Acclimation of bloom‐forming and perennial seaweeds to elevated <scp><i>p</i>CO</scp><sub>2</sub> conserved across levels of environmental complexity
Bibliographic record
Abstract
Abstract Macroalgae contribute approximately 15% of the primary productivity in coastal marine ecosystems, fix up to 27.4 Tg of carbon per year, and provide important structural components for life in coastal waters. Despite this ecological and commercial importance, direct measurements and comparisons of the short‐term responses to elevated pCO2 in seaweeds with different life‐history strategies are scarce. Here, we cultured several seaweed species (bloom forming/nonbloom forming/perennial/annual) in the laboratory, in tanks in an indoor mesocosm facility, and in coastal mesocosms under pCO2 levels ranging from 400 to 2,000 μatm. We find that, across all scales of the experimental setup, ephemeral species of the genus Ulva increase their photosynthesis and growth rates in response to elevated pCO2 the most, whereas longer‐lived perennial species show a smaller increase or a decrease. These differences in short‐term growth and photosynthesis rates are likely to give bloom‐forming green seaweeds a competitive advantage in mixed communities, and our results thus suggest that coastal seaweed assemblages in eutrophic waters may undergo an initial shift toward communities dominated by bloom‐forming, short‐lived seaweeds.
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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 | 0.000 |
| 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 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".