Reading the Complex Skipper Butterfly Fauna of One Tropical Place
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.
Bibliographic record
Abstract
Background: An intense, 30-year, ongoing biodiversity inventory of Lepidoptera, together with their food plants and parasitoids, is centered on the rearing of wild-caught caterpillars in the 120,000 terrestrial hectares of dry, rain, and cloud forest of Area de Conservacion Guanacaste (ACG) in northwestern Costa Rica. Since 2003, DNA barcoding of all species has aided their identification and discovery. We summarize the process and results for a large set of the species of two speciose subfamilies of ACG skipper butterflies (Hesperiidae) and emphasize the effectiveness of barcoding these species (which are often difficult and time-consuming to identify). Methodology/Principal Findings: Adults are DNA barcoded by the Biodiversity Institute of Ontario, Guelph, Canada; and they are identified by correlating the resulting COI barcode information with more traditional information such as food plant, facies, genitalia, microlocation within ACG, caterpillar traits, etc. This process has found about 303 morphologically defined species of eudamine and pyrgine Hesperiidae breeding in ACG (about 25% of the ACG butterfly fauna) and another 44 units indicated by distinct barcodes (n = 9,094), which may be additional species and therefore may represent as much as a 13% increase. All but the members of one complex can be identified by their DNA barcodes. Conclusions/Significance: Addition of DNA barcoding to the methodology greatly improved the inventory, both through faster (hence cheaper) accurate identification of the species that are distinguishable without barcoding, as well as those that require it, and through the revelation of species "hidden" within what have long been viewed as single species. Barcoding increased the recognition of species-level specialization. It would be no more appropriate to ignore barcode data in a species inventory than it would be to ignore adult genitalia variation or caterpillar ecology.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it