Fidelity to spawning habitats can maximise reproductive success of fish by synchronising movements to sites of previous recruitment. To determine the role of reproductive fidelity in structuring walleye Sander vitreus populations in the Laurentian Great Lakes, we used acoustic telemetry combined with Cormack–Jolly–Seber capture–recapture models to estimate spawning site fidelity and apparent annual survival for the Tittabawassee River in Lake Huron and Maumee River in Lake Erie. Walleye in spawning condition were tagged from the Tittabawassee River in Lake Huron and Maumee River in Lake Erie in 2011–2012. Site fidelity and apparent annual survival were estimated from return of individuals to the stream where tagged. Site fidelity estimates were higher in the Tittabawassee River (95%) than the Maumee River (70%) and were not related to sex or fish length at tagging. Apparent annual survival of walleye tagged in the Tittabawassee did not differ among spawning seasons but was higher for female than male walleye and decreased linearly as fish length increased. Apparent annual survival of walleye tagged in the Maumee River did not differ among spawning seasons but was higher for female walleye than male walleye and increased linearly as fish length increased. Greater fidelity of walleye tagged in the Tittabawassee River than walleye tagged in the Maumee River may be related to the close proximity to the Maumee River of other spawning aggregations and multiple spawning sites in Lake Erie. As spawning site fidelity increases, management actions to conserve population structure require an increasing focus on individual stocks.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12350","usgsCitation":"Hayden, T.A., Binder, T., Holbrook, C., Vandergoot, C., Fielder, D.G., Cooke, S., Dettmers, J.M., and Krueger, C., 2018, Spawning site fidelity and apparent annual survival of walleye (Sander vitreus) differ between a Lake Huron and Lake Erie tributary: Ecology of Freshwater Fish, v. 27, no. 1, p. 339-349, https://doi.org/10.1111/eff.12350.","productDescription":"11 p.","startPage":"339","endPage":"349","ipdsId":"IP-083488","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469201,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12350","text":"Publisher Index Page"},{"id":340180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie, Lake Huron","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.5,\n 43.4\n ],\n [\n -83,\n 43.4\n ],\n [\n -83,\n 44.2\n ],\n [\n -84.5,\n 44.2\n ],\n [\n -84.5,\n 43.4\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.7,\n 41.55\n ],\n [\n -83.3,\n 41.55\n ],\n [\n -83.3,\n 41.75\n ],\n [\n -83.7,\n 41.75\n ],\n [\n -83.7,\n 41.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-19","publicationStatus":"PW","scienceBaseUri":"58ff0e9be4b006455f2d61b0","contributors":{"authors":[{"text":"Hayden, Todd A. 0000-0002-0451-0425 thayden@usgs.gov","orcid":"https://orcid.org/0000-0002-0451-0425","contributorId":5987,"corporation":false,"usgs":true,"family":"Hayden","given":"Todd","email":"thayden@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":692498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binder, Thomas 0000-0001-9266-9120 tbinder@usgs.gov","orcid":"https://orcid.org/0000-0001-9266-9120","contributorId":4958,"corporation":false,"usgs":true,"family":"Binder","given":"Thomas","email":"tbinder@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":692499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":692500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":692501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fielder, David G.","contributorId":127528,"corporation":false,"usgs":false,"family":"Fielder","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":692502,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":692503,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dettmers, John M.","contributorId":191256,"corporation":false,"usgs":false,"family":"Dettmers","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":692504,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krueger, Charles C.","contributorId":67821,"corporation":false,"usgs":false,"family":"Krueger","given":"Charles C.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":692505,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186978,"text":"70186978 - 2018 - Rapid evolution meets invasive species control: The potential for pesticide resistance in sea lamprey","interactions":[],"lastModifiedDate":"2018-01-05T14:40:09","indexId":"70186978","displayToPublicDate":"2017-04-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Rapid evolution meets invasive species control: The potential for pesticide resistance in sea lamprey","docAbstract":"Rapid evolution of pest, pathogen and wildlife populations can have undesirable effects; for example, when insects evolve resistance to pesticides or fishes evolve smaller body size in response to harvest. A destructive invasive species in the Laurentian Great Lakes, the sea lamprey (Petromyzon marinus) has been controlled with the pesticide 3-trifluoromethyl-4-nitrophenol (TFM) since the 1950s. We evaluated the likelihood of sea lamprey evolving resistance to TFM by (1) reviewing sea lamprey life history and control; (2) identifying physiological and behavioural resistance strategies; (3) estimating the strength of selection from TFM; (4) assessing the timeline for evolution; and (5) analyzing historical toxicity data for evidence of resistance. The number of sea lamprey generations exposed to TFM was within the range observed for fish populations where rapid evolution has occurred. Mortality from TFM was estimated as 82-90%, suggesting significant selective pressure. However, 57 years of toxicity data revealed no increase in lethal concentrations of TFM. Vigilance and the development of alternative controls are required to prevent this aquatic invasive species from evolving strategies to evade control.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2017-0015","usgsCitation":"Dunlop, E.S., McLaughlin, R.L., Adams, J.V., Jones, M., Birceanu, O., Christie, M.R., Criger, L.A., Hinderer, J., Hollingworth, R.M., Johnson, N., Lantz, S.R., Li, W., Miller, J.R., Morrison, B.J., Mota-Sanchez, D., Muir, A.M., Sepulveda, M.S., Steeves, T.B., Walter, L., Westman, E., Wirgin, I., and Wilkie, M.P., 2018, Rapid evolution meets invasive species control: The potential for pesticide resistance in sea lamprey: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 1, p. 152-168, https://doi.org/10.1139/cjfas-2017-0015.","productDescription":"17 p.","startPage":"152","endPage":"168","ipdsId":"IP-071542","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":469202,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2017-0015","text":"Publisher Index 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Guelph","active":true,"usgs":false}],"preferred":false,"id":691630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":691628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Michael L.","contributorId":7219,"corporation":false,"usgs":false,"family":"Jones","given":"Michael L.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":691631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Birceanu, 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Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":691639,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Miller, James R.","contributorId":191040,"corporation":false,"usgs":false,"family":"Miller","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":691640,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Morrison, Bruce J.","contributorId":150824,"corporation":false,"usgs":false,"family":"Morrison","given":"Bruce","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":691641,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mota-Sanchez, 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Centre","active":true,"usgs":false}],"preferred":false,"id":691645,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Walter, Lisa","contributorId":191043,"corporation":false,"usgs":false,"family":"Walter","given":"Lisa","email":"","affiliations":[],"preferred":false,"id":691646,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Westman, Erin","contributorId":191044,"corporation":false,"usgs":false,"family":"Westman","given":"Erin","email":"","affiliations":[],"preferred":false,"id":691647,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Wirgin, Isaac","contributorId":138929,"corporation":false,"usgs":false,"family":"Wirgin","given":"Isaac","affiliations":[{"id":12583,"text":"New York University School of Medicine Tuxedo, New York, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":691648,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wilkie, Michael P.","contributorId":191045,"corporation":false,"usgs":false,"family":"Wilkie","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":691649,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}} ,{"id":70216316,"text":"70216316 - 2018 - Interoperability in planetary research for geospatial data analysis","interactions":[],"lastModifiedDate":"2020-11-11T15:52:00.197038","indexId":"70216316","displayToPublicDate":"2017-04-13T09:43:43","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3083,"text":"Planetary and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Interoperability in planetary research for geospatial data analysis","docAbstract":"For more than a decade there has been a push in the planetary science community to support interoperable methods for accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics, digital elevation or terrain models, geologic maps, geographic location databases (e.g., craters, volcanoes) or any data that can be tied to the surface of a planetary body (including moons, comets or asteroids). Several U.S. and international cartographic research institutions have converged on mapping standards that embrace standardized geospatial image formats, geologic mapping conventions, U.S. Federal Geographic Data Committee (FGDC) cartographic and metadata standards, and notably on-line mapping services as defined by the Open Geospatial Consortium (OGC). The latter includes defined standards such as the OGC Web Mapping Services (simple image maps), Web Map Tile Services (cached image tiles), Web Feature Services (feature streaming), Web Coverage Services (rich scientific data streaming), and Catalog Services for the Web (data searching and discoverability). While these standards were developed for application to Earth-based data, they can be just as valuable for planetary domain. Another initiative, called VESPA (Virtual European Solar and Planetary Access), will marry several of the above geoscience standards and astronomy-based standards as defined by International Virtual Observatory Alliance (IVOA). This work outlines the current state of interoperability initiatives in use or in the process of being researched within the planetary geospatial community.
