Cycle lengths and phase portrait characteristics as probes for predator–prey interactions: comparing simulations and observed data
Bibliographic record
Abstract
In this paper we explore the cyclic interactions of prey–predator systems by examining the relationship between cycle lengths of both species and the strength of their interaction. As a probe of interaction strength, we use the degree of counter-clockwise rotation in phase plots with the prey on the x axis and the predator on the y axis. We compare the results from a 25-year time series from the Hudson’s Bay Company data on American mink ( Neovison vison (Schreber, 1777)) and muskrat ( Ondatra zibethicus (L., 1766)) with results from three simulation models. We found that the strength of interaction (rotation range: –0.4 to 1.1 rad/year) was strongest when the two cycle lengths were similar and that it increased with the amplitude of the cycles (cycle range: 4–10 years). The time difference between prey and predator cycles that corresponded to the highest interaction strength was 2–3 years. Similar results were obtained with simulation models; the most complex Hanski model showing the overall best fit with observations. However, none of the models were able to reproduce long ranges of stable cycles by only changing one of their parameters at a time (ranges 2–4 years), whereas the observed range of stable cycles was 4–10 years.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".