The U.S. Geological Survey collects groundwater data and conducts studies to monitor hydrologic conditions, define groundwater resources, and address problems related to water supply, water use, and water quality. In Georgia, water levels were monitored continuously at 157 wells during calendar years 2015 and 2016. Because of missing data or short periods of record (less than 5 years) for several of these wells, data for 147 wells are presented in this report. These wells include 15 in the surficial aquifer system, 18 in the Brunswick aquifer system and equivalent sediments, 59 in the Upper Floridan aquifer, 13 in the Lower Floridan aquifer and underlying units, 9 in the Claiborne aquifer, 1 in the Gordon aquifer, 8 in the Clayton aquifer, 16 in the Cretaceous aquifer system, 2 in Paleozoic-rock aquifers, and 6 in crystalline-rock aquifers. Data from the well network indicate that water levels generally rose during the 10-year period from 2007 through 2016, with water levels rising in 105 wells and declining in 31 wells; insufficient data prevented determination of a 10-year trend in 11 wells. Water levels declined over the long-term period of record at 80 wells, increased at 62 wells, and remained relatively constant at 5 wells.
In addition to continuous water-level data, periodic water-level data were collected and used to construct potentiometric-surface maps for the Upper Floridan aquifer in the Brunswick–Glynn County area during October 2015 and October 2016 and in the Albany–Dougherty County area during December 2015 and November and December 2016. Periodic water-level measurements were also collected and used to construct potentiometric-surface maps for the Cretaceous aquifer system in the Augusta–Richmond County area during July 2015 and June 2016. In general, water levels in the Upper Floridan aquifer were higher during 2015 than during 2016 in the Brunswick–Glynn County and Albany–Dougherty County areas due to higher precipitation during 2015. Water levels were lower, however, during 2015 than during 2016 in the Cretaceous aquifer system in the Augusta–Richmond County area.
In the Brunswick area, maps showing the chloride concentration of water in the Upper Floridan aquifer constructed using data collected from 33 wells during October 2015 and from 30 wells during October 2016 indicate that chloride concentrations remained above the U.S. Environmental Protection Agency’s secondary drinking-water standard in an approximately 2-square-mile area. During calendar years 2015–16, chloride concentrations generally were similar to those measured during 2012–14; however, some wells did show an increase in chloride concentration, likely due to increases in pumping.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175142","usgsCitation":"Gordon, D.W., and Painter, J.A., 2018, Groundwater conditions in Georgia, 2015–16: U.S. Geological Survey Scientific Investigations Report 2017–5142, 59 p., https://doi.org/10.3133/sir20175142.","productDescription":"iv, 59 p.","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088486","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":351599,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5142/coverthb.jpg"},{"id":351600,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5142/sir20175142.pdf","text":"Report","size":"8.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5142"}],"country":"United 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
In 1998, the Michigan Department of Environmental Quality and the U.S. Geological Survey began the Water Chemistry Monitoring Program for select streams in the State of Michigan. Objectives of this program were to provide assistance with (1) statewide water-quality assessments, (2) the National Pollutant Discharge Elimination System permitting process, and (3) water-resource management decisions. As part of this program, water-quality data collected from 1998 to 2013 were analyzed to identify potential trends for select constituents that were sampled. Sixteen water-quality constituents were analyzed at 32 stations throughout Michigan. Trend analysis on the various water-quality data was done using either the uncensored Seasonal Kendall test or through Tobit regression. In total, 79 trends were detected in the constituents analyzed for 32 river stations sampled for the study period—53 downward trends and 26 upward trends were detected. The most prevalent trend detected throughout the State was for ammonia, with 11 downward trends and 1 upward trend estimated.
In addition to trends, constituent loads were estimated for 31 stations from 2002 to 2013 for stations that were sampled 12 times per year. Loads were computed using the Autobeale load computation program, which used the Beale ratio estimator approach to estimate an annual load. Constituent loads were the largest in large watershed streams with the highest annual flows such as the Saginaw and Grand Rivers. Likewise, constituent loads were the smallest in smaller tributaries that were sampled as part of this program such as the Boardman and Thunder Bay Rivers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175147","collaboration":"Prepared in cooperation with the Michigan Department of Environmental Quality","usgsCitation":"Hoard, C.J., Fogarty, L.R., and Duris, J.W., 2018, Temporal trends in water-quality constituent concentrations and annual loads of chemical constituents in Michigan watersheds, 1998–2013: U.S. Geological Survey Scientific Investigations Report 2017–5147, 79 p., https://doi.org/10.3133/sir20175147.","productDescription":"vi, 79 p.","numberOfPages":"90","onlineOnly":"N","ipdsId":"IP-077501","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":351840,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5147/coverthb.jpg"},{"id":351841,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5147/sir20175147.pdf","text":"Report","size":"4.32 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\"}}]}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way
Suite 5
Lansing, MI 48911
Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeog.2018.02.005","usgsCitation":"Bagstad, K.J., Cohen, E., Ancona, Z.H., McNulty, S., and Sun, G., 2018, The sensitivity of ecosystem service models to choices of input data and spatial resolution: Applied Geography, v. 93, p. 25-36, https://doi.org/10.1016/j.apgeog.2018.02.005.","productDescription":"12 p.","startPage":"25","endPage":"36","ipdsId":"IP-089975","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":438005,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CR5S92","text":"USGS data release","linkHelpText":"Data Release for The sensitivity of ecosystem service models to choices of input data and spatial resolution"},{"id":351849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Rwanda","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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Ge","contributorId":145893,"corporation":false,"usgs":false,"family":"Sun","given":"Ge","email":"","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":729148,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195514,"text":"70195514 - 2018 - On the exchange of sensible and latent heat between the atmosphere and melting snow","interactions":[],"lastModifiedDate":"2018-02-20T10:13:24","indexId":"70195514","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":681,"text":"Agricultural and Forest Meteorology","active":true,"publicationSubtype":{"id":10}},"title":"On the exchange of sensible and latent heat between the atmosphere and melting snow","docAbstract":"The snow energy balance is difficult to measure during the snowmelt period, yet critical for predictions of water yield in regions characterized by snow cover. Robust simplifications of the snowmelt energy balance can aid our understanding of water resources in a changing climate. Research to date has demonstrated that the net turbulent flux (FT) between a melting snowpack and the atmosphere is negligible if the sum of atmospheric vapor pressure (ea) and temperature (Ta) equals a constant, but it is unclear how frequently this situation holds across different sites. Here, we quantified the contribution of FT to the snowpack energy balance during 59 snowmelt periods across 11 sites in the FLUXNET2015 database with a detailed analysis of snowmelt in subarctic tundra near Abisko, Sweden. At the Abisko site we investigated the frequency of occurrences during which sensible heat flux (H) and latent heat flux (λE) are of (approximately) equal but opposite sign, and if the sum of these terms, FT, is therefore negligible during the snowmelt period. H approximately equaled -λE for less than 50% of the melt period and FT was infrequently a trivial term in the snowmelt energy balance at Abisko. The reason is that the relationship between observed ea and Ta is roughly orthogonal to the “line of equality” at which H equals -λE as warmer Ta during the melt period usually resulted in greater ea. This relationship holds both within melt periods at individual sites and across different sites in the FLUXNET2015 database, where FTcomprised less than 20% of the energy available to melt snow, Qm, in 44% of the snowmelt periods studied here. FT/Qm was significantly related to the mean ea during the melt period, but not mean Ta, and FT tended to be near 0 W m−2 when ea averaged ca. 0.5 kPa. FT may become an increasingly important term in the snowmelt energy balance across many global regions as warmer temperatures are projected to cause snow to melt more slowly and earlier in the year under conditions of lower net radiation (Rn). Eddy covariance research networks such as Ameriflux must improve their ability to observe cold-season processes to enhance our understanding of water resources and surface-atmosphere exchange in a changing climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agrformet.2018.01.028","usgsCitation":"Stoy, P., Peitzsch, E.H., Wood, D.J., Rottinghaus, D., Wohlfahrt, G., Goulden, M., and Ward, H., 2018, On the exchange of sensible and latent heat between the atmosphere and melting snow: Agricultural and Forest Meteorology, v. 252, p. 167-174, https://doi.org/10.1016/j.agrformet.2018.01.028.","productDescription":"8 p.","startPage":"167","endPage":"174","ipdsId":"IP-087816","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468984,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agrformet.2018.01.028","text":"Publisher Index Page"},{"id":351808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"252","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee729e4b0da30c1bfc158","contributors":{"authors":[{"text":"Stoy, Paul C.","contributorId":60860,"corporation":false,"usgs":true,"family":"Stoy","given":"Paul C.","affiliations":[],"preferred":false,"id":728960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":728958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, David J. 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A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":728959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rottinghaus, Daniel","contributorId":202579,"corporation":false,"usgs":false,"family":"Rottinghaus","given":"Daniel","email":"","affiliations":[{"id":36485,"text":"Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana, USA.","active":true,"usgs":false}],"preferred":false,"id":728961,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wohlfahrt, Georg","contributorId":202591,"corporation":false,"usgs":false,"family":"Wohlfahrt","given":"Georg","email":"","affiliations":[],"preferred":false,"id":728989,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Goulden, Michael","contributorId":192006,"corporation":false,"usgs":false,"family":"Goulden","given":"Michael","email":"","affiliations":[],"preferred":false,"id":728963,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ward, Helen","contributorId":202581,"corporation":false,"usgs":false,"family":"Ward","given":"Helen","email":"","affiliations":[{"id":36487,"text":"Department of Meteorology, University of Reading, Reading, RG6 6BB, United Kingdom and Institute of Atmospheric and Cryospheric Sciences, University of Innsbruck, 6020 Innsbruck, Austria","active":true,"usgs":false}],"preferred":false,"id":728964,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195518,"text":"70195518 - 2018 - Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor","interactions":[],"lastModifiedDate":"2018-02-20T12:46:47","indexId":"70195518","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor","title":"Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor","docAbstract":"Defining and identifying changes to seasonal ranges of migratory species is required for effective conservation. Historic sightings of migrating whooping cranes (Grus americana) have served as sole source of information to define a migration corridor in the Great Plains of North America (i.e., Canadian Prairies and United States Great Plains) for this endangered species. We updated this effort using past opportunistic sightings from 1942–2016 (n = 5,055) and more recent (2010–2016) location data from 58 telemetered birds (n = 4,423) to delineate migration corridors that included 50%, 75%, and 95% core areas. All migration corridors were well defined and relatively compact, with the 95% core corridor averaging 294 km wide, although it varied approximately ±40% in width from 170 km in central Texas to 407 km at the international border of the United States and Canada. Based on historic sightings and telemetry locations, we detected easterly movements in locations over time, primarily due to locations west of the median shifting east. This shift occurred from northern Oklahoma to central Saskatchewan at an average rate of 1.2 km/year (0.3–2.8 km/year). Associated with this directional shift was a decrease in distance of locations from the median in the same region averaging -0.7 km/year (-0.3–-1.3 km/year), suggesting a modest narrowing of the migration corridor. Changes in the corridor over the past 8 decades suggest that agencies and organizations interested in recovery of this species may need to modify where conservation and recovery actions occur. Whooping cranes showed apparent plasticity in their migratory behavior, which likely has been necessary for persistence of a wetland-dependent species migrating through the drought-prone Great Plains. Behavioral flexibility will be useful for whooping cranes to continue recovery in a future of uncertain climate and land use changes throughout their annual range.