Drought tolerance characteristics of black spruce (<i>Picea mariana</i>) seedlings in relation to sodium sulfate and sodium chloride injury
Bibliographic record
Abstract
This study examined the feasibility of using water relations to screen black spruce (Picea mariana (Mill.) BSP) planting stock for salt tolerance, prior to planting in saline oil sands tailings. To do so, water relations parameters were derived from pressurevolume curves for individual seedlings prior to salt stress treatments. Pressurevolume curves were constructed for branches removed from the seedlings and the seedlings were subsequently treated with 60 mM NaCl, 120 mM NaCl, or 90 mM Na2SO4in solution culture. After 2 weeks of treatment, seedlings treated with NaCl solutions had greater needle electrolyte leakage and visible needle injury compared with equimolar and iso-osmotic solutions of Na2SO4, suggesting that chloride played a role in needle injury. At turgor loss point, a more negative osmotic potential was significantly correlated with lower electrolyte leakage in seedlings treated with Na2SO4but not in those treated with NaCl. The results suggest that, in contrast with NaCl, Na2SO4injury to black spruce seedlings may be largely due to osmotic stress and that drought tolerance parameters may be more helpful in predicting salt tolerance in plants treated with Na2SO4than in those treated with NaCl.Key words: osmotic stress, salt stress, drought tolerance, water relations, ion toxicity, black spruce.
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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) | 0.000 | 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".