The persistence and geographic expansion of dryland forests in the 21st century will be influenced by how climate change supports the demographic processes associated with tree regeneration. Yet, the way that climate change may alter regeneration is unclear. We developed a quantitative framework that estimates forest regeneration potential (RP) as a function of key environmental conditions for ponderosa pine, a key dryland forest species. We integrated meteorological data and climate projections for 47 ponderosa pine forest sites across the western United States, and evaluated RP using an ecosystem water balance model. Our primary goal was to contrast conditions supporting regeneration among historical, mid-21st century and late-21st century time frames. Future climatic conditions supported 50% higher RP in 2020–2059 relative to 1910–2014. As temperatures increased more substantially in 2060–2099, seedling survival decreased, RP declined by 50%, and the frequency of years with very low RP increased from 25% to 58%. Thus, climate change may initially support higher RP and increase the likelihood of successful regeneration events, yet will ultimately reduce average RP and the frequency of years with moderate climate support of regeneration. Our results suggest that climate change alone may begin to restrict the persistence and expansion of dryland forests by limiting seedling survival in the late 21st century.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1791","usgsCitation":"Petrie, M., Bradford, J.B., Hubbard, R., Lauenroth, W., Andrews, C.M., and Schlaepfer, D., 2017, Climate change may restrict dryland forest regeneration in the 21st century: Ecology, v. 98, no. 6, p. 1548-1559, https://doi.org/10.1002/ecy.1791.","productDescription":"12 p.","startPage":"1548","endPage":"1559","ipdsId":"IP-081499","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":342558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.408203125,\n 26.27371402440643\n ],\n [\n -96.328125,\n 26.27371402440643\n ],\n [\n -96.328125,\n 51.12421275782688\n ],\n [\n -128.408203125,\n 51.12421275782688\n ],\n [\n -128.408203125,\n 26.27371402440643\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-30","publicationStatus":"PW","scienceBaseUri":"59439c91e4b062508e31a97e","contributors":{"authors":[{"text":"Petrie, M.D.","contributorId":192983,"corporation":false,"usgs":false,"family":"Petrie","given":"M.D.","email":"","affiliations":[],"preferred":false,"id":698374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubbard, R.M.","contributorId":167015,"corporation":false,"usgs":false,"family":"Hubbard","given":"R.M.","email":"","affiliations":[{"id":24595,"text":"USDA Forest Service, Fort Collins CO","active":true,"usgs":false}],"preferred":false,"id":698375,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, W.K.","contributorId":192984,"corporation":false,"usgs":false,"family":"Lauenroth","given":"W.K.","email":"","affiliations":[],"preferred":false,"id":698376,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrews, Caitlin M. 0000-0003-4593-1071 candrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4593-1071","contributorId":192985,"corporation":false,"usgs":true,"family":"Andrews","given":"Caitlin","email":"candrews@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":698377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlaepfer, D.R.","contributorId":140421,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"D.R.","email":"","affiliations":[{"id":13488,"text":"Dept. of Botany, University of Wyoming, 1000 E. UNIVersity Avenue, Laramie, WY 82070","active":true,"usgs":false}],"preferred":false,"id":698378,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188579,"text":"70188579 - 2017 - Nearly 400 million people are at higher risk of schistosomiasis because dams block the migration of snail-eating river prawns","interactions":[],"lastModifiedDate":"2017-06-15T16:13:29","indexId":"70188579","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Nearly 400 million people are at higher risk of schistosomiasis because dams block the migration of snail-eating river prawns","docAbstract":"Dams have long been associated with elevated burdens of human schistosomiasis, but how dams increase disease is not always clear, in part because dams have many ecological and socio-economic effects. A recent hypothesis argues that dams block reproduction of the migratory river prawns that eat the snail hosts of schistosomiasis. In the Senegal River Basin, there is evidence that prawn populations declined and schistosomiasis increased after completion of the Diama Dam. Restoring prawns to a water-access site upstream of the dam reduced snail density and reinfection rates in people. However, whether a similar cascade of effects (from dams to prawns to snails to human schistosomiasis) occurs elsewhere is unknown. Here, we examine large dams worldwide and identify where their catchments intersect with endemic schistosomiasis and the historical habitat ranges of large, migratory Macrobrachium spp. prawns. River prawn habitats are widespread, and we estimate that 277–385 million people live within schistosomiasis-endemic regions where river prawns are or were present (out of the 800 million people who are at risk of schistosomiasis). Using a published repository of schistosomiasis studies in sub-Saharan Africa, we compared infection before and after the construction of 14 large dams for people living in: (i) upstream catchments within historical habitats of native prawns, (ii) comparable undammed watersheds, and (iii) dammed catchments beyond the historical reach of migratory prawns. Damming was followed by greater increases in schistosomiasis within prawn habitats than outside prawn habitats. We estimate that one third to one half of the global population-at-risk of schistosomiasis could benefit from restoration of native prawns. Because dams block prawn migrations, our results suggest that prawn extirpation contributes to the sharp increase of schistosomiasis after damming, and points to prawn restoration as an ecological solution for reducing human disease.","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2016.0127","usgsCitation":"Sokolow, S.H., Jones, I.J., Jocque, M.M., La, D., Cords, O., Knight, A., Lund, A., Wood, C.L., Lafferty, K.D., Hoover, C.M., Collender, P.A., Remais, J.V., Lopez-Carr, D., Fisk, J.J., Kuris, A.M., and De Leo, G.A., 2017, Nearly 400 million people are at higher risk of schistosomiasis because dams block the migration of snail-eating river prawns: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 372, no. 1722, 20160127; 12 p., https://doi.org/10.1098/rstb.2016.0127.","productDescription":"20160127; 12 p.","ipdsId":"IP-077017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2016.0127","text":"Publisher Index Page"},{"id":342576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","issue":"1722","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"59439c90e4b062508e31a96d","contributors":{"authors":[{"text":"Sokolow, Susanne H.","contributorId":52503,"corporation":false,"usgs":false,"family":"Sokolow","given":"Susanne","email":"","middleInitial":"H.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":698419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Isabel J.","contributorId":173135,"corporation":false,"usgs":false,"family":"Jones","given":"Isabel","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":698420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jocque, Merlijn M. T.","contributorId":178115,"corporation":false,"usgs":false,"family":"Jocque","given":"Merlijn","email":"","middleInitial":"M. T.","affiliations":[],"preferred":false,"id":698421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La, Diana","contributorId":192996,"corporation":false,"usgs":false,"family":"La","given":"Diana","email":"","affiliations":[],"preferred":false,"id":698422,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cords, Olivia","contributorId":192997,"corporation":false,"usgs":false,"family":"Cords","given":"Olivia","email":"","affiliations":[],"preferred":false,"id":698423,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knight, Anika","contributorId":192998,"corporation":false,"usgs":false,"family":"Knight","given":"Anika","email":"","affiliations":[],"preferred":false,"id":698424,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lund, Andrea","contributorId":192999,"corporation":false,"usgs":false,"family":"Lund","given":"Andrea","affiliations":[],"preferred":false,"id":698425,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wood, Chelsea L.","contributorId":192504,"corporation":false,"usgs":false,"family":"Wood","given":"Chelsea","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":698426,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":698418,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hoover, Christopher M.","contributorId":193000,"corporation":false,"usgs":false,"family":"Hoover","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":698427,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collender, Phillip A.","contributorId":193001,"corporation":false,"usgs":false,"family":"Collender","given":"Phillip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":698428,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Remais, Justin V.","contributorId":193002,"corporation":false,"usgs":false,"family":"Remais","given":"Justin","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":698429,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lopez-Carr, David","contributorId":193003,"corporation":false,"usgs":false,"family":"Lopez-Carr","given":"David","email":"","affiliations":[],"preferred":false,"id":698430,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fisk, Jonathan J.","contributorId":193004,"corporation":false,"usgs":false,"family":"Fisk","given":"Jonathan","middleInitial":"J.","affiliations":[],"preferred":false,"id":698431,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kuris, Armand