Global biogeography of seed dormancy is determined by seasonality and seed size: a case study in the legumes
Bibliographic record
Abstract
Seed dormancy is expected to provide ecological advantages by adjusting germination to the favorable growth period. However, many species produce nondormant seeds, particularly in wet tropical forests, a biogeographic pattern that is not well accounted for in current models. We hypothesized that the global distribution of dormant seeds derives from their adaptive value in predictably fluctuating (i.e. seasonal) environments. However, the advantage conferred by dormancy might ultimately depend on other seed attributes, particularly size. This general model was tested within a phylogenetically informed framework using a data set comprising > 216 000 world-wide observations of Fabaceae, spanning three orders of magnitude in seed size and including both dormant and nondormant seeds. Our results confirmed our hypothesis: nondormant seeds can only evolve in climates with long growing seasons and/or in lineages that produce larger seeds. Conversely, dormancy should be evolutionarily stable in temperate lineages with small seeds. When the favorable season is fleeting, seed dormancy is the only adaptive strategy. Based on these results, we predict that, within a given lineage, taxa producing larger, nondormant seeds will necessarily predominate in aseasonal environments, while plants bearing small, dormant seeds will be dominant under short growing seasons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".