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0192737","usgsCitation":"Pearse, A.T., Rabbe, M., Juliusson, L.M., Bidwell, M.T., Craig-Moore, L., Brandt, D.A., and Harrell, W.C., 2018, Delineating and identifying long-term changes in the whooping crane (Grus americana) migration corridor: PLoS ONE, v. 13, no. 2, p. 1-15, https://doi.org/10.1371/journal.pone.0192737.","productDescription":"e0192737; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-090602","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0192737","text":"Publisher Index Page"},{"id":351820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-15","publicationStatus":"PW","scienceBaseUri":"5afee729e4b0da30c1bfc150","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":728990,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rabbe, Matt","contributorId":202597,"corporation":false,"usgs":false,"family":"Rabbe","given":"Matt","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":728991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Juliusson, Lara M.","contributorId":202593,"corporation":false,"usgs":false,"family":"Juliusson","given":"Lara","email":"","middleInitial":"M.","affiliations":[{"id":36490,"text":"USFWS, Lakewood, CO","active":true,"usgs":false}],"preferred":false,"id":728992,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bidwell, Mark T.","contributorId":202007,"corporation":false,"usgs":false,"family":"Bidwell","given":"Mark","email":"","middleInitial":"T.","affiliations":[{"id":36318,"text":"CWS","active":true,"usgs":false}],"preferred":false,"id":728993,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Craig-Moore, Lea","contributorId":202595,"corporation":false,"usgs":false,"family":"Craig-Moore","given":"Lea","email":"","affiliations":[{"id":36491,"text":"Environment and Climate Change Canada, Saskatoon, SK","active":true,"usgs":false}],"preferred":false,"id":728994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":728995,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Harrell, Wade C.","contributorId":147143,"corporation":false,"usgs":false,"family":"Harrell","given":"Wade","email":"","middleInitial":"C.","affiliations":[{"id":16793,"text":"USFWS, Ecological Services, Austwell, TX","active":true,"usgs":false}],"preferred":false,"id":728996,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195521,"text":"70195521 - 2018 - Improving estimation of flight altitude in wildlife telemetry studies","interactions":[],"lastModifiedDate":"2018-07-03T11:37:03","indexId":"70195521","displayToPublicDate":"2018-02-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Improving estimation of flight altitude in wildlife telemetry studies","docAbstract":"Chelonid alphaherpesvirus 5 (ChHV5) is a herpesvirus associated with fibropapillomatosis (FP) in sea turtles worldwide. Single-locus typing has previously shown differentiation between Atlantic and Pacific strains of this virus, with low variation within each geographic clade. However, a lack of multi-locus genomic sequence data hinders understanding of the rate and mechanisms of ChHV5 evolutionary divergence, as well as how these genomic changes may contribute to differences in disease manifestation. To assess genomic variation in ChHV5 among five Hawaii and three Florida green sea turtles, we used high-throughput short-read sequencing of long-range PCR products amplified from tumor tissue using primers designed from the single available ChHV5 reference genome from a Hawaii green sea turtle. This strategy recovered sequence data from both geographic regions for approximately 75% of the predicted ChHV5 coding sequences. The average nucleotide divergence between geographic populations was 1.5%; most of the substitutions were fixed differences between regions. Protein divergence was generally low (average 0.08%), and ranged between 0 and 5.3%. Several atypical genes originally identified and annotated in the reference genome were confirmed in ChHV5 genomes from both geographic locations. Unambiguous recombination events between geographic regions were identified, and clustering of private alleles suggests the prevalence of recombination in the evolutionary history of ChHV5. This study significantly increased the amount of sequence data available from ChHV5 strains, enabling informed selection of loci for future population genetic and natural history studies, and suggesting the (possibly latent) co-infection of individuals by well-differentiated geographic variants.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.4386","usgsCitation":"Morrison, C.L., Iwanowicz, L.R., Work, T.M., Fahsbender, E., Breitbart, M., Adams, C.R., Iwanowicz, D.D., Sanders, L., Ackermann, M., and Cornman, R.S., 2018, Genomic evolution, recombination, and inter-strain diversity of chelonid alphaherpesvirus 5 from Florida and Hawaii green sea turtles with fibropapillomatosis: PeerJ, v. 6, p. 1-33, https://doi.org/10.7717/peerj.4386.","productDescription":"e4386; 33 p.","startPage":"1","endPage":"33","ipdsId":"IP-091221","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":461031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.4386","text":"Publisher Index 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Elizabeth","contributorId":139299,"corporation":false,"usgs":false,"family":"Fahsbender","given":"Elizabeth","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":729208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Breitbart, Mya","contributorId":139298,"corporation":false,"usgs":false,"family":"Breitbart","given":"Mya","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":729209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adams, Cynthia R. 0000-0003-4383-530X cradams@usgs.gov","orcid":"https://orcid.org/0000-0003-4383-530X","contributorId":176965,"corporation":false,"usgs":true,"family":"Adams","given":"Cynthia","email":"cradams@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science 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Mathias","contributorId":127682,"corporation":false,"usgs":false,"family":"Ackermann","given":"Mathias","email":"","affiliations":[{"id":7110,"text":"Institute of Virology, University of Zurich, Switzerland.","active":true,"usgs":false}],"preferred":false,"id":729210,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":729213,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70197034,"text":"70197034 - 2018 - The potential of unmanned aerial systems for sea turtle research and conservation: a review and future directions","interactions":[],"lastModifiedDate":"2018-05-15T16:10:55","indexId":"70197034","displayToPublicDate":"2018-02-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"The potential of unmanned aerial systems for sea turtle research and conservation: a review and future directions","docAbstract":"The use of satellite systems and manned aircraft surveys for remote data collection has been shown to be transformative for sea turtle conservation and research by enabling the collection of data on turtles and their habitats over larger areas than can be achieved by surveys on foot or by boat. Unmanned aerial vehicles (UAVs) or drones are increasingly being adopted to gather data, at previously unprecedented spatial and temporal resolutions in diverse geographic locations. This easily accessible, low-cost tool is improving existing research methods and enabling novel approaches in marine turtle ecology and conservation. Here we review the diverse ways in which incorporating inexpensive UAVs may reduce costs and field time while improving safety and data quality and quantity over existing methods for studies on turtle nesting, at-sea distribution and behaviour surveys, as well as expanding into new avenues such as surveillance against illegal take. Furthermore, we highlight the impact that high-quality aerial imagery captured by UAVs can have for public outreach and engagement. This technology does not come without challenges. We discuss the potential constraints of these systems within the ethical and legal frameworks which researchers must operate and the difficulties that can result with regard to storage and analysis of large amounts of imagery. We then suggest areas where technological development could further expand the utility of UAVs as data-gathering tools; for example, functioning as downloading nodes for data collected by sensors placed on turtles. Development of methods for the use of UAVs in sea turtle research will serve as case studies for use with other marine and terrestrial taxa.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr00877","usgsCitation":"Rees, A.F., Avens, L., Ballorain, K., Bevan, E., Broderick, A.C., Carthy, R.R., Christianen, M.J., Duclos, G., Heithaus, M.R., Johnston, D.W., Mangel, J.C., Paladino, F.V., Pendoley, K., Reina, R.D., Robinson, N.J., Ryan, R., Sykora-Bodie, S.T., Tilley, D., Varela, M.R., Whitman, E.R., Whittock, P.A., Wibbels, T., and Godley, B.J., 2018, The potential of unmanned aerial systems for sea turtle research and conservation: a review and future directions: Endangered Species Research, v. 35, p. 81-100, https://doi.org/10.3354/esr00877.","productDescription":"20 p.","startPage":"81","endPage":"100","ipdsId":"IP-093032","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr00877","text":"Publisher Index Page"},{"id":354192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee72ae4b0da30c1bfc15e","contributors":{"authors":[{"text":"Rees, Alan F.","contributorId":112862,"corporation":false,"usgs":true,"family":"Rees","given":"Alan","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":735424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avens, Larisa","contributorId":204905,"corporation":false,"usgs":false,"family":"Avens","given":"Larisa","email":"","affiliations":[],"preferred":false,"id":735425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ballorain, Katia","contributorId":204906,"corporation":false,"usgs":false,"family":"Ballorain","given":"Katia","email":"","affiliations":[],"preferred":false,"id":735426,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bevan, Elizabeth","contributorId":204907,"corporation":false,"usgs":false,"family":"Bevan","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":735427,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Broderick, Annette C.","contributorId":174296,"corporation":false,"usgs":false,"family":"Broderick","given":"Annette","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":735428,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":735322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christianen, Marjolijn J. A.","contributorId":204908,"corporation":false,"usgs":false,"family":"Christianen","given":"Marjolijn","email":"","middleInitial":"J. A.","affiliations":[],"preferred":false,"id":735429,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duclos, Gwenael","contributorId":204909,"corporation":false,"usgs":false,"family":"Duclos","given":"Gwenael","email":"","affiliations":[],"preferred":false,"id":735430,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Heithaus, Michael R.","contributorId":42828,"corporation":false,"usgs":true,"family":"Heithaus","given":"Michael","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735431,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnston, David