Developing a method to track marine snow aggregation through individual collisions using stereoscopic imaging
Date of Award
Thesis: Open Access
MS Marine Science
Environmental and Ocean Sciences
Jennifer C. Prairie
Michel A. Boudrias
Suzanne C. Walther
The aggregation of individual phytoplankton into marine snow allows particles to sink more quickly, thus resulting in the transport of particulate organic carbon from surface waters to the deep ocean. Aggregate formation has previously been measured in experiments indirectly by quantifying how particle size or particle concentration changes over time. Here, I present my thesis in which I applied high-resolution imaging to quantify aggregate formation using two different methodologies.
We conducted experiments to investigate aggregate formation using stereoscopic imaging, tracking individual particles directly in a 3D volume. Phytoplankton cultures were rolled in cylindrical tanks and imaged by two cameras illuminated by an infrared laser sheet. Using particle tracking velocimetry (PTV) we were able to directly track particles using two different algorithms to match the same particle in the left and right images taken from the two cameras. We were able to compare the efficacy of these two algorithms, finding that an algorithm that matched particles in using the locations of individual particles in both cameras had a higher rate of matching particles correctly compared to an algorithm that instead matched particles using assembled 2D tracks from each camera.
We also analyzed the use of imaging as an indirect method of measuring aggregation formation, and explored how this method differed from those used in previous studies. Observing aggregate formation on the individual scale for the first time can further our understanding of how different biological and physical factors may affect the carbon cycle on much larger scales.
Copyright held by the author
Digital USD Citation
Henning, Riley, "Developing a method to track marine snow aggregation through individual collisions using stereoscopic imaging" (2021). Theses. 48.