Statistical Mechanics Modeling of Critical Phenomena in Phytoplankton Living in a Cold Environment

Phytoplankton are a critical component of Earth's carbon cycle and thus play an important role in the climate system. Recent observations have shown that climate change can be a leading factor influencing ecosystem behavior. One specific example where environmental conditions may be related to the dynamics of the plankton ecosystem is an unusual massive phytoplankton bloom that was observed underneath the ice pack in the Arctic Ocean.

During the Arctic melt season, the sea ice surface undergoes a remarkable transformation to a complex mosaic of melt ponds, snow and ice. The transition in pond fractal geometry revolves around a critical length scale of about 100 square meters in area, as isolated ponds grow and coalesce into larger connected structures with complex, self-similar boundaries.

Moreover, the transition from isolated sunlight penetration associated with individual ponds to a continuous matrix of light associated with large connected pond configurations could help trigger the under-ice blooms and influence biological productivity and bio-geochemical processes. This work will shed light on key concerns such as ecosystem transformations under changing conditions of solar radiation; the melting process and the dynamics of living matter; energy balance in the Arctic climate system; and, the contribution of phytoplankton in the Arctic to climate feedbacks.

The PI will explore how conceptual physical models arising in statistical mechanics can be used to efficiently characterize and quantify Arctic phytoplankton under nonlinear dynamics. In outreach efforts, the PI will convey to the general public the importance of rigorous and fundamental approaches to climate and ecosystem research. The PI will prepare illustrative material (scientific infographics) about this research that will explain a strong interdisciplinary approach to this problem.

The scientific infographics will be made freely downloadable by the general public and educators from a project webpage. The fundamental concepts of ecosystem modeling will be used in a teaching context in computational and statistical physics classes. A board game based on these principles will be created and tested in local K-12 schools.

This research will also provide funding for an undergraduate and PhD student, providing valuable experience in theoretical applications within the broad framework of interdisciplinary research. The PI will involve undergraduate students who are participating in the summer research program of the University of Dayton for minority-serving institutions to participate in this project, which will enable them to gain skills in modeling and teamwork.

This project will offer the universality of statistical mechanics models for making robust, quantitative predictions about critical transitions in phytoplankton populations where the full complexity of local dynamics could never be modeled explicitly. The project will reveal some universal links between recent environmental changes and complex behavior of phytoplankton communities and increase our knowledge of phytoplankton ecosystems, including bloom development.

The methods and physical interpretation of living matter-climate interaction discovered in this research will also be applicable to future studies of possible organisms in polar regions of the Earth and "extraterrestrial oceans" beneath icy surfaces. This project synthesizes available remote sensing and fieldwork data in an innovative quantitative framework to improve description of phytoplankton dynamics.

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.