W.","contributorId":112845,"corporation":false,"usgs":true,"family":"Johnston","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":735432,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mangel, Jeffrey C.","contributorId":204910,"corporation":false,"usgs":false,"family":"Mangel","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":735433,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Paladino, Frank V.","contributorId":192083,"corporation":false,"usgs":false,"family":"Paladino","given":"Frank","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":735434,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pendoley, Kellie","contributorId":204911,"corporation":false,"usgs":false,"family":"Pendoley","given":"Kellie","email":"","affiliations":[],"preferred":false,"id":735435,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Reina, Richard D.","contributorId":204912,"corporation":false,"usgs":false,"family":"Reina","given":"Richard","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":735436,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Robinson, Nathan J.","contributorId":204913,"corporation":false,"usgs":false,"family":"Robinson","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735437,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ryan, Robert","contributorId":204914,"corporation":false,"usgs":false,"family":"Ryan","given":"Robert","affiliations":[],"preferred":false,"id":735438,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sykora-Bodie, Seth T.","contributorId":204915,"corporation":false,"usgs":false,"family":"Sykora-Bodie","given":"Seth","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":735439,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Tilley, Dominic","contributorId":204916,"corporation":false,"usgs":false,"family":"Tilley","given":"Dominic","email":"","affiliations":[],"preferred":false,"id":735440,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Varela, Miguel R.","contributorId":204917,"corporation":false,"usgs":false,"family":"Varela","given":"Miguel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735441,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Whitman, Elizabeth R.","contributorId":204918,"corporation":false,"usgs":false,"family":"Whitman","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":735442,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Whittock, Paul A.","contributorId":204919,"corporation":false,"usgs":false,"family":"Whittock","given":"Paul","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":735443,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Wibbels, Thane","contributorId":200839,"corporation":false,"usgs":false,"family":"Wibbels","given":"Thane","email":"","affiliations":[],"preferred":false,"id":735444,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Godley, Brendan J.","contributorId":174289,"corporation":false,"usgs":false,"family":"Godley","given":"Brendan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":735445,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70195463,"text":"70195463 - 2018 - Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)","interactions":[],"lastModifiedDate":"2018-02-16T10:33:21","indexId":"70195463","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)","docAbstract":"Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2018.1437297","usgsCitation":"Wilson, N., and Norman, L., 2018, Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI): International Journal of Remote Sensing, v. 39, no. 10, p. 3243-3274, https://doi.org/10.1080/01431161.2018.1437297.","productDescription":"30 p.","startPage":"3243","endPage":"3274","ipdsId":"IP-087663","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":468994,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/01431161.2018.1437297","text":"Publisher Index Page"},{"id":438011,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F798867T","text":"USGS data release","linkHelpText":"Data Release for Analysis of Vegetation Recovery Surrounding a Restored Wetland using the Normalized Difference Infrared Index (NDII) and Normalized Difference Vegetation Index (NDVI)"},{"id":351692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Cuenca Los Ojos, San Bernardino National Wildlife Refuge, San Bernadino Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.51995849609375,\n 31.049404461655996\n ],\n [\n -108.93630981445312,\n 31.049404461655996\n ],\n [\n -108.93630981445312,\n 31.468496379205966\n ],\n [\n -109.51995849609375,\n 31.468496379205966\n ],\n [\n -109.51995849609375,\n 31.049404461655996\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-12","publicationStatus":"PW","scienceBaseUri":"5afee72be4b0da30c1bfc16e","contributors":{"authors":[{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":728707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura","contributorId":202535,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":728708,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195452,"text":"70195452 - 2018 - Molecular and morphological data reveal non-monophyly and speciation in imperiled freshwater mussels (Anodontoides and Strophitus)","interactions":[],"lastModifiedDate":"2018-02-16T10:41:06","indexId":"70195452","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Molecular and morphological data reveal non-monophyly and speciation in imperiled freshwater mussels (Anodontoides and Strophitus)","title":"Molecular and morphological data reveal non-monophyly and speciation in imperiled freshwater mussels (Anodontoides and Strophitus)","docAbstract":"Accurate taxonomic placement is vital to conservation efforts considering many intrinsic biological characteristics of understudied species are inferred from closely related taxa. The rayed creekshell, Anodontoides radiatus (Conrad, 1834), exists in the Gulf of Mexico drainages from western Florida to Louisiana and has been petitioned for listing under the Endangered Species Act. We set out to resolve the evolutionary history of A. radiatus, primarily generic placement and species boundaries, using phylogenetic, morphometric, and geographic information. Our molecular matrix contained 3 loci: cytochrome c oxidase subunit I, NADH dehydrogenase subunit I, and the nuclear-encoded ribosomal internal transcribed spacer I. We employed maximum likelihood and Bayesian inference to estimate a phylogeny and test the monophyly of Anodontoides and Strophitus. We implemented two coalescent-based species delimitation models to test seven species models and evaluate species boundaries within A. radiatus. Concomitant to molecular data, we also employed linear morphometrics and geographic information to further evaluate species boundaries. Molecular and morphological evidence supports the inclusion of A. radiatus in the genus Strophitus, and we resurrect the binomial Strophitus radiatus to reflect their shared common ancestry. We also found strong support for polyphyly in Strophitus and advocate the resurrection of the genus Pseudodontoideus to represent ‘Strophitus’ connasaugaensis and ‘Strophitus’ subvexus. Strophitus radiatus exists in six well-supported clades that were distinguished as evolutionary independent lineages using Bayesian inference, maximum likelihood, and coalescent-based species delimitation models. Our integrative approach found evidence for as many as 4 evolutionary divergent clades within S. radiatus. Therefore, we formally describe two new species from the S. radiatus species complex (Strophitus williamsi and Strophitus pascagoulaensis) and recognize the potential for a third putative species (Strophitus sp. cf. pascagoulaensis). Our findings aid stakeholders in establishing conservation and management strategies for the members of Anodontoides, Strophitus, and Pseudodontoideus.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2017.10.018","usgsCitation":"Smith, C.H., Johnson, N.A., Pfeiffer, J., and Gangloff, M.M., 2018, Molecular and morphological data reveal non-monophyly and speciation in imperiled freshwater mussels (Anodontoides and Strophitus): Molecular Phylogenetics and Evolution, v. 119, p. 50-62, https://doi.org/10.1016/j.ympev.2017.10.018.","productDescription":"13 p.","startPage":"50","endPage":"62","ipdsId":"IP-079947","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":351691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":351688,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CC0Z5N","text":"USGS data release","linkHelpText":"Genetics rayed creekshell"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.09790039062499,\n 27.916766641249065\n ],\n [\n -82.90283203125,\n 27.916766641249065\n ],\n [\n -82.90283203125,\n 35.04798673426734\n ],\n [\n -94.09790039062499,\n 35.04798673426734\n ],\n [\n -94.09790039062499,\n 27.916766641249065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee72ce4b0da30c1bfc172","contributors":{"authors":[{"text":"Smith, Chase H. 0000-0002-1499-0311 csmith@usgs.gov","orcid":"https://orcid.org/0000-0002-1499-0311","contributorId":202519,"corporation":false,"usgs":true,"family":"Smith","given":"Chase","email":"csmith@usgs.gov","middleInitial":"H.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":728672,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan A. 0000-0001-5167-1988 najohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":4175,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","email":"najohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":728671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeiffer, John M.","contributorId":202521,"corporation":false,"usgs":false,"family":"Pfeiffer","given":"John M.","affiliations":[{"id":36469,"text":"Florida Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":728673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gangloff, Michael M.","contributorId":178871,"corporation":false,"usgs":false,"family":"Gangloff","given":"Michael","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":728674,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195449,"text":"70195449 - 2018 - Spatial patterns and temporal changes in atmospheric-mercury deposition for the midwestern USA, 2001–2016","interactions":[],"lastModifiedDate":"2018-02-20T10:17:43","indexId":"70195449","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Spatial patterns and temporal changes in atmospheric-mercury deposition for the midwestern USA, 2001–2016","docAbstract":"Spatial patterns and temporal changes in atmospheric-mercury (Hg) deposition were examined in a five-state study area in the Midwestern USA where 32% of the stationary sources of anthropogenic Hg emissions in the continental USA were located. An extensive monitoring record for wet and dry Hg deposition was compiled for 2001–2016, including 4666 weekly precipitation samples at 13 sites and 27 annual litterfall-Hg samples at 7 sites. This study is the first to examine these Hg data for the Midwestern USA. The median annual precipitation-Hg deposition at the study sites was 10.4 micrograms per square meter per year (ug/m2/year) and ranged from 5.8 ug/m2/year to 15.0 ug/m2/year. The median annual Hg concentration was 9.4 ng/L. Annual litterfall-Hg deposition had a median of 16.1 ug/m2/year and ranged from 9.7 to 23.4 ug/m2/year. Isopleth maps of annual precipitation-Hg deposition indicated a recurring spatial pattern similar to one revealed by statistical analysis of weekly precipitation-Hg deposition. In that pattern, high Hg deposition in southeastern Indiana was present each year, frequently extending to southern Illinois. Most of central Indiana and central Illinois had similar Hg deposition. Areas with comparatively lower annual Hg deposition were observed in Michigan and Ohio for many years and frequently included part of northern Indiana. The area in southern Indiana where high Hg deposition predominated had the highest number of extreme episodes of weekly Hg deposition delivering up to 15% of the annual Hg load from precipitation in a single week. Modeled 48-h back trajectories indicated air masses for these episodes often arrived from the south and southwest, crossing numerous stationary sources of Hg emissions releasing from 23 to more than 300 kg Hg per year. This analysis suggests that local and regional, rather than exclusively continental or global Hg emissions were likely contributing to the extreme episodes and at least in part, to the spatial patterns of precipitation-Hg deposition in the study area. Statistically significant temporal decreases in weekly precipitation-Hg concentrations in\nthe study area between the periods 2001–2013 and 2014–2016 were observed, coinciding with reported reductions in Hg emissions in the USA required by implementation of national Hg emissions-control rules. These decreases in atmospheric-Hg concentrations are believed to have resulted in the reduced atmospheric-Hg deposition