This project will develop models to predict how competition for light and nutrients affect phytoplankton in lakes. Algae are microscopic organisms that drift in the water columns of lakes and oceans. They form the foundation of the aquatic food web and produce approximately 50% to 85% of the world's oxygen via photosynthesis. Their population persistence is critical to ecosystem health. However, harmful algal blooms are a serious problem in some bodies of water, including Lake Erie. Blooms can be caused by the reversal of the competition between toxin-producing algae and the non-toxic diatoms. In well-mixed environments, cyanobacteria are competitively excluded by diatoms, but in poorly mixed or stratified water the toxic cyanobacteria float upwards to form surface scum and exclude diatoms. Hydrologic measures, such as altering the turbulent mixing in lakes, can solve the problem under appropriate conditions. This project will use mathematical models to understand the competition among phytoplankton and help design more effective hydrologic control strategies. Innovative mathematical analysis will be performed to quantify the effect of various environmental processes in shaping the population dynamics of phytoplankton. This project will provide research topics for PhD students and undergraduate summer projects. The undergraduate mentorship will be leveraged with the Summer Undergraduate Capstone Conference of the Mathematical Biosciences Institute at Ohio State University.
This project aims to understand the effect of environmental drivers, including spatial heterogeneity, non-uniform mixing, and light and nutrient availability, in shaping the community structure of a diverse phytoplankton population. We will develop phytoplankton population models of a single species, multiple species, and a continuous spectrum of species to address four key biological questions: (1) In eutrophic conditions nutrients are abundant, but light is limited. How does water column stratification affect the persistence of a single species? (2) Human activities have accelerated the eutrophication of many freshwater lakes and coastal ecosystems, causing harmful algal blooms to emerge. Can artificial mixing create a competitive reversal, allowing non-toxic diatoms to competitively exclude the toxic algae? (3) Phytoplankton communities are diverse and can be structured along various functional trade-offs. How do trade-offs in light acquisition affect coexistence among phytoplankton species? (4) How do nutrient dynamics influence phytoplankton competition in spatially heterogeneous environments? For two-species competing in stratified water columns, long-term dynamics will be classified by monotone dynamical systems results. A significant methodological advance of this project is the game-theoretical approach of using mutation-selection models. This approach captures the surprising diversity of the phytoplankton by grouping various phytoplankton species according to their functional traits. Finally, the effect of nutrient dynamics will be addressed in a thin-layer limit, with emphasis on the evolutionary stability of deep chlorophyll maxima. This project will further understanding of population persistence, vertical distribution, and community diversity of phytoplankton through mathematical modeling and analysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
