Stable annual pattern of water use by Acacia tortilis in Sahelian Africa
Bibliographic record
Abstract
Water use by mature trees of Acacia tortilis (Forsk.) Hayne ssp. raddiana (Savi) Brenan var. raddiana growing in the northern Sahel was continuously recorded over 4 years. Water use was estimated from xylem sap flow measured by transient heat dissipation. Concurrently, cambial growth, canopy phenology, leaf water potential, climatic conditions and soil water availability (SWA) were monitored. In addition to the variation attributable to interannual variation in rainfall, SWA was increased by irrigation during one wet season. The wet season lasted from July to September, and annual rainfall ranged between 146 and 367 mm. The annual amount and pattern of tree water use were stable from year-to-year despite interannual and seasonal variations in SWA in the upper soil layers. Acacia tortilis transpired readily throughout the year, except for one month during the dry season when defoliation was at a maximum. Maximum water use of about 23 l (dm sapwood area)(-2) day(-1) was recorded at the end of the wet season. While trees retained foliage in the dry season, the decline in water use was modest at around 30%. Variation in predawn leaf water potential indicated that the trees were subject to soil water constraint. The rapid depletion of water in the uppermost soil layers after the wet season implies that there was extensive use of water from deep soil layers. The deep soil profile revealed (1) the existence of living roots at 25 m and (2) that the availability of soil water was low (-1.6 MPa) down to the water table at a depth of 31 m. However, transpiration was recorded at a predawn leaf water potential of -2.0 MPa, indicating that the trees used water from both intermediary soil layers and the water table. During the full canopy stage, mean values of whole-tree hydraulic conductance were similar in the wet and dry seasons. We propose that the stability of water use at the seasonal and annual scales resulted from a combination of features, including an extensive rooting habit related to deep water availability and an effective regulation of canopy conductance. Despite a limited effect on tree water use, irrigation during the wet season sharply increased predawn leaf water potential and cambial growth of trunks and branches.
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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 | 0.001 | 0.001 |
| 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".