recorded because precipitation depths between the two periods were not significantly different. The Hg-monitoring data for the study area identified an atmospheric deposition response to decreased local and regional Hg emissions.","language":"English","publisher":"MDPI","doi":"10.3390/atmos9010029","usgsCitation":"Risch, M.R., and Kenski, D.M., 2018, Spatial patterns and temporal changes in atmospheric-mercury deposition for the midwestern USA, 2001–2016: Atmosphere, v. 9, no. 1, p. 1-20, https://doi.org/10.3390/atmos9010029.","productDescription":"Article 29; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-091127","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":469098,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos9010029","text":"Publisher Index Page"},{"id":351696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Kentucky, Michigan, Ohio","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-89.366031,42.500274],[-87.815872,42.49192],[-87.812461,42.232278],[-87.365439,41.629536],[-86.679672,41.844579],[-86.23528,42.564958],[-86.226305,42.988284],[-86.540916,43.633158],[-86.25395,44.64808],[-86.066745,44.905685],[-85.780439,44.977932],[-85.540497,45.210169],[-85.641652,44.810816],[-85.520205,44.960347],[-85.477423,44.813781],[-85.355478,45.282774],[-84.91585,45.393115],[-85.069573,45.459239],[-85.079528,45.617083],[-84.94565,45.708621],[-85.011433,45.757962],[-84.774156,45.788918],[-83.488826,45.355872],[-83.316118,45.141958],[-83.435822,45.000012],[-83.277213,44.7167],[-83.335248,44.357995],[-83.890145,43.934672],[-83.909479,43.672622],[-83.618602,43.628891],[-83.227093,43.981003],[-82.915976,44.070503],[-82.643166,43.852468],[-82.423086,42.988728],[-82.509935,42.637294],[-82.648776,42.550401],[-82.630922,42.64211],[-82.780817,42.652232],[-83.40822,41.832654],[-83.37573,41.686647],[-82.481214,41.381342],[-81.69325,41.514161],[-80.533774,41.973475],[-80.518991,40.638801],[-80.667957,40.582496],[-80.619297,40.26517],[-80.88036,39.620706],[-81.656138,39.277355],[-81.874857,38.881174],[-82.068864,38.984878],[-82.318111,38.457876],[-82.569368,38.406258],[-82.611343,38.171548],[-82.474635,37.905902],[-81.982479,37.541807],[-83.128813,36.757864],[-83.690714,36.582581],[-88.011792,36.677025],[-88.127378,36.49854],[-89.380085,36.500416],[-89.192542,36.635997],[-89.098843,36.95785],[-89.438275,37.161287],[-89.566704,37.707189],[-90.353902,38.213855],[-90.166409,38.876348],[-90.406367,38.962554],[-90.625122,38.888654],[-90.767648,39.280025],[-91.367753,39.729029],[-91.511073,40.188794],[-91.406202,40.542698],[-91.123928,40.669152],[-90.952233,40.954047],[-91.100829,41.230532],[-91.05158,41.385283],[-90.364128,41.579633],[-90.153362,41.915593],[-90.206369,42.1455],[-90.646727,42.471904],[-89.366031,42.500274]]],[[[-88.684434,48.115785],[-88.447236,48.182916],[-89.022736,47.858532],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-88.116846,45.921703],[-90.120489,46.336852],[-90.344338,46.552087],[-89.790663,46.818469],[-88.982483,46.99883],[-88.400224,47.379551],[-87.816958,47.471998],[-87.730804,47.449112],[-88.349952,47.076377],[-88.462349,46.786711],[-88.167373,46.9588],[-87.915943,46.909508],[-87.619747,46.79821],[-87.366767,46.507303],[-86.850111,46.434114],[-86.188024,46.654008],[-84.964652,46.772845],[-84.969464,46.47629],[-84.177428,46.52692],[-84.097766,46.256512],[-84.247687,46.17989],[-83.931175,46.017871],[-83.63498,46.103953],[-83.49484,45.999541],[-84.345451,45.946569],[-84.656567,46.052654],[-84.820557,45.868293],[-85.047028,46.020603],[-85.528403,46.087121],[-85.663966,45.967013],[-86.278007,45.942057],[-86.687208,45.634253],[-86.532989,45.882665],[-86.92106,45.697868],[-87.018902,45.838886],[-87.612019,45.123377],[-87.727276,45.216129],[-87.648476,45.352243],[-87.860432,45.423504],[-87.831442,45.714938],[-88.131834,45.811312],[-88.116846,45.921703]]]]},\"properties\":{\"name\":\"Illinois\",\"nation\":\"USA \"}}]}","volume":"9","issue":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-18","publicationStatus":"PW","scienceBaseUri":"5afee72ce4b0da30c1bfc174","contributors":{"authors":[{"text":"Risch, Martin R. 0000-0002-7908-7887 mrrisch@usgs.gov","orcid":"https://orcid.org/0000-0002-7908-7887","contributorId":2118,"corporation":false,"usgs":true,"family":"Risch","given":"Martin","email":"mrrisch@usgs.gov","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":728666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenski, Donna M.","contributorId":202515,"corporation":false,"usgs":false,"family":"Kenski","given":"Donna","email":"","middleInitial":"M.","affiliations":[{"id":36467,"text":"Lake Michigan Air Directors Consortium","active":true,"usgs":false}],"preferred":false,"id":728667,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195448,"text":"70195448 - 2018 - Host-pathogen metapopulation dynamics suggest high elevation refugia for boreal toads","interactions":[],"lastModifiedDate":"2018-06-04T16:13:31","indexId":"70195448","displayToPublicDate":"2018-02-16T00:00:00","publicationYear":"2018","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":"Host-pathogen metapopulation dynamics suggest high elevation refugia for boreal toads","docAbstract":"Emerging infectious diseases are an increasingly common threat to wildlife. Chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), is an emerging infectious disease that has been linked to amphibian declines around the world. Few studies exist that explore amphibian-Bd dynamics at the landscape scale, limiting our ability to identify which factors are associated with variation in population susceptibility and to develop effective in situdisease management. Declines of boreal toads (Anaxyrus boreas boreas) in the Southern Rocky Mountains are largely attributed to chytridiomycosis but variation exists in local extinction of boreal toads across this metapopulation. Using a large-scale historic dataset, we explored several potential factors influencing disease dynamics in the boreal toad-Bd system: geographic isolation of populations, amphibian community richness, elevational differences, and habitat permanence. We found evidence that boreal toad extinction risk was lowest at high elevations where temperatures may be sub-optimal for Bd growth and where small boreal toad populations may be below the threshold needed for efficient pathogen transmission. In addition, boreal toads were more likely to recolonize high elevation sites after local extinction, again suggesting that high elevations may provide refuge from disease for boreal toads. We illustrate a modeling framework that will be useful to natural resource managers striving to make decisions in amphibian-Bdsystems. Our data suggest that in the southern Rocky Mountains high elevation sites should be prioritized for conservation initiatives like reintroductions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1699","usgsCitation":"Mosher, B.A., Bailey, L.L., Muths, E.L., and Huyvaert, K.P., 2018, Host-pathogen metapopulation dynamics suggest high elevation refugia for boreal toads: Ecological Applications, v. 28, no. 4, p. 926-937, https://doi.org/10.1002/eap.1699.","productDescription":"12 p.","startPage":"926","endPage":"937","ipdsId":"IP-088106","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-07","publicationStatus":"PW","scienceBaseUri":"5afee72ce4b0da30c1bfc176","contributors":{"authors":[{"text":"Mosher, Brittany A.","contributorId":189579,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":728663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bailey, Larissa L. 0000-0002-5959-2018","orcid":"https://orcid.org/0000-0002-5959-2018","contributorId":189578,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":728664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":728662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huyvaert, Kathryn P.","contributorId":202514,"corporation":false,"usgs":false,"family":"Huyvaert","given":"Kathryn","email":"","middleInitial":"P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":728665,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195402,"text":"ofr20171166 - 2018 - Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region","interactions":[],"lastModifiedDate":"2022-04-22T16:28:36.224437","indexId":"ofr20171166","displayToPublicDate":"2018-02-15T16:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1166","title":"Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region","docAbstract":"To improve understanding of the distribution of ecologically important, ephemeral wetland habitats across the Great Plains, the occurrence and distribution of surface water in playa wetland complexes were documented for four different years across the Great Plains Landscape Conservation Cooperative (GPLCC) region. This information is important because it informs land and wildlife managers about the timing and location of habitat availability. Data with an accurate timestamp that indicate the presence of water, the percent of the area inundated with water, and the spatial distribution of playa wetlands with water are needed for a host of resource inventory, monitoring, and research applications. For example, the distribution of inundated wetlands forms the spatial pattern of available habitat for resident shorebirds and water birds, stop-over habitats for migratory birds, connectivity and clustering of wetland habitats, and surface waters that recharge the Ogallala aquifer; there is considerable variability in the distribution of playa wetlands holding water through time. Documentation of these spatially and temporally intricate processes, here, provides data required to assess connections between inundation and multiple environmental drivers, such as climate, land use, soil, and topography. Climate drivers are understood to interact with land cover, land use and soil attributes in determining the amount of water that flows overland into playa wetlands. Results indicated significant spatial variability represented by differences in the percent of playas inundated among States within the GPLCC. Further, analysis-of-variance comparison of differences in inundation between years showed significant differences in all cases. Although some connections with seasonal moisture patterns may be observed, the complex spatial-temporal gradients of precipitation, temperature, soils, and land use need to be combined as covariates in multivariate models to effectively account for these patterns. We demonstrate the feasibility of using classification of Landsat satellite imagery to describe playa-wetland inundation across years and seasons. Evaluating classifications representing only 4 years of imagery, we found significant year-to-year and state-to-state differences in inundation rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171166","collaboration":"Prepared in cooperation with the Great Plains Landscape Conservation Cooperative, U.S. Fish and Wildlife Service, Albuquerque, New Mexico","usgsCitation":"Manier, D.J., and Rover, J.R., 2018, Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region: U.S. Geological Survey Open-File Report 2017–1166, 20 p., https://doi.org/10.3133/ofr20171166.","productDescription":"iv, 20 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-073569","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438012,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MW2GCN","text":"USGS data release","linkHelpText":"Landsat classification of surface water for multiple seasons to monitor inundation of playa wetlands"},{"id":351569,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1166/ofr20171166.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1166"},{"id":351568,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1166/coverthb.jpg"}],"country":"United States","otherGeospatial":"Great Plains Landscape Conservation Cooperative","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 30\n ],\n [\n -96,\n 30\n ],\n [\n -96,\n 44\n ],\n [\n -106,\n 44\n ],\n [\n -106,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
The greater sage-grouse (Centrocercus urophasianus; hereafter GRSG) has been a focus of scientific investigation and management action for the past two decades. The 2015 U.S. Fish and Wildlife Service listing determination of “not warranted” was in part due to a large-scale collaborative effort to develop strategies to conserve GRSG populations and their habitat and to reduce threats to both. New scientific information augments existing knowledge and can help inform updates or modifications to existing plans for managing GRSG and sagebrush ecosystems. However, the sheer number of scientific publications can be a challenge for managers tasked with evaluating and determining the need for potential updates to existing planning documents. To assist in this process, the U.S. Geological Survey (USGS) has reviewed and summarized the scientific literature published since January 1, 2015.
