Scatter-hoarding birds disperse seeds to sites unfavorable for plant regeneration
Bibliographic record
Abstract
Scatter-hoarding birds provide effective long-distance seed dispersal for plants. Transporting seeds far promotes population spread, colonization of new areas, and connectivity between populations. However, whether seeds transported over long distances are deposited in habitats favorable to plant regeneration has rarely been investigated, mainly due to methodological constraints. To investigate dispersal patterns and distances of Swiss stone pine (Pinus cembra) seeds we utilized advances in tracking technology to track the movements of their sole disperser, the spotted nutcracker (Nucifraga caryocatactes). We found routine individual movements between single seed harvesting and seed caching site. Harvesting sites of individual birds overlapped, whereas seed caching sites were separated and located on average 5.3 km away from the harvesting site. Interestingly, most distant caching sites were located at low elevations and in spruce forest, where Swiss stone pine does not naturally occur. This suggests that nutcrackers disperse seeds over long distances but that a large portion of these seeds are cached outside the known pine habitat. Therefore, we conclude that the implications of such long-distance seed dispersal movements for plant populations should be carefully considered in combination with the effects of habitat quality on plant recruitment.
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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".