Comparing ageing and the effects of diet supplementation in wild vs. captive antler flies, <i>Protopiophila litigata</i>
Bibliographic record
Abstract
Few studies have simultaneously compared ageing within genetically similar populations in both laboratory and natural environments. Such comparisons are important for interpreting laboratory studies, because factors such as diet could affect ageing in environment-dependent ways. Using a natural population of antler flies (Protopiophila litigata), we conducted separate factorial experiments in 2012 and 2013 that compared age-specific male survival and mating success in laboratory cages versus a natural field environment while supplementing their diets with protein or sugar. We found consistent and substantial increases in both survival and mating rates in the laboratory compared to the field, but remarkably, despite these large differences actuarial ageing was only higher in the laboratory than in the field in 2012 and similar in the two environments in 2013. In both years, there was no difference between environments in reproductive ageing. We found that males fed protein had a higher mortality rate than males fed sugar (strong and low support in 2012 and 2013, respectively). In contrast, diet did not strongly impact average mating rates, actuarial ageing or reproductive ageing in either experiment. Our results provide the first evidence that the negative effect of protein on life span reported in many laboratory studies can also occur in wild populations, although perhaps less consistently. They also highlight how laboratory environments can influence life-history traits and suggest caution when extrapolating from the laboratory to the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".