Centuries of change: Salinity and carbon dynamics in a large shallow lake
Bibliographic record
Abstract
This study examines over a century of salinity changes in Lake Balaton, the largest shallow lake in Central Europe. Total ion concentrations have increased from a historical baseline of 450 mg/L to approximately 650 mg/L today, with an annual rise of 5.0 mg/L in the largest basin since the 1970s. Notable annual increases include magnesium (0.7 mg/L), sodium (0.6 mg/L), chloride (0.7 mg/L), sulfate (1.8 mg/L), and bicarbonate-carbonate ions (1.0 mg/L). In contrast, calcium levels have remained stable due to substantial calcite precipitation, which reduces the calcium content of inflowing waters by over half. Calcite precipitation in Lake Balaton varies significantly, ranging from 25,000 to 125,000 tons/year, with an average of 75,000 tons/year between 2010 and 2022. Biologically induced calcite precipitation, driven by photosynthesis, occurs seasonally during summer but dissolves again in autumn and winter. However, the majority of calcite precipitation is non-biogenic, driven by the equilibration of CO 2 -supersaturated inflows with atmospheric CO 2 . This process releases approximately 33,000 tons of CO 2 annually, underscoring Lake Balaton’s contribution to global carbon cycling. These findings highlight the combined impact of natural processes and anthropogenic influences on Lake Balaton’s salinity and biogeochemical dynamics, emphasizing its importance as a model for understanding the broader implications of freshwater salinization and carbon flux in shallow lakes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Research integrity | 0.001 | 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".