Species diversity and community structure of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in an eastern amazonian forest
Bibliographic record
Abstract
Deforestation has negative impacts on diversity and community patterns of several taxa. In the eastern Amazon, where much deforestation is predicted for the coming years, forests patches may be essential to maintain the local biodiversity. Despite increasing concerns about the conservation of threatened areas, few studies have been performed to analyze the communities of diversified groups, such as insects, in the eastern Amazon. Here, we investigated species diversity and community structure of fruit-feeding butterflies, a well-known bioindicator group, in a threatened remnant of an eastern Amazonian forest located on Maranhão Island, northeastern Brazil. Fruit-feeding butterflies were sampled monthly for one year. Diversity and evenness indices, richness estimators, rarefaction curve, and rank-abundance plot were used to describe community structure in the study area. We captured 529 fruit-feeding butterflies in four subfamilies, 23 genera and 34 species. The three most abundant species, Hamadryas februa, Hamadryas feronia, and Hermeuptychia cf. atalanta are indicators of disturbed habitats and represented more than half of the collected individuals. Richness estimators revealed that between 87 and 94% of the fruit-feeding butterfly species were sampled, suggesting few additional records would be made for the area. Our results indicate that human-caused disturbances have altered local community patterns and provide baseline data for future research in threatened regions of the eastern Amazon.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".