Climatic niche evolution is faster in sympatric than allopatric lineages of the butterfly genus<i>Pyrgus</i>
Bibliographic record
Abstract
Understanding how speciation relates to ecological divergence has long fascinated biologists. It is assumed that ecological divergence is essential to sympatric speciation, as a mechanism to avoid competition and eventually lead to reproductive isolation, while divergence in allopatry is not necessarily associated with niche differentiation. The impact of the spatial context of divergence on the evolutionary rates of abiotic dimensions of the ecological niche has rarely been explored for an entire clade. Here, we compare the magnitude of climatic niche shifts between sympatric versus allopatric divergence of lineages in butterflies. By combining next-generation sequencing, parametric biogeography and ecological niche analyses applied to a genus-wide phylogeny of Palaearctic Pyrgus butterflies, we compare evolutionary rates along eight climatic dimensions across sister lineages that diverged in large-scale sympatry versus allopatry. In order to examine the possible effects of the spatial scale at which sympatry is defined, we considered three sets of biogeographic assignments, ranging from narrow to broad definition. Our findings suggest higher rates of niche evolution along all climatic dimensions for sister lineages that diverge in sympatry, when using a narrow delineation of biogeographic areas. This result contrasts with significantly lower rates of climatic niche evolution found in cases of allopatric speciation, despite the biogeographic regions defined here being characterized by significantly different climates. Higher rates in allopatry are retrieved when biogeographic areas are too widely defined—in such a case allopatric events may be recorded as sympatric. Our results reveal the macro-evolutionary significance of abiotic niche differentiation involved in speciation processes within biogeographic regions, and illustrate the importance of the spatial scale chosen to define areas when applying parametric biogeographic analyses.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".