Plant Trait Assembly in Species-Rich Forests at Varying Elevations in the Northwest Andes of Colombia
Bibliographic record
Abstract
Andean forests are home to a strikingly high diversity of plants, making it difficult to understand the main drivers of species assembly. Trait-based approaches, however, help overcome some challenges associated with high taxonomic complexity, providing insights into the main drivers of species coexistence. Here, we evaluated the roles of climate, soil fertility, and symbiotic root associations on shaping the assembly of six plant functional traits (leaf area, specific leaf area, dry leaf matter content, leaf thickness, leaf toughness, and wood density) along an elevational gradient in the species-rich northwestern Andean forests of Colombia. The two main axes of the correspondence RLQ analysis explained 95.75% of the variability. The first axis was associated with the leaf economic spectrum, while the second axis with the tradeoff between growth and survival. Furthermore, the fourth corner method showed that both regional (climatic variables) and local factors (soil fertility, symbiotic root associations, and light distribution) played a key role in determining plant trait assembly. In summary, our study emphasizes the importance of considering both individual size and local factors to better understand drivers of plant trait assembly along environmental gradients.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".