Species Richness and Distribution of Calliphoridae Along an Elevation Gradient in Sicily (Italy) and Ecuador
Bibliographic record
Abstract
Blow flies (Diptera: Calliphoridae) are among the first insects to arrive on a corpse, and so they are particularly important in forensic entomology. To use blow flies in forensic investigations, there must be information available on their species diversity, abundance, and distribution in the areas where investigations are conducted. Several factors can contribute to species distribution, and elevation is one of those factors. The purpose of this study was to document the distribution of Calliphoridae across four elevational gradients in Sicily and Ecuador, where little information is available. Baited traps were placed at elevations ranging from 20 m to 1552 m in Sicily (a major island and region of Italy and a distinct ecoregion) and 561 m to 3336 m in Ecuador. Species richness, relative abundance, and diversity were calculated, as well as the ratio of female to male blow flies and community assemblage. Twelve species were collected in Sicily, and seventeen species were collected in Ecuador. In Sicily, the most abundant species was Lucilia sericata (Meigen) (68.50% of the total capture), while in Ecuador, it was Compsomyiops verena (Walker) (51.67% of the total capture). In Sicily, significant differences were only observed in the relative abundance of L. sericata across elevations. In Ecuador, significant differences were observed in the relative abundance of Calliphora nigribasis (Macquart), Chrysomya albiceps (Wiedemann), C. verena, Hemilucilia semidiaphana (Rondani), Lucilia ibis (Shannon), L. purpurascens (Walker), and Paralucilia sp. across elevations. These data can help build a checklist of blow fly species in these two regions and can be instrumental in environmental and forensic investigations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".