Deltaic Burial of Authigenic Calcite Modulates the Carbon Balance of Hardwater Lakes
Bibliographic record
Abstract
Abstract. Inland waters play an important role in the terrestrial carbon cycle by burying carbon in aquatic sediments while simultaneously releasing CO2 to the atmosphere and laterally exporting carbon along the land-ocean aquatic continuum. Especially in hardwater lakes, where increased primary productivity can trigger CO2 outgassing via calcite precipitation, the interactions of processes influencing the balance between carbon burial and release remains incompletely constrained. To better understand these dynamics, we analyzed organic and inorganic carbon fluxes in a year long (June 2022 to June 2023) sediment trap study in Lake Geneva, the largest natural lake in Western Europe. Two sediment traps - one deployed in the subaqueous delta of the upper Rhône River, the other in the lake’s deepest basin - were sampled monthly. Analyzing the radiocarbon (14C) signatures of particulate organic and inorganic carbon, allowed us to resolve allochthonous (external) and autochthonous (internal) contributions to absolute carbon fluxes. We found that the flux of autochthonous particulate inorganic carbon in the river-proximal deltaic site was approximately four times higher than in the distal one. This is likely the result of calcite precipitation driven by increased fluvial supply of nutrients and suspended carbonate-bearing particles. Sediment core analysis in the same location suggests efficient preservation of this calcite over at least centennial timescales, which we conservatively estimate around 7-10 Gg C yr-1 lake-wide. This indicates at least partial offset of the CO2 released during calcite precipitation and is an important flux to be considered in mechanistic carbon cycle models.
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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 | 0.000 | 0.000 |
| 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".