A dynamic model of wetland extent and peat accumulation: results for the Holocene
Bibliographic record
Abstract
Abstract. Substantial deposits of peat have accumulated since the last glacial. Since peat accumulation rates are rather low, this process was previously neglected in carbon cycle models. For assessments of the global carbon cycle on millennial or even longer timescales, though, the carbon storage in peat cannot be neglected any more. We have therefore developed a dynamic model of wetland extent and peat accumulation in order to assess the influence of peat accumulation on the global carbon cycle. The model is based on the dynamic global vegetation model LPJ and consists of a wetland module and routines describing the accumulation and decay of peat. The wetland module, based on the TOPMODEL approach, determines wetland area and water table. Peatland area is given by the innundated area at the summer minimum water table position and changes dynamically, depending on climate. The peat module describes oxic and anoxic decomposition of organic matter in the acrotelm, i.e., the part of the peat column above the permanent water table, as well as anoxic decoposition in the catotelm, the peat below the summer minimum water table. We apply the model to the period of the last 8000 yr, during which the model accumulates 210 ± 40 PgC as catotelm peat in the areas above 40° N.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".