Mechanisms to Explain the Elemental Composition of the Initial Aragonite Shell of Larval Oysters
Bibliographic record
Abstract
Abstract Calcifying organisms face increasing stress from the changing carbonate chemistry of an acidifying ocean, particularly bivalve larvae that live in upwelling regions of the world, such as the coastal and estuarine waters of Oregon (USA). Arguably the first and most significant developmental hurdle faced by larval oysters is formation of their initial prodissoconch I (PDI) shell, upon which further ontological development depends. We measured the minor metal compositions (Sr/Ca, Mg/Ca) of this aragonitic PDI shell and of post‐PDI larval Crassostrea gigas shell, as well as the water they were reared in, over ∼20 days for a May and an August cohort in 2011, during which time there was no period of carbonate under‐saturation. After testing various methods, we successfully isolated the shell from organic tissue using a 5% active chlorine bleach solution. Elemental compositions (Sr, Mg, C, N) of the shells post‐treatment showed that shell Sr/Ca ranged from 1.55 to 1.82 mmol/mol; Mg/Ca from 0.60 to 1.11 mmol/mol, similar to the few comparable published data for larval oyster aragonite compositions. We compare these data in light of possible biomineralization mechanisms: an amorphous calcium carbonate (ACC) path, an intercellular path, and a direct‐from‐seawater path to shell formation via biologically induced inorganic precipitation of aragonite. The last option provides a mechanistic explanation for: (1) the accelerated precipitation rates of biogenic calcification in the absence of a calcifying fluid; (2) consistently elevated precipitation rates at varying ambient‐water saturation states; and (3) the high Ca‐selectivity of the early larval calcification despite rapid precipitation rates.
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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".