Relations among larval tailed frogs, forest harvesting, stream microhabitat, and site parameters in southwestern British Columbia
Bibliographic record
Abstract
Amphibians are the most abundant vertebrates in many forests and have the potential to play a significant role in ecosystem dynamics. We examined the effects of logging on larval Ascaphus truei Stejneger in low-order streams. Density, biomass, and mean snoutvent length were greatest in streams flowing through old growth; however, effects associated with forest harvest depended on elevation, stream size, percent cover of sand, boulders, runs, and riffles. Density and biomass were highest in high-elevation streams where silt and algae were absent and where temperature and percent cover of sand were lowest. Larvae appeared to select pool, run, or riffle microhabitats depending on their body size or developmental stage, with larger and more developed larvae occupying faster stream sections. Logging history appears to have less influence on Ascaphus variables than do stream microhabitat and site. In our study, over 86% of the variation in both density and biomass was associated with stream and site parameters. Because our results suggest that forest disturbance has major impacts under only certain conditions, we recommend that the variability of stream microhabitat and site parameters be considered prior to making harvesting decisions when managing for Ascaphus and other organisms with similar habitat requirements.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".