Rodent populations on the northern Great Plains respond to weather variation at a landscape scale
Bibliographic record
Abstract
Extreme weather variation on the northern Great Plains of North America can potentially influence the abundance of grassland rodents across vast areas. We used the remains of 33,697 small mammals collected from owl pellets in central and western Canada over 15 years to determine the influence of weather on the annual abundance of deer mice (Peromyscus maniculatus), sagebrush voles (Lemmiscus curtatus), and meadow voles (Microtus pennsylvanicus). Weather variation affected the annual abundances of all 3 species; however, influence on deer mouse and sagebrush vole annual abundances was relatively small compared to that on meadow voles. This finding may indicate that factors other than weather (i.e., habitat availability) are more important for the abundance of deer mice and sagebrush voles at the landscape scale. In contrast, meadow voles were positively associated with the duration of snow cover above the hiemal threshold (20 cm), exhibiting up to 5-fold increases (i.e., irruptions) in abundance following winters of persistent, deep snow cover. Our study is the first to examine the effects of weather on landscape-scale abundance of rodent species on the northern Great Plains of North America, providing further insight into the role weather plays in driving rodent population fluctuations in this highly seasonal environment.
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 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 | 0.001 | 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 | 0.000 |
| 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 | 0.001 |
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 teacher head, 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".