Modelling the Exchange of Energy, Water and Carbon in Peatland Ecosystems
Bibliographic record
Abstract
Peatland ecosystems store between 200 and 450 Gt C (1015 gC). It is estimated that peatlands constitute an annual sink of between 0.1 and 0.3 Gt C yr-1 but this is based on very few contemporary measurements. With the huge amount of carbon stored in peatlands and the close association between the hydrology, - i. e. saturation, of peatlands and climate, concerns have been raised about a possibility of a positive climate feedback involving peatlands: increases in temperature, and/or decreases in water excess in northern peatland could lead to increased carbon mineralization and a conversion of peatlands from a sink to a source of CO2. To gain a greater understanding of the climate-hydrology-carbon coupling in northern peatland ecosystems we initiated, in 1997, the Peatland Carbon Study and this study is continuing as the eastern peatland initiative of the Fluxnet Canada. Our objectives are to measure and model the energy, water and carbon balance of northern peatlands. To study the climate - carbon association over the short-term, e. g. decades to several centuries, we developed a processed based peatland model, the Peatlands Carbon Simulator (PCARS). PCARS couples with the wetland version of the Canadian Land Surface Scheme (CLASS) and it contains a fairly complete description of photosynthesis, autotrophic, and oxic and anoxic heterotrophic respiration, allocates fixed carbon to above and below ground components of trees, shrubs, sedges and mosses, and outputs the loss of carbon as CO2, CH4, and dissolved organic carbon (DOC). This model has gone through extensive testing against the measure carbon fluxes at Mer Bleue peatland, the main site of the Eastern Peatland Station of Fluxnet Canada. PCARS reproduces the net carbon exchange well but over-estimates the disaggregated components of gross photosynthesis and ecosystem representation. To study the climate - carbon association over longer periods, e. g. decades to millennia, we developed a phenomenological model, the Peat Accumulation Model (PAM). This model is based on two coupled equations: one describing the net carbon input based on the association between ecosystem production and decomposition and the water table position, while the other equation solves for the change in water table position as a function of the change in the mass of carbon stored in the peatland, i. e. the peatland height, and the annual water balance. The model compares well with reconstructed carbon accumulation from the analysis of peat cores when an independent estimate of relative wetness is used to increase or decrease the precipitation input.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".