Positive phenotypic correlations among life‐history traits remain in the absence of differential resource ingestion
Bibliographic record
Abstract
Summary A central tenet of life‐history theory states that individuals are constrained from maximizing all aspects of fitness simultaneously through negative correlations among life‐history traits, known as trade‐offs. Although evidence for trade‐offs is abundant, a surprising number of taxa reveal positive correlations where trade‐offs are expected. Previous studies suggest two mechanisms to explain the lack of trade‐offs in situations where they are predicted by theory: differential resource acquisition and multidimensional trait constraints expressed in the presence of genetic variation. However, there is no direct empirical evidence supporting either hypothesis. Using individuals from multiple genotypes of the cyclic parthenogenic freshwater zooplankton, Daphnia pulicaria, we conducted life‐history experiments that prevented two key aspects of these mechanisms from operating. The experiments were conducted under a range of resources from levels causing near‐starvation to levels of resource abundance yielding a mean clutch size of 4–5 eggs. Growth, reproduction and survival were measured for each individual. Contrary to expectations, we found strong positive correlations among life‐history traits in the absence of both differential resource ingestion, which is one form of differential resource acquisition, and genetic variation. These positive correlations emerge from differential resource utilization, which is one of the steps along the resource ingestion‐utilization‐allocation pathway. Our results demonstrate that strong positive correlations among life‐history traits emerge from variation among individuals in an underappreciated aspect of their energy budget. This alternative mechanism has different implications for understanding life‐history evolution, and reinforces the potential role that physiological ecology has in shaping life‐history trait correlations.
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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 | 0.002 |
| 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 | 0.001 |
| 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 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".