988 resultados para Global Start-ups


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In this study we present a global distribution pattern and budget of the minimum flux of particulate organic carbon to the sea floor (J POC alpha). The estimations are based on regionally specific correlations between the diffusive oxygen flux across the sediment-water interface, the total organic carbon content in surface sediments, and the oxygen concentration in bottom waters. For this, we modified the principal equation of Cai and Reimers [1995] as a basic monod reaction rate, applied within 11 regions where in situ measurements of diffusive oxygen uptake exist. By application of the resulting transfer functions to other regions with similar sedimentary conditions and areal interpolation, we calculated a minimum global budget of particulate organic carbon that actually reaches the sea floor of ~0.5 GtC yr**-1 (>1000 m water depth (wd)), whereas approximately 0.002-0.12 GtC yr**-1 is buried in the sediments (0.01-0.4% of surface primary production). Despite the fact that our global budget is in good agreement with previous studies, we found conspicuous differences among the distribution patterns of primary production, calculations based on particle trap collections of the POC flux, and J POC alpha of this study. These deviations, especially located at the southeastern and southwestern Atlantic Ocean, the Greenland and Norwegian Sea and the entire equatorial Pacific Ocean, strongly indicate a considerable influence of lateral particle transport on the vertical link between surface waters and underlying sediments. This observation is supported by sediment trap data. Furthermore, local differences in the availability and quality of the organic matter as well as different transport mechanisms through the water column are discussed.

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs Gamma-A nifH genes abundance, computed from a collection of source data sets.

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.

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Phytoplankton cell size is important to biogeochemical and food web processes. The goal of this study is to estimate phytoplankton cell size distribution from satellite imagery of spectral remote sensing reflectance (Rrs(lambda)). Previous studies have indicated phytoplankton size classes have distinctive absorption spectra despite the physiological and taxonomic variability within an assemblage. For this study, the chlorophyll specific absorption spectra for phytoplankton size class extremes, pico- and microphytoplankton, are weighted by the percent microplankton (Sfm) and are the basis of phytoplankton size retrieval from SeaWiFS imagery. Satellite retrievals of Sfm are done through implementation of a forward optical model look-up table (LUT) that incorporates the range of absorption and scattering variability due to phytoplankton size, chlorophyll concentration ([Chl]) and dissolved and detrital matter (acdm(443)) in the global ocean from which Rrs(lambda) is calculated by the radiative transfer software, Hydrolight. The Hydrolight modeled Rrs(lambda) options for a given combination of [Chl] and acdm(443) within the LUT vary only due to Sfm. For a given pixel, the LUT search space was limited by satellite imagery of [Chl] and acdm(443). Within the narrowed search space, SeaWiFS Rrs(lambda) was matched with the closest LUT Rrs(lambda) option and the associated Sfm was assigned. Thresholds at which changes in Rrs(lambda) due to Sfm could be discerned were established in terms of [Chl] and acdm(443). In situ high-precision liquid chromatography-derived estimates of cell size are used in conjunction with matched daily satellite estimates of Sfm for validation and agree well. A single month is displayed as an example of the Sfm retrieval.

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The present data set is a worldwide compilation from 11 oceanographic expeditions during which an underwater vision profiler (UVP) was deployed in situ to determine the vertical distribution (biomass) of 4 taxonomic groups of plankton larger than 600 µm, belonging to the Infrakingdom Rhizaria, including Collodaria, Acantharia, Phaeodaria and other Rhizaria. Vertical distributions are binned in four layers: 0-100, 0-200, 100-500 and 0-500 m.

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The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs nitrogen fixation rates, computed from a collection of source data sets.

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Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the (15)N:(14)N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in (15)N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8°C, soil δ(15)N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil δ(15)N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.

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In this work, the volatile chromatographic profiles of roasted Arabica coffees, previously analyzed for their sensorial attributes, were explored by principal component analysis. The volatile extraction technique used was the solid phase microextraction. The correlation optimized warping algorithm was used to align the gas chromatographic profiles. Fifty four compounds were found to be related to the sensorial attributes investigated. The volatiles pyrrole, 1-methyl-pyrrole, cyclopentanone, dihydro-2-methyl-3-furanone, furfural, 2-ethyl-5-methyl-pyrazine, 2-etenyl-n-methyl-pyrazine, 5-methyl-2-propionyl-furan compounds were important for the differentiation of coffee beverage according to the flavour, cleanliness and overall quality. Two figures of merit, sensitivity and specificity (or selectivity), were used to interpret the sensory attributes studied.