Mitigating CO2 emissions from cultivated peatlands: Efficiency of straws and wood chips applications in maintaining carbon stock in two contrasting soils
Bibliographic record
Abstract
Repeated applications of straw and wood chips were recently proposed as a conservation strategy for preserving cultivated peatland carbon (C) stock. However, the variability in the amendment biostability and the possible divergent responses of contrasting peat soils need to be assessed. This study investigated the effect of amendment with different plant materials on carbon dioxide (CO2) emissions from two contrasting peat soils (sapric and hemic) in two laboratory experiments. The sapric soil received one application of plant materials and was incubated for 3190 degree-days (145 days at 22°C), while the hemic soil received three successive applications of plant materials and was incubated for three successive periods of 3150 degree-days (126 days at 25°C). CO2 emissions were measured at time intervals ranging from 2 to 14 days and the apparent proportion of the plant material’s C remaining in the soil was modeled using an exponential decay function. CO2 emissions from the 0-25 cm horizon of the unamended peats represented 0.7 t C-CO2 ha-1 yr-1 in the sapric soil and 7.3, 1.1, and 0.5 t C-CO2 ha-1 yr-1 in the hemic soil for the first, second, and third amendment periods, respectively. The apparent remaining C of the plant material varied from 52% to 81% in the two experiments, resulting in biomass requirements ranging from 2 to 32 t ha-1. The apparent remaining C was from 26% to 36% higher in the sapric soil than in the hemic soil. The apparent remaining C was also 9% to 38% higher for the treated softwoods than the untreated materials (straws: miscanthus, switchgrass, sorghum; wood chips: willow, birch). The repeated application of straw and wood chips increased CO2 emissions in the first 35 days following each application, resulting in an increased decomposition rate for the tested model. However, no change was detected for the final apparent remaining C across the three applications. These findings highlight the importance of considering soil properties, material types, and the impact of repeated applications for designing effective amendment programs and accurate C projection models for cultivated peatlands.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".