The enigma of the 10-year wildlife population cycle solved? Evidence that the periodicity and regularity of the cycle are driven by a lunar zeitgeber
Bibliographic record
Abstract
Despite nearly 100 years of research, the periodicity and regularity of the 10-year wildlife population cycle remain an enigma. This paper presents the hypothesis that the 9.3-year nodal half-cycle of the moon is the zeitgeber (“time-giver”) of the 10-year wildlife population cycle. The period of the population cycles of the Snowshoe Hare (Lepus americanus) and Ruffed Grouse (Bonasa umbellus) is close to 9.3 years. These wildlife cycles have stayed closely in phase with the 9.3-year nodal half-cycle for 150 years. Population density of the Snowshoe Hare and Ruffed Grouse is inversely related to a 9.3-year cycle of the moon's tidal force. There is also a 9.3-year cycle of “nights without darkness” at the equinoxes, in which the full moon rises before sunset and sets after sunrise the following morning in certain years. Snowshoe Hare and Ruffed Grouse cycles are positively correlated with this phenomenon. The nodal cycle provides explanations for the key features of the 10-year wildlife cycle: regularity, periodicity, amplitude, distribution, and synchrony. Population models based solely on the nodal cycle account for 62% of the variation in the Canada Lynx (Lynx canadensis) cycle and 37% in the Ruffed Grouse cycle. The mechanism(s) by which herbivore cycles might be entrained by the lunar nodal cycle could involve a cyclic effect on factors including predation, stress, photoperiod, phenology, temperature, cloudiness, ultraviolet B radiation, cosmic rays, and food plant quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".