Field Study of Growth and Calcification Rates of Three Species of Articulated Coralline Algae in British Columbia, Canada
Bibliographic record
Abstract
Ocean acidification caused by rising atmospheric CO₂ is predicted to negatively impact growth and calcification rates of coralline algae. Decreases in coralline abundance may have cascading effects on marine ecosystems and on carbon sequestration worldwide. In this study, we measured growth and calcification rates of three common species of articulated coralline algae (Bossiella plumosa, Calliarthron tuberculosum, and Corallina vancouveriensis) at an intertidal field site in British Columbia. Linear growth rates measured in the field were slow, although Bossiella grew significantly faster (0.22 cm mon⁻¹) than Calliarthron and Corallina (0.17 and 0.15 cm mon⁻¹, respectively). Growth rates in the field were generally slower than growth rates in the laboratory, suggesting that data generated in the laboratory may not be representative of natural field conditions. Growth rates did not decrease as fronds approached their maximum observed size, suggesting that maximum frond size might be determined not by intrinsic factors but by external factors such as wave-induced drag forces. Using growth data, we estimate that the largest observed Bossiella frond (20 cm²) and Calliarthron frond (40 cm²) were about 4- and 11-years-old, respectively, and had deposited approximately 1 and 6 g CaCO₃ in that time. Given the great abundance of coralline algae along the coast of British Columbia, deposition rates of CaCO₃ are expected to play a significant but poorly characterized role in carbon sequestration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".