Dividing the Waters offers this groundwater science bench book that cannot be matched by any other scientific or judicial publication. Adjudicating Groundwater combines the expertise and experience of academic scientists (UC Davis/Stanford), federal scientists (U.S. Geological Survey), and judicial officers to create a resource that can fulfill the needs of judges tackling the most difficult groundwater conflicts. This bench book explains both the fundamentals of groundwater science (hydrogeology) and groundwater modeling. The bench book received peer review from scientists and judges, with oversight by the U.S. Geological Survey, making this book among the most reliable resources for judges with water cases.
","language":"English","publisher":"The National Judicial College","usgsCitation":"Harter, T., Moran, T., and Wildman, E., 2019, Adjudicating groundwater: A judge’s guide to understanding groundwater and modeling.","ipdsId":"IP-097084","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":362180,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":362145,"type":{"id":15,"text":"Index Page"},"url":"https://www.judges.org/dtw/adjudicating-groundwater/"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Brandt, Alf","contributorId":214284,"corporation":false,"usgs":false,"family":"Brandt","given":"Alf","email":"","affiliations":[],"preferred":false,"id":759544,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759545,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"White, Jeremy T. 0000-0002-4950-1469 jwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":167708,"corporation":false,"usgs":true,"family":"White","given":"Jeremy","email":"jwhite@usgs.gov","middleInitial":"T.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":759546,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Harter, Thomas","contributorId":178245,"corporation":false,"usgs":false,"family":"Harter","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":759547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Tara","contributorId":214282,"corporation":false,"usgs":false,"family":"Moran","given":"Tara","email":"","affiliations":[],"preferred":false,"id":759548,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wildman, Eric","contributorId":214283,"corporation":false,"usgs":false,"family":"Wildman","given":"Eric","email":"","affiliations":[],"preferred":false,"id":759549,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202442,"text":"70202442 - 2019 - Hillslope hydrology in global change research and earth system modeling","interactions":[],"lastModifiedDate":"2019-03-26T16:04:00","indexId":"70202442","displayToPublicDate":"2019-03-01T10:35:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hillslope hydrology in global change research and earth system modeling","docAbstract":"Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐m deep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018WR023903","usgsCitation":"Fan, Y., Clark, M., Lawrence, D.M., Swenson, S., Band, L.E., Brantley, S.L., Brooks, P.D., Dietrich, W.E., Flores, A., Grant, G., Kirchner, J.W., Mackay, D., McDonnell, J., Milly, P.C., Sullivan, P.L., Tague, C., Ajami, H., Chaney, N.W., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad-Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B.P., Nijssen, B., Safeeq, M., Shen, C., van Verseveld, W., Volk, J., and Yamazaki, D., 2019, Hillslope hydrology in global change research and earth system modeling: Water Resources Research, v. 55, no. 2, p. 1737-1772, https://doi.org/10.1029/2018WR023903.","productDescription":"36 p.","startPage":"1737","endPage":"1772","ipdsId":"IP-102674","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467856,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr023903","text":"Publisher Index Page"},{"id":361636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Ying","contributorId":213846,"corporation":false,"usgs":false,"family":"Fan","given":"Ying","email":"","affiliations":[{"id":38903,"text":"Rutgers Univ.","active":true,"usgs":false}],"preferred":false,"id":758550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn","contributorId":176319,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","affiliations":[],"preferred":false,"id":758551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, David M.","contributorId":105206,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":758552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swenson, Sean","contributorId":213847,"corporation":false,"usgs":false,"family":"Swenson","given":"Sean","email":"","affiliations":[{"id":6648,"text":"National Center for Atmospheric Research","active":true,"usgs":false}],"preferred":false,"id":758553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Band, L. 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Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across northern high‐latitude ecosystems. Here we characterize the historical sensitivity of Alaska's ecosystems to environmental change and anthropogenic disturbances using expert knowledge, remote sensing data, and spatiotemporal analyses and modeling. Time‐series analysis of moderate—and high‐resolution imagery was used to characterize land‐ and water‐surface dynamics across Alaska. Some 430,000 interpretations of ecological and geomorphological change were made using historical air photos and satellite imagery, and corroborate land‐surface greening, browning, and wetness/moisture trend parameters derived from peak‐growing season Landsat imagery acquired from 1984 to 2015. The time series of change metrics, together with climatic data and maps of landscape characteristics, were incorporated into a modeling framework for mapping and understanding of drivers of change throughout Alaska. According to our analysis, approximately 13% (~174,000 ± 8700 km2) of Alaska has experienced directional change in the last 32 years (±95% confidence intervals). At the ecoregions level, substantial increases in remotely sensed vegetation productivity were most pronounced in western and northern foothills of Alaska, which is explained by vegetation growth associated with increasing air temperatures. Significant browning trends were largely the result of recent wildfires in interior Alaska, but browning trends are also driven by increases in evaporative demand and surface‐water gains that have predominately occurred over warming permafrost landscapes. Increased rates of photosynthetic activity are associated with stabilization and recovery processes following wildfire, timber harvesting, insect damage, thermokarst, glacial retreat, and lake infilling and drainage events. Our results fill a critical gap in the understanding of historical and potential future trajectories of change in northern high‐latitude regions.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.14279","usgsCitation":"Pastick, N.J., Jorgenson, M., Goetz, S., Jones, B.M., Wylie, B.K., Minsley, B.J., Genet, H., Knight, J.F., Swanson, D.K., and Jorgenson, J.C., 2019, Spatiotemporal remote sensing of ecosystem change and causation across Alaska: Global Change Biology, v. 25, no. 3, p. 1171-1189, https://doi.org/10.1111/gcb.14279.","productDescription":"18 p.","startPage":"1171","endPage":"1189","ipdsId":"IP-096342","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":437552,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DV1J6N","text":"USGS data release","linkHelpText":"Probabilistic estimates of landscape change in Alaska (1984 to 2015)"},{"id":359597,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Heat stored in the water column in chemically stratified Antarctic lakes that have middepth temperature maxima can significantly influence the ice thickness trends via upward heat flux to the ice/water interface. We modeled the ice thickness of the west lobe of Lake Bonney, Antarctica, based on possible future climate scenarios utilizing a 1D thermodynamic model that accounts for surface radiative fluxes as well as the heat flux associated with the temperature evolution of the water column. Model results predict that the ice cover of Lake Bonney will shift from perennial to seasonal within one to four decades, a change that will drastically influence ecosystem processes within the lake.
