Water and Photosynthetic Rate Flows Under Drought Conditions in a Cork Oak (Quercus suber L.) Forest of Tunisia
Bibliographic record
Abstract
Relationships between drought, carbon and water fluxes have been rarely studied in south Mediterranean forests. The present research focused on the determination of seasonal and annual water and carbon fluxes of Quercus suber L. forests in northern Tunisia. The methodology was based on the calculation of the standard precipitation index, measurements of trees sap flow and net photosynthesis. Estimations of photosynthesis and transpiration during the 1965-2003 period were used on crop coefficients and water use efficiency terms. Results indicate a wide evapotranspiration rates fluctuating from 354 mm y-1 to 784 mm y-1 with an average value of 553 mm y-1. Extreme values of the standard precipitation index were -2.4 and +2.7. The carbon flux ranged from 0.255 to 0.586 kg y-1 m-2 with a mean value of 0.448 kg y-1 m-2 while average water efficiency reached 0.8 gr C kg-1 H2O. Despite the fact, that there is a significant difference between the four studied sites and important annual variability of carbon fluxes, the correlations between water and carbon fluxes and drought index were very low. The results clearly indicate that deep transformations are occurring in the Quercus suber L. forests, as a result of carbon dioxide fertilization being cancelled by the drought effect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".