Does size matter? Particle size vs. quality in bivalve suspension feeding
Bibliographic record
Abstract
Abstract Increases in total suspended solids ( TSS ) in rivers have likely contributed to the decline in unionid mussel population sizes as feeding and reproduction are reduced at high TSS concentrations. Surprisingly, however, unionids are often found in turbid rivers. We predicted that clay‐sized particles, which comprise > 80% of river seston (particles in suspension), were too small to affect unionid clearance rate ( CR ) and thus explain this conundrum. We examined this hypothesis in laboratory experiments involving four unionid species exposed to four particle‐size based TSS treatments (mixed sediment: 0–63 μm; clay: 0–5 μm; fine silt: 5–38 μm; coarse silt: 38–63 μm; sourced from mussel sites) at 20 mg/L, which is a TSS concentration sufficient to reduce CR . Whereas the CR for all species was lower for mixed sediment, coarse silt and clay treatments—the latter was opposite to our prediction—the CR of mussels given the fine silt treatment was similar to the no‐ TSS control for two species and higher than the other TSS treatments in the other two species. Fine silt contained the most fluorescent (i.e. algal) particles and the highest protein and lipid content, which suggests that CR were higher on the more nutritious diet. Particle quality, rather than size, is what modulates suspension feeding in turbid rivers. Our current understanding of the ecological effects of bivalve suspension feeding will need to be revised to incorporate field‐based measurements.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.082 | 0.014 |
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; both teacher heads agree on what is shown here.
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".