You can hide but you can’t run: apparent competition, predator responses and the decline of Arctic ground squirrels in boreal forests of the southwest Yukon
Bibliographic record
Abstract
Throughout much of North America's boreal forest, the cyclical fluctuations of snowshoe hare populations (Lepus americanus) may cause other herbivores to become entrained in similar cycles. Alternating apparent competition via prey switching followed by positive indirect effects are the mechanisms behind this interaction. Our purpose is to document a change in the role of indirect interactions between sympatric populations of hares and arctic ground squirrels (Urocitellus parryii plesius), and to emphasize the influence of predation for controlling ground squirrel numbers. We used mark-recapture to estimate the population densities of both species over a 25-year period that covered two snowshoe hare cycles. We analysed the strength of association between snowshoe hare and ground squirrel numbers, and the changes to the seasonal and annual population growth rates of ground squirrels over time. A hyperbolic curve best describes the per capita rate of increase of ground squirrels relative to their population size, with a single stable equilibrium and a lower critical threshold below which populations drift to extinction. The crossing of this unstable boundary resulted in the subsequent uncoupling of ground squirrel and hare populations following the decline phase of their cycles in 1998. The implications are that this sustained Type II predator response led to the local extinction of ground squirrels. When few individuals are left in a colony, arctic ground squirrels may also have exhibited an Allee effect caused by the disruption of social signalling of approaching predators.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".