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%.

A comparison of two zooplankton time series data collected in the Gulf of Maine

Interannual and seasonal trends of zooplankton abundance and species composition were compared between the Bongo net and Continuous Plankton Recorder (CPR) time series in the Gulf of Maine. Data from 5799 Bongo and 3118 CPR samples were compared from the years 1978–2006. The two programs use different sampling methods, with the Bongo time series composed of bimonthly vertically integrated samples from locations throughout the region, while the CPR was towed monthly at 10 m depth on a transect that bisects the region. It was found that there was a significant correlation between the interannual (r = 0.67, P < 0.01) and seasonal (r = 0.95, P < 0.01) variability of total zooplankton counts. Abundance rankings of individual taxa were highly correlated and temporal trends of dominant copepods were similar between samplers. Multivariate analysis also showed that both time series equally detected major shifts in community structure through time. However, absolute abundance levels were higher in the Bongo and temporal patterns for many of the less abundant taxa groups were not similar between the two devices. The different mesh sizes of the samplers probably caused some of the discrepancies; but diel migration patterns, damage to soft bodied animals and avoidance of the small CPR aperture by some taxa likely contributed to the catch differences between the two devices. Nonetheless, Bongo data presented here confirm the previously published patterns found in the CPR data set, and both show that the abundance increase of the 1990s has been followed by average to below average levels from 2002 to 06.