Incubation with macroalgae induces large shifts in water column microbiota, but minor changes to the epibiota of co‐occurring macroalgae
Bibliographic record
Abstract
Macroalgae variably promote and deter microbial growth through release of organic carbon and antimicrobial compounds into the water column. Consequently, macroalgae influence the microbial composition of the surrounding water column and biofilms on nearby surfaces. Here, we use manipulative experiments to test the hypotheses that (i) Nereocystis luetkeana and Mastocarpus sp. macroalgae alter the water column microbiota in species-specific manner, that (ii) neighbouring macroalgae alter the bacterial communities on the surface (epibiota) of actively growing Nereocystis luetkeana meristem fragments (NMFs), and that (iii) neighbours alter NMF growth rate. We also assess the impact of laboratory incubation on macroalgal epibiota by comparing each species to wild counterparts. We find strong differences between the Nereocystis and Mastocarpus epibiota that are maintained in the laboratory. Nereocystis and Mastocarpus alter water column bacterial community composition and richness in a species specific manner, but cause only small compositional shifts on NMF surfaces that do not differ by species, and do not change richness. Co-incubation with macroalgae results in significant change in abundance of fivefold more genera in the water column compared to NMF surfaces, although the direction (i.e., enrichment or reduction) of shift is generally consistent between the water and NMF surfaces. Finally, NMFs grew during the experiment, but growth did not depend on the presence or identity of neighbouring macroalgae. Thus, macroalgae exhibit a strong and species-specific influence on the water column microbiota, but a much weaker influence on the epibiota of neighbouring macroalgae. Overall, these results support the idea that macroalgae surfaces are highly selective and demonstrate that modulations of macroalgal microbiota operate within an overarching paradigm of host species specificity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".