M.","contributorId":189859,"corporation":false,"usgs":false,"family":"Kuris","given":"Armand","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":698432,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"De Leo, Giulio A.","contributorId":146323,"corporation":false,"usgs":false,"family":"De Leo","given":"Giulio","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":698433,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70188580,"text":"70188580 - 2017 - Season, molt, and body size influence mercury concentrations in grebes","interactions":[],"lastModifiedDate":"2017-12-04T12:49:03","indexId":"70188580","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Season, molt, and body size influence mercury concentrations in grebes","docAbstract":"We studied seasonal and physiological influences on mercury concentrations in western grebes (Aechmophorus occidentalis) and Clark's grebes (A. occidentalis) across 29 lakes and reservoirs in California, USA. Additionally, at three of these lakes, we conducted a time series study, in which we repeatedly sampled grebe blood mercury concentrations during the spring, summer, and early fall. Grebe blood mercury concentrations were higher among males (0.61 ± 0.12 μg/g ww) than females (0.52 ± 0.10 μg/g ww), higher among Clark's grebes (0.58 ± 0.12 μg/g ww) than western grebes (0.51 ± 0.10 μg/g ww), and exhibited a strong seasonal pattern (decreasing by 60% from spring to fall). Grebe blood THg concentrations exhibited a shallow, inverse U-shaped pattern with body size, and was lowest among the smallest and largest grebes. Further, the relationship between grebe blood mercury concentrations and wing primary feather molt exhibited a shallow U-shaped pattern, where mercury concentrations were highest among birds that had not yet begun molting, decreased approximately 24% between pre-molt and late molt, and increased approximately 19% from late molt to post-molt. Because grebes did not begin molting until mid-summer, lower grebe blood mercury concentrations observed in late summer and early fall were consistent with the onset of primary feather molt. However, because sampling date was a much stronger predictor of grebe mercury concentrations than molt, other seasonally changing environmental factors likely played a larger role than molt in the seasonal variation in grebe mercury concentrations. In the time series study, we found that seasonal trends in grebe mercury concentrations were not consistent among lakes, indicating that lake-specific variation in mercury dynamics influence the overall seasonal decline in grebe blood mercury concentrations. These results highlight the importance of accounting for sampling date, as well as ecological processes that may influence mercury concentrations, when developing monitoring programs to assess site-specific exposure risk of mercury to wildlife.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.05.058","usgsCitation":"Hartman, C.A., Ackerman, J., Herzog, M.P., and Eagles-Smith, C.A., 2017, Season, molt, and body size influence mercury concentrations in grebes: Environmental Pollution, v. 229, p. 29-39, https://doi.org/10.1016/j.envpol.2017.05.058.","productDescription":"11 p.","startPage":"29","endPage":"39","ipdsId":"IP-083568","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":342579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"229","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59439c8ee4b062508e31a966","contributors":{"authors":[{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131157,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":698435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":698434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":698436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":698437,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191185,"text":"70191185 - 2017 - UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA","interactions":[],"lastModifiedDate":"2017-09-28T16:33:02","indexId":"70191185","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA","docAbstract":"Forest vegetation classification and structure measurements are fundamental steps for planning, monitoring, and evaluating large-scale forest changes including restoration treatments. High spatial and spectral resolution remote sensing data are critically needed to classify vegetation and measure their 3-dimensional (3D) canopy structure at the level of individual species. Here we test high-resolution lidar, hyperspectral, and multispectral data collected from unmanned aerial vehicles (UAV) and demonstrate a lidar-hyperspectral image fusion method in treated and control forests with varying tree density and canopy cover as well as in an ecotone environment to represent a gradient of vegetation and topography in northern Arizona, U.S.A. The fusion performs better (88% overall accuracy) than either data type alone, particularly for species with similar spectral signatures, but different canopy sizes. The lidar data provides estimates of individual tree height (R2 = 0.90; RMSE = 2.3 m) and crown diameter (R2 = 0.72; RMSE = 0.71 m) as well as total tree canopy cover (R2 = 0.87; RMSE = 9.5%) and tree density (R2 = 0.77; RMSE = 0.69 trees/cell) in 10 m cells across thin only, burn only, thin-and-burn, and control treatments, where tree cover and density ranged between 22 and 50% and 1–3.5 trees/cell, respectively. The lidar data also produces highly accurate digital elevation model (DEM) (R2 = 0.92; RMSE = 0.75 m). In comparison, 3D data derived from the multispectral data via structure-from-motion produced lower correlations with field-measured variables, especially in dense and structurally complex forests. The lidar, hyperspectral, and multispectral sensors, and the methods demonstrated here can be widely applied across a gradient of vegetation and topography for monitoring landscapes undergoing large-scale changes such as the forests in the southwestern U.S.A.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.04.007","usgsCitation":"Sankey, T.T., Donager, J., McVay, J.L., and Sankey, J.B., 2017, UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA: Remote Sensing of Environment, v. 195, p. 30-43, https://doi.org/10.1016/j.rse.2017.04.007.","productDescription":"14 p.","startPage":"30","endPage":"43","ipdsId":"IP-073648","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":346176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","volume":"195","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59ce0a2be4b05fe04cc0210a","contributors":{"authors":[{"text":"Sankey, Temuulen T.","contributorId":173297,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"T.","affiliations":[{"id":7202,"text":"NAU","active":true,"usgs":false}],"preferred":false,"id":711500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Donager, Jonathon","contributorId":196772,"corporation":false,"usgs":false,"family":"Donager","given":"Jonathon","affiliations":[{"id":12698,"text":"Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":711501,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McVay, Jason L.","contributorId":196235,"corporation":false,"usgs":false,"family":"McVay","given":"Jason","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":711502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":711499,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188474,"text":"70188474 - 2017 - Relationship between water and aragonite barium concentrations in aquaria reared juvenile corals","interactions":[],"lastModifiedDate":"2017-06-13T12:25:06","indexId":"70188474","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Relationship between water and aragonite barium concentrations in aquaria reared juvenile corals","docAbstract":"Coral barium to calcium (Ba/Ca) ratios have been used to reconstruct records of upwelling, river and groundwater discharge, and sediment and dust input to the coastal ocean. However, this proxy has not yet been explicitly tested to determine if Ba inclusion in the coral skeleton is directly proportional to seawater Ba concentration and to further determine how additional factors such as temperature and calcification rate control coral Ba/Ca ratios. We measured the inclusion of Ba within aquaria reared juvenile corals (Favia fragum) at three temperatures (∼27.7, 24.6 and 22.5 °C) and three seawater Ba concentrations (73, 230 and 450 nmol kg−1). Coral polyps were settled on tiles conditioned with encrusting coralline algae, which complicated chemical analysis of the coral skeletal material grown during the aquaria experiments. We utilized Sr/Ca ratios of encrusting coralline algae (as low as 3.4 mmol mol−1) to correct coral Ba/Ca for this contamination, which was determined to be 26 ± 11% using a two end member mixing model. Notably, there was a large range in Ba/Ca across all treatments, however, we found that Ba inclusion was linear across the full concentration range. The temperature sensitivity of the distribution coefficient is within the range of previously reported values. Finally, calcification rate, which displayed large variability, was not correlated to the distribution coefficient. The observed temperature dependence predicts a change in coral Ba/Ca ratios of 1.1 μmol mol−1 from 20 to 28 °C for typical coastal ocean Ba concentrations of 50 nmol kg−1. Given the linear uptake of Ba by corals observed in this study, coral proxy records that demonstrate peaks of 10–25 μmol mol−1 would require coastal seawater Ba of between 60 and 145 nmol kg−1. Further validation of the coral Ba/Ca proxy requires evaluation of changes in seawater chemistry associated with the environmental perturbation recorded by the coral as well as verification of these results for Porites species, which are widely used in paleo reconstructions.
