Pinus devoniana LIKELY AVOIDS DROUGHT STRESS BY DELAYING SHOOT ELONGATION
Bibliographic record
Abstract
Understanding the growth rate and the timing of conifer seedling bud elongation can be useful in selecting tree species for commercial plantations and ecological restoration, either under the current climate or to adapt to climatic change. Shoot growth dynamics of three dominant Pinus species of the pine-oak forest of the Nuevo San Juan Parangaricutiro indigenous community in Western Mexico were inspected. Using a common garden trial of three species and seven provenances, growth was related to contemporary (1961-1990 period averages) and future (rcp6.0 ensemble and decade centered on year 2060) climate. Significant differences between specieswere found in two-year-old plants, P. pseudostrobus and P. leiophylla showed greater shoot elongation and plant height, larger elongation period and plant height, and later growth cessation than P. devoniana, P. pseudostrobus and P. leiophylla, which begin their growth and elongate their shoots during the warm, dry season (March to May). Pinus devoniana delays the start of growth until the end of the dry season (end of May). This suggests that P. devoniana, at least for the second year of growth, probably avoids drought stress by delaying shoot elongation, which could partly explain why this species grows at lower altitude than the other pines. Climate change projections for Mexico indicate an increase in aridity conditions by the year 2060, particularly for the lower altitudinal limit of the populations of P. pseudostrobus and P. leiophylla. Reforestation with P. devoniana might be required at the lower altitud limits of these pines if forest decline continues.
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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 | 0.000 |
| 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 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".