Wetlands in the Prairie Pothole Region (PPR) of North America support macroinvertebrate communities that are integral to local food webs and important to breeding waterfowl. Macroinvertebrates in PPR wetlands are primarily generalists and well adapted to within and among year changes in water permanence and salinity. The Williston Basin, a major source of U.S. energy production, underlies the southwest portion of the PPR. Development of oil and gas results in the coproduction of large volumes of highly saline, sodium chloride dominated water (brine) and the introduction of brine can alter wetland salinity. To assess potential effects of brine contamination on macroinvertebrate communities, 155 PPR wetlands spanning a range of hydroperiods and salinities were sampled between 2014 and 2016. Brine contamination was documented in 34 wetlands with contaminated wetlands having significantly higher chloride concentrations, specific conductance and percent dominant taxa, and significantly lower taxonomic richness, Shannon diversity, and Pielou evenness scores compared to uncontaminated wetlands. Non-metric multidimensional scaling found significant correlations between several water quality parameters and macroinvertebrate communities. Chloride concentration and specific conductance, which can be elevated in naturally saline wetlands, but are also associated with brine contamination, had the strongest correlations. Five wetland groups were identified from cluster analysis with many of the highly contaminated wetlands located in a single cluster. Low or moderately contaminated wetlands were distributed among the remaining clusters and had macroinvertebrate communities similar to uncontaminated wetlands. While aggregate changes in macroinvertebrate community structure were observed with brine contamination, systematic changes were not evident, likely due to the strong and potentially confounding influence of hydroperiod and natural salinity. Therefore, despite the observed negative response of macroinvertebrate communities to brine contamination, macroinvertebrate community structure alone is likely not the most sensitive indicator of brine contamination in PPR wetlands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2018.04.088","usgsCitation":"Preston, T.M., Borgreen, M.J., and Ray, A.M., 2018, Effects of brine contamination from energy development on wetland macroinvertebrate community structure in the Prairie Pothole Region: Environmental Pollution, v. 239, p. 722-732, https://doi.org/10.1016/j.envpol.2018.04.088.","productDescription":"11 p.","startPage":"722","endPage":"732","ipdsId":"IP-093113","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":437922,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB8141","text":"USGS data release","linkHelpText":"Macroinvertebrate and water quality data from the Prairie Pothole Region of the Williston Basin (2014-2016)"},{"id":353964,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Williston Basin","volume":"239","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbde2","contributors":{"authors":[{"text":"Preston, Todd M. 0000-0002-8812-9233","orcid":"https://orcid.org/0000-0002-8812-9233","contributorId":204676,"corporation":false,"usgs":true,"family":"Preston","given":"Todd","email":"","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":734648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borgreen, Michael J. 0000-0002-5879-6414","orcid":"https://orcid.org/0000-0002-5879-6414","contributorId":204677,"corporation":false,"usgs":false,"family":"Borgreen","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":734649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":734650,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196815,"text":"70196815 - 2018 - Stream fish colonization but not persistence varies regionally across a large North American river basin","interactions":[],"lastModifiedDate":"2018-05-03T09:50:28","indexId":"70196815","displayToPublicDate":"2018-05-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Stream fish colonization but not persistence varies regionally across a large North American river basin","docAbstract":"Many species have distributions that span distinctly different physiographic regions, and effective conservation of such taxa will require a full accounting of all factors that potentially influence populations. Ecologists recognize effects of physiographic differences in topography, geology and climate on local habitat configurations, and thus the relevance of landscape heterogeneity to species distributions and abundances. However, research is lacking that examines how physiography affects the processes underlying metapopulation dynamics. We used data describing occupancy dynamics of stream fishes to evaluate evidence that physiography influences rates at which individual taxa persist in or colonize stream reaches under different flow conditions. Using periodic survey data from a stream fish assemblage in a large river basin that encompasses multiple physiographic regions, we fit multi-species dynamic occupancy models. Our modeling results suggested that stream fish colonization but not persistence was strongly governed by physiography, with estimated colonization rates considerably higher in Coastal Plain streams than in Piedmont and Blue Ridge systems. Like colonization, persistence was positively related to an index of stream flow magnitude, but the relationship between flow and persistence did not depend on physiography. Understanding the relative importance of colonization and persistence, and how one or both processes may change across the landscape, is critical information for the conservation of broadly distributed taxa, and conservation strategies explicitly accounting for spatial variation in these processes are likely to be more successful for such taxa.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.04.023","usgsCitation":"Wheeler, K., Wenger, S., Walsh, S.J., Martin, Z.P., Jelks, H.L., and Freeman, M., 2018, Stream fish colonization but not persistence varies regionally across a large North American river basin: Biological Conservation, v. 223, p. 1-10, https://doi.org/10.1016/j.biocon.2018.04.023.","productDescription":"10 p.","startPage":"1","endPage":"10","ipdsId":"IP-091967","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460780,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2018.04.023","text":"Publisher Index Page"},{"id":353928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia","otherGeospatial":"Apalachicola-Chattahoochee-Flint River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.792236328125,\n 30.65681556429287\n ],\n [\n -83.38623046875,\n 30.65681556429287\n ],\n [\n -83.38623046875,\n 34.939985151560435\n ],\n [\n -85.792236328125,\n 34.939985151560435\n ],\n [\n -85.792236328125,\n 30.65681556429287\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"223","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbde4","contributors":{"authors":[{"text":"Wheeler, Kit","contributorId":203872,"corporation":false,"usgs":false,"family":"Wheeler","given":"Kit","email":"","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":734573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":734574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walsh, Stephen J. 0000-0002-1009-8537 swalsh@usgs.gov","orcid":"https://orcid.org/0000-0002-1009-8537","contributorId":1456,"corporation":false,"usgs":true,"family":"Walsh","given":"Stephen","email":"swalsh@usgs.gov","middleInitial":"J.","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":734577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Zachary P. 0000-0001-5779-3548 zmartin@usgs.gov","orcid":"https://orcid.org/0000-0001-5779-3548","contributorId":204653,"corporation":false,"usgs":false,"family":"Martin","given":"Zachary","email":"zmartin@usgs.gov","middleInitial":"P.","affiliations":[{"id":36970,"text":"Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":734576,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jelks, Howard L. 0000-0002-0672-6297 hjelks@usgs.gov","orcid":"https://orcid.org/0000-0002-0672-6297","contributorId":168997,"corporation":false,"usgs":true,"family":"Jelks","given":"Howard","email":"hjelks@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":734575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734572,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196406,"text":"ds1083 - 2018 - Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California","interactions":[],"lastModifiedDate":"2018-05-04T10:15:17","indexId":"ds1083","displayToPublicDate":"2018-05-03T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1083","title":"Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California","docAbstract":"In situ soil moisture datasets are important inputs used to calibrate and validate watershed, regional, or statewide modeled and satellite-based soil moisture estimates. The soil moisture dataset presented in this report includes hourly time series of the following: soil temperature, volumetric water content, water potential, and total soil water content. Data were collected by the U.S. Geological Survey at five locations in California: three sites in the central Sierra Nevada and two sites in the northern Coast Ranges. This report provides a description of each of the study areas, procedures and equipment used, processing steps, and time series data from each site in the form of comma-separated values (.csv) tables.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1083","collaboration":"Prepared in cooperation with the California Department of Water Resources, National Park Service, and Pepperwood Preserve","usgsCitation":"Stern, M.A., Anderson, F.A., Flint, L.E., and Flint, A.L., 2018, Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California: U.S. Geological Survey Data Series 1083, 23 p., https://doi.org/10.3133/ds1083.","productDescription":"Report: viii, 23 p.; 5 Tables","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080152","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":353696,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1083/coverthb.jpg"},{"id":353697,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1083/ds1083_.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Data Series 1083"},{"id":353698,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/1083/ds1083_tables12-15_17.zip","text":"Tables 12, 13, 14, 15, and 17","size":"5.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"Data Series 1083 table files"}],"country":"United States","state":"California","otherGeospatial":"Central Sierra Nevada Range, Northern Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.83612060546874,\n 37.73379707124429\n ],\n [\n -119.20852661132812,\n 37.73379707124429\n ],\n [\n -119.20852661132812,\n 37.965854128749434\n ],\n [\n -119.83612060546874,\n 37.965854128749434\n ],\n [\n -119.83612060546874,\n 37.73379707124429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6963424682617,\n 38.56887107621966\n ],\n [\n -122.68930435180664,\n 38.56887107621966\n ],\n [\n -122.68930435180664,\n 38.57256189519067\n ],\n [\n -122.6963424682617,\n 38.57256189519067\n ],\n [\n -122.6963424682617,\n 38.56887107621966\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
Demographic assessments of nesting birds typically focus on failures due to nest predation or brood parasitism. Extreme weather events such as hailstorms, however, can also destroy eggs and injure or kill juvenile and adult birds at the nest. We documented the effects of a severe hailstorm on 3 species of sagebrush-associated songbirds: Sage Thrasher (Oreoscoptes montanus), Brewer's Sparrow (Spizella breweri), and Vesper Sparrow (Pooecetes gramineus), nesting at eight 24 ha study plots in central Wyoming, USA. Across all plots, 17% of 128 nests failed due to the hailstorm; however, all failed nests were located at a subset of study plots (n = 3) where the hailstorm was most intense, and 45% of all nests failures on those plots were due to hail. Mortality rates varied by species, nest architecture, and nest placement. Nests with more robust architecture and those sited more deeply under the shrub canopy were more likely to survive the hailstorm, suggesting that natural history traits may modulate mortality risk due to hailstorms. While sporadic in nature, hailstorms may represent a significant source of nest failure to songbirds in certain locations, especially with increasing storm frequency and severity forecasted in some regions with ongoing climate change.
