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Summary TheSynechococcuscyanobacterial population at the Scripps Institution of Oceanography pier in La Jolla, CA, shows large increases in abundance, typically in the spring and summer followed, by rapid declines within weeks. Here we used amplicon sequencing of the ribosomal RNA internal transcribed spacer region to examine the microdiversity within this cyanobacterial genus during these blooms as well as further offshore in the Southern California coastal ecosystem (CCE). These analyses revealed numerousSynechococcusamplicon sequence variants (ASVs) and that clade and ASV composition can change over the course of blooms. We also found that a large bloom in August 2016 was highly anomalous both in its overallSynechococcusabundance and in terms of the presence of normally oligotrophicSynechococcusclade II. The dominant ASVs at the pier were found further offshore and in the California Current, but we did observe more oligotrophic ASVs and clades along with depth variation inSynechococcusdiversity. We also observed that the dominant sequence variant switched during the peak of multipleSynechococcusblooms, with this switch occurring in multiple clades, but we present initial evidence that this apparent ASV switch is a physiological response rather than a change in the dominant population.
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The importance of making testable predictions: A cautionary tale
We found a startling correlation (Pearson ρ > 0.97) between a single event in daily sea surface temperatures each spring, and peak fish egg abundance measurements the following summer, in 7 years of approximately weekly fish egg abundance data collected at Scripps Pier in La Jolla California. Even more surprising was that this event-based result persisted despite the large and variable number of fish species involved (up to 46), and the large and variable time interval between trigger and response (up to ~3 months). To mitigate potential over-fitting, we made an out-of-sample prediction beyond the publication process for the peak summer egg abundance observed at Scripps Pier in 2020 (available on bioRxiv). During peer-review, the prediction failed, and while it would be tempting to explain this away as a result of the record-breaking toxic algal bloom that occurred during the spring (9x higher concentration of dinoflagellates than ever previously recorded), a re-examination of our methodology revealed a potential source of over-fitting that had not been evaluated for robustness. This cautionary tale highlights the importance of testable true out-of-sample predictions of future values that cannot (even accidentally) be used in model fitting, and that can therefore catch model assumptions that may otherwise escape notice. We believe that this example can benefit the current push towards ecology as a predictive science and support the notion that predictions should live and die in the public domain, along with the models that made them.
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- PAR ID:
- 10233986
- Editor(s):
- Belgrano, Andrea
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 15
- Issue:
- 12
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0236541
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0236541
