Effects of a stand-replacing fire on small-mammal communities in montane forest
Bibliographic record
Abstract
Wildfire, ubiquitous and recurring over thousands of years, is the most important natural disturbance in northern coniferous forest. Accordingly, forest fires may exert a strong influence on the structure and functioning of small-mammal communities. We compared the composition of rodent and shrew communities in burned and unburned patches of a Douglas-fir ( Pseudotsuga menziesii (Mirbel) Franco) – western larch ( Larix occidentalis Nutt.) forest in western Montana, USA. Trapping was conducted during two consecutive summers after a wildfire. Four trapping sites were sampled in areas that burned at high severity and two in unburned forest. Small-mammal communities in burned sites were characterized by strong numerical dominance of deer mice ( Peromyscus maniculatus (Wagner, 1845)) and greatly reduced proportion of southern red-backed voles ( Clethrionomys gapperi (Vigors, 1830)) and red-toothed shrews (genus Sorex L., 1758). Relatively rare species such as northern flying squirrels ( Glaucomys sabrinus (Shaw, 1801)) and bushy-tailed woodrats ( Neotoma cinerea (Ord, 1815)) were largely restricted to unburned areas. The numbers of chipmunks (genus Tamias Illiger, 1811) were similar in burned and unburned areas. Rodent diversity was higher in unburned forest, but only during the 1st year after fire. Overall, the fire shifted small-mammal communities away from more specialized red-backed voles and shrews and towards greater abundance of generalist deer mice.
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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".