","language":"English","publisher":"Wilson Ornithological Society","doi":"10.1676/17-025.1","usgsCitation":"Hightower, J.N., Carlisle, J.D., and Chalfoun, A.D., 2018, Nest mortality of sagebrush songbirds due to a severe hailstorm: Wilson Journal of Ornithology, v. 130, no. 2, p. 561-567, https://doi.org/10.1676/17-025.1.","productDescription":"7 p.","startPage":"561","endPage":"567","ipdsId":"IP-084991","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":353911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c3e4b0da30c1bfbdec","contributors":{"authors":[{"text":"Hightower, Jessica N.","contributorId":204645,"corporation":false,"usgs":false,"family":"Hightower","given":"Jessica","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":734554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Jason D.","contributorId":204646,"corporation":false,"usgs":false,"family":"Carlisle","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalfoun, Anna D. 0000-0002-0219-6006 achalfoun@usgs.gov","orcid":"https://orcid.org/0000-0002-0219-6006","contributorId":197589,"corporation":false,"usgs":true,"family":"Chalfoun","given":"Anna","email":"achalfoun@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196805,"text":"70196805 - 2018 - Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data","interactions":[],"lastModifiedDate":"2018-08-31T11:00:41","indexId":"70196805","displayToPublicDate":"2018-05-02T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data","docAbstract":"Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2017-0052","usgsCitation":"Li, Y., Wagner, T., Jiao, Y., Lorantas, R.M., and Murphy, C., 2018, Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data: Canadian Journal of Fisheries and Aquatic Sciences, v. 75, no. 9, p. 1436-1452, https://doi.org/10.1139/cjfas-2017-0052.","productDescription":"17 p.","startPage":"1436","endPage":"1452","ipdsId":"IP-084291","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468778,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/99273","text":"External Repository"},{"id":353912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Yan","contributorId":204633,"corporation":false,"usgs":false,"family":"Jiao","given":"Yan","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":734529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorantas, Robert M.","contributorId":204631,"corporation":false,"usgs":false,"family":"Lorantas","given":"Robert","email":"","middleInitial":"M.","affiliations":[{"id":36966,"text":"Pennsylvania Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":734527,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murphy, Cheryl","contributorId":204632,"corporation":false,"usgs":false,"family":"Murphy","given":"Cheryl","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":734528,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199368,"text":"70199368 - 2018 - Spatial distribution of estuarine diamond-backed terrapins (Malaclemys terrapin) and risk analysis from commercial blue crab (Callinectes sapidus) trapping at the Savannah Coastal Refuges Complex, USA","interactions":[],"lastModifiedDate":"2018-09-14T15:07:33","indexId":"70199368","displayToPublicDate":"2018-05-01T15:07:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2926,"text":"Ocean and Coastal Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatial distribution of estuarine diamond-backed terrapins (Malaclemys terrapin) and risk analysis from commercial blue crab (Callinectes sapidus) trapping at the Savannah Coastal Refuges Complex, USA","title":"Spatial distribution of estuarine diamond-backed terrapins (Malaclemys terrapin) and risk analysis from commercial blue crab (Callinectes sapidus) trapping at the Savannah Coastal Refuges Complex, USA","docAbstract":"The diamond-backed terrapin (Malaclemys terrapin) is a small estuarine turtle distributed along the Atlantic and Gulf Coasts of the USA. Terrapin populations are declining throughout their range and one of the main causes is mortality by drowning as bycatch in commercially-fished blue crab (Callinetes sapidus) traps (aka pots). We conducted head counts of terrapins and documented the distribution and number of crab pots on the Savannah Coastal Refuges Complex in southeast Georgia, USA. Using an index for representing relative degree of crabbing pressure, we conducted a spatial risk analysis for each of the four refuges surveyed. We fit a series of generalized linear mixed effect models to test hypotheses about the scale (creek scale vs. refuge/island scale) at which terrapin relative abundances respond to crab trapping. Several creeks were found to be at high risk of terrapin mortality from crab pots. Areas with low terrapin head counts may be a result of past crab pot mortality. The best model relating terrapin counts to crab trapping revealed a negative effect of crab pots calculated at the refuge/island scale and included a positive association between cloud cover and terrapin counts. The estimated effect of crab pot number at the refuge/island scale suggests that an increase in crab pot density of one pot per creek is associated with a 74.6% decline in terrapin head counts, underscoring the sensitivity of terrapin populations to crab pot mortality. Mitigation of this mortality factor via redesigned crab traps with bycatch reduction devices may be necessary to maintain healthy terrapin populations on the refuges.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2018.02.012","usgsCitation":"Lovich, J.E., Thomas, M., Ironside, K.E., Yackulic, C.B., and Puffer, S., 2018, Spatial distribution of estuarine diamond-backed terrapins (Malaclemys terrapin) and risk analysis from commercial blue crab (Callinectes sapidus) trapping at the Savannah Coastal Refuges Complex, USA: Ocean and Coastal Management, v. 157, p. 160-167, https://doi.org/10.1016/j.ocecoaman.2018.02.012.","productDescription":"8 p.","startPage":"160","endPage":"167","ipdsId":"IP-090417","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468780,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocecoaman.2018.02.012","text":"Publisher Index Page"},{"id":437925,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PN94W3","text":"USGS data release","linkHelpText":"Spatial distribution and risk analysis data for diamond-backed terrapins relative to crab trapping, Savannah Coastal Refuge Complex, USA"},{"id":357350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Blackbeard Island National Wildlife Refuge, Harris Neck National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.26106262207031,\n 31.435693747063894\n ],\n [\n -81.17523193359375,\n 31.435693747063894\n ],\n [\n -81.17523193359375,\n 31.53991946406062\n ],\n [\n -81.26106262207031,\n 31.53991946406062\n ],\n [\n -81.26106262207031,\n 31.435693747063894\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.29754066467285,\n 31.62144765808016\n ],\n [\n -81.24209403991699,\n 31.62144765808016\n ],\n [\n -81.24209403991699,\n 31.653527524300973\n ],\n [\n -81.29754066467285,\n 31.653527524300973\n ],\n [\n -81.29754066467285,\n 31.62144765808016\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"157","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff8e4b0fc368eb539b4","contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Meagan","contributorId":207526,"corporation":false,"usgs":false,"family":"Thomas","given":"Meagan","email":"","affiliations":[{"id":37553,"text":"Davidson College, Department of Biology, Davidson, NC 28035-7118, USA","active":true,"usgs":false}],"preferred":false,"id":745063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ironside, Kirsten E. 0000-0003-1166-3793 kironside@usgs.gov","orcid":"https://orcid.org/0000-0003-1166-3793","contributorId":3379,"corporation":false,"usgs":true,"family":"Ironside","given":"Kirsten","email":"kironside@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Puffer, Shellie R. 0000-0003-4957-0963","orcid":"https://orcid.org/0000-0003-4957-0963","contributorId":193099,"corporation":false,"usgs":true,"family":"Puffer","given":"Shellie R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":745065,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201610,"text":"70201610 - 2018 - Integrating forest inventory data and MODIS data to map species-level biomass in Chinese boreal forests","interactions":[],"lastModifiedDate":"2018-12-18T14:07:03","indexId":"70201610","displayToPublicDate":"2018-05-01T14:07:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1170,"text":"Canadian Journal of Forest Research","active":true,"publicationSubtype":{"id":10}},"title":"Integrating forest inventory data and MODIS data to map species-level biomass in Chinese boreal forests","docAbstract":"Timely and accurate knowledge of species-level biomass is essential for forest managers to sustain forest resources and respond to various forest disturbance regimes. In this study, maps of species-level biomass in Chinese boreal forests were generated by integrating Moderate Resolution Imaging Spectroradiometer (MODIS) images with forest inventory data using k nearest neighbor (kNN) methods and evaluated at different scales. The performance of 630 kNN models based on different distance metrics, k values, and temporal MODIS predictor variables were compared. Random Forest (RF) showed the best performance among the six distance metrics: RF, Euclidean distance, Mahalanobis distance, most similar neighbor in canonical correlation space, most similar neighbor computed using projection pursuit, and gradient nearest neighbor. No appreciable improvement was observed using multi-month MODIS data compared with using single-month MODIS data. At the pixel scale, species-level biomass for larch and white birch had relatively good accuracy (root mean square deviation < 62.1%), while the other species had poorer accuracy. The accuracy of most species except for willow and spruce was improved up to the ecoregion scale. The maps of species-level biomass captured the effects of disturbances including fire and harvest and can provide useful information for broad-scale forest monitoring over time.