","language":"English","publisher":"Geochemical Society","doi":"10.1016/j.gca.2017.04.006","usgsCitation":"Gonneea Eagle, M., Cohen, A.L., DeCarlo, T.M., and Charette, M.A., 2017, Relationship between water and aragonite barium concentrations in aquaria reared juvenile corals: Geochimica et Cosmochimica Acta, v. 209, p. 123-134, https://doi.org/10.1016/j.gca.2017.04.006.","productDescription":"12 p.","startPage":"123","endPage":"134","ipdsId":"IP-079452","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469749,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/9163","text":"External Repository"},{"id":342424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"209","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1c8e4b0d1f9f05b37b0","contributors":{"authors":[{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":697917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Anne L.","contributorId":190716,"corporation":false,"usgs":false,"family":"Cohen","given":"Anne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":697918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCarlo, Thomas M.","contributorId":190720,"corporation":false,"usgs":false,"family":"DeCarlo","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Charette, Matthew A.","contributorId":92355,"corporation":false,"usgs":true,"family":"Charette","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":697920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188610,"text":"70188610 - 2017 - Quantifying drivers of wild pig movement across multiple spatial and temporal scales","interactions":[],"lastModifiedDate":"2017-06-17T11:53:46","indexId":"70188610","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying drivers of wild pig movement across multiple spatial and temporal scales","docAbstract":"Background\nThe movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management.\n\nMethods\nWe obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season.\n\nResults\nWe found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales.\n\nConclusions\nThe analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.","language":"English","publisher":"BioMedCentral","doi":"10.1186/s40462-017-0105-1","usgsCitation":"Kay, S.L., Fischer, J.W., Monaghan, A.J., Beasley, J.C., Boughton, R., Campbell, T.A., Cooper, S.M., Ditchkoff, S.S., Hartley, S.B., Kilgo, J.C., Wisely, S.M., Wyckoff, A.C., Vercauteren, K.C., and Pipen, K.M., 2017, Quantifying drivers of wild pig movement across multiple spatial and temporal scales: Movement Ecology, v. 5, no. 14, p. 1-15, https://doi.org/10.1186/s40462-017-0105-1.","productDescription":" 15 p. ","startPage":"1","endPage":"15","ipdsId":"IP-078294","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-017-0105-1","text":"Publisher Index Page"},{"id":342619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"14","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-15","publicationStatus":"PW","scienceBaseUri":"59463fa3e4b062508e34408f","contributors":{"authors":[{"text":"Kay, Shannon L.","contributorId":193049,"corporation":false,"usgs":false,"family":"Kay","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":698585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, Justin W.","contributorId":171828,"corporation":false,"usgs":false,"family":"Fischer","given":"Justin","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":698586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monaghan, Andrew J.","contributorId":179216,"corporation":false,"usgs":false,"family":"Monaghan","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":698587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beasley, James C","contributorId":193050,"corporation":false,"usgs":false,"family":"Beasley","given":"James","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":698588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boughton, Raoul","contributorId":172817,"corporation":false,"usgs":false,"family":"Boughton","given":"Raoul","affiliations":[{"id":27096,"text":"Wildlife Ecology and Conservation, Range Cattle Research and Education Center, University of Florida, 3401 Experiment Station, Ona, Florida 33865 USA","active":true,"usgs":false}],"preferred":false,"id":698589,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campbell, Tyler A","contributorId":193051,"corporation":false,"usgs":false,"family":"Campbell","given":"Tyler","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":698590,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cooper, Susan M","contributorId":193052,"corporation":false,"usgs":false,"family":"Cooper","given":"Susan","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":698591,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ditchkoff, Stephen S.","contributorId":193053,"corporation":false,"usgs":false,"family":"Ditchkoff","given":"Stephen","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":698592,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hartley, Stephen B. 0000-0003-1380-2769 hartleys@usgs.gov","orcid":"https://orcid.org/0000-0003-1380-2769","contributorId":4164,"corporation":false,"usgs":true,"family":"Hartley","given":"Stephen","email":"hartleys@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":698584,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kilgo, John C","contributorId":193054,"corporation":false,"usgs":false,"family":"Kilgo","given":"John","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":698593,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wisely, Samantha M","contributorId":193055,"corporation":false,"usgs":false,"family":"Wisely","given":"Samantha","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":698594,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wyckoff, A Christy","contributorId":193056,"corporation":false,"usgs":false,"family":"Wyckoff","given":"A","email":"","middleInitial":"Christy","affiliations":[],"preferred":false,"id":698595,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vercauteren, Kurt C.","contributorId":193057,"corporation":false,"usgs":false,"family":"Vercauteren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":698596,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pipen, Kim M","contributorId":193058,"corporation":false,"usgs":false,"family":"Pipen","given":"Kim","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":698597,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70188578,"text":"70188578 - 2017 - Continuity of the Reelfoot fault across the Cottonwood Grove and Ridgely faults of the New Madrid Seismic Zone","interactions":[],"lastModifiedDate":"2017-06-20T13:28:55","indexId":"70188578","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":960,"text":"BSSA","active":true,"publicationSubtype":{"id":10}},"title":"Continuity of the Reelfoot fault across the Cottonwood Grove and Ridgely faults of the New Madrid Seismic Zone","docAbstract":"Previous investigators have argued that the northwest-striking Reelfoot\nfault of northwest Tennessee and southeastern Missouri is segmented. One segment\nboundary is at the intersection of the northeast-striking Cottonwood Grove and\nRidgely strike-slip faults with the Reelfoot fault. We use seismic reflection and geologic\nmapping to locate and determine the history of the Reelfoot South fault across\nthis boundary zone. One reflection profile revealed a southwest-dipping (81°) Reelfoot\nSouth reverse fault that displaces the top of the Paleozoic 65 m, Cretaceous 40 m,\nPaleocene 31 m, Eocene Wilcox Group 20 m, and Eocene Memphis Sand 16 m. A\nsecond reflection profile reveals a north-dipping (84°) reverse fault 4.3 km south of the\nReelfoot South fault, which defines the southwest margin of the Tiptonville dome.\nA geologic profile of the base of the ∼3:1 Ma Upland complex (Mississippi River\nterrace alluvium) within theMississippi River bluffs reveals ∼6 m of displacement across\nthe Reelfoot South fault. Similarly, Quaternary stream terrace distribution suggests ∼6 m\nof Reelfoot South hanging-wall (Tiptonville dome) uplift that is probably Holocene.\nFault strike trends show the Reelfoot fault and its hanging-wall Tiptonville dome are\nnot laterally offset across the Cottonwood Grove and Ridgely faults. The Reelfoot South\nfault northwest and southeast of the Cottonwood Grove and Ridgely faults has very similar\nvertical displacement on common stratigraphic marker horizons in the upper 900 m.\nThese data indicate the Reelfoot fault/Tiptonville dome has acted as one continuous fault\nzone across the Cottonwood Grove and Ridgely faults since Late Cretaceous.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120150290","usgsCitation":"Greenwood, M., Woolery, E.W., Van Arsdale, R.B., Stephenson, W.J., and Patterson, G.L., 2017, Continuity of the Reelfoot fault across the Cottonwood Grove and Ridgely faults of the New Madrid Seismic Zone: BSSA, v. 106, no. 6, p. 2674-2685, https://doi.org/10.1785/0120150290.","productDescription":"12 p.","startPage":"2674","endPage":"2685","ipdsId":"IP-072716","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":342577,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Tennessee","otherGeospatial":"Reelfoot fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.56878662109375,\n 35.68184060244453\n ],\n [\n -89.1046142578125,\n 36.73668306473141\n ],\n [\n -89.6319580078125,\n 36.78949107451841\n ],\n [\n -90.1153564453125,\n 35.75765724051559\n ],\n [\n -89.56878662109375,\n 35.68184060244453\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-25","publicationStatus":"PW","scienceBaseUri":"59439c90e4b062508e31a972","contributors":{"authors":[{"text":"Greenwood, M.L.","contributorId":192993,"corporation":false,"usgs":false,"family":"Greenwood","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":698414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woolery, Edward W 0000-0003-3398-5830","orcid":"https://orcid.org/0000-0003-3398-5830","contributorId":192994,"corporation":false,"usgs":false,"family":"Woolery","given":"Edward","email":"","middleInitial":"W","affiliations":[],"preferred":false,"id":698415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Arsdale, R. B.","contributorId":121450,"corporation":false,"usgs":true,"family":"Van Arsdale","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":698416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Patterson, Gary L. glpatter@usgs.gov","contributorId":519,"corporation":false,"usgs":true,"family":"Patterson","given":"Gary","email":"glpatter@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":698444,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188351,"text":"ofr20171069 - 2017 - Inter-annual variability in apparent relative production, survival, and growth of juvenile Lost River and shortnose suckers in Upper Klamath Lake, Oregon, 2001–15","interactions":[],"lastModifiedDate":"2017-06-16T08:26:47","indexId":"ofr20171069","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1069","title":"Inter-annual variability in apparent relative production, survival, and growth of juvenile Lost River and shortnose suckers in Upper Klamath Lake, Oregon, 2001–15","docAbstract":"Populations of the once abundant Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) of the Upper Klamath Basin, decreased so substantially throughout the 20th century that they were listed under the Endangered Species Act in 1988. Major landscape alterations, deterioration of water quality, and competition with and predation by exotic species are listed as primary causes of the decreases in populations. Upper Klamath Lake populations are decreasing because fish lost due to adult mortality, which is relatively low for adult Lost River suckers and variable for adult shortnose suckers, are not replaced by new young adult suckers recruiting into known adult spawning aggregations. Catch-at-age and size data indicate that most adult suckers presently in Upper Klamath Lake spawning populations were hatched around 1991. While, a lack of egg production and emigration of young fish (especially larvae) may contribute, catch-at-length and age data indicate high mortality during the first summer or winter of life may be the primary limitation to the recruitment of young adults. The causes of juvenile sucker mortality are unknown.
