Microclimatic and soil moisture responses to gap formation in coastal Douglas-fir forests
Bibliographic record
Abstract
The effects of gap formation on solar radiation, soil and air temperature, and soil moisture were studied in mature coniferous forests of the Pacific Northwest, U.S.A. Measurements were taken over a 6-year period in closed-canopy areas and recently created gaps in four stands of mature (90140 years) and old-growth (>400 years) Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forest in the western Cascade Range of central Oregon and southern Washington. Gap sizes ranged from 40 to 2000 m 2 . Summer solar radiation levels and soil temperatures differed significantly among gap sizes and positions within gaps and were driven primarily by patterns of direct radiation. Nevertheless, effects on air temperature were slight. Soil moisture was more abundant in gaps than in controls, was most abundant in intermediate gap sizes, and tended to decline during the growing season in single-tree gaps and on the north edges of large gaps. However, there was substantial variation in moisture availability within individual gaps, primarily related to the variety of organic substrates present. Moisture in gaps declined over multiple years, likely caused by encroachment of vegetation within and around gaps. Low light levels probably limit filling of natural gaps in these forests, but the variety of microenvironments in large gaps may facilitate diverse plant communities.
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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) | 0.000 | 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".