Effects of temperature and oxygen on cyanobacterial DNA preservation in sediments: A comparison study of major taxa
Bibliographic record
Abstract
Abstract The analysis of sediment DNA has emerged as a promising alternative to classical paleolimnological proxies, which typically rely on hard fossils to reconstruct environmental change. In recent studies, the timing and causes of apparent increases in toxic cyanobacterial blooms in lakes around the world have been identified by high‐throughput sequencing of cyanobacterial 16S rRNA genes from decadal‐ and centennial‐scale sediment records. However, the reconstruction of ecological time series can be influenced by DNA degradation processes interfering with taxonomic resolution and quantification of target genes. To determine whether some cyanobacterial taxa degrade more rapidly than others, a one‐year incubation experiment was performed to estimate degradation rates in sediments under contrasting environmental conditions of temperature (4°C vs. 25°C) and sediment redox (oxic vs. anoxic). Using sediments collected from an oligotrophic lake, serum bottles were inoculated with either Microcystis aeruginosa , Synechococcus sp., or Trichormus variabilis . These cyanobacteria were chosen because they are widespread yet exhibit contrasting morphologies. The absolute concentrations of the target genes were measured over time through droplet digital PCR. The three taxa exhibited log‐linear declines with different rates of decay. Based on first‐order linear decay models, Microcystis exhibited faster decay under oxic conditions, whereas Synechococcu s sp. and Trichormus were both temperature and anoxic dependent. Overall, cyanobacterial decay rates were lowest under 4°C anoxic conditions, corresponding to conditions in deep temperate lakes. Under 4°C, Synechococcus exhibited the lowest degradation rates followed by Trichormus , then Microcystis . These findings will be useful in the interpretation of population and community structure data based on sediment DNA and advances our current understanding of cyanobacterial preservation in sediment.
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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) | 0.000 | 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 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".