Wetland chronosequence as a model of peatland development: Vegetation succession, peat and carbon accumulation
Bibliographic record
Abstract
Model validation experiments are fundamental to ensure that the peat growth models correspond with the diversity in nature. We evaluated the Holocene Peatland Model (HPM) simulation against the field observations from a chronosequence of peatlands and peat core data. The ongoing primary peatland formation on the isostatically rising coast of Finland offered us an exceptional opportunity to study the peatland succession along a spatial continuum and to compare it with the past succession revealed by vertical peat sequences. The current vegetation assemblages, from the seashore to a 3000 year old bog, formed a continuum from minerotrophic to ombrotrophic plant communities. A similar sequence of plant communities was found in the palaeovegetation. The distribution of plant functional types was related to peat thickness and water-table depth (WTD) supporting the assumptions in HPM, though there were some differences between the field data and HPM. Palaeobotanical evidence from the oldest site showed a rapid fen–bog transition, indicated by a coincidental decrease in minerotrophic plant functional types and an increase in ombrotrophic plant functional types. The long-term mean rate of carbon (C) accumulation varied from 2 to 34 g C/m 2 per yr, being highest in the intermediate age cohorts. Mean nitrogen (N) accumulation varied from 0.1 to 3.9 g N/m 2 per yr being highest in the youngest sites. WTD was the deepest in the oldest sites and its variation there was temporally the least but spatially the highest. Evaluation of the HPM simulations against the field observations indicated that HPM reasonably well simulates peatland development, except for very young peatlands.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".