Tropical niche conservatism and the species richness gradient of North American butterflies
Bibliographic record
Abstract
Abstract Aim We explore the potential role of the ‘tropical conservatism hypothesis’ in explaining the butterfly species richness gradient in North America. Its applicability can be derived from the tropical origin of butterflies and the presumed difficulties in evolving the cold tolerance required to permit the colonization and permanent occupation of the temperate zone. Location North America. Methods Digitized range maps for butterfly species north of Mexico were used to map richness for all species, species with distributions north of the Tropic of Capricorn (Extratropicals), and species that also occupy the tropics (Tropicals). A phylogeny resolved to subfamily was used to map the geographical pattern of mean root distance, a metric of the evolutionary development of assemblages. Regression models and general linear models examined environmental correlates of overall richness and for Extratropicals vs. Tropicals, patterns in summer vs. winter, and patterns in northern vs. southern North America. Results Species in more basal subfamilies dominate the south, whereas more derived clades occupy the north. There is also a ‘latitudinal’ richness gradient in Canada/Alaska, whereas in the conterminous USA richness primarily varies longitudinally. Overall richness is associated with broad‐ and mesoscale temperature gradients. The richness of Tropicals is strongly associated with temperature and distance from winter population sources. The richness of Extratropicals in the north is most strongly correlated with the pattern of glacial retreat since the more recent Ice Age, whereas in the south, richness is positively associated with the range of temperatures in mountains and the presence of forests but is negatively correlated with the broad‐scale temperature gradient. Main conclusions The tropical conservatism hypothesis provides a possible explanation for the complex structure of the species richness gradient. The Canada/Alaska fauna comprises temperate, boreal and tundra species that are nevertheless constrained by cold climates and limited vegetation, coupled with possible post‐Pleistocene recolonization lags. In the USA tropical species are constrained by temperature in winter as well as recolonization distances in summer, whereas temperate‐zone groups are richer in cooler climates in mountains and forests, where winter conditions are more suitable for diapause. The evolution of cold tolerance is key to both the evolutionary and ecological patterns.
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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 | 0.000 |
| 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) | 0.002 | 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".