Genetic admixture and heterosis may enhance the invasiveness of common ragweed
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Biological invasions are often associated with multiple introductions and genetic admixture of previously isolated populations. In addition to enhanced evolutionary potential through increased genetic variation, admixed genotypes may benefit from heterosis, which could contribute to their increased performance and invasiveness. To deepen our understanding of the mechanisms and management strategies for biological invasions, we experimentally studied whether intraspecific admixture causes heterosis in common ragweed ( Ambrosia artemisiifolia ) by comparing the performance of crosses (F1) between populations relative to crosses within these populations for each range (native, introduced) under different ecologically relevant conditions (control, drought, competition, simulated herbivory). Performance of admixed genotypes was highly variable, ranging from strong heterotic effects to weak outbreeding depression. Moreover, heterosis was not uniformly observed among between‐population crosses, but certain native population crosses showed considerable heterosis, especially under simulated herbivory. In contrast, heterosis was largely absent in crosses from the introduced range, possibly implying that these populations were already admixed and benefit little from further mixing. In conclusion, these results support the hypothesis that heterosis may contribute to biological invasions, and indicate the need to minimize new introductions of exotic species, even if they are already present in the introduced range.
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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 | 0.000 | 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 | 0.001 |
| 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