Awardee: Nikita Burger
Bio:
Nikita Burger is an undergraduate student pursuing a B.S. in Computational and Systems Biology at UCLA. They are currently a research assistant in the Alfaro Lab, where they working with Dr. Michael Alfaro on studying global fish diversity as part of the image processing team. Nikita’s previous research experiences focused on machine learning theory, and they recently presented some of their team’s research on memorization in diffusion models at the 2023 ACM SIGKDD Conference. They are currently interested in the intersection of computation with plant and fungus ecology, as well as ecological engineering and agroecology as they pertain to building sustainable communities where humans can exist with minimal ecological consequences.
Project:
This project studies the relationship between hyperspectral signatures, functional traits, and tree health in the Quercus agrifolia population at Stunt Ranch Reserve. Past studies have demonstrated the accuracy of hyperspectral signatures in predicting nutrient content and other functional traits of plants. In Southern California ecosystems, Q. agrifolia (coast live oak) is considered a keystone species, and examining species traits can be instrumental to informing ecosystem management. Bridging these two areas of research, hyperspectral imaging can be useful in monitoring the physiological state of individuals or a population, allowing scientists to more effectively study certain phenomena (ex. tree health). Plant individuals may have significantly variable spectra within a species or population, because spectral signatures are directly influenced by phytochemistry and plant physiology, which in turn are affected by a variety of environmental factors(e.g. soil composition or water potential). This project will focus on 1) documenting the relationships between hyperspectral signatures and derived metrics, functional traits, and tree health in the Q. agrifolia population at Stunt Ranch; 2) evaluating variation in oak nutrient contents, hyperspectral signatures, etc. with regards to geographic variables; and 3) creating a publicly available dataset of Q. agrifolia spectral signatures and other collected data. The results of this study can inform ecology-based management and conservation of Q. agrifolia, which not only provides numerous ecosystem services as a keystone species, but also provides cultural and supporting services to First Nation groups in Southern and Central California.