Development of white spruce tree islands in the shrub zone of the forest-tundra. Arctic Antarctic Alpine Res
Bibliographic record
Abstract
ABSTRACT. The growth of four white spruce (Picea glauca) clonal islands ranging in age from ca. 98 years to more than 400 years was investigated in the shrub zone of the forest-tundra east of Churchill, Manitoba, Canada. The elongation of 20 similar-aged stems in each of the three youngest islands was monitored during 1988 and 1989, along with ground and air temperatures. Stems in the younger islands showed a more flexible response to both daily and annual variation in temperature. Younger islands showed faster recovery from frost events during elongation and longer periods of elongation in cooler years. Early spring warming that caused snowmelt to occur before the growing season appeared to result in moisture stress later in the period of elongation. In stems of spruce shrub, the branches are concentrated near ground level because growth is slow and adventitious buds develop on the stem after repeated loss of stem terminals through snow abrasion. In young trees, shading and increased moisture from trapped snow coincide with feather moss establishment and a deep active layer, resulting in higher ground temperatures and faster tree growth. It is during this early period of development that a tree may be best able to develop an erect stem. In later development, the lowest branches of trees become appressed, grow roots, and become second-order stems, and this process continues outward from the central stem. In older tree islands, peat accumulation and needle abrasion can lead to conditions less favourable for growth and maintenance of needles. Consequently, the canopy may thin, which reduces its ability to trap snow. When snow cover is reduced, lichen-heath establishes and permafrost intrudes into the mound. Subsequent growth of the secondary stems on the mound may be too slow to enable successful development of an erect stem. Thus, island development is largely dependent on
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 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".