Dissolved organic carbon from European beech logs: Patterns of input to and retention by surface soil
Bibliographic record
Abstract
The flux of dissolved organic carbon (DOC) from aboveground litter into the soil is generally considered an important pathway for carbon transport. However, the extent to which dead wood, a highly concentrated source of carbon (C), may contribute not only to this flux but also to the accumulation of soil organic carbon (SOC) is still unknown. Here, concentrations and fluxes of DOC in solution beneath 5 logs of Fagus sylvatica were quantified using tension lysimeters. Soil samples beneath and adjacent to an additional 18 logs were analyzed for SOC. Concentrations of stable C isotopes were determined in wood of logs, DOC, and SOC to follow the fate of C from logs to the soil. Mean DOC concentrations in soil solution beneath logs were highly variable and ranged between 11.6 ± 5.8 mgL−1 (± SD) and 696 ± 654 mg·L-1, while beneath litter without logs the DOC concentrations had an average value of 10 ± 3 mg·L-1. Peak DOC concentrations beneath logs reached 4317 mg·L-1. At 0–20 cm soil depth, SOC concentrations and SOC pools beneath logs were not higher than for control soils. The difference in the composition of stable C isotopes between wood (-25.5 ± 1.0%o) and litter (-28.4 ± 0.2%o) was maintained in DOC and SOC beneath respective substrates. A calculated amount of 20.5 ± 13.6% of the original SOC within 0–20 cm mineral soil was exchanged over a period of 17 ± 8 y by C from logs. However, despite the increased DOC fluxes, SOC pools beneath logs did not increase.
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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 | 0.001 | 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".