Geomorphic Controls on Floodplain Soil Organic Carbon in the Yukon Flats, Interior Alaska, From Reach to River Basin Scales
Bibliographic record
Abstract
Abstract Floodplains accumulate and store organic carbon (OC) and release OC to rivers, but studies of floodplain soil OC come from small rivers or small spatial extents on larger rivers in temperate latitudes. Warming climate is causing substantial change in geomorphic process and OC fluxes in high latitude rivers. We investigate geomorphic controls on floodplain soil OC concentrations in active‐layer mineral sediment in the Yukon Flats, interior Alaska. We characterize OC along the Yukon River and four tributaries in relation to geomorphic controls at the river basin, segment, and reach scales. Average OC concentration within floodplain soil is 2.8% (median = 2.2%). Statistical analyses indicate that OC varies among river basins, among planform types along a river depending on the geomorphic unit, and among geomorphic units. OC decreases with sample depth, suggesting that most OC accumulates via autochthonous inputs from floodplain vegetation. Floodplain and river characteristics, such as grain size, soil moisture, planform, migration rate, and riverine DOC concentrations, likely influence differences among rivers. Grain size, soil moisture, and age of surface likely influence differences among geomorphic units. Mean OC concentrations vary more among geomorphic units (wetlands = 5.1% versus bars = 2.0%) than among study rivers (Dall River = 3.8% versus Teedrinjik River = 2.3%), suggesting that reach‐scale geomorphic processes more strongly control the spatial distribution of OC than basin‐scale processes. Investigating differences at the basin and reach scale is necessary to accurately assess the amount and distribution of floodplain soil OC, as well as the geomorphic controls on OC.
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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 | 0.001 |
| 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) | 0.001 | 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".