Effects of mulching and insecticides on establishment and growth of Norway spruce
Bibliographic record
Abstract
Establishment of Norway spruce (Picea abies (L.) Karst.) seedlings is often restricted by competition from vegetation, drought, and damage by pine weevils. In this study, effects of mulching on these factors were investigated. Norway spruce seedlings were planted on fresh and 1-year-old clearcuts treated with mulch on three sites in southern Sweden. Mulch was made of slash from the old stand and applied on whole blocks at three different depths: 0, 10, and 20 cm. Both insecticide-treated and untreated seedlings were planted. By reducing the competing vegetation and improving soil moisture and mineralization, mulching created a favorable growth environment. Mulching significantly improved growth in terms of height, diameter, and volume of the seedlings. Growth continued to increase over time in mulched treatments, probably as an effect of increased nutrient availability. The 20 cm mulch layer generated the greatest increase in growth throughout the 10-year experimental period. Soil moisture was preserved under the isolating mulch layer and during periods of drought soil water potential was significantly higher in mulched treatments. After 2 years, percent cover of competing vegetation was 50%–60% without mulch and 10%–20% with a mulch depth of 20 cm. Insecticide-treated seedlings achieved a survival rate close to 100% in all mulching treatments, whereas survival among untreated seedlings was only 40% on some clearcuts. Mulching alone did not affect survival or abundance of pine weevils.
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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".