Influence of Holocene permafrost aggradation and thaw on the paleoecology and carbon storage of a peatland complex in northwestern Canada
Bibliographic record
Abstract
Permafrost in peatlands strongly influences ecosystem characteristics, including vegetation composition, hydrological functions, and carbon cycling. Large amounts of organic carbon are stored in permafrost peatlands in northwestern Canada. Their possible degradation into permafrost-free wetlands including thermokarst bogs may affect carbon (C) stocks, but the direction and magnitude of change are uncertain. Using peat core reconstructions, we characterized the temporal and spatial variability in vegetation macrofossil, testate amoebae, C content, and peat decomposition along a permafrost thaw chronosequence in the southern portion of the Scotty Creek watershed near Fort Simpson, Northwest Territories. The accumulation of limnic and minerotrophic peat prevailed at the site until permafrost formed around 5000 cal. yr BP. Three distinct permafrost periods were identified in the permafrost peat plateau profile, while permafrost only aggraded once in the thermokarst bog profile. Permafrost thawed at ~550 and ~90 cal. yr BP in the thermokarst bog center and edge, respectively. Both allogenic (climatic shifts and wildfire) and autogenic (peat accumulation, Sphagnum growth) processes likely exerted control on permafrost aggradation and thaw. While apparent carbon accumulation rates (ACARs) were lower during present and past permafrost periods than during non-permafrost periods, long-term C accumulation remained similar between cores with different permafrost period lengths. Deep peat was less decomposed in the permafrost plateau compared with the thermokarst bog, which we speculate is due more to differences in peat type rather than differences in decomposition environment between these two ecosystem states. Our study highlights the importance of considering potential deep peat C losses to project the fate of thawing permafrost peat C stores.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".