We compiled and analyzed catch, length, age, and species data on juvenile suckers from Upper Klamath Lake from eight prior studies conducted from 2001 to 2015 to examine annual variation in apparent production, survival, and growth of young suckers. We used a combination of qualitative assessments, general linear models, and linear regression to make inferences about annual differences in juvenile sucker dynamics. The intent of this exercise is to provide information that can be compared to annual variability in environmental conditions with the hopes of understanding what drives juvenile sucker population dynamics.
Age-0 Lost River suckers generally grew faster than age-0 shortnose suckers, but the difference in growth rates between the two species varied among years. This unsynchronized annual variation in daily growth may be an indication that environmental conditions are affecting growth rates of these species in different ways.
The combined evidence outlined in this report and in Simon and others (2012) indicates that years of relatively high age-0 sucker production occurred in the late 1990s through at least 2000, in 2006, and in 2011. Our analysis of annual age-0 sucker catch per unit effort (CPUE), which accounted for zero inflated data and annual variation in sampling gears and locations, indicated that 2006 had the greatest apparent relative production of age-0 suckers ≥ 45 mm standard length (SL) during the time period examined. Midsummer trap net effort by the U.S. Geological Survey (USGS) was too sparse to examine age-0 sucker CPUE from 2011 to 2013. Relatively frequent catches of age-1 suckers in 2001, 2007, and 2012 corroborated relatively high CPUE for age-0 suckers during 1999–2000, 2006, and 2011, as reported by USGS or Simon and others (2012).
There were several indications in the data that juvenile sucker survival is low from at least midsummer of the first year of life through mid-September of the second year of life. Our estimated index of relative apparent age-0 sucker late-summer survival, which accounted for zero inflated data and variations in sampling gears and locations, was higher in 2009 than in 2004. Our index of apparent age-0 sucker mortality for all other years from 2001 to 2015 was similar among years. Seventy-five percent of age-1 suckers were captured prior to July 17 each year. In 2007, the one year with substantial age-1 sucker summertime catches, the proportion of nets to capture age-1 suckers decreased from July to mid-September. Maximum annual age-2+ sucker CPUE was 0.02 fish per net, 10,000 times less than the maximum annual age-0 sucker CPUE.
Analysis of species data indicated that juvenile Lost River suckers may have greater apparent mortality than shortnose suckers. Lost River suckers made up a smaller proportion of age-0 suckers captured in July each year than would be expected, based on the abundance of adult Lost River suckers relative to shortnose suckers, and higher Lost River than shortnose sucker fecundity. The proportion of age-0 suckers captured that were Lost River suckers decreased from July to September in several years. Only 14 percent of age-1 or older juvenile suckers identified to species over the 15-year time period were Lost River suckers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171069","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Burdick, S.M., and Martin, B.A., 2017, Inter-annual variability in apparent relative production, survival, and growth of juvenile Lost River and shortnose suckers in Upper Klamath Lake, Oregon, 2001–15: U.S. Geological Survey Open-File Report 2017–1069, 55 p., https://doi.org/10.3133/ofr20171069.","productDescription":"Report: vi, 55 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-082248","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":342516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1069/ofr20171069.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1069"},{"id":342517,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC812F","text":"USGS data release","description":"USGS data release","linkHelpText":"Data for trap net captured juvenile Lost River and shortnose suckers from Upper Klamath Lake, Oregon"},{"id":342515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1069/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14,\n 42.20\n ],\n [\n -121.7,\n 42.20\n ],\n [\n -121.7,\n 42.64\n ],\n [\n -122.14,\n 42.64\n ],\n [\n -122.14,\n 42.20\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The Bushy Park Reservoir is a relatively shallow impoundment in a semi-tropical climate and is the principal water supply for the 400,000 people of the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there is an adequate supply of freshwater in the reservoir, taste-and-odor water-quality issues are a concern. The U.S. Geological Survey conducted an investigation in cooperation with the Charleston Water System to study the hydrology and hydrodynamics of the Bushy Park Reservoir to identify factors affecting water-quality conditions. Specifically, five areas for monitoring and (or) analysis were addressed: (1) hydrologic monitoring of the reservoir to establish a water budget, (2) flow monitoring in the tunnels to compute flow from Bushy Park Reservoir and at critical distribution junctions, (3) water-quality sampling, profiling, and continuous monitoring to identify the causes of taste-and-odor occurrence, (4) technical evaluation of appropriate hydrodynamic and water-quality simulation models for the reservoir, and (5) preliminary evaluation of alternative reservoir operations scenarios.
This report describes the hydrodynamic and hydrologic data collected from 2013 to 2015 to support the application and calibration of a three-dimensional hydrodynamic model and the water-quality monitoring and analysis to gain insight into the principal causes of the Bushy Park Reservoir taste-and-odor episodes. The existing U.S. Geological Survey real-time network on the West Branch of the Cooper River was augmented with a tidal flow gage on Durham Canal Back River, and Foster Creek. The Charleston Water System intake structure was instrumented to collect water-level, water temperature (top and bottom probes), specific conductance (top and bottom probes), wind speed and direction, and photosynthetically active radiation data. In addition to the gages attached to fixed structures, four bottom-mounted velocity profilers were deployed at six locations over different periods. The deployment period for the velocity profiler ranged from 2 weeks to 4 months. During the investigation, tidal cycle (13-hour) streamflow measurements were made at 30-minute intervals at five locations.
The Williams Station is a coal-fired powerplant that withdraws water from Bushy Park Reservoir for cooling purposes. The magnitude of the withdrawal (approximately 550 million gallons per day) is the major factor controlling the circulation in the reservoir. The net flow in Durham Canal to the reservoir is comparable to the withdrawal rates of the powerplant. When the Williams Station is not withdrawing water, the net flow in Durham Canal quickly goes to zero or reverses with a net flow away from the reservoir and to the Cooper River. Plan views of the velocity vectors for the tidal cycle streamflow measurements and rose diagram of the velocity profilers created with the Williams Station withdrawing and not withdrawing water show substantial effects of the distribution of magnitude and direction of the water velocities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175050","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Conrads, P.A., Petkewich, M.D., Falls, W.F., and Lanier, T.H., 2017, Hydrologic characterization of Bushy Park Reservoir, South Carolina, 2013–15: U.S. Geological Survey Scientific Investigations Report 2017–5050, 83 p., https://doi.org/10.3133/sir20175050.","productDescription":"Report: ix, 83 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077941","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":342449,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GB2274","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrodynamic data of Bushy Park Reservoir, South Carolina 2013–15"},{"id":342447,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5050/coverthb.jpg"},{"id":342448,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5050/sir20175050.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5050"}],"country":"United States","state":"South Carolina","otherGeospatial":"Santee-Cooper River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.5,\n 32.68\n ],\n [\n -79.7,\n 32.68\n ],\n [\n -79.7,\n 33.56\n ],\n [\n -80.5,\n 33.56\n ],\n [\n -80.5,\n 32.68\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Since juvenile Atlantic salmon (Salmo salar) and Chinook salmon (Oncorhynchus tshawytscha) occupy a similar habitat in Lake Ontario tributaries, we sought to determine the degree of diet similarity between these species in order to assess the potential for interspecific competition. Atlantic salmon, an historically important but currently extirpated component of the Lake Ontario fish community, are the focus of a bi-national restoration effort. Presently this effort includes the release of hatchery produced juvenile Atlantic salmon in Lake Ontario tributaries. These same tributaries support substantial numbers of naturally reproduced juvenile Pacific salmonids including Chinook salmon. Subyearling Atlantic salmon and subyearling Chinook salmon had significantly different diets during each of the three time periods examined. Atlantic salmon fed slightly more from the benthos than from the drift and consumed mainly chirononmids (47.0%) and ephemeropterans (21.1%). The diet of subyearling Chinook salmon was more closely associated with the drift and consisted mainly of chironomids (60.2%) and terrestrial invertebrates (16.0%). Low diet similarity between subyearling Atlantic salmon and subyearling Chinook salmon likely minimizes competitive interactions for food between these species in Lake Ontario tributaries. However, the availability of small prey such as chironomids which comprise over 50% of the diet of each species, soon after emergence, could constitute a short term resource limitation. To our knowledge this is the first study of interspecific diet associations between these two important salmonid species.
