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

将通过藻类生长动力学的关键方面进行研究，以突出光合作用培养的生物量生产力的控制参数。微藻生长与营养物质或光照资源之间的相互作用随时间和空间而变化，在一定条件下，可能会导致有害藻华(HAB)等不稳定情况。技术进步扩大了我们观察和可视化分水岭的能力，不仅为探测水华提供了前所未有的机会，也为触发水华发生、发展、扩散和最终死亡的物理、化学和生物因素提供了前所未有的机会。然而，尽管这些能力迅速扩大，但由于与这些复杂现象相关的时空尺度范围很广，微藻模式在分析和预防方面将继续抽样不足。因此，我们必须依靠数学模型来帮助解释我们的观察结果。这类模型可以采取多种形式，从概念框架到简单的分析公式和可以吸收数据的复杂的数值模型。这项提议旨在为微藻在其繁殖过程中作为光、气候因素和营养资源的函数的时空行为提供独特的预测情景。 围绕完全集成的建模框架的概念，该研究计划将通过三个相互衔接的主题来发展：1)自然界大尺度的藻类动态；2)实验室尺度的藻类行为；3)藻类研究在复杂的水监测和分配系统中的应用。这些将基于相互作用的方法，通过实验和现场测量以及数学模型来开发两个数据集，然后使用这些数据集来相互验证。 这项研究将通过观察藻类在不同营养水平下的集体行为、在各种情况下的水吸收和光照强度、温度变化以及主要由细菌活动调节的营养循环来促进对藻类生长动力学的了解。长期的建模目标是制定更定量的模型，并与数据进行严格的比较；开发数据同化技术，以提高模型的预测能力；并将模型开发与实地和抽样设计联系起来。 建模的结果将为使用水处理技术的利益攸关方提供清晰的解释。它们还将使人们能够建立HAB问题的风险水平警报系统，这种问题在加拿大许多工业和农业省份以及世界各国都很常见。

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.