider range of environments than available previously. Here we review the principal biogenic methane-yielding pathways in coal beds and shales and the isotope effects imparted on methane, document the uncertainties and inconsistencies in established isotopic fingerprinting techniques, and identify the knowledge gaps in understanding the subsurface processes that govern H and C isotope signatures of biogenic methane. We also compare established isotopic interpretations with recent microbial community characterization techniques, which reveal additional inconsistencies in the interpretation of microbial metabolic pathways in coal beds and shales. Collectively, the re-assessed data show that widely-utilized isotopic fingerprinting techniques neglect important complications in coal beds and shales.
Isotopic fingerprinting techniques that combine δ13C-CH4 with δD-CH4 and/or δ13C-CO2have significant limitations: (1) The consistent ~ 160‰ offset between δD-H2O and δD-CH4 could imply that hydrogenotrophic methanogenesis is the dominant metabolic pathway in microbial gas systems. However, hydrogen isotopes can equilibrate between methane precursors and coexisting water, yielding a similar apparent H isotope signal as hydrogenotrophic methanogenesis, regardless of the actual methane formation pathway. (2) Non-methanogenic processes such as sulfate reduction, Fe oxide reduction, inputs of thermogenic methane, anaerobic methane oxidation, and/or formation water interaction can cause the apparent carbon isotope fractionation between δ13C-CH4 and δ13C-CO2(α13CCO2-CH4) to differ from the true methanogenic fractionation, complicating interpretation of methanogenic pathways. (3) Where little-fractionating non-methanogenic bacterial processes compete with highly-fractionating methanogenesis, the mass balance between CH4 and CO2 is affected. This has implications for δ13C values and provides an alternative interpretation for net C isotope signatures than solely the pathways used by active methanogens. (4) While most of the reviewed values of δD-H2O - δD-CH4 and α13CCO2-CH4 are apparently consistent with hydrogenotrophic methanogenesis as the dominant pathway in coal beds and shales, recent microbial community characterization techniques suggest a possible role for acetoclastic or methylotrophic methanogenesis in some basins.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.01.027","usgsCitation":"Vinson, D.S., Blair, N.E., Martini, A.M., Larter, S., Orem, W.H., and McIntosh, J.C., 2017, Microbial methane from in situ biodegradation of coal and shale: A review and reevaluation of hydrogen and carbon isotope signatures: Chemical Geology, v. 453, p. 128-145, https://doi.org/10.1016/j.chemgeo.2017.01.027.","productDescription":"18 p.","startPage":"128","endPage":"145","ipdsId":"IP-073590","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469977,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2017.01.027","text":"Publisher Index Page"},{"id":342186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"453","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2de4b0f6c2d0d9c756","contributors":{"authors":[{"text":"Vinson, David S.","contributorId":172390,"corporation":false,"usgs":false,"family":"Vinson","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":25392,"text":"Department of Geography and Earth Science, University of North Carolina at Charlotte, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":697341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blair, Neal E.","contributorId":192674,"corporation":false,"usgs":false,"family":"Blair","given":"Neal","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":697342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martini, Anna M.","contributorId":192675,"corporation":false,"usgs":false,"family":"Martini","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":35249,"text":"Department of Geology, Amherst College","active":true,"usgs":false}],"preferred":false,"id":697343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larter, Steve","contributorId":192676,"corporation":false,"usgs":false,"family":"Larter","given":"Steve","email":"","affiliations":[],"preferred":false,"id":697344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":697340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McIntosh, Jennifer C.","contributorId":139870,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":13301,"text":"Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona","active":true,"usgs":false}],"preferred":false,"id":697345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70194199,"text":"70194199 - 2017 - Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area","interactions":[],"lastModifiedDate":"2018-01-12T15:20:13","indexId":"70194199","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area","docAbstract":"Drought events are increasing globally, and reports of consequent forest mortality are widespread. However, due to a lack of a quantitative global synthesis, it is still not clear whether drought-induced mortality rates differ among global biomes and whether functional traits influence the risk of drought-induced mortality. To address these uncertainties, we performed a global meta-analysis of 58 studies of drought-induced forest mortality. Mortality rates were modelled as a function of drought, temperature, biomes, phylogenetic and functional groups and functional traits. We identified a consistent global-scale response, where mortality increased with drought severity [log mortality (trees trees−1 year−1) increased 0.46 (95% CI = 0.2–0.7) with one SPEI unit drought intensity]. We found no significant differences in the magnitude of the response depending on forest biomes or between angiosperms and gymnosperms or evergreen and deciduous tree species. Functional traits explained some of the variation in drought responses between species (i.e. increased from 30 to 37% when wood density and specific leaf area were included). Tree species with denser wood and lower specific leaf area showed lower mortality responses. Our results illustrate the value of functional traits for understanding patterns of drought-induced tree mortality and suggest that mortality could become increasingly widespread in the future.
