New views on “old” carbon in the Amazon River: Insight from the source of organic carbon eroded from the Peruvian Andes
Bibliographic record
Abstract
Abstract Mountain rivers play a key role in the delivery of particulate organic carbon (POC) to large river systems and the ocean. Due to the extent of its drainage area and runoff, the Amazon River is one of Earth's most important biogeochemical systems. However, the source of POC eroded from the humid region of the Eastern Andes and the input of fossil POC from sedimentary rocks (POCfossil) remains poorly constrained. Here we collected suspended sediments from the Kosñipata River during flood events to better characterize Andean POC, measuring the nitrogen to organic carbon ratio (N/C), stable carbon isotopes (δ13Corg) and radiocarbon (Δ14Corg). Δ14Corg values ranged from −711‰ to −15‰, and significant linear trends between Δ14Corg, N/C and δ13Corg suggested that this reflects the mixing of POCfossil with very young organic matter (Δ14Corg ~ 50‰) from the terrestrial biosphere (POCnon‐fossil). Using N/C and Δ14Corg in an end‐member mixing analysis, we quantify the fraction of POCfossil (to within 0.1) and find that it contributes a constant proportion of the suspended sediment mass (0.37 ± 0.03%) and up to 80% of total POC. In contrast, the relative contribution of POCnon‐fossil was variable, being most important during the rising limb and peak discharges of flood events. The new data shed light on published measurements of “old” POC (low Δ14Corg) in Andean‐fed tributaries of the Amazon River, with their Δ14Corg and δ13Corg values consistent with variable addition of POCfossil. The findings suggest a greater persistence of Andean POC in the lowland Amazon than previously recognized.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".