To identify articles and reports published about GRSG, we first conducted a structured search of three reference databases (Web of Science, Scopus, and Google Scholar) using the search term “greater sage-grouse.” We refined the initial list of products by (1) removing duplicates, (2) excluding products that were not published as research or scientific review articles in peer-reviewed journals or as formal government technical reports, and (3) retaining only those products for which GRSG or their habitat was a research focus.
We summarized the contents of each product by using a consistent structure (background, objectives, methods, location, findings, and implications) and assessed the content of each product relevant to a list of 31 management topics. These topics include GRSG biology and habitat characteristics along with potential management actions, land uses, and environmental factors related to GRSG management and conservation. We also noted which articles/reports created new geospatial data.
The final search was conducted on January 6, 2018, and application of our criteria resulted in the inclusion of 169 published products (2 of these products were published corrections to journal articles). The management topics most commonly addressed were GRSG behavior or demographics and GRSG habitat selection or habitat characteristics at broad or site scales. Few products addressed captive breeding, recreation, wild horses and burros, and range management structures (including fences). We include in this annotated bibliography the full citation, product summary, and management topics addressed by each product. The online version of this bibliography (https://apps.usgs.gov/gsgbib/index.php) is searchable by topic and location and includes links to the original publications.
A substantial body of literature has been compiled based on research explicitly related to the conservation, management, monitoring, and assessment of GRSG. These studies may inform planning and management actions that seek to balance conservation, economic, and social objectives and manage diverse resource uses and values across the western United States.
The review process for this product included requesting input on each summary from one or more authors of the original peer-reviewed article or report and a formal review of the entire document by three independent reviewers and, subsequently, the USGS Bureau Approving Official. This process is consistent with USGS Fundamental Science Practices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181008","usgsCitation":"Carter, S.K., Manier, D.J., Arkle, R.S., Johnston, A.N., Phillips, S.L., Hanser, S.E., and Bowen, Z.H., 2018, Annotated bibliography of scientific research on greater sage-grouse published since January 2015: U.S. Geological Survey Open-File Report 2018–1008, 183 p., https://doi.org/10.3133/ofr20181008.","productDescription":"v, 183 p.","numberOfPages":"189","onlineOnly":"Y","ipdsId":"IP-093354","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":351662,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181017","text":"Open-File Report 2018-1017:","linkHelpText":"Greater Sage-Grouse Science (2015–17)—Synthesis and Potential Management Implications"},{"id":351501,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://apps.usgs.gov/gsgbib/index.php","text":"Interactive, searchable version:","linkHelpText":"Annotated Bibliography of Scientific Research on Greater Sage-Grouse Published since January 2015"},{"id":351500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1008/ofr20181008.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1008"},{"id":351499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1008/coverthb2.jpg"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
In this study, the Precipitation-Runoff Modelling System (PRMS) was used to simulate changes in surface-water depression storage in the 1,126-km2 Upper Pipestem Creek basin located within the Prairie Pothole Region of North Dakota, USA. The Prairie Pothole Region is characterized by millions of small water bodies (or surface-water depressions) that provide numerous ecosystem services and are considered an important contribution to the hydrologic cycle. The Upper Pipestem PRMS model was extracted from the U.S. Geological Survey's (USGS) National Hydrologic Model (NHM), developed to support consistent hydrologic modelling across the conterminous United States. The Geospatial Fabric database, created for the USGS NHM, contains hydrologic model parameter values derived from datasets that characterize the physical features of the entire conterminous United States for 109,951 hydrologic response units. Each hydrologic response unit in the Geospatial Fabric was parameterized using aggregated surface-water depression area derived from the National Hydrography Dataset Plus, an integrated suite of application-ready geospatial datasets. This paper presents a calibration strategy for the Upper Pipestem PRMS model that uses normalized lake elevation measurements to calibrate the parameters influencing simulated fractional surface-water depression storage. Results indicate that inclusion of measurements that give an indication of the change in surface-water depression storage in the calibration procedure resulted in accurate changes in surface-water depression storage in the water balance. Regionalized parameterization of the USGS NHM will require a proxy for change in surface-storage to accurately parameterize surface-water depression storage within the USGS NHM.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11416","usgsCitation":"Hay, L.E., Norton, P.A., Viger, R.J., Markstrom, S.L., Regan, R.S., and Vanderhoof, M.K., 2018, Modelling surface-water depression storage in a Prairie Pothole Region: Hydrological Processes, v. 32, no. 4, p. 462-479, https://doi.org/10.1002/hyp.11416.","productDescription":"18 p.","startPage":"462","endPage":"479","ipdsId":"IP-080013","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","otherGeospatial":"Upper Pipestem Creek basin","volume":"32","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-08","publicationStatus":"PW","scienceBaseUri":"5afee72de4b0da30c1bfc182","contributors":{"authors":[{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norton, Parker A. 0000-0002-4638-2601 pnorton@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-2601","contributorId":2257,"corporation":false,"usgs":true,"family":"Norton","given":"Parker","email":"pnorton@usgs.gov","middleInitial":"A.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":729978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, R. Steve 0000-0003-4803-8596 rsregan@usgs.gov","orcid":"https://orcid.org/0000-0003-4803-8596","contributorId":196973,"corporation":false,"usgs":true,"family":"Regan","given":"R.","email":"rsregan@usgs.gov","middleInitial":"Steve","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":729975,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":729979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195764,"text":"70195764 - 2018 - Egg turning behavior and incubation temperature in Forster’s terns in relation to mercury contamination","interactions":[],"lastModifiedDate":"2018-03-01T10:51:27","indexId":"70195764","displayToPublicDate":"2018-02-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Egg turning behavior and incubation temperature in Forster’s terns in relation to mercury contamination","docAbstract":"Egg turning behavior is an important determinant of egg hatchability, but it remains relatively understudied. Here, we examined egg turning rates and egg temperatures in Forster’s terns (Sterna forsteri). We used artificial eggs containing a data logger with a 3-D accelerometer, a magnetometer, and a temperature thermistor to monitor parental incubation behavior of 131 tern nests. Overall, adults turned their eggs an average (±SD) of 3.8 ± 0.8 turns h-1, which is nearly two times higher than that of other seabirds. Egg turning rates increased with nest initiation date. We also examined egg turning rates and egg temperatures in relation to egg mercury contamination. Mercury contamination has been shown to be associated with reduced egg hatchability, and we hypothesized that mercury may decrease egg hatchability via altered egg turning behavior by parents. Despite the high variability in egg turning rates among individuals, the rate of egg turning was not related to mercury concentrations in sibling eggs. These findings highlight the need for further study concerning the potential determinants of egg turning behavior.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0191390","usgsCitation":"Taylor, G.T., Ackerman, J., and Shaffer, S.A., 2018, Egg turning behavior and incubation temperature in Forster’s terns in relation to mercury contamination: PLoS ONE, v. 13, no. 2, p. 1-16, https://doi.org/10.1371/journal.pone.0191390.","productDescription":"e0191390; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-083523","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468995,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0191390","text":"Publisher Index Page"},{"id":352163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-15","publicationStatus":"PW","scienceBaseUri":"5afee72ee4b0da30c1bfc184","contributors":{"authors":[{"text":"Taylor, Gregory T.","contributorId":202849,"corporation":false,"usgs":false,"family":"Taylor","given":"Gregory","email":"","middleInitial":"T.