The Effects of Dietary Nutrient Balance on Life-History Traits and Sexual Selection in the Field Cricket, Gryllus Veletis
Bibliographic record
Abstract
Nutrition is an important driver of biological variation.Macronutrients such as protein and carbohydrates, and elemental nutrients such as phosphorus, are known to affect animal fitness traits.No study, however, has investigated the importance of phosphorus relative to dietary protein or carbohydrates, or their interactive effects, on animal performance.To advance our understanding of the impact of nutrition on individual fitness, my thesis examined the influence of dietary protein, carbohydrate, and phosphorus balance on fitness-related life-history traits, including those involved in intraand inter-sexual selection, of Gryllus veletis field crickets.My findings revealed that adult lifespan, weight gain, males' acoustic mate attraction signals, and females' egg production were maximized on diets with different protein:carbohydrate ratios, such that not all fitness traits could simultaneously be maximized on the same diet.Similarly, juvenile females could not simultaneously maximize their growth, development rate, survival, and dispersal capability at adulthood on the same dietary protein:carbohydrate ratio.Adult males and females also had different optimal nutrient intake ratios for reproductive performance.My results support theoretical predictions for the conditiondependence of traits involved in inter-and intra-sexual selection; both male mate attraction signals, and female sexual responsiveness and preferences for such signals, were influenced by dietary protein:carbohydrate ratio.However, male aggressiveness in agonistic contests with rivals was not influenced by dietary nutrient balance.Contrary to my expectations, dietary phosphorus had little influence on fitness traits, with the exception of a negative influence of high phosphorus diets on male mate attraction iii signals.When given a choice between diets containing differing but complementary nutrient compositions, both adults and juveniles demonstrated an ability to regulate their protein and carbohydrate intakes, but not their phosphorus intake.These self-selected diets often represented a compromise between the differing nutrient requirements of multiple fitness traits.Overall, my findings suggest that environmental heterogeneity in nutrient availability is an important driver of variation in animal fitness, and highlight the importance of disentangling the influences of different nutrients on animal fitness traits.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".