The effect of adaptive change in the prey on the dynamics of an exploited predator population
Bibliographic record
Abstract
Mathematical models examine the relationship between harvesting effort and stock size for a predator species when the prey adapts to the risk of predation. In one set of models, the prey can increase its own reproductive rate if it increases its vulnerability to the predator. In the second set of models, each of two prey species has fixed characteristics, but changes in the average characteristics within the prey trophic level occur via shifts in the relative abundance of the two species. In both models, the equilibrium predator population can increase as harvest of that species increases. In the case of two-prey models, the predator's equilibrium population always increases with an increased harvest rate if the two prey coexist and share a single resource. The predator's equilibrium population often decreases from its maximum size to zero over a very small range of harvest rates, once those rates become high enough. Because increased stock size is often used to justify increased harvest rates, this relationship poses a risk that harvest rate will increase to the point where the stock quickly collapses. The results are relevant to understanding changes in the population size of a species experiencing declining environmental conditions.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".