A Review of Recent Machine Learning Advances for Forecasting Harmful Algal Blooms and Shellfish Contamination

Models of Harmful Algal Blooms

Models used to study harmful algal blooms are a subset of those used to examine more general planktonic processes. Most models have been heuristic, examining the likelihood of certain processes generating a harmful algal bloom. Several models have been more closely coupled to field data and have been used to gain insights into the dynamics underlying the observations. As better physical and bio...

Molecular tools for monitoring harmful algal blooms.

The world's oceans cover 70 % of the Earth's surface, and their dominant populations, both numerically and biomasswise, belong to microscopic protists and prokaryotes. The marine phytoplanktons are major components of both groups and are, by definition, high dispersal taxa with large population sizes. Small photosynthetic organisms are responsible for the bulk of primary production in oceanic a...

Review of Harmful Algal Blooms in Scottish coastal waters

Harmful Algal Blooms and Public Health.

The five most commonly recognized Harmful Algal Bloom related illnesses include Ciguatera poisoning, Paralytic Shellfish poisoning, Neurotoxin Shellfish poisoning, Diarrheic Shellfish Poisoning and Amnesic Shellfish poisoning. Although they are each the product of different toxins, toxin assemblages or HAB precursors these clinical syndromes have much in common. Exposure occurs through the cons...

Optical Monitoring and Forecasting Systems for Harmful Algal Blooms: Possibility or Pipe Dream?

Monitoring programs for harmful algal blooms Field data will provide inputs to optically based eco­ (HABs) are currently reactive and provide little or no system models, which are fused to the observational means for advance warning. Given this, the develnetworks through data-assimilation methods. Poten­ opment of algal forecasting systems would be of tial model structure and data-assimilation ...