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":729899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":729898,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaffer, Scott A. 0000-0002-7751-5059","orcid":"https://orcid.org/0000-0002-7751-5059","contributorId":202761,"corporation":false,"usgs":false,"family":"Shaffer","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":24620,"text":"San Jose State University","active":true,"usgs":false}],"preferred":false,"id":729900,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196261,"text":"70196261 - 2018 - Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies","interactions":[],"lastModifiedDate":"2018-03-28T17:05:14","indexId":"70196261","displayToPublicDate":"2018-02-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies","docAbstract":"Our understanding of deglacial climate history in the southern Great Lakes region of the United States is primarily based upon fossil pollen data, with few independent and multi-proxy climate reconstructions. Here we introduce a new, well-dated fossil pollen record from Stotzel-Leis, OH, and a new deglacial temperature record based on branched glycerol dialkyl glycerol tetraethers (brGDGTs) at Silver Lake, OH. We compare these new data to previously published records and to a regional stack of pollen-based temperature reconstructions from Stotzel-Leis, Silver Lake, and three other well-dated sites. The new and previously published pollen records at Stotzel-Leis are similar, but our new age model brings vegetation events into closer alignment with known climatic events such as the Younger Dryas (YD). brGDGT-inferred temperatures correlate strongly with pollen-based regional temperature reconstructions, with the strongest correlation obtained for a global soil-based brGDGT calibration (r2 = 0.88), lending confidence to the deglacial reconstructions and the use of brGDGT and regional pollen stacks as paleotemperature proxies in eastern North America. However, individual pollen records show large differences in timing, rates, and amplitudes of inferred temperature change, indicating caution with paleoclimatic inferences based on single-site pollen records. From 16.0 to 10.0ka, both proxies indicate that regional temperatures rose by ∼10 °C, roughly double the ∼5 °C estimates for the Northern Hemisphere reported in prior syntheses. Change-point analysis of the pollen stack shows accelerated warming at 14.0 ± 1.2ka, cooling at 12.6 ± 0.4ka, and warming from 11.6 ± 0.5ka into the Holocene. The timing of Bølling-Allerød (B-A) warming and YD onset in our records lag by ∼300–500 years those reported in syntheses of temperature records from the northern mid-latitudes. This discrepancy is too large to be attributed to uncertainties in radiocarbon dating, and correlation between pollen and brGDGT temperature reconstructions rules out vegetation lags as a cause. However, the YD termination appears synchronous among the brGDGT record, regional pollen stack, and Northern Hemisphere stack. The cause of the larger and lagged temperature changes in the southern Great Lakes relative to Northern Hemisphere averages remains unclear, but may be due to the effects of continentality and ice sheet extent on regional climate evolution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2017.12.011","usgsCitation":"Watson, B.I., Williams, J.W., Russell, J.M., Jackson, S.T., Shane, L., and Lowell, T.V., 2018, Temperature variations in the southern Great Lakes during the last deglaciation: Comparison between pollen and GDGT proxies: Quaternary Science Reviews, v. 182, p. 78-92, https://doi.org/10.1016/j.quascirev.2017.12.011.","productDescription":"15 p.","startPage":"78","endPage":"92","ipdsId":"IP-088633","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":468997,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2017.12.011","text":"Publisher Index Page"},{"id":352887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"182","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee72de4b0da30c1bfc180","contributors":{"authors":[{"text":"Watson, Benjamin I.","contributorId":203629,"corporation":false,"usgs":false,"family":"Watson","given":"Benjamin","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":731980,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":731981,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Russell, James M.","contributorId":174740,"corporation":false,"usgs":false,"family":"Russell","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":27506,"text":"Department of Earth, Environmental and Planetary Sciences, Brown University, Providence RI 02912 USA","active":true,"usgs":false}],"preferred":false,"id":731982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":731921,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shane, Linda","contributorId":203630,"corporation":false,"usgs":false,"family":"Shane","given":"Linda","email":"","affiliations":[],"preferred":false,"id":731983,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lowell, Thomas V.","contributorId":203631,"corporation":false,"usgs":false,"family":"Lowell","given":"Thomas","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":731984,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70191170,"text":"sir20175108 - 2018 - Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa","interactions":[],"lastModifiedDate":"2018-02-14T15:01:18","indexId":"sir20175108","displayToPublicDate":"2018-02-14T13:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5108","title":"Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa","docAbstract":"Basin-characteristic measurements related to stream length, stream slope, stream density, and stream order have been identified as significant variables for estimation of flood, flow-duration, and low-flow discharges in Iowa. The placement of channel initiation points, however, has always been a matter of individual interpretation, leading to differences in stream definitions between analysts.
This study investigated five different methods to define stream initiation using 3-meter light detection and ranging (lidar) digital elevation models (DEMs) data for 17 streamgages with drainage areas less than 50 square miles within the Des Moines Lobe landform region in north-central Iowa. Each DEM was hydrologically enforced and the five stream initiation methods were used to define channel initiation points and the downstream flow paths. The five different methods to define stream initiation were tested side-by-side for three watershed delineations: (1) the total drainage-area delineation, (2) an effective drainage-area delineation of basins based on a 2-percent annual exceedance probability (AEP) 12-hour rainfall, and (3) an effective drainage-area delineation based on a 20-percent AEP 12-hour rainfall.
Generalized least squares regression analysis was used to develop a set of equations for sites in the Des Moines Lobe landform region for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs. A total of 17 streamgages were included in the development of the regression equations. In addition, geographic information system software was used to measure 58 selected basin-characteristics for each streamgage.
Results of the regression analyses of the 15 lidar datasets indicate that the datasets that produce regional regression equations (RREs) with the best overall predictive accuracy are the National Hydrographic Dataset, Iowa Department of Natural Resources, and profile curvature of 0.5 stream initiation methods combined with the 20-percent AEP 12-hour rainfall watershed delineation method. These RREs have a mean average standard error of prediction (SEP) for 4-, 2-, and 1-percent AEP discharges of 53.9 percent and a mean SEP for all eight AEPs of 55.5 percent. Compared to the RREs developed in this study using the basin characteristics from the U.S. Geological Survey StreamStats application, the lidar basin characteristics provide better overall predictive accuracy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175108","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR–692) ","usgsCitation":"Eash, D.A., Barnes, K.K., O’Shea, P.S., and Gelder, B.K., 2018, Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa: U.S. Geological Survey Scientific Investigations Report 2017–5108, 23 p., https://doi.org/10.3133/sir20175108. ","productDescription":"vi, 23 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081688","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":351551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5108/coverthb.jpg"},{"id":351552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5108/sir20175108.pdf","text":"Report","size":"1.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5108"}],"country":"United States","state":"Iowa","otherGeospatial":"Des Moines Lobe landform region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96,\n 41.5\n ],\n [\n -93,\n 41.5\n ],\n [\n -93,\n 43.50075243569041\n ],\n [\n -96,\n 43.50075243569041\n ],\n [\n -96,\n 41.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 S. Clinton St., Rm 269
Iowa City, IA 52240
Quiescence is a period of inactivity that occurs before the onset of migratory activity in nocturnally migrating birds. This behavior has been observed in captive birds in migratory disposition, but its occurrence in free-ranging migratory birds has been documented only anecdotally, and causal factors and function(s), if any, are unknown. In this study, we documented and characterized quiescence in three migratory songbird species (red-eyed vireo [Vireo olivaceus], Swainson’s thrush [Catharus ustulatus], and wood thrush [Hylocichla mustelina]) by measuring movement and proportion of time spent inactive prior to departure from a stopover site during fall migration. Individuals of each species displayed a period of inactivity prior to departure which varied from less than 30 min to over 90 min with red-eyed vireos engaged in the longest, most pronounced quiescence. We also examined how quiescence was related to intrinsic and extrinsic factors known to influence the departure of migrating birds, and found some evidence for an effect of age and departure time but no effect of a migrant’s energetic condition, departure direction, atmospheric conditions around departure, or day of year on quiescence. Our novel application of an automated radiotelemetry system yielded a large amount of data to characterize quiescence in free-ranging migratory birds, and we provide guidance for future studies to tease apart the various causal factors and function(s) of this migratory behavior.
