A comparative analysis of metacommunities reveals contrasting drivers of alpha and beta diversity in urban butterflies
Bibliographic record
Abstract
Abstract Urbanization reduces biodiversity and accelerates biotic homogenization, including among pollinators. However, questions remain concerning urban pollinator ecology and conservation, particularly: to what extent does pollinator alpha and beta diversity decline across urban landscapes, and what drives these patterns? We investigated the impacts of local and landscape characteristics on community diversity in four increasingly urban butterfly metacommunities, collecting data on butterfly diversity, butterfly host plant richness, flowering plant richness, and impervious surface area in the landscape. Suburban and urban metacommunities supported similarly low levels of butterfly diversity compared to a natural peri-urban metacommunity. Host plant richness increased butterfly diversity, but floral richness was correlated with reduced diversity, suggesting that many species-rich gardens are low in diversity of plants that support butterflies. In contrast, dissimilarity was driven by both local and landscape scale factors. Dissimilarities in site area and landscape impervious surface area drove overall dissimilarity, while these factors in addition to host and floral communities drove butterfly turnover (loss with replacement) and nestedness (loss without replacement). Our findings demonstrate that alpha and beta diversity are driven by different factors, and both must be considered to understand urban butterfly ecology and conservation. While butterfly species are filtered out of landscapes with high amounts of impervious surface area, even small sites can support diverse butterfly communities if they contain rich assemblages of butterfly host plants. Our comparative analysis of metacommunities provides a framework for future studies in human-altered environments.
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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".