Multi-Annual Oscillations in Animal Population Size: Internal and External Factors
Bibliographic record
Abstract
We find multi-annual oscillations in the population size of seven Canadian species, based on century-long time-series of fur harvests. Our statistical analysis aims to ascertain the factors that influence the dynamics of the populations hunted. To do so, we use the advanced spectral methods of singular spectrum analysis and multi-tapering. The dynamics of the seven populations have several common features. First, they share periodic components with periods of 2.5, 3 and 10 years. Second, all of them exhibit small-amplitude oscillations during the first decades of the century of record (1752-1849), and a much larger amplitude in the following decades. We determine the dominant frequency of each time-series at a given epoch, and the shifts between these dominant frequencies from epoch to epoch. A simple predator-prey model helps us interpret of these results. The two integer-valued periods, of 3 and 10 years, are likely to arise from the food-web interactions between the four species most involved in the predation. The 2.5-year period is attributed to the remote climatic effects of the tropical Pacific's quasi-biennial oscillation.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".