The aim of this project is to develop, validate and apply a versatile instrument and software package for automatised identification and quantification of biomasses in the marine microplankton. Presently, these tasks rely on laborious manual microscopy. Consequently, biological parameters are often undersampled in oceanographic studies, and biological data handling lags months behind sampling, rendering an interactive sampling strategy not feasible.
Digital image analysis will be applied to video images of planktonic micro-organisms, obtained by microscopy. Routines will be developed to facilitate discrimination, identification/classification, enumeration and sizing of organisms. Neural network computing will be utilised to enable a morphologically-based classification of objects in digitized imagery, a classification which is in accordance with the accumulated taxonomic experience rather than being an alternative to it. The versatility of the image analysis will be evaluated through an intercalibration study on circulated samples and through joint application studies. A user-interface will be developed to facilitate training and quality assurance.
This project will initialise a European network for intercalibration and validation of identification and quantification of biomasses in the marine plankton. The achievement of the goals of this project will enable faster acquisition of quantitative biomass data in the study and monitoring of marine pelagic environments, leading to an improved understanding of the structure and functions of marine pelagic ecosystems and providing a better data base for numerical modelling.
Funding SchemeCSC - Cost-sharing contracts
901 87 Umeaa