Temporal Population Genetics of Time Travelling Insects: A Long Term Study in a Seed-Specialized Wasp
Bibliographic record
Abstract
Many animal species experiencing spatial or interannual fluctuations of their environment are capable of prolonged diapause, a kind of dormancy that extends over more than one year. Such a prolonged diapause is commonly perceived as a temporal demographic refuge in stochastic environments, but empirical evidence is still lacking of its consequences on temporal population genetic structures. In this long-term study, we investigated how a particular pattern of prolonged diapause may influence the temporal population genetics of the invasive seed-specialized wasp Megastigmus schimitscheki (Hymenoptera: Torymidae) in southeastern France. We characterized the diapause strategy of M. schimitscheki using records of emergence from diapause in 97 larval cohorts, and we conducted a temporal population genetic study on a natural invasive wasp population sampled during ten consecutive years (1999-2008) using polymorphic microsatellite markers. We found that M. schimitscheki can undergo a prolonged diapause of up to five years and displays two main adult emergence peaks after two and four years of diapause. Such a bimodal and atypical pattern did not disrupt temporal gene flow between cohorts produced in even and in odd years during the period of the study. Unexpectedly, we found that this wasp population consisted of two distinct genetic sub-populations that strongly diverged in their diapause strategies, with very few admixed individuals. One of the sub-populations displayed both short and prolonged diapause (2 and 4 years respectively) in equal proportions, whereas the other sub-population displayed mainly short diapause. This study provided empirical evidence that prolonged diapause phenotypes can substantially contribute to reproduction and impact temporal genetic structures. Prolonged diapause is likely to act as both demographic and genetic refuges for insect populations living in fluctuating environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".