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Comparisons of morphological characteristics and genetics were made between Trapa populations from the native region of Eurasia and Africa versus the NE US. Unpublished data suggests a new introduction of Trapa (herein referred to as Trapa sp.) has occurred in the Commonwealth of Virginia, US with unknown biology and life history. Observations of morphological and phenological characteristics of this potential new taxon of Trapa differ from those typically found with naturalized Trapa natans reported in the NE US. 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Determining the influence of site characteristics on amphibian presence and success is vital to developing effective conservation strategies. We used occupancy analysis to estimate presence of four anuran species at wetlands in northern Iowa as a function of eight environmental covariates hypothesized to affect occupancy: fish and salamander abundance, invertebrate density, aquatic vegetative cover, wetland area, atrazine concentration in water, surrounding agricultural land use, and an overall wetland health score (wetland condition index [WCI]). We surveyed 27 wetlands multiple times in 2015 and 2016. Leopard Frogs (Lithobates pipiens) and American Toads (Anaxyrus americanus) were observed at 100% of the sites, Boreal Chorus Frogs (Pseudacris maculata) at 96%, and Gray Treefrogs (Hyla spp.) at 81%. Wetland site occupancy for all species in our study ranged from 0.23 (Hyla spp. tadpoles) to 0.95 (L. pipiens adults), indicating that agricultural wetlands can provide refuge or habitat for amphibians. Fish abundance, percentage of cropland cover within 500 m of the wetland, and salamander abundance were among the variables best supported by our models although their estimated effects were weak. Wetland area, atrazine concentration, vegetative cover, and WCI also influenced occupancy probability, but for only a small number of species and life stages. The direction of predicted effects varied by species and life stage. Despite only weak evidence that the environmental factors we measured influenced anuran occupancy, our results provide insights for managers seeking to understand how amphibians use landscapes modified by agriculture.
","language":"English","publisher":"Allen Press","doi":"10.1655/HERPETOLOGICA-D-18-00013.1","usgsCitation":"Swanson, J.E., Pierce, C., Dinsmore, S., Smalling, K., Vandever, M.W., Stewart, T.W., and Muths, E., 2019, Factors influencing anuran wetland occupancy in an agricultural landscape: Herpetologica, v. 75, no. 1, p. 47-56, https://doi.org/10.1655/HERPETOLOGICA-D-18-00013.1.","productDescription":"10 p.","startPage":"47","endPage":"56","ipdsId":"IP-090725","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":395063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.339111328125,\n 42.00032514831621\n ],\n [\n -90.010986328125,\n 42.00848901572399\n ],\n [\n -90.19775390625,\n 42.26917949243506\n ],\n [\n -90.538330078125,\n 42.54498667313236\n ],\n [\n -90.560302734375,\n 42.68243539838623\n ],\n [\n -90.977783203125,\n 42.79540065303723\n ],\n [\n -91.065673828125,\n 43.13306116240612\n ],\n [\n -90.977783203125,\n 43.28520334369384\n ],\n [\n -91.175537109375,\n 43.51668853502906\n ],\n [\n -96.64672851562499,\n 43.51668853502906\n ],\n [\n -96.64672851562499,\n 43.30919109985686\n ],\n [\n -96.580810546875,\n 43.1090040242731\n ],\n [\n -96.800537109375,\n 42.76314586689492\n ],\n [\n -96.45996093749999,\n 42.45588764197166\n ],\n [\n -96.339111328125,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-01-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Swanson, Jennifer E.","contributorId":140894,"corporation":false,"usgs":false,"family":"Swanson","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":832143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dinsmore, Stephen J.","contributorId":61718,"corporation":false,"usgs":true,"family":"Dinsmore","given":"Stephen J.","affiliations":[],"preferred":false,"id":832144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smalling, Kelly L. 0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandever, Mark W. 0000-0003-0247-2629 vandeverm@usgs.gov","orcid":"https://orcid.org/0000-0003-0247-2629","contributorId":197674,"corporation":false,"usgs":true,"family":"Vandever","given":"Mark","email":"vandeverm@usgs.gov","middleInitial":"W.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":832026,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Timothy W.","contributorId":171433,"corporation":false,"usgs":false,"family":"Stewart","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":26913,"text":"Iowa State University, Ames, Iowa","active":true,"usgs":false}],"preferred":false,"id":832145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":832027,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70206132,"text":"70206132 - 2019 - Role of recovering river herring population on smallmouth bass diet and growth","interactions":[],"lastModifiedDate":"2019-10-30T06:31:02","indexId":"70206132","displayToPublicDate":"2019-03-01T09:06:53","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Role of recovering river herring population on smallmouth bass diet and growth","docAbstract":"Fish assemblages in Atlantic coastal rivers have undergone extensive ecological change in the last two and a half centuries due to human influence, including extirpation of many migratory fish species, such as river herring (Alosa spp.) and introduction of nonnative piscivores, notably Smallmouth Bass Micropterus dolomieu. Recently, dam removals and fish passage improvements in the Penobscot River, Maine, have allowed river herring to return to reaches of the river that have been inaccessible since the late 19th century. Alosine populations have increased and this trend is anticipated to continue. This may increase forage in the system which could potentially increase growth for Smallmouth Bass, the dominant piscivore. We examined the diet and growth of Smallmouth Bass collected from areas of the Penobscot River watershed with and without access to river herring as prey. We collected 765 Smallmouth Bass throughout 2015, examined the stomach contents of 573 individuals, and found notable differences in diet among three river reaches with common seasonal trends. Juvenile river herring composed an average of 19% (SE = ±6%) of stomach contents by mass from Smallmouth Bass collected in the freshwater tidal area but were rarely observed in the diets upstream. We used estimates from von Bertalanffy growth models to examine differences in growth among reaches and found that asymptotic length was the longest (425 mm TL) in the Tidal reach where access to river herring was unrestricted. We then used these data to predict changes to growth associated with increased access to juvenile river herring prey with bioenergetics models. Results indicated that substituting juvenile river herring for less energy-dense prey (e.g.,invertebrates) may lead to increases in seasonal growth throughout the watershed as river herring populations continue to rebound in response to dam removal. Our results provide insight into the diet and growth of Smallmouth Bass in a large New England river, and provide a foundation for future work investigating unfolding changes to these characteristics following recent dam removals.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Managing centrarchid fisheries in rivers and streams","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","isbn":"9781934874523","usgsCitation":"Watson, J.M., Coghlan, S.M., Zydlewski, J.D., Hayes, D.B., and Stich, D.S., 2019, Role of recovering river herring population on smallmouth bass diet and growth, chap. of Managing centrarchid fisheries in rivers and streams, 18 p.","productDescription":"18 p.","ipdsId":"IP-086810","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":368699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":368671,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/afs-symposia/54087p/"}],"country":"United States","state":"Maine","otherGeospatial":"Penobscot River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.8348388671875,\n 44.70770622183535\n ],\n [\n -68.34869384765625,\n 44.70770622183535\n ],\n [\n -68.34869384765625,\n 45.94160076422081\n ],\n [\n -68.8348388671875,\n 45.94160076422081\n ],\n [\n -68.8348388671875,\n 44.70770622183535\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Watson, Jonathan M.","contributorId":207174,"corporation":false,"usgs":false,"family":"Watson","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coghlan, Stephen M. Jr.","contributorId":169678,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","suffix":"Jr.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773993,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":773683,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Daniel B.","contributorId":16799,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":773994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stich, Daniel S.","contributorId":139212,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":12606,"text":"University of Maine, Dept of Plant, Soil, & Envir Sciences","active":true,"usgs":false}],"preferred":false,"id":773995,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203997,"text":"70203997 - 2019 - Strontium residual salt analyses (SrRSA) and geochemistry of Bakken Formation core samples from Fleckten 1-20, North Dakota","interactions":[],"lastModifiedDate":"2019-06-26T13:45:00","indexId":"70203997","displayToPublicDate":"2019-02-28T13:44:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Strontium residual salt analyses (SrRSA) and geochemistry of Bakken Formation core samples from Fleckten 1-20, North Dakota","docAbstract":"Samples of Bakken Formation core from the Fleckton 1-20 well in Ward County, North Dakota, were analyzed using the Strontium Residual Salt Analysis (SrRSA) method to assess pore-water communication among the upper, middle, and lower sections of the unit by analyzing 87Sr/86Sr in pore-water salts leached from the core. Major and trace element analyses were also conducted on bulk-rock samples and leachates (Elemental Residual Salt Analysis or ERSA). The middle part of the Bakken Formation, a calcareous and dolomitic siltstone to fine sandstone, is encased between two black shales—the upper and lower sections of the formation. These units are informal and herein named the upper, middle, and lower Bakken members. Strontium isotope measurements and concentration of some solutes in leachates indicate that pore water in the black shale of the upper Bakken member has remained isolated from pore water in the middle Bakken member except for within a few feet immediately near the contact where elemental profiles indicate diffusive mixing. The SrRSA 87Sr/86Sr values from the middle Bakken member are consistent with produced water collected from 28 wells in Montana and North Dakota. In contrast to the similarity in 87Sr/86Sr values, ratios of concentrations such as K/Rb, Ca/Sr, Ca/Mg, and Na/Cl are slightly different between the pore-water leachates and produced water values. The differences in K/Rb and Ca/Sr are probably due to selective adsorption of Rb leading to larger K/Rb ratios and minor dissolution of carbonate minerals leading to larger Ca/Sr ratios in the leachates.
