Evolutionary constraints on adaptive evolution during range expansion in an invasive plant
Bibliographic record
Abstract
Biological invasions may expose populations to strong selection for local adaptation along geographical gradients in climate. However, evolution during contemporary timescales can be constrained by low standing genetic variation and genetic correlations among life-history traits. We examined limits to local adaptation associated with northern migration of the invasive wetland plant purple loosestrife (Lythrum salicaria) using a selection model incorporating a trade-off between flowering time and size at reproduction, and common garden experiments of populations sampled along a latitudinal transect of approximately 1200 km in eastern North America. A strong trade-off between flowering time and size at reproduction caused early-flowering plants to be smaller with reduced seed production in northern populations. Northward spread was associated with a decline in genetic variance within populations and an increase in genetic skew for flowering time and size, with limited genetic variation for small, early-flowering genotypes. These patterns were predicted by our selection model of local adaptation to shorter growing seasons and were not consistent with expectations from non-adaptive processes. Reduced fecundity may limit population growth and rates of spread in northern populations. Identifying genetic constraints on key life-history traits can provide novel insights into invasion dynamics and the causes of range limits in introduced species.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".