Intrinsic and extrinsic factors in the dynamics of local small-mammal populations
Bibliographic record
Abstract
We studied dynamics of local small-mammal assemblages consisting of shrews, voles, and mice by small-scale snap trapping in each spring and autumn from 1981 to 2006 in southern Finland. Our aim was to search for relative roles of possible regulatory associations within and between species, as well as to find reflections of the effects of large-scale climatic phenomena on local populations. Preceding intraspecific densities had a dominating role in seasonal changes in small-mammal numbers. Their relationships with weather-related factors indicated by the indices of the North Atlantic Oscillation (NAO) were most pronounced during winter. Relationships with the NAO indices, increasing values of which indicate milder weather in the north, were negative in voles but positive in shrews and mice. Spring densities were governed by the largely compensatory effects of the growth rate of the preceding summer and subsequent population decline during winter in the field vole ( Microtus agrestis (L., 1761)) and mice, while the effects of winter decline dominated in shrews. The bank vole ( Myodes glareolus (Schreber, 1780) = Clethrionomys glareolus (Schreber, 1780)) showed decreasing winter decline, which had a considerable positive effect on population densities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".