","language":"English","publisher":"RMAG","doi":"10.31582/rmag.mg.56.1.5","usgsCitation":"Peterman, Z.E., Futa, K., and Oliver, T., 2019, Strontium residual salt analyses (SrRSA) and geochemistry of Bakken Formation core samples from Fleckten 1-20, North Dakota: Mountain Geologist, v. 56, no. 1, p. 5-17, https://doi.org/10.31582/rmag.mg.56.1.5.","productDescription":"13 p.","startPage":"5","endPage":"17","ipdsId":"IP-098925","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota, South Dakota","county":"Ward County","otherGeospatial":"Bakken Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.611083984375,\n 45.336701909968134\n ],\n [\n -100.107421875,\n 45.336701909968134\n ],\n [\n -100.107421875,\n 48.90083790234091\n ],\n [\n -107.611083984375,\n 48.90083790234091\n ],\n [\n -107.611083984375,\n 45.336701909968134\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peterman, Zell E. 0000-0002-5694-8082 peterman@usgs.gov","orcid":"https://orcid.org/0000-0002-5694-8082","contributorId":167699,"corporation":false,"usgs":true,"family":"Peterman","given":"Zell","email":"peterman@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Futa, Kiyoto 0000-0001-8649-7510 kfuta@usgs.gov","orcid":"https://orcid.org/0000-0001-8649-7510","contributorId":619,"corporation":false,"usgs":true,"family":"Futa","given":"Kiyoto","email":"kfuta@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oliver, Thomas","contributorId":216615,"corporation":false,"usgs":true,"family":"Oliver","given":"Thomas","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765162,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202406,"text":"70202406 - 2019 - A multidisciplinary framework to derive global river reach classifications at high spatial resolution","interactions":[],"lastModifiedDate":"2019-02-27T16:29:14","indexId":"70202406","displayToPublicDate":"2019-02-27T16:29:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"A multidisciplinary framework to derive global river reach classifications at high spatial resolution","docAbstract":"Projected climate and environmental change are expected to increase the pressure on global freshwater resources. To prepare for and cope with the related risks, stakeholders need to devise plans for sustainable management of river systems, which in turn requires the identification of management-appropriate operational units, such as groups of rivers that share similar environmental and biological characteristics. Ideally, these units are of a manageable size, and are biotically or abiotically distinguishable across a variety of river types. Here, we aim to address this need by presenting a new global river classification framework (GloRiC) to establish a common vocabulary and standardized approach to the development of globally comprehensive and integrated river classifications that can be tailored to different goals and requirements. We define the GloRiC conceptual framework based on five categories of variables: (1) hydrology; (2) physiography and climate; (3) fluvial geomorphology; (4) water chemistry; and (5) aquatic biology. We then apply the framework using hydro-environmental attributes provided by a seamless high-resolution river reach database to create initial instances of three sub-classifications (hydrologic, physio-climatic, and geomorphic) which we ultimately combine into 127 river reach types at the global scale. These supervised classifications utilize a mix of statistical analyses and expert interpretation to identify the classifier variables, the number of classes, and their thresholds. In addition, we also present an unsupervised, multivariable k-means statistical clustering of all river reaches into 30 groups. These first-of-their-kind global river reach classifications at high spatial resolution provide baseline information for a total of 35.9 million kilometers of rivers that have been assessed in this study, and are expected to be particularly useful in remote or data-poor river basins. The GloRiC framework and associated data are primarily designed for broad and rapid applicability in assessments that require stratified analyses of river ecosystem conditions at global and regional scales; smaller-scale applications could follow the same conceptual framework yet use more detailed data sources.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aad8e9","usgsCitation":"Ouellet Dallaire, C., Lehner, B., Sayre, R., and Thieme, M., 2019, A multidisciplinary framework to derive global river reach classifications at high spatial resolution: Environmental Research Letters, v. 14, no. 2, p. 1-12, https://doi.org/10.1088/1748-9326/aad8e9.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-091251","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":467864,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aad8e9","text":"Publisher Index Page"},{"id":361601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Ouellet Dallaire, Camille","contributorId":213685,"corporation":false,"usgs":false,"family":"Ouellet Dallaire","given":"Camille","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":758282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lehner, Bernhard","contributorId":213686,"corporation":false,"usgs":false,"family":"Lehner","given":"Bernhard","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":758283,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sayre, Roger 0000-0001-6703-7105 rsayre@usgs.gov","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":191629,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","email":"rsayre@usgs.gov","affiliations":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":758281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thieme, Michele","contributorId":213687,"corporation":false,"usgs":false,"family":"Thieme","given":"Michele","affiliations":[{"id":37767,"text":"World Wildlife Fund","active":true,"usgs":false}],"preferred":false,"id":758284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202401,"text":"70202401 - 2019 - A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units","interactions":[],"lastModifiedDate":"2019-10-28T09:44:47","indexId":"70202401","displayToPublicDate":"2019-02-27T15:48:01","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5621,"text":"Journal of Operational Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units","docAbstract":"A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km2 (21,818), and islands smaller than 1 km2 (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/1755876X.2018.1529714","usgsCitation":"Sayre, R., Noble, S., Hamann, S.L., Smith, R.A., Wright, D.J., Breyer, S.P., Butler, K., Van Graafeiland, K., Frye, C., Karagulle, D., Hopkins, D., Stephens, D., Kelly, K., Basher, Z., Burton, D., Cress, J., Atkins, K., Van Sistine, D.P., Friesen, B., Allee, R., Allen, T., Aniello, P., Asaad, I., Costello, M.J., Goodin, K., Harrison, P., Kavanaugh, M.T., Lillis, H., Manca, E., Muller-Karger, F.E., Nyberg, B., Parsons, R., Saarinen, J., Steiner, J., and Reed, A., 2019, A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units: Journal of Operational Oceanography, v. 12, no. suppl 2, p. s47-s56, https://doi.org/10.1080/1755876X.2018.1529714.","productDescription":"10 p.","startPage":"s47","endPage":"s56","ipdsId":"IP-097896","costCenters":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"links":[{"id":460457,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/1755876x.2018.1529714","text":"Publisher Index Page"},{"id":437558,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91ZCSGM","text":"USGS data release","linkHelpText":"Global Islands"},{"id":361594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"suppl 2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Sayre, Roger 0000-0001-6703-7105","orcid":"https://orcid.org/0000-0001-6703-7105","contributorId":213640,"corporation":false,"usgs":true,"family":"Sayre","given":"Roger","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":758208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noble, Suzanne","contributorId":213641,"corporation":false,"usgs":false,"family":"Noble","given":"Suzanne","affiliations":[],"preferred":false,"id":758209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamann, Sharon L. shamann@usgs.gov","contributorId":4059,"corporation":false,"usgs":true,"family":"Hamann","given":"Sharon","email":"shamann@usgs.gov","middleInitial":"L.","affiliations":[{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":758220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Rebecca A. 0000-0002-9823-706X rsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9823-706X","contributorId":201349,"corporation":false,"usgs":true,"family":"Smith","given":"Rebecca","email":"rsmith@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":758366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, Dawn J.","contributorId":191639,"corporation":false,"usgs":false,"family":"Wright","given":"Dawn","email":"","middleInitial":"J.","affiliations":[{"id":18946,"text":"Environmental Systems Research Institute, Inc. 