Ocean Acidification Decreases Growth and Development in American Lobster (<i>Homarus americanus</i>) Larvae
Bibliographic record
Abstract
Ocean acidification resulting from the global increase in atmospheric CO 2 concentration is emerging as a threat to marine species, including crustaceans.Fisheries involving the American lobster (Homarus americanus) are economically important in eastern Canada and United States.Based on ocean pH levels predicted for 2100, this study examined the effects of reduced seawater pH on the growth (carapace length) and development (time to molt) of American lobster larvae throughout stages I-III until reaching stage IV (postlarvae).Each stage is reached after a corresponding molt.Larvae were reared from stage I in either acidified (pH = 7.7) or control (pH = 8.1) seawater.Organisms in acidified seawater exhibited a significantly shorter carapace length than those in control seawater after every molt.Larvae in acidified seawater also took significantly more time to reach each molt than control larvae.In nature, slowed progress through larval molts could result in greater time in the water column, where larvae are vulnerable to pelagic predators, potentially leading to reduced benthic recruitment.Evidence was also found of reduced survival when reaching the last stage under acidified conditions.Thus, from the perspective of larval ecology, it is possible that future ocean acidification may harm this important marine resource.
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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".