Belize contains important habitat for Antillean manatees (Trichechus manatus manatus) and provides refuge for the highest known population density of this subspecies. As these animals face impending threats, knowledge of their dietary habits can be used to interpret resource utilization. The contents of 13 mouth, 6 digestive tract (stomach, duodenum and colon), and 124 fecal samples were microscopically examined using a modified point technique detection protocol to identify key plant species consumed by manatees at two important aggregation sites in Belize: Southern Lagoon and the Drowned Cayes. Overall, 15 different items were identified in samples from manatees in Belize. Five species of seagrasses (Halodule wrightii, Thalassia testudinum, Ruppia maritima, Syringodium filiforme, and Halophila sp.) made up the highest percentage of items. The red mangrove (Rhizophora mangle), was also identified as an important food item. Algae (Ulva sp., Chara sp., Lyngbya sp.) and invertebrates (sponges and diatoms) were also consumed. Variation in the percentage of seagrasses, other vascular plants, and algae consumption was analyzed as a 4-factor analysis of variance (ANOVA) with main effects and interactions for locality, sex, size classification, and season. While sex and season did not influence diet composition, differences for locality and size classification were observed. These results suggest that analysis of diet composition of Antillean manatees may help to determine critical habitat and use of associated food resources which, in turn can be used to aid conservation efforts in Belize.
","language":"English","publisher":"Marine Biological Association of the United Kingdom","doi":"10.1017/S0025315417000182","usgsCitation":"Allen, A.C., Beck, C.A., Bonde, R.K., Powell, J.A., and Gomez, N.A., 2018, Diet of the Antillean manatee (Trichechus manatus manatus) in Belize, Central America: Journal of the Marine Biological Association of the United Kingdom, v. 98, no. 7, p. 1831-1840, https://doi.org/10.1017/S0025315417000182.","productDescription":"10 p.","startPage":"1831","endPage":"1840","ipdsId":"IP-078899","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469204,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0025315417000182","text":"Publisher Index Page"},{"id":339432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Belize","volume":"98","issue":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-03","publicationStatus":"PW","scienceBaseUri":"58e8a540e4b09da6799d639b","contributors":{"authors":[{"text":"Allen, Aarin Conrad","contributorId":139671,"corporation":false,"usgs":false,"family":"Allen","given":"Aarin","email":"","middleInitial":"Conrad","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":690339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beck, Cathy A. 0000-0002-5388-5418 cbeck@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-5418","contributorId":2919,"corporation":false,"usgs":true,"family":"Beck","given":"Cathy","email":"cbeck@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":690340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonde, Robert K. 0000-0001-9179-4376 rbonde@usgs.gov","orcid":"https://orcid.org/0000-0001-9179-4376","contributorId":2675,"corporation":false,"usgs":true,"family":"Bonde","given":"Robert","email":"rbonde@usgs.gov","middleInitial":"K.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":690338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, James A.","contributorId":190683,"corporation":false,"usgs":false,"family":"Powell","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":690341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gomez, Nicole Auil","contributorId":40465,"corporation":false,"usgs":true,"family":"Gomez","given":"Nicole","email":"","middleInitial":"Auil","affiliations":[],"preferred":false,"id":690342,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186327,"text":"70186327 - 2018 - Shallow bedrock limits groundwater seepage-based headwater climate refugia","interactions":[],"lastModifiedDate":"2018-02-14T14:34:38","indexId":"70186327","displayToPublicDate":"2017-04-04T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5362,"text":"Limnologica - Ecology and Management of Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Shallow bedrock limits groundwater seepage-based headwater climate refugia","docAbstract":"Groundwater/surface-water exchanges in streams are inexorably linked to adjacent aquifer dynamics. As surface-water temperatures continue to increase with climate warming, refugia created by groundwater connectivity is expected to enable cold water fish species to survive. The shallow alluvial aquifers that source groundwater seepage to headwater streams, however, may also be sensitive to seasonal and long-term air temperature dynamics. Depth to bedrock can directly influence shallow aquifer flow and thermal sensitivity, but is typically ill-defined along the stream corridor in steep mountain catchments. We employ rapid, cost-effective passive seismic measurements to evaluate the variable thickness of the shallow colluvial and alluvial aquifer sediments along a headwater stream supporting cold water-dependent brook trout (Salvelinus fontinalis) in Shenandoah National Park, VA, USA. Using a mean depth to bedrock of 2.6 m, numerical models predicted strong sensitivity of shallow aquifer temperature to the downward propagation of surface heat. The annual temperature dynamics (annual signal amplitude attenuation and phase shift) of potential seepage sourced from the shallow modeled aquifer were compared to several years of paired observed stream and air temperature records. Annual stream water temperature patterns were found to lag local air temperature by ∼8–19 d along the stream corridor, indicating that thermal exchange between the stream and shallow groundwater is spatially variable. Locations with greater annual signal phase lag were also associated with locally increased amplitude attenuation, further suggestion of year-round buffering of channel water temperature by groundwater seepage. Numerical models of shallow groundwater temperature that incorporate regional expected climate warming trends indicate that the summer cooling capacity of this groundwater seepage will be reduced over time, and lower-elevation stream sections may no longer serve as larger-scale climate refugia for cold water fish species, even with strong groundwater discharge.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.limno.2017.02.005","usgsCitation":"Briggs, M.A., Lane, J.W., Snyder, C.D., White, E.A., Johnson, Z., Nelms, D.L., and Hitt, N.P., 2018, Shallow bedrock limits groundwater seepage-based headwater climate refugia: Limnologica - Ecology and Management of Inland Waters, v. 68, p. 142-156, https://doi.org/10.1016/j.limno.2017.02.005.","productDescription":"15 p.","startPage":"142","endPage":"156","ipdsId":"IP-081517","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":469205,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.limno.2017.02.005","text":"Publisher Index Page"},{"id":438092,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IJMGIB","text":"USGS data release","linkHelpText":"Passive seismic data collected along headwater stream corridors in Shenandoah National Park in 2016 - 2020"},{"id":438091,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JW8C04","text":"USGS data release","linkHelpText":"Seismic data for study of shallow mountain bedrock limits seepage-based headwater climate refugia, Shenandoah National Park, Virginia"},{"id":438090,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9VFS","text":"USGS data release","linkHelpText":"Temperature data for study of shallow mountain bedrock limits seepage-based headwater climate refugia, Shenandoah National Park, Virginia"},{"id":339122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"68","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e4b0b0e4b09da679997770","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":688331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":false,"id":688332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":688335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Eric