Integration of soil moisture, xylem water potential, and fall–spring herbicide treatments to achieve the maximum growth response in newly planted Douglas-fir seedlings
Bibliographic record
Abstract
Early in the establishment of Pacific Northwest Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) plantations, herbaceous vegetation can decrease seedling growth through competition for soil moisture during the dry summer months. This study was designed to statistically quantify soil moisture, seedling xylem water potential (Ψ), vegetation community, and seedling growth response to six herbicide treatment regimes commonly applied over the first 2 years of establishment. When compared with the control, soil moisture and seedling Ψ increased in response to reductions in competitive cover, allowing seedlings to extend productive growing time from 28 to 80 days. As a result, seedling volume growth increased from 56 cm 3 in the untreated control to greater than 250 cm 3 for the most intensive herbicide treatment regimes. Vegetation surveys revealed that treatment regimes had the potential to provide a disturbance, which could shift community composition from native to introduced species as the relationship decreased from 10:1 to 2:1. The most intense herbicide treatment regime reduced cover below 20%, retained soil moisture >30%, maintained predawn seedling Ψ above –1.0 MPa, and decreased height to diameter ratio below 50, increasing the likelihood of successful plantation establishment.
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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 | 0.002 | 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".