Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data

The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.

Is there a connection between high transport of water through the Rockall Trough and ecological changes in the North Sea?

Changes in the ecosystem of the North Sea may occur as pronounced inter-annual and step-wise shifts as well as gradual trends. Marked inter-annual shifts have occurred at least twice in the last two decades, the late 1980s and the late 1990s, that appear to reflect an increased inflow of oceanic water and species. Numerical modelling has demonstrated a link between altered rates of inflow of oceanic water into the northern North Sea and a regime shift after 1988. In 1989 and 1997 oceanic species not normally found in the North Sea were observed there, suggesting pulses of oceanic water had entered the basin and triggered the subsequent ecosystem change. The oceanic water has origins mainly west of Britain in the Rockall Trough, where the long-term mean volume transport is around 3.7Sv northwards (1Sv=10 super(6)m super(3)s super(1)), but in early 1989 and early 1998 was observed to be more than twice the mean value, reaching over 7Sv. These periods of high transport coinciding with the inferred pulses of oceanic water into the North Sea suggest a connection through the continental shelf edge current. Copyright 2001 International Council for the Exploration of the Sea

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%.