","language":"English","publisher":"Wiley","doi":"10.1111/ele.12748","usgsCitation":"Greenwood, S., Ruiz-Benito, P., Martínez-Vilalta, J., Lloret, F., Kitzberger, T., Allen, C.D., Fensham, R., Laughlin, D.C., Kattge, J., Bonisch, G., Kraft, N.J., and Jump, A.S., 2017, Tree mortality across biomes is promoted by drought intensity, lower wood density and higher specific leaf area: Ecology Letters, v. 20, no. 4, p. 539-553, https://doi.org/10.1111/ele.12748.","productDescription":"15 p.","startPage":"539","endPage":"553","ipdsId":"IP-080072","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":469957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.12748","text":"Publisher Index Page"},{"id":349077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-21","publicationStatus":"PW","scienceBaseUri":"5a60fbede4b06e28e9c2379b","contributors":{"authors":[{"text":"Greenwood, Sarah","contributorId":200537,"corporation":false,"usgs":false,"family":"Greenwood","given":"Sarah","email":"","affiliations":[],"preferred":false,"id":722619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruiz-Benito, Paloma","contributorId":200538,"corporation":false,"usgs":false,"family":"Ruiz-Benito","given":"Paloma","email":"","affiliations":[],"preferred":false,"id":722620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martínez-Vilalta, Jordi","contributorId":182016,"corporation":false,"usgs":false,"family":"Martínez-Vilalta","given":"Jordi","affiliations":[],"preferred":false,"id":722621,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lloret, Francisco","contributorId":181986,"corporation":false,"usgs":false,"family":"Lloret","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":722622,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kitzberger, Thomas","contributorId":181980,"corporation":false,"usgs":false,"family":"Kitzberger","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":722623,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":722618,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fensham, Rod","contributorId":200542,"corporation":false,"usgs":false,"family":"Fensham","given":"Rod","email":"","affiliations":[],"preferred":false,"id":722624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Laughlin, Daniel C.","contributorId":200543,"corporation":false,"usgs":false,"family":"Laughlin","given":"Daniel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":722625,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kattge, Jens","contributorId":200544,"corporation":false,"usgs":false,"family":"Kattge","given":"Jens","email":"","affiliations":[],"preferred":false,"id":722626,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bonisch, Gerhard","contributorId":200545,"corporation":false,"usgs":false,"family":"Bonisch","given":"Gerhard","email":"","affiliations":[],"preferred":false,"id":722627,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kraft, Nathan J. B.","contributorId":190203,"corporation":false,"usgs":false,"family":"Kraft","given":"Nathan","email":"","middleInitial":"J. B.","affiliations":[],"preferred":false,"id":722628,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jump, Alistair S.","contributorId":200547,"corporation":false,"usgs":false,"family":"Jump","given":"Alistair","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":722629,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70187329,"text":"70187329 - 2017 - A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations","interactions":[],"lastModifiedDate":"2017-04-28T15:43:43","indexId":"70187329","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations","docAbstract":"Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/690444","usgsCitation":"Ward, A.S., Kelleher, C.A., Mason, S.J., Wagener, T., McIntyre, N., McGlynn, B.L., Runkel, R.L., and Payn, R.A., 2017, A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations: Freshwater Science, v. 36, no. 1, p. 195-217, https://doi.org/10.1086/690444.","productDescription":"23 p.","startPage":"195","endPage":"217","ipdsId":"IP-074821","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":461661,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/2ec1a71e-046a-4faa-ad85-2f323af51119","text":"External Repository"},{"id":340632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590454a1e4b022cee40dc222","contributors":{"authors":[{"text":"Ward, Adam S.","contributorId":11508,"corporation":false,"usgs":true,"family":"Ward","given":"Adam","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelleher, Christa A.","contributorId":46417,"corporation":false,"usgs":true,"family":"Kelleher","given":"Christa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Seth J. K.","contributorId":191535,"corporation":false,"usgs":false,"family":"Mason","given":"Seth","email":"","middleInitial":"J. K.","affiliations":[],"preferred":false,"id":693395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagener, Thorsten","contributorId":176323,"corporation":false,"usgs":false,"family":"Wagener","given":"Thorsten","email":"","affiliations":[],"preferred":false,"id":693396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntyre, Neil","contributorId":191602,"corporation":false,"usgs":false,"family":"McIntyre","given":"Neil","email":"","affiliations":[],"preferred":false,"id":693397,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGlynn, Brian L.","contributorId":83012,"corporation":false,"usgs":true,"family":"McGlynn","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693398,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693392,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Payn, Robert