Effects of pH and Mineral Nutrition on Growth and Physiological Responses of Trembling Aspen (Populus tremuloides), Jack Pine (Pinus banksiana), and White Spruce (Picea glauca) Seedlings in Sand Culture
Bibliographic record
Abstract
) seedlings to root zone pH ranging from 5 to 9 were studied in sand culture in the presence of two mineral nutrition levels. After eight weeks of treatments, effects of pH on plant dry weights varied between the plant species and were relatively minor in white spruce. Higher nutrient supply significantly increased dry weights only in trembling aspen subjected to pH 5 treatment. There was little effect of pH and nutrition level on net photosynthesis and transpiration rates in white spruce and jack pine, but net photosynthesis markedly declined in aspen at high pH. Chlorophyll concentrations in young foliage decreased the most in trembling aspen and jack pine. The effects of high pH treatments on the concentrations of Mg, P, Ca, Mn, Zn, and Fe in young foliage varied between the plant species with no significant decreases of Fe and Zn recorded in trembling aspen and white spruce, respectively. This was in contrast to earlier reports from the studies carried out in hydroponic culture. The sand culture system that we developed could be a more suitable alternative to hydroponics to study plant responses to pH in the root zone. Plant responses to high pH appear to involve complex events with a likely contribution of nutritional effects and altered water transport processes.
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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 | 0.000 |
| 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".