A novel approach reveals underestimation of productivity in the globally important macroalga, Ascophyllum nodosum
Bibliographic record
Abstract
Abstract Ascophyllum nodosum (L.) Le Jolis (Fucales, Fucaceae) is a modular intertidal brown alga that has the particularity of forming an air bladder once a year at the apical tip of the growing shoots. This characteristic provides a means for aging and estimating the growth of individuals. While it has long been recognized that growth can occur in older parts of the frond, this has not been properly assessed until now and has largely been overlooked when calculating the productivity of the species. Recent studies have suggested that the growth and elongation of older segments is minimal and thus has been used to infer past environmental conditions. Here we assessed the length and mass of successive internodal segments from 25 sites spread over both sides of the North Atlantic, covering a wide portion of the distribution of the species. By calculating the ratio of the mass and length of a segment divided by the segment produced the following year, we established that internodal segments continue accumulating mass for 1–5 years and increase in length for 1–3 years at most sites. Segments can almost triple their mass during their second year and more than double their length. These results indicate that previous productivity and growth estimates for A. nodosum based on apical growth alone greatly underestimate the true productivity of the species and its role in coastal carbon cycling. Furthermore, because they grow over several years, internodal segments should not be used to infer past environmental conditions or to reconstruct growth patterns over time.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".