A.","contributorId":36461,"corporation":false,"usgs":true,"family":"Payn","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693399,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187327,"text":"70187327 - 2017 - A decade of insights into grassland ecosystem responses to global environmental change","interactions":[],"lastModifiedDate":"2017-04-28T15:36:26","indexId":"70187327","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5263,"text":"Nature Ecology & Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A decade of insights into grassland ecosystem responses to global environmental change","docAbstract":"Earth’s biodiversity and carbon uptake by plants, or primary productivity, are intricately interlinked, underlie many essential ecosystem processes, and depend on the interplay among environmental factors, many of which are being changed by human activities. While ecological theory generalizes across taxa and environments, most empirical tests of factors controlling diversity and productivity have been observational, single-site experiments, or meta-analyses, limiting our understanding of variation among site-level responses and tests of general mechanisms. A synthesis of results from ten years of a globally distributed, coordinated experiment, the Nutrient Network (NutNet), demonstrates that species diversity promotes ecosystem productivity and stability, and that nutrient supply and herbivory control diversity via changes in composition, including invasions of non-native species and extinction of native species. Distributed experimental networks are a powerful tool for tests and integration of multiple theories and for generating multivariate predictions about the effects of global changes on future ecosystems.","language":"English","publisher":"Nature","doi":"10.1038/s41559-017-0118","usgsCitation":"Borer, E.T., Grace, J.B., Harpole, W., MacDougall, A.S., and Seabloom, E.W., 2017, A decade of insights into grassland ecosystem responses to global environmental change: Nature Ecology & Evolution, v. 1, Article 0118, https://doi.org/10.1038/s41559-017-0118.","productDescription":"Article 0118","ipdsId":"IP-080267","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":340631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-20","publicationStatus":"PW","scienceBaseUri":"590454a1e4b022cee40dc224","contributors":{"authors":[{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":693343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":693342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpole, W. 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Stanley","affiliations":[{"id":12468,"text":"Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":693344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDougall, Andrew S.","contributorId":39509,"corporation":false,"usgs":true,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":693346,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192945,"text":"70192945 - 2017 - Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration","interactions":[],"lastModifiedDate":"2025-12-23T14:37:28.701523","indexId":"70192945","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration","docAbstract":"Regional classification of streams is an early step in the Ecological Limits of Hydrologic Alteration framework. Many stream classifications are based on an inductive approach using hydrologic data from minimally disturbed basins, but this approach may underrepresent streams from heavily disturbed basins or sparsely gaged arid regions. An alternative is a deductive approach, using watershed climate, land use, and geomorphology to classify streams, but this approach may miss important hydrological characteristics of streams. We classified all stream reaches in California using both approaches. First, we used Bayesian and hierarchical clustering to classify reaches according to watershed characteristics. Streams were clustered into seven classes according to elevation, sedimentary rock, and winter precipitation. Permutation-based analysis of variance and random forest analyses were used to determine which hydrologic variables best separate streams into their respective classes. Stream typology (i.e., the class that a stream reach is assigned to) is shaped mainly by patterns of high and mean flow behavior within the stream's landscape context. Additionally, random forest was used to determine which hydrologic variables best separate minimally disturbed reference streams from non-reference streams in each of the seven classes. In contrast to stream typology, deviation from reference conditions is more difficult to detect and is largely defined by changes in low-flow variables, average daily flow, and duration of flow. Our combined deductive/inductive approach allows us to estimate flow under minimally disturbed conditions based on the deductive analysis and compare to measured flow based on the inductive analysis in order to estimate hydrologic change.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1802","usgsCitation":"Pyne, M.I., Carlisle, D.M., Konrad, C.P., and Stein, E.D., 2017, Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration: Ecohydrology, v. 10, no. 3, e1802, 14 p; Data Release, https://doi.org/10.1002/eco.1802.","productDescription":"e1802, 14 p; Data Release","ipdsId":"IP-073147","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":348846,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9MJ7","text":"USGS data release","description":"USGS data release","linkHelpText":"Select watershed attributes for California stream segments (NHDPlus V.1)"},{"id":348662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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