Long‐term cyanobacterial dynamics from lake sediment <scp>DNA</scp> in relation to experimental eutrophication, acidification and climate change
Bibliographic record
Abstract
Abstract Cyanobacterial blooms in aquatic environments have impacted ecosystem health, altered food webs and contributed to substantial regional economic losses. The relative impacts of climate change, eutrophication and other environmental stressors on the formation of cyanobacterial blooms remain unclear as a consequence of the lack of long‐term data. The analysis of lake sediment archives can help address such questions. The abundance of target cyanobacterial genes was quantified using droplet digital PCR from two experimental and two reference lakes at the IISD ‐ Experimental Lakes Area, Northwestern Ontario, Canada where various anthropogenic drivers have been manipulated and phytoplankton biomass and taxonomy (via microscopy) tracked over the past 50 years. Based on sediment DNA (sedDNA) records, Lake 227 has seen more than two full orders of magnitude rise in cyanobacterial abundance in response to experimental nutrient (nitrogen and phosphorus) loading since 1969. Lake 223 also experienced a small increase in cyanobacterial abundance during a period of experimental acidification. The sedDNA archives also identified an increase in abundance of mcyE , a gene involved in microcystin synthesis, in Lake 227 after 1990 when experimental nitrogen loading ceased and only phosphorus loading continued. Sequencing of the cyanobacterial 16S rRNA gene from sedDNA revealed a shift towards Nostocales dominance in response to eutrophication in Lake 227; this was also seen in the more recent sediments of the other lakes but to a much lesser extent. When comparing the sedDNA data with historical phytoplankton records of the past ~50 years, moderate‐to‐strong correlations were found between the two. This research validated the use of sedDNA for the analysis of long‐term trends in lakes and the results revealed additional changes that were not recorded from the surface‐water records. Experimental nutrient loading had the greatest influence on the cyanobacterial community in Lake 227. However, climate change, via declines in heating degree days, was also significant in explaining variation in the cyanobacterial communities in the experimental lakes as well as the reference lakes.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".