Erosion of organic carbon from the Andes and its effects on ecosystem carbon dioxide balance
Bibliographic record
Abstract
Abstract Productive forests of the Andes are subject to high erosion rates that supply to the Amazon River sediment and carbon from both recently photosynthesized biomass and geological sources. Despite this recognition, the source and discharge of particulate organic carbon (POC) in Andean Rivers remain poorly constrained. We collected suspended sediments from the Kosñipata River, Peru, over 1 year at two river gauging stations. Carbon isotopes (14C, 13C, and 12C) and nitrogen to organic carbon ratios of the suspended sediments suggest a mixture of POC from sedimentary rocks (POCpetro) and from the terrestrial biosphere (POCbiosphere). The majority of the POCbiosphere has a composition similar to surface soil horizons, and we estimate that it is mostly younger than 850 14C years. The suspended sediment yield in 2010 was 3500 ± 210 t km−2 yr−1, >10 times the yield from the Amazon Basin. The POCbiosphere yield was 12.6 ± 0.4 t C km−2 yr−1 and the POCpetro yield was 16.1 ± 1.4 t C km−2 yr−1, mostly discharged in the wet season (December to March) during flood events. The river POCbiosphere discharge is large enough to play a role in determining whether Andean forests are a source or sink of carbon dioxide. The estimated erosional discharge of POCpetro from the Andes is much larger (~1 Mt C yr−1) than the POCpetro discharge by the Madeira River downstream in the Amazon Basin, suggesting that oxidation of POCpetro counters CO2 drawdown by silicate weathering. The flux and fate of Andean POCbiosphere and POCpetro need to be better constrained to fully understand the carbon budget of the Amazon River basin.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".