Bibliographic record
Abstract
Constraints on plant distributions resulting from seed limitation (i.e. dispersal filters) were evaluated on two scales of ecological organization on islands off the coast of British Columbia, Canada. First, island plant communities were separated into groups based on fruit morphology, and patterns in species diversity were compared between fruit‐type groups. Second, abundance patterns in several common fleshy‐fruited, woody angiosperm species were compared to species‐specific patterns in seed dispersal by birds. Results from community‐level analyses showed evidence for dispersal filters. Dry‐fruited species were rare on islands, despite being common on the mainland. Island plant communities were instead dominated by fleshy‐fruited species. Patterns in seed dispersal were consistent with differences in diversity, as birds dispersed thousands of fleshy‐fruited seeds out to islands, while dry fruited species showed no evidence of mainland‐island dispersal. Results from population‐level analyses showed no evidence for dispersal filters. Population sizes of common fleshy‐fruited species were unrelated to island isolation, as were rates of seed dispersal. Therefore, island isolation distances were not large enough to impose constraints on species’ distributions resulting from seed limitation. Rates of seed dispersal were also unrelated to island area. However, several species increased in abundance with island area, indicating post‐dispersal processes also help to shape species distributions. Overall results suggest that seed dispersal processes play an important role in determining the diversity and distribution of plants on islands. At the community‐level, dry‐fruited species were seed limited and island communities were instead dominated by fleshy‐fruited species. At the population‐level, common fleshy‐fruited species were not seed limited and showed few differences in distribution among islands. Therefore, although evidence for dispersal filters was observed, their effects on plant distributions were scale‐dependent.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".