17 resultados para 336-U1382A
em Plymouth Marine Science Electronic Archive (PlyMSEA)
Resumo:
Notes on: Virgularia mirabilis and Coryphella smaragdina
Resumo:
The Continuous Plankton Recorder (CPR) survey provides a unique multi- decadal dataset on the abundance of plankton in the North Sea and North Atlantic and is one of only a few monitoring programmes operating at a large spatio- temporal scale. The results of all samples analysed from the survey since 1946 are stored on an Access Database at the Sir Alister Hardy Foundation for Ocean Science (SAHFOS) in Plymouth. The database is large, containing more than two million records (~80 million data points, if zero results are added) for more than 450 taxonomic entities. An open data policy is operated by SAHFOS. However, the data are not on-line and so access by scientists and others wishing to use the results is not interactive. Requests for data are dealt with by the Database Manager. To facilitate access to the data from the North Sea, which is an area of high research interest, a selected set of data for key phytoplankton and zooplankton species has been processed in a form that makes them readily available on CD for research and other applications. A set of MATLAB tools has been developed to provide an interpolated spatio-temporal description of plankton sampled by the CPR in the North Sea, as well as easy and fast access to users in the form of a browser. Using geostatistical techniques, plankton abundance values have been interpolated on a regular grid covering the North Sea. The grid is established on centres of 1 degree longitude x 0.5 degree latitude (~32 x 30 nautical miles). Based on a monthly temporal resolution over a fifty-year period (1948-1997), 600 distribution maps have been produced for 54 zooplankton species, and 480 distribution maps for 57 phytoplankton species over the shorter period 1958-1997. The gridded database has been developed in a user-friendly form and incorporates, as a package on a CD, a set of options for visualisation and interpretation, including the facility to plot maps for selected species by month, year, groups of months or years, long-term means or as time series and contour plots. This study constitutes the first application of an easily accessed and interactive gridded database of plankton abundance in the North Sea. As a further development the MATLAB browser is being converted to a user- friendly Windows-compatible format (WinCPR) for release on CD and via the Web in 2003.
Resumo:
A sensitive method using Competitive Ligand Exchange-Adsorptive Cathodic Stripping Voltammetry (CLE-ACSV) has been developed to determine for the first time iron (Fe) organic speciation in rainwater over the typical natural range of pH. We have adapted techniques previously developed in other natural waters to rainwater samples, using the competing ligand 1-nitroso-2-naphthol (NN). The blank was equal to 0.17 ± 0.05 nM (n = 14) and the detection limit (DL) for labile Fe was 0.15 nM which is 10–70 times lower than that of previously published methods. The conditional stability constant for NN under rainwater conditions was calibrated over the pH range 5.52–6.20 through competition with ethylenediaminetetraacetic acid (EDTA). The calculated value of the logarithm of β′Fe3+3(NN)β′Fe3+(NN)3 increased linearly with increasing pH according to log β′Fe3+3(NN)=2.4±0.6×pH+11.9±3.5log β′Fe3+(NN)3=2.4±0.6×pH+11.9±3.5 (salinity = 2.9, T = 20 °C). The validation of the method was carried out using desferrioxamine mesylate B (DFOB) as a natural model ligand for Fe. Adequate detection windows were defined to detect this class of ligands in rainwater with 40 μM of NN from pH 5.52 to 6.20. The concentration of Fe-complexing natural ligands was determined for the first time in three unfiltered and one filtered rainwater samples. Organic Fe-complexing ligand concentrations varied from 104.2 ± 4.1 nM equivalent of Fe(III) to 336.2 ± 19.0 nM equivalent of Fe(III) and the logarithm of the conditional stability constants, with respect to Fe3+, varied from 21.1 ± 0.2 to 22.8 ± 0.3. This method will provide important data for improving our understanding of the role of wet deposition in the biogeochemical cycling of iron.