Flux of Dissolved and Particulate Low-Temperature Pyrogenic Carbon from Two High-Latitude Rivers across the Spring Freshet Hydrograph
Bibliographic record
Abstract
A number of recent studies have documented that pyrogenic carbon (PyC) is an integral and significant proportion of DOM in worldwide rivers. This material originates from all fractions of the PyC continuum, from highly condensed PyC to more functionalized components that retain some structural identity of fuel molecules. Understanding the transfer of PyC to river systems is paramount for Arctic regions, given the projected increase in frequency and intensity of forest fires within these ecosystems. However, the environmental distribution and concentration of soluble and particulate PyC, parameters that govern the overall fate of PyC in aquatic systems, has so far been unstudied. Here, we analyze the concentration and phase distribution of the anhydrosugar biomarker levoglucosan, as a proxy for low-temperature PyC, in two high-latitude river systems: a small sub-Arctic Canadian river, the Great Whale River in northern Québec, and the largest Arctic River, the Yenisei River in north-central Siberia. Low-temperature PyC, as estimated by levoglucosan concentrations, is exported predominantly in the dissolved phase. Peak export of low-temperature PyC occurs during the spring freshet period in both rivers. Seasonal variability of dissolved and particulate PyC export in each river elucidated that the export of PyC in the particulate and dissolved phases were temporally decoupled throughout the peak discharge events. While the present work confirms that levoglucosan is exported in particulate phase at a high enough level to enter sedimentary deposits and record historical wildfire signatures, as the phase distribution varies between rivers and during different flow regimes, spatial and temporal differences may affect the usage of levoglucosan as a PyC proxy in depositional settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 teacher head, 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".