Spacial patterns of soil temperature and moisture across subalpine forest-clearcut edges in the southern interior of British Columbia
Bibliographic record
Abstract
To investigate if timber harvesting influences spatial patterns of soil micro climate, forest floor soil temperature and moisture were examined across forest-clearcut edges. Transects were sampled during the 2000 growing season across a 1-ha clearcut at a subalpine forest site in the southern interior of British Columbia, Canada. Forest floor temperature measurements were made twice, once under sunny and once under overcast conditions. Moisture status, measured under wet and dry conditions, was expressed as gravimetric and volumetric moisture content and matric potential. Wavelet analysis was used to detect and compare the location of edges in soil properties, and variance partitioning was used to examine the environmental and spatial sources of variability in temperature and moisture. Based on the wavelet analyses, the transition zone, in both temperature and moisture between forest and clearcut occurred at 7–15 m into the clearcut from the south edge and at 8–18 m into the forest from the north edge. Spatial patterns were consistent between clear and overcast conditions and wet and dry conditions. Distance from the edge was a minor source of spatial variability in temperature and moisture relative to the strong contrast between forest and clearcut conditions. The edge influences may have implications for nutrient cycling, plant available water and forest regeneration. Key words: Soil temperature, soil moisture, forest floor, subalpine forest, wavelet analysis, edge effects
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".