Tropical wet season runoff mobilises younger carbon in rainforest streams but older carbon in agricultural streams
Bibliographic record
Abstract
Abstract. Knowledge of the age of organic carbon (C) that is leached from soils to streams is key to understanding how C is mobilised within ecosystems. The tropics are characterised by significant C fluxes through streams, yet the time scales of organic C sequestration and export remain uncertain in these regions. Here we examined the concentration, composition and age of dissolved organic C (DOC) in 18 small mountainous catchments of the Australian humid tropics, including six rainforest and 12 agricultural catchments, sampled during both the dry and wet seasons. We found that DOC ages varied widely across sites but were generally centuries to millennia old (median ± standard deviation 1,553 ± 848 years BP), with no consistent differences between rainforest and agricultural catchments. However, the two land use categories diverged in their responses to high flow conditions, with DOC age in rainforest streams tending to decrease from 1,878 ± 604 years BP in the dry season to 708 ± 791 years BP in the wet season, whereas agricultural streams mobilised similarly aged or older DOC in the wet season (1,728 ± 641 years BP) than in the dry season (1,303 ± 1,036 years BP). A subset of dissolved inorganic C (DIC) samples collected from three of the catchments (both rainforest and agricultural) indicated that DIC was mostly modern (123 ± 136 years BP) and always younger than DOC. These differences in DIC and DOC ages suggest a partial decoupling between DOC and DIC export pathways, with DOC derived from older soil C pools, while DIC reflected recent C inputs from vegetation uptake and decomposition. Our results highlight the importance of seasonal shifts in the age of C export and the need to conduct sampling that encompasses seasonality in human-impact studies to better constrain C pools and sinks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".