Data from: Fine-scale local adaptation in an invasive freshwater fish has evolved in contemporary time
Bibliographic record
Abstract
Adaptive evolutionary change in only a few generations can increase the ability of non-native invasive species to spread, and yet adaptive divergence is rarely assessed in recently established populations. In this paper, we experimentally test for evidence of fine-scale local adaptation in juvenile survival and growth among three populations of an invasive freshwater fish with reciprocal transplants and common-garden experiments. Despite intrinsic differences in habitat quality, in two out of three populations we detected evidence of increased survival in ‘home’ vs. ‘away’ environments with a Bayesian occupancy model fitted to mark-recapture data. We found support for the ‘local vs. foreign’ criterion of local adaptation as 14 out of 15 pairwise comparisons of performance were consistent with local adaptation (p < 0.001). Patterns in growth were less clear, though we detected evidence of location and population-level effects. Although the agents of divergent ecological selection are not known in this system, our results combine to indicate that adaptive divergence – reflected by higher relative survival of local individuals – can occur in a small number of generations and only a few kilometers apart on the landscape.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".