The microbiome of the habitat‐forming brown alga <i>Fucus vesiculosus</i> (Phaeophyceae) has similar cross‐Atlantic structure that reflects past and present drivers<sup>1</sup>
Bibliographic record
Abstract
Latitudinal diversity gradients have provided many insights into species differentiation and community processes. In the well-studied intertidal zone, however, little is known about latitudinal diversity in microbiomes associated with habitat-forming hosts. We investigated microbiomes of Fucus vesiculosus because of deep understanding of this model system and its latitudinally large, cross-Atlantic range. Given multiple effects of photoperiod, we predicted that cross-Atlantic microbiomes of the Fucus microbiome would be similar at similar latitudes and correlate with environmental factors. We found that community structure and individual amplicon sequencing variants (ASVs) showed distinctive latitudinal distributions, but alpha diversity did not. Latitudinal differentiation was mostly driven by ASVs that were more abundant in cold temperate to subarctic (e.g., Granulosicoccus_t3260, Burkholderia/Caballeronia/Paraburkholderia_t8371) or warm temperate (Pleurocapsa_t10392) latitudes. Their latitudinal distributions correlated with different humidity, tidal heights, and air/sea temperatures, but rarely with irradiance or photoperiod. Many ASVs in potentially symbiotic genera displayed novel phylogenetic biodiversity with differential distributions among tissues and regions, including closely related ASVs with differing north-south distributions that correlated with Fucus phylogeography. An apparent southern range contraction of F. vesiculosus in the NW Atlantic on the North Carolina coast mimics that recently observed in the NE Atlantic. We suggest cross-Atlantic microbial structure of F. vesiculosus is related to a combination of past (glacial-cycle) and contemporary environmental drivers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".