","language":"English","publisher":"Springer","doi":"10.1007/s00265-018-2449-y","usgsCitation":"Schofield, L.N., Deppe, J.L., Diehl, R.H., Ward, M.P., Bolus, R.T., Zenzal, T., Smolinsky, J.A., and Moore, F.R., 2018, Occurrence of quiescence in free-ranging migratory songbirds: Behavioral Ecology and Sociobiology, v. 72, 36, https://doi.org/10.1007/s00265-018-2449-y.","productDescription":"36","ipdsId":"IP-091881","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":410462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","noUsgsAuthors":false,"publicationDate":"2018-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Schofield, Lynn N.","contributorId":173623,"corporation":false,"usgs":false,"family":"Schofield","given":"Lynn","email":"","middleInitial":"N.","affiliations":[{"id":27256,"text":"Dept of Biological Sciences, Eastern Illinois University, Charleston, IL","active":true,"usgs":false}],"preferred":false,"id":858911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deppe, Jill L.","contributorId":173619,"corporation":false,"usgs":false,"family":"Deppe","given":"Jill","email":"","middleInitial":"L.","affiliations":[{"id":27256,"text":"Dept of Biological Sciences, Eastern Illinois University, Charleston, IL","active":true,"usgs":false}],"preferred":false,"id":858912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":858913,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, Michael P.","contributorId":173620,"corporation":false,"usgs":false,"family":"Ward","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":27257,"text":"Dept of Nat Resources and Env Sciences, University of Illinois, Urbana, IL","active":true,"usgs":false}],"preferred":false,"id":858914,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bolus, Rachel T. rbolus@usgs.gov","contributorId":299881,"corporation":false,"usgs":false,"family":"Bolus","given":"Rachel","email":"rbolus@usgs.gov","middleInitial":"T.","affiliations":[{"id":32977,"text":"Southern Utah University","active":true,"usgs":false}],"preferred":false,"id":858915,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zenzal, Theodore J. Jr.","contributorId":299882,"corporation":false,"usgs":false,"family":"Zenzal","given":"Theodore J.","suffix":"Jr.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":858916,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smolinsky, Jaclyn A.","contributorId":202723,"corporation":false,"usgs":false,"family":"Smolinsky","given":"Jaclyn","email":"","middleInitial":"A.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":858917,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moore, Frank R.","contributorId":54582,"corporation":false,"usgs":false,"family":"Moore","given":"Frank","email":"","middleInitial":"R.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":858918,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70247739,"text":"70247739 - 2018 - On the depth extent of co-seismic rupture","interactions":[],"lastModifiedDate":"2023-08-15T14:24:25.063401","indexId":"70247739","displayToPublicDate":"2018-02-13T09:21:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"On the depth extent of co-seismic rupture","docAbstract":"We investigate the implications of deformation experiments for the coseismic down‐dip extent of rupture in quasi‐dynamic, whole‐cycle earthquake models of a fault for which the depth of the transition between seismic and aseisimic fault slip depends on strain rate. The calculations use a dislocation fault model from Tse and Rice (1986) with a vertical strike‐slip orientation, mode III rupture, and variable along‐strike length. Our reference calculation is the original rheological representation of Tse and Rice with a strain‐rate‐independent transition. The primary calculations use two different representations of a strain‐rate‐dependent transition: (1) between rate‐weakening friction and dislocation creep and (2) between rate‐weakening and rate‐strengthening frictions. For both these cases, when fault strength is high (friction between 0.5 and 0.6) and the transition is sharp, coseismic slip extends a small distance (1–2 km) below the fixed temperature (depth) that is commonly used to define the rheological transition at the plate‐motion rate. Thus, coseismic slip occurs below the depth assumed in seismic hazard models using microseismicity or a chosen fixed‐temperature contour. Though significant coseismic slip occurs below the plate‐rate transition depth, the added moment is
Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12609","usgsCitation":"Cohen, S., Brakenridge, G.R., Kettner, A., Bates, B., Nelson, J.M., McDonald, R.R., Huang, Y., Munasinghe, D., and Zhang, J., 2018, Estimating floodwater depths from flood inundation maps and topography: Journal of the American Water Resources Association, v. 54, no. 4, p. 847-858, https://doi.org/10.1111/1752-1688.12609.","productDescription":"12 p.","startPage":"847","endPage":"858","ipdsId":"IP-085532","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":469000,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12609","text":"Publisher Index Page"},{"id":351559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-11-17","publicationStatus":"PW","scienceBaseUri":"5afee730e4b0da30c1bfc19a","contributors":{"authors":[{"text":"Cohen, Sagy","contributorId":202461,"corporation":false,"usgs":false,"family":"Cohen","given":"Sagy","email":"","affiliations":[{"id":36450,"text":"Department of Geography, University of Alabama, Tuscaloosa, AL 35487, USA","active":true,"usgs":false}],"preferred":false,"id":728452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brakenridge, G. Robert","contributorId":202462,"corporation":false,"usgs":false,"family":"Brakenridge","given":"G.","email":"","middleInitial":"Robert","affiliations":[{"id":36451,"text":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":728453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kettner, Albert","contributorId":202463,"corporation":false,"usgs":false,"family":"Kettner","given":"Albert","affiliations":[{"id":36451,"text":"Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309, USA","active":true,"usgs":false}],"preferred":false,"id":728454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bates, Bradford","contributorId":202464,"corporation":false,"usgs":false,"family":"Bates","given":"Bradford","email":"","affiliations":[{"id":36450,"text":"Department of Geography, University of Alabama, Tuscaloosa, AL 35487, USA","active":true,"usgs":false}],"preferred":false,"id":728455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":728451,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":728456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Yu-Fen","contributorId":202465,"corporation":false,"usgs":false,"family":"Huang","given":"Yu-Fen","email":"","affiliations":[{"id":36452,"text":"University of Hawaii at Manoa, HI 96822, USA","active":true,"usgs":false}],"preferred":false,"id":728457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Munasinghe, Dinuke","contributorId":202466,"corporation":false,"usgs":false,"family":"Munasinghe","given":"Dinuke","email":"","affiliations":[{"id":36450,"text":"Department of Geography, University of Alabama, Tuscaloosa, AL 35487, USA","active":true,"usgs":false}],"preferred":false,"id":728458,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zhang, Jiaqi","contributorId":202467,"corporation":false,"usgs":false,"family":"Zhang","given":"Jiaqi","email":"","affiliations":[{"id":36453,"text":"University of Texas, Arlington, TX, USA","active":true,"usgs":false}],"preferred":false,"id":728459,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194535,"text":"sir20175153 - 2018 - Water pressure and ground vibrations induced by water guns near Brandon Road Lock and Dam and Lemont, Illinois","interactions":[],"lastModifiedDate":"2019-07-01T06:32:59","indexId":"sir20175153","displayToPublicDate":"2018-02-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5153","title":"Water pressure and ground vibrations induced by water guns near Brandon Road Lock and Dam and Lemont, Illinois","docAbstract":"Multiple geophysical sensors were used to characterize the underwater pressure field and ground vibrations of a seismic water gun and its suitability to deter the movement of Asian carps (particularly the silver [Hypophthalmichthys molitrix] and bighead [Hypophthalmichthys nobilis] carps) while ensuring the integrity of surrounding structures. The sensors used to collect this information were blast-rated hydrophones, surface- and borehole-mounted geophones, and fixed accelerometers.
Results from two separate studies are discussed in this report. The Brandon Road study took place in May 2014, in the Des Plaines River, in a concrete-walled channel downstream of the Brandon Road Lock and Dam near Joliet, Illinois. The Lemont study took place in June 2014, in a segment of the dolomite setblock-lined Chicago Sanitary and Ship Canal near Lemont, Illinois.
Two criteria were evaluated to assess the potential deterrence to carp migration, and to minimize the expected effect on nearby structures from discharge of the seismic water gun. The first criterion was a 5-pound-per-square-inch (lb/in2) limit for dynamic underwater pressure variations. The second criterion was a maximum velocity and acceleration disturbance of 0.75 inch per second (in/s) for sensitive machinery (such as the lock gates and pumps) and 2.0 in/s adjacent to canal walls, respectively. The criteria were based on previous studies of fish responses to dynamic pressure variations, and effects of vibrations on the structural integrity of concrete walls.
The Brandon Road study evaluated the magnitude and extent of the pressure field created by two water gun configurations in the concrete-walled channel downstream of the lock where channel depths ranged from 11 to 14 feet (ft). Data from a single 80-cubic-inch (in³) water gun set at 6 ft below water surface (bws) produced a roughly cylindrical 5-lb/in2 pressure field 20 ft in radius, oriented vertically, with the radius decreasing to less than 15 ft at the water surface. A combination of two 80-in3 water guns set at 6 and 8 ft, respectively, produced a similarly shaped 5 lb/in2 pressure field 30 ft in radius. Neither of the water gun configurations exceeded the given threshold of 5 lb/in2 above the static pressure along the walls of the canal at the 700 lb/in2 water gun input pressure. Velocity and acceleration data were collected simultaneously with the underwater pressure data to understand the response of adjacent canal walls to the water gun firings. Maximum velocity and acceleration were 0.239 in/s and 0.0188 feet per second squared (ft/s2), respectively.
The Lemont study replicated and expanded upon work done in 2011. The pressure field created by the water gun was evaluated in a deeper environment (about 25 ft of water depth) than that of the Brandon Road study. To replicate the 2011 study, data were collected with the same water gun placements and input pressure, but static underwater pressure monitoring was added. Two 80-in3 water guns were suspended below a platform at depths of 4 and 14 ft bws. Pressure was lower when the gun suspended at 4 ft bws was fired as compared to firing the single gun suspended at 14 ft bws. Firing both guns simultaneously produced similar pressures to the single gun suspended at 14 ft bws. Data were collected to assess the pressure field produced by two 80-in3 water guns separated by 80 ft and suspended at a depth of 14 ft bws. The spatial extent of the 5-lb/in2 threshold varied substantially with gun input air pressure. Firing the water gun with an air pressure of 2,000 lb/in2 generated a pressure field greater than the threshold at all but one location in the measured region. Additionally, the water gun with an air pressure of 1,000 lb/in2 did not reach the threshold anywhere in the measured region. Maximum velocity and acceleration were 0.304 in/s and 0.015 ft/s2, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175153","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency, Great Lakes Restoration Initiative","usgsCitation":"Adams, R.F., Koebel, C.M., and Morrow, W.S., 2018, Water pressure and ground vibrations induced by water guns near Brandon Road Lock and Dam and Lemont, Illinois: U.S. Geological Survey Scientific Investigations Report 2017–5153, 55 p., https://doi.org/10.3133/sir20175153.","productDescription":"ix, 55 p.","numberOfPages":"70","onlineOnly":"Y","ipdsId":"IP-075231","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":351541,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5153/coverthb.jpg"},{"id":351542,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5153/sir20175153.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5153"}],"country":"United States","state":"Illinois","city":" Lemont","otherGeospatial":"Brandon Road Lock and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.1056,\n 41.5033\n ],\n [\n -88.1033,\n 41.5033\n ],\n [\n -88.1033,\n 41.5011\n ],\n [\n -88.1056,\n 41.5011\n ],\n [\n -88.1056,\n 41.5033\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
Urbana, IL 61801
The term resilience describes stress–response patterns of subjects across scientific disciplines. In ecology, advances have been made to clearly distinguish resilience definitions based on underlying mechanistic assumptions. Engineering resilience (rebound) is used for describing the ability of subjects to recover from adverse conditions (disturbances), and is the rate of recovery. In contrast, the ecological resilience definition considers a systemic change: when complex systems (including humans) respond to disturbances by reorganizing into a new regime (stable state) where structural and functional aspects have fundamentally changed relative to the prior regime. In this context, resilience is an emergent property of complex systems. We argue that both resilience definitions and uses are appropriate in psychology and psychiatry, but although the differences are subtle, the implications and uses are profoundly different.
