Why Marine Mammals Matter to Your Terrestrial Export Pipeline Project
Bibliographic record
Abstract
Increases in export pipeline development can result in a corresponding increase in marine transportation activities and the potential to escalate adverse interactions with marine wildlife. Ship traffic introduces risks of vessel strikes as well as the amount of underwater noise produced in the marine environment. Growing public and scientific concern over the potential effects of increasing ship traffic on marine wildlife mean that even terrestrially-based pipeline projects need to start considering the effects of shipping in developing environmental mitigation programs for their export operations. Northern Gateway is proposing to construct and operate twin pipelines between Alberta and British Columbia, and an associated tank and marine terminal for export operations. While Northern Gateway will not own or operate any of the tankers, they have committed to implementing a comprehensive marine mitigation, monitoring and research program, including measures to reduce ship strikes and effects of underwater noise on marine mammals. Vessel strikes can cause severe or fatal injuries. Higher relative risk exists where shipping traffic overlaps with increased densities of marine mammals. Vessel speed has been positively correlated with the degree of risk and injury; consequently, Northern Gateway has set maximum year-round speed restrictions of 10–12 knots for all Project-related tankers calling at the marine terminal, with further restrictions of 8–10 knots in key areas. Other large vessels in this region currently travel at speeds of 16–21 knots. Mandatory speed restrictions will also reduce the Project’s contribution to underwater noise. Effects of underwater noise on marine mammals include temporary habitat avoidance, reduced feeding efficiency, behavioural change, increased stress, and communication masking. Acoustic modeling conducted for the project predicted that reducing vessel speeds from 15 to 9.6 knots would decrease underwater noise input by nearly 12 dB, making the zone of ensonification 2–3 times smaller than in the absence of mitigations. Purpose-built escort tugs will use best commercially-available noise-quieting technology and speed restriction areas will be refined through six-years of surveys and a quantitative vessel strike analysis. Vessel traffic is not unique to Northern Gateway; however, through minimizing their incremental contribution, they hope to serve as an industry example. This approach to minimizing effects of routine marine export operations is unique in the shipping industry in Canada and the United States. If other proponents were to adopt similar types of measures, Northern Gateway believes that the marine environment would see some net benefits in terms of a reduction in adverse effects on marine mammals.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.089 | 0.018 |
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".