Monitoring beluga whales from space: estimating abundance and evaluating social structure using VHR satellite imagery
Bibliographic record
Abstract
Improving monitoring efforts of Arctic species is becoming increasingly important given the rate of change in Arctic marine ecosystems and the presumed impact on Arctic marine mammals, such as beluga whales (Delphinapterus leucas). Very High Resolution (VHR) satellite imagery is emerging as a promising tool for efficiently monitoring beluga whale populations, which can be logistically challenging with current methods. Here we use VHR satellite imagery to investigate two conservation relevant aspects of beluga whale populations: abundance and social dynamics. First we determined two missing pieces of information required to estimate beluga whale abundance in VHR satellite imagery: 1) depths that beluga whales are visible in VHR satellite images, which are used to define availability bias correction factors, and 2) a comparison of abundance estimates in VHR satellite imagery to current aerial methods. We determined that beluga whales can be detected only at the surface in turbid water and at depths of 0 – 2 m in clear water in 0.31 m resolution VHR imagery, and that beluga whale availability bias corrected abundance estimates made from synchronous VHR satellite imagery and drone surveys were comparable. We further used VHR imagery to describe beluga whale group size, composition, and cohesion in beluga whale populations from Cumberland Sound, Eastern High Arctic – Baffin Bay, and Western Hudson Bay in relation to anthropogenic disturbance, density, and social context. We found that group size decreased with harvest, which seemingly reflects population decline or removal of key social individuals, while recent increases in vessel traffic were associated with larger group sizes and greater spatial cohesion, possibly suggesting an adaptative response to increase vigilance to vessel disturbance. Beluga whale social cohesion was mainly influenced by the presence of juvenile whales, with adult-juvenile mixed groups having smaller inter-individual distances than groups with adults only. Future beluga whale management efforts may benefit from incorporating VHR imagery into research programs and continuing to assess beluga whale social group dynamics alongside traditional abundance estimates; particularly given the expansion of anthropogenic disturbance in the Arctic.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".