Code from: Geometric-mean fitness does not correspond to long-term survival probability

Unpredictable randomness plays a crucial role in the long-term sustainability of biological systems. The population growth of a species in variable environments is typically described in terms of a long-term measure, such as geometric mean fitness or the geometric mean of stochastic growth rates. However, a quantitative understanding of the relationship between these fitness measures and long-term survival probability remains a critical, and often overlooked, aspect of ecological modeling. Here, we investigate this relationship using large-scale numerical simulations, focusing on the implications for bet-hedging strategies. To this end, we develop two individual-based growth models incorporating randomly varying growth rates. Our simulations reveal that a one-to-one correspondence, or monotonic relationship, does not exist between geometric-mean fitness and survival probability. Specifically, higher geometric-mean fitness does not necessarily correlate with increased survival probabilit..., , # Code from: Geometric-mean fitness does not correspond to long-term survival probability

Dataset DOI: [10.5061/dryad.0k6djhbdq](https://doi.org/10.5061/dryad.0k6djhbdq)

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We present the code snippets used for the study titled *Geometric-mean Fitness Does Not Correspond to Long-term Survival Probability* by Takuya Okabe, Jin Yoshimura, and Hiromu Ito. The survival probability is estimated using a Monte Carlo simulation in Mathematica. A population is initialized with 100 individuals. The size of this population is iteratively updated based on a `NextSize` function, which determines the next population size from the previous one. This simulation is repeated 10,000 times. We record the proportion of simulations resulting in extinction and calculate the survival probability as 111 minus this extinction proportion.

#### File: Code.nb

**Description:** The notebook simulates how a population grows or goes extinct when its environment randomly changes over time. Star...,