Butterfly Communities Vary under Different Urbanization Types in City Parks
Bibliographic record
Abstract
Butterflies are key indicators of urban biodiversity and one of the most vulnerable organism groups to environmental changes. Studying how butterflies are distributed and what factors might influence them in urban green spaces is crucial. In this study, from July 2022 to September 2022, we examined and analyzed the butterfly diversity in nine parks in Fuzhou, China, along three different levels of urbanization (urban, peri-urban, and suburban). We investigated how butterfly communities respond to increasing urbanization. The findings revealed that: (1) A total of 427 butterfly individuals from 4 families and 13 species were observed; (2) Shannon diversity, richness, and abundance of the overall butterfly community were lower in the more urbanized parks. Urbanization had significant effects on Shannon diversity (p = 0.003) and abundance (p = 0.007) but no significant effects on the whole butterfly community richness (p = 0.241); (3) non-metric multidimensional scaling revealed that there were differences in the overall number of butterfly species in urban parks among different geographic regions.
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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) | 0.001 | 0.001 |
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".