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Life-History Evolution of Insects in Response to Climate Variation: Seasonal Timing Versus Thermal Physiology
Karl Gotthard1, David Berger2, Patrick Rohner3
1Department of Zoology and The Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden;
Annual Review of Entomology
|September 24, 2025
Summary
Insect adaptation to climate change involves life-history shifts and phenological changes. Evolution of photoperiodism offers a more predictable pathway for insect adaptation to warming climates.
Area of Science:
- Ecology
- Evolutionary Biology
- Climate Change Biology
Background:
- Insects adapt to climate change through life-history traits and phenological shifts.
- Photoperiodism, or the response to day length, influences insect phenology.
- Predicting insect responses to climate change requires understanding adaptive evolution in natural populations.
Purpose of the Study:
- To review and analyze literature on insect adaptation to climate change.
- To determine the evolutionary predictability of life-history traits versus photoperiodism.
- To forecast how insects will respond to ongoing climate change.
Main Methods:
- Literature review of published studies on insect adaptation.
- Analysis of studies examining life-history traits, thermal plasticity, and photoperiodism.
- Assessment of clinal variation in adaptation across geographic latitudes.
Main Results:
- Photoperiodism for diapause induction shows predictable latitudinal clines, with earlier diapause in high-latitude populations.
- Life-history traits and thermal plasticity exhibit less consistent clinal variation across taxa.
- Evolutionary potential for both adaptation modes is demonstrated, but predictability differs.
Conclusions:
- Phenological shifts driven by the evolution of photoperiodism are likely more common and predictable insect responses to climate change.
- While insect life history and physiological adaptation to temperature can evolve, photoperiodism offers a clearer adaptive strategy.
- Understanding photoperiodism evolution is crucial for predicting insect population dynamics under climate change.
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