Automatic classification of field-collected dinoflagellates by artificial neural network

Automatic taxonomic categorisation of 23 species of dinoflagellates was demonstrated using field-collected specimens. These dinoflagellates have been responsible for the majority of toxic and noxious phytoplankton blooms which have occurred in the coastal waters of the European Union in recent years and make severe impact on the aquaculture industry. The performance by human 'expert' ecologists/taxonomists in identifying these species was compared to that achieved by 2 artificial neural network classifiers (multilayer perceptron and radial basis function networks) and 2 other statistical techniques, k-Nearest Neighbour and Quadratic Discriminant Analysis. The neural network classifiers outperform the classical statistical techniques. Over extended trials, the human experts averaged 85% while the radial basis network achieved a best performance of 83%, the multilayer perceptron 66%, k-Nearest Neighbour 60%, and the Quadratic Discriminant Analysis 56%.

Columnar aerosol properties in a northeastern atlantic site (plymouth united kingdom) by means of ground based skyradiometer data during years 2000-2008.

Between 2000 and 2008, columnar optical and radiative properties were measured at the Plymouth Marine Laboratory (PML), UK (50° 21.95′N, 4° 8.85′W) using an automatic Prede POM01L sun–sky photometer. The database was analyzed for aerosol optical properties using the SKYRAD radiative inversion algorithm and calibrated using the in situ SKYIL calibration method. Retrievals include aerosol optical depth, Ångström wavelength exponent, aerosol volume distribution, refractive index and single scattering albedo. The results show that the Plymouth site is characterized by low values of aerosol optical depth with low variability (0.18 ± 0.08 at 500 nm) and a mean annual Ångström exponent of 1.03 ± 0.21. The annual mean of the single scattering albedo is 0.97, indicative of non-absorbing aerosols. The aerosol properties were classified in terms of air mass back trajectories: the area is mainly affected by Atlantic air masses and the dominant aerosol type is a mixture of maritime particles, present in low burdens with variable size. The maritime air masses were defined by annual mean values for the AOD (at 500 nm) of 0.13–0.14 and a wavelength exponent of 0.96–1.03. Episodic anthropogenic and mineral dust intrusions occasionally occur, but they are sporadic and dilute (AOD at 500 nm about 0.20). Tropical continental air masses were characterized by the highest AOD at 500 nm (0.34) and the lowest wavelength exponent (0.83), although they were the least represented in the analysis.

Validation of the detection of Alexandrium species using specific RNA probes tested in a microarray format: Calibration of signal using variability of RNA content with environmental conditions.

The dinoflagellate genus Alexandrium contains several toxin producing species and strains, which can cause major economic losses to the shell fish industry. It is therefore important to be able to detect these toxin producers and also distinguish toxic strains from some of the morphologically identical non-toxic strains. To facilitate this DNA probes to be used in a microarray format were designed in silico or developed from existing published probes. These probes targeted either the 18S or 28S ribosomal ribonucleic acid (rRNA) gene in Alexandrium tamarense Group I, Group III and Group IV, Alexandrium ostenfeldii and Alexandrium minutum. Three strains of A. tamarense Group I, A. tamarense Group III, A. minutum and two strains of A. ostenfeldii were grown at optimal conditions and transferred into new environmental conditions changing either the light intensity, salinity, temperature or nutrient concentrations, to check if any of these environmental conditions induced changes in the cellular ribonucleic acid (RNA) concentration or growth rate. The aim of this experiment was the calibration of several species-specific probes for the quantification of the toxic Alexandrium strains. Growth rates were highly variable but only elevated or lowered salinity significantly lowered growth rate for A. tamarense Group I and Group III; differences in RNA content were not significant for the majority of the treatments. Only light intensity seemed to affect significantly the RNA content in A. tamarense Group I and Group III, but this was still within the same range as for the other treatments meaning that a back calibration from RNA to cell numbers was possible. The designed probes allow the production of quantitative information for Alexandrium species for the microarray chip.