Do North American Migratory Barren-Ground Caribou Subpopulations Cycle?
Bibliographic record
Abstract
Unlike all other members of the deer family, subpopulations of barren-ground caribou (Rangifer tarandus groenlandicus) are typically sine-cyclic. We used Bayesian Information Criteria (BIC) to rank competing population dynamics models for 11 North American barren-ground caribou subpopulations. Nine of these subpopulations were best described as sine-cyclic with periods ranging from a minimum of 26 years (Bluenose-East and Porcupine) to a maximum of 55 years (Western Arctic); and amplitudes ranging from a minimum of 8 455 (Cape Bathurst) to a maximum of 327 432 (George River). Time series estimates of subpopulation abundance generated by the sine cycle models showed good correspondence to published subpopulation estimates of abundance for all nine sine-cyclic subpopulations (r = 0.978; p < 0.001). Lack of demographic closure (migration between subpopulations) was evident in both of the subpopulations that were not identified as sine-cyclic. Barren-ground caribou subpopulation amplitudes were mostly determined by subpopulation total range size and summer range productivity (R2 = 0.962; p < 0.001) and subpopulation periods were mostly determined by amplitude, total range productivity, and land surface temperature (R2 = 0.950; p < 0.001). Time series estimates of subpopulation abundance generated from the respective environmental regression models were highly correlated (r = 0.964; p < 0.001) to the published subpopulation estimates of abundance for the set of 9 sine-cyclic subpopulations. Extended (> 3 generations) subpopulation declines are a natural feature of cyclic barren-ground caribou subpopulations. Trends in species abundance based on pooled assemblages of asynchronous cyclic subpopulations should be interpreted with caution.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".