Dispersing male<i>Parnassius smintheus</i>butterflies are more strongly affected by forest matrix than are females
Bibliographic record
Abstract
Dispersal is a central aspect of the ecology, evolution, and conservation of species. Predicting how species will respond to changing environmental conditions requires understanding factors that produce variation in dispersal. We explore one source of variation, differences between sexes within a spatial population network. Here, we compare the dispersal patterns of male and female Parnassius smintheus among 18 subpopulations over 8 years using the Virtual Migration Model. Estimated dispersal parameters differed between males and females, particularly with respect to movement through meadow and forest matrix habitat. The estimated dispersal distances of males through forest were much less than for females. Observations of female movement showed that, unlike males, females do not avoid forest nor does forest exert an edge effect. We explored whether further forest encroachment in this system would have different effects for males and females by fitting mean parameter estimates to the landscape configuration seen in 1993 and 2012. Despite differences in their dispersal due presumably to both habitat and physiological differences, males and females are predicted to respond in similar ways to reduced meadow area and increased forest isolation.
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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 | 0.000 |
| 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) | 0.002 | 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".