Is adaptation associated with long-term persistence beyond a geographic range limit?
Bibliographic record
Abstract
Adaptation to new habitats might facilitate species' range shifts in response to climate change. In 2005, we transplanted experimental populations of coastal dune plant Camissoniopsis cheiranthifolia into 4 sites within and 1 site beyond its poleward range limit. Beyond-range transplants had high fitness but often delayed reproduction. To test for adaptation associated with experimental range expansion, we transplanted descendants from beyond- and within-range populations after 10 generations in situ into 2 sites within the range, 1 at the range edge, and 2 sites beyond the range. We expected to detect adaptation to beyond-range conditions due to substantial genetic variation within experimental populations and environmental variation among sites. However, individuals from beyond-range experimental populations were not fitter than those from within the range when planted at either beyond-range site, indicating no adaptation to the beyond-range site or beyond-range environments in general. Beyond-range descendants also did not suffer lower fitness within the range. Although reproduction was again delayed beyond the range, late reproduction was not favored more strongly beyond than within the range, and beyond-range descendants did not delay reproduction more than within-range descendants. Persistence in beyond-range environments may not require adaptation, which could allow a rapid response to climate change.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".