Impact of vessel traffic on the home ranges and movement of shorthorn sculpin (<i>Myoxocephalus scorpius</i>) in the nearshore environment of the high Arctic
Bibliographic record
Abstract
Sea ice reduction in the Arctic is allowing for increased vessel traffic and activity. Vessel noise is a known anthropogenic disturbance, but its effects on Arctic fish are largely unknown. Using acoustic telemetry — Vemco positioning system — we quantified the home ranges and fine-scale movement types (MT) of shorthorn sculpin (Myoxocephalus scorpius), a common benthic Arctic fish, in response to vessels and environmental drivers during open water over 3 years (2012–2014). Low overlap of core home ranges (50%) for all years and a change of overall MT proportions (significant in 2012 only) were observed when vessels were present compared with absent. However, changes in MTs associated with vessel presence were not consistent between years. Photoperiod was the only environmental driver that influenced (R2 = 0.32) MTs of sculpin. This is the first study of vessel impacts on Arctic fish using acoustic telemetry and demonstrates that individuals alter their behavior and home ranges when vessels are present. Given increasing vessel traffic in the Arctic, additional study on the impact of vessels on these ecosystems is warranted.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".