A. 0000-0002-7782-146X eawhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7782-146X","contributorId":1737,"corporation":false,"usgs":false,"family":"White","given":"Eric","email":"eawhite@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":688333,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":688336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":688334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":688337,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70219130,"text":"70219130 - 2018 - Pore-types and pore-network evolution in Upper Devonian-Lower Mississippian Woodford and Mississippian Barnett mudstones: Insights from laboratory thermal maturation and organic petrology","interactions":[],"lastModifiedDate":"2021-03-25T13:22:16.408161","indexId":"70219130","displayToPublicDate":"2017-03-25T08:17:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Pore-types and pore-network evolution in Upper Devonian-Lower Mississippian Woodford and Mississippian Barnett mudstones: Insights from laboratory thermal maturation and organic petrology","docAbstract":"Pore-evolution models from immature organic-matter (OM) -rich Barnett (0.42%Ro) and Woodford (0.49%Ro) mudstones were compared with models previously developed from low-maturity OM-lean Boquillas (Eagle Ford-equivalent) mudstones to investigate whether (1) different mineralogy (siliceous vs. calcareous) exerts different catalytic and sorption effects and influences OM-pore origin and evolution; and (2) different types of macerals show different OM pore evolution history. Laboratory gold-tube pyrolysis, scanning electron microscopy (SEM) and thin-section petrography, organic petrography, and geochemical characterization were used to investigate the role of bulk mineralogy, maceral type, and thermal maturation on OM-pore evolution. Results suggest that mineralogy has little impact on OM-pore development and evolution. Macerals, identified using both SEM (platy OM, particulate OM, organic–mineral admixtures, Tasmanites) and organic petrology (vitrinite, inertinite, amorphous organic matter [AOM]/bituminite, telalginite [Leiosphaeridia, Tasmanites]), do affect the origin and evolution of OM pores owing to differences in chemical compositions, generation kinetics, and activation-energy distributions between Tasmanites, matrix bituminite, and other types of macerals. Leiosphaeridia and Tasmanites in Woodford mudstone samples exhibit a delay in onset and a shorter period of petroleum generation and pore development compared to the matrix bituminite in the Barnett and Woodford mudstone samples. Pre-oil solid bitumen was observed to have migrated into initial primary mineral pore networks at the bitumen generation stage in both Barnett and Woodford samples. At higher levels of thermal maturation, the volume of primary mineral pores decreases and the pore volume composed of modified mineral pores and OM pores becomes greater. Pore evolution and pore-type heterogeneity in these mudstones is a function of the initial mineral pore network, types of kerogen and macerals, and generation kinetics of individual macerals upon thermal maturation.
Piston core TN062-O550, collected about 33 km offshore of Eureka, California, contains a high-resolution record of the climate and oceanography of coastal northernmost California during the past ∼7.34 kyr. Chronology established by nine AMS ages on a combination of planktic foraminifers, bivalve shell fragments, and wood yields a mean sedimentation rate of 103 cm kyr−1. Marine proxies (diatoms and silicoflagellates) and pollen transported by the nearby Eel River reveal a stepwise development of both modern offshore surface water oceanography and coastal arboreal ecosystems. Beginning at ∼5.4 cal ka the relative abundance of coastal redwood pollen, a proxy for coastal fog, displays a two fold increase suggesting enhanced coastal upwelling. A decline in the relative contribution of subtropical diatoms at ∼5.0 cal ka implies cooling of sea surface temperatures (SSTs). At ∼3.6 cal ka an increase in the relative abundance of alder and oak at the expense of coastal redwood likely signals intensified riverine transport of pollen from inland environments. Cooler offshore SSTs and increased precipitation characterize the interval between ∼3.6 and 2.8 cal ka. A rapid, stepwise change in coastal climatology and oceanography occurs between ∼2.8 and 2.6 cal ka that suggests an enhanced expression of modern Pacific Decadal Oscillation-like (PDO) cycles. A three-fold increase in the relative abundance of the subtropical diatom Fragilariopsis doliolus at 2.8 cal ka appears to mark an abrupt warming of winter SSTs. Soon afterwards at 2.6 cal ka, a two fold increase in the relative abundance of coastal redwood pollen is suggestive of an abrupt intensification of spring upwelling. After ∼2.8 cal ka a sequence of cool-warm, PDO-like cycles occurs wherein cool cycles are characterized by relative abundance increases in coastal redwood pollen and decreased contributions of subtropical diatoms, whereas opposite proxy trends distinguish warm cycles.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2016.10.039","usgsCitation":"Barron, J.A., Bukry, D., Heusser, L.E., Addison, J.A., and Alexander, C.R., 2018, High-resolution climate of the past ∼7300 years of coastal northernmost California: Results from diatoms, silicoflagellates, and pollen: Quaternary International, v. 469, no. B, p. 109-119, https://doi.org/10.1016/j.quaint.2016.10.039.","productDescription":"11 p.","startPage":"109","endPage":"119","ipdsId":"IP-072222","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":469207,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quaint.2016.10.039","text":"Publisher Index Page"},{"id":333326,"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 -125,\n 40\n ],\n [\n -125,\n 42\n ],\n [\n -123,\n 42\n ],\n [\n -123,\n 40\n ],\n [\n -125,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"469","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58808d3ce4b01dfadfff1529","contributors":{"authors":[{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":658624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bukry, David 0000-0003-4540-890X dbukry@usgs.gov","orcid":"https://orcid.org/0000-0003-4540-890X","contributorId":3550,"corporation":false,"usgs":true,"family":"Bukry","given":"David","email":"dbukry@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":658625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heusser, Linda E.","contributorId":178365,"corporation":false,"usgs":false,"family":"Heusser","given":"Linda","email":"","middleInitial":"E.","affiliations":[{"id":28041,"text":"Lamont-Doherty Earth Observatory, Columbia University","active":true,"usgs":false}],"preferred":false,"id":658626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":658627,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alexander, Clark R. Jr.","contributorId":178366,"corporation":false,"usgs":false,"family":"Alexander","given":"Clark","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[{"id":28042,"text":"Skidaway Institute of Oceanography, Savannah, GA 31411","active":true,"usgs":false}],"preferred":false,"id":658628,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70179784,"text":"70179784 - 2018 - Disease protection and allelopathic interactions of seed-transmitted endophytic pseudomonads of invasive reed grass (Phragmites australis)","interactions":[],"lastModifiedDate":"2018-02-05T15:44:52","indexId":"70179784","displayToPublicDate":"2017-01-17T00:00:00","publicationYear":"2018","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":"Disease protection and allelopathic interactions of seed-transmitted endophytic pseudomonads of invasive reed grass (Phragmites australis)","docAbstract":"Background and aims
Non-native Phragmites australis (haplotype M) is an invasive grass that decreases biodiversity and produces dense stands. We hypothesized that seeds of Phragmites carry microbes that improve seedling growth, defend against pathogens and maximize capacity of seedlings to compete with other plants.
