Hydraulic adjustment in jack pine and black spruce seedlings under controlled cycles of dehydration and rehydration
Bibliographic record
Abstract
Drought adjustments were compared in black spruce (Picea mariana[Mill] B.S.P), and jack pine (Pinus banksiana[Lamb.]) by subjecting seedlings to five cycles of dehydration and rehydration. A computer-controlled root misting chamber system, supplied low (-1.5 MPa), moderate (-2.0 MPa), and severe (-2.5 MPa) dehydration, respectively, in cycles 1, 3 and 5. Although cell water relations failed to adjust to chronic dehydration, there was limited osmotic adjustment in black spruce (cycle 3), and water was re-allocated from the apoplast to the symplast in jack pine (cycles 1 and 3). Dehydration postponement was more important than dehydration tolerance. Jack pine was better able to postpone dehydration than black spruce. Specific conductivity, the hydraulic conductivity per unit stem cross-sectional area, was lower in jack pine and slower to decline during chronic dehydration. When specific conductivity was corrected for the greater leaf area in black spruce, the leaf-specific conductivity did not differ in the two species. There was no increase in needle leakage in jack pine and stomata in jack pine seedlings reopened fully after rehydration. Black spruce was more of a 'water spender', and less water stress (-2.0 MPa, cycle 3) was required to lower specific conductivity, compared to jack pine (-2.5 MPa, cycle 5). Leakage from needle membranes increased in black spruce, and stomata failed to reopen after rewatering (cycles 3 and 5). A greater needle area, smaller root system, and a higher specific conductivity lowered the water stress threshold for cavitation in black spruce, which is confined to moister sites in the boreal forest. Jack pine had a larger root system, smaller needle area and lower specific conductivity than black spruce. Because of these static features, jack pine is more drought tolerant and it is often found on sites that are too hot and dry for black spruce.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".