Stand age and soils as drivers of plant functional traits and aboveground biomass in secondary tropical dry forest
Bibliographic record
Abstract
The distribution of tropical forest biomass across the landscape is poorly understood, particularly in increasingly common secondary tropical forests. We studied the landscape-scale distribution of edaphic properties, plant community characteristics, and aboveground biomass (AGB) in secondary tropical dry forests in northwest Costa Rica. We used structural equation modeling to examine conceptual models of relationships among these factors, with data from 84 0.1 ha plots. Stand age and soils explained 33%–60% of the variation in community-weighted mean values of foliar traits including specific leaf area, foliar nitrogen, phosphorus, and δ 13 C. Aboveground biomass ranged from 1.7 to 409 Mg·ha −1 among plots between 5 and >100 years old. Stand age alone explained 46% of the variation in AGB among plots, while a model including age, soil pH, traits, and forest type explained 58%. Stand age was the most important variable explaining the distribution of AGB and community characteristics in secondary forests. We speculate that plot size, landscape heterogeneity, disturbance history, and stand dynamics contribute to the unexplained variation in AGB across the landscape.
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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 | 0.001 | 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".