Role of satiation in the functional response of a piscivore, largemouth bass (<i>Micropterus salmoides</i>)
Bibliographic record
Abstract
We evaluated whether satiation regulates the predation rates of a piscivore, largemouth bass (Micropterus salmoides), in natural settings. A functional response model indicated that predation rates can be reduced by satiation when mean prey density is high or when prey encounters are highly patchy. We then used bioenergetics modeling to estimate the predation rates of individual bass in four lakes during a 16-year period and used stomach content mass in diet samples to evaluate the variability in daily predation rates. Predation rates, expressed as the proportion (p) of the maximum daily consumption rate, were low (mode = 0.3, mean = 0.4). Stomach fullness (s), expressed as the proportion of the stomach fullness associated with the maximum sustainable consumption rate, was highly variable, and 13% of all bass diets had s > 1, indicating that bass could opportunistically forage at rates exceeding their maximum sustainable rate. The low predation rates and the ability to consume prey at rates exceeding the maximum sustainable rate make it unlikely that satiation was an important constraint on bass predation rates. Thus, satiation effects widely represented in modeling studies may be a rare component in piscivore-prey interactions, while prey behavior may be a more important component governing predation 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 | 0.001 |
| 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".