Diatom community composition on submerged macrophyte species from an Ontario (Canada) lake
Bibliographic record
Abstract
The introduction of invasive macrophyte species can affect submerged macrophyte community composition and abundance, which in turn can alter the functions of lake ecosystems. Knowing when and how invasive macrophytes arrive and spread can help disentangle the effects of invasive species from other stressors on lake ecosystems. This requires a long-term (decades) perspective of macrophyte community composition, which is rarely available. An alternative is paleolimnological inferences of macrophyte community composition from fossil diatom assemblages, which requires knowledge of epiphytic diatom communities. Here, we investigated the epiphytic diatom community composition of three common submerged macrophyte species (Chara sp., Potamogeton robbinsii, and the invasive Myriophyllum spicatum) in a typical temperate, mixed forest lake, Chandos Lake, Ontario, Canada, to provide a basis for future paleolimnological research. Non-parametric, multivariate analysis of variance indicated a statistically significant difference in the epiphytic diatom communities of different macrophyte species, despite principal components analysis showing some overlap among the diatom communities. Diatom community composition of all macrophytes had abundant Achnanthidium minutissimum and Cocconeis placentula. Generalized linear models and univariate analysis of variance identified six diatoms (Encyonopsis microcephala, Epithemia turgida, Gomphonema parvulius, Navicula gerloffi, Rhopalodia gibba, and Rossithidium anastasiae) that were significantly different among macrophyte species. Although it remains uncertain whether these differences are sufficient to infer historical macrophyte community composition from epiphytic diatom fossil assemblages, our results indicate the potential of such an approach and offer suggestions for future research.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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".