| Summary: | Thesis (M.S.) University of Alaska Fairbanks, 2020 The phytoplankton of the Bering and Chukchi seas support highly productive ecosystems characterized by tight benthic-pelagic coupling. In this study, we focus on the northern Bering and Chukchi seas, considering them as one ecosystem. This community has historically been dominated by diatoms; however, climate change and accompanying warming ocean temperatures may alter primary producer communities. Using metabarcoding, we present the first synoptic, high-throughput molecular phylogenetic investigation of phytoplankton diversity in the Bering and Chukchi seas based on hundreds of samples collected from June to September in 2017. We identify the major and minor taxonomic groups of diatoms and picophytoplankton, relative abundances of genera, exact sequence variants (201 for diatoms and 227 for picophytoplankton), and describe their biogeography. These phylogenetic insights and environmental data are used to characterize preferred temperature ranges, offering insight into which specific phytoplankton (Chaetoceros, Pseudo−nitzschia, Micromonas, Phaeocystis) may be most affected as the region warms. Finally, we investigated the likelihood of using shipboard CTD data alone as predictive variables for which members of phytoplankton communities may be present. We found that the suite of environmental data collected from a shipboard CTD is a poor predictor of community composition, explaining only 12.6% of variability within diatom genera and 14.2% variability within picophytoplankton genera. Clustering these communities by similarity of samples did improve predictability (43.6% for diatoms and 32.5% for picophytoplankton). However, our analyses succeeded in identifying temperature as a key driver for certain taxa found commonly throughout the region, offering a key insight into which common phytoplankton community members may be affected first as the Alaskan Arctic continues to warm. National Oceanic and Atmospheric Administration, National Science Foundation, ...
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