Growth of 10 Tree Species in Relation to Location and Microclimatic Gradients in a Strip Shelterwood
Bibliographic record
Abstract
Strip shelterwood systems are used in some areas to favour establishment of intolerant and moderately tolerant tree species or to facilitate harvesting. There is substantial variation in microclimate within cleared strips, which can influence survival and growth of regeneration. The growth of the established regeneration depends on the microclimate (light, soil moisture, air and soil temperature) at different locations in gaps. This poster presents results from a study being conducted at Nakusp in Southern BC, Canada. The purpose of this study is to improve our understanding of the microclimatic pattern after gap creation and its influence on the growth of planted seedlings of 10 native tree species. Preliminary results, collected 13 to 14 years after planting, show gradual increase of light and air temperature from the south to the north edge of the gaps. Soil moisture stress also increased from the south to the north edge. Species are showing variable growth response to these gradients. Shade intolerant species performed better at the centre and north edge of the gap, while shade tolerant species have survived and established well under the canopy and near the edges. Among the tree species evaluated, Western hemlock and Engelmann spruce were best suited to the south edge and in the intact forest, while Douglas fir performed best at north edge and inside the opening. Regardless of their shade tolerance classification, all the species grow best near the centre of the opening, where light levels are highest.
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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".