Tolerance to low leaf water status of tropical tree seedlings is related to drought performance and distribution
Why this work is in the frame
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Bibliographic record
Abstract
Habitat specialization models predict that adaptations to environmental conditions explain species distributions. In tropical rainforests, the ability of the seedlings to survive during drought has been shown to be a key determinant of species distributions. We hypothesize that differences among species in their tolerance to low tissue water status is the mechanism underlying differences in performance during drought. 2. To test this hypothesis we quantified tolerance to low leaf water status for over 20 species from central Panama in screenhouse experiments using two different experimental approaches. Results from both approaches were highly correlated with each other. 3. We found that tolerance to low leaf water status correlated with species drought performance in the field and with their distribution across a gradient of dry season length, with the more desiccationtolerant species having higher survival in dry relative to irrigated conditions, and occurring in drier areas. These results support the hypothesis that, in tropical forests, tolerance to low tissue water status governs seedling performance during drought, as well as being a determinant of species distribution patterns. 4. Lower tolerance to low leaf water status was correlated with greater stem hydraulic conductance. In addition, all species tested, including both desiccation-sensitive and desiccation-resistant species, showed similar losses of xylem conductance, about 80%, when near death. These results suggest that a principal mechanism by which desiccation leads to plant mortality is the loss of xylem conductivity.
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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) | 0.001 | 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 it