Factors affecting distribution of wood, detritus, and sediment in headwater streams draining managed young-growth red alder conifer forests in southeast Alaska
Bibliographic record
Abstract
Factors (riparian stand condition, management regimes, and channel properties) affecting distributions of wood, detritus (leaves and branches), and sediment were examined in headwater streams draining young-growth red alder (Alnus rubra Bong.) conifer riparian forests (< 40 years old) in southeast Alaska. More riparian red alder were found along streams affected by both timber harvesting and mass movement than in streams affected by timber harvesting alone. Young-growth stands produced little large wood material (diameter ≥10 cm) and had little effect on altering the size distribution of functional large wood in channels, although more alder wood pieces were found in streams with greater numbers of riparian alder trees. Legacy wood pieces (>40 years old) remained in channels and provided sites for sediment and organic matter storage. Despite various alderconifer mixtures and past harvesting effects, the abundance of large wood, fine wood, and detritus accumulations significantly decreased with increasing channel bank-full width ( 0.53.5 m) along relatively short channel distances (up to 700 m). Changes in wood, detritus, and sediment accumulations together with changes in riparian stand characteristics create spatial and temporal variability of in-channel conditions in headwater systems. A component of alder within young-growth riparian forests may benefit both wood production and biological recovery in disturbed headwater stream channels.
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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) | 0.000 | 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".