Pull the trigger: interplay between benthic and pelagic cues driving the early recruitment of a natural bivalve assemblage
Bibliographic record
Abstract
Abstract Larval settlement and recruitment are crucial phases in the benthic‐pelagic life cycle of marine benthic invertebrates that controls population dynamic and habitat connectivity. Our study investigated potential triggers driving the settlement of bivalve larvae in a highly dynamic intertidal coarse sand habitat. The early recruitment rate of five dominant bivalve families and abiotic conditions, particulate (<20 µm) organic matter and sediment organic matter, were monitored from May to October 2014. Pelagic particulate organic matter (<20 µm) was dominated by picoplankton throughout the sampling period, with a substantial diatom bloom in spring. Sediment was characterized by fresh organic matter in spring, as suggested by the dominant contribution of polyunsaturated fatty acids, and by a higher proportion of bacterial fatty acid markers during late summer. Different dynamics were also observed in early bivalve recruitment rates, with four different patterns observed over the sampling period. Multiple regression analysis on selected bivalve families showed species‐specific responses to trophic settlement triggers. Indeed, the larva recruitment rate of Mytilidae paralleled pelagic concentration of picoeucaryotes, with the peak early recruitment rate occurring in spring. Surprisingly, the early recruitment rate of Mactridae larvae showed a significant relation to bacterial concentration in the surficial sediment at the end of summer. While the Mytilidae results in such a eutrophic system confirmed those of a previous study in oligotrophic lagoons, therefore supporting the trophic settlement trigger hypothesis, more work is needed to understand the potential role of bacteria in the early recruitment of Mactridae. These results highlight for the first‐time inter‐specific differences in trophic cues that potentially trigger primary settlement in natural bivalve assemblages.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".