A transcontinental experiment elucidates (mal)adaptation of a cosmopolitan plant to climate in space and time
Bibliographic record
Abstract
Abstract Climate change and the global spread of non-native species are two of the most significant threats to biodiversity and ecosystem function. Both these phenomena subject populations to novel conditions, either in space (species introductions) or in time (climate change), yet the role of adaptation in how populations respond to these rapid environmental shifts is poorly understood. We conducted a large-scale trans-continental common garden experiment using white clover ( Trifolium repens , Fabaceae) to test whether adaptive evolution to spatiotemporal variation in climate could contribute to the ecological success of one of the most widespread plant species in the world. Individuals from 96 populations of Trifolium repens (white clover) from both its native (Europe) and introduced (North America) ranges were planted into four experimental common gardens located in northern (Uppsala, Sweden) and southern (Montpellier, France) Europe, and northern (Mississauga, Canada) and southern (Lafayette, USA) North America. We recorded plant sexual and clonal fitness in each common garden and assessed whether the strength of local adaptation differed between the native and introduced ranges and whether populations are rapidly adapting to climate change. Results show that local adaptation was only evident when populations were transplanted into common gardens located in the same range (native or introduced) from which they originated and was driven by stronger selection (due to climatic factors rather than herbivory) at lower latitudes in both ranges. Our results indicate rapid local adaptation across a large latitudinal gradient in introduced T. repens populations, along with an associated adaptation cost when transplanted back into the native range. We also find evidence of an adaptation lag in the northern common garden in the introduced range, with plants from historically warmer climates exhibiting the greatest fitness. These findings support two major conclusions: 1) white clover can rapidly adapt to spatial variation in climate in its introduced range as well as the native range, and 2) despite rapid adaptation to novel environments, introduced white clover populations are not keeping pace with rapid climate change. Overall, our results provide insight into the role of adaptation in facilitating the ecological success of non-native species in a rapidly changing world. Open Research Statement Data are provided for peer review. All data involved in this study is available on the GitHub page for LJA ( https://github.com/ljalbano/transcontinental_common_garden ).
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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 | 0.001 |
| 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 | 0.001 |
| 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".