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USA","interactions":[],"lastModifiedDate":"2019-02-27T12:59:07","indexId":"70202393","displayToPublicDate":"2019-02-27T12:59:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Adapting a regional water-quality model for local application: A case study for Tennessee, USA","docAbstract":"We evaluated whether SPAtially Referenced Regression On Watershed attributes (SPARROW) models calibrated for two adjacent USA regions could be applied at the local scale to support management decisions for streams in Tennessee. Nutrient-source apportionment of load is important for this local-scale application and demands careful consideration of uncertainty in the calibrated coefficients. We used Gauss-Newton regression to test the published SPARROW models for constancy of coefficient estimates between calibration sites on streams within (n = 59) versus outside (n = 327) Tennessee and concluded source apportionment was unbiased for Tennessee streams. The SPARROW models were then applied without re-calibration to predict stream loads and source apportionment for Tennessee streams and to build tools for displaying model results and evaluating source-change scenarios. This approach may inform the adaptation of other regional-scale regression models for use to address water-resource management issues in smaller-scale watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2019.01.001","usgsCitation":"Hoos, A.B., Wang, S.H., and Schwarz, G., 2019, Adapting a regional water-quality model for local application: A case study for Tennessee, USA: Environmental Modelling and Software, v. 115, p. 187-199, https://doi.org/10.1016/j.envsoft.2019.01.001.","productDescription":"13 p.","startPage":"187","endPage":"199","ipdsId":"IP-083893","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":460459,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2019.01.001","text":"Publisher Index Page"},{"id":361588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","volume":"115","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hoos, Anne B. 0000-0001-9845-7831","orcid":"https://orcid.org/0000-0001-9845-7831","contributorId":207575,"corporation":false,"usgs":true,"family":"Hoos","given":"Anne","email":"","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Sherry H.","contributorId":213620,"corporation":false,"usgs":false,"family":"Wang","given":"Sherry","email":"","middleInitial":"H.","affiliations":[{"id":38823,"text":"TDEC","active":true,"usgs":false}],"preferred":false,"id":758166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":758167,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202392,"text":"70202392 - 2019 - Geochemically distinct oil families in the onshore and offshore Santa Maria basins, California","interactions":[],"lastModifiedDate":"2019-02-27T12:56:23","indexId":"70202392","displayToPublicDate":"2019-02-27T12:56:18","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Geochemically distinct oil families in the onshore and offshore Santa Maria basins, California","docAbstract":"The purpose of this work is to identify genetic affinities among 48 crude oil samples from the onshore and offshore Santa Maria basins. A total of 21 source-related biomarker and stable carbon isotope ratios among the samples were assessed to assure that they were unaffected by secondary processes. Chemometric analysis of these data identifies six oil families with map and stratigraphic distributions that reflect organofacies variations within the Miocene Monterey Formation source rock. The data comprise a training set that was used to create a chemometric decision tree to classify newly collected oil samples. Three onshore families originated from two synclines, which may contain one or more pods of thermally mature source rock. Multiple biomarker parameters indicate that the six oil families achieved early oil window maturity in the range of 0.6%–0.7% equivalent vitrinite reflectance. The offshore oil samples consist of one family from Point Pedernales field and two families from the “B” prospect. Geochemical characteristics of these families indicate origins under differing water column and sediment oxicity and carbonate versus siliceous and detrital input in ‘carbonate,’ ‘marl,’ and ‘shale’ organofacies like those in the lower calcareous–siliceous, carbonaceous marl, and clayey–siliceous members of the Monterey Formation elsewhere in coastal California. The corresponding lithofacies and organofacies appear to be linked to the early–middle Miocene climate optimum and subsequent paleoclimatic cooling after circa 14 Ma, a systematic up-section increase in the stable carbon isotope composition of related oil samples, decreased preservation of calcium carbonate shells from planktic foraminifera and coccoliths, and increased preservation of clay-sized siliceous shells of diatoms and radiolarians. The results show that organofacies within the Monterey source rock are responsible for many of the geochemical differences between the oil families. This paleoclimate–organofacies model for crude oil from the Monterey Formation can be used to enhance future exploration efforts in many areas of coastal California.
","language":"English","publisher":"American Association of Petroleum Geology","doi":"10.1306/07111818014","usgsCitation":"Peters, K.E., Lillis, P.G., Lorenson, T., and Zumberge, J.E., 2019, Geochemically distinct oil families in the onshore and offshore Santa Maria basins, California: AAPG Bulletin, v. 103, no. 2, p. 243-271, https://doi.org/10.1306/07111818014.","productDescription":"28 p.","startPage":"243","endPage":"271","ipdsId":"IP-093274","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":361587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Maria basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121,\n 34.5\n ],\n [\n -120,\n 34.5\n ],\n [\n -120,\n 35.1667\n ],\n [\n -121,\n 35.1667\n ],\n [\n -121,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peters, Kenneth E.","contributorId":213618,"corporation":false,"usgs":false,"family":"Peters","given":"Kenneth","email":"","middleInitial":"E.","affiliations":[{"id":27162,"text":"Schlumberger","active":true,"usgs":false}],"preferred":false,"id":758162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":758163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenson, Thomas 0000-0001-7669-2873 tlorenson@usgs.gov","orcid":"https://orcid.org/0000-0001-7669-2873","contributorId":174599,"corporation":false,"usgs":true,"family":"Lorenson","given":"Thomas","email":"tlorenson@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zumberge, J. E.","contributorId":213619,"corporation":false,"usgs":false,"family":"Zumberge","given":"J.","email":"","middleInitial":"E.","affiliations":[{"id":38822,"text":"GeoMark Research LLC","active":true,"usgs":false}],"preferred":false,"id":758164,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227740,"text":"70227740 - 2019 - Communication strategies for reducing lead poisoning in wildlife and human health risks","interactions":[],"lastModifiedDate":"2022-01-28T16:20:03.256212","indexId":"70227740","displayToPublicDate":"2019-02-27T10:04:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Communication strategies for reducing lead poisoning in wildlife and human health risks","docAbstract":"Although lead poisoning in North American waterfowl has been reduced, it persists among other wildlife. To address this issue, we review lead poisoning in wildlife and threats to human health, describe the recent socio-political landscape, and develop a framework for reducing lead exposure related to hunting ammunition and fishing tackle. Despite substantial information about lead poisoning in wildlife, an explicit and strategic plan for using existing information to develop an effective communication program is lacking. Local and regional efforts encouraging hunters and anglers to voluntarily use nonlead alternatives could benefit from a nationally coordinated and strategic focus. We propose that the diffusion of innovation theory provides a useful framework for developing and implementing voluntary nonlead hunting ammunition and fishing tackle programs. Further, it can help communicators refine messages, increase efficiencies in developing communication materials, and monitor adoption of nonlead alternatives. The initial step in this process, however, is to engage stakeholders about the importance of the issue and leverage that concern as a catalyst for positive change. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.
