Biochemical characteristics of peat organic matter and distribution of testate amoebae patterns in two naturally regenerating cutover Sphagnum peatlands of the Jura Mountains.
Bibliographic record
Abstract
To restore peat accumulation and long-term carbon sequestration in peatlands which have been abandoned or designated for restoration, it is essential to consider a wide range of indicators, such as vegetation, diversity of microorganisms and physico-chemical properties of peat organic matter. Pattern of biodiversity and biochemical characteristics of the peat provide clues for the functioning of the system, including gas exchanges at the soil surface. . A combined study of organic matter, testate amoebae and heterotrophic bacteria has been carried out on peat profiles (up to 1 m depth) from two cutover Sphagnum-dominated peatlands in the Jura Mountains (France and Switzerland). The sites are representative of a range of regeneration stages and are compared to reference profiles taken from undisturbed areas. The uppermost soil (0 to 3 cm) corresponding to living Sphagnum was analysed for testate amoebae, whereas other analyses were conducted on the whole profile. Results show contrasting signatures in terms of elemental, micromorphological and biochemical compositions of peat organic matter (OM) along the profile: - in exploited sites, the depth evolution of C/N ratios shows a clear threshold between regenerating litter and “old” catotelm peat. The “young” peat is characterised by high C/N ratios (60 to 100) and well-preserved Sphagnum tissues. In contrast, the underlying “old” peat shows distinct properties which are characteristic of an intensive degradation of OM (lower C/N ratios, large amounts of amorphous OM, high proportions of microbial monossacharides...) ; - in the intact site, depth pattern of C/N ratios is nearly constant (60 to 80), and peat OM is exclusively composed of well-preserved plant tissues mainly derived from Sphagnum, except in 2 levels (16-19 cm and 44-54 cm depth) where the OM composition may highlight events such as natural or anthropogenic drainage phases. A total of 33 testate amoebae taxa were found. Of these, 10 belonged to the group of testate amoebae with filose pseudopodia and 23 to the Arcellinida. Contribution of these taxonomic groups varied in the different sites, depending on recovered vegetation and hydrological conditions. Moreover, higher testate amoebae densities, carbon biomass and species diversity tended to be associated with the natural vegetation communities in the intact site and the more advanced regeneration stages.
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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 | 0.000 |
| 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 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".