NSF abstract:
Photosynthetic microbes (phytoplankton) are vitally important for maintaining a habitable planet. These tiny organisms contribute approximately half of global photosynthesis, and form the base of the marine food web -- thereby supporting global fisheries and other marine ecosystem services. Understanding how these essential microbes will evolve as the oceans change is essential for predicting future shifts in marine ecosystem dynamics, global carbon cycling and climate. However, we still lack fundamental knowledge about how phytoplankton may adapt to future environmental changes. In addition, the representation of phytoplankton evolution has not yet been explicitly included in global climate models. As a result, our predictions of future carbon cycling and climate-feedbacks do not include this important mechanism (evolution) that will alter marine ecosystem dynamics. This project is developing and testing new hypotheses related to phytoplankton adaptation using a new framework that combines evolutionary theory with ecological and physical ocean models. This project investigates how phytoplankton community dynamics will be altered by adaptation in a changing ocean and the implications of these changes on ocean carbon cycling. In this age of big data, it is imperative that we provide our students with a deeper, more rigorous foundation in data analysis and experience with computational tools. This project is generating a set of computational modules aimed at increasing the quantitative curriculum provided to environmental studies students at both the undergraduate and K-12 level. This curriculum is being broadly distributed using online platforms with particular focus on providing access and training to Minority Serving Institutions. A key aim of this project is to increase quantitative curriculum for under-represented groups with the ultimate goal of increasing representation in STEM fields.
This project is providing new insights into phytoplankton trait adaptation in a dynamic environment by combining an evolutionary model of trait adaptation with a mechanistic, trait-based quota model for phytoplankton dynamics. By explicitly validating the model with physiology data from published experimental evolution studies and then applying the model to realistic environmental fluctuations (temperature, light and nutrient limitation) from a global circulation model, this study is scaling-up the impact of phytoplankton adaptation to the global scale. Specifically, this project is generating new hypotheses about the types of trait changes that might result from adaptation under multi-stressor selective pressure, constraining the relevant timescales for marine phytoplankton adaptation, and creating new understanding of the implications of phytoplankton adaptation for carbon cycling and ecosystem dynamics. The project is creating a novel framework for understanding the complex multi-dimensional problem of phytoplankton trait adaptation to multi-stressors and new understanding of how carbon cycling might change in the future.
Principal Investigator: Naomi M. Levine
University of Southern California (USC)
DMP_OCE-2044852_Levine.pdf (174.21 KB)
02/03/2021