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfr-2017-0346","usgsCitation":"Zhang, Q., He, H.S., Liang, Y., Hawbaker, T., Henne, P., Liu, J., Huang, S., Wu, Z., and Huang, C., 2018, Integrating forest inventory data and MODIS data to map species-level biomass in Chinese boreal forests: Canadian Journal of Forest Research, v. 48, no. 5, p. 461-479, https://doi.org/10.1139/cjfr-2017-0346.","productDescription":"19 p.","startPage":"461","endPage":"479","ipdsId":"IP-085665","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":360498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 121,\n 50\n ],\n [\n 127.5,\n 50\n ],\n [\n 127.5,\n 53.5\n ],\n [\n 121,\n 53.5\n ],\n [\n 121,\n 50\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1a1533e4b0708288c23538","contributors":{"authors":[{"text":"Zhang, Qinglong","contributorId":211615,"corporation":false,"usgs":false,"family":"Zhang","given":"Qinglong","email":"","affiliations":[{"id":38276,"text":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Shenyang 110016, China","active":true,"usgs":false}],"preferred":false,"id":754516,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"He, Hong S.","contributorId":211612,"corporation":false,"usgs":true,"family":"He","given":"Hong","email":"","middleInitial":"S.","affiliations":[{"id":38275,"text":"Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; School of Natural Resources, University of Missouri, 203 ABNR Building, Columbia, MO, USA","active":true,"usgs":false}],"preferred":false,"id":754517,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liang, Yu","contributorId":211613,"corporation":false,"usgs":false,"family":"Liang","given":"Yu","email":"","affiliations":[{"id":38274,"text":"Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China","active":true,"usgs":false}],"preferred":false,"id":754518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":754626,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":754519,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":754520,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huang, Shengli","contributorId":192377,"corporation":false,"usgs":false,"family":"Huang","given":"Shengli","affiliations":[],"preferred":false,"id":754521,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wu, Zhiwei","contributorId":211614,"corporation":false,"usgs":false,"family":"Wu","given":"Zhiwei","email":"","affiliations":[{"id":38274,"text":"Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China","active":true,"usgs":false}],"preferred":false,"id":754522,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huang, Chao","contributorId":211611,"corporation":false,"usgs":false,"family":"Huang","given":"Chao","email":"","affiliations":[{"id":38274,"text":"Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China","active":true,"usgs":false}],"preferred":true,"id":754523,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198415,"text":"70198415 - 2018 - Process convolution approaches for modeling interacting trajectories","interactions":[],"lastModifiedDate":"2018-08-03T13:49:42","indexId":"70198415","displayToPublicDate":"2018-05-01T13:49:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1577,"text":"Environmetrics","active":true,"publicationSubtype":{"id":10}},"title":"Process convolution approaches for modeling interacting trajectories","docAbstract":"Gaussian processes are a fundamental statistical tool used in a wide range of applications. In the spatiotemporal setting, several families of covariance functions exist to accommodate a wide variety of dependence structures arising in different applications. These parametric families can be restrictive and are insufficient in some situations. In contrast, process convolutions represent a flexible, interpretable approach to defining the covariance of a Gaussian process and have modest requirements to ensure validity. We introduce a generalization of the process convolution approach that employs multiple convolutions sequentially to form a “process convolution chain”. In our proposed multistage framework, complex dependencies that arise from a combination of different interacting mechanisms are decomposed into a series of interpretable kernel smoothers. We demonstrate an application of process convolution chains to model killer whale movement, in which the paths taken by multiple individuals are not independent but reflect dynamic social interactions within the population. Our proposed model for dependent movement provides inference for the latent dynamic social structure in the study population. Additionally, by leveraging the positive dependence among individual paths, we achieve a reduction in uncertainty for the estimated locations of the killer whales, compared with a model that treats paths as independent.
","language":"English","publisher":"Wiley","doi":"10.1002/env.2487","usgsCitation":"Scharf, H.R., Hooten, M., Johnson, D.S., and Durban, J.W., 2018, Process convolution approaches for modeling interacting trajectories: Environmetrics, v. 29, no. 3, e2487; 18 p., https://doi.org/10.1002/env.2487.","productDescription":"e2487; 18 p.","ipdsId":"IP-083224","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468782,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/env.2487","text":"Publisher Index Page"},{"id":356148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-29","publicationStatus":"PW","scienceBaseUri":"5b6fc45ce4b0f5d57878ea5f","contributors":{"authors":[{"text":"Scharf, Henry R.","contributorId":206652,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","email":"","middleInitial":"R.","affiliations":[{"id":37371,"text":"Colorado State University, Department of Statistics","active":true,"usgs":false}],"preferred":false,"id":741368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":741367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Devin S.","contributorId":198622,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":741369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Durban, John W.","contributorId":206653,"corporation":false,"usgs":false,"family":"Durban","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37372,"text":"N OAA, National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":741370,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70198990,"text":"70198990 - 2018 - Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta","interactions":[],"lastModifiedDate":"2018-08-28T13:49:01","indexId":"70198990","displayToPublicDate":"2018-05-01T13:48:56","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta","docAbstract":"Measurements of naturally occurring, short-lived radioisotopes from sediment cores on the Mississippi subaqueous delta have been used to infer event bed characteristics such as depositional thicknesses and accumulation rates. Specifically, the presence of Beryllium-7 (7Be) indicates recent riverine-derived terrestrial sediment deposition; while Thorium-234 (234Th) provides evidence of recent suspension in marine waters. Sediment transport models typically represent coastal flood and storm deposition via estimated grain size patterns and deposit thicknesses, however, and do not directly calculate radioisotope activities and profiles, which leads to a disconnect between the numerical model and field observations. Here, observed radioisotopic profiles from the Mississippi subaqueous delta cores were directly related to a numerical model that represented resuspension and deposition using a new approach to account for the behavior of short-lived radioisotopes. Appropriate selection of parameters such as the biodiffusion coefficient, sediment accumulation rate, and radioisotopic source terms enabled a good match between the modeled and observed cores. Comparisons of modelled profiles with geochronological analytical models that estimate accumulation rate and flood layer thickness revealed potential avenues for refining these tools, and highlight the importance of constraining the biodiffusion coefficient.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI85-092.1","usgsCitation":"Birchler, J.J., Harris, C.K., Kniskern, T.A., and Sherwood, C.R., 2018, Numerical model of geochronological tracers for deposition and reworking applied to the Mississippi subaqueous delta: Journal of Coastal Research, v. Special Issue 85, p. 456-460, https://doi.org/10.2112/SI85-092.1.","productDescription":"5 p.","startPage":"456","endPage":"460","ipdsId":"IP-092729","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2112/si85-092.1","text":"Publisher Index Page"},{"id":356848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico, Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5,\n 28.5\n ],\n [\n -88,\n 28.5\n ],\n [\n -88,\n 30.5\n ],\n [\n -90.5,\n 30.5\n ],\n [\n -90.5,\n 28.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue 85","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2cfe4b0702d0e842ff1","contributors":{"authors":[{"text":"Birchler, Justin J. 0000-0002-0379-2192 jbirchler@usgs.gov","orcid":"https://orcid.org/0000-0002-0379-2192","contributorId":169117,"corporation":false,"usgs":true,"family":"Birchler","given":"Justin","email":"jbirchler@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":743670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Courtney K.","contributorId":19620,"corporation":false,"usgs":false,"family":"Harris","given":"Courtney","email":"","middleInitial":"K.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":743671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kniskern, Tara A.","contributorId":207384,"corporation":false,"usgs":false,"family":"Kniskern","given":"Tara","email":"","middleInitial":"A.","affiliations":[{"id":37527,"text":"Virginia Institute of Marine Sciences, College of William & Mary","active":true,"usgs":false}],"preferred":false,"id":743672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":743673,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202358,"text":"70202358 - 2018 - Operational nowcasting of electron flux levels in the outer zone of Earth's radiation belt","interactions":[],"lastModifiedDate":"2019-02-25T13:38:25","indexId":"70202358","displayToPublicDate":"2018-05-01T13:38:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Operational nowcasting of electron flux levels in the outer zone of Earth's radiation belt","docAbstract":"We describe a lightweight, accurate nowcasting model for electron flux levels measured by the Van Allen probes. Largely motivated by Rigler et al. (2004, https://doi.org/10.1029/2003SW000036), we turn to a time‐varying linear filter of previous flux levels and Kp. We train and test this model on data gathered from the 2.10 MeV channel of the Relativistic Electron‐Proton Telescope sensor onboard the Van Allen probes. Dynamic linear models are a specific case of state space models and can be made flexible enough to emulate the nonlinear behavior of particle fluxes within the radiation belts. Real‐time estimation of the parameters of the model is done using a Kalman filter, where the state of the model is exactly the parameters. Nowcast performance is assessed against several baseline interpolation schemes. Our model demonstrates significant improvements in performance over persistence nowcasting. In particular, during times of high geomagnetic activity, our model is able to attain performance substantially better than a persistence model. In addition, residual analysis is conducted in order to assess model fit and to suggest future improvements to the model.
