Collaborative Proposal: Intraspecific Trait Variation in Phytoplankton at Different Scales

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Tiny microscopic organisms called phytoplankton form the base of lake food webs. Phytoplankton determine the health of lake ecosystems, from harmful blooms reducing water quality to fish productivity. They adapt to the conditions they live in but are sensitive to changes in the environment, including nutrients, light, temperature, and grazers. If phytoplankton species have many types with different responses to the environment, then they are more likely to successfully adapt to novel conditions. To understand how phytoplankton may respond to future lake environments, such as warmer and more nutrient-rich conditions, we need to understand how diverse phytoplankton are and what drives that diversity. This project will characterize the diversity of phytoplankton responses, both within and across species, to key factors that determine phytoplankton growth. The researchers will also use mathematical models to develop a new theory of what drives the diversity within and among species and test it with the empirical data. The results will enable better predictions of how lakes will respond to changing environments. Graduate students and postdoctoral associates will be trained in multiple scientific approaches such as lake sampling, laboratory experiments, genomic analyses and mathematical modeling. Project results will be incorporated into K-12 teaching, including data exercises for rural schools in Michigan and teacher workshops that provide Professional Development Credit in evolution at the Texas Memorial Museum. This project will advance our knowledge of intraspecific trait variation in ecologically important microbes, phytoplankton, and provide insights into how trait diversity is generated and maintained, both within and among species. It will use an integrated approach combining the development of a theoretical framework for predicting intraspecific trait variation at different scales and tests of this theory though experimental trait determination and measurements of genetic relatedness among numerous phytoplankton strains isolated from different lakes. The eco-evolutionary framework will embed quantitative genetics approaches in a spatial metacommunity setting. To test the specific predictions from this framework for how intraspecific trait distributions depend on selection regime and other factors, the researchers will determine the degree of intraspecific variation (mean and variance) in key functional traits for several species of phytoplankton from major taxonomic groups in Michigan lakes of contrasting resource levels and grazing pressure, creating a gradient of selection regimes. The traits include resource utilization traits (phosphorus, nitrogen and light), temperature response traits, and cell size, often considered a proxy for grazer resistance. Looking at several traits simultaneously, the project will be able to explore pairwise and higher dimensional trade-offs within species, which has not previously been done for phytoplankton, and compare them to interspecific trade-offs. Additionally, the eco-evolutionary models developed to predict intraspecific variation in multidimensional trait space at different spatial scales should be relevant for other organisms.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.