Common garden comparisons of native and introduced plant populations: latitudinal clines can obscure evolutionary inferences
Bibliographic record
Abstract
Common garden studies are increasingly used to identify differences in phenotypic traits between native and introduced genotypes, often ignoring sources of among-population variation within each range. We re-analyzed data from 32 common garden studies of 28 plant species that tested for rapid evolution associated with biological invasion. Our goals were: (i) to identify patterns of phenotypic trait variation among populations within native and introduced ranges, and (ii) to explore the consequences of this variation for how differences between the ranges are interpreted. We combined life history and physiologic traits into a single principal component (PCALL) and also compared subsets of traits related to size, reproduction, and defense (PCSIZE, PCREP, and PCDEF, respectively). On average, introduced populations exhibited increased growth and reproduction compared to native conspecifics when latitude was not included in statistical models. However, significant correlations between PC-scores and latitude were detected in both the native and introduced ranges, indicating population differentiation along latitudinal gradients. When latitude was explicitly incorporated into statistical models as a covariate, it reduced the magnitude and reversed the direction of the effect for PCALL and PCSIZE. These results indicate that unrecognized geographic clines in phenotypic traits can confound inferences about the causes of evolutionary change in invasive plants.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".