Survey and data considerations to adopt a multi-whale trigger density for protecting the North Atlantic Right Whale in Canadian waters
Bibliographic record
Abstract
The role of Canada in protecting the endangered North Atlantic right whale (NARW) and promoting their recovery is crucial as a large proportion of the population spends all or part of the spring, summer, and autumn months in Canadian waters. Starting in 2018, Fisheries and Oceans Canada (DFO) and Transport Canada (TC) used the presence of a single whale to trigger management actions in some areas such as the Gulf of St. Lawrence or NARW Critical Habitat in Canadian waters. Outside of these areas, a trigger applied for dynamic management in the Unites States of American (USA), and based on a minimum density of 0.04 whales/nm2 or equivalent to three or more whales separated by less than 5.5 nm (10.2 km) from each other, was implemented. This minimal density trigger is rooted in the idea that group size may be a reasonable indicator of whales persisting in a region. Whether this density is adequate for Canadian waters given the observed variability in habitat characteristics and NARW behaviour is, however, unknown. This paper addresses the information required to reliably locate NARW aggregations, the challenges in identifying and enumerating NARW given the current monitoring framework, the information needed to develop a tailored density trigger in Canada, and short and long-term considerations to enhance NARW protection in Canada. This advice was developed in a peer review meeting in 2018 and should be interpreted within the context of the situation at that time. It was concluded that there were insufficient information to develop a multi-whale management trigger specific to Canadian waters. An approach using multiple whales to trigger management actions would require methods designed to assess the number of individuals and their persistence in a given area, as well as other operational requirements. Data on NARW over multiple years would also be required to assess the probability of reliably detecting NARW, as well as NARW persistence, habitat use, and behaviours in Canadian waters, and to determine if the approach used in the USA is appropriate for Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.037 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".