Using metabarcoding and droplet digital PCR to investigate drivers of historical shifts in cyanobacteria from six contrasting lakes
Bibliographic record
Abstract
The frequency and intensity of cyanobacterial blooms is increasing worldwide. Multiple factors are implicated, most of which are anthropogenic. New Zealand provides a useful location to study the impacts of human settlement on lake ecosystems. The first humans (Polynesians) arrived about 750 years ago. Following their settlement, there were marked landscape modifications which intensified after European settlement about 150 years ago. The aims of this study were to reconstruct cyanobacterial communities in six lakes over the last 1000 years and explore key drivers of change. Cyanobacterial environmental DNA was extracted from sediment cores and analysed using metabarcoding and droplet digital PCR. Cyanobacteria, including potentially toxic or bloom forming species, were already present in these lakes prior to human arrival, however their overall abundance was low. Total cyanobacteria abundance and richness increased in all lakes after European settlement but was very pronounced in four lakes, where bloom-forming taxa became dominant. These shifts occurred concomitant with land-use change. The catchment of one deteriorated lake is only moderately modified, thus the introduction of non-native fish is posited as the key factor driving this change. The paleolimnological approach used in this study has enabled new insights into timing and potential causes of changes in cyanobacterial communities.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".