Global biogeography and diversification of a group of brown seaweeds (Phaeophyceae) driven by clade‐specific evolutionary processes
Bibliographic record
Abstract
Abstract Aim Historical processes that shaped current diversity patterns of seaweeds remain poorly understood. Using Dictyotales, a globally distributed order of brown seaweeds as a model, we test if historical biogeographical and diversification patterns are comparable across clades. Dictyotales contain some 22 genera, three of which, Dictyota, Lobophora and Padina, are exceptionally diverse. Specifically, we test whether the evolutionary processes that shaped the latitudinal diversity patterns in these clades are in line with the tropical conservatism, out‐of‐the‐tropics or diversification rate hypotheses. Location Global coastal benthic marine environments. Taxon Dictyotales (Phaeophyceae). Methods Species diversity was inferred using DNA‐based species delineation, addressing cryptic diversity and circumventing taxonomic problems. A six‐gene time‐calibrated phylogeny, distribution data of 3,755 specimens and probabilistic modelling of geographical range evolution were used to infer historical biogeographical patterns. The phylogeny was tested against different trait‐dependent models to compare diversification rates for different geographical units as well as different thermal affinities. Results Our results indicate that Dictyotales originated in the Middle Jurassic and reach a current peak of species diversity in the Central Indo‐Pacific. Ancestral range estimation points to a southern hemisphere origin of Dictyotales corresponding to the tropical southern Tethys Sea. Our results demonstrate that diversification rates were generally higher in tropical regions, but increased diversification rates in different clades are driven by different processes. Our results suggest that three major clades underwent a major diversification burst in the early Cenozoic, with Dictyota and Padina expanding their distribution into temperate regions while Lobophora retained a predominantly tropical niche. Main conclusions Our results are consistent with both the tropical conservatism hypothesis, in which clades originate and remain in the tropics (Lobophora), and the out‐of‐the‐tropics scenario, where taxa originate and expand towards the temperate regions while preserving their presence in the tropics (Dictyota, Padina).
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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 | 0.001 |
| 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 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".