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America\"}}]}","volume":"43","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Schulz, John H.","contributorId":44082,"corporation":false,"usgs":true,"family":"Schulz","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":832000,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilhelm Stanis, Sonja A.","contributorId":145937,"corporation":false,"usgs":false,"family":"Wilhelm Stanis","given":"Sonja","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":832001,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832002,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Christine Jie","contributorId":272563,"corporation":false,"usgs":false,"family":"Li","given":"Christine","email":"","middleInitial":"Jie","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":832147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Damon M.","contributorId":215880,"corporation":false,"usgs":false,"family":"Hall","given":"Damon","email":"","middleInitial":"M.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":832148,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70202040,"text":"ofr20191008 - 2019 - Bridge scour countermeasure assessments at select bridges in the United States, 2016–18","interactions":[],"lastModifiedDate":"2019-03-08T12:20:27","indexId":"ofr20191008","displayToPublicDate":"2019-02-27T07:11:46","publicationYear":"2019","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":"2019-1008","displayTitle":"Bridge Scour Countermeasure Assessments at Select Bridges in the United States, 2016–18","title":" Bridge scour countermeasure assessments at select bridges in the United States, 2016–18","docAbstract":"In 2009, the Federal Highway Administration published Hydraulic Engineering Circular No. 23 (HEC-23) to provide specific design and implementation guidelines for bridge scour and stream instability countermeasures. However, the effectiveness of countermeasures implemented over the past decade following those guidelines has not been evaluated. Therefore, in 2013, the U.S. Geological Survey, in cooperation with the Federal Highway Administration, began a study to assess the current condition of bridge-scour countermeasures at selected sites to evaluate their effectiveness. Bridge-scour countermeasures were assessed during 2016–2018 after additional sites were added following a similar study. Site assessments included reviewing countermeasure design plans, summarizing the peak and daily streamflow history, and assessments at each site. Each site survey included a photo log summary, field form, and topographic and bathymetric geospatial data and metadata. This report documents the study area and site-selection criteria, explains the survey methods used to evaluate the condition of countermeasures, and presents the complete documentation for each countermeasure assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191008","collaboration":"Prepared in cooperation with the Federal Highway Administration","usgsCitation":"Dudunake, T.J., Huizinga , R.J., and Fosness, R.L., 2019, Bridge scour countermeasure assessments at select bridges in the United States, 2016–18: U.S. Geological Survey Open-File Report 2019-1008, 12 p., https://doi.org/10.3133/ofr20191008.","productDescription":"Report: iv, 12 p.; Data release","numberOfPages":"20","onlineOnly":"Y","temporalStart":"2016-01-01","temporalEnd":"2018-12-31","ipdsId":"IP-085157","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":361447,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WW7G4W","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial data for bridge scour countermeasure assessments at select bridges in the United States, 2016-2018"},{"id":361446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1008/ofr20191008.pdf","text":"Report","size":"735 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1008"},{"id":361445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1008/coverthb.jpg"}],"country":"United States","state":"Connecticut, Idaho, Iowa, Missouri, Montana, New Jersey, Pennsylvania, South Carolina","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Shark attacks are a global phenomenon that attracts widespread attention and publicity, often with negative outcomes for shark populations. Despite the widespread perceptions of shark attacks, trends in human water activities and shark populations are both dynamic, resulting in variable rates of shark attacks over space and time. Understanding variable trends in shark attacks may contribute to a better understanding of risk, and a more tempered response in the wake of an attack. We found that global shark attack rates are low, yet variable across global regions and over decades. Countries with low populations were found to have the highest rates of attack, while countries with high populations (U.S.A., Australia, South Africa) tended to have overall low attack rates, but also much more interannual variability. From the 1960s to the present, those countries with the highest populations also tended to be the places where attack rates have increased. Ultimately, shark attack risk is also driven by local conditions (e.g., time of day, species present); however, a global scale understanding of attack rates helps place risk into perspective and may contribute to a more scientifically-grounded discussion of sharks, and their management and conservation.
","language":"English","publisher":"PLoS One","doi":"10.1371/journal.pone.0211049","usgsCitation":"Midway, S.R., Wagner, T., and Burgess, G., 2019, Trends in global shark attacks: PLoS ONE, v. 14, no. 2, e0211049, 13 p., https://doi.org/10.1371/journal.pone.0211049.","productDescription":"e0211049, 13 p.","ipdsId":"IP-103459","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0211049","text":"Publisher Index Page"},{"id":387457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2019-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Midway, Stephen R. 0000-0003-0162-1995","orcid":"https://orcid.org/0000-0003-0162-1995","contributorId":261377,"corporation":false,"usgs":false,"family":"Midway","given":"Stephen","email":"","middleInitial":"R.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":819939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":819938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burgess, George H.","contributorId":261378,"corporation":false,"usgs":false,"family":"Burgess","given":"George H.","affiliations":[{"id":36469,"text":"Florida Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":819940,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202376,"text":"70202376 - 2019 - Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers","interactions":[],"lastModifiedDate":"2019-02-26T15:01:06","indexId":"70202376","displayToPublicDate":"2019-02-26T15:01:02","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers","docAbstract":"Large floodplain-river ecosystems are often highly modified to provide services that society desires, yet these modifications can limit an ecosystem’s ability to adapt to changing conditions. The adaptive capacity of an ecosystem, its general resilience, is a conceptual framework for considering how a system will respond to such changes. We sought to apply aspects of three general resilience principles (diversity and redundancy, connectivity, and controlling variables) to our understanding of floodplain-river ecosystem structure and function. We demonstrate the applicability of this approach in a case study of the Upper Mississippi River System (UMRS). In doing so, we developed ten indicators that highlight important structural and functional aspects of this floodplain-river ecosystem, and likely underlie the capacity of large rivers to cope with environmental change and disturbance. We developed diversity and redundancy indicators for aquatic habitats, patterns of floodplain inundation, and fish communities. Connectivity indicators included metrics of longitudinal and lateral connections. Controlling variable indicators included deviations from historic water surface elevation fluctuations, water clarity, nutrient concentrations, and