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Discriminating plant species in a local temperate flora using the <i>rbcL</i>+<i>matK</i> DNA barcode

2011· article· en· W2151714956 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMethods in Ecology and Evolution · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaUniversity of Guelph
FundersOntario GenomicsUniversity of GuelphOntario Genomics InstituteGenome Canada
KeywordsBarcodeDNA barcodingBiologyIntergenic regionDNA sequencingLocus (genetics)BotanyEvolutionary biologyGeneGeneticsGenomeComputer science

Abstract

fetched live from OpenAlex

Summary 1. A major goal of DNA barcoding is to identify species in local floras and ecological communities. With the consensus of a two‐locus DNA barcode ( rbcL+matK ) by the Consortium for the Barcode of Life (CBOL) Plant Working Group (2009), barcoding efforts have begun to focus on building the barcode library for land plants. 2. Here, we establish a barcoding database for a temperate flora of moderate taxonomic breadth at the Koffler Scientific Reserve, Ontario, Canada based on the rbcL+matK barcode. We evaluated the performance of this combination in comparison with three other potential supplementary regions (the coding region rpoC1 and two non‐coding intergenic spacers trnH‐psbA and atpF‐atpH ). We examined these markers singly and in combination to evaluate their discriminatory power among 436 species in 269 genera of land plants. 3. Using high‐throughput techniques, we recovered a high‐quality sequence from at least one region for 98.2% of the 513 samples screened; 55% had complete coverage across all five gene regions. Sequencing success was highest for rbcL (91.4% of samples collected) and lowest for rpoC1 (74.5%). The two coding regions rbcL and matK provided a relatively high number of high‐quality bi‐directional sequences compared with the non‐coding intergenic spacers, and in combination were able to correctly identify 93.1% of the species sampled. Marginal increases in species resolution were obtained with the inclusion of the trnH‐psbA intergenic spacer (95.3%), or by using all five gene regions combined (97.3%). 4. There was a weak relation between the number of species per genus and identification success rate using rbcL+matK ; 100% for monotypic genera (70.5% of the flora) and 83.6% for polytypic genera. Identification success using the rbcL+matK barcode was higher (100%) for gymnosperms, bryophytes, lycophytes and monilophytes (collectively representing 5% of the flora), compared with angiosperms (92.7%). 5. Our results indicate that the rbcL+matK barcode can provide an acceptably high rate of species resolution in the context of this and other local northern temperate floras. It does so in a cost‐effective manner, with relatively modest laboratory effort, and despite the presence of missing data from individual plastid regions in a subset of samples.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.282
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it