Variability in snow accumulation patterns within forest stands on the interior plateau of British Columbia, Canada
Bibliographic record
Abstract
Abstract Previous research has highlighted the relationship between snow accumulation and forest stand characteristics, as well as the effects of topography, but not the variability within stands. This study examined spatial patterns in snow accumulation within forest stands, their consistency from year to year, and the extent to which they can be predicted from commonly used stand measurements. Snow water equivalent (SWE) was measured on or near April 1, 1995 to 1997, and a forest inventory was completed at 64 points (15‐m grid spacing) in each of nine stand types including mature and juvenile forests and clearcuts. Semivariograms revealed little evidence of spatial correlation among sample points, indicating that each sample could be considered statistically independent for analysis. Within the study stands, no strong spatial trends were evident through quadratic trend surface analysis. The within‐stand coefficient of variation (CV) generally decreased with increasing mean accumulation. Spearman's rank correlation analysis and principal components analysis (PCA) indicated a weak to moderate similarity in snow accumulation patterns from year to year. Site‐scale canopy measures do not appear to provide a reliable basis for parameterizing the variability of within‐stand snow deposition. Through the fitting of general linear models (GLM), year alone accounted for 33% of the variability in snow water equivalent within stands, on average. Of the stand inventory variables measured, crown closure explained the largest proportion of the variability in SWE within each stand, but together with year never more than 43%. The strongest correlations between snow water equivalent and crown closure were found in those stands exhibiting the greatest consistency in interannual spatial patterns of snow accumulation. Copyright © 2006 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 teacher head, 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".