aquatic invasive species. This set of indicators provides a simple description of the adaptive capacity of four distinct reaches of the UMRS: Upper Impounded, Lower Impounded, Unimpounded Reaches of the Upper Mississippi River and the entire Illinois River. High aquatic habitat diversity and redundancy, fish functional diversity and redundancy, and water clarity, and the scarcity of invasive fish species are all factors that likely contribute to the high general resilience of the Upper Impounded Reach. However, the limited longitudinal connectivity and establishment of a minimum water level for navigation are factors that may inhibit the general resilience of this reach. In the Lower Impounded Reach, there is high within-reach variability for individual indicators such as aquatic habitat diversity, fish functional diversity and redundancy, and longitudinal and lateral connectivity. In the Unimpounded Reach, a high degree of longitudinal connectivity likely enhances its general resilience, but low aquatic habitat diversity, low lateral connectivity, and relatively high number of invasive fish species inhibit general resilience. For the Illinois River Reach, the relatively high fish functional diversity and redundancy likely contributes to its general resilience, whereas high number of invasive fish species, low water clarity, low lateral connectivity, and high range of water levels may inhibit general resilience. Indicators derived from application of concepts of general resilience provide insight into the current coping capacity of the UMRS and identify opportunities for enhancing resilience.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2019.02.002","usgsCitation":"Bouska, K.L., Houser, J.N., De Jager, N.R., Van Appledorn, M., and Rogala, J.T., 2019, Applying concepts of general resilience to large river ecosystems: A case study from the Upper Mississippi and Illinois rivers: Ecological Indicators, v. 101, p. 1094-1110, https://doi.org/10.1016/j.ecolind.2019.02.002.","productDescription":"7 p.","startPage":"1094","endPage":"1110","ipdsId":"IP-099227","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437559,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J8BBQ3","text":"USGS data release","linkHelpText":"Percentage of annual days that river stage exceeds 'open river' conditions for lock and dams on the Upper Mississippi River, 1985-2015"},{"id":361559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.31787109374999,\n 36.87962060502676\n ],\n [\n -87.51708984375,\n 36.87962060502676\n ],\n [\n -87.51708984375,\n 45.01141864227728\n ],\n [\n -93.31787109374999,\n 45.01141864227728\n ],\n [\n -93.31787109374999,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"101","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":758093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":758095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201152,"text":"sir20185127 - 2019 - Escherichia coli and microbial source tracking marker concentrations in and near a constructed wetland in Maumee Bay State Park, Oregon, Ohio, 2015–16","interactions":[],"lastModifiedDate":"2019-02-27T11:58:30","indexId":"sir20185127","displayToPublicDate":"2019-02-26T14:45:00","publicationYear":"2019","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":"2018-5127","displayTitle":"Escherichia coli and Microbial Source Tracking Marker Concentrations in and Near a Constructed Wetland in Maumee Bay State Park, Oregon, Ohio, 2015–16","title":"Escherichia coli and microbial source tracking marker concentrations in and near a constructed wetland in Maumee Bay State Park, Oregon, Ohio, 2015–16","docAbstract":"Elevated Escherichia coli (E. coli) concentrations at the Maumee Bay State Park (MBSP) Lake Erie beach have resulted in frequent recreational water-quality advisories. After the construction of a wetland along Berger Ditch in Maumee Bay State Park, Oregon, Ohio, samples were collected and analyzed for concentrations of E. coli and microbial source tracking (MST) markers. This study was done by the U.S. Geological Survey, in cooperation with the University of Toledo, to provide data that can be used to help evaluate the effects of the wetland on water quality in MBSP. From July 2015 to February 2016, 116 samples were collected from six sites. Median GenBac (general marker) and E. coli concentrations were higher in samples from Berger Ditch sites than in samples from the wetland sites. No statistically significant difference was found between median E. coli concentrations in samples collected at Berger Ditch sites upstream and downstream from the wetland. The frequency of detection of the human-associated Bacteroides MST marker (HF183) decreased from 39 percent upstream from the wetland to 22 percent downstream from the wetland; however, the HF183 median concentrations from these two groups of samples were nearly the same (2,700 to 2,800 copies per 100 milliliters from upstream to downstream). The waterfowl-associated Helicobacter MST marker (GFD) was detected in 13 percent of samples from the Berger Ditch site upstream from the wetland, although it was not detected in samples from the Berger Ditch site downstream from the wetland. The ruminant-associated MST marker, Rum2Bac, was not detected at any site during this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185127","collaboration":"Prepared in cooperation with the University of Toledo","usgsCitation":"Kephart, C.M., Brady, A.M.G., and Jackwood, R.W., 2019, Escherichia coli and microbial source tracking marker concentrations in and near a constructed wetland in Maumee Bay State Park, Oregon, Ohio, 2015–16: U.S. Geological Survey Scientific Investigations Report 2018–5127, 13 p., https://doi.org/10.3133/sir20185127.","productDescription":"v, 13 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093044","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":361498,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5127/coverthb.jpg"},{"id":361499,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5127/sir20185127.pdf","text":"Report","size":"77.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5127"}],"country":"United States","state":"Ohio","city":"Oregon","otherGeospatial":"Lake Erie, Maumee Bay State Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.387003,41.678489 ], [ -83.387003,41.689931 ], [ -83.362584,41.689931 ], [ -83.362584,41.678489 ], [ -83.387003,41.678489 ] ] ] } } ] }","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Available stopover habitats with quality foraging opportunities are essential for migrating waterbirds, including Whooping Crane (Grus americana). Several studies have evaluated habitats used by Whooping Crane for roosting throughout its migration corridor; however, habitats associated with foraging and other diurnal activities have received less attention. We used data collected from 42 Whooping Crane individuals that included 2169 diurnal use locations within 395 stopover sites evaluated during spring 2013 to fall 2015 to assess diurnal habitat selection throughout the U.S. portion of the migration corridor. We found that Whooping Crane selected wetland land-cover types (i.e., open water, riverine, and semipermanent wetlands) and lowland grasslands for diurnal activities over all other land-cover types that we evaluated, including croplands. Whooping Crane generally avoided roads, and avoidance varied based on land-cover class. There has been considerable alteration and destruction of natural wetlands and rivers that serve as roosting and foraging sites for migrating Whooping Crane. Given recent droughts and the likelihood of future landscape changes within the migration corridor, directing conservation efforts toward protecting and enhancing wetland stopover areas may prove critical for continued growth of the last remaining wild population of Whooping Crane. Future studies of this Whooping Crane population should focus on specific wetland complexes and riverine sites throughout the migration corridor to identify precise management actions that could be taken to enhance and protect these imperilled land-cover types.
