Predator-induced phenotypic plasticity of shape and behavior: parallel and unique patterns across sexes and species
Bibliographic record
Abstract
Phenotypic plasticity is often an adaptation of organisms to cope with temporally or spatially heterogenous landscapes. Like other adaptations, one would predict that different species, populations, or sexes might thus show some degree of parallel evolution of plasticity, in the form of parallel reaction norms, when exposed to analogous environmental gradients. Indeed, one might even expect parallelism of plasticity to repeatedly evolve in multiple traits responding to the same gradient, resulting in integrated parallelism of plasticity. In this study, we experimentally tested for parallel patterns of predator-mediated plasticity of size, shape, and behavior of 2 species and sexes of mosquitofish. Examination of behavioral trials indicated that the 2 species showed unique patterns of behavioral plasticity, whereas the 2 sexes in each species showed parallel responses. Fish shape showed parallel patterns of plasticity for both sexes and species, albeit males showed evidence of unique plasticity related to reproductive anatomy. Moreover, patterns of shape plasticity due to predator exposure were broadly parallel to what has been depicted for predator-mediated population divergence in other studies (slender bodies, expanded caudal regions, ventrally located eyes, and reduced male gonopodia). We did not find evidence of phenotypic plasticity in fish size for either species or sex. Hence, our findings support broadly integrated parallelism of plasticity for sexes within species and less integrated parallelism for species. We interpret these findings with respect to their potential broader implications for the interacting roles of adaptation and constraint in the evolutionary origins of parallelism of plasticity in general.
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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 | 0.001 | 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) | 0.002 | 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".