Temperature outweighs diet in shaping developmental performance in two cricket species via growth delays and physiological limits
Bibliographic record
Abstract
Abstract Understanding how chronic environmental stressors shape animal development is essential for predicting ecological responses and optimizing rearing systems. This perspective complements the use of short-term tolerance assays, which overlook the cumulative effects of sustained stress. Temperature and nutrition affect key life-history traits such as growth, development rate, and survival, which are closely tied to reproductive success and fitness. While both factors have been widely studied, their relative impacts aren’t clearly defined. We investigated how constant temperature (26– 41°C) and dietary protein-to-carbohydrate (P:C) ratio (0.15–2.18) influence development in two cricket species, Acheta domesticus and Gryllodes sigillatus . Growth trajectories were modelled using a unified-logistic equation to estimate asymptotic mass and relative growth rate. This approach captures the growth trajectory in a simplified and interpretable way, enabling comparisons across treatments. Asymptotic mass was combined with developmental rate and survival to calculate a composite metric of developmental performance. Developmental performance peaked at 35°C but fell at thermal extremes due to delayed development (in cold) or reduced mass and survival (in heat). Diet had more modest effects. Performance was stable across most P:C ratios, declining only at extreme imbalances. Notably, the performance cost of the most unbalanced diets was comparable to a 4-5°C shift from thermal optimum. Our results demonstrate that temperature, more than diet, drives variation in developmental performance during ad libitum feeding. This integrative framework provides a robust approach to quantify environmental sensitivity, define performance limits, and guide us toward the mechanisms underlying those limits and/or performance trade-offs. Summary statement Temperature more strongly influences growth trajectories and developmental performance than diet, due to delayed development and reduced survival at thermal extremes.
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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 | 0.001 |
| 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 | 0.001 | 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".