","language":"English","publisher":"Wiley","doi":"10.1111/jai.13335","usgsCitation":"Johnson, J.H., Nash, K.J., Chiavelli, R.A., DiRado, J.A., Mackey, G.E., Knight, J.R., and Diaz, A.R., 2017, Diet, feeding patterns, and prey selection of subyearling Atlantic salmon (Salmo salar) and subyearling chinook salmon (Oncorhynchus tshawytscha) in a tributary of Lake Ontario: Journal of Applied Ichthyology, v. 33, no. 3, p. 502-508, https://doi.org/10.1111/jai.13335.","productDescription":"7 p.","startPage":"502","endPage":"508","ipdsId":"IP-079275","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":345158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-03-11","publicationStatus":"PW","scienceBaseUri":"59a288c7e4b077f0056692ad","contributors":{"authors":[{"text":"Johnson, J. H.","contributorId":54914,"corporation":false,"usgs":true,"family":"Johnson","given":"J.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":708501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nash, K. J.","contributorId":195876,"corporation":false,"usgs":false,"family":"Nash","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":708502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chiavelli, R. A.","contributorId":195877,"corporation":false,"usgs":false,"family":"Chiavelli","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":708503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiRado, J. A.","contributorId":195878,"corporation":false,"usgs":false,"family":"DiRado","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":708504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mackey, G. E.","contributorId":195879,"corporation":false,"usgs":false,"family":"Mackey","given":"G.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":708505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knight, J. R.","contributorId":195880,"corporation":false,"usgs":false,"family":"Knight","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":708506,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Diaz, A. R.","contributorId":195881,"corporation":false,"usgs":false,"family":"Diaz","given":"A.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":708507,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70190004,"text":"70190004 - 2017 - Modelling moose–forest interactions under different predation scenarios at Isle Royale National Park, USA","interactions":[],"lastModifiedDate":"2017-08-03T07:15:20","indexId":"70190004","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Modelling moose–forest interactions under different predation scenarios at Isle Royale National Park, USA","docAbstract":"Loss of top predators may contribute to high ungulate population densities and chronic over-browsing of forest ecosystems. However, spatial and temporal variability in the strength of interactions between predators and ungulates occurs over scales that are much shorter than the scales over which forest communities change, making it difficult to characterize trophic cascades in forest ecosystems. We applied the LANDIS-II forest succession model and a recently developed ungulate browsing extension to model how the moose population could interact with the forest ecosystem of Isle Royale National Park, USA, under three different wolf predation scenarios. We contrasted a 100-yr future without wolves (no predation) with two predation scenarios (weak, long-term average predation rates and strong, higher than average rates). Increasing predation rates led to lower peak moose population densities, lower biomass removal rates, and higher estimates of forage availability and landscape carrying capacity, especially during the first 40 yr of simulations. Thereafter, moose population density was similar for all predation scenarios, but available forage biomass and the carrying capacity of the landscape continued to diverge among predation scenarios. Changes in total aboveground live biomass and species composition were most pronounced in the no predation and weak predation scenarios. Consistent with smaller-scale studies, high browsing rates led to reductions in the biomass of heavily browsed Populus tremuloides, Betula papyrifera, and Abies balsamea, and increases in the biomass of unbrowsed Picea glauca and Picea mariana, especially after the simulation year 2050, when existing boreal hardwood stands at Isle Royale are projected to senesce. As a consequence, lower predation rates corresponded with a landscape that progressively shifted toward dominance by Picea glauca and Picea mariana, and lacking available forage biomass. Consistencies with previously documented small-scale successional shifts, and population estimates and trends that approximate those from this and other boreal forests that support moose provide some confidence that these dynamics represent a trophic cascade and therefore provide an important baseline against which to evaluate long-term and large-scale effects of alternative predator management strategies on ungulate populations and forest succession.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1526","usgsCitation":"De Jager, N.R., Rohweder, J.J., Miranda, B.R., Sturtevant, B.R., Fox, T.J., and Romanski, M.C., 2017, Modelling moose–forest interactions under different predation scenarios at Isle Royale National Park, USA: Ecological Applications, v. 27, no. 4, p. 1317-1337, https://doi.org/10.1002/eap.1526.","productDescription":"21 p.","startPage":"1317","endPage":"1337","ipdsId":"IP-077308","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":344546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Isle Royale National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.93295288085938, 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}\n","volume":"27","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-20","publicationStatus":"PW","scienceBaseUri":"5984364ae4b0e2f5d46653bf","contributors":{"authors":[{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miranda, Brian R.","contributorId":195443,"corporation":false,"usgs":false,"family":"Miranda","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":707104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sturtevant, Brian R.","contributorId":190143,"corporation":false,"usgs":false,"family":"Sturtevant","given":"Brian","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":707105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, Timothy J. 0000-0002-6167-3001 tfox@usgs.gov","orcid":"https://orcid.org/0000-0002-6167-3001","contributorId":1701,"corporation":false,"usgs":true,"family":"Fox","given":"Timothy","email":"tfox@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":707106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romanski, Mark C.","contributorId":190147,"corporation":false,"usgs":false,"family":"Romanski","given":"Mark","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":707107,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187796,"text":"sir20175052 - 2017 - Prehistoric floods on the Tennessee River—Assessing the use of stratigraphic records of past floods for improved flood-frequency analysis","interactions":[],"lastModifiedDate":"2020-12-08T12:32:23.922721","indexId":"sir20175052","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5052","title":"Prehistoric floods on the Tennessee River—Assessing the use of stratigraphic records of past floods for improved flood-frequency analysis","docAbstract":"Stratigraphic analysis, coupled with geochronologic techniques, indicates that a rich history of large Tennessee River floods is preserved in the Tennessee River Gorge area. Deposits of flood sediment from the 1867 peak discharge of record (460,000 cubic feet per second at Chattanooga, Tennessee) are preserved at many locations throughout the study area at sites with flood-sediment accumulation. Small exposures at two boulder overhangs reveal evidence of three to four other floods similar in size, or larger, than the 1867 flood in the last 3,000 years—one possibly as much or more than 50 percent larger. Records of floods also are preserved in stratigraphic sections at the mouth of the gorge at Williams Island and near Eaves Ferry, about 70 river miles upstream of the gorge. These stratigraphic records may extend as far back as about 9,000 years ago, giving a long history of Tennessee River floods. Although more evidence is needed to confirm these findings, a more in-depth comprehensive paleoflood study is feasible for the Tennessee River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175052","collaboration":"Prepared in cooperation with the Nuclear Regulatory Commission","usgsCitation":"Harden, T.M., and O’Connor, J.E., 2017, Prehistoric floods on the Tennessee River—Assessing the use of stratigraphic records of past floods for improved flood-frequency analysis: U.S. Geological Survey Scientific Investigations Report 2017–5052, 15 p., https://doi.org/10.3133/sir20175052.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-081426","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":342450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5052/coverthb.jpg"},{"id":342451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5052/sir20175052.