Smouldering fire signatures in peat and their implications for palaeoenvironmental reconstructions
Bibliographic record
Abstract
Peatland ecosystems are valued as natural archives of past climatic and vegetation changes and as such their study is essential for palaeoenvironmental reconstructions over millennia. Fires in peatlands are dominated by smouldering combustion which is the self-sustained, slow, low temperature, flameless form of burning. Most studies on peat fires to date have focused on ignition conditions, C losses or atmospheric emissions, but there is a significant gap in the understanding of the evolution of organic matter (OM) following smouldering. A key feature of smouldering fires is that they consume most of the pyrogenic char produced. Consequently, it may be that most smouldering fires are simply not visible using standard palaeontological techniques. Here we present the possibility of identifying palaeofires by following their physical and chemical signature along a peat profile. We have undertaken laboratory experiments on Sphagnum peat columns and measured physical, chemical and spectroscopic changes of OM features induced by smouldering on samples of varying moisture content. We reveal that there is a higher production of aromatic and condensed molecules, an increase of the total N and a decrease of the C/N ratio, besides significant variations of pH, electrical conductivity and ash content. Several of these changes have, in previous studies, been taken to be indicative of alterations in atmospheric dust deposition and climate-driven changes (e.g., vegetation, water table fluctuation, decomposition and mineralization processes), but are also produced by smouldering fires. Our results imply that smouldering fires should therefore also be considered in climatic and floral reconstructions drawn from peat cores and that these additional physical and chemical changes may serve to enhance our understanding of palaeofire histories.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".