Effects of pine shelterwoods on microclimate and frost damage to Norway spruce seedlings
Bibliographic record
Abstract
Cuttings of Norway spruce, Picea abies (L.) Karst., were planted under two Scots pine, Pinus sylvestris L., shelterwoods with a density gradient varying from fully stocked forest to clearcuts. This provided a range of near-ground temperature and radiation regimes. The microclimate was monitored near each cutting, using an automated mobile system. The factors monitored were air temperature, global radiation, and net radiation. Frost damage to the spruce cuttings was assessed by two methods. First, the percentage of actively growing shoots with visible damage was determined. Second, the maximum photochemical efficiency of photosystem II (Fv/Fm) in 1-year-old and current-year needles was estimated from measurements of chlorophyll a fluorescence. A frost event in May 1990 was analysed using the partial least squares in latent variables (PLS) method of multivariate statistical analysis. Different microclimatic variables were used as predictors. Visible damage to actively growing shoots and the Fv/Fmratio in 1-year-old needles were used as response variables. The predictors were used to produce a separate PLS model for each response variable. Nocturnal net radiation during the frost event, and both the net and global radiation the day after, were found to be important for explaining the visible damage and the Fv/Fmratios. In both the PLS analyses, the modelling power of these three variables was ranked among the highest of all microclimatic factors tested. The accumulated air temperature below 0°C, the duration of the frost, and the minimum air temperature near the ground (at 0.4 m) also had high predictive power. Thus, both higher nocturnal air temperature near the ground and shading the day after the frost event were important factors explaining the reduction of visible damage and low-temperature induced photoinhibition. Leaving a dense shelterwood moderates both the nocturnal air temperature and the radiation regime and, therefore, is recommended on sites where early summer frosts are expected.
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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".