High diversity of freshwater invertebrates on inuinnait nuna, the canadian arctic, revealed using mitochondrial DNA barcodes
Bibliographic record
Abstract
Knowledge of genetic and species-level diversity for freshwater invertebrates in the Canadian Arctic is currently limited. Here, we sampled benthic and planktonic invertebrates from 68 ponds, seven lakes, and six rivers near Cambridge Bay (Iqaluktuuttiaq), Nunavut, between 2018 and 2021 and analysed individuals using mitochondrial cytochrome c oxidase subunit 1 (COI) gene sequences. From the 9336 specimens collected, 7186 provided sequences > 400 base pairs (83% success rate), representing 3358 unique haplotypes and 467 putative species based on Barcode Index Numbers (BINs; as a surrogate for species-level diversity). Chironomidae (non-biting midges) was the most diverse taxon, followed by Trombidiformes mites and Anomopoda (water fleas). Species’ accumulation curves for total diversity as well as the major taxa suggest that taxa we identified represent < 63% of the total diversity likely to be found in this region of the western Canadian Arctic (estimated n = 739) during the ice-free season. Further sampling over a wider geographical range as well as assessments of temporal (seasonal and inter-annual) variability will be required to assess comprehensively the total species richness currently found in the Canadian Arctic. In the interim, the publicly available data we provide here can be used as a baseline for ongoing studies and to track ecological changes occurring in aquatic habitats of the central Canadian Arctic and beyond.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".