Investigating the Distribution of Peatland Permafrost and Its Sensitivity to Climate and Ecosystem Change in Coastal Labrador, Northeastern Canada
Bibliographic record
Abstract
Northern peatlands cover nearly 4 million km2, and roughly half of these contain periglacial landforms (palsas, peat plateaus). Recent estimates report that palsas and peat plateaus are more abundant in continental than coastal locations in northeastern Canada. However, use of coastal permafrost peatlands by Labrador Inuit and Innu for traditional activities suggests an abundance of palsas and peat plateaus along the Labrador Sea coastline. This thesis investigates the current distribution and thermal state, past sensitivity, and future resilience of peatland permafrost in coastal Labrador using field, remote sensing, and thermal modelling investigations. A permafrost peatland inventory was developed through a multi-mapper consensus-based process, supported by extensive field validations. Permafrost peatlands were found in lowland locations within 22 km of the coastline. While palsas were spread along the coastline, peat plateaus were concentrated between 53 and 55°N, where post-glacial marine invasions had occurred. The thermal state of four palsas in southeastern Labrador was then evaluated using records from shallow boreholes (<5.7 m). These palsas were characterized by low initial ground temperatures but experienced warming and subsidence throughout the study period (2015-2022). The greatest thaw occurred following the exceptionally warm winter of 2020-2021. Long-term changes in peatland permafrost were explored using aerial photography and satellite imagery of seven peatlands (1948-2021). Changes in landform extents were noted, though peat plateaus were found to thaw at lower rates than palsas. Widespread degradation was linked to regional warming and local greening. Finally, thermal modelling simulations calibrated to borehole records from nine peatlands were generated in the Northern Ecosystem Soil Temperature model. Permafrost was projected to disappear at all sites by 2100 under both climate and/or ecosystem change scenarios, and landforms were found to be more sensitive to ecosystem change than to climate warming alone. This thesis significantly advances our knowledge on peatland permafrost in coastal Labrador. Permafrost was more widespread than expected, though much of it is undergoing thaw and subsidence in response to climate warming and ecosystem change. The sensitivity of palsas and peat plateaus to ecosystem change necessitates the development of local ecosystem-based adaptation strategies for peatland permafrost in coastal Labrador.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".