","language":"English","publisher":"Avian Conservation and Ecology","doi":"10.5751/ACE-01317-140106","usgsCitation":"Baasch, D.M., Farrell, P.D., Pearse, A.T., Brandt, D.A., Caven, A.J., Harner, M.J., Wright, G.D., and Metzger, K.L., 2019, Diurnal habitat selection of migrating Whooping Crane in the Great Plains: Avian Conservation and Ecology, v. 14, no. 1, p. 1-14, https://doi.org/10.5751/ACE-01317-140106.","productDescription":"Article 6; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-099721","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467870,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-01317-140106","text":"Publisher Index Page"},{"id":361554,"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 -104.5458984375,\n 29.34387539941801\n ],\n [\n -94.482421875,\n 29.34387539941801\n ],\n [\n -94.482421875,\n 48.980216985374994\n ],\n [\n -104.5458984375,\n 48.980216985374994\n ],\n [\n -104.5458984375,\n 29.34387539941801\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baasch, David M.","contributorId":147145,"corporation":false,"usgs":false,"family":"Baasch","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16795,"text":"Headwaters Corp, Kearney, NE","active":true,"usgs":false}],"preferred":false,"id":758103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farrell, Patrick D.","contributorId":212085,"corporation":false,"usgs":false,"family":"Farrell","given":"Patrick","email":"","middleInitial":"D.","affiliations":[{"id":36320,"text":"PRRIP","active":true,"usgs":false}],"preferred":false,"id":758104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":758102,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, David A. 0000-0001-9786-307X dbrandt@usgs.gov","orcid":"https://orcid.org/0000-0001-9786-307X","contributorId":149929,"corporation":false,"usgs":true,"family":"Brandt","given":"David","email":"dbrandt@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":758105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Caven, Andrew J.","contributorId":177586,"corporation":false,"usgs":false,"family":"Caven","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":758106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harner, Mary J.","contributorId":177584,"corporation":false,"usgs":false,"family":"Harner","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":758107,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, Greg D.","contributorId":177585,"corporation":false,"usgs":false,"family":"Wright","given":"Greg","email":"","middleInitial":"D.","affiliations":[{"id":12957,"text":"Chippewa Ottawa Resource Authority","active":true,"usgs":false}],"preferred":false,"id":758108,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Metzger, Kristine L.","contributorId":147144,"corporation":false,"usgs":false,"family":"Metzger","given":"Kristine","email":"","middleInitial":"L.","affiliations":[{"id":16794,"text":"USFWS, Div of Biol Serv, Albuquerque, NM","active":true,"usgs":false}],"preferred":false,"id":758109,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70204682,"text":"70204682 - 2019 - Landscape and organismal factors affecting sagebrush-seedling transplant survival after megafire restoration","interactions":[],"lastModifiedDate":"2019-09-16T12:28:21","indexId":"70204682","displayToPublicDate":"2019-02-26T14:09:32","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape and organismal factors affecting sagebrush-seedling transplant survival after megafire restoration","docAbstract":"Larger and more frequent disturbances are motivating efforts to accelerate recovery of foundational perennial species by focusing efforts into establishing island patches to sustain keystone species and facilitate recovery of the surrounding plant community. Evaluating the variability in abiotic and biotic factors that contribute to differences in survival and establishment can provide useful insight into the relative importance of these factors. In the western United States, severe degradation of the sagebrush steppe has motivated substantial efforts to restore native perennial cover, but success has been mixed. In this study, we evaluated survival of >3000 sagebrush seedlings transplanted on 12 patches totaling of 650 ha within a 113,000 ha burn area, and related the survival to organismal and sub‐taxonomic traits, and to landscape variables. Big sagebrush has high intraspecific diversity attributed to subspecies and cytotypes identifiable through UV‐induced fluorescence, length:width of leaves, or genome size (ploidy). Of these organismal traits, survival was related only to UV fluorescence, and then only so when landscape variables were excluded from analyses. The most significant landscape variable affecting survival was soil taxonomic subgroup, with much lower survival where buried restrictive layers reduce deep water infiltration. Survival also decreased with greater slope steepness, exotic annual grass cover, and burn severity. Survival was optimal where perennial bunchgrasses comprised 8‐14% of total cover. These soil, topographic, and community condition factors revealed through monitoring of landscape‐level treatments can be used to explain the success of plantings and to strategically plan future restoration projects.","language":"English","publisher":"Wiley","doi":"10.1111/rec.12940","usgsCitation":"Davidson, B., Germino, M., Richardson, B., and Barnard, D., 2019, Landscape and organismal factors affecting sagebrush-seedling transplant survival after megafire restoration: Restoration Ecology, v. 27, no. 5, p. 1008-1020, https://doi.org/10.1111/rec.12940.","productDescription":"13 p.","startPage":"1008","endPage":"1020","ipdsId":"IP-102038","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":437560,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XMR9G9","text":"USGS data release","linkHelpText":"Survival data of transplanted sagebrush (Artemesia tridentata) seedlings in relation to vegetative, organismal, and topographic conditions after megafire"},{"id":366411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Davidson, Bill","contributorId":218014,"corporation":false,"usgs":true,"family":"Davidson","given":"Bill","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":768054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Bryce 0000-0001-9521-4367","orcid":"https://orcid.org/0000-0001-9521-4367","contributorId":195702,"corporation":false,"usgs":false,"family":"Richardson","given":"Bryce","email":"","affiliations":[],"preferred":false,"id":768056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnard, David","contributorId":218015,"corporation":false,"usgs":true,"family":"Barnard","given":"David","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":768057,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201177,"text":"sir20185145 - 2019 - Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012","interactions":[],"lastModifiedDate":"2019-02-27T11:51:29","indexId":"sir20185145","displayToPublicDate":"2019-02-26T12:06:29","publicationYear":"2019","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":"2018-5145","displayTitle":"Catchment-Level Estimates of Nitrogen and Phosphorus Agricultural Use from Commercial Fertilizer Sales for the Conterminous United States, 2012","title":"Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012","docAbstract":"Nutrient inputs from commercial agricultural fertilizer, particularly nitrogen and phosphorus, are important factors contributing to the degradation of surface-water quality and the alteration of aquatic ecosystems. Despite this importance, information about the application of fertilizer to agricultural land is not available in a consistent manner across the United States at a scale useful for regional water-quality assessment. To address this need, an approach is developed to relate commercial fertilizer sales to a set of explanatory variables using spatially referenced modeling methods. Spatially referenced modeling in this study refers to statistically relating fertilizer use, estimated from commercial fertilizer sales data, to spatially referenced data on watershed attributes. Separate models for nitrogen and phosphorus are developed to estimate elemental fertilizer use on agricultural lands for the conterminous United States at the National Hydrography Dataset Plus (NHDPlus) catchment scale for the year 2012. The approach builds on earlier efforts that use Association of American Plant Food Control Officials data on fertilizer sales to provide county-level estimates of nitrogen and phosphorus fertilizer use. The spatially referenced method improves on these efforts by allowing for varying nitrogen to phosphorus ratios at the catchment scale and expanding the set of variables used to allocate county-level sales data to the catchment scale. The models include catchment-level factors that are either primary determinants of fertilizer use, such as the acreage of different crop types, or measures reflecting the intensity of use, such as climate. Explanatory variables available only at the county scale, such as U.S. Department of Agriculture Census of Agriculture estimates of fertilizer expenditures, are included to improve the model predictions of elemental use. The nitrogen and phosphorus models explain more than 90 percent of the variation in elemental use at the state level, and the statistical approach allows for the estimation of uncertainty of predicted use in each catchment. The spatial patterns of model predictions reflect known agricultural cropping practices across the United States that transcend political boundaries, despite the county/state orientation of the fertilizer sales information. The results are expected to be useful for a variety of water-quality assessments that are intended to estimate nitrogen and phosphorus loads to streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185145","usgsCitation":"Stewart, J.S., Schwarz, G.E., Brakebill, J.W., and Preston, S.D., 2019, Catchment-level estimates of nitrogen and phosphorus agricultural use from commercial fertilizer sales for the conterminous United States, 2012: U.S. Geological Survey Scientific Investigations Report 2018–5145, 52 p., https://doi.org/10.3133/sir20185145.","productDescription":"Report: x, 52 p.; Data releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092916","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":361425,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5145/sir20185145.pdf","text":"Report","size":"54.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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U.S. Geological Survey
8505 Research Way
Middleton, Wisconsin 53562
Submerged macrophyte habitats provide significant benefits to estuarine systems. In southeast Louisiana, Myriophyllum spicatum L. (milfoil) and Ruppia maritima L. (widgeongrass) are dominant species existing across fresh to brackish areas. Though frequently co-occurring across the range of salinity and light conditions, their individual responses to changing environmental conditions from restoration, weather and climate may determine overall species distribution, and biomass abundance. We compared milfoil and widgeongrass growth (i.e., biomass increase) across a range of salinity and light, in monoculture (salinity: 0, 5, 10, 15, 20; light: high ˜ 50% ambient; low ˜ 20% ambient), and in mixture (salinity: 0, 10, 20; light: high, low). In monoculture, milfoil growth was reduced at high salinity (20) versus low salinity (0), while biomass allocation differed significantly with greater allocation to shoots under high light, compared to low light. Widgeongrass was minimally affected by salinity, with reduced stem densities at high salinity compared to low salinity. In mixture, both species under-yielded compared to monoculture with milfoil reduced with high salinity and light, and low salinity and light; widgeongrass under-yielded with low salinity and high light, and mid salinity (10) and low light. These differences in species’ responses suggest that salinity and light contribute to the distribution of milfoil and widgeongrass, with higher salinities and light favoring widgeongrass growth, and lower light possibly decreasing both species’ growth, and ultimately, distribution. With continued changes occurring and predicted from both coastal restoration and climate change, understanding drivers of habitat forming species remains critical to inform future landscapes.
