106 resultados para Data anonymization and sanitization


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The Last Interglacial (LIG), corresponding to Marine Isotope Stage (MIS) 5e, provides a reference of interglacial climate variability in the absence of anthropogenic forcing. Using an expanded section of the LIG gained at Integrated Ocean Drilling Program Site U1304 in the Subarctic Atlantic, we demonstrate that the early MIS 5e was marked by oceanographic conditions conducive for high diatom production and accumulation. The appearance of diatom-dominated laminated oozes ~3 k.y. after the beginning of MIS 5e at ca. 125 ka coincides with a shift to higher d30Sidiat values together with the dominance of Thalassiothrix longissima, indicative of increased nutrient availability and silicic acid utilization in surface waters. Though the Subarctic Front provided the physical conditions for high diatom production and deposition, these processes alone are insufficient to explain the high rates of siliceous productivity and the formation of diatomaceous sediments. Instead, the additional presence of an increased nutrient pool provided by Subantarctic Mode Water played the decisive role in initiating and sustaining diatom production. The high diatom productivity and the occurrence of diatomaceous sediments in the late Quaternary challenge the current hypothesis of a silica-depleted North Atlantic during the LIG.

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Methane (CH4) concentrations and CH4 stable carbon isotopic composition (d13CCH4) were investigated in the water column within Jaco Scar. It is one of several scars formed by massive slides resulting from the subduction of seamounts offshore Costa Rica, a process that can open up structural and stratigraphical pathways for migrating CH4. The release of large amounts of CH4 into the adjacent water column was discovered at the outcropping lowermost sedimentary sequence of the hanging wall in the northwest corner of Jaco Scar, where concentrations reached up to 1,500 nmol L-1. There CH4-rich fluids seeping from the sedimentary sequence stimulate both growth and activity of a dense chemosynthetic community. Additional point sources supplying CH4 at lower concentrations were identified in density layers above and below the main plume from light carbon isotope ratios. The injected CH4 is most likely a mixture of microbial and thermogenic CH4 as suggested by d13CCH4 values between -50 and -62 per mil Vienna Pee Dee Belemnite. This CH4 spreads along isopycnal surfaces throughout the whole area of the scar, and the concentrations decrease due to mixing with ocean water and microbial oxidation. The supply of CH4 appears to be persistent as repeatedly high CH4 concentrations were found within the scar over 6 years. The maximum CH4 concentration and average excess CH4 concentration at Jaco Scar indicate that CH4 seepage from scars might be as significant as seepage from other tectonic structures in the marine realm. Hence, taking into account the global abundance of scars, such structures might constitute a substantial, hitherto unconsidered contribution to natural CH4 sources at the seafloor.

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Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.

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Pteropods are a group of holoplanktonic gastropods for which global biomass distribution patterns remain poorly resolved. The aim of this study was to collect and synthesize existing pteropod (Gymnosomata, Thecosomata and Pseudothecosomata) abundance and biomass data, in order to evaluate the global distribution of pteropod carbon biomass, with a particular emphasis on its seasonal, temporal and vertical patterns. We collected 25 902 data points from several online databases and a number of scientific articles. The biomass data has been gridded onto a 360 x 180° grid, with a vertical resolution of 33 WOA depth levels. Data has been converted to NetCDF format. Data were collected between 1951-2010, with sampling depths ranging from 0-1000 m. Pteropod biomass data was either extracted directly or derived through converting abundance to biomass with pteropod specific length to weight conversions. In the Northern Hemisphere (NH) the data were distributed evenly throughout the year, whereas sampling in the Southern Hemisphere was biased towards the austral summer months. 86% of all biomass values were located in the NH, most (42%) within the latitudinal band of 30-50° N. The range of global biomass values spanned over three orders of magnitude, with a mean and median biomass concentration of 8.2 mg C l-1 (SD = 61.4) and 0.25 mg C l-1, respectively for all data points, and with a mean of 9.1 mg C l-1 (SD = 64.8) and a median of 0.25 mg C l-1 for non-zero biomass values. The highest mean and median biomass concentrations were located in the NH between 40-50° S (mean biomass: 68.8 mg C l-1 (SD = 213.4) median biomass: 2.5 mg C l-1) while, in the SH, they were within the 70-80° S latitudinal band (mean: 10.5 mg C l-1 (SD = 38.8) and median: 0.2 mg C l-1). Biomass values were lowest in the equatorial regions. A broad range of biomass concentrations was observed at all depths, with the biomass peak located in the surface layer (0-25 m) and values generally decreasing with depth. However, biomass peaks were located at different depths in different ocean basins: 0-25 m depth in the N Atlantic, 50-100 m in the Pacific, 100-200 m in the Arctic, 200-500 m in the Brazilian region and >500 m in the Indo-Pacific region. Biomass in the NH was relatively invariant over the seasonal cycle, but more seasonally variable in the SH. The collected database provides a valuable tool for modellers for the study of ecosystem processes and global biogeochemical cycles.