Effect of feeding history on metabolic rate of largemouth bass (<i>Micropterus nigricans</i>): implications for bioenergetics models
Bibliographic record
Abstract
Metabolic rate is a key parameter in fish energy budgets that strongly influences the output of bioenergetics models. In this study, we tested the hypothesis that metabolic rate varies with growth history of age-1 largemouth bass Micropterus nigricans Cuvier, 1828. Two groups of fish were fed alternating maintenance or ad libitum rations of fathead minnow Pimephales promelas Rafinesque, 1820, so that over a 9-week period, initial and ending size of fish was similar. After 9 weeks, oxygen consumption was measured using static, closed respirometry. Although final body weight was similar between the two groups (means, 104–108 g), specific oxygen consumption for fish fed maintenance rations (0.094 mg O2 g−2 h−1) was 38% less than that measured for fish fed ad libitum (0.152 mg O2 g−2 h−1). Bioenergetics estimates of food consumption were similar to observed values for fish fed ad libitum (∼7% error), but for fish fed maintenance rations, the model overestimated food consumption by 65%. By accounting for changes in metabolic rate owing to reduced feeding, error in model estimates of food consumption was reduced. These findings shed new insight into factors associated with consumption-dependent error in bioenergetics models and highlight the importance of feeding history on metabolic rate of fish. Incorporating growth-dependent metabolism into bioenergetics models can improve model accuracy and allow fisheries biologists to make more informed decisions regarding fish growth and energetics.
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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".