Food availability in spring influences reproductive output in the seed-preying edible dormouse (Glis glis)
Bibliographic record
Abstract
Edible dormice ( Glis glis (L., 1766)) display strong annual variation in their reproductive output that is closely related to resource availability, commonly measured through the quantity of seeds produced by their most important food provider, the European beech ( Fagus sylvatica L.). Dormouse mating takes place several weeks before beech seeds ripen, and to the present day it remains unclear how dormice achieve optimized reproductive output in reflection of the quantity of food available in the future. The first aim of this field study carried out over 13 years was thus to investigate the relationship between beech masting and reproductive performance in edible dormice in Germany. If food availability in spring influenced litter size, this would partially explain observed natural variability in offspring numbers. We thus chose an experimental approach and provided supplemental food to edible dormice in the field. Our results showed that numbers and proportions of reproductively active females, as well as litter sizes, between 1993 and 2005 were positively correlated with beech mast. Food supplementation positively affected litter size and litters of food-supplemented females were found to be larger than those of unsupplemented females. Food-supplemented mothers and their offspring gained body mass considerably faster during lactation and were heavier at the end of the lactation period compared with controls. However, juvenile body size, as well as its increase, did not differ between the two treatments. Our results suggest a link between edible dormice reproductive output and food availability after emergence from hibernation.
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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) | 0.001 | 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".