Small mammal response to habitat change following fire in the taiga of southeastern Manitoba
Bibliographic record
Abstract
The influence of fire on small mammal populations was investigated in the taiga of southeastern Manitoba. Small mammals were sampled by annual removal trapping in six different habitats over twenty-five years at Taiga Biological Station (TBS). Changes in temporal patterns of short-term abundance and long-term population synchronicity were investigated for fluctuating numbers of small mammals. The southern red-backed vole (Clethrionomys gapperi),the deer mouse (Peromyscus maniculatus), and the masked shrew (Sorex cinereus), were the three most common small mammals captured. Examination of population fluctuations revealed that while fire-induced changes in food availability, cover and moisture were likely responsible for differences in small mammal abundance, populations of individual species were alternatively affected by unknown, large-scale, synchronizing influences. This discovery became evident through the common occurrence of similar peak abundance years for C. gapperi, regardless of habitat-type or distance between sampling sites. Additionally, the examination of annual combined small mammal biomass revealed a distinct pattern, with a repetitive maxima occurring every 3- to 4- yrs at TBS across all six sites...
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".