Selection on Sporulation Strategies in a Metapopulation Can Lead to Coexistence

In constant environments the coexistence of similar species or genotypes is generally limited. In a metapopulation context, however, types that utilize the same resource but are distributed along a competition-colonization trade-off, can coexist. Much thought in this area focuses on a generic trade-off between within-deme competitive ability and between-deme dispersal ability. We point out that the sporulation program in yeasts and other microbes can create a natural trade-off such that strains which initiate sporulation at higher rates suffer in terms of within-deme competition but benefit in terms of between deme dispersal. We develop metapopulation models where the within-deme behavior follows chemostat dynamics. We first show that the rate of sporulation determines the colonization ability of the strain, with colonization ability increasing with sporulation rate up to a point. Metapopulation stability of a single strain exists in a defined range of sporulation rates. We then use pai..., Data for this paper consist of numerical and stochastic simulations performed using Mathematica and the Rust programming language. Some data files were stored as .csv files to transfer between simulation platforms. , , # Selection on sporulation strategies in a metapopulation can lead to coexistence

[https://doi.org/10.5061/dryad.18931zd6m](https://doi.org/10.5061/dryad.18931zd6m)

## Description of the data and file structure

Numerical calculations were performed using Wolfram Mathematica. 

Stochastic simulations were performed in both Wolfram Mathematica and using the Rust programing language.  

### Files and variables

1. pip-fitness.csv is a comma separated value file that includes output from the Rust code. It has 3 columns, rho1, rho2, and value. Rho1 is the resident sporulation rate (cells/unit time), rho2 is the mutant sporulation rate (cells/unit time), and value is the simulated result for the growth factor of the mutant population. Values greater than 1 indicate that the mutant increases numerically over one generation when starting from a single mutant patch, on average. Values less than 1 indicate that fewer than 1 patch, on average, is present at the next timestep.

## Code/software
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