Methods
We isolated bacteria from seeds of Phragmites, then evaluated representatives for their capacities to become intracellular in root cells, and their effects on: 1.) germination rates and seedling growth, 2.) susceptibility to damping-off disease, and 3.) mortality and growth of competitor plant seedlings (dandelion (Taraxacum officionale F. H. Wigg) and curly dock (Rumex crispus L.)).
Results
Ten strains (of 23 total) were identified and characterized; seven were identified as Pseudomonas spp. Strains Sandy LB4 (Pseudomonas fluorescens) and West 9 (Pseudomonas sp.) entered root meristems and became intracellular. These bacteria improved seed germination in Phragmites and increased seedling root branching in Poa annua. They increased plant growth and protected plants from damping off disease. Sandy LB4 increased mortality and reduced growth rates in seedlings of dandelion and curly dock.
Conclusions
Phragmites plants associate with endophytes to increase growth and disease resistance, and release bacteria into the soil to create an environment that is favorable to their seedlings and less favorable to competitor plants.
No abstract available.
","language":"English","publisher":"Exxon Valdez Oil Spill Trustee Council","usgsCitation":"Hershberger, P., and Purcell, M.K., 2018, Herring Disease Program – Herring Disease Program II, 7 p.","productDescription":"7 p.","ipdsId":"IP-094651","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":361875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361354,"type":{"id":11,"text":"Document"},"url":"https://www.evostc.state.ak.us/Store/AnnualReports/2017-17120111E-Annual.pdf"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hershberger, Paul 0000-0002-2261-7760 phershberger@usgs.gov","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":150816,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757583,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195495,"text":"70195495 - 2018 - Direct and indirect controls on organic matter decomposition in four coastal wetland communities along a landscape salinity gradient","interactions":[],"lastModifiedDate":"2018-02-20T10:21:02","indexId":"70195495","displayToPublicDate":"2017-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Direct and indirect controls on organic matter decomposition in four coastal wetland communities along a landscape salinity gradient","docAbstract":"Many species living in deeper lentic ecosystems exhibit daily movements that cycle through the water column, generally referred to as diel vertical migration (DVM). In this study, we applied bioenergetics modelling to evaluate growth as a hypothesis to explain DVM by bull trout (Salvelinus confluentus) in a thermally stratified reservoir (Ross Lake, WA, USA) during the peak of thermal stratification in July and August. Bioenergetics model parameters were derived from observed vertical distributions of temperature, prey and bull trout. Field sampling confirmed that bull trout prey almost exclusively on recently introduced redside shiner (Richardsonius balteatus). Model predictions revealed that deeper (>25 m) DVMs commonly exhibited by bull trout during peak thermal stratification cannot be explained by maximising growth. Survival, another common explanation for DVM, may have influenced bull trout depth use, but observations suggest there may be additional drivers of DVM. We propose these deeper summertime excursions may be partly explained by an alternative hypothesis: the importance of colder water for gametogenesis. In Ross Lake, reliance of bull trout on warm water prey (redside shiner) for consumption and growth poses a potential trade-off with the need for colder water for gametogenesis.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12321","usgsCitation":"Eckmann, M., Dunham, J.B., Connor, E.J., and Welch, C.A., 2018, Bioenergetic evaluation of diel vertical migration by bull trout (Salvelinus confluentus) in a thermally stratified reservoir: Ecology of Freshwater Fish, v. 27, no. 1, p. 30-43, https://doi.org/10.1111/eff.12321.","startPage":"30","endPage":"43","ipdsId":"IP-062351","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":332614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Ross Lake, North Cascades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.03363037109374,\n 48.82268881260476\n ],\n 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jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":656804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connor, Edward J.","contributorId":177723,"corporation":false,"usgs":false,"family":"Connor","given":"Edward","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":656827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welch, Carmen A.","contributorId":177724,"corporation":false,"usgs":false,"family":"Welch","given":"Carmen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":656828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189657,"text":"70189657 - 2018 - Introduction to the Wetland Book 1: Wetland structure and function, management, and nethods","interactions":[],"lastModifiedDate":"2018-09-11T11:13:17","indexId":"70189657","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Introduction to the Wetland Book 1: Wetland structure and function, management, and nethods","docAbstract":"The Wetland Book 1 is designed as a ‘first port-of-call’ reference work for information on the structure and functions of wetlands, current approaches to wetland management, and methods for researching and understanding wetlands. Contributions by experts summarize key concepts, orient the reader to the major issues, and support further research on such issues by individuals and multidisciplinary teams. The Wetland Book 1 is organized in three parts - Wetland structure and function; Wetland management; and Wetland methods - each of which is divided into a number of thematic sections. Each section starts with one or more overview chapters, supported by chapters providing further information and case studies on different aspects of the theme.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Wetland Book","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-90-481-9659-3_356","isbn":"978-94-007-6172-8","usgsCitation":"Davidson, N.C., Middleton, B.A., McInnes, R.J., Everard, M., Irvine, K., Van Dam, A., and Finlayson, C., 2018, Introduction to the Wetland Book 1: Wetland structure and function, management, and nethods, chap. of The Wetland Book, p. 3-14, https://doi.org/10.1007/978-90-481-9659-3_356.","productDescription":"12 p.","startPage":"3","endPage":"14","ipdsId":"IP-079069","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":344055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","scienceBaseUri":"59706fb7e4b0d1f9f065a896","contributors":{"editors":[{"text":"Finlayson, C. 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Max","affiliations":[],"preferred":false,"id":705634,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70178531,"text":"70178531 - 2018 - Climate-induced seasonal changes in smallmouth bass growth rate potential at the southern range extent","interactions":[],"lastModifiedDate":"2017-12-11T14:02:08","indexId":"70178531","displayToPublicDate":"2016-11-23T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Climate-induced seasonal changes in smallmouth bass growth rate potential at the southern range extent","docAbstract":"Temperature increases due to climate change over the coming century will likely affect smallmouth bass (Micropterus dolomieu) growth in lotic systems at the southern extent of their native range. However, the thermal response of a stream to warming climate conditions could be affected by the flow regime of each stream, mitigating the effects on smallmouth bass populations. We developed bioenergetics models to compare change in smallmouth bass growth rate potential (GRP) from present to future projected monthly stream temperatures across two flow regimes: runoff and groundwater-dominated. Seasonal differences in GRP between stream types were then compared. The models were developed for fourteen streams within the Ozark–Ouachita Interior Highlands in Arkansas, Oklahoma and Missouri, USA, which contain smallmouth bass. In our simulations, smallmouth bass mean GRP during summer months decreased by 0.005 g g−1 day−1 in runoff streams and 0.002 g g−1 day−1 in groundwater streams by the end of century. Mean GRP during winter, fall and early spring increased under future climate conditions within both stream types (e.g., 0.00019 g g−1 day−1 in runoff and 0.0014 g g−1 day−1 in groundwater streams in spring months). We found significant differences in change in GRP between runoff and groundwater streams in three seasons in end-of-century simulations (spring, summer and fall). Potential differences in stream temperature across flow regimes could be an important habitat component to consider when investigating effects of climate change as fishes from various flow regimes that are relatively close geographically could be affected differently by warming climate conditions.
