Retracing the routes of introduction of invasive species: the case of the <i><scp>S</scp>irex noctilio</i> woodwasp
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding the evolutionary histories of invasive species is critical to adopt appropriate management strategies, but this process can be exceedingly complex to unravel. As illustrated in this study of the worldwide invasion of the woodwasp Sirex noctilio, population genetic analyses using coalescent-based scenario testing together with Bayesian clustering and historical records provide opportunities to address this problem. The pest spread from its native Eurasian range to the Southern Hemisphere in the 1900s and recently to Northern America, where it poses economic and potentially ecological threats to planted and native Pinus spp. To investigate the origins and pathways of invasion, samples from five continents were analysed using microsatellite and sequence data. The results of clustering analysis and scenario testing suggest that the invasion history is much more complex than previously believed, with most of the populations being admixtures resulting from independent introductions from Europe and subsequent spread among the invaded areas. Clustering analyses revealed two major source gene pools, one of which the scenario testing suggests is an as yet unsampled source. Results also shed light on the microevolutionary processes occurring during introductions, and showed that only few specimens gave rise to some of the populations. Analyses of microsatellites using clustering and scenario testing considered against historical data drastically altered our understanding of the invasion history of S. noctilio and will have important implications for the strategies employed to fight its spread. This study illustrates the value of combining clustering and ABC methods in a comprehensive framework to dissect the complex patterns of spread of global invaders.
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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 | 0.001 |
| 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 | 0.000 | 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 it