Fearfulness of geese and swans on cropland in winter: A multi-species Flight Initiation Distance approach
Bibliographic record
Abstract
Geese and swans are focal species in conservation and in management aimed at reducing crop damage. In the former disturbance should be minimized, and in the latter it is important to know how different species react to scaring activities. Previous research about trade-off between predation risk and foraging in birds often use ‘Flight Initiation Distance’ (FID) as a proxy to compare fearfulness under different circumstances and among species. We studied variation in FID in geese and swans by species, flock size and composition, time of day, and body size (408 scaring trials on agricultural land in winters 2018—2021). In single-species flocks mean FID decreased in the order: bean goose (171 m) > greylag goose (104 m) > whooper swan (102 m) > Canada goose (92 m) > barnacle goose (77 m). In line with predictions based on body mass, the lightest species (barnacle goose) was the least fearful, but contrary to prediction neither of the two heaviest species (whooper swan, Canada goose) was the most fearful. FID was negatively correlated with flock size in bean goose. Flock size and FID did not correlate in greylag, Canada, and barnacle geese. FID did not differ between morning and afternoon in the 4 species with >20 single-species trials (i.e., supposedly hungry versus satiated geese). When in multi-species flocks, FID differed less among species, converging in the 108—138 m range. For example, bean goose FID decreased significantly whereas it increased significantly in barnacle and greylag geese. Barnacle goose (protected from open hunting in EU) was less fearful than species with an open hunting season in the EU, implying that exposure to hunting affect species-specific FID. We show that the level of fearfulness varied among swan and goose species, making it necessary to adopt diverse strategies in conservation as well as crop protection.
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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 | 0.000 | 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".