The economy of the Khorezm Province in Uzbekistan relies on the large-scale agricultural production of cotton. To sustain their staple crop, water from the Amu Darya is diverted for irrigation through canal systems constructed during the early to mid-twentieth century when this region was part of the Soviet Union. These diversions severely reduce river flow to the Aral Sea. The Province has >400 small shallow (<3 m deep) lakes that may have originated because of this intensive irrigation. Sediment cores were collected from 12 lakes to elucidate their origin because this knowledge is critical to understanding water use in Khorezm. Core chronological data indicate that the majority of the lakes investigated are less than 150 years old, which supports a recent origin of the lakes. The thickness of lacustrine sediments in the cores analyzed ranged from 20 to 60 cm in all but two of the lakes, indicating a relatively slow sedimentation rate and a relatively short-term history for the lakes. Hydrologic changes in the lakes are evident from loss on ignition and pollen analyses of a subset of the lake cores. The data indicate that the lakes have transitioned from a dry, saline, arid landscape during pre-lake conditions (low organic carbon content) and low pollen concentrations (in the basal sediments) to the current freshwater lakes (high organic content), with abundant freshwater pollen taxa over the last 50–70 years. Sediments at the base of the cores contain pollen taxa dominated by Chenopodiaceae and Tamarix, indicating that the vegetation growing nearby was tolerant to arid saline conditions. The near surface sediments of the cores are dominated by Typha/Sparganium, which indicate freshwater conditions. Increases in pollen of weeds and crop plants indicate an intensification of agricultural activities since the 1950s in the watersheds of the lakes analyzed. Pesticide profiles of DDT (dichlorodiphenyltrichloroethane) and its degradates and γ-HCH (gamma-hexachlorocyclohexane), which were used during the Soviet era, show peak concentrations in the top 10 cm of some of the cores, where estimated ages of the sediments (1950–1990) are associated with peak pesticide use during the Soviet era. These data indicate that the lakes are relatively young (mostly <150 years old) and that without irrigation and canal inputs from the Amu Darya, the lakes would not exist as freshwater lakes.
","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10933-016-9914-2","usgsCitation":"Rosen, M.R., Crootof, A., Reidy, L., Saito, L., Nishonov, B., and Scott, J.A., 2018, The origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these lakes: Journal of Paleolimnology, v. 59, no. 2, p. 201-219, https://doi.org/10.1007/s10933-016-9914-2.","productDescription":"19 p.","startPage":"201","endPage":"219","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073927","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":438095,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7319T07","text":"USGS data release","linkHelpText":"Datasets for determining the origin of shallow lakes in the Khorezm Province, Uzbekistan, and the history of pesticide use around these 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Arizona","active":true,"usgs":false}],"preferred":false,"id":651050,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reidy, Liam","contributorId":175417,"corporation":false,"usgs":false,"family":"Reidy","given":"Liam","affiliations":[],"preferred":false,"id":651051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saito, Laurel","contributorId":139343,"corporation":false,"usgs":false,"family":"Saito","given":"Laurel","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":651052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nishonov, Bakhriddin","contributorId":15860,"corporation":false,"usgs":false,"family":"Nishonov","given":"Bakhriddin","email":"","affiliations":[],"preferred":false,"id":651053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Julian 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Chapter A10 reviews limnological principles, describes the characteristics that distinguish lakes from reservoirs, and provides guidance for developing temporal and spatial sampling strategies and data-collection approaches to be used in lake and reservoir environmental investigations.
Within this chapter are references to other chapters of the NFM that provide more detailed guidelines related to specific topics and more detailed protocols for the quality assurance and assessment of the lake and reservoir data. Protocols and procedures to address and document the quality of lake and reservoir investigations are adapted from, or referenced to, the protocols and standard operating procedures contained in related chapters of this NFM.
Before 2017, the U.S. Geological Survey (USGS) “National Field Manual for the Collection of Water-Quality Data” (NFM) chapters were released in the USGS Techniques of Water-Resources Investigations series. Effective in 2018, new and revised NFM chapters are being released in the USGS Techniques and Methods series; this series change does not affect the content and format of the NFM. More information is in the general introduction to the NFM (USGS Techniques and Methods, book 9, chapter A0, 2018) at https://doi.org/10.3133/tm9A0. The authoritative current versions of NFM chapters are available in the USGS Publications Warehouse at https://pubs.er.usgs.gov. Comments, questions, and suggestions related to the NFM can be addressed to nfm-owq@usgs.gov.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: National field manual for the collection of water-quality data in Book 9:Handbooks for water-resources investigations","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm9A10","usgsCitation":"U.S. Geological Survey, 2018, Lakes and reservoirs—Guidelines for study design and sampling: U.S. Geological Survey Techniques and Methods, book 9, chap. A10, 48 p., https://doi.org/10.3133/tm9a10. [Supersedes USGS Techniques of Water-Resources Investigations, book 9, chap. A10, version 1.0]","productDescription":"vi, 48 p.","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-033791","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":354591,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm9A0","text":"Techniques and Methods 9-A0","linkHelpText":"- General Introduction for the “National Field Manual for the Collection of Water-Quality Data”"},{"id":310891,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/09/a10/tm9a10.pdf","text":"Report","size":"4.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 9-A10"},{"id":354561,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/09/a10/versionHist.txt","size":"2.11 KB","linkFileType":{"id":2,"text":"txt"}},{"id":310892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/09/a10/coverthb3.jpg"}],"edition":"Version 1.0: May 2018","publicComments":"This report is Chapter 10 of Section A: National field manual for the collection of water-quality data in Book 9:Handbooks for water-resources investigations. [Supersedes USGS Techniques of Water-Resources Investigations, book 9, chap. A10, version 1.0]","contact":"Chief, Office of Quality Assurance
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 432
Reston, VA 20192
In response to recent diplomatic developments between Cuba and the United States, the National Minerals Information Center compiled available information on the mineral industries of Cuba. This fact sheet highlights a new map and table that identify mines, mineral processing facilities, and petroleum facilities as well as information on location, operational status, and ownership. It also addresses the current status of known mineral industry projects, historical developments, and trends of the Cuban economy with an emphasis on mineral industries, and the supply and demand for Cuba’s mineral resources.
