Uncrewed Aerial Vehicle–Based Assessments of Peatland Permafrost Vulnerability Along the Labrador Sea Coastline, Northern Canada
Bibliographic record
Abstract
ABSTRACT Palsas and peat plateaus in subarctic peatlands are some of the southernmost lowland permafrost landforms in the Northern Hemisphere. Peatland permafrost along the Labrador Sea coastline in northeastern Canada is substantially understudied despite the importance of these landforms for wildlife, carbon stores, and Indigenous land users. In this study, we derived geomorphological and resiliency indices for peatland permafrost landforms at 20 wetland complexes, spanning a latitudinal gradient from Blanc‐Sablon, QC (51.4° N), to Nain, NL (56.5° N). Orthomosaics and three‐dimensional point clouds were created for each site using UAV‐based surveys and structure‐from‐motion photogrammetry. Analyses revealed that landforms in the region are characterized by short heights (maximum height: 3.65 m, average height: 0.49 m) with lichen and dwarf shrub cover, making them more similar to features in northern Europe than western Canada. Palsas and peat plateaus ranged in size from 49 to 14,233 m2, with a median feature size of 259 m2. Peatland permafrost in the region exhibits high levels of fragmentation, with most study sites (90%) exhibiting low or very low thaw resiliency. The results from this study indicate a high vulnerability to thaw and degradational processes, with potential negative consequences for species of cultural value to Labrador Inuit, Kallunângajuit, and Innu.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".