Rapid evolution of life‐history traits in response to warming, predation and competition: A meta‐analysis
Bibliographic record
Abstract
Although studies quantifying evolutionary change in response to the selective pressures that organisms face in the wild have demonstrated that organisms can evolve rapidly, we lack a systematic assessment of the frequency, magnitude and direction of rapid evolutionary change across taxa. To address this gap, we conducted a meta-analysis of 58 studies that document the effects of warming, predation or competition on the evolution of body size, development rate or fecundity in natural or experimental animal populations. We tested whether there was a consistent effect of any selective agent on any trait, whether the direction of these effects align with theoretical predictions, and whether the three agents select in opposing directions on any trait. Overall, we found weak effects of all three selective agents on trait evolution: none of our nine traits by selective agent combinations had an overall effect that differed from zero, only 31% of studies had a significant within-study effect, and attributes of the included studies generally did not account for between-study variation in results. One notable exception was that predation targeting adults consistently resulted in the evolution of smaller prey body size. We discuss potential causes of these generally weak responses and consider how our results inform the ongoing development of eco-evolutionary research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".