Impact of global change and forest management on carbon sequestration in northern forested peatlands
Bibliographic record
Abstract
Northern peatlands occupy approximately 4% of the global land surface and store about 30% of the global soil carbon (C). A compilation of C accumulation rates in northern peatlands indicated a long-term average rate of C accumulation of 24.1 g m 2 year 1 . However, several studies have indicated that on a short-time scale and given the proper conditions, these ecosystems can exhibit very high rates of C accumulation (up to 425 g m 2 year 1 ). Peatland development is related to precipitation and temperature, and climate change is expected to have an important impact on the C balance of this ecosystem. Given the expected climate change, we suggest that most of the northern forested peatlands located in areas where precipitation is expected to increase (eastern Canada, Alaska, FSU, and Fennoscandia) will continue to act as a C sink in the future. In contrast, forested peatlands of western and central Canada, where precipitation is predicted to decrease, should have a reduction in their C sequestration rates and (or) could become a C source. These trends could be affected by forest management in forested peatlands and by changes in fire cycles. Careful logging, as opposed to wildfire, will facilitate C sequestration in forested peatlands and boreal forest stands prone to paludification while silvicultural treatments (e.g., drainage, site preparation) recommended to increase site productivity will enhance C losses from the soil, but this loss could be compensated by an increase in C storage in tree biomass.Key words: C sequestration, forested peatland, paludification, greenhouse gases, climate change, forest management.
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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 | 0.000 |
| 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".