Effects of log booms on physical habitat, water quality, and benthic invertebrates in the lower Fraser River and estuary
Bibliographic record
Abstract
To facilitate the movement and processing of timber in some regions of the Pacific Northwest, logs are tied together to form large rectangular rafts (often called “booms”) which are transported and stored in aquatic environments. In the lower Fraser River, British Columbia, some reaches have >50% of shoreline with adjacent log booms, yet our understanding of the effects of log booms on habitats and biota is very limited. We compared sites that have never had log booms to nearby ones with active boom storage occurring to examine differences in environmental characteristics. In contrast to reference sites, nearly all active sites had compacted sediments and little vegetation coverage, likely caused by logs “grounding” onto benthic environments due to tidally influenced water level changes. Total benthic invertebrate abundance was higher at reference sites which had relatively more Amphipoda and Trichoperta, but fewer Haplotaxida, compared to active sites whose compacted and more detrital-laden sediments should favour haplotaxids. Water quality variables generally did not differ between reference and active sites. Grounding of log booms and contact with the below substrate is in contradiction of best management practices and has clear effects on the physical habitat and biota of the area underneath booming sites.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".