Back

Hydrothermal activity and water mass composition shape microbial eukaryote diversity and biogeography in the Okinawa Trough

Brisbin, M. M.; Conover, A. E.; Mitarai, S.

2019-07-25 ecology
10.1101/714816 bioRxiv
Show abstract

Microbial eukaryotes (protists) contribute substantially to ecological functioning in marine ecosystems, but factors shaping protist diversity, such as dispersal barriers and environmental selection, remain difficult to parse. Deep-sea water masses, which form geographic barriers, and hydrothermal vents, which represent isolated productivity hotspots, are ideal opportunities for studying the effects of dispersal barriers and environmental selection on protist communities. The Okinawa Trough, a deep, back-arc spreading basin, contains distinct water masses in the bottom waters of northern and southern regions and at least twenty-five active hydrothermal vents. In this study, we used metabarcoding to characterize protist communities from fourteen stations spanning the length of the Okinawa Trough, including three hydrothermal vent sites. Significant differences in community structure reflecting regional oceanography and water mass composition were present, indicating the importance of geographic factors in shaping protist communities. Protist communities in bottom waters affected by hydrothermal activity were significantly different from communities in other bottom waters, suggesting that environmental factors can be especially important in shaping community composition under specific conditions. Amplicon sequence variants that were enriched in hydrothermally influenced bottom waters largely derived from cosmopolitan protists that were present, but rare, in other near-bottom samples, thus highlighting the importance of the rare biosphere.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.