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Updated: Jul 2, 2026

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
Published on: February 25, 2021
DEBtox theory and matrix population models as helpful tools in understanding the interaction between toxic
Elise Billoir1, Aloysio da Silva Ferrão-Filho, Marie Laure Delignette-Muller
1Université de Lyon, F-69000, Lyon, Université Lyon 1, CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, F-69622 Villeurbanne, France. billoir@biomserv.univ-lyon1.fr
Abstract:
Bioassays were performed to find out how field samples of the toxic cyanobacteria Microcystis aeruginosa affect Moina micrura, a cladoceran found in the tropical Jacarepagua Lagoon (Rio de Janeiro, Brazil). The DEBtox (Dynamic Energy Budget theory applied to toxicity data) approach has been proposed for use in analysing chronic toxicity tests as an alternative to calculating the usual safety parameters (NOEC, ECx). DEBtox theory deals with the energy balance between physiological processes (assimilation, maintenance, growth and reproduction), and it can be used to investigate and compare various hypotheses concerning the mechanism of action of a toxicant. Even though the DEBtox framework was designed for standard toxicity bioassays carried out with standard species (fish, daphnids), we applied the growth and reproduction models to M. micrura, by adapting the data available using a weight-length allometric relationship. Our modelling approach appeared to be very relevant at the individual level, and confirmed previous conclusions about the toxic mechanism. In our study we also wanted to assess the toxic effects at the population level, which is a more relevant endpoint in risk assessment. We therefore incorporated both lethal and sublethal toxic effects in a matrix population model used to calculate the finite rate of population change as a continuous function of the exposure concentration. Alongside this calculation, we constructed a confidence band to predict the critical exposure concentration for population health. Finally, we discuss our findings with regard to the prospects for further refining the analysis of ecotoxicological data.
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