","language":"English","publisher":"AGU","doi":"10.1029/2017SW001788","usgsCitation":"Coleman, T., McCollough, J.P., Young, S.L., and Rigler, E.J., 2018, Operational nowcasting of electron flux levels in the outer zone of Earth's radiation belt: Space Weather, v. 16, no. 5, p. 501-518, https://doi.org/10.1029/2017SW001788.","productDescription":"18 p.","startPage":"501","endPage":"518","ipdsId":"IP-096545","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":361501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Coleman, Tim","contributorId":213545,"corporation":false,"usgs":false,"family":"Coleman","given":"Tim","email":"","affiliations":[],"preferred":false,"id":757979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCollough, James P.","contributorId":204030,"corporation":false,"usgs":false,"family":"McCollough","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":757980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, Shawn L.","contributorId":204031,"corporation":false,"usgs":false,"family":"Young","given":"Shawn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":757981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":757982,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197548,"text":"70197548 - 2018 - Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS","interactions":[],"lastModifiedDate":"2018-09-26T12:40:44","indexId":"70197548","displayToPublicDate":"2018-05-01T12:40:37","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS","docAbstract":"On the open coast, flooding is largely driven by tides, storm surge, waves, and in areas near coastal inlets, the magnitude and co-occurrence of high fluvial discharges. Statistical methods are typically used to estimate the individual probability of coastal storm and fluvial discharge occurrences for use in sophisticated flood hazard models. A challenge arises when considering possible future climate changes and the relation between the intensity of extreme coastal water levels and high fluvial discharges.
In this study, the Coastal Storm Modeling System (CoSMoS) is used to dynamically downscale global climate projections to local-scale storm-driven coastal water levels, including associated fluvial discharges. An efficient approach to derive 21st century projected fluvial discharges for rivers within San Francisco Bay was developed, leveraging a readily-available time-series of projected (2010 – 2100) discharge rates of the predominant river system (the “Delta”). Delta projections were used to estimate flow rates of 8 Bay rivers for the IPCC's CMIP5 RCP4.5 climate scenario. Relationships describing discharge rates, normalized by respective watershed areas, were developed and applied to projected data to generate 21st century fluvial discharge time-series for each river. Results indicate decreasing discharge rates throughout the 21st century with the exception of extreme flows.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI85-159.1","usgsCitation":"Erikson, L.H., O'Neill, A., and Barnard, P., 2018, Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS: Journal of Coastal Research, v. Special Issue No. 85, p. 791-795, https://doi.org/10.2112/SI85-159.1.","productDescription":"5 p.","startPage":"791","endPage":"795","ipdsId":"IP-092829","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":357779,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.387451171875,\n 36.94989178681327\n ],\n [\n -121.201171875,\n 36.94989178681327\n ],\n [\n -121.201171875,\n 38.565347844885466\n ],\n [\n -123.387451171875,\n 38.565347844885466\n ],\n [\n -123.387451171875,\n 36.94989178681327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue No. 85","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02ff9e4b0fc368eb539b6","contributors":{"authors":[{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O'Neill, Andrea C. 0000-0003-1656-4372 aoneill@usgs.gov","orcid":"https://orcid.org/0000-0003-1656-4372","contributorId":5351,"corporation":false,"usgs":true,"family":"O'Neill","given":"Andrea C.","email":"aoneill@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":737617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":746347,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201554,"text":"70201554 - 2018 - Atmospheric and surface climate associated with 1986–2013 wildfires in North America","interactions":[],"lastModifiedDate":"2018-12-18T12:39:58","indexId":"70201554","displayToPublicDate":"2018-05-01T12:40:05","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric and surface climate associated with 1986–2013 wildfires in North America","docAbstract":"We analyze climate simulations conducted with the RegCM3 regional climate model on 50‐ and 15‐km model grids to diagnose the dependence of wildfire incidence and area burned variations on monthly climate long‐term means and anomalies over North America for the period 1986–2013. We created a new wildfire database by merging the Fire Program Analysis Fire‐Occurrence Database, the National Interagency Fire Center Fire History Data, and the Canadian National Fire Database. The database includes 2,083,865 daily fire starts that burned a total of 1.25 × 108 ha in North America. We derive long‐term climatologies, standardized gamma indices, and composite climate anomalies of atmospheric circulation (500‐hPa height and wind) and various surface fields (e.g., solar radiation, soil moisture, vapor pressure deficit, and latent and sensible heat fluxes) to illustrate the climatology of burned area. The immediate and lagged monthly atmospheric circulation and surface climate anomalies differentiate high‐ and low‐fire years and the role of El Niño–Southern Oscillation in wildfire occurrence. Our approach demonstrates the association of the seasonal cycles of wildfire and climate and the strong role of climatic variability in modulating the seasonal cycle as a control of wildfire on monthly time scales.
","language":"English","publisher":"AGU","doi":"10.1029/2017JG004195","usgsCitation":"Hostetler, S.W., Bartlein, P.J., and Alder, J.R., 2018, Atmospheric and surface climate associated with 1986–2013 wildfires in North America: Journal of Geophysical Research: Biogeosciences, v. 123, no. 5, p. 1588-1609, https://doi.org/10.1029/2017JG004195.","productDescription":"22 p.","startPage":"1588","endPage":"1609","ipdsId":"IP-090909","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jg004195","text":"Publisher Index Page"},{"id":360457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-16","publicationStatus":"PW","scienceBaseUri":"5c1a1534e4b0708288c2353e","contributors":{"authors":[{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":754432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartlein, Patrick J. 0000-0001-7657-5685","orcid":"https://orcid.org/0000-0001-7657-5685","contributorId":211587,"corporation":false,"usgs":false,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":33397,"text":"U of Oregon","active":true,"usgs":false}],"preferred":false,"id":754433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":754434,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198040,"text":"70198040 - 2018 - Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions","interactions":[],"lastModifiedDate":"2018-08-07T12:07:51","indexId":"70198040","displayToPublicDate":"2018-05-01T12:07:45","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions","docAbstract":"Enhanced reservoir connectivity generally requires maximizing the intersection between hydraulic fracture (HF) and preexisting underground natural fractures (NF), while having the hydraulic fracture cross the natural fractures (and not arrest). We have studied the interaction between a hydraulic fracture and a polished saw-cut fault. The experiments include a hydraulic fracture initiating from a pressurized axial borehole (using water) that approaches a dry fault that is inclined at an angle θ with respect to the borehole axis. The experiments are conducted on Poly(methyl) Meta Acrylate (PMMA) and Solnhofen limestone, a finely grained (<5 μm grain), low permeability (<10 nD) carbonate. The confining pressure in all experiments is 5 MPa, while the differential stress (1-80 MPa) and approach angle, θ (30, 45, 60, 90°) are experimental variables. During the hydraulic fracture, acoustic emissions (AE), slip velocity, slip magnitude, stress drop and pore pressure are recorded at a 5 MHz sampling rate. A Doppler laser vibrometer measures piston velocity outside the pressure vessel to infer fault slip duration and a strain gauge adjacent to the saw-cut provides a near-field measure of axial stress.
For PMMA, the coefficient of friction was 0.30 and sliding was unstable (stick-slip). The approaching HF in PMMA created a tensile fracture detected by AE transducers ~100 μs before the significant stick-slip event (45% stress drop and slip velocity of ~60 mm/s) and was arrested by the fault at all fault orientations and differential stresses, even at 90° fault orientation and 80 MPa differential stress. For Solnhofen limestone, we observed stable sliding at a coefficient of friction of 0.12. In contrast to PMMA, the HF in Solnhofen consistently crossed to the other side of the fault. When the HF crossed the fault, it produced a small stress drop (<10%) and slip velocity of only 0.5 mm/s. Theoretical models by Blanton (1986) and Renshaw and Pollard (1995) predict that HF will be arrested for Solnhofen limestone and cross PMMA 90° fault at 80 MPa differential stress. Although the exact cause for the discrepancy between experiments and the theory is not known, one feature present in the experiments but not considered in the models, is the diffusion of fluid driven by the fault slip. Thus, the formation of a \"fluid-filled patch\" on the fault surface as it is intersected by the HF may substantially impact the crossing/arrest behavior. The approach angle and differential stress also influence the HF initiation azimuth and breakdown pressure. In most cases, the HF initiation azimuth was normal to the fault strike. These observations suggest that the presence of natural fractures could result in rotation of hydraulic fractures to be more normal to their strike and a subsequent change in the downhole pressure recordings. The latter could be used as a diagnostic tool for predicting this interaction.
