The influence of spatially variable and connected recruitment on complex stock dynamics and its ecological and management implications
Bibliographic record
Abstract
To evaluate the influence of spatially variable and connected recruitments at spawning component scale on complex stock dynamics, a typical agent-based complex stock was modeled based on the Atlantic cod (Gadus morhua) stock in the Gulf of Maine. We simulated three scenarios with different degrees of connectivity (i.e., individual exchange) between the spatially variable recruitments of 36 spawning components within four subpopulations under the stock. Subsequently, the temporal trends were compared for different scenarios in age-1 recruitment, spawning stock biomass, and local depletion proportion of the overall complex stock and the individual subpopulations. Results show that increased recruitment connectivity from 0.1–0.2 to 0.6–0.8 between various components tends to increase the productivity and stability of a complex stock at local and global scales and reduce the proportion of depleted components due to overfishing. Moreover, depletions of less productive components may occur without a substantial reduction in the overall complex stock biomass and recruitment.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".