Cryptic diversity and significant cophylogenetic signal detected by DNA barcoding the rust fungi (Pucciniaceae) of Cyperaceae–Juncaceae
Bibliographic record
Abstract
Abstract Plants play important roles as habitat and food for a tremendous diversity of specialist animals and fungi. The disappearance of any plant species can lead to extinction cascades of its associated biota. In consequence, documenting the diversity and specificity of plant‐associated organisms is of high practical relevance in biodiversity conservation. Here, we present the first large‐scale molecular investigation into the diversity, host specificity, and cophylogenetic congruence of an especially rich plant–fungal association, the rust fungi (Pucciniaceae) of Cyperaceae and Juncaceae. Using the largest rust fungi DNA barcoding dataset published to date (252 sequences, 82 taxa), we reject the presence of a global ITS2‐28S barcode gap, but find a local gap in Cyperaceae–Juncaceae rusts, and suggest the existence of many cryptic species in North America, with some broadly circumscribed species possibly corresponding to >10 cryptic species. We test previous hypotheses of correlations between the phylogenies of rust fungi and their Cyperaceae–Juncaceae hosts using a combination of global‐fit and event‐based cophylogenetic methods. A significant cophylogenetic signal is detected between rusts and their hosts, but the small number of cospeciations argues for preferential host jumps as the driving process behind these correlations. In addition, temporal congruence between the origin of major Carex clades and their rusts suggests that host diversification may have promoted parasite diversification. Finally, we discuss the relevance of rust infection patterns to the systematics of Cyperaceae, highlight some taxonomic problems uncovered by the analyses, and call attention to the promise of DNA barcoding for bridging knowledge gaps in poorly studied plant‐associated microorganisms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".