","largerWorkTitle":"SPE Hydraulic Fracturing Technology Conference and Exhibition","conferenceTitle":"SPE Hydraulic Fracturing Technology Conference and Exhibition","conferenceDate":"January 23-25, 2018","conferenceLocation":"The Woodlands, TX","language":"English","publisher":"Society of Petroleum Engineers","doi":"10.2118/189901-MS","usgsCitation":"Mighani, S., Lockner, D.A., Kilgore, B.D., Sheibani, F., and Evans, B., 2018, Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions, in SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, TX, January 23-25, 2018, 26 p., https://doi.org/10.2118/189901-MS.","productDescription":"26 p.","ipdsId":"IP-095560","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":437926,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DQOE6D","text":"USGS data release","linkHelpText":"Data Release for "Interaction between hydraulic fracture and a preexisting fracture under triaxial stress conditions""},{"id":356278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-23","publicationStatus":"PW","scienceBaseUri":"5b6fc45ce4b0f5d57878ea61","contributors":{"authors":[{"text":"Mighani, Saied","contributorId":206821,"corporation":false,"usgs":false,"family":"Mighani","given":"Saied","email":"","affiliations":[],"preferred":false,"id":741866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833 dlockner@usgs.gov","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":567,"corporation":false,"usgs":true,"family":"Lockner","given":"David","email":"dlockner@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":741867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kilgore, Brian D. 0000-0003-0530-7979 bkilgore@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7979","contributorId":3887,"corporation":false,"usgs":true,"family":"Kilgore","given":"Brian","email":"bkilgore@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":741868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sheibani, Farrokh 0000-0002-5105-4792","orcid":"https://orcid.org/0000-0002-5105-4792","contributorId":205992,"corporation":false,"usgs":false,"family":"Sheibani","given":"Farrokh","email":"","affiliations":[{"id":37205,"text":"Post-Doctoral researcher at M.I.T. Cambridge MA","active":true,"usgs":false}],"preferred":false,"id":741869,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Evans, Brian 0000-0003-0324-0969","orcid":"https://orcid.org/0000-0003-0324-0969","contributorId":205993,"corporation":false,"usgs":false,"family":"Evans","given":"Brian","email":"","affiliations":[{"id":37206,"text":"Professor, Massachusetts Institute of Technology: Cambridge, MA","active":true,"usgs":false}],"preferred":false,"id":741870,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199214,"text":"70199214 - 2018 - The influence of sea level rise on the regional interdependence of coastal infrastructure","interactions":[],"lastModifiedDate":"2018-09-11T10:18:00","indexId":"70199214","displayToPublicDate":"2018-05-01T10:17:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"The influence of sea level rise on the regional interdependence of coastal infrastructure","docAbstract":"Sea level rise (SLR) is placing both immediate and long‐term pressures on coastal communities to take protective actions. Projects in the United States, and in many locations throughout the world, generally involve local jurisdictions raising the elevation of shoreline protection elements, with limited or no analysis of the feedback between shoreline management decisions and the impacts to water levels regionally. Our study examines the impact of local shoreline development on regional flood risk and considers SLR scenarios up to 1.5 m using a large‐scale numerical model, as an example, for San Francisco Bay. Here we show that measures to prevent flooding along an embayment shoreline in one location or subregion may increase inundation elsewhere in the system. The network of interactions occurs not only within subbasins of the Bay but also across the greater geographic extent from one end of the Bay to the other, and local jurisdiction may have either reciprocal relationships with or asymmetric impacts on one other. Importantly, the nature of the interaction network is seen to evolve with SLR: interactions are purely subregional at current sea level but with higher sea level (e.g., 1 m of SLR), not only do the subregional interdependencies strengthen but also regional interdependences emerge.
","language":"English","publisher":"AGU","doi":"10.1002/2017EF000742","usgsCitation":"Wang, R., Stacey, M., Herdman, L.M., Barnard, P., and Erikson, L.H., 2018, The influence of sea level rise on the regional interdependence of coastal infrastructure: Earth's Future, v. 6, no. 5, p. 677-688, https://doi.org/10.1002/2017EF000742.","productDescription":"12 p.","startPage":"677","endPage":"688","ipdsId":"IP-086793","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017ef000742","text":"Publisher Index Page"},{"id":357219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.67333984374999,\n 37.391981943533544\n ],\n [\n -121.75872802734375,\n 37.391981943533544\n ],\n [\n -121.75872802734375,\n 38.26406296833961\n ],\n [\n -122.67333984374999,\n 38.26406296833961\n ],\n [\n -122.67333984374999,\n 37.391981943533544\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-02","publicationStatus":"PW","scienceBaseUri":"5b98a2cfe4b0702d0e842ff3","contributors":{"authors":[{"text":"Wang, Ruo-Quian","contributorId":206190,"corporation":false,"usgs":false,"family":"Wang","given":"Ruo-Quian","email":"","affiliations":[{"id":37278,"text":"University of Dundee","active":true,"usgs":false}],"preferred":false,"id":744708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":744709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744710,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":744711,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227668,"text":"70227668 - 2018 - Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho","interactions":[],"lastModifiedDate":"2022-01-26T15:33:15.901065","indexId":"70227668","displayToPublicDate":"2018-05-01T09:31:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho","docAbstract":"Resource managers have been attempting to recover the kokanee (Oncorhynchus nerka) population in Lake Pend Oreille, Idaho for more than three decades using an annual stocking program and an experimental water-level management strategy. This study evaluated the effect of both management actions on kokanee recruitment. A bootstrap-based generalized Ricker model was used to test if wild kokanee recruitment was significantly influenced by water-level management, while accounting for error due to sampling variability and differential survival of wild- and hatchery-origin fish within age-classes. Wild kokanee exhibited a compensatory stock-recruitment relationship, whereas hatchery recruitment was positively and linearly related to stocking. The model did not identify a significant relationship between water level and wild kokanee recruitment. Density dependence and variable stocking appeared to explain the synchronized and cyclic recruitment of wild and hatchery fry.
","language":"English","publisher":"Washington State University Press","doi":"10.3955/046.092.0206","usgsCitation":"Whitlock, S., Quist, M.C., and Dux, A.M., 2018, Effects of water-level management and hatchery supplementation on kokanee recruitment in Lake Pend Oreille, Idaho, v. 92, no. 2, p. 136-148, https://doi.org/10.3955/046.092.0206.","productDescription":"13 p.","startPage":"136","endPage":"148","ipdsId":"IP-053519","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":394866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Pend Oreille","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.69677734375,\n 47.93934692855592\n ],\n [\n -116.19415283203125,\n 47.93934692855592\n ],\n [\n -116.19415283203125,\n 48.32612605157941\n ],\n [\n -116.69677734375,\n 48.32612605157941\n ],\n [\n -116.69677734375,\n 47.93934692855592\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whitlock, Steven L.","contributorId":267708,"corporation":false,"usgs":false,"family":"Whitlock","given":"Steven L.","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":831780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dux, Andrew M.","contributorId":212798,"corporation":false,"usgs":false,"family":"Dux","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":831781,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236152,"text":"70236152 - 2018 - Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","interactions":[],"lastModifiedDate":"2022-08-30T14:26:41.124038","indexId":"70236152","displayToPublicDate":"2018-05-01T09:19:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States","docAbstract":"Winter snowfall and accumulation is an important component of the surface water supply in the western United States. In these areas, increasing winter temperatures T associated with global warming can influence the amount of winter precipitation P that falls as snow S. In this study we examine long-term trends in the fraction of winter P that falls as S (Sfrac) for 175 hydrologic units (HUs) in snow-covered areas of the western United States for the period 1951–2014. Because S is a substantial contributor to runoff R across most of the western United States, we also examine long-term trends in water-year runoff efficiency [computed as water-year R/water-year P (Reff)] for the same 175 HUs. In that most S records are short in length, we use model-simulated S and R from a monthly water balance model. Results for Sfrac indicate long-term negative trends for most of the 175 HUs, with negative trends for 139 (~79%) of the HUs being statistically significant at a 95% confidence level (p = 0.05). Additionally, results indicate that the long-term negative trends in Sfrac have been largely driven by increases in T. In contrast, time series of Reff for the 175 HUs indicate a mix of positive and negative long-term trends, with few trends being statistically significant (at p = 0.05). Although there has been a notable shift in the timing of R to earlier in the year for most HUs, there have not been substantial decreases in water-year R for the 175 HUs.