Successional shifts in tree demographic strategies in wet and dry Neotropical forests
Bibliographic record
Abstract
Tropical forest succession and associated changes in community composition are driven by species' demographic rates, but how demographic strategies shift during succession remains unclear. To identify generalities in demographic trade-offs and successional shifts in demographic strategies, we quantified demographic rates of 787 tree species from two wet and two dry Neotropical forests. Across all forests, we found two demographic trade-offs -- the growth--survival and the stature--recruitment trade-off -- enabling the data-driven assignment of species to five demographic strategies. Fast species dominated early in succession and were then replaced by long-lived pioneers in three forests. Intermediate and slow species increased in basal area over succession but in contrast to the current conceptual model, long-lived pioneers continued to dominate until the old-growth stage in all forests. The basal area of short-lived breeders was low across all successional stages. These results increase the mechanistic understanding and predictability of Neotropical forest succession.
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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 | 0.001 | 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".