Synergistic warming- and catchment-driven mid-Holocene cyanobacterial development: Pigment evidence from shallow eutrophic Lake Mayinghai on the Chinese Loess Plateau
Bibliographic record
Abstract
The current lake environmental problem of harmful cyanobacterial blooms cannot be mitigated effectively despite numerous eutrophication control strategies, and climate warming may have been considered as a potential key driver. However, it is still unclear how climate change and associated natural processes influence cyanobacterial development. Here we use a sedimentary pigment record from a remote, alpine, small and eutrophic lake (Lake Mayinghai) on the Chinese Loess Plateau and take the mid-Holocene as an analog to explore the possible influences of temperature, precipitation and terrestrial vegetation on in-lake and catchment processes, algal compositional changes and cyanobacterial development. The pigment data indirectly suggest that a distinctly low β -carotene to chlorophyll a ratio during the mid-Holocene is likely due to an increase in non-nitrogen-fixing colonial coccoid cyanobacteria at the expense of nitrogen-fixing filamentous cyanobacteria. There are two probable synergistic driving mechanisms, of which one is high temperatures and associated increased lake thermal stratification and the other is high inorganic nitrogen supply and resultant increased lake nitrogen to phosphorus ratio. This study provides implications for the potential influences of future climate change on cyanobacterial development under a warmer, wetter and re-forested environment on the Chinese Loess Plateau.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".