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Alternative Title

Assessing microbial community responses to food web perturbations

Publication Date


First Advisor

Laura A. Katz

Document Type

Honors Project

Degree Name

Bachelor of Arts


Biological Sciences


Microbial, Ecology, Ciliates, SAR, Molecular biology, DGGE, High through put sequencing, Marine, Ocean, Microcosm, Microorganisms, Food chains (Ecology), Ecological disturbances, Phytoplankton, Algal bloom, Eukaryotic cells


Marine microbes are the base of the marine food webs. Many microbial lineages are understudied, therefore their role in marine food webs go underappreciated due to the limited knowledge on their biotic interactions and influences on abiotic processes. In order to understand the dynamics of microbes in marine food webs, I conducted two microcosm experiments to study how shifts in the community of primary producer microbes (phytoplankton) influences higher trophic level microbes and small animals (e.g., ciliates, copepods). My predation microcosm experiment showed that copepods displayed homogenous preference for naked ciliates over shelled ciliates but I also found that the number of copepod grazers did not affect other eukaryotes. Based on those findings, I hypothesized that incubation plays a role in microbial response and that ciliates and other microbes within the SAR clade (Stramenopila, Alveolata, Rhizaria) would have a detectable homogenous response to the different phytoplankton blooms. My findings suggest that microcosms are an effective way to study how biotic disturbances, like “red tides” or other major shifts in abundance and identify of primary producers, might impact microbial communities and that combining DGGE and high throughput sequencing is a powerful approach for analyzing community patterns. My phytoplankton microcosm experiments tested this by comparing controls (no phytoplankton addition), to three blooms: the diatom Phaeodactylum tricornutum, the chlorophyte Tetraselmis chuii (green microalgae), and the haptophyte Isochrysis galbana (‘brown’ microalgae). I also looked to see if there were differences among filter sizes as perhaps the size of the phytoplankton food would influence community composition based on the basic principle that the bigger you are, the more you will eat. My preliminary data indicate that DGGE can be a powerful tool to visualize how community composition changes once the communities are incubated and how they respond to different biotic pressures (i.g predation or phytoplankton blooms). In the phytoplankton bloom microcosm we found that sampling on different days resulted in different starting communities, once they were incubated, their response to blooms became less homogenous, suggesting that blooms were impacting community dynamics as our control community differed greatly from our starting community. There was not a detectable difference among sizes seen in phytoplankton bloom DGGE gels in spirotrich ciliates but high throughput sequencing data show that there was a difference in responses among sizes in all groups of SAR. High throughput sequencing data also suggests that the Chlorophyte, Tetraselmis chuii (green microalgae) supported a more diverse community at the microsize fraction and that the haptophyte, Isochrysis galbana (brown microalgae) supported a more diverse community at the nanosize fraction. We suggest that our microcosm experiments were able to capture that microbial communities are highly dynamic and their responses to biotic disturbances can vary across time and among different microbial groups.




78 pages : color illustrations. Includes bibliographical references (pages 74-78)