Demographic fluctuations lead to rapid and cyclic shifts in genetic structure among populations of an alpine butterfly, <i>Parnassius smintheus</i>
Bibliographic record
Abstract
Many populations, especially in insects, fluctuate in size, and periods of particularly low population size can have strong effects on genetic variation. Effects of demographic bottlenecks on genetic diversity of single populations are widely documented. Effects of bottlenecks on genetic structure among multiple interconnected populations are less studied, as are genetic changes across multiple cycles of demographic collapse and recovery. We take advantage of a long-term data set comprising demographic, genetic and movement data from a network of populations of the butterfly, Parnassius smintheus, to examine the effects of fluctuating population size on spatial genetic structure. We build on a previous study that documented increased genetic differentiation and loss of spatial genetic patterns (isolation by distance and by intervening forest cover) after a network-wide bottleneck event. Here, we show that genetic differentiation was reduced again and spatial patterns returned to the system extremely rapidly, within three years (i.e. generations). We also show that a second bottleneck had similar effects to the first, increasing differentiation and erasing spatial patterns. Thus, bottlenecks consistently drive random divergence of allele frequencies among populations in this system, but these effects are rapidly countered by gene flow during demographic recovery. Our results reveal a system in which the relative influence of genetic drift and gene flow continually shift as populations fluctuate in size, leading to cyclic changes in genetic structure. Our results also suggest caution in the interpretation of patterns of spatial genetic structure, and its association with landscape variables, when measured at only a single point in time.
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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) | 0.000 | 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".