Size at hatching determines population dynamics and response to harvesting in cannibalistic fish
Bibliographic record
Abstract
We hypothesize that size at hatching strongly affects population dynamics of cannibalistic fish species and is a crucial determinant of how populations respond to selective removal of large individuals (harvesting). We use a mechanistic mathematical model to study the relation between hatching size and response to harvesting mortality, using Eurasian perch ( Perca fluviatilis ) as a model organism. We show how hatching size determines dynamics through its effect on the relative strength of cannibalistic mortality and resource competition as mechanisms of population regulation. In populations with intermediate and large hatching size, cannibalistic mortality is an important determinant of population dynamics, and harvesting destabilizes population dynamics. When hatching size is small, population stability is less sensitive to this type of harvesting. Populations hatching at small size are regulated by competition, and harvesting large individuals affects such populations less. Harvesting can also induce the growth of very large individuals, absent in unharvested populations. Our results show that harvesting in cannibalistic lake fish populations can strongly alter population dynamics in ways that can only be anticipated on the basis of mechanistic knowledge about how populations are regulated.
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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 | 0.002 |
| 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) | 0.001 | 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".