Environmental drivers of mixotrophs in boreal lakes
Bibliographic record
Abstract
Abstract Mixotrophy is increasingly recognized as an important trophic pathway among phytoplankton, yet its underlying drivers remain largely unknown and unexplored. Here, we present a study utilizing 69 lake samplings in boreal Quebec, Canada, identifying variables driving the success of phytoplankton that have a capacity for mixotrophy and pointing to the underlying mechanisms. We found that the success of mixotrophs (% of total biomass) was positively influenced by both colored dissolved organic matter (cDOM) and dissolved CO 2 concentration but limited by the abundance of crustacean zooplankton. The effect of cDOM manifested as a consequence of limited autotrophic phytoplankton biomass in lakes with reduced light penetration. We observed a nonlinear (u‐shaped) relation between CO 2 and mixotrophs, with biomass favored at both low and high CO 2 concentrations. A reduced fitness of mixotrophs at near‐atmospheric CO 2 concentrations is likely owing to the costs of rapidly switching between or maintaining multiple trophic strategies. The abundance of zooplankton had a negative effect on mixotroph biomass but a positive effect on autotrophic phytoplankton. We also found that while the community composition of potentially mixotrophic phytoplankton was to some degree likely influenced by zooplankton biomass, composition was unaffected by the CO 2 and cDOM gradients. Overall, this study highlights mixotrophy in boreal lake systems as a strategy of persistence, with the maintenance of a moderate but constant presence across a changing gradient of light and trophic conditions. The results of our study support the hypothesis that phytoplankton with a capacity for mixotrophy provide a superior and stable stoichiometric food source for zooplankton, implicating mixotrophs as a vital component of boreal lake food webs.
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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 | 0.000 |
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".