Individual behaviour shapes patterns of bird‐mediated seed dispersal
Bibliographic record
Abstract
Abstract Seed dispersal is a key component in a plant's life cycle, allowing the colonization of new habitat and eventually enabling range shifts. For animal‐dispersed plants, the behaviour of seed‐dispersing animals has direct consequences for the fate of a seed. However, there is little empirical evidence on how individual behaviour of animals affects seed dispersal. Here we investigated the effects of individual behaviour on seed dispersal distance and location by analysing movement data of spotted nutcrackers (Nucifraga caryocatactes) during harvest and scatter‐hoarding of Swiss stone pine (Pinus cembra) seeds. To assess individual variation in seed dispersal patterns, we compared daytime hourly displacement patterns across individuals. We further identified seed caching locations of individual birds and analysed their potential for pine regeneration. We found that nutcrackers showed one of two distinct behaviours: short‐distance seed dispersal and long‐distance seed dispersal. The caching locations resulting from the two behaviours differed markedly in the regeneration potential of Swiss stone pine: seeds transported over short distances were cached at high elevations with high regeneration potential within the pine's current habitat, while seeds transported over long distances were cached at low elevations with low regeneration potential outside of the pine's habitat. The behaviours were not associated with bird body mass, relative wing length or sex. Our results emphasize that intraspecific individual behaviours of seed‐dispersing animals can have far‐reaching consequences for ecosystem functions. As a major determinant of seed dispersal dynamics, individual behaviour should be taken into account for a better understanding of ecosystem functions under current and future environmental conditions. Read the free Plain Language Summary for this article on the Journal blog.
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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) | 0.002 | 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".