Vulnerability of peatland complexes in the Hudson Plains, Canada to permafrost-thaw-driven hydrological change
Bibliographic record
Abstract
Thawing discontinuous permafrost in subarctic peatland-dominated landscapes is increasingly recognized as an indicator of a warming climate and potentially shifting these landscapes from atmospheric carbon store to source. Furthermore, in certain discontinuous permafrost landscapes (e.g., northwest Canada) the thaw of permafrost peatlands leads to a reorganization of near-surface flow paths as permafrost-free peatlands expand, connect, merge, and drain. Collectively, these permafrost-thaw-driven landcover and hydrological changes have increased runoff and altered biogeochemical cycles threatening natural resources and critical infrastructure in Indigenous peoples’ traditional territories along with aquatic and terrestrial wildlife habitat. Owing to the region’s remote position and vast scale, comparatively less is known about the landcover and hydrological impacts of permafrost thaw in the Hudson Plains, the world’s third largest peatland region (370,000 km2) and southern most extent continental permafrost. For this study, we assign specific hydrological functions to individual peatland types based on their form, to then infer hydrological flux and storage processes within and between peatlands un a circuitry analog, at the scale of the peatland complexes and peatland complex regions. We analyze several remotely sensed data, including high-resolution lidar, historical air photographs, and recent panchromatic and multispectral satellite imagery along a latitudinal transect to evaluate peatland form, complex, and regional patterns. We then summarise these results and interpretation to present an initial vulnerability map of peatland complexes in the Hudson Plains to permafrost-thaw-driven hydrological change.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".