Anthropogenic Perturbations Change the Quality and Quantity of Terrestrial Carbon Flux to the Coastal Ocean
Bibliographic record
Abstract
Abstract Human activities have increasingly changed terrestrial particulate organic carbon (POC) export to the coastal ocean since the Industrial Age (19th century). However, the influence of human perturbations on the composition and flux of terrestrial biospheric and petrogenic POC sub‐pools remains poorly constrained. Here, we examined 13C and 14C compositions of bulk POC and source‐specific biomarkers (fatty acids, FA) from two nearshore sediment cores collected in the Pearl River‐derived mudbelt, to determine the impacts of human perturbations of the Pearl River watershed on the burial of terrestrial POC in the coastal ocean over the last century. Our results show that although agricultural practices and deforestation during the 1930s–1950s increased C4 plant coverage in the watershed, the export fluxes of terrestrial biospheric and petrogenic POC remained rather unchanged; however, added perturbations since 1974, including increasing coal consumption, embankment and dam constructions caused massive export of both petrogenic POC and relatively fresh terrestrial biospheric POC from the river delta. Our data reveal that human activities substantially enhance the transfer of petrogenic POC and fresh biospheric POC to the coastal ocean after ca. 1974, with the latter process acting as an important sink for anthropogenic CO2.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".