Macroalgal spore dysfunction: ocean acidification delays and weakens adhesion
Bibliographic record
Abstract
Early life stages of marine organisms are predicted to be vulnerable to ocean acidification. For macroalgae, reproduction and population persistence rely on spores to settle, adhere and continue the algal life cycle, yet the effect of ocean acidification on this critical life stage has been largely overlooked. We explicitly tested the biomechanical impact of reduced pH on early spore adhesion. We developed a shear flume to examine the effect of reduced pH on spore attachment time and strength in two intertidal rhodophyte macroalgae, one calcified (Corallina vancouveriensis) and one noncalcified (Polyostea robusta). Reduced pH delayed spore attachment of both species by 40%-52% and weakened attachment strength in C. vancouveriensis, causing spores to dislodge at lower flow-induced shear forces, but had no effect on the attachment strength of P. robusta. Results are consistent with our prediction that reduced pH disrupts proper curing and gel formation of spore adhesives (anionic polysaccharides and glycoproteins) via protonation and cation displacement, although experimental verification is needed. Our results demonstrate that ocean acidification negatively, and differentially, impacts spore adhesion in two macroalgae. If results hold in field conditions, reduced ocean pH has the potential to impact macroalgal communities via spore dysfunction, regardless of the physiological tolerance of mature thalli.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".