A review of greenhouse gas emissions and removals from Irish peatlands
Bibliographic record
Abstract
Since peatlands cover around 20 % of the land area in the Republic of Ireland, their management is of particular significance in reducing national greenhouse gases (GHG) emissions. We reviewed peatland carbon (C) flux studies within Ireland, extracting data for carbon dioxide, methane, and nitrous oxide fluxes, as well as fluvial losses and here propose preliminary country-specific emission factors (EFs) for various peatland land uses and management practices. Using our derived EFs and latest areal estimates, national emissions from peatlands (excluding horticulture and combustion) amount to 1.9 Mt C y-¹ (± 0.4–3.4 Mt C y-¹), with more than half of all peatland GHG emissions coming from grasslands on organic soils and over one-third from domestic extraction drained peatlands. Our analyses suggest that peatland management through rewetting and restoration has the potential to substantially reduce emissions from drained peatlands, and this article attempts to quantify this reduction. This is critically important given the large areas of degraded peatlands that have been earmarked for rewetting in the next decade.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".