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-17-0227.1","usgsCitation":"McCabe, G.J., Wolock, D.M., and Valentin, M., 2018, Warming is driving decreases in snow fractions while runoff efficiency remains mostly unchanged in snow-covered areas of the western United States: Journal of Hydrometeorology, v. 19, p. 803-814, https://doi.org/10.1175/JHM-D-17-0227.1.","productDescription":"12 p.","startPage":"803","endPage":"814","ipdsId":"IP-080058","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":468787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-17-0227.1","text":"Publisher Index Page"},{"id":405909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.7734375,\n 32.39851580247402\n ],\n [\n -107.70996093749999,\n 31.840232667909365\n ],\n [\n -106.69921875,\n 33.394759218577995\n ],\n [\n -106.4794921875,\n 35.209721645221386\n ],\n [\n -104.67773437499999,\n 35.92464453144099\n ],\n [\n -104.7216796875,\n 37.64903402157866\n ],\n [\n -104.5458984375,\n 38.89103282648846\n ],\n [\n -104.94140625,\n 39.80853604144591\n ],\n [\n -104.80957031249999,\n 40.48038142908172\n ],\n [\n -105.64453124999999,\n 41.343824581185686\n ],\n [\n -104.94140625,\n 42.19596877629178\n ],\n [\n -106.787109375,\n 43.35713822211053\n ],\n [\n -106.6552734375,\n 44.308126684886126\n ],\n [\n -107.9296875,\n 45.36758436884978\n ],\n [\n -110.25878906249999,\n 45.85941212790755\n ],\n [\n -111.09374999999999,\n 46.76996843356982\n ],\n [\n -112.67578124999999,\n 47.66538735632654\n ],\n [\n -113.51074218749999,\n 49.06666839558117\n ],\n [\n -123.53027343749999,\n 49.06666839558117\n ],\n [\n -123.26660156249999,\n 48.37084770238366\n ],\n [\n -125.3759765625,\n 48.60385760823255\n ],\n [\n -124.4091796875,\n 45.336701909968134\n ],\n [\n -124.93652343749999,\n 43.004647127794435\n ],\n [\n -124.76074218749999,\n 40.38002840251183\n ],\n [\n -124.18945312500001,\n 38.75408327579141\n ],\n [\n -122.3876953125,\n 36.35052700542763\n ],\n [\n -120.9375,\n 34.19817309627726\n ],\n [\n -117.7734375,\n 32.39851580247402\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-05-17","publicationStatus":"PW","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":200854,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory","email":"gmccabe@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"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":850262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":850263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Valentin, Melissa","contributorId":202218,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":850264,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70200606,"text":"70200606 - 2018 - Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU","interactions":[],"lastModifiedDate":"2018-11-21T09:14:01","indexId":"70200606","displayToPublicDate":"2018-05-01T09:13:26","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU","docAbstract":"The portion of the Snake River fall Chinook Salmon Oncorhynchus tshawytscha ESU that spawns upstream of Lower Granite Dam transitioned from low to high abundance during 1992–2017 in association with U.S. Endangered Species Act recovery efforts and other federally mandated actions. This annual report focuses on (1) numeric and habitat use responses by natural- and hatchery-origin spawners, (2) phenotypic and numeric responses by natural-origin juveniles, (3) USGS use of a small unmanned aerial system (sUAS) to search for fall Chinook salmon redds and carcasses, and (4) the detection of 8-mm PIT tags at Lower Granite Dam. Spawners have located and used most of the available spawning habitat and that habitat is gradually approaching redd capacity. Timing of spawning and fry emergence has been relatively stable; whereas the timing of parr dispersal from riverine rearing habitat into Lower Granite Reservoir has become earlier as apparent abundance of juveniles has increased. Growth rate (g/d) and dispersal size of parr also declined as apparent abundance of juveniles increased. Passage timing of smolts from the two Snake River reaches has become earlier and downstream movement rate faster as estimated abundance of fall Chinook Salmon smolts in Lower Granite Reservoir has increased. These findings coupled with stock-recruitment analyses presented in this report provide evidence for density-dependence in the Snake River reaches and in Lower Granite Reservoir that was influenced by the expansion of the recovery program. The long-term goal is to use the information covered here in a comprehensive modeling effort to conduct action effectiveness and uncertainty research and to inform Fish Population, Hydrosystem, Harvest, Hatchery, and Predation and Invasive Species Management RM&E.\n\nIn 2017, the USGS searched 15 shallow water spawning sites in conjunction with the Idaho Power Company (IPC). Redd counts agreed with those of IPC for a little more than half the sites suggesting that we need more training in redd counting. We recovered 67 carcasses, and tissue samples are currently being analyzed for parentage to ultimately determine the percentage of hatchery-origin spawners on the spawning grounds. Redd fading was examined to determine the frequency at which aerial surveys should be conducted. Most redds surveyed through time were visible for at least 4 weeks after the redd was initially constructed. Redd fading was variable amongst sites and depended on location.\n\nIn 2017, we conducted a second year of evaluating detection efficiency of 8-mm PIT tags in the Lower Granite Dam juvenile fish collection system. Groups of 75–78 fish were tagged\nwith 8-mm Biomark, 8-mm Oregon RFID, 9-mm Biomark, and 12-mm Biomark PIT tags and released into the bypass upstream of the upwell. From 97.4 to 100% (depending on tag type) of tagged fish were detected on at least one antenna in the Lower Granite Dam bypass system. Mean detection efficiency within the predominant passage route (i.e., diversion river exit) exceeded 0.98 for all tag types in both years. These results suggest that fish tagged in the field with 8-mm PIT tags should be detected at rates similar to larger tags at main-stem hydroelectric dams.","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Tiffan, K., Plumb, J.M., Perry, R.W., Erhardt, J., Hemingway, R.J., Bickford, B., Rhodes, T., Connor, W., and Mullins, F.L., 2018, Research, monitoring, and evaluation of emerging issues and measures to recover the Snake River fall Chinook salmon ESU, 67 p.","productDescription":"67 p.","ipdsId":"IP-097295","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359627,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":358776,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P160478/75986-1.pdf"}],"country":"United States","otherGeospatial":"Snake River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.35546875000001,\n 44.715513732021336\n ],\n [\n -114.6478271484375,\n 44.715513732021336\n ],\n [\n -114.6478271484375,\n 47.10378387099161\n ],\n [\n -119.35546875000001,\n 47.10378387099161\n ],\n [\n -119.35546875000001,\n 44.715513732021336\n ]\n ]\n ]\n }\n }\n ]\n}","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bf67cf5e4b045bfcae2cffe","contributors":{"authors":[{"text":"Tiffan, Kenneth 0000-0002-5831-2846 ktiffan@usgs.gov","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":210058,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","email":"ktiffan@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":751889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":751890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erhardt, John 0000-0002-5170-285X jerhardt@usgs.gov","orcid":"https://orcid.org/0000-0002-5170-285X","contributorId":210059,"corporation":false,"usgs":true,"family":"Erhardt","given":"John","email":"jerhardt@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749720,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hemingway, Rulon J. 0000-0001-8143-0325 rhemingway@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-0325","contributorId":194697,"corporation":false,"usgs":true,"family":"Hemingway","given":"Rulon","email":"rhemingway@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":751891,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bickford, Brad 0000-0003-3756-6588 bbickford@usgs.gov","orcid":"https://orcid.org/0000-0003-3756-6588","contributorId":210056,"corporation":false,"usgs":true,"family":"Bickford","given":"Brad","email":"bbickford@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749717,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rhodes, Tobyn N. 0000-0002-4023-4827","orcid":"https://orcid.org/0000-0002-4023-4827","contributorId":210057,"corporation":false,"usgs":true,"family":"Rhodes","given":"Tobyn N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":749718,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Connor, William P.","contributorId":115438,"corporation":false,"usgs":true,"family":"Connor","given":"William P.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":751892,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mullins, Frank L.","contributorId":146343,"corporation":false,"usgs":false,"family":"Mullins","given":"Frank","email":"","middleInitial":"L.","affiliations":[{"id":16677,"text":"U.S. Fish and Wildlife Service, Idaho Fishery Resource Office, 276 Dworshak Complex Drive, Orofino, ID 83544","active":true,"usgs":false}],"preferred":false,"id":751893,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70196803,"text":"70196803 - 2018 - Co‐occurrence dynamics of endangered Lower Keys marsh rabbits and free‐ranging domestic cats: Prey responses to an exotic predator removal program","interactions":[],"lastModifiedDate":"2018-05-02T11:27:51","indexId":"70196803","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Co‐occurrence dynamics of endangered Lower Keys marsh rabbits and free‐ranging domestic cats: Prey responses to an exotic predator removal program","docAbstract":"
The Lower Keys marsh rabbit (Sylvilagus palustris hefneri) is one of many endangered endemic species of the Florida Keys. The main threats are habitat loss and fragmentation from sea‐level rise, development, and habitat succession. Exotic predators such as free‐ranging domestic cats (Felis catus) pose an additional threat to these endangered small mammals. Management strategies have focused on habitat restoration and exotic predator control. However, the effectiveness of predator removal and the effects of anthropogenic habitat modifications and restoration have not been evaluated. Between 2013 and 2015, we used camera traps to survey marsh rabbits and free‐ranging cats at 84 sites in the National Key Deer Refuge, Big Pine Key, Florida, USA. We used dynamic occupancy models to determine factors associated with marsh rabbit occurrence, colonization, extinction, and the co‐occurrence of marsh rabbits and cats during a period of predator removal. Rabbit occurrence was positively related to freshwater habitat and patch size, but was negatively related to the number of individual cats detected at each site. Furthermore, marsh rabbit colonization was negatively associated with relative increases in the number of individual cats at each site between survey years. Cat occurrence was negatively associated with increasing distance from human developments. The probability of cat site extinction was positively related to a 2‐year trapping effort, indicating that predator removal reduced the cat population. Dynamic co‐occurrence models suggested that cats and marsh rabbits co‐occur less frequently than expected under random conditions, whereas co‐detections were site and survey‐specific. Rabbit site extinction and colonization were not strongly conditional on cat presence, but corresponded with a negative association. Our results suggest that while rabbits can colonize and persist at sites where cats occur, it is the number of individual cats at a site that more strongly influences rabbit occupancy and colonization. These findings indicate that continued predator management would likely benefit endangered small mammals as they recolonize restored habitats.