FLUX AND STABLE ISOTOPE FRACTIONATION OF CO2 IN A MESIC PRAIRIE HEADWATER STREAM
Bibliographic record
Abstract
This study quantifies small-scale carbon dioxide (CO 2 ) efflux and estimates annual CO 2 emission from a headwater stream at the Konza Prairie Long-Term Ecological Research Site and Biological Station (Konza), in a terrain of horizontal, alternating limestones and shales. We characterized the CO 2 efflux and stable carbon isotopes (δ 13 C-CO 2 ) at point sources of groundwater discharge from small-scale karst features, identified by temperature, and downstream of those point sources, as well as in stream reaches without identifiable point sources. CO 2 effluxes ranged from 2.2 to 214 g CO 2 m -2 day -1 (mean was 20.9± 41.4 g CO 2 m -2 day -1 ). Downstream of point groundwater discharge sources, CO 2 efflux decreased, over 2 meters, to 3% to 40% of the point-source flux, while δ 13 C-CO 2 increased, ranging from -9.8 ‰ to -23.2 ‰ V-PDB (mean was -14.9 ‰ ± 4.2 ‰ V-PDB). The δ 13 C-CO 2 increase was not strictly proportional to the CO 2 flux but related to the origin of vadose-zone CO 2 (C3 versus C4 vegetation). Over the study period, ~7.0 metric tons of CO 2 were emitted from the 1.1-km-long stream, comparable to other headwater streams. The high spatial and temporal variability of CO 2 efflux from this headwater stream informs those doing similar measurements and those working on upscaling stream data, that local variability should be assessed to make the best estimate of the impact of headwater stream CO 2 efflux on the global carbon cycle.
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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 | 0.000 | 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".