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Record W196961967 · doi:10.47536/jcrm.v9i1.688

Distribution and abundance of marine mammals in the coastal waters of British Columbia, Canada

2023· article· en· W196961967 on OpenAlexaffabout
Rob Williams, Len Thomas

Bibliographic record

Venue˜The œjournal of cetacean research and management. Special issue · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPorpoiseFisheryAbundance (ecology)HarbourMinke whaleWhaleWhalingBalaenopteraOceanographyAerial surveyGeographyBayShoreEnvironmental scienceBiologyGeology

Abstract

fetched live from OpenAlex

Information on animal distribution and abundance is integral to wildlife conservation and management. However abundance estimates have not been available for many cetacean species inhabiting the coastal waters of Canada’s Pacific coast, including those species that were heavily depleted by commercial whaling. Systematic sightings surveys were conducted in the inshore coastal waters of the Inside Passage, between the British Columbia (BC)-Washington and the BC-Alaska borders. A total of 4,400km (2,400 n.miles) of trackline were surveyed in the summers of 2004 and 2005. Abundance estimates (with 95% confidence intervals) assuming certain trackline detection for seven cetacean species were as follows: harbour porpoise, 9,120 (4,210-19,760); Dall’s porpoise, 4,910 (2,700-8,940); Pacific white-sided dolphin, 25,900 (12,900-52,100); humpback whale, 1,310 (755-2,280); fin whale, 496 (201-1,220); common minke whale, 388 (222-680); and ‘northern resident’ killer whale, 161 (45-574). The potential for responsive movement to have affected the accuracy and precision of these estimates is difficult to assess in small-boat surveys. However, the analyses were designed to minimise this factor in the most obvious case (Pacific white-sided dolphins) and pilot data collection has begun to assess the magnitude of the effect and to calculate correction factors for other species. The density of harbour seals, both along the shoreline and at sea, was calculated and it was estimated that total abundance of harbour seals in the study area was at least 19,400 (14,900-25,200). These are new abundance estimates for this region for all cetacean species except killer whales. The small sample size makes the killer whale estimate tenuous, but one worth noting, as it is close to the known number of northern resident killer whales (2004 census was 219 animals, Cetacean Research Program, Pacific Biological Station, Fisheries and Oceans Canada). The common minke whale abundance estimate is similarly tentative, however the results do reveal that common minke whales were relatively rare in this region. While the majority of harbour seals were found as expected in the southern straits and in the mainland inlets, a substantial number of animals were on the north coast and in the Queen Charlotte Basin as well. These data provide a systematic snapshot of summertime distribution and abundance of marine mammals in the Queen Charlotte Basin, where offshore oil and gas development and seismic surveys for geophysical research have been proposed to take place. Similarly, the abundance estimates could be used to form the basis of a simulation exercise to assess the sustainability of observed levels of incidental bycatch of small cetaceans in commercial fisheries. The results described here provide a useful reference point to which future survey data can be compared.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.018
GPT teacher head0.259
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations91
Published2023
Admission routes2
Has abstractyes

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