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.3954","usgsCitation":"Cove, M., Gardner, B., Simons, T.R., and O’Connell, A.F., 2018, Co‐occurrence dynamics of endangered Lower Keys marsh rabbits and free‐ranging domestic cats: Prey responses to an exotic predator removal program: Ecology and Evolution, v. 8, no. 8, p. 4042-4052, https://doi.org/10.1002/ece3.3954.","productDescription":"11 p.","startPage":"4042","endPage":"4052","ipdsId":"IP-083926","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.3954","text":"Publisher Index Page"},{"id":353915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"National Key Deer Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.40869140625,\n 24.662306385334862\n ],\n [\n -81.33522033691405,\n 24.662306385334862\n ],\n [\n -81.33522033691405,\n 24.747454885176023\n ],\n [\n -81.40869140625,\n 24.747454885176023\n ],\n [\n -81.40869140625,\n 24.662306385334862\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-26","publicationStatus":"PW","scienceBaseUri":"5afee6c5e4b0da30c1bfbe06","contributors":{"authors":[{"text":"Cove, Michael V.","contributorId":176507,"corporation":false,"usgs":false,"family":"Cove","given":"Michael V.","affiliations":[],"preferred":false,"id":734564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":734565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":734521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734566,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196772,"text":"70196772 - 2018 - Quantifying salinity and season effects on eastern oyster clearance and oxygen consumption rates","interactions":[],"lastModifiedDate":"2018-05-01T11:37:43","indexId":"70196772","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying salinity and season effects on eastern oyster clearance and oxygen consumption rates","docAbstract":"There are few data on Crassostrea virginica physiological rates across the range of salinities and temperatures to which they are regularly exposed, and this limits the applicability of growth and production models using these data. The objectives of this study were to quantify, in winter (17 °C) and summer (27 °C), the clearance and oxygen consumption rates of C. virginica from Louisiana across a range of salinities typical of the region (3, 6, 9, 15 and 25). Salinity and season (temperature and reproduction) affected C. virginica physiology differently; salinity impacted clearance rates with reduced feeding rates at low salinities, while season had a strong effect on respiration rates. Highest clearance rates were found at salinities of 9–25, with reductions ranging from 50 to 80 and 90 to 95% at salinities of 6 and 3, respectively. Oxygen consumption rates in summer were four times higher than in winter. Oxygen consumption rates were within a narrow range and similar among salinities in winter, but varied greatly among individuals and salinities in summer. This likely reflected varying stages of gonad development. Valve movements measured at the five salinities indicated oysters were open 50–60% of the time in the 6–25 salinity range and ~ 30% at a salinity of 3. Reduced opening periods, concomitant with narrower valve gap amplitudes, are in accord with the limited feeding at the lowest salinity (3). These data indicate the need for increased focus on experimental determination of optimal ranges and thresholds to better quantify oyster population responses to environmental changes.
","language":"English","publisher":"Springer","doi":"10.1007/s00227-018-3351-x","usgsCitation":"Casas, S., Lavaud, R., LaPeyre, M.K., Comeau, L., Filgueira, R., and LaPeyre, J.F., 2018, Quantifying salinity and season effects on eastern oyster clearance and oxygen consumption rates: Marine Biology, v. 165, p. 1-13, https://doi.org/10.1007/s00227-018-3351-x.","productDescription":"Article 90; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-092990","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":353872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-25","publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe14","contributors":{"authors":[{"text":"Casas, S.M.","contributorId":8321,"corporation":false,"usgs":true,"family":"Casas","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":734390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lavaud, Romain","contributorId":200114,"corporation":false,"usgs":false,"family":"Lavaud","given":"Romain","email":"","affiliations":[],"preferred":false,"id":734391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":734313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Comeau, L. A.","contributorId":204577,"corporation":false,"usgs":false,"family":"Comeau","given":"L. A.","affiliations":[],"preferred":false,"id":734392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Filgueira, R.","contributorId":204578,"corporation":false,"usgs":false,"family":"Filgueira","given":"R.","email":"","affiliations":[],"preferred":false,"id":734393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaPeyre, Jerome F.","contributorId":189466,"corporation":false,"usgs":false,"family":"LaPeyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":734394,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196821,"text":"70196821 - 2018 - Reduced arctic tundra productivity linked with landform and climate change interactions","interactions":[],"lastModifiedDate":"2018-05-03T13:48:20","indexId":"70196821","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Reduced arctic tundra productivity linked with landform and climate change interactions","docAbstract":"Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (~60,000 km²) using the Landsat archive (1999–2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-20692-8","usgsCitation":"Lara, M.J., Nitze, I., Grosse, G., Martin, P., and McGuire, A.D., 2018, Reduced arctic tundra productivity linked with landform and climate change interactions: Scientific Reports, v. 8, Article 2345; 10 p., https://doi.org/10.1038/s41598-018-20692-8.","productDescription":"Article 2345; 10 p.","ipdsId":"IP-085871","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-20692-8","text":"Publisher Index Page"},{"id":353942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-05","publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbe02","contributors":{"authors":[{"text":"Lara, Mark J.","contributorId":194640,"corporation":false,"usgs":false,"family":"Lara","given":"Mark","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":734605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nitze, Ingmar","contributorId":191057,"corporation":false,"usgs":false,"family":"Nitze","given":"Ingmar","affiliations":[],"preferred":false,"id":734606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":734607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Philip","contributorId":204661,"corporation":false,"usgs":false,"family":"Martin","given":"Philip","affiliations":[{"id":27594,"text":"Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":734608,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":734604,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196770,"text":"70196770 - 2018 - Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA","interactions":[],"lastModifiedDate":"2018-05-01T13:25:49","indexId":"70196770","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA","docAbstract":"Understanding the controls of agriculture and climate change on recharge rates is critically important to develop appropriate sustainable management plans for groundwater resources and coupled irrigated agricultural systems. In this study, several physical (total potential (ψT) time series) and chemical tracer and dating (3H, Cl−, Br−, CFCs, SF6, and 3H/3He) methods were used to quantify diffuse recharge rates beneath two rangeland sites and irrigation recharge rates beneath two irrigated corn sites along an east-west (wet-dry) transect of the northern High Plains aquifer, Platte River Basin, central Nebraska. The field-based recharge estimates and historical climate were used to calibrate site-specific Hydrus-1D models, and irrigation requirements were estimated using the Crops Simulation Model (CROPSIM). Future model simulations were driven by an ensemble of 16 global climate models and two global warming scenarios to project a 2050 climate relative to the historical baseline 1990 climate, and simulate changes in precipitation, irrigation, evapotranspiration, and diffuse and irrigation recharge rates. Although results indicate statistical differences between the historical variables at the eastern and western sites and rangeland and irrigated sites, the low warming scenario (+1.0 °C) simulations indicate no statistical differences between 2050 and 1990. However, the high warming scenarios (+2.4 °C) indicate a 25% and 15% increase in median annual evapotranspiration and irrigation demand, and decreases in future diffuse recharge by 53% and 98% and irrigation recharge by 47% and 29% at the eastern and western sites, respectively. These results indicate an important threshold between the low and high warming scenarios that if exceeded could trigger a significant bidirectional shift in 2050 hydroclimatology and recharge gradients. The bidirectional shift is that future northern High Plains temperatures will resemble present central High Plains temperatures and future recharge rates in the east will resemble present recharge rates in the western part of the northern High Plains aquifer. The reductions in recharge rates could accelerate declining water levels if irrigation demand and other management strategies are not implemented. Findings here have important implications for future management of irrigation practices and to slow groundwater depletion in this important agricultural region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2018.03.022","usgsCitation":"Lauffenburger, Z.H., Gurdak, J., Hobza, C.M., Woodward, D., and Wolf, C., 2018, Irrigated agriculture and future climate change effects on groundwater recharge, northern High Plains aquifer, USA: Agricultural Water Management, v. 204, p. 69-80, https://doi.org/10.1016/j.agwat.2018.03.022.","productDescription":"12 p.","startPage":"69","endPage":"80","ipdsId":"IP-095074","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":468796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.agwat.2018.03.022","text":"Publisher Index Page"},{"id":353879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern High Plains Aquifer","volume":"204","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe18","contributors":{"authors":[{"text":"Lauffenburger, Zachary H.","contributorId":204545,"corporation":false,"usgs":false,"family":"Lauffenburger","given":"Zachary","email":"","middleInitial":"H.