Data from: Complex phylogeographic patterns in the freshwater alga Synura provide new insights on ubiquity versus endemism in microbial eukaryotes
Bibliographic record
Abstract
The global distribution, abundance, and diversity of microscopic freshwater algae demonstrate an ability to overcome significant barriers such as dry land and oceans by exploiting a range of biotic and abiotic colonization vectors. If these vectors are considered unlimited and colonization occurs in proportion to population size, then globally ubiquitous distributions are predicted to arise. This model contrasts with observations that many freshwater microalgal taxa possess true biogeographies. Here, using a concatenated multi-gene dataset, we study the phylogeography of the freshwater heterokont alga Synura petersenii sensu lato. Our results suggest that this Synura morphotaxon contains both cosmopolitan and regionally endemic cryptic species, co-occurring in some cases, and masked by a common ultrastructural morphology. Phylogenies based on both proteins (seven protein-coding plastid and mitochondrial genes) and DNA (nine genes including ITS and 18S rDNA) reveal pronounced biogeographic delineations within phylotypes of this cryptic species complex, while retaining one clade that is globally distributed. Relaxed molecular clock calculations, constrained by fossil records, suggest that the genus Synura is considerably older than currently proposed. The availability of tectonically-relevant geological time (10^7-10^8 years) has enabled the development of the observed, complex biogeographic patterns. Our comprehensive analysis of freshwater algal biogeography suggests that neither ubiquity nor endemism wholly explain global patterns of microbial eukaryote distribution, and that processes of dispersal remain poorly understood.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".