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%.

Population-Dynamics And Production Of Euphausiids .2. Thysanoessa-Inermis And Thysanoessa-Raschi In The North-Sea And American Coastal Waters

Results from the Continuous Plankton Recorder (CPR) survey for 1966 and 1967 are used to describe seasonal changes in abundance, size and aspects of the population structure of Thysanoessa inermis (Krøyer) and T. raschi (M. Sars) at a depth of 10 m in the North Sea and in American coastal waters from the Grand Banks to the Gulf of Maine. Production and dry weight were estimated from these data. Two year-groups were usually present in the breeding population, the proportion surviving into a second year being higher in American waters than in the North Sea. Annual production for each species was within the range 0.69 to 4.66 mg m-3 and the ratio between production and biomass (P:B) was between 1.3 and 4.2; values outside these ranges were obtained only for American coastal waters in 1967, when the frequency of sampling was low.