Characterization and comparison of poorly known moth communities through DNA barcoding in two Afrotropical environments in Gabon
Bibliographic record
Abstract
Biodiversity research in tropical ecosystems-popularized as the most biodiverse habitats on Earth-often neglects invertebrates, yet invertebrates represent the bulk of local species richness. Insect communities in particular remain strongly impeded by both Linnaean and Wallacean shortfalls, and identifying species often remains a formidable challenge inhibiting the use of these organisms as indicators for ecological and conservation studies. Here we use DNA barcoding as an alternative to the traditional taxonomic approach for characterizing and comparing the diversity of moth communities in two different ecosystems in Gabon. Though sampling remains very incomplete, as evidenced by the high proportion (59%) of species represented by singletons, our results reveal an outstanding diversity. With about 3500 specimens sequenced and representing 1385 BINs (Barcode Index Numbers, used as a proxy to species) in 23 families, the diversity of moths in the two sites sampled is higher than the current number of species listed for the entire country, highlighting the huge gap in biodiversity knowledge for this country. Both seasonal and spatial turnovers are strikingly high (18.3% of BINs shared between seasons, and 13.3% between sites) and draw attention to the need to account for these when running regional surveys. Our results also highlight the richness and singularity of savannah environments and emphasize the status of Central African ecosystems as hotspots of biodiversity.
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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 | 0.000 |
| 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".