Relationships between seed banks and spatial heterogeneity of North American alvar vegetation
Bibliographic record
Abstract
Abstract. This is the first quantitative study of seed bank characteristics in North American alvar habitats. We assessed seed bank density, species richness, and species composition in 75 plots distributed among five alvar sites in Bruce Peninsula National Park, Ontario, Canada, each of which displayed areas of high and low vegetation cover within the alvar and a fully forested perimeter area. Forested habitats immediately adjacent to alvar patches contained minimal seed banks for species restricted to the alvar patches. Open alvars contained less than 1% seeds from woody forest species. This suggests that forest is not invading adjacent alvar habitat via seeds and that adjacent forest does not contain a reservoir of alvar seeds. When compared to areas on the alvar with high vascular plant cover, areas with low cover contained a slightly smaller viable seed bank, but seed banks from high and low vegetation cover plots had similar species composition and species richness. High vegetation cover plots had slightly higher mean and maximum soil depths compared with low cover plots, but no differences in other physical and chemical parameters. Thus, spatial heterogeneity in plant cover is associated only weakly with heterogeneity in below-ground factors. Despite the availability of seed and soil resources, vegetation dynamics are constrained in areas with low plant cover, and thus alvar community development seems to respond non-linearly to resource availability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".