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5052"}],"country":"United States","state":"Tennessee","otherGeospatial":"Tennessee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.68649291992186,\n 35.10024874332443\n ],\n [\n -85.6940460205078,\n 34.98837848142154\n ],\n [\n -85.26145935058594,\n 34.99231621532155\n ],\n [\n -85.25871276855467,\n 35.12271673061634\n ],\n [\n -85.2593994140625,\n 35.18952235197259\n ],\n [\n -85.67344665527342,\n 35.184471743812225\n ],\n [\n -85.68649291992186,\n 35.185594128309006\n ],\n [\n -85.68649291992186,\n 35.10024874332443\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Molluscs possess a number of attributes that make them an excellent source of past environmental conditions in estuaries: they are common in estuarine environments; they typically have hard shells and are usually well preserved in sediments; they are relatively easy to detect in the environment; they have limited mobility as adults; they grow by incremental addition of layers to their shells; and they are found in all the major environments surrounding estuaries—terrestrial, freshwater, brackish, and marine waters. Analysis of molluscan assemblages can contribute information about past changes in sea level, climate, land use patterns, anthropogenic alterations, salinity, and other parameters of the benthic habitat and water chemistry within the estuary. High-resolution (from less than a day to annual) records of changes in environmental parameters can be obtained by analyzing the incremental growth layers in mollusc shells (sclerochronology). The shell layers retain information on changes in water temperature, salinity, seasonality, climate, river discharge, productivity, pollution and human activity. Isotopic analyses of mollusc shell growth layers can be problematic in estuaries where water temperatures and isotopic ratios can vary simultaneously; however, methods are being developed to overcome these problems. In addition to sclerochronology, molluscs are important to Holocene and Pleistocene estuarine palaeoenvironmental studies because of their use in the development of age models through radiocarbon dating, amino acid racemization, uranium-thorium series dating, and electron spin resonance (ESR) dating.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applications of Paleoenvironmental Techniques in Estuarine Studies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Dordrecht","doi":"10.1007/978-94-024-0990-1_15","usgsCitation":"Wingard, G.L., and Surge, D., 2017, Application of molluscan analyses to the reconstruction of past environmental conditions in estuaries, chap. 15 of Applications of Paleoenvironmental Techniques in Estuarine Studies, v. 20, p. 357-387, https://doi.org/10.1007/978-94-024-0990-1_15.","productDescription":"31 p.","startPage":"357","endPage":"387","ipdsId":"IP-056056","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"59424b36e4b0764e6c65dc10","contributors":{"authors":[{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Surge, Donna","contributorId":192887,"corporation":false,"usgs":false,"family":"Surge","given":"Donna","email":"","affiliations":[],"preferred":false,"id":698208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188488,"text":"70188488 - 2017 - The spatial distribution of earthquake stress rotations following large subduction zone earthquakes","interactions":[],"lastModifiedDate":"2017-06-14T08:56:36","indexId":"70188488","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"The spatial distribution of earthquake stress rotations following large subduction zone earthquakes","docAbstract":"Rotations of the principal stress axes due to great subduction zone earthquakes have been used to infer low differential stress and near-complete stress drop. The spatial distribution of coseismic and postseismic stress rotation as a function of depth and along-strike distance is explored for three recent M ≥ 8.8 subduction megathrust earthquakes. In the down-dip direction, the largest coseismic stress rotations are found just above the Moho depth of the overriding plate. This zone has been identified as hosting large patches of large slip in great earthquakes, based on the lack of high-frequency radiated energy. The large continuous slip patches may facilitate near-complete stress drop. There is seismological evidence for high fluid pressures in the subducted slab around the Moho depth of the overriding plate, suggesting low differential stress levels in this zone due to high fluid pressure, also facilitating stress rotations. The coseismic stress rotations have similar along-strike extent as the mainshock rupture. Postseismic stress rotations tend to occur in the same locations as the coseismic stress rotations, probably due to the very low remaining differential stress following the near-complete coseismic stress drop. The spatial complexity of the observed stress changes suggests that an analytical solution for finding the differential stress from the coseismic stress rotation may be overly simplistic, and that modeling of the full spatial distribution of the mainshock static stress changes is necessary.
","language":"English","publisher":"Springer","doi":"10.1186/s40623-017-0654-y","usgsCitation":"Hardebeck, J.L., 2017, The spatial distribution of earthquake stress rotations following large subduction zone earthquakes: Earth, Planets and Space, v. 69, no. 69, 11 p., https://doi.org/10.1186/s40623-017-0654-y.","productDescription":"11 p.","ipdsId":"IP-083499","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469752,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-017-0654-y","text":"Publisher Index Page"},{"id":342461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Chile, Indonesia, Japan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -221,\n 34.5\n ],\n [\n -216,\n 34.5\n ],\n [\n -216,\n 41.5\n ],\n [\n -221,\n 41.5\n ],\n [\n -221,\n 34.5\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5,\n -32\n ],\n [\n -75.5,\n -39.5\n ],\n [\n -70,\n -39.5\n ],\n [\n -70,\n -32\n ],\n [\n -75.5,\n -32\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 90.5,\n -1\n ],\n [\n 100,\n -1\n ],\n [\n 100,\n 15\n ],\n [\n 90.5,\n 15\n ],\n [\n 90.5,\n -1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"69","issue":"69","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-18","publicationStatus":"PW","scienceBaseUri":"59424b37e4b0764e6c65dc17","contributors":{"authors":[{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780 jhardebeck@usgs.gov","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":841,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"jhardebeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697976,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70190144,"text":"70190144 - 2017 - Sulfolobus islandicus meta-populations in Yellowstone National Park hot springs","interactions":[],"lastModifiedDate":"2017-11-08T19:25:56","indexId":"70190144","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1548,"text":"Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Sulfolobus islandicus meta-populations in Yellowstone National Park hot springs","title":"Sulfolobus islandicus meta-populations in Yellowstone National Park hot springs","docAbstract":"Abiotic and biotic forces shape the structure and evolution of microbial populations. We investigated forces that shape the spatial and temporal population structure of Sulfolobus islandicus by comparing geochemical and molecular analysis from seven hot springs in five regions sampled over 3 years in Yellowstone National Park. Through deep amplicon sequencing, we uncovered 148 unique alleles at two loci whose relative frequency provides clear evidence for independent populations in different hot springs. Although geography controls regional geochemical composition and population differentiation, temporal changes in population were not explained by corresponding variation in geochemistry. The data suggest that the influence of extinction, bottleneck events and/or selective sweeps within a spring and low migration between springs shape these populations. We suggest that hydrologic events such as storm events and surface snowmelt runoff destabilize smaller hot spring environments with smaller populations and result in high variation in the S. islandicus population over time. Therefore, physical abiotic features such as hot spring size and position in the landscape are important factors shaping the stability and diversity of the S. islandicus meta-population within Yellowstone National Park.
","language":"English","publisher":"Society for Applied Microbiology","doi":"10.1111/1462-2920.13728","usgsCitation":"Campbell, K.M., Kouris, A., England, W., Anderson, R.E., McCleskey, R.B., Nordstrom, D.K., and Whitaker, R.J., 2017, Sulfolobus islandicus meta-populations in Yellowstone National Park hot springs: Environmental Microbiology, v. 19, no. 6, p. 2334-2347, https://doi.org/10.1111/1462-2920.13728.","productDescription":"14 p.","startPage":"2334","endPage":"2347","ipdsId":"IP-076920","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344770,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.368408203125,\n 43.67581809328341\n ],\n [\n -109.522705078125,\n 43.67581809328341\n ],\n [\n -109.522705078125,\n 45.19752230305682\n ],\n [\n -111.368408203125,\n 45.19752230305682\n ],\n [\n -111.368408203125,\n 43.67581809328341\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-22","publicationStatus":"PW","scienceBaseUri":"598e905ae4b09fa1cb160971","contributors":{"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":707677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kouris, Angela","contributorId":195622,"corporation":false,"usgs":false,"family":"Kouris","given":"Angela","email":"","affiliations":[],"preferred":false,"id":707678,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"England, Whitney","contributorId":195623,"corporation":false,"usgs":false,"family":"England","given":"Whitney","email":"","affiliations":[],"preferred":false,"id":707679,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anderson, Rika E.","contributorId":195624,"corporation":false,"usgs":false,"family":"Anderson","given":"Rika","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":707680,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":707681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":707682,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whitaker, Rachel J.","contributorId":195625,"corporation":false,"usgs":false,"family":"Whitaker","given":"Rachel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":707683,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188529,"text":"70188529 - 2017 - Gray Wolf (Canis lupus) death by stick impalement","interactions":[],"lastModifiedDate":"2017-06-14T12:37:04","indexId":"70188529","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Gray Wolf (Canis lupus) death by stick impalement","title":"Gray Wolf (Canis lupus) death by stick impalement","docAbstract":"Although Canis lupus L. (Gray Wolf) individuals are sometimes impaled by sticks, we could find no documentation of natural impalement by sticks as a cause of death for wild Wolves. Here we report on a wild Gray Wolf from northeastern Minnesota that died due to stick puncture of its thorax and abdomen.
