Whales Without Borders: Aligning Environmental Policies to Enhance Whale Conservation in the Salish Sea
Bibliographic record
Abstract
The Salish Sea is a biologically diverse ecosystem which is home to at least six species of cetaceans (whales, dolphins and porpoises). This inland sea supports seasonal booms of numerous cetacean prey species, including Chinook salmon (Oncorhynchus tshawytscha), Pacific herring (Clupea pallasii), and ghost shrimp (Palaemonetes paludosus), making the Salish Sea an important foraging ground for cetaceans (Gaydos & Pearson, 2011; Pietsch & Orr, 2015; Quinn & Losee, 2022). Subsequently, there is designated critical habitat for two at-risk cetaceans – Southern Resident killer whales (Orcinus orca) and humpback whales (Megaptera novaeangliae) within the Salish Sea (Figure 1). Southern Resident killer whales are listed as ‘endangered’ under both Canada’s Species at Risk Act (SARA) and the United States (U.S.) Endangered Species Act (ESA; U.S. Fish and Wildlife Service, 1973; Government of Canada, 2002). This population of killer whale has suffered historic declines starting in the 1960s, with currently 74 individuals remaining in the population as of April 2025. Conversely, over 1,200 individual humpback whales have been observed in the Salish Sea, consisting of whales from three distinct population segments (DPS) – Central America, Mexico, and Hawaii DPS (Martien et al., 2021; Taylor et al., 2021; Malleson & Shaw, 2024). Humpback whales have been steadily increasing in numbers over the last two decades following the end of commercial whaling, however, both Southern Residents and humpback whales are facing increasing pressure from anthropogenic effects, including acoustic and physical disturbance from vessels, reduced prey availability, and persistent environmental contaminants (Fisheries and Oceans Canada, 2018; Sato & Wiles, 2021). Despite a total of 16 laws, seven regulations, and one treaty enacted across Canada and the U.S. to reduce these threats, the transboundary nature of the Salish Sea is challenging for ensuring sufficient overlap of protections between state, provincial, and federal measures.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".