Context Algal blooms, massive developments of algae and cyanobacteria floating on the surface of waters, have been an increasing phenomenon in the freshwaters of the world over the last decade. These blooms, in particular the ones dominated by cyanobacteria, present potential major risks for human and animal health and interfere negatively with the uses of surface waters (drinking water, recreation, irrigation, pisciculture,). B-BLOOMS studies this phenomenon in Belgian waters and will make it possible to obtain the scientific data for the establishment of predictive models for the long-term, in order to help authorities take decisions and implement the European directives concerning drinking and bathing waters. Project description Objectives To document the extent, nature (diversity of organisms and toxins) and phenology of toxic blooms in Belgium. This data will be integrated into a database. To contribute to the development of predictive models based on the monitoring of ecological conditions leading to the formation of blooms. To develop the tools (sampling protocols, models, molecular markers) necessary to create a national monitoring network, and to allow the rapid detection and identification of blooms. Methodology Monitoring of reference lakes (FUNDP, UGent) Regular sampling and determination of classical physical and chemical parameters of the Lac de líEau díHeure (FUNDP) and Blaarmeersen (UGent). Analysis of samples (ULg, FUNDP, UGent) Analysis of pigments by HPLC with ëphotodiode arrayí and use of the software CHEMTAX (FUNDP, UGent) Microscopic observations and construction of a digital image database of the cyanobacterial taxa (ULg, FUNDP, UGent) Isolation and cultivation of cyanobacterial strains from blooms (ULg) Identification and measurements by assays and HPLC of cyanotoxins (CRITT-Bioindustries, subcontractor ULg) Analysis of genotypic diversity of cyanobacteria from blooms (ULg, UGent) on the basis of ribosomal DNA sequences, using DGGE (Denaturing Gradient Gel Electrophoresis) and clone libraries Analysis of the molecular diversity of cyanotoxin genes and detection by PCR (Polymerase Chain Reaction) (ULg) Database, network and website (ULg, FUNDP, UGent) Creation of a national network of bloom observers and samplers BLOOMNET; ULg, FUNDP, UGent) Design and creation of a database using Microsoft ACCESS (BLOOMBASE; FUNDP) Design and creation of a website giving access to the data of BLOOMBASE and the information from BLOOMNET (BLOOMWEB) Modeling (BLOOMODEL; FUNDP) Construction of an ANN (Artificial Neural Network) model to identify and predict blooms (BLOOMODEL) Coupling of BLOOMODEL with watershed models for the Lac de líEau díHeure