Harnessing thermal plasticity to enhance the performance of mass-reared insects: opportunities and challenges
Bibliographic record
Abstract
Insects are mass-reared for release for biocontrol including the sterile insect technique. Insects are usually reared at temperatures that maximize the number of animals produced, are chilled for handling and transport, and released into the field, where temperatures may be considerably different to those experienced previously. Insect thermal biology is phenotypically plastic (i.e. flexible), which means that there may exist opportunities to increase the performance of these programmes by modifying the temperature regimes during rearing, handling, and release. Here we synthesize the literature on thermal plasticity in relation to the opportunities to reduce temperature-related damage and increase the performance of released insects. We summarize how and why temperature affects insect biology, and the types of plasticity shown by insects. We specifically identify aspects of the production chain that might lead to mismatches between the thermal acclimation of the insect and the temperatures it is exposed to, and identify ways to harness physiological plasticity to reduce that potential mismatch. We address some of the practical (especially engineering) challenges to implementing some of the best-supported thermal regimes to maximize performance (e.g. fluctuating thermal regimes), and acknowledge that a focus only on thermal performance may lead to unwanted trade-offs with other traits that contribute to the success of the programme. Together, it appears that thermal physiological plasticity is well-enough understood to allow its implementation in release programmes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".