Data from: Behavioral diversity is maintained by a conditional strategy in a freshwater zooplankton
Bibliographic record
Abstract
Many populations have intraspecific diversity in phenotype and ecological strategy, but the mechanisms maintaining such diversity are not fully understood. Multiple behaviors can be maintained either as a conditional strategy, where fitness depends on an individual’s phenotype, or as a mixed strategy where alternative behaviors have similar fitness independent of phenotype. Using high-resolution depth and time sampling, we characterize two distinct diel vertical migration behaviors in a population of freshwater zooplankton (Daphnia pulicaria). Individuals in this population differ in their color phenotype and migratory behavior with red morphs upregulating hemoglobin and undergoing a deep migration, and pale morphs not producing hemoglobin and undergoing a shallow migration. We experimentally manipulated the behavior of each phenotype in the field, and measured population growth in their natural migration behavior as well as population growth in their alternative behaviors. Experimental populations of pale and red morphs under their natural migrations had roughly equal fitness, despite vast differences in environmental conditions. When forced to switch behaviors, pale morphs suffered reduced fitness, whereas red morphs had similar fitness compared to their natural migration. Our results suggest that while behavioral diversity may be promoted by the opportunity for alternative behaviors of equal fitness, the distinct physiological conditions required for survival in alternative behaviors limit the capacity for individual behavioral switching and likely maintain behavioral diversity as a conditional strategy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.030 |
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".