In 2013, Cuba was estimated to be among the world’s top ten producers of cobalt and nickel, which are the country’s leading exports. Cuba’s current crude oil and associated natural gas production from onshore and shallow water coastal reservoirs is approximately 50,000 barrels per day of liquids and about 20,000 barrels per day oil equivalent of natural gas. In 2013, the value of mining and quarrying activities accounted for 0.6 percent of Cuba’s gross domestic product (GDP), compared with 1.4 percent in 2000. The value of production from Cuba’s industrial manufacturing sector increased by 88 percent between 1993 and 2013, whereas the sector’s share in the GDP decreased by about 3 percent during the same time period reflecting economic growth in other sectors of the economy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153032","usgsCitation":"Wacaster, Susan, Baker, M.S., Soto-Viruet, Yadira, and Textoris, S.D., 2018, Recent trends in Cuba’s mining and petroleum industries (ver. 2.0,Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
A shapefile of 311 undersea features from all major oceans and seas has been created as an aid for retrieving georeferenced information resources. Geospatial information systems with the capability to search user-defined, polygonal geographic areas will be able to utilize this shapefile or secondary products derived from it, such as linked data based on well-known text representations of the individual polygons within the shapefile. Version 1.1 of this report also includes a linked data representation of 299 of these features and their spatial extents.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141040","usgsCitation":"Hartwell, S., Wingfield, D.K., Allwardt, A., Lightsom, F.L., and Wong, F.L., 2018, Polygons of global undersea features for geographic searches (Version 1.1: June 2018; Version 1.0: March 2014): U.S. Geological Survey Open-File Report 2014-1040, HTML, https://doi.org/10.3133/ofr20141040.","productDescription":"HTML","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053850","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":284379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141040.jpg"},{"id":284377,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1040/","text":"Index page","linkFileType":{"id":5,"text":"html"},"description":"OFR 2014-1040"},{"id":354598,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2014/1040/versionHist.txt","size":"1.75 KB","linkFileType":{"id":2,"text":"txt"}},{"id":284378,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1040/ofr2014-1040-title_page.html","text":"Report (HTML)"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","edition":"Version 1.1: June 2018; Version 1.0: March 2014","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th, Bldg 7
Oklahoma City, OK 73116
This publication is the User's Guide for software developed to estimate wildlife fatalities at wind-power facilities, although the software is applicable to a variety of circumstances in which the objective is to estimate the size of a superpopulation and the probability of detection of the individuals is less than one. Simple counts of carcasses do not accurately reflect fatality and do not allow comparison among locations because carcasses may be detected at different rates. This software uses data collected during carcass searches and knowledge of detection rates to accurately estimate the number of fatalities and to provide a measure of precision associated with the estimate. These estimates are fundamental to understanding acute and cumulative effects of wind power on wildlife populations.
Only carcasses judged to have been killed after the previous search should be included in the fatality data set submitted to this estimator software. This estimator already corrects for carcasses missed in previous searches, so carcasses judged to have been missed at least once should be considered “incidental” and not included in the fatality data set used to estimate fatality. Note: When observed carcass count is <5 (including 0 for species known to be at risk, but not observed), USGS Data Series 881 (https://pubs.usgs.gov/ds/0881/) is recommended for fatality estimation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds729","usgsCitation":"Huso, Manuela, Som, Nicholas, and Ladd, Lew, 2018, Fatality estimator user’s guide (ver. 1.2, December 2018): U.S. Geological Survey Data Series 729, 22 p., https://doi.org/10.3133/ds729.","productDescription":"Report: vi, 22 p.; Estimator Software ZIP download","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":311790,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/729/InputPlaceholderV1.1.zip","text":"Input Placeholder 1.1","size":"10 KB","linkFileType":{"id":6,"text":"zip"}},{"id":263935,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/729/pdf/ds729.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":263936,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/729/ds729_EstimatorSetup.zip","text":"Estimator Software","size":"250 KB","linkFileType":{"id":6,"text":"zip"}},{"id":263934,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/729/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":311792,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/729/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":311791,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/729/ds729_readme.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}},{"id":360159,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/729/images/coverthb.jpg"}],"edition":"Version 1: Originally posted December 2012; Version 1.1: December 2015; Version 1.2: December 2018","contact":"Director, Forest and Rangeland Ecosystem Science Center,
U.S. Geological Survey, 777 NW 9th Street
Corvallis, Oregon 97330
http://fresc.usgs.gov
Crystalline bedrock aquifers in New England and parts of New Jersey and New York (NECR aquifers) are a major source of drinking water. Because the quality of water in these aquifers is highly variable, the U.S. Geological Survey (USGS) statistically analyzed chemical data on samples of untreated groundwater collected from 117 domestic bedrock wells in New England, New York, and New Jersey, and from 4,775 public-supply bedrock wells in New England to characterize the quality of the groundwater. The domestic-well data were from samples collected by the USGS National Water-Quality Assessment (NAWQA) Program from 1995 through 2007. The public-supply-well data were from samples collected for the U.S. Environmental Protection Agency (USEPA) Safe Drinking Water Act (SDWA) Program from 1997 through 2007. Chemical data compiled from the domestic wells include pH, specific conductance, dissolved oxygen, alkalinity, and turbidity; 6 nitrogen and phosphorus compounds, 14 major ions, 23 trace elements, 222radon gas (radon), 48 pesticide compounds, and 82 volatile organic compounds (VOCs). Additional samples were collected from the domestic wells for the analysis of gross alpha- and gross beta-particle radioactivity, radium isotopes, chlorofluorocarbon isotopes, and the dissolved gases methane, carbon dioxide, nitrogen, and argon. Chemical data compiled from the public-supply wells include pH, specific conductance, nitrate, iron, manganese, sodium, chloride, fluoride, arsenic, uranium, radon, combined radium (226radium plus 228radium), gross alpha-particle radioactivity, and methyl tert-butyl ether (MtBE).
Patterns in fluoride, arsenic, uranium, and radon distributions were discernable when the data were compared to lithology groupings of the bedrock, indicating that the type of bedrock has an effect on the quality of groundwater from NECR aquifers. Fluoride concentrations were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and metaluminous granite lithology groups than from samples in the other lithology groups. Water samples from 1.4 percent of 2,167 studied wells had fluoride concentrations that were equal to or greater than the maximum contaminant level (MCL) of 4 milligrams per liter (mg/L) and 7.5 percent of the wells had fluoride concentrations that were equal to or greater than the secondary MCL of 2 mg/L. For arsenic, groundwater samples from the calcareous metasedimentary rocks in the New Hampshire-Maine geologic province, peraluminous granite, and pelitic rocks lithology groups had higher concentrations than did samples from the other lithology groups. Water samples from 13.3 percent of 2,054 studied wells had arsenic concentrations that were equal to or greater than the MCL of 10 micrograms per liter (μg/L), about double the national rate of occurrence in community-supply systems and in domestic wells of the United States. Uranium concentrations were significantly higher in groundwater samples from the peraluminous granite, alkali granite, and calcareous metasedimentary rocks in the New Hampshire-Maine geologic province lithology groups than from samples in the other lithology groups. Water samples from 14.2 percent of 556 studied wells had uranium concentrations equal to or greater than the MCL of 30 μg/L. Radon activities were equal to or greater than the proposed MCL of 300 picocuries per liter (pCi/L) in 95 percent of 943 studied wells, and 33 percent of the wells had radon activities were equal to or greater than the proposed alternative maximum contaminant level (AMCL) of 4,000 pCi/L. Radon activities exceeded the proposed AMCL in 20 percent or more of groundwater samples in each of the studied lithology groups with a minimum of 9 samples, but radon activities were significantly higher in groundwater samples from the alkali granite, peraluminous granite, and Narragansett basin metasedimentary rocks lithology groups. Water samples from 3.2 percent of 564 studied wells had combined radium activities equal to or greater than the MCL of 5 pCi/L; however, combined radium activities were not significantly different among the studied lithology groups.
