Irrigation Control and Physiological Responses of Nursery-grown Black Spruce Seedlings (1+0) Cultivated in Air-slit Containers
Bibliographic record
Abstract
Air-slit containerized ( IPL 25-350A ) black spruce [ Picea mariana (Mill) BSP; 1+0] seedlings, were subjected to four irrigation regimes (IR-15%, IR-30%, IR-45%, and IR-60%, by volume, cm 3 water/cm 3 substrate) under tunnel conditions in a forest nursery. Irrigation regimes were controlled by time-domain reflectometry during the first growing season. With exception of midday water potential, water relation and gas exchange variables were unaffected by substrate water content. There were no significant differences in height, diameter or number of needle primordia of the seedlings grown under IR-15%, IR-30%, and IR-45%. Seedlings grown in a substrate with a high water content (IR-60%) had lower oven-dry biomass and higher cuticular transpiration rates than seedlings grown under the three other irrigation regimes. Root hydraulic conductivity was not affected by irrigation regime, but showed a general decrease towards the end of the growing season. Variation in root hydraulic conductivity was most likely related to root growth and degree of lignification. Seedlings that had been exposed to IR-60% during the first growing season remained smaller than the other seedlings throughout the second growing season. Results of this study indicate that nursery managers can reduce the quantity of irrigation water used without significantly affecting the growth or physiology of air-slit containerized black spruce seedlings (1+0) grown under tunnel conditions.
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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) | 0.001 | 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".