Mechanisms and source distances for the input of large woody debris to forested streams in British Columbia, Canada
Bibliographic record
Abstract
The geomorphic process domain concept predicts consistent associations between stream channel geomorphology and large woody debris (LWD) input mechanisms. We used synoptic surveys at 51 stream reaches adjacent to undisturbed mature or old-growth forests in central and southern British Columbia to test associations between stream geomorphology and the input processes, source distances, physical characteristics, and geomorphic functions of LWD within the bankfull channel. Standing dead tree fall was the dominant input mechanism, but bank erosion was important in low- and medium-gradient channels >3 m bankfull width. Wind-induced inputs (stem breakage and windthrow) were relatively more important in small or steep channels. LWD piece size and source distance varied among delivery processes. LWD originated at ground distances up to 65 m from the streams, but 90% of the LWD at a site originated within 18 m of the channel at 90% of the sites. Statistical models incorporating tree size and stream characteristics (bankfull width, channel type) explained 40%–64% of the variation among sites in the distances from which LWD entered streams. In general, LWD source distances increased with increasing tree height and decreased with increasing stream width; however, the strengths of these relationships were modified by channel type.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".