Potential for long‐term transfer of dissolved organic carbon from riparian zones to streams in boreal catchments
Bibliographic record
Abstract
Boreal regions store most of the global terrestrial carbon, which can be transferred as dissolved organic carbon (DOC) to inland waters with implications for both aquatic ecology and carbon budgets. Headwater riparian zones (RZ) are important sources of DOC, and often just a narrow 'dominant source layer' (DSL) within the riparian profile is responsible for most of the DOC export. Two important questions arise: how long boreal RZ could sustain lateral DOC fluxes as the sole source of exported carbon and how its hydromorphological variability influences this role. We estimate theoretical turnover times by comparing carbon pools and lateral exports in the DSL of 13 riparian profiles distributed over a 69 km(2) catchment in northern Sweden. The thickness of the DSL was 36 ± 18 (average ± SD) cm. Thus, only about one-third of the 1-m-deep riparian profile contributed 90% of the lateral DOC flux. The 13 RZ exported 8.7 ± 6.5 g C m(-2) year(-1) , covering the whole range of boreal stream DOC exports. The variation could be explained by local hydromorphological characteristics including RZ width (R(2) = 0.90). The estimated theoretical turnover times were hundreds to a few thousands of years, that is there is a potential long-lasting supply of DOC. Estimates of net ecosystem production in the RZ suggest that lateral fluxes, including both organic and inorganic C, could be maintained without drawing down the riparian pools. This was supported by measurements of stream DO(14) C that indicated modern carbon as the predominant fraction exported, including streams disturbed by ditching. The transfer of DOC into boreal inland waters from new and old carbon sources has a major influence on surface water quality and global carbon balances. This study highlights the importance of local variations in RZ hydromorphology and DSL extent for future DOC fluxes under a changing climate.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".