Predation by red fox on European roe deer fawns in relation to age, sex, and birth date
Bibliographic record
Abstract
Mortality in radio-marked European roe deer (Capreolus capreolus (Linnaeus, 1758)) neonates was studied during 14 years in a mixed forestagricultural landscape in Sweden. A total of 233 fawns were marked. Births were synchronized, with 79% occurring during 25 days and a peak between 25 May and 7 June encompassing 62% of the births. Overall mortality was 42%, but in three single years, it exceeded 85%. Predation by red fox (Vulpes vulpes Desmarest, 1820) accounted for 81% of total mortality. The effects of age, sex, and time of birth on the vulnerability to predation were analysed. Fawns born just after the birth peak had the lowest predation risk. Predation rate was highest for the fawns that had the very earliest or the very latest birth dates. Predation thereby seems to strengthen the birth synchrony in roe deer. Contrary to earlier published findings, there was no difference in susceptibility to predation between the sexes. Also differing from earlier findings was that predation rate was highest during the first week of life and declined thereafter almost linearly. The majority of the fawns (85%) were killed before 30 days of age and 98% before 40 days. Different types of landscapes may explain the discrepancies between our study and earlier findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".