Relating the 4-year lemming (<i>Lemmus</i> spp. and <i>Dicrostonyx</i> spp.) population cycle to a 3.8-year lunar cycle and ENSO
Bibliographic record
Abstract
Reported peak years of lemming (Lemmus spp. and Dicrostonyx spp.) and Arctic fox (Vulpes lagopus (Linnaeus, 1758)) abundance were compiled from the literature for 12 locations spanning 127 years. The mean period of the 34 reported lemming and Arctic fox cycles from 1868 to 1994 was 3.8 years, suggesting that the period of the 4-year cycle is actually 3.8 years. Peak population years were predicted using a simple model based on a 3.8-year lunar cycle. For nearly 130 years, reported years of peak abundance of lemmings and Arctic foxes were significantly correlated with and have persistently stayed in phase with predicted peak years of abundance. Over the same period, predicted peak years of lemming abundance have been closely aligned with peak (i.e., La Niña) years of the January–March Southern Oscillation Index (SOI). From 1952 to 1995, peak flowering in Norway tended to occur close to trough June–August SOI (El Niño) years. The hypothesis proposed is that the 3.8-year lunar cycle governs the timing of the lemming cycle, but it does not cause the population cycling itself. If this hypothesis is true, then the heretofore unexplained source of the persistent periodicity and quasi-metronomic regularity of the lemming cycle is identified.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".