Are small mountainous tropical watersheds of oceanic islands important for carbon export?
Bibliographic record
Abstract
Abstract. In the tropic, the small watersheds are affected by intense meteorological events playing an important role on the erosion of soils and therefore on the associated organic carbon fluxes. We studied the geochemistry of three small watersheds around the Basse-Terre volcanic Island (FWI) during a four years period, by measuring DOC, POC and DIC concentrations. The mean annual yields ranged 8.1–15.8 t C km−2 yr−1, 1.9–8.6 t C km−2 yr−1 and 8.1–25.5 t C km−2 yr−1 for DIC, DOC and POC, respectively. Floods and extreme floods represent 45 to 70 % of the annual DOC flux, and more than 80 % of the annual POC flux. The DIC flux occurs essentially during the low water level, only 43 % of the annual DIC flux is exported during floods. The distribution of the dissolved carbon between the inorganic and the organic fraction is correlated to the hydrodynamic of rivers. During low water level and floods, the dissolved carbon is exported under the inorganic form (DIC/DOC = 2.6 ± 2.1), while during extreme floods, the dissolved carbon transported is mostly organic (DIC/DOC = 0.7 ± 0.2). The residence time of the organic carbon in Guadeloupean soils may vary from 381 to 1000 yr, and is linked to the intensity of meteorological events than the frequency of meteorological events. Looking at the global carbon mass balance, the total export of organic carbon coming from small tropical and volcanic mountainous rivers is estimated about 2.0–8.9 Tg C yr−1 for DOC and about 8.4–26.5 Tg C yr−1 for POC, emphasizing that these carbon fluxes are significant and should be included in global carbon budgets.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".