Early Detection and Mitigation Techniques for P. Bahamense- caused Harmful Algal Blooms as tested in a Computational Framework

Abstract

The dinoflagellate Pyrodinium bahamense var. compressum is the major causative organism of harmful algal bloom (HABs), colloquially known as red tides, in Manila Bay and other bodies of water in the Philippines. Early detection of P.Bahamense-caused blooms is of primary interest as it would enable the implementation of measures that would minimize economic losses and in worse cases, casualties. Mitigation procedures and techniques, on the other hand, may prevent or decrease the intensity of upcoming blooms. Using a population-level computational model for P.Bahamense, theoretical bloom-causing scenarios are tested, with the population trending compared with that of the population patterns observed in normal or non-bloom scenarios. Knowledge in population trending could potentially confer predictive and forecasting capabilities to marine scientists. Mitigation techniques, both those already being applied and still being proposed, are also tested in silico, with their theoretical efficacies compared to each other, and to actual field data.

*accepted for poster presentation for the 3rd ASEAN Civil and Engineering Conference