Early human impact on lake cyanobacteria revealed by a Holocene record of sedimentary ancient DNA
Bibliographic record
Abstract
Sedimentary DNA-based studies revealed the effects of human activity on lake cyanobacteria communities over the last centuries, yet we continue to lack information over longer timescales. Here, we apply high-resolution molecular analyses on sedimentary ancient DNA to reconstruct the history of cyanobacteria throughout the Holocene in a lake in north-eastern Germany. We find a substantial increase in cyanobacteria abundance coinciding with deforestation during the early Bronze Age around 4000 years ago, suggesting increased nutrient supply to the lake by local communities settling on the lakeshore. The next substantial human-driven increase in cyanobacteria abundance occurred only about a century ago due to intensified agricultural fertilisation which caused the dominance of potentially toxic taxa (e.g., Aphanizomenon). Our study provides evidence that humans began to locally impact lake ecology much earlier than previously assumed. Consequently, managing aquatic systems today requires awareness of the legacy of human influence dating back potentially several millennia.
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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 | 0.000 | 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".