The influence of rainfall on murid densities through a trophic chain in the Kluane boreal forest, Yukon
Bibliographic record
Abstract
Vole and mouse population densities in the Kluane boreal forest (Yukon) vary noncyclically; densities are usually low but unpredictable and ephemeral high densities occasionally occur. Anecdotal observations suggest that vole and mouse densities could be correlated to summer rainfall amounts. Small mammal populations in Kluane are suspected to be food-limited, and food production is suspected to be rainfall-limited, since the Kluane boreal forest experiences a water-deficit during the summer. I tested the hypothesis that rainfall acts through a trophic chain to influence vole numbers, and that vole numbers should increase with rainfall two-to-three fold as they do with addition of sunflower seed. To simulate increased rainfall, I installed irrigation systems and operated them for two summers on three areas of approximately 1.5 hectares of boreal forest habitat. I monitored small mammals, mushrooms, understory vegetation, spruce trees and forest-floor invertebrates. Three unirrigated areas of equal size were used as control grids: treatment and control grids were paired within three different sites. Mushrooms and one species of understory plant (Arctostaphylos uva-ursi) responded significantly to the treatment. There was no clear treatment effect on spruce trees, invertebrates, and shrews. Voles were generally more numerous on the treatment grids than on the controls, but the difference was of the expected three-fold magnitude at only one site. Overall, only one out of three sites supported the hypothesis that vole densities can be affected by rainfall through a trophic chain.
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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 | 0.000 |
| 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) | 0.000 | 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, 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".