Exploring feeding physiology of Mytilus edulis across geographic and fjord gradients in low-seston environments
Bibliographic record
Abstract
It is important to be able to predict the growth of filter-feeding bivalves, as they grow in dense populations both naturally and for commercial production. To understand the growth of bivalves it is necessary to have a mechanistic understanding of how they acquire energy through ingestion. This study was designed to understand if capture efficiency (CE), a primary step in ingestion for filter-feeders, is variable in the blue mussel Mytilus edulis . CE was measured using natural seston in 3 populations of naturally occurring M. edulis and within 2 populations along a fjord gradient. Differences in CE were found within a single population as well as along the fjord gradient. To determine if these differences were driven by short- or long-term changes, a single population of mussels was reciprocally transplanted between 2 locations along a fjord. This study is the first time CE has been measured within a population of M. edulis using a regional transplant experiment. Results showed that CE may vary between populations and change within populations, indicating that CE seems primarily driven by environmental cues. Pumping and overall ingestion rates differed between populations and varied within populations. For widely distributed species in changing environments, it is increasingly relevant to understand the limits of plasticity of specific traits to be able to predict their growth, survival, and distribution. Here, we aimed to provide a more mechanistic description of CE, pumping rate, and overall ingestion in M. edulis.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".