Microalgae growth dynamics and physical-biochemical coupled effects versus aquatic biomass productivity

Research will be carried out through key aspects of algae growth dynamics in order to highlight the controlling parameters for biomass productivity of photosynthetic cultures. The interactions between microalgae growth and nutrients or light resources vary with time and space, and under certain conditions, can lead to unstable situations such as harmful algal blooms (HAB). Technological advances have expanded our capabilities for observing and visualizing the watershed, providing unprecedented opportunities not only for the detection of blooms, but also for the physical, chemical, and biological factors that trigger their onset, development, proliferation, and ultimate demise. However, despite these rapidly expanding capabilities, microalgae patterns will continue to be undersampled for the analyses and preventing perspective, because of the wide range of spatial-temporal scales relevant to these complex phenomena. Therefore, we must rely on mathematical models to help interpret our observations. Such models can take many forms, ranging from conceptual frameworks, to simple analytic formulation and complex numerical models that can assimilate data. This proposal aims to provide unique predictive scenarios for the spatial-temporal behavior of microalgae within their reproduction processes as a function of light, climate factors and nutrient resources. Focusing on the conception of a fully integrated modelling framework, the research program will be developed through three cohesive themes: 1) algae dynamics in large scale of the nature; 2) algae behaviours at laboratory scale; 3) applications of algae studies within the complex water monitoring and distribution system. These will be based on the reciprocal approach to develop both the datasets through both experimental and field measurements and mathematical models, and then use these to validate each other. The research will advance the knowledge on algae growth dynamics under different nutrient levels by looking at their collective behaviour, under various scenarios of water absorption and light intensity, temperature variations and nutrient recycling which is mediated primarily by bacterial activity. The long term modelling goal is to formulate models more quantitative and which critically compare to data; to develop data assimilation techniques to improve the predictive power of models; and to connect model development to the field and sampling design. Results from the modelling will bring a clear explanation to stakeholders using water treatment techniques. They will also enable to setup the alarm system for risk levels for HAB problems which are common in many industrial and agricultural provinces of Canada, and countries around the world.