Shared space, individually used: spatial behaviour of non-breeding ravens (Corvus corax) close to a permanent anthropogenic food source
Bibliographic record
Abstract
Natal dispersal is a well-studied phenomenon that can be divided into three stages: (1) starting from an area, (2) wandering to another area and (3) either settling in that area to breed or merely temporarily stopping there before continuing to wander. During the third phase, we can distinguish breeders from non-breeders, which may show similar or different patterns of space use. Breeding Common Ravens are territorial year-round; non-breeders are highly vagrant but may gather at food sources and night roosts for varying lengths of time. In contrast to the wandering phase, little is known about the space use of ravens at such “stop” sites. Here, we used radio telemetry to investigate the space use of 21 non-breeding ravens in the Austrian Alps during a stop stage at an anthropogenic food source. The tagged ravens were present in 69.2 % of the relocation attempts. They used only 27.0 ha (range 6.7–59.7 ha, 95 % utilisation distribution) of the study area, and their activity ranges strongly overlapped with each other. However, within this shared space, sub/adult non-breeders could be found at individually distinct locations, while juveniles showed similar spatial distributions. These results, combined with reported long-distance movements, underline the high behavioural flexibility of non-breeding ravens, which may be a reason for their success in very different habitats throughout the Northern Hemisphere.
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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 | 0.001 |
| 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) | 0.001 | 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".