This paper describes coupling field experiments with surface and groundwater modeling to investigate rangelands of SE Arizona, USA using erosion-control structures to augment shallow and deep aquifer recharge. We collected field data to describe the physical and hydrological properties before and after gabions (caged riprap) were installed in an ephemeral channel. The modular finite-difference flow model is applied to simulate the amount of increase needed to raise groundwater levels. We used the average increase in infiltration measured in the field and projected on site, assuming all infiltration becomes recharge, to estimate how many gabions would be needed to increase recharge in the larger watershed. A watershed model was then applied and calibrated with discharge and 3D terrain measurements, to simulate flow volumes. Findings were coupled to extrapolate simulations and quantify long-term impacts of riparian restoration. Projected scenarios demonstrate how erosion-control structures could impact all components of the annual water budget. Results support the potential of watershed-wide gabion installation to increase total aquifer recharge, with models portraying increased subsurface connectivity and accentuated lateral flow contributions.
","language":"English","publisher":"MDPI","doi":"10.3390/w11020381","usgsCitation":"Norman, L., Callegary, J.B., Lacher, L., Wilson, N., Fandel, C., Forbes, B.T., and Swetnam, T., 2019, Modeling riparian restoration impacts on the hydrologic cycle at the Babacomari Ranch, SE Arizona, USA: Water, v. 11, no. 2, p. 1-20, https://doi.org/10.3390/w11020381.","productDescription":"Article 381; 20 p.","startPage":"1","endPage":"20","ipdsId":"IP-090323","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":467872,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w11020381","text":"Publisher Index Page"},{"id":361505,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Babacomari Ranch","volume":"11","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":757998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Callegary, James B. 0000-0003-3604-0517 jcallega@usgs.gov","orcid":"https://orcid.org/0000-0003-3604-0517","contributorId":2171,"corporation":false,"usgs":true,"family":"Callegary","given":"James","email":"jcallega@usgs.gov","middleInitial":"B.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacher, Laurel","contributorId":213547,"corporation":false,"usgs":false,"family":"Lacher","given":"Laurel","affiliations":[{"id":38785,"text":"Lacher Hydrological Consulting, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Natalie R. 0000-0001-5145-1221","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":202534,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":758001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fandel, Chloé","contributorId":213548,"corporation":false,"usgs":false,"family":"Fandel","given":"Chloé","affiliations":[{"id":38786,"text":"University of Arizona, Hydrology and Water Resources, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Forbes, Brandon T. 0000-0003-4051-0593 bforbes@usgs.gov","orcid":"https://orcid.org/0000-0003-4051-0593","contributorId":213549,"corporation":false,"usgs":true,"family":"Forbes","given":"Brandon","email":"bforbes@usgs.gov","middleInitial":"T.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swetnam, Tyson","contributorId":213550,"corporation":false,"usgs":false,"family":"Swetnam","given":"Tyson","email":"","affiliations":[{"id":38787,"text":"University of Arizona , BIO5 Institute, Tucson, AZ 85719","active":true,"usgs":false}],"preferred":false,"id":758004,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202357,"text":"70202357 - 2019 - Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","interactions":[],"lastModifiedDate":"2019-06-18T10:22:04","indexId":"70202357","displayToPublicDate":"2019-02-25T13:41:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","title":"Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation","docAbstract":"In many important coastal habitats, a combination of increasing soil salinization due to sea level rise, reduced precipitation and storm surges may induce regime shift from salinity-intolerant glycophytic vegetation to salinity-tolerant halophytic species. Early detection of regime shift due to salinity stress in vegetation may facilitate conservation efforts. It has been shown that the 18O value of water in the xylem of trees can be used as a surrogate for salinity in the rooting zone of plants. Coupling measured δ18O values in the tree xylem with simulated δ18O values in trees and salinity in the vadose zone can be used to investigate competitive responses of glycophytic versus halophytic trees. MANTRA-O18 simulations suggest that the impacts of salinization on diminishing the resilience of salinity-intolerant trees can be detected up to 25 years before the glycophytic trees are threatened with regime shift to halophytic species. This early detection provides critical lead time and valuable information and insights useful for planning adaptation strategy to mitigate against the adverse impacts of sea level rise and climate change.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-019-01930-3","usgsCitation":"Teh, S.Y., Koh, H.L., DeAngelis, D.L., Voss, C.I., and da Silveira Lobo Sternberg, L., 2019, Modeling δ18O as an early indicator of regime shift arising from salinity stress in coastal vegetation: Hydrogeology Journal, v. 27, no. 4, p. 1257-1276, https://doi.org/10.1007/s10040-019-01930-3.","productDescription":"10 p.","startPage":"1257","endPage":"1276","ipdsId":"IP-095257","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":361502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"4","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Teh, Su Yean","contributorId":202650,"corporation":false,"usgs":false,"family":"Teh","given":"Su","email":"","middleInitial":"Yean","affiliations":[{"id":36510,"text":"School of Mathematicla Sciences, Universiti Sains Malaysia","active":true,"usgs":false}],"preferred":false,"id":757975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koh, Hock Lye","contributorId":202651,"corporation":false,"usgs":false,"family":"Koh","given":"Hock","email":"","middleInitial":"Lye","affiliations":[{"id":36511,"text":"Sunway University Business School, Jalan Universiti, Malaysia","active":true,"usgs":false}],"preferred":false,"id":757976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":757974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":757977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"da Silveira Lobo Sternberg, Leonel","contributorId":206740,"corporation":false,"usgs":false,"family":"da Silveira Lobo Sternberg","given":"Leonel","email":"","affiliations":[{"id":13532,"text":"Department of Biology, University of Miami","active":true,"usgs":false}],"preferred":false,"id":757978,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}