Effet d’un assèchement édaphique sur la croissance, l’allocation de biomasse et les relations hydriques chez <i>Casuarina glauca</i>
Bibliographic record
Abstract
Tunisia has vast land tracts that are marginal, arid, semiarid, or desert (about three quarters of the surface of the country). Reforestation of these regions is one of the methods being used to rehabilitate degraded areas. Casuarina glauca Sieber, a fast-growing tree species that is widely used outside of its native range, was tested in the present study with respect to its degree of acclimatization and hardening in response to drought. Three water regimes, simulating the conditions of the reforestation sites, were applied to C. glauca seedlings. These regimes included a control treatment (T : predawn water potential Ψb = –0.2 MPa), a moderate stress treatment (M : Ψb = –0.5 MPa), and a severe stress treatment (S : Ψb = –1.0 MPa). Water relations parameters, estimated by pressure–volume curves through a repeat pressurization method, as well as accumulated dry mass were measured at the beginning of the experiment and 2, 4, and 6 months following treatment imposition. The total dry mass of M and S plants was significantly affected by the treatments. However, water stress favoured dry mass allocation to roots and decreased the shoot turgid mass / dry mass ratio (TM/DM). The evolution of water relations parameters under M or S regimes revealed an adaptive capacity of C. glauca seedlings, as expressed by a significant decrease of the osmotic potentials at full turgor (Ψπ100) and at the turgor loss point (Ψπ0), an osmotic adjustment in water-stressed plants reaching 0.31 and 0.56 MPa, and a significant increase in εmax reaching 26 % and 68 % of that of the control plants, respectively, at the end of the drought period. A reduction in shoot TM/DM combined with increases in εmax during water stress suggests the presence of a cell wall adjustment. These effects were more pronounced under the severe stress. Our results suggest that preconditioning seedlings to drought under nursery conditions by applying a moderate or severe stress, depending on the conditions of the planting site, for 4 months prior to outplanting, possibly will allow the seedlings to adapt morphologically and physiologically and improve their chance of survival in arid and semiarid zones.
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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 | 0.001 |
| 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".