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Record W7133273068

Distribution of north Atlantic Right Whales, Eubalaena glacialis, in Eastern Canada from line-transect surveys from 2017 to 2022

2024· other· en· W7133273068 on OpenAlexaboutno aff
Anne St-Pierre, Talia Koll-Egyed, Valérie Harvey, Jack W. Lawson, Caroline C. Sauvé, Angélique Ollier, Pierre J. Goulet, Mike O. Hammill, Jean-François Gosselin

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAerial surveyTransectAbundance (ecology)Distribution (mathematics)CensusDistance samplingSurvey methodology
DOInot available

Abstract

fetched live from OpenAlex

In response to the unusually high number of North Atlantic Right Whales (NARW) carcasses (N=12) reported in the Gulf of St. Lawrence (GSL) in 2017, an unprecedented aerial survey effort was deployed for the monitoring of NARW presence in Canadian waters starting in late August 2017. Between 2017 and 2022, a total of 561,187 km of systematic transect lines have been surveyed over periods of up to 7.5 months in some years, involving up to three aircraft simultaneously. Survey effort was deployed in potential NARW foraging areas across eastern Canadian waters, by covering the entire GSL each summer, and the Scotian Shelf and the continental shelf around Newfoundland and southern Labrador every second summer. A total of 185 NARW groups (246 whales) were observed by primary observers during the systematic surveys, with 6 groups in 2017, 25 groups in 2018, 23 groups in 2019, 43 groups in 2020, 31 groups in 2021, and 57 groups in 2022. The vast majority of NARW sightings (93%) occurred in the two survey stratum in the southern GSL (i.e., separated into southeastern and southwestern stratum), however this area accounted for ~58% of the total survey effort. Abundance estimates in this study were calculated based on a distance sampling approach, and reported for each survey pass of each stratum in order to compare abundances among strata and over time (i.e., within a survey season in the case of repeated surveys, and also across years). Two correction factors specific to NARW and to the region surveyed were computed to correct inherent biases of aerial surveys, i.e., availability bias, for animals underwater when the aircraft passed overhead, and perception bias, for animals at the surface of the water that are missed by observers. These two corrections increased abundance estimates by a factor of ~3. While NARW were consistently detected at the beginning (May to mid-June) and at the end (September to November) of the survey season in the southeastern GSL stratum, they also occur in this area in July and August. Indeed, the highest abundance estimate in this stratum across survey years was recorded for the survey conducted in mid August 2022 (97 animals, CI: 31-308). In the southwestern GSL stratum, peak abundances were observed consistently observed each year between early June and early August. The highest fully corrected abundance for the study period came from a pass of the southwestern GSL stratum in mid-June 2018, with 281 animals (CI: 100-790). All surveys of the southwestern GSL stratum conducted between June and end of August reported observations of NARW. Systematic aerial surveys are one of the set of tools available to monitor NARW which, combined with other approaches such as acoustic monitoring, provide useful information required for the conservation of the species.

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 score0.015
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.234
Teacher spread0.224 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207