Land use and population density also were evaluated to explain patterns in water quality. Concentrations of nitrate, sodium, chloride, and MtBE from the studied wells were significantly greater in areas of high population density (≥50 persons per square kilometer) than in areas of low population density (<50 persons per square kilometer). Concentrations of sodium, chloride, and MtBE from the studied wells were significantly greater in areas classified as developed (urban lands) than in areas classified as undeveloped (forested), agricultural, or mixed (no dominant land use). Nitrate concentrations from the public-supply wells were not significantly different among the four land use categories, but nitrate concentrations from the domestic wells were significantly greater in areas classified as developed than in areas classified as undeveloped, agricultural, or mixed.
Chloride to bromide mass ratios in the domestic well samples indicate that the groundwater was probably affected by at least three halogen sources: local precipitation and recharge waters, remnant seawater and connate waters evolved from seawater, and recharge waters affected by road salt. The groundwater in the NECR aquifers generally contained low concentrations of nitrate, VOCs, and pesticides. Less than 1 percent of water samples from 4,781 studied wells had concentrations of nitrate greater than the MCL of 10 mg/L. Less than 1 percent of water samples from 1,299 studied wells exceeded the USEPA advisory level of 20 to 40 μg/L for MtBE. None of the other studied VOCs exceeded a human health benchmark. MtBE (36 percent frequency detection) and chloroform (32.9 percent frequency detection) were the most frequently detected (>0.02 μg/L) VOCs in the domestic wells. MtBE was detected more often in water samples with apparent ages of less than 25 years than in water samples with apparent ages greater than 25 years. This finding is consistent with the time period of high MtBE use in areas in the United States where reformulated gasoline was mandated. The largest pesticide concentration was an estimated concentration of 0.06 μg/L for the herbicide metolachlor. Deethylatrazine, a degradate of atrazine, (18 percent frequency detection) and atrazine (8 percent frequency detection) were the only pesticide compounds detected (>0.001 μg/L) in more than 3 percent of the domestic wells. None of the detected pesticide compounds exceeded human health benchmarks.
Concentrations of nitrate and gross alpha-particle activities were significantly greater in the water samples from the domestic wells than in samples from the public-supply wells. Concentrations of sodium, chloride, iron, manganese, and uranium were significantly greater in the water samples from the public-supply wells than in the samples from the domestic wells. One possible explanation may be related to differences in field processing (filtered samples from the domestic wells compared to unfiltered samples from the public-supply wells).
The high frequency of detections for a wide variety of manmade and naturally occurring contaminants in both domestic and public-supply wells shows the vulnerability of NECR aquifers to contamination. The highly variable water quality and the association with highly variable lithology of crystalline bedrock underscores the importance of testing individual wells to determine if concentrations for the most commonly detected contaminants exceed human health benchmarks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115220","isbn":"ISBN 978-1-411-33417-5","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Flanagan, S.M., Ayotte, J.D., Robinson, G.R., Jr., 2018, Quality of water from crystalline rock aquifers in New England, New Jersey, and New York, 1995–2007 (ver.1.1, April 2018): U.S. Geological Survey 2011–5220, 104 p., https://doi.org/10.3133/sir20115220.\n","productDescription":"Report: xiv, 104 p.","numberOfPages":"122","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353386,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/pdf/sir20115220.pdf","text":"Report","size":"9.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2011-5220"},{"id":353387,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2011/5220/versionHist.txt","size":"1.33 KB","linkFileType":{"id":2,"text":"txt"}},{"id":257873,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5220/index.html","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":257884,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2011/5220/images/coverthb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.03662109375,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 40.56389453066509\n ],\n [\n -66.90673828125,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 47.39834920035926\n ],\n [\n -75.03662109375,\n 40.56389453066509\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released June 25, 2012; Version 1.1: April 13, 2018","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Conservation and recovery of species of concern necessitates evaluating forest habitat conditions under changing climate conditions, especially in the early stages of the delisting process. Managers must weigh implications of near-term habitat management activities within the context of changing environmental conditions and a species’ biological traits that may influence their vulnerability to changing conditions. Here we applied established population-habitat relationships based on decades of monitoring and research-management collaborations for the Kirtland’s Warbler (Setophaga kirtlandii) to project potential impacts of changing environmental conditions to breeding habitat distribution, quantity, and quality in the near future. Kirtland’s warblers are habitat-specialists that nest exclusively within dense jack pine (Pinus banksiana) forests between ca. 5–20 years of age. Using Random Forests to predict changes in distribution and growth rate of jack pine under future scenarios, results indicate the projected distribution of jack pine will contract considerably (ca. 75%) throughout the Lake States region, U.S.A. in response to projected environmental conditions in 2099 under RCP 4.5 and 8.5 climate scenarios regardless of climate model. Reduced suitability for jack pine regeneration across the Lake States may constrain management options, especially for creating high stem-density plantations nesting habitat. However, conditions remain suitable for jack pine regeneration within their historical and current core breeding range in northern Lower Michigan and several satellite breeding areas. Projected changes in jack pine growth rates varied within the core breeding area, but altered growth rates did not greatly alter the duration that habitat remained suitable for nesting by the Kirtland’s Warblers. These findings contribute to Kirtland’s Warbler conservation by informing habitat spatial planning of plantation management to provide a constant supply of nesting habitat based on the spatial variability of potential loss or gain of lands environmentally suitable for regenerating jack pine in the long-term.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2018.08.026","usgsCitation":"Donner, D.M., Brown, D., Ribic, C., Nelson, M., and Greco, T., 2018, Managing forest habitat for conservation-reliant species in a changing climate: The case of the endangered Kirtland’s Warbler: Forest Ecology and Management, v. 430, p. 265-279, https://doi.org/10.1016/j.foreco.2018.08.026.","productDescription":"15 p.","startPage":"265","endPage":"279","ipdsId":"IP-094530","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469210,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2018.08.026","text":"Publisher Index Page"},{"id":380304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.62744140625,\n 43.8028187190472\n ],\n [\n -83.29833984375,\n 43.8028187190472\n ],\n [\n -83.29833984375,\n 45.583289756006316\n ],\n [\n -85.62744140625,\n 45.583289756006316\n ],\n [\n -85.62744140625,\n 43.8028187190472\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.31982421875,\n 45.78284835197676\n ],\n [\n -83.07861328125,\n 45.78284835197676\n ],\n [\n -83.07861328125,\n 46.70973594407157\n ],\n [\n -85.31982421875,\n 46.70973594407157\n ],\n [\n -85.31982421875,\n 45.78284835197676\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.57177734375,\n 45.75219336063106\n ],\n [\n -85.69335937499999,\n 45.75219336063106\n ],\n [\n -85.69335937499999,\n 47.010225655683485\n ],\n [\n -88.57177734375,\n 47.010225655683485\n ],\n [\n -88.57177734375,\n 45.75219336063106\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.8017578125,\n 46.08847179577592\n ],\n [\n -90.28564453124999,\n 46.08847179577592\n ],\n [\n -90.28564453124999,\n 47.100044694025215\n ],\n [\n -91.8017578125,\n 47.100044694025215\n ],\n [\n -91.8017578125,\n 46.08847179577592\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.681640625,\n 44.91813929958515\n ],\n [\n -87.5830078125,\n 44.91813929958515\n ],\n [\n -87.5830078125,\n 45.85941212790755\n ],\n [\n -88.681640625,\n 45.85941212790755\n ],\n [\n -88.681640625,\n 