Microcosm tests of the effects of temperature and microbial species number on the decomposition of <i>Carex aquatilis</i> and <i>Sphagnum fuscum</i> litter from southern boreal peatlands
Bibliographic record
Abstract
Increased decomposition rates in boreal peatlands with global warming might increase the release of atmospheric greenhouse gases, thereby producing a positive feedback to global warming. How temperature influences microbial decomposers is unclear. We measured in vitro rates of decomposition of senesced sedge leaves and rhizomes (Carex aquatilis), from a fen, and peat moss (Sphagnum fuscum), from a bog, at 14 and 20 degrees C by the three most frequently isolated fungi and bacteria from these materials. Decomposition rates of the bog litter decreased (5- to 17-fold) with elevated temperatures, and decomposition of the sedge litters was either enhanced (2- to 30-fold) or remained unaffected by elevated temperatures. The increased temperature regime always favoured fungal over bacterial decomposition rates (2- to 3-fold). Different physiological characteristics of these microbes suggest that fungi using polyphenolic polymers as a carbon source cause greater mass losses of these litters. Litter quality exerted a stronger influence on decomposition at elevated temperatures, as litter rich in nutrients decomposed more quickly than litter poorer in nutrients at higher temperatures (8.0%-25.7% for the sedge litters vs. 0.2% for the bryophyte litter). We conclude that not all peatlands may provide a positive feedback to global warming. Cautious extrapolation of our data to the ecosystem level suggests that decomposition rates in fens may increase and those in bogs may decrease under a global warming scenario.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".