Multimolecular tracers of terrestrial carbon transfer across the pan‐Arctic: <sup>14</sup>C characteristics of sedimentary carbon components and their environmental controls
Bibliographic record
Abstract
Abstract Distinguishing the sources, ages, and fate of various terrestrial organic carbon (OC) pools mobilized from heterogeneous Arctic landscapes is key to assessing climatic impacts on the fluvial release of carbon from permafrost. Through molecular 14 C measurements, including novel analyses of suberin‐ and/or cutin‐derived diacids (DAs) and hydroxy fatty acids (FAs), we compared the radiocarbon characteristics of a comprehensive suite of terrestrial markers (including plant wax lipids, cutin, suberin, lignin, and hydroxy phenols) in the sedimentary particles from nine major arctic and subarctic rivers in order to establish a benchmark assessment of the mobilization patterns of terrestrial OC pools across the pan‐Arctic. Terrestrial lipids, including suberin‐derived longer‐chain DAs (C 24,26,28 ), plant wax FAs (C 24,26,28 ), and n ‐alkanes (C 27,29,31 ), incorporated significant inputs of aged carbon, presumably from deeper soil horizons. Mobilization and translocation of these “old” terrestrial carbon components was dependent on nonlinear processes associated with permafrost distributions. By contrast, shorter‐chain (C 16,18 ) DAs and lignin phenols (as well as hydroxy phenols in rivers outside eastern Eurasian Arctic) were much more enriched in 14 C, suggesting incorporation of relatively young carbon supplied by runoff processes from recent vegetation debris and surface layers. Furthermore, the radiocarbon content of terrestrial markers is heavily influenced by specific OC sources and degradation status. Overall, multitracer molecular 14 C analysis sheds new light on the mobilization of terrestrial OC from arctic watersheds. Our findings of distinct ages for various terrestrial carbon components may aid in elucidating fate of different terrestrial OC pools in the face of increasing arctic permafrost thaw.
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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 | 0.000 | 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 | 0.001 |
| 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 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".