The Evolution of Annual and Perennial Plant Life Histories: Ecological Correlates and Genetic Mechanisms
Bibliographic record
Abstract
Flowering plants exhibit two principal life-history strategies: annuality (living and reproducing in one year) and perenniality (living more than one year). The advantages of either strategy depend on the relative benefits of immediate reproduction balanced against survivorship and future reproduction. This trade-off means that life-history strategies are associated with particular environments, with annuals being found more often in unpredictable habitats. Annuality and perenniality are the outcome of developmental genetic programs responding to their environment, with perennials being distinguished by their delayed competence to flower and reversion to growth after flowering. Evolutionary transitions between these strategies are frequent and have consequences for mating systems and genome evolution, with perennials being more likely to outcross with higher inbreeding depression and lower rates of molecular evolution. Integrating expectations from life-history theory with knowledge of the developmental genetics of flowering and seasonality is required to understand the mechanisms involved in the evolution of annual and perennial life histories.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".