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":734307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurdak, Jason J.","contributorId":189822,"corporation":false,"usgs":false,"family":"Gurdak","given":"Jason J.","affiliations":[],"preferred":false,"id":734308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodward, Duane","contributorId":204547,"corporation":false,"usgs":false,"family":"Woodward","given":"Duane","affiliations":[{"id":36954,"text":"Central Platte Natural Resources District","active":true,"usgs":false}],"preferred":false,"id":734310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Cassandra","contributorId":204546,"corporation":false,"usgs":false,"family":"Wolf","given":"Cassandra","email":"","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":734309,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196771,"text":"70196771 - 2018 - Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches","interactions":[],"lastModifiedDate":"2018-05-01T11:40:01","indexId":"70196771","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches","docAbstract":"Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision making. Therefore, we also discuss alternative approaches to yield unbiased estimates of population state variables using similar data types, and we stress that there is no substitute for an effective sample design that is grounded upon well-defined management objectives.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.02.007","usgsCitation":"Duarte, A., Adams, M.J., and Peterson, J., 2018, Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches: Ecological Modelling, v. 374, p. 51-59, https://doi.org/10.1016/j.ecolmodel.2018.02.007.","productDescription":"9 p.","startPage":"51","endPage":"59","ipdsId":"IP-090875","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468791,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.02.007","text":"Publisher Index Page"},{"id":353873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"374","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cce4b0da30c1bfbe16","contributors":{"authors":[{"text":"Duarte, Adam","contributorId":79822,"corporation":false,"usgs":true,"family":"Duarte","given":"Adam","email":"","affiliations":[],"preferred":false,"id":734395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, M. J. 0000-0001-8844-042X mjadams@usgs.gov","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":3133,"corporation":false,"usgs":false,"family":"Adams","given":"M.","email":"mjadams@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":734312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734311,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196986,"text":"70196986 - 2018 - The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival","interactions":[],"lastModifiedDate":"2018-05-15T16:34:47","indexId":"70196986","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival","docAbstract":"On-going climate change has major impacts on ecological processes and patterns. Understanding the impacts of climate on the geographical patterns of survival can provide insights to how population dynamics respond to climate change and provide important information for the development of appropriate conservation strategies at regional scales. It is challenging to understand the impacts of climate on survival, however, due to the fact that the non-linear relationship between survival and climate can be modified by density-dependent processes. In this study we extended the Brownie model to partition hunting and non-hunting mortalities and linked non-hunting survival to covariates. We applied this model to four decades (1972–2014) of waterfowl band-recovery, breeding population survey, and precipitation and temperature data covering multiple ecological regions to examine the non-linear, interactive effects of population density and climate on waterfowl non-hunting survival at a regional scale. Our results showed that the non-linear effect of temperature on waterfowl non-hunting survival was modified by breeding population density. The concave relationship between non-hunting survival and temperature suggested that the effects of warming on waterfowl survival might be multifaceted. Furthermore, the relationship between non-hunting survival and temperature was stronger when population density was higher, suggesting that high-density populations may be less buffered against warming than low-density populations. Our study revealed distinct relationships between waterfowl non-hunting survival and climate across and within ecological regions, highlighting the importance of considering different conservation strategies according to region-specific population and climate conditions. Our findings and associated novel modelling approach have wide implications in conservation practice.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2018.02.024","usgsCitation":"Zhao, Q., Boomer, G., and Kendall, W.L., 2018, The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival: Biological Conservation, v. 221, p. 1-9, https://doi.org/10.1016/j.biocon.2018.02.024.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-091712","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":354197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"221","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c4e4b0da30c1bfbdf6","contributors":{"authors":[{"text":"Zhao, Qing","contributorId":174370,"corporation":false,"usgs":false,"family":"Zhao","given":"Qing","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":735451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boomer, G. Scott","contributorId":84603,"corporation":false,"usgs":true,"family":"Boomer","given":"G. Scott","affiliations":[],"preferred":false,"id":735452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":735184,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196796,"text":"70196796 - 2018 - Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development","interactions":[],"lastModifiedDate":"2018-05-01T15:45:19","indexId":"70196796","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development","docAbstract":"Shale gas development continues to outpace the implementation of best management practices for wildlife affected by development. We examined demographic responses of the Louisiana Waterthrush (Parkesia motacilla) to shale gas development during 2009–2011 and 2013–2015 in a predominantly forested landscape in West Virginia, USA. Forest cover across the study area decreased from 95% in 2008 to 91% in 2015, while the area affected by shale gas development increased from 0.4% to 3.9%. We quantified nest survival and productivity, a source–sink threshold, riparian habitat quality, territory density, and territory length by monitoring 58.1 km of forested headwater streams (n = 14 streams). Across years, we saw annual variability in nest survival, with a general declining trend over time. Of 11 a priori models tested to explain nest survival (n = 280 nests), 4 models that included temporal, habitat, and shale gas covariates were supported, and 2 of these models accounted for most of the variation in daily nest survival rate. After accounting for temporal effects (rainfall, nest age, and time within season), shale gas development had negative effects on nest survival. Population-level nest productivity declined and individual productivity was lower in areas disturbed by shale gas development than in undisturbed areas, and a source–sink threshold suggested that disturbed areas were more at risk of being sink habitat. Riparian habitat quality scores, as measured by a U.S. Environmental Protection Agency index and a waterthrush-specific habitat suitability index, differed by year and were negatively related to the amount of each territory disturbed by shale gas development. Territory density was not related to the amount of shale gas disturbance, but decreased over time as territory lengths increased. Overall, our results suggest a decline in waterthrush site quality as shale gas development increases, despite relatively small site-wide forest loss.
","language":"English","publisher":"American Ornithological Society","doi":"10.1650/CONDOR-17-130.1","usgsCitation":"Frantz, M.W., Wood, P.B., Sheehan, J., and George, G., 2018, Demographic response of Louisiana Waterthrush, a stream obligate songbird of conservation concern, to shale gas development: Condor, v. 120, no. 2, p. 265-282, https://doi.org/10.1650/CONDOR-17-130.1.","productDescription":"18 p.","startPage":"265","endPage":"282","ipdsId":"IP-081181","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468794,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.1650/CONDOR-17-130.1","text":"External Repository"},{"id":353898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Lewis Wetzel Wildlife Management Area","volume":"120","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6c5e4b0da30c1bfbe0a","contributors":{"authors":[{"text":"Frantz, Mack W.","contributorId":191486,"corporation":false,"usgs":false,"family":"Frantz","given":"Mack","email":"","middleInitial":"W.","affiliations":[{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false},{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":734475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":734431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, James","contributorId":169745,"corporation":false,"usgs":false,"family":"Sheehan","given":"James","email":"","affiliations":[],"preferred":false,"id":734476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"George, Gregory","contributorId":204601,"corporation":false,"usgs":false,"family":"George","given":"Gregory","affiliations":[],"preferred":false,"id":734477,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197428,"text":"70197428 - 2018 - Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information","interactions":[],"lastModifiedDate":"2018-06-04T10:36:56","indexId":"70197428","displayToPublicDate":"2018-05-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information","docAbstract":"Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.2279","usgsCitation":"Jarnevich, C.S., Young, N.E., Talbert, M., and Talbert, C., 2018, Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information: Ecosphere, v. 9, no. 5, p. 1-12, https://doi.org/10.1002/ecs2.2279.","productDescription":"e02279; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-097154","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468799,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2279","text":"Publisher Index Page"},{"id":437929,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Y99UFF","text":"USGS data release","linkHelpText":"Data for forecasting buffelgrass distribution with global distribution data, local data, and physiological information"},{"id":354686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Saguaro National Park","volume":"9","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-29","publicationStatus":"PW","scienceBaseUri":"5b155d84e4b092d9651e1b61","contributors":{"authors":[{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":737118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nicholas E.","contributorId":58572,"corporation":false,"usgs":true,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":737119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Talbert, Marian 0000-0003-0588-0265 mtalbert@usgs.gov","orcid":"https://orcid.org/0000-0003-0588-0265","contributorId":196740,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":737120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbert, Colin 0000-0002-9505-1876 talbertc@usgs.gov","orcid":"https://orcid.org/0000-0002-9505-1876","contributorId":181913,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":737121,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}