Match/mismatch between the <i>Mytilus edulis</i> larval supply and seston quality: effect on recruitment
Bibliographic record
Abstract
We considered Cushing's match/mismatch theory in a heterotrophic environment and hypothesized that settlement and recruitment success in blue mussel are higher when the food supply is rich in polyunsaturated and essential fatty acids (PUFA/EFA). To test this hypothesis, we monitored larval development as well as fatty acid composition in trophic resources during two successive reproductive seasons. The decoupling we found between the presence of competent larvae in the water column and settlement rates strongly suggests that metamorphosis is delayed until conditions are suitable. In both years, the major mussel settlement peak was synchronized with a phytoplanktonic pulse rich in EFA, consisting of a large autotrophic bloom in 2007 and a short but substantial peak of picoeukaryotes in 2008. These results suggest a "trophic settlement trigger" that indirectly affects recruitment by strongly improving the settlement rate. Despite similar larval settlement rates during both years, the lower 2007 recruitment likely resulted from a mismatch with a high lipid-quality trophic resource. The seasonal trophic conditions differed greatly between the two years, with fatty acids profiles reflecting heterotrophic plankton production in 2007 and mostly autotrophic production in 2008. In agreement with Cushing's theory, our results highlight a match/mismatch, related to the food lipid quality rather than food quantity. For the first time, we show that the recruitment in marine bivalves may be dependent on phytoplanktonic pulses characterized by high levels of PUFA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
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 teacher head, 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".