Rainfall and topographic position determine tree embolism resistance in Amazônia and Cerrado sites
Bibliographic record
Abstract
Abstract Droughts are predicted to increase in both frequency and intensity by the end of the 21st century, but ecosystem response is not expected to be uniform across landscapes. Here we assess the importance of the hill-to-valley hydrologic gradient in shaping vegetation embolism resistance under different rainfall regimes using hydraulic functional traits. We demonstrate that rainfall and hydrology modulate together the embolism resistance of tree species in different sites and topographic positions. Although buffered by stable access to groundwater, valley plants are intrinsically more vulnerable to drought-induced embolism than those on hills. In all study sites, the variability in resistance to embolism is higher on hills than on valleys, suggesting that the diversity of strategies to cope with drought is more important for tree communities on hills. When comparing our results with previously published data across the tropics, we show greater variability at the local scale than previously reported. Our results reinforce the urgent need to extend sampling efforts across rainfall regimes and topographic positions to improve the characterization of ecosystem resistance to drought at finer spatial scales.
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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 | 0.000 | 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) | 0.001 | 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".