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%.

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.

Prioritization of knowledge needs for sustainable aquaculture: a national and global perspective

Aquaculture is currently the fastest expanding global animal food production sector and is a key future contributor to food security. An increase in food security will be dependent upon the development and improvement of sustainable practices. A prioritization exercise was undertaken, focusing on the future knowledge needs to underpin UK sustainable aquaculture (both domestic and imported products) using a ‘task force’ group of 36 ‘practitioners’ and 12 ‘research scientists’ who have an active interest in sustainable aquaculture. A long list of 264 knowledge needs related to sustainable aquaculture was developed in conjunction with the task force. The long list was further refined through a three stage process of voting and scoring, including discussions of each knowledge need. The top 25 knowledge needs are presented, as scored separately by ‘practitioners’ or ‘research scientists’. There was similar agreement in priorities identified by these two groups. The priority knowledge needs will provide guidance to structure ongoing work to make science accessible to practitioners and help to prioritize future science policy needs and funding. The process of knowledge exchange, and the mechanisms by which this can be achieved, effectively emerged as the top priority for sustainable aquaculture. Viable alternatives to wild fish-based aquaculture feeds, resource constraints that will potentially limit expansion of aquaculture, sustainable offshore aquaculture and the treatment of sea lice also emerged as strong priorities. Although the exercise was focused on UK needs for sustainable aquaculture, many of the emergent issues are considered to have global application.