Stand mortality in buffer strips and the supply of woody debris to streams in Southeast Alaska
Bibliographic record
Abstract
We compared the stand conditions in buffer strips with those in unlogged riparian stands with similar site characteristics using large-scale aerial photography to deduce differences in stand mortality and large woody debris (LWD) recruitment. We found the cumulative stand mortality (CSM) was significantly greater in buffer units compared with reference units and that mortality varied with distance from the stream. In the inner zone (0–10 m from stream), the mean difference in CSM between buffer and reference units was relatively small (22% of unlogged CSM), but the CSM in the buffer units of the outer zone (10–20 m from stream) was more than double (120%) the CSM in the reference units. The greater CSM in the buffer units is primarily the result of a significant increase in mortality by windthrow at a small proportion (11%) of the logged units. We found that logging caused an increase in the proportion of tree recruitment to the stream from the outer zone of buffers and changed the shape of the LWD source distance recruitment curve. Based on our findings, we estimate the future potential supply of LWD is diminished by 10% compared with an unlogged reference stand.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".