44.91813929958515\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.04669189453125,\n 43.65594991256823\n ],\n [\n -89.50698852539062,\n 43.65594991256823\n ],\n [\n -89.50698852539062,\n 44.219615400229195\n ],\n [\n -90.04669189453125,\n 44.219615400229195\n ],\n [\n -90.04669189453125,\n 43.65594991256823\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"430","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donner, Deahn M.","contributorId":171823,"corporation":false,"usgs":false,"family":"Donner","given":"Deahn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":804353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Donald J.","contributorId":191568,"corporation":false,"usgs":false,"family":"Brown","given":"Donald J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":804354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribic, Christine 0000-0003-2583-1778 caribic@usgs.gov","orcid":"https://orcid.org/0000-0003-2583-1778","contributorId":147952,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":804352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Mark","contributorId":244674,"corporation":false,"usgs":false,"family":"Nelson","given":"Mark","affiliations":[{"id":27863,"text":"U. S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":804355,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greco, Tim","contributorId":244675,"corporation":false,"usgs":false,"family":"Greco","given":"Tim","email":"","affiliations":[{"id":6983,"text":"Michigan DNR","active":true,"usgs":false}],"preferred":false,"id":804356,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":47797,"text":"wri034009 - 2018 - Evaluation of the Source and Transport of High Nitrate Concentrations in Ground Water, Warren Subbasin, California","interactions":[],"lastModifiedDate":"2018-09-19T16:54:36","indexId":"wri034009","displayToPublicDate":"2003-08-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4009","title":"Evaluation of the Source and Transport of High Nitrate Concentrations in Ground Water, Warren Subbasin, California","docAbstract":"Ground water historically has been the sole source of water supply for the Town of Yucca Valley in the Warren subbasin of the Morongo ground-water basin, California. An imbalance between ground-water recharge and pumpage caused ground-water levels in the subbasin to decline by as much as 300 feet from the late 1940s through 1994. In response, the local water district, Hi-Desert Water District, instituted an artificial recharge program in February 1995 using imported surface water to replenish the ground water. The artificial recharge program resulted in water-level recoveries of as much as 250 feet in the vicinity of the recharge ponds between February 1995 and December 2001; however, nitrate concentrations in some wells also increased from a background concentration of 10 milligrams per liter to more than the U.S. Environmental Protection Agency (USEPA) maximum contaminant level (MCL) of 44 milligrams per liter (10 milligrams per liter as nitrogen).
The objectives of this study were to: (1) evaluate the sources of the high-nitrate concentrations that occurred after the start of the artificial-recharge program, (2) develop a ground-water flow and solute-transport model to better understand the source and transport of nitrates in the aquifer system, and (3) utilize the calibrated models to evaluate the possible effect of a proposed conjunctive-use project. These objectives were accomplished by collecting water-level and water-quality data for the subbasin and assessing changes that have occurred since artificial recharge began. Collected data were used to calibrate the ground-water flow and solute-transport models.
Data collected for this study indicate that the areal extent of the water-bearing deposits is much smaller (about 5.5 square miles versus 19 square miles) than that of the subbasin. These water-bearing deposits are referred to in this report as the Warren ground-water basin. Faults separate the ground-water basin into five hydrogeologic units: the west, the midwest, the mideast, the east and the northeast hydrogeologic units.
Water-quality analyses indicate that septage from septic tanks is the primary source of the high-nitrate concentrations measured in the Warren ground-water basin. Water-quality and stable-isotope data, collected after the start of the artificial recharge program, indicate that mixing occurs between imported water and native ground water, with the highest recorded nitrate concentrations in the midwest and the mideast hydrogeologic units. In general, the timing of the increase in measured nitrate concentrations in the midwest hydrogeologic unit is directly related to the distance of the monitoring well from a recharge site, indicating that the increase in nitrate concentrations is related to the artificial recharge program. Nitrate-to-chloride and nitrogen-isotope data indicate that septage is the source of the measured increase in nitrate concentrations in the midwest and the mideast hydrogeologic units. Samples from four wells in the Warren ground-water basin were analyzed for caffeine and selected human pharmaceutical products; these analyses suggest that septage is reaching the water table.
There are two possible conceptual models that explain how high-nitrate septage reaches the water table: (1) the continued downward migration of septage through the unsaturated zone to the water table and (2) rising water levels, a result of the artificial recharge program, entraining septage in the unsaturated zone. The observations that nitrate concentrations increase in ground-water samples from wells soon after the start of the artificial recharge program in 1995 and that the largest increase in nitrate concentrations occur in the midwest and mideast hydrogeologic units where the largest increase in water levels occur indicate the validity of the second conceptual model (rising water levels). The potential nitrate concentration resulting from a water-level rise in the midwest and mideast hydrogeologic units was estimated using a simple mixing-cell model. The estimated value is within the range of concentrations measured in samples from wells, further indicating the validity of the second conceptual model.
A ground-water flow model and a solute-transport model were developed for the Warren ground-water basin for the period 1956-2001. MODFLOW-96 was used for the ground-water flow model and MOC3D was used for the solute-transport model. The model cell size is about 500 feet by 500 feet and the models were discretized vertically into three layers. The models were calibrated using a trial-and-error approach using water-level and nitrate-concentration data collected between 1956-2001. In order to better match the measured data, low fault hydraulic characteristic values were required, thereby compartmentalizing the ground-water basin. In addition, it was necessary to parameterize the specific yield distribution for the top model layer where unconfined ground-water conditions occur into three homogeneous zones. Separate sets of specific- yield values were needed to simulate the drawdown and subsequent water-level recovery. In addition, the calibrated natural recharge was about 83 acre-feet per year. The entrainment of unsaturated-zone septage was simulated as recharge having an associated nitrate concentration. The volume of recharge was a function of the measured water-level rise between 1994-98 and the moisture content of the unsaturated zone. The nitrate concentration of the recharge water was a weighted function of the assumed nitrate concentration in the infiltrating water associated with the overlying land use. The simulated hydraulic head and nitrate concentration results were in good agreement with the measured data indicating that the mechanism for the increase in nitrate concentrations was rising water levels entraining high-nitrate septage in the unsaturated-zone.
The calibrated models were used to simulate the possible effects of a planned conjunctive-use project in the western part of the ground-water basin. The simulated project included the addition of a new recharge pond and a new extraction well. In addition, recharge at two existing recharge ponds was increased and three existing production wells were pumped, treated in a nitrate-removal facility, and used for water supply. The simulated hydraulic heads increased in the west, the mideast, and parts of the east hydrogeologic units; however, the simulated hydraulic heads decreased in the midwest and northeast hydrogeologic units. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter (10 milligrams per liter as nitrogen) in parts of the west as a result of the increase in simulated hydraulic head. The simulated nitrate concentrations decreased in part of the midwest hydrogeologic unit as a result of the artificial recharge and pumping from the nitrate-removal wells. The simulated nitrate concentrations increased to above the MCL of 44 milligrams per liter in part of the mideast and parts of the east hydrogeologic units beneath commercial land-use areas.