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Geometric-Mean Fitness Does Not Correspond to Long-Term Survival Probability
Takuya Okabe1, Jin Yoshimura1,2,3,4, Hiromu Ito2
1Graduate School of Integrated Science and Technology Shizuoka University Hamamatsu Japan.
Ecology and Evolution
|December 30, 2025
Summary
Biological systems rely on randomness for sustainability. This study shows higher geometric mean fitness doesn't always mean better survival probability, challenging long-term ecological models.
Area of Science:
- Ecology
- Evolutionary Biology
- Mathematical Biology
Background:
- Randomness is vital for biological system sustainability in variable environments.
- Geometric-mean fitness is a common measure for population growth, but its link to survival is unclear.
- Understanding the relationship between fitness measures and survival probability is critical for ecological modeling.
Purpose of the Study:
- To investigate the quantitative relationship between geometric mean fitness and long-term survival probability.
- To explore the implications of this relationship for bet-hedging strategies in ecological systems.
- To challenge assumptions about universal, time-independent measures of long-term fitness.
Main Methods:
- Developed two individual-based growth models with randomly varying growth rates.
- Conducted large-scale numerical simulations to analyze population dynamics.
- Examined the correlation between geometric mean fitness and survival probability.
Main Results:
- A direct, one-to-one correspondence between geometric mean fitness and survival probability was not found.
- Increased geometric mean fitness does not consistently predict higher survival probability.
- The effectiveness of survival strategies is dependent on the observation timescale.
Conclusions:
- The assumption of a universal measure for long-term fitness is challenged.
- Ecological models may need refinement to account for the complex relationship between fitness and survival.
- Optimal survival strategies are likely context-dependent and vary with the timescale.
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