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David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":698153,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188151,"text":"ofr20171067 - 2017 - A new seamless, high-resolution digital elevation model of the San Francisco Bay-Delta Estuary, California","interactions":[],"lastModifiedDate":"2017-06-22T16:14:38","indexId":"ofr20171067","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1067","title":"A new seamless, high-resolution digital elevation model of the San Francisco Bay-Delta Estuary, California","docAbstract":"Climate change, sea-level rise, and human development have contributed to the changing geomorphology of the San Francisco Bay - Delta (Bay-Delta) Estuary system. The need to predict scenarios of change led to the development of a new seamless, high-resolution digital elevation model (DEM) of the Bay – Delta that can be used by modelers attempting to understand potential future changes to the estuary system. This report details the three phases of the creation of this DEM. The first phase took a bathymetric-only DEM created in 2005 by the U.S. Geological Survey (USGS), refined it with additional data, and identified areas that would benefit from new surveys. The second phase began a USGS collaboration with the California Department of Water Resources (DWR) that updated a 2012 DWR seamless bathymetric/topographic DEM of the Bay-Delta with input from the USGS and modifications to fit the specific needs of USGS modelers. The third phase took the work from phase 2 and expanded the coverage area in the north to include the Yolo Bypass up to the Fremont Weir, the Sacramento River up to Knights Landing, and the American River up to the Nimbus Dam, and added back in the elevations for interior islands. The constant evolution of the Bay-Delta will require continuous updates to the DEM of the Delta, and there still are areas with older data that would benefit from modern surveys. As a result, DWR plans to continue updating the DEM.
Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
The 1959 summit eruption of Kīlauea Volcano exhibited high lava fountains of gas-rich, primitive magma, containing olivine + chromian spinel in highly vesicular brown glass. Microprobe analysis of these samples shows that euhedral rims on olivine phenocrysts, in direct contact with glass, vary significantly in forsterite (Fo) content, at constant major-element melt composition, as do unzoned groundmass olivine crystals. Ferric/total iron (Fe+ 3/FeT)ratios for matrix and interstitial glasses, plus olivine-hosted glass inclusions in eight 1959 scoria samples have been determined by micro X-ray absorption near-edge structure spectroscopy (μ-XANES). These data show that much of the variation in Fo content reflects variation in oxidation state of iron in the melt, which varies with sulfur concentration in the glass and (locally) with proximity to scoria edges in contact with air. Data for 24 olivine-melt pairs in the better-equilibrated samples from later in the eruption show KD averaging 0.280 ± 0.03 for the exchange of Fe and Mg between olivine and melt, somewhat displaced from the value of 0.30 ± 0.03 given by Roeder and Emslie (1970). This may reflect the low SiO2 content of the 1959 magmas, which is lower than that in most Kīlauea tholeiites. More broadly, we show the potential of μ-XANES and electron microprobe to revisit and refine the value of KD in natural systems.
The observed variations of Fe+ 3/FeT ratios in the glasses reflect two distinct processes. The main process, sulfur degassing, produces steady decrease of the Fe+ 3/FeT ratio. Melt inclusions in olivine are high in sulfur (1060–1500 ppm S), with Fe+ 3/FeT = 0.160–0.175. Matrix glasses are degassed (mostly S < 200 ppm) with generally lower Fe+ 3/FeT(0.114–0.135). Interstitial glasses within clumps of olivine crystals locally show intermediate levels of sulfur and Fe+ 3/FeT ratio. The correlation suggests that (1) the 1959 magma was significantly reduced by sulfur degassing during the eruption and (2) the melts originally had Fe+ 3/FeT ≥ 0.175, consistent with oxygen fugacity (fO2) at least 0.4 log units above the fayalite-magnetite-quartz (FMQ) buffer at 1 atm and magmatic temperature of 1200 °C.
The second process is interaction between the melts and atmospheric oxygen, which results in higher Fe+ 3/FeT ratios. Detailed μ-XANES traverses show gradients in Fe+ 3/FeT of 0.145 to 0.628 over distances of 100–150 μm in thin, visibly reddened matrix glass bordering some scoriae, presumably caused by contact with air. This process was extremely rapid, giving insight into how fast the Fe+ 3/FeT ratio can change in response to changes in external conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2016.12.006","usgsCitation":"Helz, R.L., Cottrell, E., Brounce, M.N., and Kelley, K.A., 2017, Olivine-melt relationships and syneruptive redox variations in the 1959 eruption of Kīlauea Volcano as revealed by XANES: Journal of Volcanology and Geothermal Research, v. 333-334, p. 1-14, https://doi.org/10.1016/j.jvolgeores.2016.12.006.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-077122","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469753,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.uri.edu/gsofacpubs/1592","text":"Publisher Index Page"},{"id":342492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3240203857422,\n 19.369454073094243\n ],\n [\n -155.2206802368164,\n 19.369454073094243\n ],\n [\n -155.2206802368164,\n 19.45364383358209\n ],\n [\n -155.3240203857422,\n 19.45364383358209\n ],\n [\n -155.3240203857422,\n 19.369454073094243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"333-334","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59424b35e4b0764e6c65dc0d","contributors":{"authors":[{"text":"Helz, Rosalind L. 0000-0003-1550-0684 rhelz@usgs.gov","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":1952,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind","email":"rhelz@usgs.gov","middleInitial":"L.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cottrell, Elizabeth","contributorId":192904,"corporation":false,"usgs":false,"family":"Cottrell","given":"Elizabeth","email":"","affiliations":[],"preferred":false,"id":698112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brounce, Maryjo N.","contributorId":192906,"corporation":false,"usgs":false,"family":"Brounce","given":"Maryjo","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":698114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelley, Katherine A.","contributorId":192905,"corporation":false,"usgs":false,"family":"Kelley","given":"Katherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":698113,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188499,"text":"70188499 - 2017 - Soils as relative-age dating tools","interactions":[],"lastModifiedDate":"2017-06-14T14:08:17","indexId":"70188499","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Soils as relative-age dating tools","docAbstract":"Soils develop at the earth's surface via multiple processes that act through time. Precluding burial or disturbance, soil genetic horizons form progressively and reflect the balance among formation processes, surface age, and original substrate composition. Soil morphology provides a key link between process and time (soil age), enabling soils to serve as both relative and numerical dating tools for geomorphic studies and landscape evolution. Five major factors define the contemporary state of all soils: climate, organisms, topography, parent material, and time. Soils developed on similar landforms and parent materials within a given landscape comprise what we term a soil/landform/substrate complex. Soils on such complexes that differ in development as a function of time represent a soil chronosequence. In a soil chronosequence, time constitutes the only independent formation factor; the other factors act through time. Time dictates the variations in soil development or properties (field or laboratory measured) on a soil/landform/substrate complex. Using a dataset within the chronosequence model, we can also formulate various soil development indices based upon one or a combination of soil properties, either for individual soil horizons or for an entire profile. When we evaluate soil data or soil indices mathematically, the resulting equation creates a chronofunction. Chronofunctions help quantify processes and mechanisms involved in soil development, and relate them mathematically to time. These rigorous kinds of comparisons among and within soil/landform complexes constitute an important tool for relative-age dating. After determining one or more absolute ages for a soil/landform complex, we can calculate quantitative soil formation, and or landform-development rates. Multiple dates for several complexes allow rate calculations for soil/landform-chronosequence development and soil-chronofunction calibration.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The International Encyclopedia of Geography","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"John Wiley & Sons, Ltd.","doi":"10.1002/9781118786352.wbieg0437","usgsCitation":"Markewich, H.W., Pavich, M.J., and Wysocki, D., 2017, Soils as relative-age dating tools, chap. of The International Encyclopedia of Geography, 14 p., https://doi.org/10.1002/9781118786352.wbieg0437.","productDescription":"14 p.","ipdsId":"IP-053464","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"59424b37e4b0764e6c65dc14","contributors":{"authors":[{"text":"Markewich, Helaine W. 0000-0001-9656-3243 helainem@usgs.gov","orcid":"https://orcid.org/0000-0001-9656-3243","contributorId":2008,"corporation":false,"usgs":true,"family":"Markewich","given":"Helaine","email":"helainem@usgs.gov","middleInitial":"W.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":698027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pavich, Milan J. mpavich@usgs.gov","contributorId":2348,"corporation":false,"usgs":true,"family":"Pavich","given":"Milan","email":"mpavich@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wysocki, Douglas A.","contributorId":61320,"corporation":false,"usgs":true,"family":"Wysocki","given":"Douglas A.","affiliations":[],"preferred":false,"id":698029,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188850,"text":"70188850 - 2017 - A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada","interactions":[],"lastModifiedDate":"2017-06-27T10:52:46","indexId":"70188850","displayToPublicDate":"2017-06-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada","docAbstract":"We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within “dry” meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in “wet” meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes.
