Palaeoecology of a palsa and a filled thermokarst pond in a permafrost peatland, subarctic Québec, Canada
Bibliographic record
Abstract
Radiocarbon dating and macrofossil data from a palsa and a filled thermokarst pond within a subarctic permafrost peatland were used to reconstruct their evolution and to distinguish between allogenic and autogenic processes that had been involved in their development. Peat began to accumulate in the peatland basin shortly after 6000 cal. BR The initial stage was a shallow bay or a salty marsh, followed by a wet marsh triggered by a relatively rapid drop in sea level related to a rapid isostatic uplift of land. By 5640 cal. BP, the site had transformed into a rich fen. A high rate of peat accumulation led to the establishment of a short-lived intermediate fen by 4610 cal. BP and to a poor fen from 4200 cal. BP until 1760 cal. BP. Low water-tables associated with decreased precipitation occurred between 5170 and 4610 cal. BP, and 3100 and 1760 cal. BP Between 1760 and the Little Ice Age, there was ombrotrophication of the site largely as a result of a thick peat accumulation. During this period, autogenic processes had controlled the general hydrosere, while allogenic processes, mainly precipitation, had influenced species composition. Permafrost established during the Little Ice Age leading to palsa formation and it has been melting in response to recent climate warming and precipitation increases. Macrofossil results from the filled thermokarst pond show that plant succession used the followed hydrosere: Calliergon giganteum and Sphagnum riparium when the pond's depth was at a maximum, S. riparium and C. giganteum when the pond was partly filled in, and S. lindbergii and S. riparium since the pond has been completely filled in.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".