Data from: Modification of reproductive schedule in response to pathogen exposure in a wild insect: support for the terminal investment hypothesis
Bibliographic record
Abstract
Trade-offs in the time and energy allocated to different functions, such as reproductive activities, can be driven by alterations in condition which reduce resources, often in response to extrinsic factors such as pathogens or parasites. When individuals are challenged by a pathogen they may either reduce reproduction as a cost of increasing defence mechanisms, or alternatively, modify reproductive activities so as to increase fecundity thereby minimizing the fitness costs of earlier death, a behaviour consistent with the terminal investment hypothesis (TIH). The TIH predicts that individuals with decreased likelihood of future reproduction will maximize current reproductive effort, which may include shifts in reproductive timing. We examined how wild, adult female click beetles (Agriotes obscurus) responded after exposure to the fungal pathogenMetarhizium brunneum. Field-collected beetles exposed to a high concentration of M. brunneum died earlier and in greater numbers than those exposed to a low concentration. Using a multi-variate approach we examined the impact of pathogen challenge on lifespan and a suite of reproductive traits. Stepdown regression analysis showed that only female lifespan differed among the fungal treatments. Fungal-induced reductions in lifespan drove changes in the reproductive schedule, characterized by a decrease in preoviposition period. Moving the start of egg laying forward allowed the females to offset the costs of a shortened lifespan. These changes suggest that there is a threshold for terminal investment which is dependent on strength of the survival threat. From an applied perspective, our findings imply that exposing adult click beetles to M. brunneum to reduce their population densitymight not succeed and is an approach that needs further investigation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.011 |
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".