","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0178536","usgsCitation":"Lee, S.R., Berlow, E.L., Ostoja, S., Brooks, M.L., Génin, A., Matchett, J.R., and Hart, S.C., 2017, A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada: PLoS ONE, v. 12, no. 6, p. 1-20, https://doi.org/10.1371/journal.pone.0178536.","productDescription":"20 p. 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Garnering this information from the rock record greatly benefits from integrating textural and compositional data with radiometric dating of accessory minerals. Length scales of crystal growth and diffusive transport in accessory minerals under realistic geologic conditions are typically in the range of 1–10’s of μm, and in some cases even substantially smaller, with zircon having among the lowest diffusion coefficients at a given temperature (e.g., Cherniak and Watson 2003). Intrinsic to the compartmentalization of geochemical and geochronologic information from intra-crystal domains is the requirement to determine accessory mineral compositions using techniques that sample at commensurate spatial scales so as to not convolute the geologic signals that are recorded within crystals, as may be the case with single grain or large grain fragment analysis by isotope dilution thermal ionization mass spectrometry (ID-TIMS; e.g., Schaltegger and Davies 2017, this volume; Schoene and Baxter 2017, this volume). Small crystals can also be difficult to extract by mineral separation techniques traditionally used in geochronology, which also lead to a loss of petrographic context. Secondary Ionization Mass Spectrometry, that is SIMS performed with an ion microprobe, is an analytical technique ideally suited to meet the high spatial resolution analysis requirements that are critical for petrochronology (Table 1).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reviews in Mineralogy and Geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Mineralogical Society of America","publisherLocation":"Washington, D.C.","usgsCitation":"Schmitt, A.K., and Vazquez, J.A., 2017, Secondary ionization mass spectrometry analysis in petrochronology, chap. 7 of Reviews in Mineralogy and Geochemistry, v. 83, no. 1, p. 199-230.","productDescription":"32 p.","startPage":"199","endPage":"230","ipdsId":"IP-078815","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":342430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342410,"type":{"id":15,"text":"Index Page"},"url":"https://rimg.geoscienceworld.org/content/83/1/199"}],"volume":"83","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b1e4b0764e6c63eaa8","contributors":{"authors":[{"text":"Schmitt, Axel K.","contributorId":127614,"corporation":false,"usgs":false,"family":"Schmitt","given":"Axel","email":"","middleInitial":"K.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":697889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":697888,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188485,"text":"70188485 - 2017 - The evolution of different maternal investment strategies in two closely related desert vertebrates","interactions":[],"lastModifiedDate":"2017-06-13T14:44:35","indexId":"70188485","displayToPublicDate":"2017-06-13T00:00:00","publicationYear":"2017","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":"The evolution of different maternal investment strategies in two closely related desert vertebrates","docAbstract":"We compared egg size phenotypes and tested several predictions from the optimal egg size (OES) and bet-hedging theories in two North American desert-dwelling sister tortoise taxa, Gopherus agassizii and G. morafkai, that inhabit different climate spaces: relatively unpredictable and more predictable climate spaces, respectively. Observed patterns in both species differed from the predictions of OES in several ways. Mean egg size increased with maternal body size in both species. Mean egg size was inversely related to clutch order in G. agassizii, a strategy more consistent with the within-generation hypothesis arising out of bet-hedging theory or a constraint in egg investment due to resource availability, and contrary to theories of density dependence, which posit that increasing hatchling competition from later season clutches should drive selection for larger eggs. We provide empirical evidence that one species, G. agassizii, employs a bet-hedging strategy that is a combination of two different bet-hedging hypotheses. Additionally, we found some evidence for G. morafkai employing a conservative bet-hedging strategy. (e.g., lack of intra- and interclutch variation in egg size relative to body size). Our novel adaptive hypothesis suggests the possibility that natural selection favors smaller offspring in late-season clutches because they experience a more benign environment or less energetically challenging environmental conditions (i.e., winter) than early clutch progeny, that emerge under harsher and more energetically challenging environmental conditions (i.e., summer). We also discuss alternative hypotheses of sexually antagonistic selection, which arise from the trade-offs of son versus daughter production that might have different optima depending on clutch order and variation in temperature-dependent sex determination (TSD) among clutches. Resolution of these hypotheses will require long-term data on fitness of sons versus daughters as a function of incubation environment, data as yet unavailable for any species with TSD.
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Summaries of repeat observations performed by multiple independent observers are reviewed and discussed. These summaries show variability among observers and the potential for errors being made in blister rust status. Based on this assessment, we utilized occupancy models to analyze blister rust prevalence while explicitly accounting for imperfect detection. Available covariates were used to model both the probability of a tree being infected with blister rust and the probability of an observer detecting the infection. The fitted model provided strong evidence that the probability of blister rust infection increases as tree diameter increases and decreases as site elevation increases. Most importantly, we found evidence of heterogeneity in detection probabilities related to tree size and average slope of a transect. These results suggested that detecting the presence of blister rust was more difficult in larger trees. Also, there was evidence that blister rust was easier to detect on transects located on steeper slopes.
Our model accounted for potential impacts of observer experience on blister rust detection probabilities and also showed moderate variability among the different observers in their ability to detect blister rust. Based on these model results, we suggest that multiple observer sampling continue in future field seasons in order to allow blister rust prevalence estimates to be corrected for imperfect detection. We suggest that the multiple observer effort be spread out across many transects (instead of concentrated at a few each field season) while retaining the overall proportion of trees with multiple observers around 5-20%. Estimates of prevalence are confounded with detection unless it is explicitly accounted for in an analysis and we demonstrate how an occupancy model can be used to do account for this source of observation error.
","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Wright, W.J., and Irvine, K.M., 2017, Assessment of imperfect detection of blister rust in whitebark pine within the Greater Yellowstone Ecosystem: Natural Resource Report 2017/1457, vi, 24 p.","productDescription":"vi, 24 p.","ipdsId":"IP-083274","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":342431,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342427,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2240718"}],"country":"United States","state":"idaho, Montana, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 41.918628865183045\n ],\n [\n -108.446044921875,\n 41.918628865183045\n ],\n [\n -108.446044921875,\n 45.75985868785574\n ],\n [\n -112.5,\n 45.75985868785574\n ],\n [\n -112.5,\n 41.918628865183045\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b0e4b0764e6c63ea9b","contributors":{"authors":[{"text":"Wright, Wilson J.","contributorId":192867,"corporation":false,"usgs":false,"family":"Wright","given":"Wilson","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":697959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":697958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188460,"text":"70188460 - 2017 - Predation by Acanthurus leucopareius on black-band disease in Kauai, Hawaii","interactions":[],"lastModifiedDate":"2017-07-03T09:55:55","indexId":"70188460","displayToPublicDate":"2017-06-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1106,"text":"Bulletin of Marine Science","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Predation by Acanthurus leucopareius on black-band disease in Kauai, Hawaii","title":"Predation by Acanthurus leucopareius on black-band disease in Kauai, Hawaii","docAbstract":"No abstract available.