Trophic effects of rainfall on<i>Clethrionomys rutilus</i>voles: an experimental test in a xeric boreal forest in the Yukon Territory
Bibliographic record
Abstract
The Kluane forest is unusual in that it is less productive than other boreal forests because it lies in a rain-shadow zone. Densities of the boreal red-backed vole Clethrionomys rutilus are known to be food-limited in the Kluane region, and its food sources (mostly plants) could be rainfall-limited. We therefore tested the hypothesis that rainfall indirectly controlled vole densities in the Kluane region. Our predictions were that (i) food for voles would increase with additional rainfall and (ii) food-limited voles would in turn increase in numbers. Three sites in the Kluane forest were irrigated during the growing season for 5 years, and these were compared with three paired control sites without irrigation. Irrigation increased rainfall 91% above normal, on average. Neither understory plants, trees, invertebrates, nor the vole population reacted to irrigation. Only mushroom biomass increased. Hence, the above hypothesis must be rejected. The vegetation is not directly water-limited at these sites, and nitrogen limitation probably prevailed. However, mushroom biomass increased with irrigation and in turn should have increased nitrogen mineralization. It is therefore unclear why plant production and vole numbers did not increase with mushroom biomass on the irrigated 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".