Relative energy and perceived impact of vessel-generated waves in fetch-limited environments
Bibliographic record
Abstract
Houser C, Carswell A, Chittle B, Johnson G, Caschera A, Smith A. 2024. Relative energy and perceived impact of vessel-generated waves in fetch-limited environments. Lake Reserv Manag. 40:285–302Vessel-generated waves (or wakes) are perceived as an important stressor in both marine and freshwater systems, and they are an increasingly important focus of coastal management. Recent studies suggest that wakes account for a significant portion of the total wave energy in fetch-limited environments and in turn have the potential to resuspend sediment, erode shorelines, degrade water quality, damage infrastructure, and disrupt aquatic ecosystems, in addition to being considered a safety hazard and a nuisance. To assess the relative contribution of wakes to the total wave energy, monitoring was completed at 32 sites across 7 fetch-limited lakes in Ontario, Canada between 2020 and 2023. The percent wake energy was inversely related to the average fetch length, with deviations to the relationship dependent on whether the site was open, an embayment or along a narrow section of the lake. A survey of property owners and residents suggests that the perceived impact of wakes also varies with the fetch length. Shoreline erosion and degraded water quality were identified as primary impacts of wakes in lakes with the smallest average fetch, but very few respondents provided direct evidence of boat wake impacts. Most respondents described vessel operation, experience of the vessel operator and conflict over different boating uses as the primary issues associated with wakes. While boat wakes may contribute a significant portion of the wave energy in fetch-limited lakes, further research is required to determine when and where they may represent a physical and ecological stressor rather than being just a nuisance.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".