Eutrophication and Warming Drive Algal Community Shifts in Synchronised Time Series of Experimental Lakes
Bibliographic record
Abstract
Lake ecosystems are increasingly impacted by eutrophication and climate change. Whole-lake experiments have provided ecosystem-scale insights into the effects of freshwater stressors, yet these are constrained to the duration of monitoring programmes. Here, we leveraged multidecadal monitoring records and century-scale paleogenetic reconstructions for experimentally fertilised and unmanipulated lakes in the IISD Experimental Lakes Area of northwestern Ontario, Canada, to evaluate the responses of algal communities to nutrient and air temperature variation. We first validated the paleogenetic analysis of sediment DNA by demonstrating the synchrony of algal community changes with monitoring records. Algal communities underwent significant compositional shifts across experimental nutrient loading regimes and climate periods, with baseline assemblages informed by paleogenetics. Nonlinear regression modelling of algal community change in monitoring and paleogenetic time series showed the expected response that nutrients were strong drivers in fertilised lakes. Paleogenetic records reflected the century-scale impacts of climate warming and its combined effects with eutrophication, previously underestimated by monitoring. The synergy between eutrophication and warming points to eutrophic priming of the food web to respond to rising temperatures. Overall, the paleogenetic integration of algal diversity across habitats and seasons enables the detection of slow-acting climate change on lake ecosystems increasingly altered by nutrient pollution.
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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) | 0.001 | 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 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".