Climatic factors influencing fluxes of dissolved organic carbon from the forest floor in a continuous-permafrost Siberian watershed
Bibliographic record
Abstract
Fluxes of dissolved organic carbon (DOC) in forested watersheds underlain by permafrost are likely to vary with changes in climatic regime that increase soil moisture and temperature. We examined the effects of temporal and spatial variations in soil temperature and moisture on DOC fluxes from the forest floor of contrasting north- and south-facing slopes in central Siberia. DOC fluxes increased throughout the growing season (JuneSeptember) on both slopes in 2002 and 2003. The most favorable combination of moisture content and temperature (deepest active soil layer) occurred in September, and we believe this was the primary driver of increased DOC concentrations and flux in autumn. Total DOC flux for JuneSeptember was 12.617.6 g C·m2 on the south-facing slope and 4.68.9 g C·m2 on the north-facing slope. DOC concentrations in forest floor leachates increased with increasing temperature on the north-facing slope, but were almost unaffected by temperature on the south-facing slope. Our results suggest that water input in midseason from melting of ice or precipitation events is the primary factor limiting DOC production. Significant positive correlations between amounts of precipitation and DOC flux were found on both slopes. Dilution of DOC concentrations by high precipitation volumes was observed only for the forest floor leachates collected from the north-facing slope. Our results suggest that global warming will result in increased DOC production in forest floors of permafrost regions, and that precipitation patterns will play an important role in determining the magnitude of these changes in DOC flux as well as its interannual variability. However, the longer-term response of soils and DOC flux to a warming climate will be driven by changes in vegetation and microbial communities as well as by the direct results of temperature and moisture conditions.
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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 | 0.001 |
| 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) | 0.001 | 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".