Do Root Exudates Enhance Peat Decomposition?
Bibliographic record
Abstract
Despite the importance of understanding controls on microbial carbon (C) mineralization in peat soils, the role of vascular plant root exudates is still unclear. To determine whether root exudates could stimulate enhanced decomposition of peat, we utilized an in-vitro method involving the addition of a solution similar to root exudates (6 glucose-C: 2 citrate-C: 2 amino acid-C, at 3 addition levels) to peat, incubating the mixture and measuring CO2 produced over 20 d and microbial biomass and dissolved organic carbon (DOC) at the end of the incubation. We defined priming as inorganic C (IC) production (CO2 + calculated dissolved inorganic C) during the incubation being greater than that attributed to the control peat plus the added C. An addition level of 0.083 mg C g−1 dry peat, estimated to represent root exudation over one 12-h sunny day in a bog, caused an enhancement in IC production that exceeded that produced in the controls and the amount of added C after 8 d, with rates levelling to control values after 15 d. At the end of the incubation nearly 3 times the amount added C had been mineralized, relative to the control, however this represented only 4% of total microbial respiration in the controls. Although the priming effect pattern appeared to be real throughout repeated measurements in our experiments, the statistical probabilities were not always large due to high variability in background CO2 production levels. Given the observed long lag-times and overall small magnitude and large variability in observed effects, we conclude that although priming of decomposition appears to occur in peatlands, it likely has only a minor overall impact on net C loss to the atmosphere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".