Modelling Ship-Source Noise Impacts on Marine Mammals In Tallurutiup Imanga National Marine Conservation Area
Bibliographic record
Abstract
Climate change has influenced decreases in sea ice extent and thickness in the Arctic and facilitated a subsequent increase in marine traffic across the Canadian Arctic. Tallurutiup Imanga (TI), a unique National Marine Conservation Area (NMCA) which is home to rich wildlife and culture, is located in the heart of the Northwest Passage in the Canadian Arctic and has experienced some of the most rapid increases in vessel traffic in the region over the past two decades. Increases in ship traffic in this fragile and important region have the potential to negatively impact marine mammals that inhabit the area, which was the impetus for protected areas status in the first place. The focus of this thesis research was to examine the potential impacts of underwater noise from ships on marine mammals in the Tallurutiup Imanga NMCA. The approach taken involved: 1) examining historic spatial and temporal vessel traffic trends in the area of interest from 1990 to 2018, using the Canadian Coast Guard ship archive data for the Northern Canada Vessel Traffic Service (NORDREG) Zone, 2) conducting an in-depth analysis of recent traffic trends (2015-18) using spatially precise Automatic Identification System (AIS) vessel traffic data, 3) creating underwater noise profiles using in an acoustic model to produce received level values cumulatively for all vessels and also for all vessels within a single class, 4) identifying behavioural disturbance events as 500 metre cells where the received level was equal to 120 dB, which is the behavioural disturbance threshold for marine mammals defined National Ocean and Atmospheric Administration (NOAA), and 5) overlaying acoustic model outputs with important areas for marine mammals to understand the spatial extent of ship-source underwater noise impacts in TI. Study results revealed that vessel traffic in Tallurutiup Imanga has almost tripled over the past 29 years with bulk carriers and passenger ships travelling the most in 2018. In the most recent years of the study period there were also spikes in vessel traffic; 2018 saw nearly a doubling of bulk carrier traffic to Baffinland Iron Ore Mines Corporation’s Mary River Mine site on Baffin Island. From the years 2015 to 2018, there were certain areas where behavioural disturbance events overlapped beluga and narwhal core use areas (50 Percent Volume Contours), as well as observed wildlife areas (based on Inuit and local knowledge). Some areas like Eclipse Sound and Milne Inlet had an increased risk of behavioural disturbance events, especially with cargo vessels and passenger ships. These areas indicated a potential for negative impacts on marine mammals, and areas that have more disturbance events have a higher chance of being affected. The aim of this research was to inform our understanding of potential underwater noise risks to marine mammal, and to support ongoing environmental management and governance efforts that could be used to provide evidence-based decision making for future mitigation of the NMCA.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".