Identification of the vascular plants of Churchill, Manitoba, using a DNA barcode library
Bibliographic record
Abstract
BACKGROUND: Because arctic plant communities are highly vulnerable to climate change, shifts in their composition require rapid, accurate identifications, often for specimens that lack diagnostic floral characters. The present study examines the role that DNA barcoding can play in aiding floristic evaluations in the arctic by testing the effectiveness of the core plant barcode regions (rbcL, matK) and a supplemental ribosomal DNA (ITS2) marker for a well-studied flora near Churchill, Manitoba. RESULTS: This investigation examined 900 specimens representing 312 of the 354 species of vascular plants known from Churchill. Sequencing success was high for rbcL: 95% for fresh specimens and 85% for herbarium samples (mean age 20 years). ITS2 worked equally well for the fresh and herbarium material (89% and 88%). However, sequencing success was lower for matK, despite two rounds of PCR amplification, which reflected less effective primer binding and sensitivity to the DNA degradation (76% of fresh, 45% of herbaria samples). A species was considered as taxonomically resolved if its members showed at least one diagnostic difference from any other taxon in the study and formed a monophyletic clade. The highest species resolution (69%) was obtained by combining information from all three genes. The joint sequence information for rbcL and matK distinguished 54% of 286 species, while rbcL and ITS2 distinguished 63% of 285 species. Discrimination of species within Salix, which constituted 8% of the flora, was particularly problematic. Despite incomplete resolution, the barcode results revealed 22 misidentified herbarium specimens, and enabled the identification of field specimens which were otherwise too immature to identify. Although seven cases of ITS2 paralogy were noted in the families Cyperaceae, Juncaceae and Juncaginaceae, this intergenic spacer played an important role in resolving congeneric plant species at Churchill. CONCLUSIONS: Our results provided fast and cost-effective solution to create a comprehensive, effective DNA barcode reference library for a local flora.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".