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Record W4416336777 · doi:10.1016/j.ecoinf.2025.103525

Use of optical satellite imagery to estimate abundance of Narwhal (Monodon monoceros) in Makinson Inlet in the Canadian high Arctic

2025· article· en· W4416336777 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcological Informatics · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of ManitobaFisheries and Oceans Canada
FundersCrown-Indigenous Relations and Northern Affairs Canada
KeywordsSatellite imageryArcticInletFjordSatelliteAbundance (ecology)Population

Abstract

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Remote sensing technologies have expanded methods for monitoring wildlife. Very High Resolution (VHR) satellite imagery is becoming more widely used for animal detection. This is especially important for remotely based and hard to detect species such as narwhal ( Monodon monoceros Linnaeus, 1758). Narwhal are a data deficient species due to their large geographic distribution and elusive nature. During the summer, narwhal from the Baffin Bay population migrate to fiords and inlets in Canada and Greenland but their spatial use and density in fiords in the high Arctic is relatively unknown. Makinson Inlet, an inlet on Ellesmere Island in northern Canada, was surveyed using aerial methods in 2013 and estimated a surface abundance of 812 narwhal (adjusted to 2387). Another aerial survey was attempted but unsuccessful due to inclement weather in 2022; however, satellite imagery offers another method for estimating abundance of narwhal in this remote fiord. In this study the World-View 3 satellite (31 cm resolution) was tasked to obtain optical imagery from Makinson Inlet and 5752 km 2 was imaged between August 2 to 5, 2022. Imagery readers with previous satellite imagery analysis experience manually analyzed the imagery and identified 406 narwhal. The estimated number of narwhal in Makinson Inlet was adjusted for availability bias to account for deeper whales that would not be visible in the imagery (>1 m deep). The adjusted estimated abundance for narwhal in Makinson Inlet was 1987 (CV = 0.12; 95 % CI: 1578-2502). This study demonstrates the first use of VHR satellite imagery as a remotely-based non-invasive method to obtain information on narwhal abundance in the Canadian high Arctic. • Very High Resolution (VHR) satellite imagery was obtained from Makinson Inlet on Ellesmere Island in northern Canada in August 2022 to assess the use of VHR satellite imagery for monitoring narwhal ( Monodon monoceros ). • Readers with previous satellite imagery analysis experience analyzed the imagery and detected 406 narwhal. • The estimated number of narwhal in Makinson Inlet was adjusted for availability bias and was between 1578 and 2502. • This study demonstrates the first use of VHR satellite imagery as a remotely-based non-invasive method to detect and obtain information on narwhal abundance.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.632
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.277
Teacher spread0.245 · 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