Bibliographic record
Abstract
Peatlands store a vast amount of carbon (C) and have functioned as C sinks for millennia. The C sink function of peatlands may be at risk with increased nutrient deposition and climate change in the future. Models can make future projections for peatlands, but most peatland models do not include nutrient cycles, which are tightly couple to the C cycle. Furthermore, microbial activities have been found to play an essential role in regulating peatland biogeochemical cycles. Still, peatland models have not explicitly included any microbial controls, precluding our ability to examine the microbial feedbacks within the peatland ecosystem. This research explores the significance of microbe-mediated carbon-nutrient cycling in peatland ecosystem functions through a modelling approach. The McGill Wetland Model (MWM) was modified into MWMmic_NP by introducing a multi-layer cohort model to track the decrease in peat qualities with decomposition age; the growth and metabolism of saprotrophic microbes (SAP) as factors on the rates of peat decomposition; nitrogen and phosphorus cycles regulating the growth of plants and microbes; ericoid mycorrhiza fungi (ERM) exchanging nutrients for C from the host plant ericaceous shrubs; and the vertical and horizontal transport of the solutes in the peat pore water. MWMmic_NP was evaluated against the extensive whole-ecosystem measurements from the Mer Bleue Bog, eastern Canada, and the long-term fertilization experiments at the same site. MWMmic_NP was then used to examine the response of the bog to different scenarios of environmental changes. MWMmic_NP was able to replicate the overall C-N-P cycles observed at the Mer Bleue bog. In particular, the model reproduced the observed dynamics of the newly added pools of SAP and dissolved organic matter, and captured the changes in stoichiometry profiles with peat depth. Furthermore, the model performed well in reproducing the response of the bog to nutrient additions. A diminished role of mycorrhiza fungi in nutrient uptake and subsequent lower C allocation from shrubs to ERM increased shrub growth. Possible environmental changes induced a transition from mosses to shrubs domination in the vegetation community and from ERM to SAP domination in microbial community composition in the bog, thus reducing carbon sequestration capacity. Water table drawdown and increased soil temperature were the most important environmental factors for the weakening of the C sink. Reactions of SAP or ERM to changes in environmental conditions determined the response of the bog. This research contributes to a better understanding of the significance of microbe-mediated biogeochemical cycling in peatlands. ERM fungi may play a central role in maintaining the vegetation structure and C sink function of shrub-dominated ombrotrophic 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".