Tamarack response to salinity: effects of sodium chloride on growth and ion, pigment, and soluble carbohydrate levels
Bibliographic record
Abstract
The extraction of bitumen from oil sands can increase levels of sodium and chloride in boreal forest soils. A study was designed to test the effect of 30 and 60 mmol/L NaCl on 6-month-old tamarack (Larix laricina (Du Roi) K. Koch.) seedlings grown in aerated nutrient solutions. After 40 days of treatment in a growth chamber, 30 mmol/L NaCl caused injury to old needles and decreased shoot biomass, root potassium concentration, root soluble carbohydrate content, as well as chlorophyll a, chlorophyll b, and carotenoid levels in old needles. Sodium content of seedlings exposed to 30 mmol/L NaCl was higher in roots than in stems and new needles, while chloride content was higher in both old and new needles. Sodium and chloride concentrations were similar in new needles and in old needles. Seedlings exposed to 60 mmol/L NaCl showed injury in both old and new needles and lower root and shoot biomass, root magnesium and potassium concentrations, and both root and stem soluble carbohydrate levels. Furthermore chlorophyll a, chlorophyll b, and carotenoid levels were lower in all needles than in the control. Sodium and chloride contents of seedlings treated with 60 mmol/L NaCl were higher in old and new needles than in roots and stems. The results suggest that tamarack seedlings have a moderate tolerance to salinity, and when exposed to 30 mmol/L NaCl the seedlings could avoid injury by maintaining a relatively high K+/Na+ ratio in new needles and controlling Na+ transport to the shoots.
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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) | 0.001 | 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".