Diversity and life-cycle analysis of Pacific Ocean zooplankton by videomicroscopy and DNA barcoding: Crustacea
Bibliographic record
Abstract
Crustacea larvae and adults make up a large fraction of the biomass and number of organisms in both holoplankton (organisms that spend their entire lives in the plankton) and meroplankton (organisms that spend their larval stages in the plankton). The life cycles of these animals can be studied by raising individuals and studying them longitudinally in the laboratory, but this method can be very laborious. Here we show that DNA sequencing of a small element in the mitochondrial DNA (DNA barcoding) makes it possible to easily link life-cycle phases without the need for laboratory rearing. It can also be used to construct taxonomic trees, although it is not yet clear to what extent this barcode-based taxonomy reflects more traditional morphological or molecular taxonomy. Collections of zooplankton were made using conventional plankton nets in Newport Bay and the Pacific Ocean near Newport Beach, California, and individual crustacean specimens were documented by videomicroscopy. Adult crustaceans were collected from solid substrates in the same areas. Specimens were preserved in ethanol and sent to the Canadian Centre for DNA Barcoding at the University of Guelph, Ontario, Canada for sequencing of the COI DNA barcode. From 1042 specimens, 609 COI sequences were obtained falling into 169 Barcode Identification Numbers (BINs), of which 85 correspond to recognized species. The results show the utility of DNA barcoding for matching life-cycle stages as well as for documenting the diversity of this group of organisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".