Manipulations of Stocking Magnitude: Addressing Density-Dependence in a Juvenile Cohort of Common Snook (<i>Centropomus undecimalis)</i>
Bibliographic record
Abstract
We released hatchery-reared juvenile common snook (Centropomus undecimalis) to test the effects of augmenting age-1 abundance by 100% (high augmentation, n = 2) vs 10% (low augmentation, n = 2) in estuarine creeks of southwestern Florida. We monitored in-creek abundance of age-1 snook 1 month before releases in May 2002 to estimate wild snook density and stocking magnitude. All sampling used seining standardized for effort, gear efficiency, and depletion removal. After releases, sampling continued for 1 year. After 1 month, creeks with high augmentation showed a 126% and 74% increase in total age-1 abundance, and low augmentation creeks a 6% increase and an 18% decrease. Total age-1 abundance declined during fall in all creeks, but by winter, abundance increased again, comparable to earlier levels (132% and 67% above the pre-release estimates in high augmented creeks and 8% and 5% in creeks with low augmentation). While overall density was elevated in both high augmentation creeks, hatchery-reared snook in one creek experienced a 64–85% loss within 1 month after release; loss of hatchery-reared or wild snook was negligible in other experimental creeks. Pre-release density was not a good predictor of creek productive capacity, suggesting variation in habitat production and localized recruitment. Further work is needed to understand inter-cohort density-dependent interactions, food chain responses, and variation in habitat productivity.
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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".