We borrow from the field of ecology to discuss resilience concepts in the mental health sciences.
In psychology and psychiatry, the prevailing view of resilience is adaptation to, coping with, and recovery (engineering resilience) from adverse social and environmental conditions. Ecological resilience may be useful for describing vulnerability, onset, and the irreversibility patterns of mental disorders. We discuss this in the context of bipolar disorder.
Rebound, adaptation, and coping are processes that are subsumed within the broader systemic organization of humans, from which ecological resilience emanates. Discerning resilience concepts in psychology and psychiatry has potential for a mechanistically appropriate contextualization of mental disorders at large. This might contribute to a refinement of theory and contextualize clinical practice within the broader systemic functioning of mental illnesses.
","language":"English","publisher":"Springer","doi":"10.1186/s40345-017-0112-6","usgsCitation":"Angeler, D., Allen, C.R., and Persson, M., 2018, Resilience concepts in psychiatry demonstrated with bipolar disorder: International Journal of Bipolar Disorders, v. 6, 2, 8 p., https://doi.org/10.1186/s40345-017-0112-6.","productDescription":"2, 8 p.","ipdsId":"IP-092342","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40345-017-0112-6","text":"Publisher Index Page"},{"id":395145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2018-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":832311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Persson, Maj-Liz","contributorId":272839,"corporation":false,"usgs":false,"family":"Persson","given":"Maj-Liz","email":"","affiliations":[],"preferred":false,"id":832312,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70195350,"text":"70195350 - 2018 - Development of a multimetric index for integrated assessment of salt marsh ecosystem condition","interactions":[],"lastModifiedDate":"2018-02-09T12:23:09","indexId":"70195350","displayToPublicDate":"2018-02-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Development of a multimetric index for integrated assessment of salt marsh ecosystem condition","docAbstract":"Tools for assessing and communicating salt marsh condition are essential to guide decisions aimed at maintaining or restoring ecosystem integrity and services. Multimetric indices (MMIs) are increasingly used to provide integrated assessments of ecosystem condition. We employed a theory-based approach that considers the multivariate relationship of metrics with human disturbance to construct a salt marsh MMI for five National Parks in the northeastern USA. We quantified the degree of human disturbance for each marsh using the first principal component score from a principal components analysis of physical, chemical, and land use stressors. We then applied a metric selection algorithm to different combinations of about 45 vegetation and nekton metrics (e.g., species abundance, species richness, and ecological and functional classifications) derived from multi-year monitoring data. While MMIs derived from nekton or vegetation metrics alone were strongly correlated with human disturbance (r values from −0.80 to −0.93), an MMI derived from both vegetation and nekton metrics yielded an exceptionally strong correlation with disturbance (r = −0.96). Individual MMIs included from one to five metrics. The metric-assembly algorithm yielded parsimonious MMIs that exhibit the greatest possible correlations with disturbance in a way that is objective, efficient, and reproducible.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0293-3","usgsCitation":"Nagel, J.L., Neckles, H.A., Guntenspergen, G.R., Rocks, E.N., Schoolmaster, D., Grace, J.B., Skidds, D.E., and Stevens, S., 2018, Development of a multimetric index for integrated assessment of salt marsh ecosystem condition: Estuaries and Coasts, v. 41, no. 2, p. 334-348, https://doi.org/10.1007/s12237-017-0293-3.","productDescription":"15 p.","startPage":"334","endPage":"348","ipdsId":"IP-082798","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":351426,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-31","publicationStatus":"PW","scienceBaseUri":"5a7ec170e4b00f54eb25a745","contributors":{"authors":[{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neckles, Hilary A. 0000-0002-5662-2314 hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":727985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rocks, Erika N.","contributorId":202236,"corporation":false,"usgs":false,"family":"Rocks","given":"Erika","email":"","middleInitial":"N.","affiliations":[{"id":36380,"text":"National Park Service Northeastern Coastal and Barrier Network","active":true,"usgs":false}],"preferred":false,"id":727986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schoolmaster, Donald 0000-0003-0910-4458 schoolmasterd@usgs.gov","orcid":"https://orcid.org/0000-0003-0910-4458","contributorId":156350,"corporation":false,"usgs":true,"family":"Schoolmaster","given":"Donald","email":"schoolmasterd@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":727987,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":727988,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Skidds, Dennis E.","contributorId":202237,"corporation":false,"usgs":false,"family":"Skidds","given":"Dennis","email":"","middleInitial":"E.","affiliations":[{"id":36381,"text":"National Park Service Northeast Coastal and Barrier Network","active":true,"usgs":false}],"preferred":false,"id":727989,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stevens, Sara","contributorId":202238,"corporation":false,"usgs":false,"family":"Stevens","given":"Sara","email":"","affiliations":[{"id":36381,"text":"National Park Service Northeast Coastal and Barrier Network","active":true,"usgs":false}],"preferred":false,"id":727990,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70195349,"text":"70195349 - 2018 - Post-breeding migration and connectivity of red knots in the Western Atlantic","interactions":[],"lastModifiedDate":"2018-02-09T11:55:43","indexId":"70195349","displayToPublicDate":"2018-02-09T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Post-breeding migration and connectivity of red knots in the Western Atlantic","docAbstract":"Red knots (Calidris canutus rufa) have 3 distinct nonbreeding regions: 1 in the southeastern United States and Caribbean, another on the northeast coast of Brazil in the Maranhão region, and a third along the Patagonian coasts of Chile and Argentina. Effective conservation and recovery of this threatened long-distance migrant will require knowledge of population structure, migration ecology, and abundance and distribution throughout the annual cycle. We conducted a stopover population and biogeographic assessment of knots at the Altamaha River Delta, Georgia, an important stopover area in the southeastern United States. We estimated stopover population size and stopover duration during post-breeding migration in 2011 at the Altamaha study area using mark-resight data, and we inferred nonbreeding regions for this stopover population using stable isotope ratios of carbon and nitrogen in feathers, and observations (sightings and captures) during boreal winter from across the hemisphere. With an integrated Bayesian analysis of all these data, we also estimated the number of birds in the southeastern United States and northern Brazil during boreal winter. For mark-resight analyses in Georgia, we made observations of marked individuals during 14 weeks from early August to early November 2011 and detected 814 individually marked birds. We used the Jolly-Seber mark-recapture model and estimated the southbound passage population at approximately 23,400 red knots. In ongoing studies elsewhere, isotope samples were collected from 175 (21%) of the 814 birds detected in our study, and ≥1 sighting or capture record during boreal winter was located in data repositories for 659 birds (81%). Isotopic signatures and boreal winter records indicate that the majority (82–96%) of the birds that stopped at the Altamaha Delta spend the boreal winter in the northern part of the nonbreeding range (southeast USA, Caribbean, and northern Brazil). Knots migrating to the southeastern United States, Caribbean, or Brazil remained on the Altamaha Delta for 42 days, whereas birds migrating to Tierra del Fuego remained only 21 days. Combining our estimate of the Altamaha stopover population size (23,400 birds) and the estimated proportion in the northern nonbreeding region (82–96%), we derived a minimum estimate of the number of knots in the southeastern United States, Caribbean, and northern South America during the boreal winter: approximately 20,800 knots, of which approximately 10,400 knots occupy the southeastern United States and 5,400 occupy Brazil. Our results provide additional evidence that coastal Georgia is an important migration area for red knots, and provide information about population structure and migratory connectivity that will be valuable for conservation planning.
","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21389","usgsCitation":"Lyons, J.E., Winn, B., Keyes, T., and Kalasz, K.S., 2018, Post-breeding migration and connectivity of red knots in the Western Atlantic: Journal of Wildlife Management, v. 82, p. 383-396, https://doi.org/10.1002/jwmg.21389.","productDescription":"14 p.","startPage":"383","endPage":"396","ipdsId":"IP-086607","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":351422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","county":"Gylnn County, McIntosh County","otherGeospatial":"Altamaha River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.50619506835938,\n 31.208103321325254\n ],\n [\n -81.16561889648438,\n 31.208103321325254\n ],\n [\n -81.16561889648438,\n 31.52470272697062\n ],\n [\n -81.50619506835938,\n 31.52470272697062\n ],\n [\n -81.50619506835938,\n 31.208103321325254\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"82","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-23","publicationStatus":"PW","scienceBaseUri":"5a7ec171e4b00f54eb25a747","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":727979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winn, Bradford","contributorId":202233,"corporation":false,"usgs":false,"family":"Winn","given":"Bradford","email":"","affiliations":[{"id":36377,"text":"Manomet","active":true,"usgs":false}],"preferred":false,"id":727980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keyes, Timothy","contributorId":202234,"corporation":false,"usgs":false,"family":"Keyes","given":"Timothy","email":"","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":727981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kalasz, Kevin S.","contributorId":202235,"corporation":false,"usgs":false,"family":"Kalasz","given":"Kevin","email":"","middleInitial":"S.","affiliations":[{"id":36379,"text":"Delaware Division of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":727982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}